From scipy-svn at scipy.org Wed Feb 2 00:06:44 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Tue, 1 Feb 2011 23:06:44 -0600 (CST) Subject: [Scipy-svn] r7119 - trunk/scipy/weave Message-ID: <20110202050644.F21FF1B8D5D@scipy.org> Author: warren.weckesser Date: 2011-02-01 23:06:44 -0600 (Tue, 01 Feb 2011) New Revision: 7119 Modified: trunk/scipy/weave/ast_tools.py trunk/scipy/weave/bytecodecompiler.py Log: PY3: weave: Eliminate use of map(None, ...) Modified: trunk/scipy/weave/ast_tools.py =================================================================== --- trunk/scipy/weave/ast_tools.py 2011-01-31 23:06:30 UTC (rev 7118) +++ trunk/scipy/weave/ast_tools.py 2011-02-02 05:06:44 UTC (rev 7119) @@ -180,7 +180,7 @@ return (pattern == data), vars if len(data) != len(pattern): return 0, vars - for pattern, data in map(None, pattern, data): + for pattern, data in zip(pattern, data): same, vars = match(pattern, data, vars) if not same: break Modified: trunk/scipy/weave/bytecodecompiler.py =================================================================== --- trunk/scipy/weave/bytecodecompiler.py 2011-01-31 23:06:30 UTC (rev 7118) +++ trunk/scipy/weave/bytecodecompiler.py 2011-02-02 05:06:44 UTC (rev 7119) @@ -147,7 +147,7 @@ # Build one in the reverse sense # ----------------------------------------------- byOpcode = {} -for name,op in map(None, byName.keys(), byName.values()): +for name, op in byName.items(): byOpcode[op] = name del name del op @@ -1151,7 +1151,7 @@ v = self.stack[var_num] t = self.types[var_num] print 'LOADFAST',var_num,v,t - for VV,TT in map(None, self.stack, self.types): + for VV, TT in zip(self.stack, self.types): print VV,':',TT if t is None: raise TypeError('%s used before set?' % v) From scipy-svn at scipy.org Wed Feb 2 12:47:11 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Wed, 2 Feb 2011 11:47:11 -0600 (CST) Subject: [Scipy-svn] r7120 - trunk/scipy/ndimage/src Message-ID: <20110202174711.E3A711B8D85@scipy.org> Author: charris Date: 2011-02-02 11:47:10 -0600 (Wed, 02 Feb 2011) New Revision: 7120 Modified: trunk/scipy/ndimage/src/ni_support.c Log: BUG: Fix ndimage type checks, part of ticket #1724. Modified: trunk/scipy/ndimage/src/ni_support.c =================================================================== --- trunk/scipy/ndimage/src/ni_support.c 2011-02-02 05:06:44 UTC (rev 7119) +++ trunk/scipy/ndimage/src/ni_support.c 2011-02-02 17:47:10 UTC (rev 7120) @@ -119,6 +119,41 @@ return 1; } +/* Some NumPy types are ambiguous */ +int NI_CanonicalType(int type_num) +{ + switch (type_num) { + case NPY_INT: + return NPY_INT32; + + case NPY_LONG: +#if NPY_SIZEOF_LONG == 4 + return NPY_INT32; +#else + return NPY_INT64; +#endif + + case NPY_LONGLONG: + return NPY_INT64; + + case NPY_UINT: + return NPY_UINT32; + + case NPY_ULONG: +#if NPY_SIZEOF_LONG == 4 + return NPY_UINT32; +#else + return NPY_UINT64; +#endif + + case NPY_ULONGLONG: + return NPY_UINT64; + + default: + return type_num; + } +} + /* Initialize a line buffer */ int NI_InitLineBuffer(PyArrayObject *array, int axis, npy_intp size1, npy_intp size2, npy_intp buffer_lines, double *buffer_data, @@ -147,7 +182,7 @@ buffer->array_data = (void *)PyArray_DATA(array); buffer->buffer_data = buffer_data; buffer->buffer_lines = buffer_lines; - buffer->array_type = array->descr->type_num; + buffer->array_type = NI_CanonicalType(PyArray_DESCR(array)->type_num); buffer->array_lines = array_lines; buffer->next_line = 0; buffer->size1 = size1; From scipy-svn at scipy.org Wed Feb 2 16:44:08 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Wed, 2 Feb 2011 15:44:08 -0600 (CST) Subject: [Scipy-svn] r7121 - trunk/scipy/optimize/tests Message-ID: <20110202214408.7A6991B8DA6@scipy.org> Author: ptvirtan Date: 2011-02-02 15:44:07 -0600 (Wed, 02 Feb 2011) New Revision: 7121 Modified: trunk/scipy/optimize/tests/test_linesearch.py trunk/scipy/optimize/tests/test_optimize.py Log: TST: optimize: add some leeway for additional FP rounding error For instance, if arrays happen to be not aligned on 16-byte boundaries when using MKL, this produces additional (insignificant) rounding error. The tests should allow for this. Modified: trunk/scipy/optimize/tests/test_linesearch.py =================================================================== --- trunk/scipy/optimize/tests/test_linesearch.py 2011-02-02 17:47:10 UTC (rev 7120) +++ trunk/scipy/optimize/tests/test_linesearch.py 2011-02-02 21:44:07 UTC (rev 7121) @@ -2,7 +2,8 @@ Tests for line search routines """ -from numpy.testing import assert_, assert_equal, assert_array_almost_equal +from numpy.testing import assert_, assert_equal, \ + assert_array_almost_equal, assert_array_almost_equal_nulp import scipy.optimize.linesearch as ls import numpy as np @@ -36,6 +37,12 @@ def assert_line_armijo(x, p, s, f, **kw): assert_armijo(s, phi=lambda sp: f(x + p*sp), **kw) +def assert_fp_equal(x, y, err_msg="", nulp=50): + """Assert two arrays are equal, up to some floating-point rounding error""" + try: + assert_array_almost_equal_nulp(x, y, nulp) + except AssertionError, e: + raise AssertionError("%s\n%s" % (e, err_msg)) class TestLineSearch(object): # -- scalar functions; must have dphi(0.) < 0 @@ -123,8 +130,8 @@ c += 1 s, phi1, phi0 = ls.scalar_search_wolfe1(phi, derphi, phi(0), old_phi0, derphi(0)) - assert_equal(phi0, phi(0), name) - assert_equal(phi1, phi(s), name) + assert_fp_equal(phi0, phi(0), name) + assert_fp_equal(phi1, phi(s), name) assert_wolfe(s, phi, derphi, err_msg=name) assert_(c > 3) # check that the iterator really works... @@ -133,16 +140,16 @@ for name, phi, derphi, old_phi0 in self.scalar_iter(): s, phi1, phi0, derphi1 = ls.scalar_search_wolfe2( phi, derphi, phi(0), old_phi0, derphi(0)) - assert_equal(phi0, phi(0), name) - assert_equal(phi1, phi(s), name) + assert_fp_equal(phi0, phi(0), name) + assert_fp_equal(phi1, phi(s), name) if derphi1 is not None: - assert_equal(derphi1, derphi(s), name) + assert_fp_equal(derphi1, derphi(s), name) assert_wolfe(s, phi, derphi, err_msg="%s %g" % (name, old_phi0)) def test_scalar_search_armijo(self): for name, phi, derphi, old_phi0 in self.scalar_iter(): s, phi1 = ls.scalar_search_armijo(phi, phi(0), derphi(0)) - assert_equal(phi1, phi(s), name) + assert_fp_equal(phi1, phi(s), name) assert_armijo(s, phi, err_msg="%s %g" % (name, old_phi0)) # -- Generic line searches @@ -158,10 +165,10 @@ g0, f0, old_f, amax=smax) assert_equal(self.fcount, fc+gc) - assert_equal(ofv, f(x)) + assert_fp_equal(ofv, f(x)) if s is None: continue - assert_equal(fv, f(x + s*p)) + assert_fp_equal(fv, f(x + s*p)) assert_array_almost_equal(gv, fprime(x + s*p), decimal=14) if s < smax: c += 1 @@ -180,8 +187,8 @@ g0, f0, old_f, amax=smax) assert_equal(self.fcount, fc+gc) - assert_equal(ofv, f(x)) - assert_equal(fv, f(x + s*p)) + assert_fp_equal(ofv, f(x)) + assert_fp_equal(fv, f(x + s*p)) if gv is not None: assert_array_almost_equal(gv, fprime(x + s*p), decimal=14) if s < smax: @@ -198,7 +205,7 @@ s, fc, fv = ls.line_search_armijo(f, x, p, g0, f0) c += 1 assert_equal(self.fcount, fc) - assert_equal(fv, f(x + s*p)) + assert_fp_equal(fv, f(x + s*p)) assert_line_armijo(x, p, s, f, err_msg=name) assert_(c >= 9) Modified: trunk/scipy/optimize/tests/test_optimize.py =================================================================== --- trunk/scipy/optimize/tests/test_optimize.py 2011-02-02 17:47:10 UTC (rev 7120) +++ trunk/scipy/optimize/tests/test_optimize.py 2011-02-02 21:44:07 UTC (rev 7121) @@ -120,7 +120,14 @@ # Ensure that function call counts are 'known good'; these are from # Scipy 0.7.0. Don't allow them to increase. - assert_(self.funccalls == 116, self.funccalls) + # + # However, some leeway must be added: the exact evaluation + # count is sensitive to numerical error, and floating-point + # computations are not bit-for-bit reproducible across + # machines, and when using e.g. MKL, data alignment + # etc. affect the rounding error. + # + assert_(self.funccalls <= 116 + 20, self.funccalls) assert_(self.gradcalls == 0, self.gradcalls) # Ensure that the function behaves the same; this is from Scipy 0.7.0 From scipy-svn at scipy.org Wed Feb 2 17:51:52 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Wed, 2 Feb 2011 16:51:52 -0600 (CST) Subject: [Scipy-svn] r7122 - trunk/scipy/io Message-ID: <20110202225152.B1BFE363B3@scipy.org> Author: ptvirtan Date: 2011-02-02 16:51:52 -0600 (Wed, 02 Feb 2011) New Revision: 7122 Modified: trunk/scipy/io/idl.py Log: BUG: io.idl: Fix readsav() on Python 2.4 Modified: trunk/scipy/io/idl.py =================================================================== --- trunk/scipy/io/idl.py 2011-02-02 21:44:07 UTC (rev 7121) +++ trunk/scipy/io/idl.py 2011-02-02 22:51:52 UTC (rev 7122) @@ -291,7 +291,7 @@ # Reshape array if needed if array_desc['ndims'] > 1: - dims = array_desc['dims'][:array_desc['ndims']] + dims = array_desc['dims'][:int(array_desc['ndims'])] dims.reverse() array = array.reshape(dims) From scipy-svn at scipy.org Wed Feb 2 17:52:06 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Wed, 2 Feb 2011 16:52:06 -0600 (CST) Subject: [Scipy-svn] r7123 - in trunk/scipy: interpolate/tests special/tests stats/tests Message-ID: <20110202225206.CC8A41B8D8B@scipy.org> Author: ptvirtan Date: 2011-02-02 16:52:06 -0600 (Wed, 02 Feb 2011) New Revision: 7123 Modified: trunk/scipy/interpolate/tests/test_rbf.py trunk/scipy/special/tests/test_data.py trunk/scipy/stats/tests/test_continuous_basic.py Log: TST: Use np.seterr in test generators in Python2.4 compatible way The seterr should be called in the test routine itself and not in the test generator. Modified: trunk/scipy/interpolate/tests/test_rbf.py =================================================================== --- trunk/scipy/interpolate/tests/test_rbf.py 2011-02-02 22:51:52 UTC (rev 7122) +++ trunk/scipy/interpolate/tests/test_rbf.py 2011-02-02 22:52:06 UTC (rev 7123) @@ -12,59 +12,71 @@ def check_rbf1d_interpolation(function): """Check that the Rbf function interpolates throught the nodes (1D)""" - x = linspace(0,10,9) - y = sin(x) - rbf = Rbf(x, y, function=function) - yi = rbf(x) - assert_array_almost_equal(y, yi) - assert_almost_equal(rbf(float(x[0])), y[0]) + olderr = np.seterr(all="ignore") + try: + x = linspace(0,10,9) + y = sin(x) + rbf = Rbf(x, y, function=function) + yi = rbf(x) + assert_array_almost_equal(y, yi) + assert_almost_equal(rbf(float(x[0])), y[0]) + finally: + np.seterr(**olderr) def check_rbf2d_interpolation(function): """Check that the Rbf function interpolates throught the nodes (2D)""" - x = random.rand(50,1)*4-2 - y = random.rand(50,1)*4-2 - z = x*exp(-x**2-1j*y**2) - rbf = Rbf(x, y, z, epsilon=2, function=function) - zi = rbf(x, y) - zi.shape = x.shape - assert_array_almost_equal(z, zi) + olderr = np.seterr(all="ignore") + try: + x = random.rand(50,1)*4-2 + y = random.rand(50,1)*4-2 + z = x*exp(-x**2-1j*y**2) + rbf = Rbf(x, y, z, epsilon=2, function=function) + zi = rbf(x, y) + zi.shape = x.shape + assert_array_almost_equal(z, zi) + finally: + np.seterr(**olderr) def check_rbf3d_interpolation(function): """Check that the Rbf function interpolates throught the nodes (3D)""" - x = random.rand(50,1)*4-2 - y = random.rand(50,1)*4-2 - z = random.rand(50,1)*4-2 - d = x*exp(-x**2-y**2) - rbf = Rbf(x, y, z, d, epsilon=2, function=function) - di = rbf(x, y, z) - di.shape = x.shape - assert_array_almost_equal(di, d) - -def test_rbf_interpolation(): olderr = np.seterr(all="ignore") try: - for function in FUNCTIONS: - yield check_rbf1d_interpolation, function - yield check_rbf2d_interpolation, function - yield check_rbf3d_interpolation, function + x = random.rand(50,1)*4-2 + y = random.rand(50,1)*4-2 + z = random.rand(50,1)*4-2 + d = x*exp(-x**2-y**2) + rbf = Rbf(x, y, z, d, epsilon=2, function=function) + di = rbf(x, y, z) + di.shape = x.shape + assert_array_almost_equal(di, d) finally: np.seterr(**olderr) +def test_rbf_interpolation(): + for function in FUNCTIONS: + yield check_rbf1d_interpolation, function + yield check_rbf2d_interpolation, function + yield check_rbf3d_interpolation, function + def check_rbf1d_regularity(function, atol): """Check that the Rbf function approximates a smooth function well away from the nodes.""" - x = linspace(0, 10, 9) - y = sin(x) - rbf = Rbf(x, y, function=function) - xi = linspace(0, 10, 100) - yi = rbf(xi) - #import matplotlib.pyplot as plt - #plt.figure() - #plt.plot(x, y, 'o', xi, sin(xi), ':', xi, yi, '-') - #plt.title(function) - #plt.show() - msg = "abs-diff: %f" % abs(yi - sin(xi)).max() - assert_(allclose(yi, sin(xi), atol=atol), msg) + olderr = np.seterr(all="ignore") + try: + x = linspace(0, 10, 9) + y = sin(x) + rbf = Rbf(x, y, function=function) + xi = linspace(0, 10, 100) + yi = rbf(xi) + #import matplotlib.pyplot as plt + #plt.figure() + #plt.plot(x, y, 'o', xi, sin(xi), ':', xi, yi, '-') + #plt.title(function) + #plt.show() + msg = "abs-diff: %f" % abs(yi - sin(xi)).max() + assert_(allclose(yi, sin(xi), atol=atol), msg) + finally: + np.seterr(**olderr) def test_rbf_regularity(): tolerances = { @@ -76,12 +88,8 @@ 'thin-plate': 0.1, 'linear': 0.2 } - olderr = np.seterr(all="ignore") - try: - for function in FUNCTIONS: - yield check_rbf1d_regularity, function, tolerances.get(function, 1e-2) - finally: - np.seterr(**olderr) + for function in FUNCTIONS: + yield check_rbf1d_regularity, function, tolerances.get(function, 1e-2) def test_default_construction(): """Check that the Rbf class can be constructed with the default Modified: trunk/scipy/special/tests/test_data.py =================================================================== --- trunk/scipy/special/tests/test_data.py 2011-02-02 22:51:52 UTC (rev 7122) +++ trunk/scipy/special/tests/test_data.py 2011-02-02 22:52:06 UTC (rev 7123) @@ -206,13 +206,13 @@ # tgamma_ratio_data.txt ] + for test in TESTS: + yield _test_factory, test + +def _test_factory(test, dtype=np.double): + """Boost test""" olderr = np.seterr(all='ignore') try: - for test in TESTS: - yield _test_factory, test + test.check(dtype=dtype) finally: np.seterr(**olderr) - -def _test_factory(test, dtype=np.double): - """Boost test""" - test.check(dtype=dtype) Modified: trunk/scipy/stats/tests/test_continuous_basic.py =================================================================== --- trunk/scipy/stats/tests/test_continuous_basic.py 2011-02-02 22:51:52 UTC (rev 7122) +++ trunk/scipy/stats/tests/test_continuous_basic.py 2011-02-02 22:52:06 UTC (rev 7123) @@ -156,43 +156,48 @@ 'powerlognorm', 'johnsonsu', 'kstwobign'] #distslow are sorted by speed (very slow to slow) +def _silence_fp_errors(func): + def wrap(*a, **kw): + olderr = np.seterr(all='ignore') + try: + return func(*a, **kw) + finally: + np.seterr(**olderr) + wrap.__name__ = func.__name__ + return wrap + def test_cont_basic(): # this test skips slow distributions - olderr = np.seterr(all='ignore') - try: - for distname, arg in distcont[:]: - if distname in distslow: - continue - distfn = getattr(stats, distname) - np.random.seed(765456) - sn = 1000 - rvs = distfn.rvs(size=sn,*arg) - sm = rvs.mean() - sv = rvs.var() - skurt = stats.kurtosis(rvs) - sskew = stats.skew(rvs) - m,v = distfn.stats(*arg) + for distname, arg in distcont[:]: + if distname in distslow: + continue + distfn = getattr(stats, distname) + np.random.seed(765456) + sn = 1000 + rvs = distfn.rvs(size=sn,*arg) + sm = rvs.mean() + sv = rvs.var() + skurt = stats.kurtosis(rvs) + sskew = stats.skew(rvs) + m,v = distfn.stats(*arg) - yield check_sample_meanvar_, distfn, arg, m, v, sm, sv, sn, distname + \ - 'sample mean test' - # the sample skew kurtosis test has known failures, not very good distance measure - #yield check_sample_skew_kurt, distfn, arg, sskew, skurt, distname - yield check_moment, distfn, arg, m, v, distname - yield check_cdf_ppf, distfn, arg, distname - yield check_sf_isf, distfn, arg, distname - yield check_pdf, distfn, arg, distname - if distname in ['wald']: - continue - yield check_pdf_logpdf, distfn, arg, distname - yield check_cdf_logcdf, distfn, arg, distname - yield check_sf_logsf, distfn, arg, distname - if distname in distmissing: - alpha = 0.01 - yield check_distribution_rvs, distname, arg, alpha, rvs - finally: - np.seterr(**olderr) + yield check_sample_meanvar_, distfn, arg, m, v, sm, sv, sn, distname + \ + 'sample mean test' + # the sample skew kurtosis test has known failures, not very good distance measure + #yield check_sample_skew_kurt, distfn, arg, sskew, skurt, distname + yield check_moment, distfn, arg, m, v, distname + yield check_cdf_ppf, distfn, arg, distname + yield check_sf_isf, distfn, arg, distname + yield check_pdf, distfn, arg, distname + if distname in ['wald']: + continue + yield check_pdf_logpdf, distfn, arg, distname + yield check_cdf_logcdf, distfn, arg, distname + yield check_sf_logsf, distfn, arg, distname + if distname in distmissing: + alpha = 0.01 + yield check_distribution_rvs, distname, arg, alpha, rvs - @npt.dec.slow def test_cont_basic_slow(): # same as above for slow distributions @@ -223,6 +228,7 @@ alpha = 0.01 yield check_distribution_rvs, distname, arg, alpha, rvs + at _silence_fp_errors def check_moment(distfn, arg, m, v, msg): m1 = distfn.moment(1,*arg) m2 = distfn.moment(2,*arg) @@ -241,6 +247,7 @@ msg + ' - 2nd moment -infinite, m2=%s' % str(m2)) #np.isnan(m2) temporary special treatment for loggamma + at _silence_fp_errors def check_sample_meanvar_(distfn, arg, m, v, sm, sv, sn, msg): #this did not work, skipped silently by nose #check_sample_meanvar, sm, m, msg + 'sample mean test' @@ -296,11 +303,13 @@ ## else: ## assert abs(sm) > 10000, 'infinite moment, sm = ' + str(sm) + at _silence_fp_errors def check_cdf_ppf(distfn,arg,msg): npt.assert_almost_equal(distfn.cdf(distfn.ppf([0.001,0.5,0.999], *arg), *arg), [0.001,0.5,0.999], decimal=DECIMAL, err_msg= msg + \ ' - cdf-ppf roundtrip') + at _silence_fp_errors def check_sf_isf(distfn,arg,msg): npt.assert_almost_equal(distfn.sf(distfn.isf([0.1,0.5,0.9], *arg), *arg), [0.1,0.5,0.9], decimal=DECIMAL, err_msg= msg + \ @@ -310,6 +319,7 @@ decimal=DECIMAL, err_msg= msg + \ ' - cdf-sf relationship') + at _silence_fp_errors def check_pdf(distfn, arg, msg): # compares pdf at median with numerical derivative of cdf median = distfn.ppf(0.5, *arg) @@ -326,6 +336,7 @@ npt.assert_almost_equal(pdfv, cdfdiff, decimal=DECIMAL, err_msg= msg + ' - cdf-pdf relationship') + at _silence_fp_errors def check_pdf_logpdf(distfn, args, msg): # compares pdf at several points with the log of the pdf points = np.array([0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8]) @@ -336,6 +347,7 @@ logpdf = logpdf[np.isfinite(logpdf)] npt.assert_almost_equal(np.log(pdf), logpdf, decimal=7, err_msg=msg + " - logpdf-log(pdf) relationship") + at _silence_fp_errors def check_sf_logsf(distfn, args, msg): # compares sf at several points with the log of the sf points = np.array([0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8]) @@ -346,6 +358,7 @@ logsf = logsf[np.isfinite(logsf)] npt.assert_almost_equal(np.log(sf), logsf, decimal=7, err_msg=msg + " - logsf-log(sf) relationship") + at _silence_fp_errors def check_cdf_logcdf(distfn, args, msg): # compares cdf at several points with the log of the cdf points = np.array([0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8]) @@ -357,6 +370,7 @@ npt.assert_almost_equal(np.log(cdf), logcdf, decimal=7, err_msg=msg + " - logcdf-log(cdf) relationship") + at _silence_fp_errors def check_distribution_rvs(dist, args, alpha, rvs): #test from scipy.stats.tests #this version reuses existing random variables From scipy-svn at scipy.org Fri Feb 4 13:32:05 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Fri, 4 Feb 2011 12:32:05 -0600 (CST) Subject: [Scipy-svn] r7124 - in trunk/scipy/sparse: . tests Message-ID: <20110204183205.E042532154@scipy.org> Author: warren.weckesser Date: 2011-02-04 12:32:04 -0600 (Fri, 04 Feb 2011) New Revision: 7124 Modified: trunk/scipy/sparse/base.py trunk/scipy/sparse/tests/test_base.py Log: BUG: sparse: Eliminate spurious warnings generated by getrow() and getcol() (ticket #1381). Modified: trunk/scipy/sparse/base.py =================================================================== --- trunk/scipy/sparse/base.py 2011-02-02 22:52:06 UTC (rev 7123) +++ trunk/scipy/sparse/base.py 2011-02-04 18:32:04 UTC (rev 7124) @@ -434,9 +434,12 @@ # except for a_j = 1 from csc import csc_matrix n = self.shape[1] - a = csc_matrix((n, 1), dtype=self.dtype) - a[j, 0] = 1 - return self * a + if j < 0: + j += n + if j < 0 or j >= n: + raise IndexError("index out of bounds") + col_selector = csc_matrix(([1], [[j], [0]]), shape=(n,1), dtype=self.dtype) + return self * col_selector def getrow(self, i): """Returns a copy of row i of the matrix, as a (1 x n) sparse @@ -447,9 +450,12 @@ # except for a_i = 1 from csr import csr_matrix m = self.shape[0] - a = csr_matrix((1, m), dtype=self.dtype) - a[0, i] = 1 - return a * self + if i < 0: + i += m + if i < 0 or i >= m: + raise IndexError("index out of bounds") + row_selector = csr_matrix(([1], [[0], [i]]), shape=(1,m), dtype=self.dtype) + return row_selector * self #def __array__(self): # return self.toarray() Modified: trunk/scipy/sparse/tests/test_base.py =================================================================== --- trunk/scipy/sparse/tests/test_base.py 2011-02-02 22:52:06 UTC (rev 7123) +++ trunk/scipy/sparse/tests/test_base.py 2011-02-04 18:32:04 UTC (rev 7124) @@ -133,9 +133,11 @@ def test_getrow(self): assert_array_equal(self.datsp.getrow(1).todense(), self.dat[1,:]) + assert_array_equal(self.datsp.getrow(-1).todense(), self.dat[-1,:]) def test_getcol(self): assert_array_equal(self.datsp.getcol(1).todense(), self.dat[:,1]) + assert_array_equal(self.datsp.getcol(-1).todense(), self.dat[:,-1]) def test_sum(self): """Does the matrix's .sum(axis=...) method work? From scipy-svn at scipy.org Sun Feb 6 14:11:28 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 6 Feb 2011 13:11:28 -0600 (CST) Subject: [Scipy-svn] r7125 - in trunk/scipy/signal: . tests Message-ID: <20110206191128.C285A32364@scipy.org> Author: warren.weckesser Date: 2011-02-06 13:11:27 -0600 (Sun, 06 Feb 2011) New Revision: 7125 Modified: trunk/scipy/signal/filter_design.py trunk/scipy/signal/tests/test_filter_design.py Log: BUG: signal: zpk2tf returns a scalar 1.0 for the denominator when the list of poles was empty (ticket #990). Thanks to asomers for the patch. Modified: trunk/scipy/signal/filter_design.py =================================================================== --- trunk/scipy/signal/filter_design.py 2011-02-04 18:32:04 UTC (rev 7124) +++ trunk/scipy/signal/filter_design.py 2011-02-06 19:11:27 UTC (rev 7125) @@ -243,7 +243,7 @@ b[i] = k[i] * poly(z[i]) else: b = k * poly(z) - a = poly(p) + a = atleast_1d(poly(p)) return b, a def normalize(b, a): Modified: trunk/scipy/signal/tests/test_filter_design.py =================================================================== --- trunk/scipy/signal/tests/test_filter_design.py 2011-02-04 18:32:04 UTC (rev 7124) +++ trunk/scipy/signal/tests/test_filter_design.py 2011-02-06 19:11:27 UTC (rev 7125) @@ -1,9 +1,10 @@ import warnings import numpy as np -from numpy.testing import TestCase, assert_array_almost_equal, assert_raises +from numpy.testing import TestCase, assert_array_almost_equal, \ + assert_array_equal, assert_raises, assert_ -from scipy.signal import tf2zpk, bessel, BadCoefficients +from scipy.signal import tf2zpk, zpk2tf, bessel, BadCoefficients class TestTf2zpk(TestCase): @@ -32,3 +33,22 @@ assert_raises(BadCoefficients, tf2zpk, [1e-15], [1.0, 1.0]) finally: warnings.simplefilter("always", BadCoefficients) + + +class TestZpk2Tf(TestCase): + + def test_identity(self): + """Test the identity transfer function.""" + z = [] + p = [] + k = 1. + b, a = zpk2tf(z, p, k) + b_r = np.array([1.]) # desired result + a_r = np.array([1.]) # desired result + # The test for the *type* of the return values is a regression + # test for ticket #1095. In the case p=[], zpk2tf used to + # return the scalar 1.0 instead of array([1.0]). + assert_array_equal(b, b_r) + assert_(isinstance(b, np.ndarray)) + assert_array_equal(a, a_r) + assert_(isinstance(a, np.ndarray)) From scipy-svn at scipy.org Sun Feb 6 14:16:54 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 6 Feb 2011 13:16:54 -0600 (CST) Subject: [Scipy-svn] r7126 - trunk/scipy/signal Message-ID: <20110206191654.E110832364@scipy.org> Author: warren.weckesser Date: 2011-02-06 13:16:54 -0600 (Sun, 06 Feb 2011) New Revision: 7126 Modified: trunk/scipy/signal/filter_design.py Log: DOC: signal: Fix docstrings for zpk2tf and tf2zpk. Modified: trunk/scipy/signal/filter_design.py =================================================================== --- trunk/scipy/signal/filter_design.py 2011-02-06 19:11:27 UTC (rev 7125) +++ trunk/scipy/signal/filter_design.py 2011-02-06 19:16:54 UTC (rev 7126) @@ -186,9 +186,9 @@ Parameters ---------- b : ndarray - numerator polynomial. + Numerator polynomial. a : ndarray - numerator and denominator polynomials. + Denominator polynomial. Returns ------- @@ -229,7 +229,7 @@ b : ndarray Numerator polynomial. a : ndarray - Numerator and denominator polynomials. + Denominator polynomial. """ z = atleast_1d(z) From scipy-svn at scipy.org Tue Feb 8 23:42:00 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Tue, 8 Feb 2011 22:42:00 -0600 (CST) Subject: [Scipy-svn] r7127 - trunk/doc/source Message-ID: <20110209044200.249183236A@scipy.org> Author: warren.weckesser Date: 2011-02-08 22:41:59 -0600 (Tue, 08 Feb 2011) New Revision: 7127 Modified: trunk/doc/source/stats.rst Log: DOC: add more more methods to the lists of stats distributions methods in the stats rst doc. Modified: trunk/doc/source/stats.rst =================================================================== --- trunk/doc/source/stats.rst 2011-02-06 19:16:54 UTC (rev 7126) +++ trunk/doc/source/stats.rst 2011-02-09 04:41:59 UTC (rev 7127) @@ -13,12 +13,20 @@ :toctree: generated/ rv_continuous + rv_continuous.rvs rv_continuous.pdf + rv_continuous.logpdf rv_continuous.cdf + rv_continuous.logcdf rv_continuous.sf + rv_continuous.logsf rv_continuous.ppf rv_continuous.isf + rv_continuous.moment rv_continuous.stats + rv_continuous.entropy + rv_continuous.fit + rv_continuous.expect Each discrete distribution is an instance of the class rv_discrete: @@ -26,12 +34,19 @@ :toctree: generated/ rv_discrete + rv_discrete.rvs rv_discrete.pmf + rv_discrete.logpmf rv_discrete.cdf + rv_discrete.logcdf rv_discrete.sf + rv_discrete.logsf rv_discrete.ppf rv_discrete.isf rv_discrete.stats + rv_discrete.moment + rv_discrete.entropy + rv_discrete.expect Continuous distributions ======================== From scipy-svn at scipy.org Thu Feb 10 03:39:42 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Thu, 10 Feb 2011 02:39:42 -0600 (CST) Subject: [Scipy-svn] r7128 - in trunk/doc/source: . tutorial/stats Message-ID: <20110210083942.D0AA832380@scipy.org> Author: oliphant Date: 2011-02-10 02:39:41 -0600 (Thu, 10 Feb 2011) New Revision: 7128 Modified: trunk/doc/source/stats.rst trunk/doc/source/tutorial/stats/continuous.lyx Log: Add documentation to remaining methods to rv_continuous and rv_discrete. Modified: trunk/doc/source/stats.rst =================================================================== --- trunk/doc/source/stats.rst 2011-02-09 04:41:59 UTC (rev 7127) +++ trunk/doc/source/stats.rst 2011-02-10 08:39:41 UTC (rev 7128) @@ -27,6 +27,11 @@ rv_continuous.entropy rv_continuous.fit rv_continuous.expect + rv_continuous.median + rv_continuous.mean + rv_continuous.var + rv_continuous.std + rv_continuous.interval Each discrete distribution is an instance of the class rv_discrete: @@ -47,6 +52,11 @@ rv_discrete.moment rv_discrete.entropy rv_discrete.expect + rv_discrete.median + rv_discrete.mean + rv_discrete.var + rv_discrete.std + rv_discrete.interval Continuous distributions ======================== Modified: trunk/doc/source/tutorial/stats/continuous.lyx =================================================================== --- trunk/doc/source/tutorial/stats/continuous.lyx 2011-02-09 04:41:59 UTC (rev 7127) +++ trunk/doc/source/tutorial/stats/continuous.lyx 2011-02-10 08:39:41 UTC (rev 7128) @@ -1,8 +1,9 @@ -#LyX 1.5.1 created this file. For more info see http://www.lyx.org/ -\lyxformat 276 +#LyX 1.6.6.1 created this file. For more info see http://www.lyx.org/ +\lyxformat 345 \begin_document \begin_header \textclass article +\use_default_options false \language english \inputencoding auto \font_roman default @@ -13,9 +14,11 @@ \font_osf false \font_sf_scale 100 \font_tt_scale 100 + \graphics default \paperfontsize default \spacing single +\use_hyperref false \papersize default \use_geometry true \use_amsmath 2 @@ -38,6 +41,7 @@ \tracking_changes false \output_changes false \author "" +\author "" \end_header \begin_body @@ -78,43 +82,43 @@ \begin_inset Tabular - - - - - + + + + + \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout Function Name \end_layout \end_inset - + \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout Standard Function \end_layout \end_inset - + \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout Transformation \end_layout \end_inset - + \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout Cumulative Distribution Function (CDF) \end_layout @@ -123,7 +127,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $F\left(x\right)$ \end_inset @@ -135,7 +139,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $F\left(x;L,S\right)=F\left(\frac{\left(x-L\right)}{S}\right)$ \end_inset @@ -145,11 +149,11 @@ \end_inset - + \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout Probability Density Function (PDF) \end_layout @@ -158,7 +162,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $f\left(x\right)=F^{\prime}\left(x\right)$ \end_inset @@ -170,7 +174,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $f\left(x;L,S\right)=\frac{1}{S}f\left(\frac{\left(x-L\right)}{S}\right)$ \end_inset @@ -180,11 +184,11 @@ \end_inset - + \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout Percent Point Function (PPF) \end_layout @@ -193,7 +197,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $G\left(q\right)=F^{-1}\left(q\right)$ \end_inset @@ -205,7 +209,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $G\left(q;L,S\right)=L+SG\left(q\right)$ \end_inset @@ -215,11 +219,11 @@ \end_inset - + \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout Probability Sparsity Function (PSF) \end_layout @@ -228,7 +232,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $g\left(q\right)=G^{\prime}\left(q\right)$ \end_inset @@ -240,7 +244,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $g\left(q;L,S\right)=Sg\left(q\right)$ \end_inset @@ -250,11 +254,11 @@ \end_inset - + \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout Hazard Function (HF) \end_layout @@ -263,7 +267,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $h_{a}\left(x\right)=\frac{f\left(x\right)}{1-F\left(x\right)}$ \end_inset @@ -275,7 +279,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $h_{a}\left(x;L,S\right)=\frac{1}{S}h_{a}\left(\frac{\left(x-L\right)}{S}\right)$ \end_inset @@ -285,11 +289,11 @@ \end_inset - + \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout Cumulative Hazard Functon (CHF) \end_layout @@ -298,7 +302,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $H_{a}\left(x\right)=$ \end_inset @@ -314,7 +318,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $H_{a}\left(x;L,S\right)=H_{a}\left(\frac{\left(x-L\right)}{S}\right)$ \end_inset @@ -324,11 +328,11 @@ \end_inset - + \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout Survival Function (SF) \end_layout @@ -337,7 +341,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $S\left(x\right)=1-F\left(x\right)$ \end_inset @@ -349,7 +353,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $S\left(x;L,S\right)=S\left(\frac{\left(x-L\right)}{S}\right)$ \end_inset @@ -359,11 +363,11 @@ \end_inset - + \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout Inverse Survival Function (ISF) \end_layout @@ -372,7 +376,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $Z\left(\alpha\right)=S^{-1}\left(\alpha\right)=G\left(1-\alpha\right)$ \end_inset @@ -384,7 +388,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $Z\left(\alpha;L,S\right)=L+SZ\left(\alpha\right)$ \end_inset @@ -394,11 +398,11 @@ \end_inset - + \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout Moment Generating Function (MGF) \end_layout @@ -407,7 +411,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $M_{Y}\left(t\right)=E\left[e^{Yt}\right]$ \end_inset @@ -419,7 +423,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $M_{X}\left(t\right)=e^{Lt}M_{Y}\left(St\right)$ \end_inset @@ -429,11 +433,11 @@ \end_inset - + \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout Random Variates \end_layout @@ -442,7 +446,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $Y=G\left(U\right)$ \end_inset @@ -454,7 +458,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $X=L+SY$ \end_inset @@ -464,11 +468,11 @@ \end_inset - + \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout (Differential) Entropy \end_layout @@ -477,7 +481,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $h\left[Y\right]=-\int f\left(y\right)\log f\left(y\right)dy$ \end_inset @@ -489,7 +493,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $h\left[X\right]=h\left[Y\right]+\log S$ \end_inset @@ -499,11 +503,11 @@ \end_inset - + \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout (Non-central) Moments \end_layout @@ -512,7 +516,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $\mu_{n}^{\prime}=E\left[Y^{n}\right]$ \end_inset @@ -524,7 +528,7 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $E\left[X^{n}\right]=L^{n}\sum_{k=0}^{N}\left(\begin{array}{c} n\\ k\end{array}\right)\left(\frac{S}{L}\right)^{k}\mu_{k}^{\prime}$ @@ -536,11 +540,11 @@ \end_inset - + \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout Central Moments \end_layout @@ -549,8 +553,8 @@ \begin_inset Text -\begin_layout Standard -\begin_inset Formula $\mu_{n}=E\left[\left(Y-\mu\right)^{n}\right]$ +\begin_layout Plain Layout +\begin_inset Formula $\mu_{Y^{n}}=E\left[\left(Y-\mu_{Y}\right)^{n}\right]$ \end_inset @@ -561,8 +565,8 @@ \begin_inset Text -\begin_layout Standard -\begin_inset Formula $E\left[\left(X-\mu_{X}\right)^{n}\right]=S^{n}\mu_{n}$ +\begin_layout Plain Layout +\begin_inset Formula $E\left[\left(X-\mu_{X}\right)^{n}\right]=S^{n}\mu_{X^{n}}=S^{n}\mu_{n}$ \end_inset @@ -571,11 +575,11 @@ \end_inset - + \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout mean (mode, median), var \end_layout @@ -584,8 +588,8 @@ \begin_inset Text -\begin_layout Standard -\begin_inset Formula $\mu,\,\mu_{2}$ +\begin_layout Plain Layout +\begin_inset Formula $\mu_{Y},\,\mu_{Y^{2}}$ \end_inset @@ -596,30 +600,30 @@ \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $L+S\mu,\, S^{2}\mu_{2}$ \end_inset - + \end_layout \end_inset - - + + \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout skewness, kurtosis \end_layout \end_inset - + \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $\gamma_{1}=\frac{\mu_{3}}{\left(\mu_{2}\right)^{3/2}},\,$ \end_inset @@ -632,10 +636,10 @@ \end_inset - + \begin_inset Text -\begin_layout Standard +\begin_layout Plain Layout \begin_inset Formula $\gamma_{1},\,\gamma_{2}$ \end_inset @@ -653,8 +657,10 @@ \end_layout \begin_layout Standard -\InsetSpace ~ +\begin_inset space ~ +\end_inset + \end_layout \begin_layout Subsection @@ -858,16 +864,49 @@ \end_inset - If desired, sample estimates for -\begin_inset Formula $L$ + +\end_layout + +\begin_layout Subsection +Method of Moments +\end_layout + +\begin_layout Standard +Another approach to finding parameters of a distribution that explain a + collection of data is to match the expected moments of the distribution + with the computed moments and the relevant equations solved for the parameters + of the distribution. + In particular, for a distribution with no shape parameters, the following + equations can be solved for location and scale +\end_layout + +\begin_layout Standard +\begin_inset Formula \begin{align*} +\mu_{Y} & =S\mu+L\\ +\mu_{Y^{2}} & =S^{2}\mu_{2}.\end{align*} + \end_inset + Estimating +\begin_inset Formula $\mu_{Y}$ +\end_inset + + as +\begin_inset Formula $\hat{\mu}$ +\end_inset + and -\begin_inset Formula $S$ +\begin_inset Formula $\mu_{Y^{2}}$ \end_inset - (not necessarily maximum likelihood estimates) can be obtained from samples - estimates of the mean and variance using + as +\begin_inset Formula $\hat{\mu}_{2}$ +\end_inset + + gives the estimates +\end_layout + +\begin_layout Standard \begin_inset Formula \begin{eqnarray*} \hat{S} & = & \sqrt{\frac{\hat{\mu}_{2}}{\mu_{2}}}\\ \hat{L} & = & \hat{\mu}-\hat{S}\mu\end{eqnarray*} @@ -897,11 +936,64 @@ ) and \begin_inset Formula \begin{eqnarray*} \hat{\mu} & = & \frac{1}{N}\sum_{i=1}^{N}x_{i}=\bar{\mathbf{x}}\\ -\hat{\mu}_{2} & = & \frac{1}{N-1}\sum_{i=1}^{N}\left(x_{i}-\hat{\mu}\right)^{2}=\frac{N}{N-1}\overline{\left(\mathbf{x}-\bar{\mathbf{x}}\right)^{2}}\end{eqnarray*} +\hat{\mu}_{2} & = & \frac{1}{N}\sum_{i=1}^{N}\left(x_{i}-\hat{\mu}\right)^{2}=\overline{\left(\mathbf{x}-\bar{\mathbf{x}}\right)^{2}}.\end{eqnarray*} \end_inset +In general, if the distribution has +\begin_inset Formula $M$ +\end_inset + shape parameters, then to find the parameters of the distribution, we need + to add +\begin_inset Formula $M$ +\end_inset + + additional equations. + It is straightforward to add the central moment equations: +\begin_inset Formula \[ +\mu_{Y^{n}}=S^{n}\mu_{n}\left(\boldsymbol{\theta}\right)\] + +\end_inset + +for +\begin_inset Formula $n=2\ldots M+2$ +\end_inset + +. + If we can estimate the +\begin_inset Formula $n^{\mbox{th}}$ +\end_inset + + central moment of +\begin_inset Formula $Y$ +\end_inset + + as +\begin_inset Formula \[ +\hat{\mu}_{n}=\frac{1}{N}\sum_{i=1}^{N}\left(x_{i}-\hat{\mu}\right)^{n}=\overline{\left(\mathbf{x}-\bar{\mathbf{x}}\right)^{n}},\] + +\end_inset + +then these data-computed statistics can be used to estimate +\begin_inset Formula $S$ +\end_inset + + and the parameter vector +\begin_inset Formula $\boldsymbol{\theta}$ +\end_inset + + by solving this set of potentially non-linear equations. + Then, the location parameter can be found by solving the equation +\begin_inset Formula $\mu_{Y}=S\mu\left(\boldsymbol{\theta}\right)+L$ +\end_inset + +, for +\begin_inset Formula $L$ +\end_inset + +. + \end_layout \begin_layout Subsection @@ -923,7 +1015,8 @@ \begin_inset Formula $x_{i}$ \end_inset - +. + \end_layout \begin_layout Section From scipy-svn at scipy.org Thu Feb 10 03:42:04 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Thu, 10 Feb 2011 02:42:04 -0600 (CST) Subject: [Scipy-svn] r7129 - trunk/scipy/stats Message-ID: <20110210084204.00EEB1B8D20@scipy.org> Author: oliphant Date: 2011-02-10 02:42:03 -0600 (Thu, 10 Feb 2011) New Revision: 7129 Modified: trunk/scipy/stats/distributions.py trunk/scipy/stats/morestats.py Log: Add remaining docstrings for moment, median, std, var, mean, expect, logpdf, logcdf, logsf. Fix moment to take loc and scale keyword arguments. Fix documentation for other functions. Implement bayes_mvs in terms of mvsdist which returns the distributions of the estimates themselves. Modified: trunk/scipy/stats/distributions.py =================================================================== --- trunk/scipy/stats/distributions.py 2011-02-10 08:39:41 UTC (rev 7128) +++ trunk/scipy/stats/distributions.py 2011-02-10 08:42:03 UTC (rev 7129) @@ -1,8 +1,8 @@ # Functions to implement several important functions for # various Continous and Discrete Probability Distributions # -# Author: Travis Oliphant 2002-2010 with contributions from -# SciPy Developers 2004-2010 +# Author: Travis Oliphant 2002-2011 with contributions from +# SciPy Developers 2004-2011 # import math @@ -34,6 +34,38 @@ mu = data.mean() return ((data - mu)**n).mean() +def _moment_from_stats(n, mu, mu2, g1, g2, moment_func, args): + if (n==0): + return 1.0 + elif (n==1): + if mu is None: + val = moment_func(1,*args) + else: + val = mu + elif (n==2): + if mu2 is None or mu is None: + val = moment_func(2,*args) + else: + val = mu2 + mu*mu + elif (n==3): + if g1 is None or mu2 is None or mu is None: + val = moment_func(3,*args) + else: + mu3 = g1*(mu2**1.5) # 3rd central moment + val = mu3+3*mu*mu2+mu**3 # 3rd non-central moment + elif (n==4): + if g1 is None or g2 is None or mu2 is None or mu is None: + val = moment_func(4,*args) + else: + mu4 = (g2+3.0)*(mu2**2.0) # 4th central moment + mu3 = g1*(mu2**1.5) # 3rd central moment + val = mu4+4*mu*mu3+6*mu*mu*mu2+mu**4 + else: + val = moment_func(n, *args) + + return val + + def _skew(data): data = np.ravel(data) mu = data.mean() @@ -107,18 +139,34 @@ """pdf(x, %(shapes)s, loc=0, scale=1) Probability density function. """ +_doc_logpdf = \ +"""logpdf(x, %(shapes)s, loc=0, scale=1) + Log of the probability density function. +""" _doc_pmf = \ """pmf(x, %(shapes)s, loc=0, scale=1) Probability mass function. """ +_doc_logpmf = \ +"""logpmf(x, %(shapes)s, loc=0, scale=1) + Log of the probability mass function. +""" _doc_cdf = \ """cdf(x, %(shapes)s, loc=0, scale=1) Cumulative density function. """ +_doc_logcdf = \ +"""logcdf(x, %(shapes)s, loc=0, scale=1) + Log of the cumulative density function. +""" _doc_sf = \ """sf(x, %(shapes)s, loc=0, scale=1) Survival function (1-cdf --- sometimes more accurate). """ +_doc_logsf = \ +"""logsf(x, %(shapes)s, loc=0, scale=1) + Log of the survival function. +""" _doc_ppf = \ """ppf(q, %(shapes)s, loc=0, scale=1) Percent point function (inverse of cdf --- percentiles). @@ -127,6 +175,10 @@ """isf(q, %(shapes)s, loc=0, scale=1) Inverse survival function (inverse of sf). """ +_doc_moment = \ +"""moment(n, %(shapes)s, loc=0, scale=1) + Non-central moment of order n +""" _doc_stats = \ """stats(%(shapes)s, loc=0, scale=1, moments='mv') Mean('m'), variance('v'), skew('s'), and/or kurtosis('k'). @@ -139,9 +191,40 @@ """fit(data, %(shapes)s, loc=0, scale=1) Parameter estimates for generic data. """ +_doc_expect = \ +"""expect(func, %(shapes)s, loc=0, scale=1, lb=None, ub=None, conditional=False, **kwds) + Expected value of a function (of one argument) with respect to the distribution. +""" +_doc_expect_discrete = \ +"""expect(func, %(shapes)s, loc=0, lb=None, ub=None, conditional=False) + Expected value of a function (of one argument) with respect to the distribution. +""" +_doc_median = \ +"""median(%(shapes)s, loc=0, scale=1) + Median of the distribution. +""" +_doc_mean = \ +"""mean(%(shapes)s, loc=0, scale=1) + Mean of the distribution. +""" +_doc_var = \ +"""var(%(shapes)s, loc=0, scale=1) + Variance of the distribution. +""" +_doc_std = \ +"""std(%(shapes)s, loc=0, scale=1) + Standard deviation of the distribution. +""" +_doc_interval = \ +"""interval(alpha, %(shapes)s, loc=0, scale=1) + Endpoints of the range that contains alpha % of the distribution +""" _doc_allmethods = ''.join([docheaders['methods'], _doc_rvs, _doc_pdf, - _doc_cdf, _doc_sf, _doc_ppf, _doc_isf, - _doc_stats, _doc_entropy, _doc_fit]) + _doc_logpdf, _doc_cdf, _doc_logcdf, _doc_sf, + _doc_logsf, _doc_ppf, _doc_isf, _doc_moment, + _doc_stats, _doc_entropy, _doc_fit, + _doc_expect, _doc_median, + _doc_mean, _doc_var, _doc_std, _doc_interval]) # Note that the two lines for %(shapes) are searched for and replaced in # rv_continuous and rv_discrete - update there if the exact string changes @@ -217,13 +300,23 @@ docdict = {'rvs':_doc_rvs, 'pdf':_doc_pdf, + 'logpdf':_doc_logpdf, 'cdf':_doc_cdf, + 'logcdf':_doc_logcdf, 'sf':_doc_sf, + 'logsf':_doc_logsf, 'ppf':_doc_ppf, 'isf':_doc_isf, 'stats':_doc_stats, 'entropy':_doc_entropy, 'fit':_doc_fit, + 'moment':_doc_moment, + 'expect':_doc_expect, + 'interval':_doc_interval, + 'mean':_doc_mean, + 'std':_doc_std, + 'var':_doc_var, + 'median':_doc_median, 'allmethods':_doc_allmethods, 'callparams':_doc_default_callparams, 'longsummary':_doc_default_longsummary, @@ -237,11 +330,15 @@ docdict_discrete = docdict.copy() docdict_discrete['pmf'] = _doc_pmf -_doc_disc_methods = ['rvs', 'pmf', 'cdf', 'sf', 'ppf', 'isf', 'stats', - 'entropy', 'fit'] +docdict_discrete['logpmf'] = _doc_logpmf +docdict_discrete['expect'] = _doc_expect_discrete +_doc_disc_methods = ['rvs', 'pmf', 'logpmf', 'cdf', 'logcdf', 'sf', 'logsf', + 'ppf', 'isf', 'stats', 'entropy', 'fit', 'expect', 'median', + 'mean', 'var', 'std', 'interval'] for obj in _doc_disc_methods: docdict_discrete[obj] = docdict_discrete[obj].replace(', scale=1', '') docdict_discrete.pop('pdf') +docdict_discrete.pop('logpdf') _doc_allmethods = ''.join([docdict_discrete[obj] for obj in _doc_disc_methods]) @@ -334,8 +431,14 @@ def pdf(self, x): #raises AttributeError in frozen discrete distribution return self.dist.pdf(x, *self.args, **self.kwds) + def logpdf(self, x): + return self.dist.logpdf(x, *self.args, **self.kwds) + def cdf(self, x): return self.dist.cdf(x, *self.args, **self.kwds) + + def logcdf(self, x): + return self.dist.logcdf(x, *self.args, **self.kwds) def ppf(self, q): return self.dist.ppf(q, *self.args, **self.kwds) @@ -351,6 +454,9 @@ def sf(self, x): return self.dist.sf(x, *self.args, **self.kwds) + def logsf(self, x): + return self.dist.logsf(x, *self.args, **self.kwds) + def stats(self, moments='mv'): kwds = self.kwds.copy() kwds.update({'moments':moments}) @@ -369,7 +475,7 @@ return self.dist.std(*self.args, **self.kwds) def moment(self, n): - return self.dist.moment(n, *self.args) + return self.dist.moment(n, *self.args, **self.kwds) def entropy(self): return self.dist.entropy(*self.args, **self.kwds) @@ -377,6 +483,9 @@ def pmf(self,k): return self.dist.pmf(k, *self.args, **self.kwds) + def logpmf(self,k): + return self.dist.logpmf(k, *self.args, **self.kwds) + def interval(self, alpha): return self.dist.interval(alpha, *self.args, **self.kwds) @@ -860,8 +969,9 @@ New random variables can be defined by subclassing rv_continuous class and re-defining at least the - _pdf or the cdf method which will be given clean arguments (in between a - and b) and passing the argument check method + _pdf or the _cdf method (normalized to location 0 and scale 1) + which will be given clean arguments (in between a and b) and + passing the argument check method If postive argument checking is not correct for your RV then you will also need to re-define :: @@ -871,9 +981,9 @@ Correct, but potentially slow defaults exist for the remaining methods but for speed and/or accuracy you can over-ride :: - _cdf, _ppf, _rvs, _isf, _sf + _logpdf, _cdf, _logcdf, _ppf, _rvs, _isf, _sf, _logsf - Rarely would you override _isf and _sf but you could. + Rarely would you override _isf, _sf, and _logsf but you could. Statistics are computed using numerical integration by default. For speed you can redefine this using @@ -1119,7 +1229,7 @@ """ Log of the probability density function at x of the given RV. - This uses more numerically accurate calculation if available. + This uses a more numerically accurate calculation if available. Parameters ---------- @@ -1534,7 +1644,7 @@ else: return tuple(output) - def moment(self, n, *args): + def moment(self, n, *args, **kwds): """ n'th order non-central moment of distribution @@ -1543,17 +1653,23 @@ n: int, n>=1 order of moment - arg1, arg2, arg3,... : array-like + arg1, arg2, arg3,... : float The shape parameter(s) for the distribution (see docstring of the instance object for more information) + loc : float, optional + location parameter (default=0) + scale : float, optional + scale parameter (default=1) + """ - if not self._argcheck(*args): + loc, scale = map(kwds.get,['loc','scale']) + if not (self._argcheck(*args) and (scale > 0)): return nan if (floor(n) != n): raise ValueError("Moment must be an integer.") if (n < 0): raise ValueError("Moment must be positive.") - if (n == 0): return 1.0 + mu, mu2, g1, g2 = None, None, None, None if (n > 0) and (n < 5): signature = inspect.getargspec(self._stats.im_func) if (signature[2] is not None) or ('moments' in signature[0]): @@ -1561,28 +1677,20 @@ else: mdict = {} mu, mu2, g1, g2 = self._stats(*args,**mdict) - if (n==1): - if mu is None: return self._munp(1,*args) - else: return mu - elif (n==2): - if mu2 is None or mu is None: - return self._munp(2,*args) - else: return mu2 + mu*mu - elif (n==3): - if g1 is None or mu2 is None: - return self._munp(3,*args) - else: - mu3 = g1*(mu2**1.5) # 3rd central moment - return mu3+3*mu*mu2+mu**3 # 3rd non-central moment - else: # (n==4) - if g2 is None or mu2 is None: - return self._munp(4,*args) - else: - mu4 = (g2+3.0)*(mu2**2.0) # 4th central moment - mu3 = g1*(mu2**1.5) # 3rd central moment - return mu4+4*mu*mu3+6*mu*mu*mu2+mu**4 + val = _moment_from_stats(n, mu, mu2, g1, g2, self._munp, args) + + # Convert to transformed X = L + S*Y + # so E[X^n] = E[(L+S*Y)^n] = L^n sum(comb(n,k)*(S/L)^k E[Y^k],k=0...n) + if loc == 0: + return scale**n * val else: - return self._munp(n,*args) + result = 0 + fac = scale / loc + for k in range(n): + valk = _moment_from_stats(k, mu, mu2, g1, g2, self._munp, args) + result += comb(n,k,exact=True)*(fac**k) * valk + result += fac**n * val + return result * loc**n def _nnlf(self, x, *args): return -sum(self._logpdf(x, *args),axis=0) @@ -1613,6 +1721,8 @@ args = (1.0,)*self.numargs return args + self.fit_loc_scale(data, *args) + # Return the (possibly reduced) function to optimize in order to find MLE + # estimates for the .fit method def _reduce_func(self, args, kwds): args = list(args) Nargs = len(args) - 2 @@ -1660,9 +1770,9 @@ such. One can hold some parameters fixed to specific values by passing in - keyword arguments ``f0``..[is this supposed to be an ellipsis?] ``fn`` - (for shape parameters) and ``floc`` and ``fscale`` (for location and - scale parameters, respectively). + keyword arguments ``f0``, ``f1``, ..., ``fn`` (for shape parameters) + and ``floc`` and ``fscale`` (for location and scale parameters, + respectively). Parameters ---------- @@ -1677,7 +1787,7 @@ Special keyword arguments are recognized as holding certain parameters fixed: - f0..fn : hold respective shape parameters fixed. + f0...fn : hold respective shape parameters fixed. floc : hold location parameter fixed to specified value. @@ -1721,9 +1831,9 @@ except AttributeError: raise ValueError("%s is not a valid optimizer" % optimizer) vals = optimizer(func,x0,args=(ravel(data),),disp=0) - vals = tuple(vals) if restore is not None: vals = restore(args, vals) + vals = tuple(vals) return vals def fit_loc_scale(self, data, *args): @@ -1820,6 +1930,9 @@ of the integration interval. The return value is the expectation of the function, conditional on being in the given interval. + Additional keyword arguments are passed to the integration routine. + + Returns ------- expected value : float @@ -1829,19 +1942,21 @@ This function has not been checked for it's behavior when the integral is not finite. The integration behavior is inherited from integrate.quad. """ + lockwds = {'loc': loc, + 'scale':scale} if func is None: def fun(x, *args): - return x*self.pdf(x, *args, **{'loc':loc, 'scale':scale}) + return x*self.pdf(x, *args, **lockwds) else: def fun(x, *args): - return func(x)*self.pdf(x, *args, **{'loc':loc, 'scale':scale}) + return func(x)*self.pdf(x, *args, **lockwds) if lb is None: lb = loc + self.a * scale if ub is None: ub = loc + self.b * scale if conditional: - invfac = (self.sf(lb, *args, **{'loc':loc, 'scale':scale}) - - self.sf(ub, *args, **{'loc':loc, 'scale':scale})) + invfac = (self.sf(lb, *args, **lockwds) + - self.sf(ub, *args, **lockwds)) else: invfac = 1.0 kwds['args'] = args @@ -5465,17 +5580,23 @@ ---------- n: int, n>=1 order of moment - arg1, arg2, arg3,...: array-like + arg1, arg2, arg3,...: float The shape parameter(s) for the distribution (see docstring of the instance object for more information) + loc : float, optional + location parameter (default=0) + scale : float, optional + scale parameter (default=1) + """ - if not self._argcheck(*args): + loc, scale = map(kwds.get,['loc','scale']) + if not (self._argcheck(*args) and (scale > 0)): return nan if (floor(n) != n): raise ValueError("Moment must be an integer.") if (n < 0): raise ValueError("Moment must be positive.") - if (n == 0): return 1.0 + mu, mu2, g1, g2 = None, None, None, None if (n > 0) and (n < 5): signature = inspect.getargspec(self._stats.im_func) if (signature[2] is not None) or ('moments' in signature[0]): @@ -5483,28 +5604,22 @@ else: dict = {} mu, mu2, g1, g2 = self._stats(*args,**dict) - if (n==1): - if mu is None: return self._munp(1,*args) - else: return mu - elif (n==2): - if mu2 is None or mu is None: return self._munp(2,*args) - else: return mu2 + mu*mu - elif (n==3): - if (g1 is None) or (mu2 is None) or (mu is None): - return self._munp(3,*args) - else: - mu3 = g1*(mu2**1.5) # 3rd central moment - return mu3+3*mu*mu2+mu**3 # 3rd non-central moment - else: # (n==4) - if (g2 is None) or (g1 is None) or (mu is None) or (mu2 is None): - return self._munp(4,*args) - else: - mu4 = (g2+3.0)*(mu2**2.0) # 4th central moment - mu3 = g1*(mu2**1.5) # 3rd central moment - return mu4+4*mu*mu3+6*mu*mu*mu2+mu**4 + val = _moment_from_stats(n, mu, mu2, g1, g2, self._munp, args) + + # Convert to transformed X = L + S*Y + # so E[X^n] = E[(L+S*Y)^n] = L^n sum(comb(n,k)*(S/L)^k E[Y^k],k=0...n) + if loc == 0: + return scale**n * val else: - return self._munp(n,*args) + result = 0 + fac = scale / loc + for k in range(n): + valk = _moment_from_stats(k, mu, mu2, g1, g2, self._munp, args) + result += comb(n,k,exact=True)*(fac**k) * valk + result += fac**n * val + return result * loc**n + def freeze(self, *args, **kwds): return rv_frozen(self, *args, **kwds) @@ -5550,7 +5665,7 @@ Parameters ---------- fn : function (default: identity mapping) - Function for which integral is calculated. Takes only one argument. + Function for which sum is calculated. Takes only one argument. args : tuple argument (parameters) of the distribution optional keyword parameters Modified: trunk/scipy/stats/morestats.py =================================================================== --- trunk/scipy/stats/morestats.py 2011-02-10 08:39:41 UTC (rev 7128) +++ trunk/scipy/stats/morestats.py 2011-02-10 08:42:03 UTC (rev 7129) @@ -40,32 +40,6 @@ ## at http://dspace.byu.edu/bitstream/1877/438/1/bayes_mvs.pdf ## (Permanent link at http://hdl.handle.net/1877/438 ) -# assume distributions are gaussian with given means and variances. -def _gauss_mvs(x, n, alpha): - xbar = x.mean() - C = x.var() - val = distributions.norm.ppf((1+alpha)/2.0) - # mean is a Gaussian with mean xbar and variance C/n - mp = xbar - fac0 = sqrt(C/n) - term = fac0*val - ma = mp - term - mb = mp + term - # var is a Gaussian with mean C and variance 2*C*C/n - vp = C - fac1 = sqrt(2.0/n)*C - term = fac1*val - va = vp - term - vb = vp + term - # std is a Gaussian with mean sqrt(C) and variance C/(2*n) - st = sqrt(C) - fac2 = sqrt(0.5)*fac0 - term = fac2*val - sta = st - term - stb = st + term - return (mp, (ma, mb)), (vp, (va, vb)), (st, (sta, stb)) - - ## Assumes all is known is that mean, and std (variance,axis=0) exist ## and are the same for all the data. Uses Jeffrey's prior ## @@ -73,73 +47,51 @@ ## and std. def bayes_mvs(data, alpha=0.90): - """Return Bayesian confidence intervals for the mean, var, and std. + """Bayesian confidence intervals for the mean, var, and std. - Assumes 1-d data all has same mean and variance and uses Jeffrey's prior - for variance and std. + Parameters + ---------- + data : array-like + Converted to 1-d using ravel. Requires 2 or more data-points + alpha : float, optional + Probability that the returned confidence interval contains + the true parameter - alpha gives the probability that the returned confidence interval contains - the true parameter. + Returns + ------- + Returns a 3 output arguments for each of mean, variance, and standard deviation. + Each of the outputs is a pair: + (center, (lower, upper)) + with center the mean of the conditional pdf of the value given the data + and (lower, upper) is a confidence interval centered on the median, + containing the estimate to a probability alpha. + + mctr, (ma, mb) : + Estimates for mean + vctr, (va, vb) : + Estimates for variance + sctr, (sa, sb) : + Estimates for standard deviation + + Notes + ----- + Converts data to 1-d and assumes all data has the same mean and variance. + Uses Jeffrey's prior for variance and std. - Uses mean of conditional pdf as center estimate - (but centers confidence interval on the median) - - Returns (center, (a, b)) for each of mean, variance and standard deviation. - Requires 2 or more data-points. + Equivalent to tuple((x.mean(), x.interval(alpha)) for x in mvsdist(dat)) """ - x = ravel(data) - n = len(x) - if n < 2: - raise ValueError("data must contain at least two values.") + res = mvsdist(data) if alpha >= 1 or alpha <= 0: raise ValueError("0 < alpha < 1 is required, but alpha=%s was given." % alpha) - n = float(n) - if (n > 1000): # just a guess. The curves look very similar at this point. - return _gauss_mvs(x, n, alpha) - xbar = x.mean() - C = x.var() - # mean - fac = sqrt(C/(n-1)) - tval = distributions.t.ppf((1+alpha)/2.0,n-1) - delta = fac*tval - ma = xbar - delta - mb = xbar + delta - mp = xbar - # var - fac = n*C/2.0 - a = (n-1)/2 - if (n < 4): - peak = distributions.invgamma.ppf(0.5,a) - else: - peak = 2.0/(n-3.0) - q1 = (1-alpha)/2.0 - q2 = (1+alpha)/2.0 - va = fac*distributions.invgamma.ppf(q1,a) - vb = fac*distributions.invgamma.ppf(q2,a) - vp = peak*fac - # std - fac = sqrt(fac) - if (n < 3): - peak = distributions.gengamma.ppf(0.5,a,-2) - stp = fac*peak - else: - ndiv2 = (n-1)/2.0 - term = special.gammaln(ndiv2-0.5)-special.gammaln(ndiv2) - term += (log(n)+log(C)-log(2.0))*0.5 - stp = exp(term) - q1 = (1-alpha)/2.0 - q2 = (1+alpha)/2.0 - sta = fac*distributions.gengamma.ppf(q1,a,-2) - stb = fac*distributions.gengamma.ppf(q2,a,-2) + return tuple((x.mean(), x.interval(alpha)) for x in res) - return (mp,(ma,mb)),(vp,(va,vb)),(stp,(sta,stb)) - def mvsdist(data): - """Return 'frozen' distributions for mean, variance, and standard deviation of data. + """'frozen' distributions for mean, variance, and standard deviation of data. Parameters ---------- - data : array-like (raveled to 1-d) + data : array-like + Converted to 1-d using ravel. Requires 2 or more data-points Returns ------- @@ -149,6 +101,15 @@ Distribution object representing the variance of the data sdist : "frozen" distribution object Distribution object representing the standard deviation of the data + + Notes + ----- + The return values from bayes_mvs(data) is equivalent to + tuple((x.mean(), x.interval(0.90)) for x in mvsdist(data)) + + In other words, calling .mean() and .interval(0.90) on the + three distribution objects returned from this function will give the same + results that are returned from bayes_mvs """ x = ravel(data) n = len(x) From scipy-svn at scipy.org Thu Feb 10 03:57:59 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Thu, 10 Feb 2011 02:57:59 -0600 (CST) Subject: [Scipy-svn] r7130 - trunk/scipy/stats/tests Message-ID: <20110210085759.6301F1B8D55@scipy.org> Author: oliphant Date: 2011-02-10 02:57:59 -0600 (Thu, 10 Feb 2011) New Revision: 7130 Modified: trunk/scipy/stats/tests/test_distributions.py Log: Fix the test to correctly pass in the location and scale parameters to the moment method. Modified: trunk/scipy/stats/tests/test_distributions.py =================================================================== --- trunk/scipy/stats/tests/test_distributions.py 2011-02-10 08:42:03 UTC (rev 7129) +++ trunk/scipy/stats/tests/test_distributions.py 2011-02-10 08:57:59 UTC (rev 7130) @@ -491,7 +491,7 @@ assert_equal(result_f, result) result_f = frozen.moment(2) - result = dist.moment(2) + result = dist.moment(2,loc=10.0, scale=3.0) assert_equal(result_f, result) def test_gamma(self): From scipy-svn at scipy.org Thu Feb 10 03:58:58 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Thu, 10 Feb 2011 02:58:58 -0600 (CST) Subject: [Scipy-svn] r7131 - trunk/scipy/stats Message-ID: <20110210085858.51FB01B8D5C@scipy.org> Author: oliphant Date: 2011-02-10 02:58:58 -0600 (Thu, 10 Feb 2011) New Revision: 7131 Modified: trunk/scipy/stats/distributions.py Log: Fix documentation error. Fix location and scale arguments to moment method as well as a calculation with them. Modified: trunk/scipy/stats/distributions.py =================================================================== --- trunk/scipy/stats/distributions.py 2011-02-10 08:57:59 UTC (rev 7130) +++ trunk/scipy/stats/distributions.py 2011-02-10 08:58:58 UTC (rev 7131) @@ -217,7 +217,7 @@ """ _doc_interval = \ """interval(alpha, %(shapes)s, loc=0, scale=1) - Endpoints of the range that contains alpha % of the distribution + Endpoints of the range that contains alpha %% of the distribution """ _doc_allmethods = ''.join([docheaders['methods'], _doc_rvs, _doc_pdf, _doc_logpdf, _doc_cdf, _doc_logcdf, _doc_sf, @@ -1663,7 +1663,8 @@ scale parameter (default=1) """ - loc, scale = map(kwds.get,['loc','scale']) + loc = kwds.get('loc', 0) + scale = kwds.get('scale', 1) if not (self._argcheck(*args) and (scale > 0)): return nan if (floor(n) != n): @@ -1685,7 +1686,7 @@ return scale**n * val else: result = 0 - fac = scale / loc + fac = float(scale) / float(loc) for k in range(n): valk = _moment_from_stats(k, mu, mu2, g1, g2, self._munp, args) result += comb(n,k,exact=True)*(fac**k) * valk @@ -5590,7 +5591,8 @@ scale parameter (default=1) """ - loc, scale = map(kwds.get,['loc','scale']) + loc = kwds.get('loc', 0) + scale = kwds.get('scale', 1) if not (self._argcheck(*args) and (scale > 0)): return nan if (floor(n) != n): @@ -5612,7 +5614,7 @@ return scale**n * val else: result = 0 - fac = scale / loc + fac = float(scale) / float(loc) for k in range(n): valk = _moment_from_stats(k, mu, mu2, g1, g2, self._munp, args) result += comb(n,k,exact=True)*(fac**k) * valk From scipy-svn at scipy.org Thu Feb 10 09:36:29 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Thu, 10 Feb 2011 08:36:29 -0600 (CST) Subject: [Scipy-svn] r7132 - branches/0.9.x/scipy/io/matlab/tests Message-ID: <20110210143629.BD3591B8CB1@scipy.org> Author: rgommers Date: 2011-02-10 08:36:28 -0600 (Thu, 10 Feb 2011) New Revision: 7132 Modified: branches/0.9.x/scipy/io/matlab/tests/test_streams.py Log: TST: io: close file handle before unlinking, for win32 (#1379) Thanks to C. Gohlke for the patch. (backport of r7109) Modified: branches/0.9.x/scipy/io/matlab/tests/test_streams.py =================================================================== --- branches/0.9.x/scipy/io/matlab/tests/test_streams.py 2011-02-10 08:58:58 UTC (rev 7131) +++ branches/0.9.x/scipy/io/matlab/tests/test_streams.py 2011-02-10 14:36:28 UTC (rev 7132) @@ -43,6 +43,7 @@ def teardown(): global fname, fs + fs.close() del fs os.unlink(fname) From scipy-svn at scipy.org Thu Feb 10 09:36:50 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Thu, 10 Feb 2011 08:36:50 -0600 (CST) Subject: [Scipy-svn] r7133 - branches/0.9.x/scipy/ndimage/src Message-ID: <20110210143650.E38BD1B8D69@scipy.org> Author: rgommers Date: 2011-02-10 08:36:50 -0600 (Thu, 10 Feb 2011) New Revision: 7133 Modified: branches/0.9.x/scipy/ndimage/src/ni_support.c Log: BUG: Fix ndimage type checks, part of ticket #1724. (backport of r7120) Modified: branches/0.9.x/scipy/ndimage/src/ni_support.c =================================================================== --- branches/0.9.x/scipy/ndimage/src/ni_support.c 2011-02-10 14:36:28 UTC (rev 7132) +++ branches/0.9.x/scipy/ndimage/src/ni_support.c 2011-02-10 14:36:50 UTC (rev 7133) @@ -119,6 +119,41 @@ return 1; } +/* Some NumPy types are ambiguous */ +int NI_CanonicalType(int type_num) +{ + switch (type_num) { + case NPY_INT: + return NPY_INT32; + + case NPY_LONG: +#if NPY_SIZEOF_LONG == 4 + return NPY_INT32; +#else + return NPY_INT64; +#endif + + case NPY_LONGLONG: + return NPY_INT64; + + case NPY_UINT: + return NPY_UINT32; + + case NPY_ULONG: +#if NPY_SIZEOF_LONG == 4 + return NPY_UINT32; +#else + return NPY_UINT64; +#endif + + case NPY_ULONGLONG: + return NPY_UINT64; + + default: + return type_num; + } +} + /* Initialize a line buffer */ int NI_InitLineBuffer(PyArrayObject *array, int axis, npy_intp size1, npy_intp size2, npy_intp buffer_lines, double *buffer_data, @@ -147,7 +182,7 @@ buffer->array_data = (void *)PyArray_DATA(array); buffer->buffer_data = buffer_data; buffer->buffer_lines = buffer_lines; - buffer->array_type = array->descr->type_num; + buffer->array_type = NI_CanonicalType(PyArray_DESCR(array)->type_num); buffer->array_lines = array_lines; buffer->next_line = 0; buffer->size1 = size1; From scipy-svn at scipy.org Thu Feb 10 09:37:14 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Thu, 10 Feb 2011 08:37:14 -0600 (CST) Subject: [Scipy-svn] r7134 - branches/0.9.x/scipy/optimize/tests Message-ID: <20110210143714.9B3921B8D6A@scipy.org> Author: rgommers Date: 2011-02-10 08:37:14 -0600 (Thu, 10 Feb 2011) New Revision: 7134 Modified: branches/0.9.x/scipy/optimize/tests/test_linesearch.py branches/0.9.x/scipy/optimize/tests/test_optimize.py Log: TST: optimize: add some leeway for additional FP rounding error For instance, if arrays happen to be not aligned on 16-byte boundaries when using MKL, this produces additional (insignificant) rounding error. The tests should allow for this. (backport of r7121) Modified: branches/0.9.x/scipy/optimize/tests/test_linesearch.py =================================================================== --- branches/0.9.x/scipy/optimize/tests/test_linesearch.py 2011-02-10 14:36:50 UTC (rev 7133) +++ branches/0.9.x/scipy/optimize/tests/test_linesearch.py 2011-02-10 14:37:14 UTC (rev 7134) @@ -2,7 +2,8 @@ Tests for line search routines """ -from numpy.testing import assert_, assert_equal, assert_array_almost_equal +from numpy.testing import assert_, assert_equal, \ + assert_array_almost_equal, assert_array_almost_equal_nulp import scipy.optimize.linesearch as ls import numpy as np @@ -36,6 +37,12 @@ def assert_line_armijo(x, p, s, f, **kw): assert_armijo(s, phi=lambda sp: f(x + p*sp), **kw) +def assert_fp_equal(x, y, err_msg="", nulp=50): + """Assert two arrays are equal, up to some floating-point rounding error""" + try: + assert_array_almost_equal_nulp(x, y, nulp) + except AssertionError, e: + raise AssertionError("%s\n%s" % (e, err_msg)) class TestLineSearch(object): # -- scalar functions; must have dphi(0.) < 0 @@ -123,8 +130,8 @@ c += 1 s, phi1, phi0 = ls.scalar_search_wolfe1(phi, derphi, phi(0), old_phi0, derphi(0)) - assert_equal(phi0, phi(0), name) - assert_equal(phi1, phi(s), name) + assert_fp_equal(phi0, phi(0), name) + assert_fp_equal(phi1, phi(s), name) assert_wolfe(s, phi, derphi, err_msg=name) assert_(c > 3) # check that the iterator really works... @@ -133,16 +140,16 @@ for name, phi, derphi, old_phi0 in self.scalar_iter(): s, phi1, phi0, derphi1 = ls.scalar_search_wolfe2( phi, derphi, phi(0), old_phi0, derphi(0)) - assert_equal(phi0, phi(0), name) - assert_equal(phi1, phi(s), name) + assert_fp_equal(phi0, phi(0), name) + assert_fp_equal(phi1, phi(s), name) if derphi1 is not None: - assert_equal(derphi1, derphi(s), name) + assert_fp_equal(derphi1, derphi(s), name) assert_wolfe(s, phi, derphi, err_msg="%s %g" % (name, old_phi0)) def test_scalar_search_armijo(self): for name, phi, derphi, old_phi0 in self.scalar_iter(): s, phi1 = ls.scalar_search_armijo(phi, phi(0), derphi(0)) - assert_equal(phi1, phi(s), name) + assert_fp_equal(phi1, phi(s), name) assert_armijo(s, phi, err_msg="%s %g" % (name, old_phi0)) # -- Generic line searches @@ -158,10 +165,10 @@ g0, f0, old_f, amax=smax) assert_equal(self.fcount, fc+gc) - assert_equal(ofv, f(x)) + assert_fp_equal(ofv, f(x)) if s is None: continue - assert_equal(fv, f(x + s*p)) + assert_fp_equal(fv, f(x + s*p)) assert_array_almost_equal(gv, fprime(x + s*p), decimal=14) if s < smax: c += 1 @@ -180,8 +187,8 @@ g0, f0, old_f, amax=smax) assert_equal(self.fcount, fc+gc) - assert_equal(ofv, f(x)) - assert_equal(fv, f(x + s*p)) + assert_fp_equal(ofv, f(x)) + assert_fp_equal(fv, f(x + s*p)) if gv is not None: assert_array_almost_equal(gv, fprime(x + s*p), decimal=14) if s < smax: @@ -198,7 +205,7 @@ s, fc, fv = ls.line_search_armijo(f, x, p, g0, f0) c += 1 assert_equal(self.fcount, fc) - assert_equal(fv, f(x + s*p)) + assert_fp_equal(fv, f(x + s*p)) assert_line_armijo(x, p, s, f, err_msg=name) assert_(c >= 9) Modified: branches/0.9.x/scipy/optimize/tests/test_optimize.py =================================================================== --- branches/0.9.x/scipy/optimize/tests/test_optimize.py 2011-02-10 14:36:50 UTC (rev 7133) +++ branches/0.9.x/scipy/optimize/tests/test_optimize.py 2011-02-10 14:37:14 UTC (rev 7134) @@ -120,7 +120,14 @@ # Ensure that function call counts are 'known good'; these are from # Scipy 0.7.0. Don't allow them to increase. - assert_(self.funccalls == 116, self.funccalls) + # + # However, some leeway must be added: the exact evaluation + # count is sensitive to numerical error, and floating-point + # computations are not bit-for-bit reproducible across + # machines, and when using e.g. MKL, data alignment + # etc. affect the rounding error. + # + assert_(self.funccalls <= 116 + 20, self.funccalls) assert_(self.gradcalls == 0, self.gradcalls) # Ensure that the function behaves the same; this is from Scipy 0.7.0 From scipy-svn at scipy.org Thu Feb 10 09:37:40 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Thu, 10 Feb 2011 08:37:40 -0600 (CST) Subject: [Scipy-svn] r7135 - branches/0.9.x/scipy/io Message-ID: <20110210143740.7CA451B8D6B@scipy.org> Author: rgommers Date: 2011-02-10 08:37:40 -0600 (Thu, 10 Feb 2011) New Revision: 7135 Modified: branches/0.9.x/scipy/io/idl.py Log: BUG: io.idl: Fix readsav() on Python 2.4 (backport of r7122) Modified: branches/0.9.x/scipy/io/idl.py =================================================================== --- branches/0.9.x/scipy/io/idl.py 2011-02-10 14:37:14 UTC (rev 7134) +++ branches/0.9.x/scipy/io/idl.py 2011-02-10 14:37:40 UTC (rev 7135) @@ -291,7 +291,7 @@ # Reshape array if needed if array_desc['ndims'] > 1: - dims = array_desc['dims'][:array_desc['ndims']] + dims = array_desc['dims'][:int(array_desc['ndims'])] dims.reverse() array = array.reshape(dims) From scipy-svn at scipy.org Thu Feb 10 09:38:05 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Thu, 10 Feb 2011 08:38:05 -0600 (CST) Subject: [Scipy-svn] r7136 - in branches/0.9.x/scipy: interpolate/tests special/tests stats/tests Message-ID: <20110210143805.4B57E1B8D6C@scipy.org> Author: rgommers Date: 2011-02-10 08:38:04 -0600 (Thu, 10 Feb 2011) New Revision: 7136 Modified: branches/0.9.x/scipy/interpolate/tests/test_rbf.py branches/0.9.x/scipy/special/tests/test_data.py branches/0.9.x/scipy/stats/tests/test_continuous_basic.py Log: TST: Use np.seterr in test generators in Python2.4 compatible way The seterr should be called in the test routine itself and not in the test generator. (backport of r7123) Modified: branches/0.9.x/scipy/interpolate/tests/test_rbf.py =================================================================== --- branches/0.9.x/scipy/interpolate/tests/test_rbf.py 2011-02-10 14:37:40 UTC (rev 7135) +++ branches/0.9.x/scipy/interpolate/tests/test_rbf.py 2011-02-10 14:38:04 UTC (rev 7136) @@ -12,59 +12,71 @@ def check_rbf1d_interpolation(function): """Check that the Rbf function interpolates throught the nodes (1D)""" - x = linspace(0,10,9) - y = sin(x) - rbf = Rbf(x, y, function=function) - yi = rbf(x) - assert_array_almost_equal(y, yi) - assert_almost_equal(rbf(float(x[0])), y[0]) + olderr = np.seterr(all="ignore") + try: + x = linspace(0,10,9) + y = sin(x) + rbf = Rbf(x, y, function=function) + yi = rbf(x) + assert_array_almost_equal(y, yi) + assert_almost_equal(rbf(float(x[0])), y[0]) + finally: + np.seterr(**olderr) def check_rbf2d_interpolation(function): """Check that the Rbf function interpolates throught the nodes (2D)""" - x = random.rand(50,1)*4-2 - y = random.rand(50,1)*4-2 - z = x*exp(-x**2-1j*y**2) - rbf = Rbf(x, y, z, epsilon=2, function=function) - zi = rbf(x, y) - zi.shape = x.shape - assert_array_almost_equal(z, zi) + olderr = np.seterr(all="ignore") + try: + x = random.rand(50,1)*4-2 + y = random.rand(50,1)*4-2 + z = x*exp(-x**2-1j*y**2) + rbf = Rbf(x, y, z, epsilon=2, function=function) + zi = rbf(x, y) + zi.shape = x.shape + assert_array_almost_equal(z, zi) + finally: + np.seterr(**olderr) def check_rbf3d_interpolation(function): """Check that the Rbf function interpolates throught the nodes (3D)""" - x = random.rand(50,1)*4-2 - y = random.rand(50,1)*4-2 - z = random.rand(50,1)*4-2 - d = x*exp(-x**2-y**2) - rbf = Rbf(x, y, z, d, epsilon=2, function=function) - di = rbf(x, y, z) - di.shape = x.shape - assert_array_almost_equal(di, d) - -def test_rbf_interpolation(): olderr = np.seterr(all="ignore") try: - for function in FUNCTIONS: - yield check_rbf1d_interpolation, function - yield check_rbf2d_interpolation, function - yield check_rbf3d_interpolation, function + x = random.rand(50,1)*4-2 + y = random.rand(50,1)*4-2 + z = random.rand(50,1)*4-2 + d = x*exp(-x**2-y**2) + rbf = Rbf(x, y, z, d, epsilon=2, function=function) + di = rbf(x, y, z) + di.shape = x.shape + assert_array_almost_equal(di, d) finally: np.seterr(**olderr) +def test_rbf_interpolation(): + for function in FUNCTIONS: + yield check_rbf1d_interpolation, function + yield check_rbf2d_interpolation, function + yield check_rbf3d_interpolation, function + def check_rbf1d_regularity(function, atol): """Check that the Rbf function approximates a smooth function well away from the nodes.""" - x = linspace(0, 10, 9) - y = sin(x) - rbf = Rbf(x, y, function=function) - xi = linspace(0, 10, 100) - yi = rbf(xi) - #import matplotlib.pyplot as plt - #plt.figure() - #plt.plot(x, y, 'o', xi, sin(xi), ':', xi, yi, '-') - #plt.title(function) - #plt.show() - msg = "abs-diff: %f" % abs(yi - sin(xi)).max() - assert_(allclose(yi, sin(xi), atol=atol), msg) + olderr = np.seterr(all="ignore") + try: + x = linspace(0, 10, 9) + y = sin(x) + rbf = Rbf(x, y, function=function) + xi = linspace(0, 10, 100) + yi = rbf(xi) + #import matplotlib.pyplot as plt + #plt.figure() + #plt.plot(x, y, 'o', xi, sin(xi), ':', xi, yi, '-') + #plt.title(function) + #plt.show() + msg = "abs-diff: %f" % abs(yi - sin(xi)).max() + assert_(allclose(yi, sin(xi), atol=atol), msg) + finally: + np.seterr(**olderr) def test_rbf_regularity(): tolerances = { @@ -76,12 +88,8 @@ 'thin-plate': 0.1, 'linear': 0.2 } - olderr = np.seterr(all="ignore") - try: - for function in FUNCTIONS: - yield check_rbf1d_regularity, function, tolerances.get(function, 1e-2) - finally: - np.seterr(**olderr) + for function in FUNCTIONS: + yield check_rbf1d_regularity, function, tolerances.get(function, 1e-2) def test_default_construction(): """Check that the Rbf class can be constructed with the default Modified: branches/0.9.x/scipy/special/tests/test_data.py =================================================================== --- branches/0.9.x/scipy/special/tests/test_data.py 2011-02-10 14:37:40 UTC (rev 7135) +++ branches/0.9.x/scipy/special/tests/test_data.py 2011-02-10 14:38:04 UTC (rev 7136) @@ -206,13 +206,13 @@ # tgamma_ratio_data.txt ] + for test in TESTS: + yield _test_factory, test + +def _test_factory(test, dtype=np.double): + """Boost test""" olderr = np.seterr(all='ignore') try: - for test in TESTS: - yield _test_factory, test + test.check(dtype=dtype) finally: np.seterr(**olderr) - -def _test_factory(test, dtype=np.double): - """Boost test""" - test.check(dtype=dtype) Modified: branches/0.9.x/scipy/stats/tests/test_continuous_basic.py =================================================================== --- branches/0.9.x/scipy/stats/tests/test_continuous_basic.py 2011-02-10 14:37:40 UTC (rev 7135) +++ branches/0.9.x/scipy/stats/tests/test_continuous_basic.py 2011-02-10 14:38:04 UTC (rev 7136) @@ -156,43 +156,48 @@ 'powerlognorm', 'johnsonsu', 'kstwobign'] #distslow are sorted by speed (very slow to slow) +def _silence_fp_errors(func): + def wrap(*a, **kw): + olderr = np.seterr(all='ignore') + try: + return func(*a, **kw) + finally: + np.seterr(**olderr) + wrap.__name__ = func.__name__ + return wrap + def test_cont_basic(): # this test skips slow distributions - olderr = np.seterr(all='ignore') - try: - for distname, arg in distcont[:]: - if distname in distslow: - continue - distfn = getattr(stats, distname) - np.random.seed(765456) - sn = 1000 - rvs = distfn.rvs(size=sn,*arg) - sm = rvs.mean() - sv = rvs.var() - skurt = stats.kurtosis(rvs) - sskew = stats.skew(rvs) - m,v = distfn.stats(*arg) + for distname, arg in distcont[:]: + if distname in distslow: + continue + distfn = getattr(stats, distname) + np.random.seed(765456) + sn = 1000 + rvs = distfn.rvs(size=sn,*arg) + sm = rvs.mean() + sv = rvs.var() + skurt = stats.kurtosis(rvs) + sskew = stats.skew(rvs) + m,v = distfn.stats(*arg) - yield check_sample_meanvar_, distfn, arg, m, v, sm, sv, sn, distname + \ - 'sample mean test' - # the sample skew kurtosis test has known failures, not very good distance measure - #yield check_sample_skew_kurt, distfn, arg, sskew, skurt, distname - yield check_moment, distfn, arg, m, v, distname - yield check_cdf_ppf, distfn, arg, distname - yield check_sf_isf, distfn, arg, distname - yield check_pdf, distfn, arg, distname - if distname in ['wald']: - continue - yield check_pdf_logpdf, distfn, arg, distname - yield check_cdf_logcdf, distfn, arg, distname - yield check_sf_logsf, distfn, arg, distname - if distname in distmissing: - alpha = 0.01 - yield check_distribution_rvs, distname, arg, alpha, rvs - finally: - np.seterr(**olderr) + yield check_sample_meanvar_, distfn, arg, m, v, sm, sv, sn, distname + \ + 'sample mean test' + # the sample skew kurtosis test has known failures, not very good distance measure + #yield check_sample_skew_kurt, distfn, arg, sskew, skurt, distname + yield check_moment, distfn, arg, m, v, distname + yield check_cdf_ppf, distfn, arg, distname + yield check_sf_isf, distfn, arg, distname + yield check_pdf, distfn, arg, distname + if distname in ['wald']: + continue + yield check_pdf_logpdf, distfn, arg, distname + yield check_cdf_logcdf, distfn, arg, distname + yield check_sf_logsf, distfn, arg, distname + if distname in distmissing: + alpha = 0.01 + yield check_distribution_rvs, distname, arg, alpha, rvs - @npt.dec.slow def test_cont_basic_slow(): # same as above for slow distributions @@ -223,6 +228,7 @@ alpha = 0.01 yield check_distribution_rvs, distname, arg, alpha, rvs + at _silence_fp_errors def check_moment(distfn, arg, m, v, msg): m1 = distfn.moment(1,*arg) m2 = distfn.moment(2,*arg) @@ -241,6 +247,7 @@ msg + ' - 2nd moment -infinite, m2=%s' % str(m2)) #np.isnan(m2) temporary special treatment for loggamma + at _silence_fp_errors def check_sample_meanvar_(distfn, arg, m, v, sm, sv, sn, msg): #this did not work, skipped silently by nose #check_sample_meanvar, sm, m, msg + 'sample mean test' @@ -296,11 +303,13 @@ ## else: ## assert abs(sm) > 10000, 'infinite moment, sm = ' + str(sm) + at _silence_fp_errors def check_cdf_ppf(distfn,arg,msg): npt.assert_almost_equal(distfn.cdf(distfn.ppf([0.001,0.5,0.999], *arg), *arg), [0.001,0.5,0.999], decimal=DECIMAL, err_msg= msg + \ ' - cdf-ppf roundtrip') + at _silence_fp_errors def check_sf_isf(distfn,arg,msg): npt.assert_almost_equal(distfn.sf(distfn.isf([0.1,0.5,0.9], *arg), *arg), [0.1,0.5,0.9], decimal=DECIMAL, err_msg= msg + \ @@ -310,6 +319,7 @@ decimal=DECIMAL, err_msg= msg + \ ' - cdf-sf relationship') + at _silence_fp_errors def check_pdf(distfn, arg, msg): # compares pdf at median with numerical derivative of cdf median = distfn.ppf(0.5, *arg) @@ -326,6 +336,7 @@ npt.assert_almost_equal(pdfv, cdfdiff, decimal=DECIMAL, err_msg= msg + ' - cdf-pdf relationship') + at _silence_fp_errors def check_pdf_logpdf(distfn, args, msg): # compares pdf at several points with the log of the pdf points = np.array([0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8]) @@ -336,6 +347,7 @@ logpdf = logpdf[np.isfinite(logpdf)] npt.assert_almost_equal(np.log(pdf), logpdf, decimal=7, err_msg=msg + " - logpdf-log(pdf) relationship") + at _silence_fp_errors def check_sf_logsf(distfn, args, msg): # compares sf at several points with the log of the sf points = np.array([0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8]) @@ -346,6 +358,7 @@ logsf = logsf[np.isfinite(logsf)] npt.assert_almost_equal(np.log(sf), logsf, decimal=7, err_msg=msg + " - logsf-log(sf) relationship") + at _silence_fp_errors def check_cdf_logcdf(distfn, args, msg): # compares cdf at several points with the log of the cdf points = np.array([0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8]) @@ -357,6 +370,7 @@ npt.assert_almost_equal(np.log(cdf), logcdf, decimal=7, err_msg=msg + " - logcdf-log(cdf) relationship") + at _silence_fp_errors def check_distribution_rvs(dist, args, alpha, rvs): #test from scipy.stats.tests #this version reuses existing random variables From scipy-svn at scipy.org Thu Feb 10 13:01:12 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Thu, 10 Feb 2011 12:01:12 -0600 (CST) Subject: [Scipy-svn] r7137 - trunk/scipy/stats Message-ID: <20110210180112.044923233A@scipy.org> Author: oliphant Date: 2011-02-10 12:01:11 -0600 (Thu, 10 Feb 2011) New Revision: 7137 Modified: trunk/scipy/stats/distributions.py Log: Add additional method docs to the class docstring for rv_continuous and rv_discrete. Modified: trunk/scipy/stats/distributions.py =================================================================== --- trunk/scipy/stats/distributions.py 2011-02-10 14:38:04 UTC (rev 7136) +++ trunk/scipy/stats/distributions.py 2011-02-10 18:01:11 UTC (rev 7137) @@ -842,7 +842,7 @@ Parameters ---------- momtype : int, optional - The type of generic moment calculation to use (check this). + The type of generic moment calculation to use: 0 for pdf, 1 (default) for ppf. a : float, optional Lower bound of the support of the distribution, default is minus infinity. @@ -869,7 +869,7 @@ The shape of the distribution. For example ``"m, n"`` for a distribution that takes two integers as the two shape arguments for all its methods. - extradoc : str, optional + extradoc : str, optional, deprecated This string is used as the last part of the docstring returned when a subclass has no docstring of its own. Note: `extradoc` exists for backwards compatibility, do not use for new subclasses. @@ -882,20 +882,29 @@ pdf(x, , loc=0, scale=1) probability density function + logpdf(x, , loc=0, scale=1) + log of the probability density function + cdf(x, , loc=0, scale=1) cumulative density function + logcdf(x, , loc=0, scale=1) + log of the cumulative density function + sf(x, , loc=0, scale=1) survival function (1-cdf --- sometimes more accurate) + logsf(x, , loc=0, scale=1) + log of the survival function + ppf(q, , loc=0, scale=1) percent point function (inverse of cdf --- quantiles) isf(q, , loc=0, scale=1) inverse survival function (inverse of sf) - moments(n, ) - non-central n-th moment of the standard distribution (oc=0, scale=1) + moment(n, , loc=0, scale=1) + non-central n-th moment of the distribution. May not work for array arguments. stats(, loc=0, scale=1, moments='mv') mean('m'), variance('v'), skew('s'), and/or kurtosis('k') @@ -906,6 +915,27 @@ fit(data, , loc=0, scale=1) Parameter estimates for generic data + expect(func=None, args=(), loc=0, scale=1, lb=None, ub=None, + conditional=False, **kwds) + Expected value of a function with respect to the distribution. + Additional kwd arguments passed to integrate.quad + + median(, loc=0, scale=1) + Median of the distribution. + + mean(, loc=0, scale=1) + Mean of the distribution. + + std(, loc=0, scale=1) + Standard deviation of the distribution. + + var(, loc=0, scale=1) + Variance of the distribution. + + interval(alpha, , loc=0, scale=1) + Interval that with (alpha)% probability contains a random realization + of this distribution. + __call__(, loc=0, scale=1) calling a distribution instance creates a frozen RV object with the same methods but holding the given shape, location, and scale fixed. @@ -4867,24 +4897,59 @@ generic.pmf(x, , loc=0) probability mass function + logpmf(x, , loc=0) + log of the probability density function + generic.cdf(x, , loc=0) cumulative density function + generic.logcdf(x, , loc=0) + log of the cumulative density function + generic.sf(x, , loc=0) survival function (1-cdf --- sometimes more accurate) + generic.logsf(x, , loc=0, scale=1) + log of the survival function + generic.ppf(q, , loc=0) percent point function (inverse of cdf --- percentiles) generic.isf(q, , loc=0) inverse survival function (inverse of sf) + generic.moment(n, , loc=0) + non-central n-th moment of the distribution. May not work for array arguments. + generic.stats(, loc=0, moments='mv') mean('m', axis=0), variance('v'), skew('s'), and/or kurtosis('k') generic.entropy(, loc=0) entropy of the RV + generic.fit(data, , loc=0) + Parameter estimates for generic data + + generic.expect(func=None, args=(), loc=0, lb=None, ub=None, conditional=False) + Expected value of a function with respect to the distribution. + Additional kwd arguments passed to integrate.quad + + generic.median(, loc=0) + Median of the distribution. + + generic.mean(, loc=0) + Mean of the distribution. + + generic.std(, loc=0) + Standard deviation of the distribution. + + generic.var(, loc=0) + Variance of the distribution. + + generic.interval(alpha, , loc=0) + Interval that with (alpha)% probability contains a random realization + of this distribution. + generic(, loc=0) calling a distribution instance returns a frozen distribution From scipy-svn at scipy.org Sat Feb 12 05:55:24 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sat, 12 Feb 2011 04:55:24 -0600 (CST) Subject: [Scipy-svn] r7138 - branches/0.9.x/doc/release Message-ID: <20110212105524.CC3C51B8DB4@scipy.org> Author: rgommers Date: 2011-02-12 04:55:23 -0600 (Sat, 12 Feb 2011) New Revision: 7138 Modified: branches/0.9.x/doc/release/0.9.0-notes.rst Log: DOC: Add note on upcoming transition to git in 0.9.0 release notes. Modified: branches/0.9.x/doc/release/0.9.0-notes.rst =================================================================== --- branches/0.9.x/doc/release/0.9.0-notes.rst 2011-02-10 18:01:11 UTC (rev 7137) +++ branches/0.9.x/doc/release/0.9.0-notes.rst 2011-02-12 10:55:23 UTC (rev 7138) @@ -38,6 +38,16 @@ that is not yet ported is ``scipy.weave``. +Scipy source code location to be changed +======================================== + +Soon after this release, Scipy will stop using SVN as the version control +system, and move to Git. The development source code for Scipy can from then on +be found at + + http://github.com/scipy/scipy + + New features ============ From scipy-svn at scipy.org Sat Feb 12 05:56:01 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sat, 12 Feb 2011 04:56:01 -0600 (CST) Subject: [Scipy-svn] r7139 - branches/0.9.x Message-ID: <20110212105601.D5078363BA@scipy.org> Author: rgommers Date: 2011-02-12 04:56:01 -0600 (Sat, 12 Feb 2011) New Revision: 7139 Modified: branches/0.9.x/setup.py Log: REL: set version number to 0.9.0rc3. Modified: branches/0.9.x/setup.py =================================================================== --- branches/0.9.x/setup.py 2011-02-12 10:55:23 UTC (rev 7138) +++ branches/0.9.x/setup.py 2011-02-12 10:56:01 UTC (rev 7139) @@ -46,7 +46,7 @@ MINOR = 9 MICRO = 0 ISRELEASED = True -VERSION = '%d.%d.%drc2' % (MAJOR, MINOR, MICRO) +VERSION = '%d.%d.%drc3' % (MAJOR, MINOR, MICRO) # BEFORE importing distutils, remove MANIFEST. distutils doesn't properly # update it when the contents of directories change. From scipy-svn at scipy.org Sat Feb 12 05:58:52 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sat, 12 Feb 2011 04:58:52 -0600 (CST) Subject: [Scipy-svn] r7140 - tags Message-ID: <20110212105852.C80BD1B8DB6@scipy.org> Author: rgommers Date: 2011-02-12 04:58:52 -0600 (Sat, 12 Feb 2011) New Revision: 7140 Added: tags/0.9.0rc3/ Log: Create tag 0.9.0rc3 From scipy-svn at scipy.org Sat Feb 12 23:48:41 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sat, 12 Feb 2011 22:48:41 -0600 (CST) Subject: [Scipy-svn] r7141 - in trunk: doc/source/tutorial scipy/signal scipy/signal/tests Message-ID: <20110213044841.5F24837BA54@scipy.org> Author: rgommers Date: 2011-02-12 22:48:40 -0600 (Sat, 12 Feb 2011) New Revision: 7141 Added: trunk/scipy/signal/spectral.c trunk/scipy/signal/spectral.pyx trunk/scipy/signal/tests/test_spectral.py Modified: trunk/doc/source/tutorial/signal.rst trunk/scipy/signal/SConscript trunk/scipy/signal/__init__.py trunk/scipy/signal/setup.py Log: ENH: Add Lomb-Scargle periodogram in new signal.spectral module. Thanks to Pim Schellart for this contribution. Modified: trunk/doc/source/tutorial/signal.rst =================================================================== --- trunk/doc/source/tutorial/signal.rst 2011-02-12 10:58:52 UTC (rev 7140) +++ trunk/doc/source/tutorial/signal.rst 2011-02-13 04:48:40 UTC (rev 7141) @@ -3,6 +3,10 @@ .. sectionauthor:: Travis E. Oliphant +.. sectionauthor:: Pim Schellart + +.. currentmodule:: scipy.signal + The signal processing toolbox currently contains some filtering functions, a limited set of filter design tools, and a few B-spline interpolation algorithms for one- and two-dimensional data. While the @@ -19,25 +23,29 @@ A B-spline is an approximation of a continuous function over a finite- domain in terms of B-spline coefficients and knot points. If the knot- -points are equally spaced with spacing :math:`\Delta x` , then the B-spline approximation to a 1-dimensional function is the -finite-basis expansion. +points are equally spaced with spacing :math:`\Delta x` , then the B-spline +approximation to a 1-dimensional function is the finite-basis expansion. .. math:: :nowrap: \[ y\left(x\right)\approx\sum_{j}c_{j}\beta^{o}\left(\frac{x}{\Delta x}-j\right).\] -In two dimensions with knot-spacing :math:`\Delta x` and :math:`\Delta y` , the function representation is +In two dimensions with knot-spacing :math:`\Delta x` and :math:`\Delta y` , the +function representation is .. math:: :nowrap: \[ z\left(x,y\right)\approx\sum_{j}\sum_{k}c_{jk}\beta^{o}\left(\frac{x}{\Delta x}-j\right)\beta^{o}\left(\frac{y}{\Delta y}-k\right).\] -In these expressions, :math:`\beta^{o}\left(\cdot\right)` is the space-limited B-spline basis function of order, :math:`o` . The requirement of equally-spaced knot-points and equally-spaced -data points, allows the development of fast (inverse-filtering) -algorithms for determining the coefficients, :math:`c_{j}` , from sample-values, :math:`y_{n}` . Unlike the general spline interpolation algorithms, these algorithms -can quickly find the spline coefficients for large images. +In these expressions, :math:`\beta^{o}\left(\cdot\right)` is the space-limited +B-spline basis function of order, :math:`o` . The requirement of equally-spaced +knot-points and equally-spaced data points, allows the development of fast +(inverse-filtering) algorithms for determining the coefficients, :math:`c_{j}` +, from sample-values, :math:`y_{n}` . Unlike the general spline interpolation +algorithms, these algorithms can quickly find the spline coefficients for large +images. The advantage of representing a set of samples via B-spline basis functions is that continuous-domain operators (derivatives, re- @@ -179,7 +187,9 @@ In this case, the matrix multiplication can be accomplished using Fourier transforms. -Let :math:`x\left[n\right]` define a one-dimensional signal indexed by the integer :math:`n.` Full convolution of two one-dimensional signals can be expressed as +Let :math:`x\left[n\right]` define a one-dimensional signal indexed by the +integer :math:`n.` Full convolution of two one-dimensional signals can be +expressed as .. math:: :nowrap: @@ -199,14 +209,17 @@ \[ y\left[n\right]=\sum_{k=\max\left(n-M,0\right)}^{\min\left(n,K\right)}x\left[k\right]h\left[n-k\right].\] -For convenience assume :math:`K\geq M.` Then, more explicitly the output of this operation is +For convenience assume :math:`K\geq M.` Then, more explicitly the output of +this operation is .. math:: :nowrap: \begin{eqnarray*} y\left[0\right] & = & x\left[0\right]h\left[0\right]\\ y\left[1\right] & = & x\left[0\right]h\left[1\right]+x\left[1\right]h\left[0\right]\\ y\left[2\right] & = & x\left[0\right]h\left[2\right]+x\left[1\right]h\left[1\right]+x\left[2\right]h\left[0\right]\\ \vdots & \vdots & \vdots\\ y\left[M\right] & = & x\left[0\right]h\left[M\right]+x\left[1\right]h\left[M-1\right]+\cdots+x\left[M\right]h\left[0\right]\\ y\left[M+1\right] & = & x\left[1\right]h\left[M\right]+x\left[2\right]h\left[M-1\right]+\cdots+x\left[M+1\right]h\left[0\right]\\ \vdots & \vdots & \vdots\\ y\left[K\right] & = & x\left[K-M\right]h\left[M\right]+\cdots+x\left[K\right]h\left[0\right]\\ y\left[K+1\right] & = & x\left[K+1-M\right]h\left[M\right]+\cdots+x\left[K\right]h\left[1\right]\\ \vdots & \vdots & \vdots\\ y\left[K+M-1\right] & = & x\left[K-1\right]h\left[M\right]+x\left[K\right]h\left[M-1\right]\\ y\left[K+M\right] & = & x\left[K\right]h\left[M\right].\end{eqnarray*} -Thus, the full discrete convolution of two finite sequences of lengths :math:`K+1` and :math:`M+1` respectively results in a finite sequence of length :math:`K+M+1=\left(K+1\right)+\left(M+1\right)-1.` +Thus, the full discrete convolution of two finite sequences of lengths +:math:`K+1` and :math:`M+1` respectively results in a finite sequence of length +:math:`K+M+1=\left(K+1\right)+\left(M+1\right)-1.` One dimensional convolution is implemented in SciPy with the function ``signal.convolve`` . This function takes as inputs the signals @@ -237,7 +250,10 @@ \[ w\left[n\right]=\sum_{k=-\infty}^{\infty}y\left[k\right]x\left[n+k\right]\] -is the (cross) correlation of the signals :math:`y` and :math:`x.` For finite-length signals with :math:`y\left[n\right]=0` outside of the range :math:`\left[0,K\right]` and :math:`x\left[n\right]=0` outside of the range :math:`\left[0,M\right],` the summation can simplify to +is the (cross) correlation of the signals :math:`y` and :math:`x.` For +finite-length signals with :math:`y\left[n\right]=0` outside of the range +:math:`\left[0,K\right]` and :math:`x\left[n\right]=0` outside of the range +:math:`\left[0,M\right],` the summation can simplify to .. math:: :nowrap: @@ -299,7 +315,8 @@ :math:`y\left[n\right]` for :math:`n<0` resulting in a filter that cannot be expressed using convolution. -The difference equation filter can be thought of as finding :math:`y\left[n\right]` recursively in terms of it's previous values +The difference equation filter can be thought of as finding +:math:`y\left[n\right]` recursively in terms of it's previous values .. math:: :nowrap: @@ -352,7 +369,10 @@ \[ z_{m}\left[n\right]=\sum_{p=0}^{K-m-1}\left(b_{m+p+1}x\left[n-p\right]-a_{m+p+1}y\left[n-p\right]\right).\] -Using this formula we can find the intial condition vector :math:`z_{0}\left[-1\right]` to :math:`z_{K-1}\left[-1\right]` given initial conditions on :math:`y` (and :math:`x` ). The command :obj:`signal.lfiltic` performs this function. +Using this formula we can find the intial condition vector +:math:`z_{0}\left[-1\right]` to :math:`z_{K-1}\left[-1\right]` given initial +conditions on :math:`y` (and :math:`x` ). The command :obj:`signal.lfiltic` +performs this function. Other filters @@ -433,8 +453,83 @@ \[ Y=X\cdot H\] -where :math:`H` is 2 for positive frequencies, :math:`0` for negative frequencies and :math:`1` for zero-frequencies. +where :math:`H` is 2 for positive frequencies, :math:`0` for negative +frequencies and :math:`1` for zero-frequencies. + +Least-Squares Spectral Analysis (:mod:`spectral`) +------------------------------------------------- + +Least-squares spectral analysis (LSSA) is a method of estimating a frequency +spectrum, based on a least squares fit of sinusoids to data samples, similar to +Fourier analysis. Fourier analysis, the most used spectral method in science, +generally boosts long-periodic noise in long gapped records; LSSA mitigates +such problems. + + +Lomb-Scargle Periodograms (:func:`spectral.lombscargle`) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +The Lomb-Scargle method performs spectral analysis on unevenly sampled data and +is known to be a powerful way to find, and test the significance of, weak +periodic signals. + +For a time series comprising :math:`N_{t}` measurements +:math:`X_{j}\equiv X(t_{j})` sampled at times :math:`t_{j}` where +:math:`(j = 1, \ldots, N_{t})`, assumed to have been scaled and shifted +such that its mean is zero and its variance is unity, the normalized +Lomb-Scargle periodogram at frequency :math:`f` is + +.. math:: + + P_{n}(f) \frac{1}{2}\left\{\frac{\left[\sum_{j}^{N_{t}}X_{j}\cos\omega(t_{j}-\tau)\right]^{2}}{\sum_{j}^{N_{t}}\cos^{2}\omega(t_{j}-\tau)}+\frac{\left[\sum_{j}^{N_{t}}X_{j}\sin\omega(t_{j}-\tau)\right]^{2}}{\sum_{j}^{N_{t}}\sin^{2}\omega(t_{j}-\tau)}\right\}. + +Here, :math:`\omega \equiv 2\pi f` is the angular frequency. +The frequency dependent time offset :math:`\tau` is given by + +.. math:: + + \tan 2\omega\tau = \frac{\sum_{j}^{N_{t}}\sin 2\omega t_{j}}{\sum_{j}^{N_{t}}\cos 2\omega t_{j}}. + +The :func:`~scipy.signal.spectral.lombscargle` function +calculates the periodogram using a slightly +modified algorithm due to Townsend [3]_ which allows the +periodogram to be calculated using only a single pass through +the input arrays for each frequency. + +The equation is refactored as: + +.. math:: + + P_{n}(f) = \frac{1}{2}\left[\frac{(c_{\tau}XC + s_{\tau}XS)^{2}}{c_{\tau}^{2}CC + 2c_{\tau}s_{\tau}CS + s_{\tau}^{2}SS} + \frac{(c_{\tau}XS - s_{\tau}XC)^{2}}{c_{\tau}^{2}SS - 2c_{\tau}s_{\tau}CS + s_{\tau}^{2}CC}\right] + +and + +.. math:: + + \tan 2\omega\tau = \frac{2CS}{CC-SS}. + +Here, + +.. math:: + + c_{\tau} = \cos\omega\tau,\qquad s_{\tau} = \sin\omega\tau + +while the sums are + +.. math:: + + XC &= \sum_{j}^{N_{t}} X_{j}\cos\omega t_{j}\\ + XS &= \sum_{j}^{N_{t}} X_{j}\sin\omega t_{j}\\ + CC &= \sum_{j}^{N_{t}} \cos^{2}\omega t_{j}\\ + SS &= \sum_{j}^{N_{t}} \sin^{2}\omega t_{j}\\ + CS &= \sum_{j}^{N_{t}} \cos\omega t_{j}\sin\omega t_{j}. + +This requires :math:`N_{f}(2N_{t}+3)` trigonometric function +evaluations giving a factor of :math:`\sim 2` speed increase over the +straightforward implementation. + + .. XXX: TODO .. .. Detrend @@ -542,3 +637,20 @@ .. .. Tilbert transform .. ----------------- + + +.. rubric:: References + +Some further reading and related software: + +.. [1] N.R. Lomb "Least-squares frequency analysis of unequally spaced +data", Astrophysics and Space Science, vol 39, pp. 447-462, 1976 + +.. [2] J.D. Scargle "Studies in astronomical time series analysis. II - +Statistical aspects of spectral analysis of unevenly spaced data", +The Astrophysical Journal, vol 263, pp. 835-853, 1982 + +.. [3] R.H.D. Townsend, "Fast calculation of the Lomb-Scargle +periodogram using graphics processing units.", The Astrophysical +Journal Supplement Series, vol 191, pp. 247-253, 2010 + Modified: trunk/scipy/signal/SConscript =================================================================== --- trunk/scipy/signal/SConscript 2011-02-12 10:58:52 UTC (rev 7140) +++ trunk/scipy/signal/SConscript 2011-02-13 04:48:40 UTC (rev 7141) @@ -13,6 +13,8 @@ 'firfilter.c', \ 'medianfilter.c']) +env.NumpyPythonExtension('spectral', source='spectral.c') + env.NumpyPythonExtension('spline', source = ['splinemodule.c', 'S_bspline_util.c', 'D_bspline_util.c', 'C_bspline_util.c', Modified: trunk/scipy/signal/__init__.py =================================================================== --- trunk/scipy/signal/__init__.py 2011-02-12 10:58:52 UTC (rev 7140) +++ trunk/scipy/signal/__init__.py 2011-02-13 04:48:40 UTC (rev 7141) @@ -12,6 +12,7 @@ from ltisys import * from windows import * from signaltools import * +from spectral import * from wavelets import * __all__ = filter(lambda s:not s.startswith('_'),dir()) Modified: trunk/scipy/signal/setup.py =================================================================== --- trunk/scipy/signal/setup.py 2011-02-12 10:58:52 UTC (rev 7140) +++ trunk/scipy/signal/setup.py 2011-02-13 04:48:40 UTC (rev 7141) @@ -15,6 +15,8 @@ include_dirs=['.'] ) + config.add_extension('spectral', sources=['spectral.c']) + config.add_extension('spline', sources = ['splinemodule.c','S_bspline_util.c','D_bspline_util.c', 'C_bspline_util.c','Z_bspline_util.c','bspline_util.c'], Added: trunk/scipy/signal/spectral.c =================================================================== --- trunk/scipy/signal/spectral.c (rev 0) +++ trunk/scipy/signal/spectral.c 2011-02-13 04:48:40 UTC (rev 7141) @@ -0,0 +1,5108 @@ +/* Generated by Cython 0.12.1 on Sun Feb 13 12:00:22 2011 */ + +#define PY_SSIZE_T_CLEAN +#include "Python.h" +#include "structmember.h" +#ifndef Py_PYTHON_H + #error Python headers needed to compile C extensions, please install development version of Python. +#else + +#ifndef PY_LONG_LONG + #define PY_LONG_LONG LONG_LONG +#endif +#ifndef DL_EXPORT + #define DL_EXPORT(t) t +#endif +#if PY_VERSION_HEX < 0x02040000 + #define METH_COEXIST 0 + #define PyDict_CheckExact(op) (Py_TYPE(op) == &PyDict_Type) + #define PyDict_Contains(d,o) PySequence_Contains(d,o) +#endif + +#if PY_VERSION_HEX < 0x02050000 + typedef int Py_ssize_t; + #define PY_SSIZE_T_MAX INT_MAX + #define PY_SSIZE_T_MIN INT_MIN + #define PY_FORMAT_SIZE_T "" + #define PyInt_FromSsize_t(z) PyInt_FromLong(z) + #define PyInt_AsSsize_t(o) PyInt_AsLong(o) + #define PyNumber_Index(o) PyNumber_Int(o) + #define PyIndex_Check(o) PyNumber_Check(o) + #define PyErr_WarnEx(category, message, stacklevel) PyErr_Warn(category, message) +#endif + +#if PY_VERSION_HEX < 0x02060000 + #define Py_REFCNT(ob) (((PyObject*)(ob))->ob_refcnt) + #define Py_TYPE(ob) (((PyObject*)(ob))->ob_type) + #define Py_SIZE(ob) (((PyVarObject*)(ob))->ob_size) + #define PyVarObject_HEAD_INIT(type, size) \ + PyObject_HEAD_INIT(type) size, + #define PyType_Modified(t) + + typedef struct { + void *buf; + PyObject *obj; + Py_ssize_t len; + Py_ssize_t itemsize; + int readonly; + int ndim; + char *format; + Py_ssize_t *shape; + Py_ssize_t *strides; + Py_ssize_t *suboffsets; + void *internal; + } Py_buffer; + + #define PyBUF_SIMPLE 0 + #define PyBUF_WRITABLE 0x0001 + #define PyBUF_FORMAT 0x0004 + #define PyBUF_ND 0x0008 + #define PyBUF_STRIDES (0x0010 | PyBUF_ND) + #define PyBUF_C_CONTIGUOUS (0x0020 | PyBUF_STRIDES) + #define PyBUF_F_CONTIGUOUS (0x0040 | PyBUF_STRIDES) + #define PyBUF_ANY_CONTIGUOUS (0x0080 | PyBUF_STRIDES) + #define PyBUF_INDIRECT (0x0100 | PyBUF_STRIDES) + +#endif + +#if PY_MAJOR_VERSION < 3 + #define __Pyx_BUILTIN_MODULE_NAME "__builtin__" +#else + #define __Pyx_BUILTIN_MODULE_NAME "builtins" +#endif + +#if PY_MAJOR_VERSION >= 3 + #define Py_TPFLAGS_CHECKTYPES 0 + #define Py_TPFLAGS_HAVE_INDEX 0 +#endif + +#if (PY_VERSION_HEX < 0x02060000) || (PY_MAJOR_VERSION >= 3) + #define Py_TPFLAGS_HAVE_NEWBUFFER 0 +#endif + +#if PY_MAJOR_VERSION >= 3 + #define PyBaseString_Type PyUnicode_Type + #define PyString_Type PyUnicode_Type + #define PyString_CheckExact PyUnicode_CheckExact +#else + #define PyBytes_Type PyString_Type + #define PyBytes_CheckExact PyString_CheckExact +#endif + +#if PY_MAJOR_VERSION >= 3 + #define PyInt_Type PyLong_Type + #define PyInt_Check(op) PyLong_Check(op) + #define PyInt_CheckExact(op) PyLong_CheckExact(op) + #define PyInt_FromString PyLong_FromString + #define PyInt_FromUnicode PyLong_FromUnicode + #define PyInt_FromLong PyLong_FromLong + #define PyInt_FromSize_t PyLong_FromSize_t + #define PyInt_FromSsize_t PyLong_FromSsize_t + #define PyInt_AsLong PyLong_AsLong + #define PyInt_AS_LONG PyLong_AS_LONG + #define PyInt_AsSsize_t PyLong_AsSsize_t + #define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask + #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask + #define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y) +#else + #define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y) + +#endif + +#if PY_MAJOR_VERSION >= 3 + #define PyMethod_New(func, self, klass) PyInstanceMethod_New(func) +#endif + +#if !defined(WIN32) && !defined(MS_WINDOWS) + #ifndef __stdcall + #define __stdcall + #endif + #ifndef __cdecl + #define __cdecl + #endif + #ifndef __fastcall + #define __fastcall + #endif +#else + #define _USE_MATH_DEFINES +#endif + +#if PY_VERSION_HEX < 0x02050000 + #define __Pyx_GetAttrString(o,n) PyObject_GetAttrString((o),((char *)(n))) + #define __Pyx_SetAttrString(o,n,a) PyObject_SetAttrString((o),((char *)(n)),(a)) + #define __Pyx_DelAttrString(o,n) PyObject_DelAttrString((o),((char *)(n))) +#else + #define __Pyx_GetAttrString(o,n) PyObject_GetAttrString((o),(n)) + #define __Pyx_SetAttrString(o,n,a) PyObject_SetAttrString((o),(n),(a)) + #define __Pyx_DelAttrString(o,n) PyObject_DelAttrString((o),(n)) +#endif + +#if PY_VERSION_HEX < 0x02050000 + #define __Pyx_NAMESTR(n) ((char *)(n)) + #define __Pyx_DOCSTR(n) ((char *)(n)) +#else + #define __Pyx_NAMESTR(n) (n) + #define __Pyx_DOCSTR(n) (n) +#endif +#ifdef __cplusplus +#define __PYX_EXTERN_C extern "C" +#else +#define __PYX_EXTERN_C extern +#endif +#include +#define __PYX_HAVE_API__scipy__signal__spectral +#include "stdlib.h" +#include "stdio.h" +#include "numpy/arrayobject.h" +#include "numpy/ufuncobject.h" +#include "math.h" + +#ifndef CYTHON_INLINE + #if defined(__GNUC__) + #define CYTHON_INLINE __inline__ + #elif defined(_MSC_VER) + #define CYTHON_INLINE __inline + #else + #define CYTHON_INLINE + #endif +#endif + +typedef struct {PyObject **p; char *s; const long n; const char* encoding; const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; /*proto*/ + + +/* Type Conversion Predeclarations */ + +#if PY_MAJOR_VERSION < 3 +#define __Pyx_PyBytes_FromString PyString_FromString +#define __Pyx_PyBytes_FromStringAndSize PyString_FromStringAndSize +#define __Pyx_PyBytes_AsString PyString_AsString +#else +#define __Pyx_PyBytes_FromString PyBytes_FromString +#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize +#define __Pyx_PyBytes_AsString PyBytes_AsString +#endif + +#define __Pyx_PyBytes_FromUString(s) __Pyx_PyBytes_FromString((char*)s) +#define __Pyx_PyBytes_AsUString(s) ((unsigned char*) __Pyx_PyBytes_AsString(s)) + +#define __Pyx_PyBool_FromLong(b) ((b) ? 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T_ULONG : -1)))) +#else +#define __Pyx_T_UNSIGNED_INT(x) \ + ((sizeof(x) == sizeof(unsigned char)) ? T_UBYTE : \ + ((sizeof(x) == sizeof(unsigned short)) ? T_USHORT : \ + ((sizeof(x) == sizeof(unsigned int)) ? T_UINT : \ + ((sizeof(x) == sizeof(unsigned long)) ? T_ULONG : \ + ((sizeof(x) == sizeof(unsigned PY_LONG_LONG)) ? T_ULONGLONG : -1))))) +#endif +#if !defined(T_LONGLONG) +#define __Pyx_T_SIGNED_INT(x) \ + ((sizeof(x) == sizeof(char)) ? T_BYTE : \ + ((sizeof(x) == sizeof(short)) ? T_SHORT : \ + ((sizeof(x) == sizeof(int)) ? T_INT : \ + ((sizeof(x) == sizeof(long)) ? T_LONG : -1)))) +#else +#define __Pyx_T_SIGNED_INT(x) \ + ((sizeof(x) == sizeof(char)) ? T_BYTE : \ + ((sizeof(x) == sizeof(short)) ? T_SHORT : \ + ((sizeof(x) == sizeof(int)) ? T_INT : \ + ((sizeof(x) == sizeof(long)) ? T_LONG : \ + ((sizeof(x) == sizeof(PY_LONG_LONG)) ? T_LONGLONG : -1))))) +#endif + +#define __Pyx_T_FLOATING(x) \ + ((sizeof(x) == sizeof(float)) ? T_FLOAT : \ + ((sizeof(x) == sizeof(double)) ? T_DOUBLE : -1)) + +#if !defined(T_SIZET) +#if !defined(T_ULONGLONG) +#define T_SIZET \ + ((sizeof(size_t) == sizeof(unsigned int)) ? T_UINT : \ + ((sizeof(size_t) == sizeof(unsigned long)) ? T_ULONG : -1)) +#else +#define T_SIZET \ + ((sizeof(size_t) == sizeof(unsigned int)) ? T_UINT : \ + ((sizeof(size_t) == sizeof(unsigned long)) ? T_ULONG : \ + ((sizeof(size_t) == sizeof(unsigned PY_LONG_LONG)) ? T_ULONGLONG : -1))) +#endif +#endif + +static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*); +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t); +static CYTHON_INLINE size_t __Pyx_PyInt_AsSize_t(PyObject*); + +#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x)) + + +#ifdef __GNUC__ +/* Test for GCC > 2.95 */ +#if __GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95)) +#define likely(x) __builtin_expect(!!(x), 1) +#define unlikely(x) __builtin_expect(!!(x), 0) +#else /* __GNUC__ > 2 ... */ +#define likely(x) (x) +#define unlikely(x) (x) +#endif /* __GNUC__ > 2 ... */ +#else /* __GNUC__ */ +#define likely(x) (x) +#define unlikely(x) (x) +#endif /* __GNUC__ */ + +static PyObject *__pyx_m; +static PyObject *__pyx_b; +static PyObject *__pyx_empty_tuple; +static PyObject *__pyx_empty_bytes; +static int __pyx_lineno; +static int __pyx_clineno = 0; +static const char * __pyx_cfilenm= __FILE__; +static const char *__pyx_filename; +static const char **__pyx_f; + + +#if !defined(CYTHON_CCOMPLEX) + #if defined(__cplusplus) + #define CYTHON_CCOMPLEX 1 + #elif defined(_Complex_I) + #define CYTHON_CCOMPLEX 1 + #else + #define CYTHON_CCOMPLEX 0 + #endif +#endif + +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + #include + #else + #include + #endif +#endif + +#if CYTHON_CCOMPLEX && !defined(__cplusplus) && defined(__sun__) && defined(__GNUC__) + #undef _Complex_I + #define _Complex_I 1.0fj +#endif + +typedef npy_int8 __pyx_t_5numpy_int8_t; + +typedef npy_int16 __pyx_t_5numpy_int16_t; + +typedef npy_int32 __pyx_t_5numpy_int32_t; + +typedef npy_int64 __pyx_t_5numpy_int64_t; + +typedef npy_uint8 __pyx_t_5numpy_uint8_t; + +typedef npy_uint16 __pyx_t_5numpy_uint16_t; + +typedef npy_uint32 __pyx_t_5numpy_uint32_t; + +typedef npy_uint64 __pyx_t_5numpy_uint64_t; + +typedef npy_float32 __pyx_t_5numpy_float32_t; + +typedef npy_float64 __pyx_t_5numpy_float64_t; + +typedef npy_long __pyx_t_5numpy_int_t; + +typedef npy_longlong __pyx_t_5numpy_long_t; + +typedef npy_intp __pyx_t_5numpy_intp_t; + +typedef npy_uintp __pyx_t_5numpy_uintp_t; + +typedef npy_ulong __pyx_t_5numpy_uint_t; + +typedef npy_ulonglong __pyx_t_5numpy_ulong_t; + +typedef npy_double __pyx_t_5numpy_float_t; + +typedef npy_double __pyx_t_5numpy_double_t; + +typedef npy_longdouble __pyx_t_5numpy_longdouble_t; + +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + typedef ::std::complex< float > __pyx_t_float_complex; + #else + typedef float _Complex __pyx_t_float_complex; + #endif +#else + typedef struct { float real, imag; } __pyx_t_float_complex; +#endif + +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + typedef ::std::complex< double > __pyx_t_double_complex; + #else + typedef double _Complex __pyx_t_double_complex; + #endif +#else + typedef struct { double real, imag; } __pyx_t_double_complex; +#endif + +/* Type declarations */ + +typedef npy_cfloat __pyx_t_5numpy_cfloat_t; + +typedef npy_cdouble __pyx_t_5numpy_cdouble_t; + +typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; + +typedef npy_cdouble __pyx_t_5numpy_complex_t; + +#ifndef CYTHON_REFNANNY + #define CYTHON_REFNANNY 0 +#endif + +#if CYTHON_REFNANNY + typedef struct { + void (*INCREF)(void*, PyObject*, int); + void (*DECREF)(void*, PyObject*, int); + void (*GOTREF)(void*, PyObject*, int); + void (*GIVEREF)(void*, PyObject*, int); + void* (*SetupContext)(const char*, int, const char*); + void (*FinishContext)(void**); + } __Pyx_RefNannyAPIStruct; + static __Pyx_RefNannyAPIStruct *__Pyx_RefNanny = NULL; + static __Pyx_RefNannyAPIStruct * __Pyx_RefNannyImportAPI(const char *modname) { + PyObject *m = NULL, *p = NULL; 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PyInt_FromLong(i) : PyLong_FromLongLong(i); + return __Pyx_SetItemInt_Generic(o, j, v); + } +} + +static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb); /*proto*/ +static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb); /*proto*/ + +static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); + +static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(void); + +static PyObject *__Pyx_UnpackItem(PyObject *, Py_ssize_t index); /*proto*/ +static int __Pyx_EndUnpack(PyObject *); /*proto*/ + +static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); /*proto*/ + +static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); + +static void __Pyx_UnpackTupleError(PyObject *, Py_ssize_t index); /*proto*/ + +static int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed, + const char *name, int exact); /*proto*/ +#if PY_MAJOR_VERSION < 3 +static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags); +static void __Pyx_ReleaseBuffer(Py_buffer *view); +#else +#define __Pyx_GetBuffer PyObject_GetBuffer +#define __Pyx_ReleaseBuffer PyBuffer_Release +#endif + +Py_ssize_t __Pyx_zeros[] = {0}; +Py_ssize_t __Pyx_minusones[] = {-1}; + +static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list); /*proto*/ + +static PyObject *__Pyx_GetName(PyObject *dict, PyObject *name); /*proto*/ + +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb); /*proto*/ + +static CYTHON_INLINE PyObject *__Pyx_PyInt_to_py_npy_intp(npy_intp); + +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + #define __Pyx_CREAL(z) ((z).real()) + #define __Pyx_CIMAG(z) ((z).imag()) + #else + #define __Pyx_CREAL(z) (__real__(z)) + #define __Pyx_CIMAG(z) (__imag__(z)) + #endif +#else + #define __Pyx_CREAL(z) ((z).real) + #define __Pyx_CIMAG(z) ((z).imag) +#endif + +#if defined(_WIN32) && defined(__cplusplus) && CYTHON_CCOMPLEX + #define __Pyx_SET_CREAL(z,x) ((z).real(x)) + #define __Pyx_SET_CIMAG(z,y) ((z).imag(y)) +#else + #define __Pyx_SET_CREAL(z,x) __Pyx_CREAL(z) = (x) + #define __Pyx_SET_CIMAG(z,y) __Pyx_CIMAG(z) = (y) +#endif + +static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float, float); + +#if CYTHON_CCOMPLEX + #define __Pyx_c_eqf(a, b) ((a)==(b)) + #define __Pyx_c_sumf(a, b) ((a)+(b)) + #define __Pyx_c_difff(a, b) ((a)-(b)) + #define __Pyx_c_prodf(a, b) ((a)*(b)) + #define __Pyx_c_quotf(a, b) ((a)/(b)) + #define __Pyx_c_negf(a) (-(a)) + #ifdef __cplusplus + #define __Pyx_c_is_zerof(z) ((z)==(float)0) + #define __Pyx_c_conjf(z) (::std::conj(z)) + /*#define __Pyx_c_absf(z) (::std::abs(z))*/ + #else + #define __Pyx_c_is_zerof(z) ((z)==0) + #define __Pyx_c_conjf(z) (conjf(z)) + /*#define __Pyx_c_absf(z) (cabsf(z))*/ + #endif +#else + static CYTHON_INLINE int __Pyx_c_eqf(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sumf(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_difff(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prodf(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quotf(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_negf(__pyx_t_float_complex); + static CYTHON_INLINE int __Pyx_c_is_zerof(__pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conjf(__pyx_t_float_complex); + /*static CYTHON_INLINE float __Pyx_c_absf(__pyx_t_float_complex);*/ +#endif + +static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double, double); + +#if CYTHON_CCOMPLEX + #define __Pyx_c_eq(a, b) ((a)==(b)) + #define __Pyx_c_sum(a, b) ((a)+(b)) + #define __Pyx_c_diff(a, b) ((a)-(b)) + #define __Pyx_c_prod(a, b) ((a)*(b)) + #define __Pyx_c_quot(a, b) ((a)/(b)) + #define __Pyx_c_neg(a) (-(a)) + #ifdef __cplusplus + #define __Pyx_c_is_zero(z) ((z)==(double)0) + #define __Pyx_c_conj(z) (::std::conj(z)) + /*#define __Pyx_c_abs(z) (::std::abs(z))*/ + #else + #define __Pyx_c_is_zero(z) ((z)==0) + #define __Pyx_c_conj(z) (conj(z)) + /*#define __Pyx_c_abs(z) (cabs(z))*/ + #endif +#else + static CYTHON_INLINE int __Pyx_c_eq(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg(__pyx_t_double_complex); + static CYTHON_INLINE int __Pyx_c_is_zero(__pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj(__pyx_t_double_complex); + /*static CYTHON_INLINE double __Pyx_c_abs(__pyx_t_double_complex);*/ +#endif + +static CYTHON_INLINE unsigned char __Pyx_PyInt_AsUnsignedChar(PyObject *); + +static CYTHON_INLINE unsigned short __Pyx_PyInt_AsUnsignedShort(PyObject *); + +static CYTHON_INLINE unsigned int __Pyx_PyInt_AsUnsignedInt(PyObject *); + +static CYTHON_INLINE char __Pyx_PyInt_AsChar(PyObject *); + +static CYTHON_INLINE short __Pyx_PyInt_AsShort(PyObject *); + +static CYTHON_INLINE int __Pyx_PyInt_AsInt(PyObject *); + +static CYTHON_INLINE signed char __Pyx_PyInt_AsSignedChar(PyObject *); + +static CYTHON_INLINE signed short __Pyx_PyInt_AsSignedShort(PyObject *); + +static CYTHON_INLINE signed int __Pyx_PyInt_AsSignedInt(PyObject *); + +static CYTHON_INLINE unsigned long __Pyx_PyInt_AsUnsignedLong(PyObject *); + +static CYTHON_INLINE unsigned PY_LONG_LONG __Pyx_PyInt_AsUnsignedLongLong(PyObject *); + +static CYTHON_INLINE long __Pyx_PyInt_AsLong(PyObject *); + +static CYTHON_INLINE PY_LONG_LONG __Pyx_PyInt_AsLongLong(PyObject *); + +static CYTHON_INLINE signed long __Pyx_PyInt_AsSignedLong(PyObject *); + +static CYTHON_INLINE signed PY_LONG_LONG __Pyx_PyInt_AsSignedLongLong(PyObject *); + +static PyTypeObject *__Pyx_ImportType(const char *module_name, const char *class_name, long size, int strict); /*proto*/ + +static PyObject *__Pyx_ImportModule(const char *name); /*proto*/ + +static void __Pyx_AddTraceback(const char *funcname); /*proto*/ + +static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); /*proto*/ +/* Module declarations from python_buffer */ + +/* Module declarations from python_ref */ + +/* Module declarations from stdlib */ + +/* Module declarations from stdio */ + +/* Module declarations from numpy */ + +/* Module declarations from numpy */ + +static PyTypeObject *__pyx_ptype_5numpy_dtype = 0; +static PyTypeObject *__pyx_ptype_5numpy_flatiter = 0; +static PyTypeObject *__pyx_ptype_5numpy_broadcast = 0; +static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0; +static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; +static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew1(PyObject *); /*proto*/ +static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew2(PyObject *, PyObject *); /*proto*/ +static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew3(PyObject *, PyObject *, PyObject *); /*proto*/ +static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew4(PyObject *, PyObject *, PyObject *, PyObject *); /*proto*/ +static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew5(PyObject *, PyObject *, PyObject *, PyObject *, PyObject *); /*proto*/ +static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *, char *, char *, int *); /*proto*/ +static CYTHON_INLINE void __pyx_f_5numpy_set_array_base(PyArrayObject *, PyObject *); /*proto*/ +static CYTHON_INLINE PyObject *__pyx_f_5numpy_get_array_base(PyArrayObject *); /*proto*/ +/* Module declarations from cython */ + +/* Module declarations from scipy.signal.spectral */ + +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5numpy_float64_t = { "numpy.float64_t", NULL, sizeof(__pyx_t_5numpy_float64_t), 'R' }; +#define __Pyx_MODULE_NAME "scipy.signal.spectral" +int __pyx_module_is_main_scipy__signal__spectral = 0; + +/* Implementation of scipy.signal.spectral */ +static PyObject *__pyx_builtin_ValueError; +static PyObject *__pyx_builtin_range; +static PyObject *__pyx_builtin_RuntimeError; +static char __pyx_k_1[] = "Input arrays do not have the same size."; +static char __pyx_k_2[] = "ndarray is not C contiguous"; +static char __pyx_k_3[] = "ndarray is not Fortran contiguous"; +static char __pyx_k_4[] = "Non-native byte order not supported"; +static char __pyx_k_5[] = "unknown dtype code in numpy.pxd (%d)"; +static char __pyx_k_6[] = "Format string allocated too short, see comment in numpy.pxd"; +static char __pyx_k_7[] = "Format string allocated too short."; +static char __pyx_k_8[] = "Tools for spectral analysis of unequally sampled signals."; +static char __pyx_k_9[] = "lombscargle (line 16)"; +static char __pyx_k__B[] = "B"; +static char __pyx_k__H[] = "H"; +static char __pyx_k__I[] = "I"; +static char __pyx_k__L[] = "L"; +static char __pyx_k__O[] = "O"; +static char __pyx_k__Q[] = "Q"; +static char __pyx_k__b[] = "b"; +static char __pyx_k__d[] = "d"; +static char __pyx_k__f[] = "f"; +static char __pyx_k__g[] = "g"; +static char __pyx_k__h[] = "h"; +static char __pyx_k__i[] = "i"; +static char __pyx_k__l[] = "l"; +static char __pyx_k__q[] = "q"; 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+static PyObject *__pyx_n_s__float64; +static PyObject *__pyx_n_s__format; +static PyObject *__pyx_n_s__freqs; +static PyObject *__pyx_n_s__itemsize; +static PyObject *__pyx_n_s__lombscargle; +static PyObject *__pyx_n_s__names; +static PyObject *__pyx_n_s__ndim; +static PyObject *__pyx_n_s__np; +static PyObject *__pyx_n_s__numpy; +static PyObject *__pyx_n_s__obj; +static PyObject *__pyx_n_s__range; +static PyObject *__pyx_n_s__readonly; +static PyObject *__pyx_n_s__shape; +static PyObject *__pyx_n_s__strides; +static PyObject *__pyx_n_s__suboffsets; +static PyObject *__pyx_n_s__type_num; +static PyObject *__pyx_n_s__x; +static PyObject *__pyx_n_s__y; +static PyObject *__pyx_int_15; + +/* "/Users/rgommers/Code/scipy/scipy/signal/spectral.pyx":16 + * + * @cython.boundscheck(False) + * def lombscargle(np.ndarray[np.float64_t, ndim=1] x, # <<<<<<<<<<<<<< + * np.ndarray[np.float64_t, ndim=1] y, + * np.ndarray[np.float64_t, ndim=1] freqs): + */ + +static PyObject *__pyx_pf_5scipy_6signal_8spectral_lombscargle(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ +static char __pyx_doc_5scipy_6signal_8spectral_lombscargle[] = "Computes the Lomb-Scargle periodogram.\n"" \n"" The Lomb-Scargle periodogram was developed by Lomb [1]_ and further\n"" extended by Scargle [2]_ to find, and test the significance of weak\n"" periodic signals with uneven temporal sampling.\n""\n"" The computed periodogram is unnormalized, it takes the value\n"" ``(A**2) * N/4`` for a harmonic signal with amplitude A for sufficiently\n"" large N.\n""\n"" Parameters\n"" ----------\n"" x : array_like\n"" Sample times.\n"" y : array_like\n"" Measurement values.\n"" freqs : array_like\n"" Angular frequencies for output periodogram.\n""\n"" Returns\n"" -------\n"" pgram : array_like\n"" Lomb-Scargle periodogram.\n""\n"" Raises\n"" ------\n"" ValueError\n"" If the input arrays `x` and `y` do not have the same shape.\n""\n"" Notes\n"" -----\n"" This subroutine calculates the periodogram using a slightly\n"" modified algorithm due to Townsend [3]_ which allows the\n"" periodogram to be calculated using only a single pass through\n"" the input arrays for each frequency.\n""\n"" The algorithm running time scales roughly as O(x * freqs) or O(N^2)\n"" for a large number of samples and frequencies.\n""\n"" References\n"" ----------\n"" .. [1] N.R. Lomb \"Least-squares frequency analysis of unequally spaced\n"" data\", Astrophysics and Space Science, vol 39, pp. 447-462, 1976\n""\n"" .. [2] J.D. Scargle \"Studies in astronomical time series analysis. II - \n"" Statistical aspects of spectral analysis of unevenly spaced data\",\n"" The Astrophysical Journal, vol 263, pp. 835-853, 1982\n""\n"" .. [3] R.H.D. Townsend, \"Fast calculation of the Lomb-Scargle\n"" periodogram using graphics processing units.\", The Astrophysical\n"" Journal Supplement Series, vol 191, pp. 247-253, 2010\n""\n"" Examples\n"" --------\n"" >>> import scipy.signal\n""\n"" First define some input parameters for the signal:\n""\n"" >>> A = 2.\n"" >>> w = 1.\n"" >>> phi = 0.5 * np.pi\n"" >>> nin = 1000\n"" >>> nout = 100000\n"" >>> frac_points = 0.9 # Fraction of points to select\n"" \n"" Randomly select a fraction of an array with timesteps:\n""\n"" >>> r = np.random.rand(nin)\n"" >>> x = np.linspace(0.01, 10*np.pi, nin)\n"" >>> x = x[r >= frac_points]\n"" >>> normval = x.shape[0] # For normalization of the periodogram\n"" \n"" Plot a sine wave for the selected times:\n""\n"" >>> y = A * np.sin(w*x+phi)\n""\n"" Define the array of frequencies for which to compute the periodogram:\n"" \n"" >>> f = np.linspace(0.01, 10, nout)\n"" \n"" Calculate Lomb-Scargle periodogram:\n""\n"" >>> pgram = sp.signal.lombscargle(x, y, f)\n""\n"" Now make a plot of the input data:\n""\n"" >>> plt.subplot(2, 1, 1)\n"" \n"" >>> plt.plot(x, y, 'b+')\n"" []\n""\n"" Then plot the normalized periodogram:\n""\n"" >>> plt.subplot(2, 1, 2)\n"" \n"" >>> plt.plot(f, np.sqrt(4*(pgram/normval)))\n"" []\n"" >>> plt.show()\n"" \n"" "; +static PyObject *__pyx_pf_5scipy_6signal_8spectral_lombscargle(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { + PyArrayObject *__pyx_v_x = 0; + PyArrayObject *__pyx_v_y = 0; + PyArrayObject *__pyx_v_freqs = 0; + PyObject *__pyx_v_pgram; + Py_ssize_t __pyx_v_i; + Py_ssize_t __pyx_v_j; + double __pyx_v_c; + double __pyx_v_s; + double __pyx_v_xc; + double __pyx_v_xs; + double __pyx_v_cc; + double __pyx_v_ss; + double __pyx_v_cs; + double __pyx_v_tau; + double __pyx_v_c_tau; + double __pyx_v_s_tau; + double __pyx_v_c_tau2; + double __pyx_v_s_tau2; + double __pyx_v_cs_tau; + Py_buffer __pyx_bstruct_freqs; + Py_ssize_t __pyx_bstride_0_freqs = 0; + Py_ssize_t __pyx_bshape_0_freqs = 0; + Py_buffer __pyx_bstruct_y; + Py_ssize_t __pyx_bstride_0_y = 0; + Py_ssize_t __pyx_bshape_0_y = 0; + Py_buffer __pyx_bstruct_x; + Py_ssize_t __pyx_bstride_0_x = 0; + Py_ssize_t __pyx_bshape_0_x = 0; + PyObject *__pyx_r = NULL; + int __pyx_t_1; + PyObject *__pyx_t_2 = NULL; + PyObject *__pyx_t_3 = NULL; + PyObject *__pyx_t_4 = NULL; + PyObject *__pyx_t_5 = NULL; + PyObject *__pyx_t_6 = NULL; + npy_intp __pyx_t_7; + Py_ssize_t __pyx_t_8; + npy_intp __pyx_t_9; + Py_ssize_t __pyx_t_10; + Py_ssize_t __pyx_t_11; + Py_ssize_t __pyx_t_12; + Py_ssize_t __pyx_t_13; + Py_ssize_t __pyx_t_14; + Py_ssize_t __pyx_t_15; + Py_ssize_t __pyx_t_16; + double __pyx_t_17; + double __pyx_t_18; + double __pyx_t_19; + __pyx_t_5numpy_float64_t __pyx_t_20; + Py_ssize_t __pyx_t_21; + Py_ssize_t __pyx_t_22; + double __pyx_t_23; + static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__x,&__pyx_n_s__y,&__pyx_n_s__freqs,0}; + __Pyx_RefNannySetupContext("lombscargle"); + __pyx_self = __pyx_self; + if (unlikely(__pyx_kwds)) { + Py_ssize_t kw_args = PyDict_Size(__pyx_kwds); + PyObject* values[3] = {0,0,0}; + switch (PyTuple_GET_SIZE(__pyx_args)) { + case 3: values[2] = PyTuple_GET_ITEM(__pyx_args, 2); + case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1); + case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0); + case 0: break; 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+ const char *number, *more_or_less; + + if (num_found < num_min) { + num_expected = num_min; + more_or_less = "at least"; + } else { + num_expected = num_max; + more_or_less = "at most"; + } + if (exact) { + more_or_less = "exactly"; + } + number = (num_expected == 1) ? "" : "s"; + PyErr_Format(PyExc_TypeError, + #if PY_VERSION_HEX < 0x02050000 + "%s() takes %s %d positional argument%s (%d given)", + #else + "%s() takes %s %zd positional argument%s (%zd given)", + #endif + func_name, more_or_less, num_expected, number, num_found); +} + +static int __Pyx_ParseOptionalKeywords( + PyObject *kwds, + PyObject **argnames[], + PyObject *kwds2, + PyObject *values[], + Py_ssize_t num_pos_args, + const char* function_name) +{ + PyObject *key = 0, *value = 0; + Py_ssize_t pos = 0; + PyObject*** name; + PyObject*** first_kw_arg = argnames + num_pos_args; + + while (PyDict_Next(kwds, &pos, &key, &value)) { + name = first_kw_arg; + while (*name && (**name != key)) name++; + if (*name) { + values[name-argnames] = value; + } else { + #if PY_MAJOR_VERSION < 3 + if (unlikely(!PyString_CheckExact(key)) && unlikely(!PyString_Check(key))) { + #else + if (unlikely(!PyUnicode_CheckExact(key)) && unlikely(!PyUnicode_Check(key))) { + #endif + goto invalid_keyword_type; + } else { + for (name = first_kw_arg; *name; name++) { + #if PY_MAJOR_VERSION >= 3 + if (PyUnicode_GET_SIZE(**name) == PyUnicode_GET_SIZE(key) && + PyUnicode_Compare(**name, key) == 0) break; + #else + if (PyString_GET_SIZE(**name) == PyString_GET_SIZE(key) && + _PyString_Eq(**name, key)) break; + #endif + } + if (*name) { + values[name-argnames] = value; + } else { + /* unexpected keyword found */ + for (name=argnames; name != first_kw_arg; name++) { + if (**name == key) goto arg_passed_twice; + #if PY_MAJOR_VERSION >= 3 + if (PyUnicode_GET_SIZE(**name) == PyUnicode_GET_SIZE(key) && + PyUnicode_Compare(**name, key) == 0) goto arg_passed_twice; + #else + if (PyString_GET_SIZE(**name) == PyString_GET_SIZE(key) && + _PyString_Eq(**name, key)) goto arg_passed_twice; + #endif + } + if (kwds2) { + if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad; + } else { + goto invalid_keyword; + } + } + } + } + } + return 0; +arg_passed_twice: + __Pyx_RaiseDoubleKeywordsError(function_name, **name); + goto bad; +invalid_keyword_type: + PyErr_Format(PyExc_TypeError, + "%s() keywords must be strings", function_name); + goto bad; +invalid_keyword: + PyErr_Format(PyExc_TypeError, + #if PY_MAJOR_VERSION < 3 + "%s() got an unexpected keyword argument '%s'", + function_name, PyString_AsString(key)); + #else + "%s() got an unexpected keyword argument '%U'", + function_name, key); + #endif +bad: + return -1; +} + +static CYTHON_INLINE int __Pyx_IsLittleEndian(void) { + unsigned int n = 1; + return *(unsigned char*)(&n) != 0; +} + +typedef struct { + __Pyx_StructField root; + __Pyx_BufFmt_StackElem* head; + size_t fmt_offset; + int new_count, enc_count; + int is_complex; + char enc_type; + char packmode; +} __Pyx_BufFmt_Context; + +static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx, + __Pyx_BufFmt_StackElem* stack, + __Pyx_TypeInfo* type) { + stack[0].field = &ctx->root; + stack[0].parent_offset = 0; + ctx->root.type = type; + ctx->root.name = "buffer dtype"; + ctx->root.offset = 0; + ctx->head = stack; + ctx->head->field = &ctx->root; + ctx->fmt_offset = 0; + ctx->head->parent_offset = 0; + ctx->packmode = '@'; + ctx->new_count = 1; + ctx->enc_count = 0; + ctx->enc_type = 0; + ctx->is_complex = 0; + while (type->typegroup == 'S') { + ++ctx->head; + ctx->head->field = type->fields; + ctx->head->parent_offset = 0; + type = type->fields->type; + } +} + +static int __Pyx_BufFmt_ParseNumber(const char** ts) { + int count; + const char* t = *ts; + if (*t < '0' || *t > '9') { + return -1; + } else { + count = *t++ - '0'; + while (*t >= '0' && *t < '9') { + count *= 10; + count += *t++ - '0'; + } + } + *ts = t; + return count; +} + +static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) { + char msg[] = {ch, 0}; + PyErr_Format(PyExc_ValueError, "Unexpected format string character: '%s'", msg); +} + +static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) { + switch (ch) { + case 'b': return "'char'"; + case 'B': return "'unsigned char'"; + case 'h': return "'short'"; + case 'H': return "'unsigned short'"; + case 'i': return "'int'"; + case 'I': return "'unsigned int'"; + case 'l': return "'long'"; + case 'L': return "'unsigned long'"; + case 'q': return "'long long'"; + case 'Q': return "'unsigned long long'"; + case 'f': return (is_complex ? "'complex float'" : "'float'"); + case 'd': return (is_complex ? "'complex double'" : "'double'"); + case 'g': return (is_complex ? "'complex long double'" : "'long double'"); + case 'T': return "a struct"; + case 'O': return "Python object"; + case 'P': return "a pointer"; + case 0: return "end"; + default: return "unparseable format string"; + } +} + +static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': return 1; + case 'h': case 'H': return 2; + case 'i': case 'I': case 'l': case 'L': return 4; + case 'q': case 'Q': return 8; + case 'f': return (is_complex ? 8 : 4); + case 'd': return (is_complex ? 16 : 8); + case 'g': { + PyErr_SetString(PyExc_ValueError, "Python does not define a standard format string size for long double ('g').."); + return 0; + } + case 'O': case 'P': return sizeof(void*); + default: + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } +} + +static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) { + switch (ch) { + case 'c': case 'b': case 'B': return 1; + case 'h': case 'H': return sizeof(short); + case 'i': case 'I': return sizeof(int); + case 'l': case 'L': return sizeof(long); + #ifdef HAVE_LONG_LONG + case 'q': case 'Q': return sizeof(PY_LONG_LONG); + #endif + case 'f': return sizeof(float) * (is_complex ? 2 : 1); + case 'd': return sizeof(double) * (is_complex ? 2 : 1); + case 'g': return sizeof(long double) * (is_complex ? 2 : 1); + case 'O': case 'P': return sizeof(void*); + default: { + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } + } +} + +typedef struct { char c; short x; } __Pyx_st_short; +typedef struct { char c; int x; } __Pyx_st_int; +typedef struct { char c; long x; } __Pyx_st_long; +typedef struct { char c; float x; } __Pyx_st_float; +typedef struct { char c; double x; } __Pyx_st_double; +typedef struct { char c; long double x; } __Pyx_st_longdouble; +typedef struct { char c; void *x; } __Pyx_st_void_p; +#ifdef HAVE_LONG_LONG +typedef struct { char c; PY_LONG_LONG x; } __Pyx_s_long_long; +#endif + +static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': return 1; + case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short); + case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int); + case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long); +#ifdef HAVE_LONG_LONG + case 'q': case 'Q': return sizeof(__Pyx_s_long_long) - sizeof(PY_LONG_LONG); +#endif + case 'f': return sizeof(__Pyx_st_float) - sizeof(float); + case 'd': return sizeof(__Pyx_st_double) - sizeof(double); + case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double); + case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*); + default: + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } +} + +static size_t __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) { + switch (ch) { + case 'c': case 'b': case 'h': case 'i': case 'l': case 'q': return 'I'; + case 'B': case 'H': case 'I': case 'L': case 'Q': return 'U'; + case 'f': case 'd': case 'g': return (is_complex ? 'C' : 'R'); + case 'O': return 'O'; + case 'P': return 'P'; + default: { + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } + } +} + +static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) { + if (ctx->head == NULL || ctx->head->field == &ctx->root) { + const char* expected; + const char* quote; + if (ctx->head == NULL) { + expected = "end"; + quote = ""; + } else { + expected = ctx->head->field->type->name; + quote = "'"; + } + PyErr_Format(PyExc_ValueError, + "Buffer dtype mismatch, expected %s%s%s but got %s", + quote, expected, quote, + __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex)); + } else { + __Pyx_StructField* field = ctx->head->field; + __Pyx_StructField* parent = (ctx->head - 1)->field; + PyErr_Format(PyExc_ValueError, + "Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'", + field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex), + parent->type->name, field->name); + } +} + +static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) { + char group; + size_t size, offset; + if (ctx->enc_type == 0) return 0; + group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex); + do { + __Pyx_StructField* field = ctx->head->field; + __Pyx_TypeInfo* type = field->type; + + if (ctx->packmode == '@' || ctx->packmode == '^') { + size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex); + } else { + size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex); + } + if (ctx->packmode == '@') { + int align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex); + int align_mod_offset; + if (align_at == 0) return -1; + align_mod_offset = ctx->fmt_offset % align_at; + if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset; + } + + if (type->size != size || type->typegroup != group) { + if (type->typegroup == 'C' && type->fields != NULL) { + /* special case -- treat as struct rather than complex number */ + size_t parent_offset = ctx->head->parent_offset + field->offset; + ++ctx->head; + ctx->head->field = type->fields; + ctx->head->parent_offset = parent_offset; + continue; + } + + __Pyx_BufFmt_RaiseExpected(ctx); + return -1; + } + + offset = ctx->head->parent_offset + field->offset; + if (ctx->fmt_offset != offset) { + PyErr_Format(PyExc_ValueError, + "Buffer dtype mismatch; next field is at offset %"PY_FORMAT_SIZE_T"d " + "but %"PY_FORMAT_SIZE_T"d expected", ctx->fmt_offset, offset); + return -1; + } + + ctx->fmt_offset += size; + + --ctx->enc_count; /* Consume from buffer string */ + + /* Done checking, move to next field, pushing or popping struct stack if needed */ + while (1) { + if (field == &ctx->root) { + ctx->head = NULL; + if (ctx->enc_count != 0) { + __Pyx_BufFmt_RaiseExpected(ctx); + return -1; + } + break; /* breaks both loops as ctx->enc_count == 0 */ + } + ctx->head->field = ++field; + if (field->type == NULL) { + --ctx->head; + field = ctx->head->field; + continue; + } else if (field->type->typegroup == 'S') { + size_t parent_offset = ctx->head->parent_offset + field->offset; + if (field->type->fields->type == NULL) continue; /* empty struct */ + field = field->type->fields; + ++ctx->head; + ctx->head->field = field; + ctx->head->parent_offset = parent_offset; + break; + } else { + break; + } + } + } while (ctx->enc_count); + ctx->enc_type = 0; + ctx->is_complex = 0; + return 0; +} + +static int __Pyx_BufFmt_FirstPack(__Pyx_BufFmt_Context* ctx) { + if (ctx->enc_type != 0 || ctx->packmode != '@') { + PyErr_SetString(PyExc_ValueError, "Buffer packing mode currently only allowed at beginning of format string (this is a defect)"); + return -1; + } + return 0; +} + +static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) { + int got_Z = 0; + while (1) { + switch(*ts) { + case 0: + if (ctx->enc_type != 0 && ctx->head == NULL) { + __Pyx_BufFmt_RaiseExpected(ctx); + return NULL; + } + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + if (ctx->head != NULL) { + __Pyx_BufFmt_RaiseExpected(ctx); + return NULL; + } + return ts; + case ' ': + case 10: + case 13: + ++ts; + break; + case '<': + if (!__Pyx_IsLittleEndian()) { + PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler"); + return NULL; + } + if (__Pyx_BufFmt_FirstPack(ctx) == -1) return NULL; + ctx->packmode = '='; + ++ts; + break; + case '>': + case '!': + if (__Pyx_IsLittleEndian()) { + PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler"); + return NULL; + } + if (__Pyx_BufFmt_FirstPack(ctx) == -1) return NULL; + ctx->packmode = '='; + ++ts; + break; + case '=': + case '@': + case '^': + if (__Pyx_BufFmt_FirstPack(ctx) == -1) return NULL; + ctx->packmode = *ts++; + break; + case 'T': /* substruct */ + { + int i; + const char* ts_after_sub; + int struct_count = ctx->new_count; + ctx->new_count = 1; + ++ts; + if (*ts != '{') { + PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'"); + return NULL; + } + ++ts; + ts_after_sub = ts; + for (i = 0; i != struct_count; ++i) { + ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts); + if (!ts_after_sub) return NULL; + } + ts = ts_after_sub; + } + break; + case '}': /* end of substruct; either repeat or move on */ + ++ts; + return ts; + case 'x': + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->fmt_offset += ctx->new_count; + ctx->new_count = 1; + ctx->enc_count = 0; + ctx->enc_type = 0; + ++ts; + break; + case 'Z': + got_Z = 1; + ++ts; + if (*ts != 'f' && *ts != 'd' && *ts != 'g') { + __Pyx_BufFmt_RaiseUnexpectedChar('Z'); + return NULL; + } /* fall through */ + case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': + case 'l': case 'L': case 'q': case 'Q': + case 'f': case 'd': case 'g': + case 'O': + if (ctx->enc_type == *ts && got_Z == ctx->is_complex) { + /* Continue pooling same type */ + ctx->enc_count += ctx->new_count; + } else { + /* New type */ + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->enc_count = ctx->new_count; + ctx->enc_type = *ts; + ctx->is_complex = got_Z; + } + ++ts; + ctx->new_count = 1; + got_Z = 0; + break; + default: + { + ctx->new_count = __Pyx_BufFmt_ParseNumber(&ts); + if (ctx->new_count == -1) { /* First char was not a digit */ + char msg[2] = { *ts, 0 }; + PyErr_Format(PyExc_ValueError, + "Does not understand character buffer dtype format string ('%s')", msg); + return NULL; + } + } + + } + } +} + +static CYTHON_INLINE void __Pyx_ZeroBuffer(Py_buffer* buf) { + buf->buf = NULL; + buf->obj = NULL; + buf->strides = __Pyx_zeros; + buf->shape = __Pyx_zeros; + buf->suboffsets = __Pyx_minusones; +} + +static int __Pyx_GetBufferAndValidate(Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack) { + if (obj == Py_None) { + __Pyx_ZeroBuffer(buf); + return 0; + } + buf->buf = NULL; + if (__Pyx_GetBuffer(obj, buf, flags) == -1) goto fail; + if (buf->ndim != nd) { + PyErr_Format(PyExc_ValueError, + "Buffer has wrong number of dimensions (expected %d, got %d)", + nd, buf->ndim); + goto fail; + } + if (!cast) { + __Pyx_BufFmt_Context ctx; + __Pyx_BufFmt_Init(&ctx, stack, dtype); + if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; + } + if ((unsigned)buf->itemsize != dtype->size) { + PyErr_Format(PyExc_ValueError, + "Item size of buffer (%"PY_FORMAT_SIZE_T"d byte%s) does not match size of '%s' (%"PY_FORMAT_SIZE_T"d byte%s)", + buf->itemsize, (buf->itemsize > 1) ? "s" : "", + dtype->name, + dtype->size, (dtype->size > 1) ? "s" : ""); + goto fail; + } + if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones; + return 0; +fail:; + __Pyx_ZeroBuffer(buf); + return -1; +} + +static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) { + if (info->buf == NULL) return; + if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL; + __Pyx_ReleaseBuffer(info); +} + + +static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyThreadState *tstate = PyThreadState_GET(); + + tmp_type = tstate->curexc_type; + tmp_value = tstate->curexc_value; + tmp_tb = tstate->curexc_traceback; + tstate->curexc_type = type; + tstate->curexc_value = value; + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} + +static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb) { + PyThreadState *tstate = PyThreadState_GET(); + *type = tstate->curexc_type; + *value = tstate->curexc_value; + *tb = tstate->curexc_traceback; + + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +} + + +static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) { + PyErr_Format(PyExc_ValueError, + #if PY_VERSION_HEX < 0x02050000 + "need more than %d value%s to unpack", (int)index, + #else + "need more than %zd value%s to unpack", index, + #endif + (index == 1) ? "" : "s"); +} + +static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(void) { + PyErr_SetString(PyExc_ValueError, "too many values to unpack"); +} + +static PyObject *__Pyx_UnpackItem(PyObject *iter, Py_ssize_t index) { + PyObject *item; + if (!(item = PyIter_Next(iter))) { + if (!PyErr_Occurred()) { + __Pyx_RaiseNeedMoreValuesError(index); + } + } + return item; +} + +static int __Pyx_EndUnpack(PyObject *iter) { + PyObject *item; + if ((item = PyIter_Next(iter))) { + Py_DECREF(item); + __Pyx_RaiseTooManyValuesError(); + return -1; + } + else if (!PyErr_Occurred()) + return 0; + else + return -1; +} + +static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { + if (unlikely(!type)) { + PyErr_Format(PyExc_SystemError, "Missing type object"); + return 0; + } + if (likely(PyObject_TypeCheck(obj, type))) + return 1; + PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", + Py_TYPE(obj)->tp_name, type->tp_name); + return 0; +} + +static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { + PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); +} + +static void __Pyx_UnpackTupleError(PyObject *t, Py_ssize_t index) { + if (t == Py_None) { + __Pyx_RaiseNoneNotIterableError(); + } else if (PyTuple_GET_SIZE(t) < index) { + __Pyx_RaiseNeedMoreValuesError(PyTuple_GET_SIZE(t)); + } else { + __Pyx_RaiseTooManyValuesError(); + } +} + +static int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed, + const char *name, int exact) +{ + if (!type) { + PyErr_Format(PyExc_SystemError, "Missing type object"); + return 0; + } + if (none_allowed && obj == Py_None) return 1; + else if (exact) { + if (Py_TYPE(obj) == type) return 1; + } + else { + if (PyObject_TypeCheck(obj, type)) return 1; + } + PyErr_Format(PyExc_TypeError, + "Argument '%s' has incorrect type (expected %s, got %s)", + name, type->tp_name, Py_TYPE(obj)->tp_name); + return 0; +} + +#if PY_MAJOR_VERSION < 3 +static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { + #if PY_VERSION_HEX >= 0x02060000 + if (Py_TYPE(obj)->tp_flags & Py_TPFLAGS_HAVE_NEWBUFFER) + return PyObject_GetBuffer(obj, view, flags); + #endif + if (PyObject_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) return __pyx_pf_5numpy_7ndarray___getbuffer__(obj, view, flags); + else { + PyErr_Format(PyExc_TypeError, "'%100s' does not have the buffer interface", Py_TYPE(obj)->tp_name); + return -1; + } +} + +static void __Pyx_ReleaseBuffer(Py_buffer *view) { + PyObject* obj = view->obj; + if (obj) { +if (PyObject_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) __pyx_pf_5numpy_7ndarray___releasebuffer__(obj, view); + Py_DECREF(obj); + view->obj = NULL; + } +} + +#endif + +static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list) { + PyObject *__import__ = 0; + PyObject *empty_list = 0; + PyObject *module = 0; + PyObject *global_dict = 0; + PyObject *empty_dict = 0; + PyObject *list; + __import__ = __Pyx_GetAttrString(__pyx_b, "__import__"); + if (!__import__) + goto bad; + if (from_list) + list = from_list; + else { + empty_list = PyList_New(0); + if (!empty_list) + goto bad; + list = empty_list; + } + global_dict = PyModule_GetDict(__pyx_m); + if (!global_dict) + goto bad; + empty_dict = PyDict_New(); + if (!empty_dict) + goto bad; + module = PyObject_CallFunctionObjArgs(__import__, + name, global_dict, empty_dict, list, NULL); +bad: + Py_XDECREF(empty_list); + Py_XDECREF(__import__); + Py_XDECREF(empty_dict); + return module; +} + +static PyObject *__Pyx_GetName(PyObject *dict, PyObject *name) { + PyObject *result; + result = PyObject_GetAttr(dict, name); + if (!result) + PyErr_SetObject(PyExc_NameError, name); + return result; +} + +#if PY_MAJOR_VERSION < 3 +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb) { + Py_XINCREF(type); + Py_XINCREF(value); + Py_XINCREF(tb); + /* First, check the traceback argument, replacing None with NULL. */ + if (tb == Py_None) { + Py_DECREF(tb); + tb = 0; + } + else if (tb != NULL && !PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto raise_error; + } + /* Next, replace a missing value with None */ + if (value == NULL) { + value = Py_None; + Py_INCREF(value); + } + #if PY_VERSION_HEX < 0x02050000 + if (!PyClass_Check(type)) + #else + if (!PyType_Check(type)) + #endif + { + /* Raising an instance. The value should be a dummy. */ + if (value != Py_None) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto raise_error; + } + /* Normalize to raise , */ + Py_DECREF(value); + value = type; + #if PY_VERSION_HEX < 0x02050000 + if (PyInstance_Check(type)) { + type = (PyObject*) ((PyInstanceObject*)type)->in_class; + Py_INCREF(type); + } + else { + type = 0; + PyErr_SetString(PyExc_TypeError, + "raise: exception must be an old-style class or instance"); + goto raise_error; + } + #else + type = (PyObject*) Py_TYPE(type); + Py_INCREF(type); + if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto raise_error; + } + #endif + } + + __Pyx_ErrRestore(type, value, tb); + return; +raise_error: + Py_XDECREF(value); + Py_XDECREF(type); + Py_XDECREF(tb); + return; +} + +#else /* Python 3+ */ + +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb) { + if (tb == Py_None) { + tb = 0; + } else if (tb && !PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto bad; + } + if (value == Py_None) + value = 0; + + if (PyExceptionInstance_Check(type)) { + if (value) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto bad; + } + value = type; + type = (PyObject*) Py_TYPE(value); + } else if (!PyExceptionClass_Check(type)) { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto bad; + } + + PyErr_SetObject(type, value); + + if (tb) { + PyThreadState *tstate = PyThreadState_GET(); + PyObject* tmp_tb = tstate->curexc_traceback; + if (tb != tmp_tb) { + Py_INCREF(tb); + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_tb); + } + } + +bad: + return; +} +#endif + +static CYTHON_INLINE PyObject *__Pyx_PyInt_to_py_npy_intp(npy_intp val) { + const npy_intp neg_one = (npy_intp)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; + if (sizeof(npy_intp) < sizeof(long)) { + return PyInt_FromLong((long)val); + } else if (sizeof(npy_intp) == sizeof(long)) { + if (is_unsigned) + return PyLong_FromUnsignedLong((unsigned long)val); + else + return PyInt_FromLong((long)val); + } else { /* (sizeof(npy_intp) > sizeof(long)) */ + if (is_unsigned) + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG)val); + else + return PyLong_FromLongLong((PY_LONG_LONG)val); + } +} + +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return ::std::complex< float >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return x + y*(__pyx_t_float_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + __pyx_t_float_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +#if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eqf(__pyx_t_float_complex a, __pyx_t_float_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sumf(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_difff(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prodf(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quotf(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + float denom = b.real * b.real + b.imag * b.imag; + z.real = (a.real * b.real + a.imag * b.imag) / denom; + z.imag = (a.imag * b.real - a.real * b.imag) / denom; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_negf(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zerof(__pyx_t_float_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conjf(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } +/* + static CYTHON_INLINE float __Pyx_c_absf(__pyx_t_float_complex z) { +#if HAVE_HYPOT + return hypotf(z.real, z.imag); +#else + return sqrtf(z.real*z.real + z.imag*z.imag); +#endif + } +*/ +#endif + +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return ::std::complex< double >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return x + y*(__pyx_t_double_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + __pyx_t_double_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +#if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eq(__pyx_t_double_complex a, __pyx_t_double_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + double denom = b.real * b.real + b.imag * b.imag; + z.real = (a.real * b.real + a.imag * b.imag) / denom; + z.imag = (a.imag * b.real - a.real * b.imag) / denom; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zero(__pyx_t_double_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } +/* + static CYTHON_INLINE double __Pyx_c_abs(__pyx_t_double_complex z) { +#if HAVE_HYPOT + return hypot(z.real, z.imag); +#else + return sqrt(z.real*z.real + z.imag*z.imag); +#endif + } +*/ +#endif + +static CYTHON_INLINE unsigned char __Pyx_PyInt_AsUnsignedChar(PyObject* x) { + const unsigned char neg_one = (unsigned char)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; + if (sizeof(unsigned char) < sizeof(long)) { + long val = __Pyx_PyInt_AsLong(x); + if (unlikely(val != (long)(unsigned char)val)) { + if (!unlikely(val == -1 && PyErr_Occurred())) { + PyErr_SetString(PyExc_OverflowError, + (is_unsigned && unlikely(val < 0)) ? + "can't convert negative value to unsigned char" : + "value too large to convert to unsigned char"); + } + return (unsigned char)-1; + } + return (unsigned char)val; + } + return (unsigned char)__Pyx_PyInt_AsUnsignedLong(x); +} + +static CYTHON_INLINE unsigned short __Pyx_PyInt_AsUnsignedShort(PyObject* x) { + const unsigned short neg_one = (unsigned short)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; + if (sizeof(unsigned short) < sizeof(long)) { + long val = __Pyx_PyInt_AsLong(x); + if (unlikely(val != (long)(unsigned short)val)) { + if (!unlikely(val == -1 && PyErr_Occurred())) { + PyErr_SetString(PyExc_OverflowError, + (is_unsigned && unlikely(val < 0)) ? + "can't convert negative value to unsigned short" : + "value too large to convert to unsigned short"); + } + return (unsigned short)-1; + } + return (unsigned short)val; + } + return (unsigned short)__Pyx_PyInt_AsUnsignedLong(x); +} + +static CYTHON_INLINE unsigned int __Pyx_PyInt_AsUnsignedInt(PyObject* x) { + const unsigned int neg_one = (unsigned int)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; + if (sizeof(unsigned int) < sizeof(long)) { + long val = __Pyx_PyInt_AsLong(x); + if (unlikely(val != (long)(unsigned int)val)) { + if (!unlikely(val == -1 && PyErr_Occurred())) { + PyErr_SetString(PyExc_OverflowError, + (is_unsigned && unlikely(val < 0)) ? + "can't convert negative value to unsigned int" : + "value too large to convert to unsigned int"); + } + return (unsigned int)-1; + } + return (unsigned int)val; + } + return (unsigned int)__Pyx_PyInt_AsUnsignedLong(x); +} + +static CYTHON_INLINE char __Pyx_PyInt_AsChar(PyObject* x) { + const char neg_one = (char)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; + if (sizeof(char) < sizeof(long)) { + long val = __Pyx_PyInt_AsLong(x); + if (unlikely(val != (long)(char)val)) { + if (!unlikely(val == -1 && PyErr_Occurred())) { + PyErr_SetString(PyExc_OverflowError, + (is_unsigned && unlikely(val < 0)) ? + "can't convert negative value to char" : + "value too large to convert to char"); + } + return (char)-1; + } + return (char)val; + } + return (char)__Pyx_PyInt_AsLong(x); +} + +static CYTHON_INLINE short __Pyx_PyInt_AsShort(PyObject* x) { + const short neg_one = (short)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; + if (sizeof(short) < sizeof(long)) { + long val = __Pyx_PyInt_AsLong(x); + if (unlikely(val != (long)(short)val)) { + if (!unlikely(val == -1 && PyErr_Occurred())) { + PyErr_SetString(PyExc_OverflowError, + (is_unsigned && unlikely(val < 0)) ? + "can't convert negative value to short" : + "value too large to convert to short"); + } + return (short)-1; + } + return (short)val; + } + return (short)__Pyx_PyInt_AsLong(x); +} + +static CYTHON_INLINE int __Pyx_PyInt_AsInt(PyObject* x) { + const int neg_one = (int)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; + if (sizeof(int) < sizeof(long)) { + long val = __Pyx_PyInt_AsLong(x); + if (unlikely(val != (long)(int)val)) { + if (!unlikely(val == -1 && PyErr_Occurred())) { + PyErr_SetString(PyExc_OverflowError, + (is_unsigned && unlikely(val < 0)) ? + "can't convert negative value to int" : + "value too large to convert to int"); + } + return (int)-1; + } + return (int)val; + } + return (int)__Pyx_PyInt_AsLong(x); +} + +static CYTHON_INLINE signed char __Pyx_PyInt_AsSignedChar(PyObject* x) { + const signed char neg_one = (signed char)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; + if (sizeof(signed char) < sizeof(long)) { + long val = __Pyx_PyInt_AsLong(x); + if (unlikely(val != (long)(signed char)val)) { + if (!unlikely(val == -1 && PyErr_Occurred())) { + PyErr_SetString(PyExc_OverflowError, + (is_unsigned && unlikely(val < 0)) ? + "can't convert negative value to signed char" : + "value too large to convert to signed char"); + } + return (signed char)-1; + } + return (signed char)val; + } + return (signed char)__Pyx_PyInt_AsSignedLong(x); +} + +static CYTHON_INLINE signed short __Pyx_PyInt_AsSignedShort(PyObject* x) { + const signed short neg_one = (signed short)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; + if (sizeof(signed short) < sizeof(long)) { + long val = __Pyx_PyInt_AsLong(x); + if (unlikely(val != (long)(signed short)val)) { + if (!unlikely(val == -1 && PyErr_Occurred())) { + PyErr_SetString(PyExc_OverflowError, + (is_unsigned && unlikely(val < 0)) ? + "can't convert negative value to signed short" : + "value too large to convert to signed short"); + } + return (signed short)-1; + } + return (signed short)val; + } + return (signed short)__Pyx_PyInt_AsSignedLong(x); +} + +static CYTHON_INLINE signed int __Pyx_PyInt_AsSignedInt(PyObject* x) { + const signed int neg_one = (signed int)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; + if (sizeof(signed int) < sizeof(long)) { + long val = __Pyx_PyInt_AsLong(x); + if (unlikely(val != (long)(signed int)val)) { + if (!unlikely(val == -1 && PyErr_Occurred())) { + PyErr_SetString(PyExc_OverflowError, + (is_unsigned && unlikely(val < 0)) ? + "can't convert negative value to signed int" : + "value too large to convert to signed int"); + } + return (signed int)-1; + } + return (signed int)val; + } + return (signed int)__Pyx_PyInt_AsSignedLong(x); +} + +static CYTHON_INLINE unsigned long __Pyx_PyInt_AsUnsignedLong(PyObject* x) { + const unsigned long neg_one = (unsigned long)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; +#if PY_VERSION_HEX < 0x03000000 + if (likely(PyInt_Check(x))) { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to unsigned long"); + return (unsigned long)-1; + } + return (unsigned long)val; + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { + if (unlikely(Py_SIZE(x) < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to unsigned long"); + return (unsigned long)-1; + } + return PyLong_AsUnsignedLong(x); + } else { + return PyLong_AsLong(x); + } + } else { + unsigned long val; + PyObject *tmp = __Pyx_PyNumber_Int(x); + if (!tmp) return (unsigned long)-1; + val = __Pyx_PyInt_AsUnsignedLong(tmp); + Py_DECREF(tmp); + return val; + } +} + +static CYTHON_INLINE unsigned PY_LONG_LONG __Pyx_PyInt_AsUnsignedLongLong(PyObject* x) { + const unsigned PY_LONG_LONG neg_one = (unsigned PY_LONG_LONG)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; +#if PY_VERSION_HEX < 0x03000000 + if (likely(PyInt_Check(x))) { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to unsigned PY_LONG_LONG"); + return (unsigned PY_LONG_LONG)-1; + } + return (unsigned PY_LONG_LONG)val; + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { + if (unlikely(Py_SIZE(x) < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to unsigned PY_LONG_LONG"); + return (unsigned PY_LONG_LONG)-1; + } + return PyLong_AsUnsignedLongLong(x); + } else { + return PyLong_AsLongLong(x); + } + } else { + unsigned PY_LONG_LONG val; + PyObject *tmp = __Pyx_PyNumber_Int(x); + if (!tmp) return (unsigned PY_LONG_LONG)-1; + val = __Pyx_PyInt_AsUnsignedLongLong(tmp); + Py_DECREF(tmp); + return val; + } +} + +static CYTHON_INLINE long __Pyx_PyInt_AsLong(PyObject* x) { + const long neg_one = (long)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; +#if PY_VERSION_HEX < 0x03000000 + if (likely(PyInt_Check(x))) { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to long"); + return (long)-1; + } + return (long)val; + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { + if (unlikely(Py_SIZE(x) < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to long"); + return (long)-1; + } + return PyLong_AsUnsignedLong(x); + } else { + return PyLong_AsLong(x); + } + } else { + long val; + PyObject *tmp = __Pyx_PyNumber_Int(x); + if (!tmp) return (long)-1; + val = __Pyx_PyInt_AsLong(tmp); + Py_DECREF(tmp); + return val; + } +} + +static CYTHON_INLINE PY_LONG_LONG __Pyx_PyInt_AsLongLong(PyObject* x) { + const PY_LONG_LONG neg_one = (PY_LONG_LONG)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; +#if PY_VERSION_HEX < 0x03000000 + if (likely(PyInt_Check(x))) { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to PY_LONG_LONG"); + return (PY_LONG_LONG)-1; + } + return (PY_LONG_LONG)val; + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { + if (unlikely(Py_SIZE(x) < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to PY_LONG_LONG"); + return (PY_LONG_LONG)-1; + } + return PyLong_AsUnsignedLongLong(x); + } else { + return PyLong_AsLongLong(x); + } + } else { + PY_LONG_LONG val; + PyObject *tmp = __Pyx_PyNumber_Int(x); + if (!tmp) return (PY_LONG_LONG)-1; + val = __Pyx_PyInt_AsLongLong(tmp); + Py_DECREF(tmp); + return val; + } +} + +static CYTHON_INLINE signed long __Pyx_PyInt_AsSignedLong(PyObject* x) { + const signed long neg_one = (signed long)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; +#if PY_VERSION_HEX < 0x03000000 + if (likely(PyInt_Check(x))) { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to signed long"); + return (signed long)-1; + } + return (signed long)val; + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { + if (unlikely(Py_SIZE(x) < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to signed long"); + return (signed long)-1; + } + return PyLong_AsUnsignedLong(x); + } else { + return PyLong_AsLong(x); + } + } else { + signed long val; + PyObject *tmp = __Pyx_PyNumber_Int(x); + if (!tmp) return (signed long)-1; + val = __Pyx_PyInt_AsSignedLong(tmp); + Py_DECREF(tmp); + return val; + } +} + +static CYTHON_INLINE signed PY_LONG_LONG __Pyx_PyInt_AsSignedLongLong(PyObject* x) { + const signed PY_LONG_LONG neg_one = (signed PY_LONG_LONG)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; +#if PY_VERSION_HEX < 0x03000000 + if (likely(PyInt_Check(x))) { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to signed PY_LONG_LONG"); + return (signed PY_LONG_LONG)-1; + } + return (signed PY_LONG_LONG)val; + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { + if (unlikely(Py_SIZE(x) < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to signed PY_LONG_LONG"); + return (signed PY_LONG_LONG)-1; + } + return PyLong_AsUnsignedLongLong(x); + } else { + return PyLong_AsLongLong(x); + } + } else { + signed PY_LONG_LONG val; + PyObject *tmp = __Pyx_PyNumber_Int(x); + if (!tmp) return (signed PY_LONG_LONG)-1; + val = __Pyx_PyInt_AsSignedLongLong(tmp); + Py_DECREF(tmp); + return val; + } +} + +#ifndef __PYX_HAVE_RT_ImportType +#define __PYX_HAVE_RT_ImportType +static PyTypeObject *__Pyx_ImportType(const char *module_name, const char *class_name, + long size, int strict) +{ + PyObject *py_module = 0; + PyObject *result = 0; + PyObject *py_name = 0; + char warning[200]; + + py_module = __Pyx_ImportModule(module_name); + if (!py_module) + goto bad; + #if PY_MAJOR_VERSION < 3 + py_name = PyString_FromString(class_name); + #else + py_name = PyUnicode_FromString(class_name); + #endif + if (!py_name) + goto bad; + result = PyObject_GetAttr(py_module, py_name); + Py_DECREF(py_name); + py_name = 0; + Py_DECREF(py_module); + py_module = 0; + if (!result) + goto bad; + if (!PyType_Check(result)) { + PyErr_Format(PyExc_TypeError, + "%s.%s is not a type object", + module_name, class_name); + goto bad; + } + if (!strict && ((PyTypeObject *)result)->tp_basicsize > size) { + PyOS_snprintf(warning, sizeof(warning), + "%s.%s size changed, may indicate binary incompatibility", + module_name, class_name); + PyErr_WarnEx(NULL, warning, 0); + } + else if (((PyTypeObject *)result)->tp_basicsize != size) { + PyErr_Format(PyExc_ValueError, + "%s.%s has the wrong size, try recompiling", + module_name, class_name); + goto bad; + } + return (PyTypeObject *)result; +bad: + Py_XDECREF(py_module); + Py_XDECREF(result); + return 0; +} +#endif + +#ifndef __PYX_HAVE_RT_ImportModule +#define __PYX_HAVE_RT_ImportModule +static PyObject *__Pyx_ImportModule(const char *name) { + PyObject *py_name = 0; + PyObject *py_module = 0; + + #if PY_MAJOR_VERSION < 3 + py_name = PyString_FromString(name); + #else + py_name = PyUnicode_FromString(name); + #endif + if (!py_name) + goto bad; + py_module = PyImport_Import(py_name); + Py_DECREF(py_name); + return py_module; +bad: + Py_XDECREF(py_name); + return 0; +} +#endif + +#include "compile.h" +#include "frameobject.h" +#include "traceback.h" + +static void __Pyx_AddTraceback(const char *funcname) { + PyObject *py_srcfile = 0; + PyObject *py_funcname = 0; + PyObject *py_globals = 0; + PyCodeObject *py_code = 0; + PyFrameObject *py_frame = 0; + + #if PY_MAJOR_VERSION < 3 + py_srcfile = PyString_FromString(__pyx_filename); + #else + py_srcfile = PyUnicode_FromString(__pyx_filename); + #endif + if (!py_srcfile) goto bad; + if (__pyx_clineno) { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, __pyx_clineno); + #else + py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, __pyx_clineno); + #endif + } + else { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromString(funcname); + #else + py_funcname = PyUnicode_FromString(funcname); + #endif + } + if (!py_funcname) goto bad; + py_globals = PyModule_GetDict(__pyx_m); + if (!py_globals) goto bad; + py_code = PyCode_New( + 0, /*int argcount,*/ + #if PY_MAJOR_VERSION >= 3 + 0, /*int kwonlyargcount,*/ + #endif + 0, /*int nlocals,*/ + 0, /*int stacksize,*/ + 0, /*int flags,*/ + __pyx_empty_bytes, /*PyObject *code,*/ + __pyx_empty_tuple, /*PyObject *consts,*/ + __pyx_empty_tuple, /*PyObject *names,*/ + __pyx_empty_tuple, /*PyObject *varnames,*/ + __pyx_empty_tuple, /*PyObject *freevars,*/ + __pyx_empty_tuple, /*PyObject *cellvars,*/ + py_srcfile, /*PyObject *filename,*/ + py_funcname, /*PyObject *name,*/ + __pyx_lineno, /*int firstlineno,*/ + __pyx_empty_bytes /*PyObject *lnotab*/ + ); + if (!py_code) goto bad; + py_frame = PyFrame_New( + PyThreadState_GET(), /*PyThreadState *tstate,*/ + py_code, /*PyCodeObject *code,*/ + py_globals, /*PyObject *globals,*/ + 0 /*PyObject *locals*/ + ); + if (!py_frame) goto bad; + py_frame->f_lineno = __pyx_lineno; + PyTraceBack_Here(py_frame); +bad: + Py_XDECREF(py_srcfile); + Py_XDECREF(py_funcname); + Py_XDECREF(py_code); + Py_XDECREF(py_frame); +} + +static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { + while (t->p) { + #if PY_MAJOR_VERSION < 3 + if (t->is_unicode) { + *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); + } else if (t->intern) { + *t->p = PyString_InternFromString(t->s); + } else { + *t->p = PyString_FromStringAndSize(t->s, t->n - 1); + } + #else /* Python 3+ has unicode identifiers */ + if (t->is_unicode | t->is_str) { + if (t->intern) { + *t->p = PyUnicode_InternFromString(t->s); + } else if (t->encoding) { + *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); + } else { + *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); + } + } else { + *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); + } + #endif + if (!*t->p) + return -1; + ++t; + } + return 0; +} + +/* Type Conversion Functions */ + +static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) { + if (x == Py_True) return 1; + else if ((x == Py_False) | (x == Py_None)) return 0; + else return PyObject_IsTrue(x); +} + +static CYTHON_INLINE PyObject* __Pyx_PyNumber_Int(PyObject* x) { + PyNumberMethods *m; + const char *name = NULL; + PyObject *res = NULL; +#if PY_VERSION_HEX < 0x03000000 + if (PyInt_Check(x) || PyLong_Check(x)) +#else + if (PyLong_Check(x)) +#endif + return Py_INCREF(x), x; + m = Py_TYPE(x)->tp_as_number; +#if PY_VERSION_HEX < 0x03000000 + if (m && m->nb_int) { + name = "int"; + res = PyNumber_Int(x); + } + else if (m && m->nb_long) { + name = "long"; + res = PyNumber_Long(x); + } +#else + if (m && m->nb_int) { + name = "int"; + res = PyNumber_Long(x); + } +#endif + if (res) { +#if PY_VERSION_HEX < 0x03000000 + if (!PyInt_Check(res) && !PyLong_Check(res)) { +#else + if (!PyLong_Check(res)) { +#endif + PyErr_Format(PyExc_TypeError, + "__%s__ returned non-%s (type %.200s)", + name, name, Py_TYPE(res)->tp_name); + Py_DECREF(res); + return NULL; + } + } + else if (!PyErr_Occurred()) { + PyErr_SetString(PyExc_TypeError, + "an integer is required"); + } + return res; +} + +static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { + Py_ssize_t ival; + PyObject* x = PyNumber_Index(b); + if (!x) return -1; + ival = PyInt_AsSsize_t(x); + Py_DECREF(x); + return ival; +} + +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) { +#if PY_VERSION_HEX < 0x02050000 + if (ival <= LONG_MAX) + return PyInt_FromLong((long)ival); + else { + unsigned char *bytes = (unsigned char *) &ival; + int one = 1; int little = (int)*(unsigned char*)&one; + return _PyLong_FromByteArray(bytes, sizeof(size_t), little, 0); + } +#else + return PyInt_FromSize_t(ival); +#endif +} + +static CYTHON_INLINE size_t __Pyx_PyInt_AsSize_t(PyObject* x) { + unsigned PY_LONG_LONG val = __Pyx_PyInt_AsUnsignedLongLong(x); + if (unlikely(val == (unsigned PY_LONG_LONG)-1 && PyErr_Occurred())) { + return (size_t)-1; + } else if (unlikely(val != (unsigned PY_LONG_LONG)(size_t)val)) { + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to size_t"); + return (size_t)-1; + } + return (size_t)val; +} + + +#endif /* Py_PYTHON_H */ Added: trunk/scipy/signal/spectral.pyx =================================================================== --- trunk/scipy/signal/spectral.pyx (rev 0) +++ trunk/scipy/signal/spectral.pyx 2011-02-13 04:48:40 UTC (rev 7141) @@ -0,0 +1,164 @@ +# Author: Pim Schellart +# 2010 - 2011 + +"""Tools for spectral analysis of unequally sampled signals.""" + +import numpy as np +cimport numpy as np +cimport cython + +cdef extern from "math.h": + double cos(double) + double sin(double) + double atan(double) + + at cython.boundscheck(False) +def lombscargle(np.ndarray[np.float64_t, ndim=1] x, + np.ndarray[np.float64_t, ndim=1] y, + np.ndarray[np.float64_t, ndim=1] freqs): + """Computes the Lomb-Scargle periodogram. + + The Lomb-Scargle periodogram was developed by Lomb [1]_ and further + extended by Scargle [2]_ to find, and test the significance of weak + periodic signals with uneven temporal sampling. + + The computed periodogram is unnormalized, it takes the value + ``(A**2) * N/4`` for a harmonic signal with amplitude A for sufficiently + large N. + + Parameters + ---------- + x : array_like + Sample times. + y : array_like + Measurement values. + freqs : array_like + Angular frequencies for output periodogram. + + Returns + ------- + pgram : array_like + Lomb-Scargle periodogram. + + Raises + ------ + ValueError + If the input arrays `x` and `y` do not have the same shape. + + Notes + ----- + This subroutine calculates the periodogram using a slightly + modified algorithm due to Townsend [3]_ which allows the + periodogram to be calculated using only a single pass through + the input arrays for each frequency. + + The algorithm running time scales roughly as O(x * freqs) or O(N^2) + for a large number of samples and frequencies. + + References + ---------- + .. [1] N.R. Lomb "Least-squares frequency analysis of unequally spaced + data", Astrophysics and Space Science, vol 39, pp. 447-462, 1976 + + .. [2] J.D. Scargle "Studies in astronomical time series analysis. II - + Statistical aspects of spectral analysis of unevenly spaced data", + The Astrophysical Journal, vol 263, pp. 835-853, 1982 + + .. [3] R.H.D. Townsend, "Fast calculation of the Lomb-Scargle + periodogram using graphics processing units.", The Astrophysical + Journal Supplement Series, vol 191, pp. 247-253, 2010 + + Examples + -------- + >>> import scipy.signal + + First define some input parameters for the signal: + + >>> A = 2. + >>> w = 1. + >>> phi = 0.5 * np.pi + >>> nin = 1000 + >>> nout = 100000 + >>> frac_points = 0.9 # Fraction of points to select + + Randomly select a fraction of an array with timesteps: + + >>> r = np.random.rand(nin) + >>> x = np.linspace(0.01, 10*np.pi, nin) + >>> x = x[r >= frac_points] + >>> normval = x.shape[0] # For normalization of the periodogram + + Plot a sine wave for the selected times: + + >>> y = A * np.sin(w*x+phi) + + Define the array of frequencies for which to compute the periodogram: + + >>> f = np.linspace(0.01, 10, nout) + + Calculate Lomb-Scargle periodogram: + + >>> pgram = sp.signal.lombscargle(x, y, f) + + Now make a plot of the input data: + + >>> plt.subplot(2, 1, 1) + + >>> plt.plot(x, y, 'b+') + [] + + Then plot the normalized periodogram: + + >>> plt.subplot(2, 1, 2) + + >>> plt.plot(f, np.sqrt(4*(pgram/normval))) + [] + >>> plt.show() + + """ + + # Check input sizes + if x.shape[0] != y.shape[0]: + raise ValueError("Input arrays do not have the same size.") + + # Create empty array for output periodogram + pgram = np.empty(freqs.shape[0], dtype=np.float64) + + # Local variables + cdef Py_ssize_t i, j + cdef double c, s, xc, xs, cc, ss, cs + cdef double tau, c_tau, s_tau, c_tau2, s_tau2, cs_tau + + for i in range(freqs.shape[0]): + + xc = 0. + xs = 0. + cc = 0. + ss = 0. + cs = 0. + + for j in range(x.shape[0]): + + c = cos(freqs[i] * x[j]) + s = sin(freqs[i] * x[j]) + + xc += y[j] * c + xs += y[j] * s + cc += c * c + ss += s * s + cs += c * s + + tau = atan(2 * cs / (cc - ss)) / (2 * freqs[i]) + c_tau = cos(freqs[i] * tau) + s_tau = sin(freqs[i] * tau) + c_tau2 = c_tau * c_tau + s_tau2 = s_tau * s_tau + cs_tau = 2 * c_tau * s_tau + + pgram[i] = 0.5 * (((c_tau * xc + s_tau * xs)**2 / \ + (c_tau2 * cc + cs_tau * cs + s_tau2 * ss)) + \ + ((c_tau * xs - s_tau * xc)**2 / \ + (c_tau2 * ss - cs_tau * cs + s_tau2 * cc))) + + return pgram + Added: trunk/scipy/signal/tests/test_spectral.py =================================================================== --- trunk/scipy/signal/tests/test_spectral.py (rev 0) +++ trunk/scipy/signal/tests/test_spectral.py 2011-02-13 04:48:40 UTC (rev 7141) @@ -0,0 +1,95 @@ +"""Unit tests for Lomb Scargle routines. +""" + +import numpy as np +from numpy.testing import dec, assert_raises, assert_equal, \ + assert_almost_equal, assert_array_equal, \ + assert_array_almost_equal, assert_approx_equal, \ + assert_, run_module_suite + +from scipy.signal.spectral import lombscargle + + +class TestLombscargle: + def test_frequency(self): + """Test if frequency location of peak corresponds to frequency of + generated input signal. + """ + + # Input parameters + ampl = 2. + w = 1. + phi = 0.5 * np.pi + nin = 100 + nout = 1000 + p = 0.7 # Fraction of points to select + + # Randomly select a fraction of an array with timesteps + np.random.seed(2353425) + r = np.random.rand(nin) + t = np.linspace(0.01*np.pi, 10.*np.pi, nin)[r >= p] + + # Plot a sine wave for the selected times + x = ampl * np.sin(w*t + phi) + + # Define the array of frequencies for which to compute the periodogram + f = np.linspace(0.01, 10., nout) + + # Calculate Lomb-Scargle periodogram + P = lombscargle(t, x, f) + + # Check if difference between found frequency maximum and input + # frequency is less than accuracy + delta = f[1] - f[0] + assert_(w - f[np.argmax(P)] < (delta/2.)) + + def test_amplitude(self): + """Test if height of peak in normalized Lomb-Scargle periodogram + corresponds to amplitude of the generated input signal. + """ + + # Input parameters + ampl = 2. + w = 1. + phi = 0.5 * np.pi + nin = 100 + nout = 1000 + p = 0.7 # Fraction of points to select + + # Randomly select a fraction of an array with timesteps + np.random.seed(2353425) + r = np.random.rand(nin) + t = np.linspace(0.01*np.pi, 10.*np.pi, nin)[r >= p] + + # Plot a sine wave for the selected times + x = ampl * np.sin(w*t + phi) + + # Define the array of frequencies for which to compute the periodogram + f = np.linspace(0.01, 10., nout) + + # Calculate Lomb-Scargle periodogram + pgram = lombscargle(t, x, f) + + # Normalize + pgram = np.sqrt(4 * pgram / t.shape[0]) + + # Check if difference between found frequency maximum and input + # frequency is less than accuracy + assert_approx_equal(np.max(pgram), ampl, significant=2) + + def test_wrong_shape(self): + t = np.linspace(0, 1, 1) + x = np.linspace(0, 1, 2) + f = np.linspace(0, 1, 3) + assert_raises(ValueError, lombscargle, t, x, f) + + def test_zero_division(self): + t = np.zeros(1) + x = np.zeros(1) + f = np.zeros(1) + assert_raises(ZeroDivisionError, lombscargle, t, x, f) + + +if __name__ == "__main__": + run_module_suite() + From scipy-svn at scipy.org Sun Feb 13 07:25:20 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 13 Feb 2011 06:25:20 -0600 (CST) Subject: [Scipy-svn] r7142 - trunk/scipy/stats Message-ID: <20110213122520.D94DA37A551@scipy.org> Author: rgommers Date: 2011-02-13 06:25:19 -0600 (Sun, 13 Feb 2011) New Revision: 7142 Modified: trunk/scipy/stats/distributions.py Log: BUG: do not use "%" in distribution docstrings, it messes up string substitution. Modified: trunk/scipy/stats/distributions.py =================================================================== --- trunk/scipy/stats/distributions.py 2011-02-13 04:48:40 UTC (rev 7141) +++ trunk/scipy/stats/distributions.py 2011-02-13 12:25:19 UTC (rev 7142) @@ -38,14 +38,14 @@ if (n==0): return 1.0 elif (n==1): - if mu is None: + if mu is None: val = moment_func(1,*args) else: val = mu elif (n==2): if mu2 is None or mu is None: val = moment_func(2,*args) - else: + else: val = mu2 + mu*mu elif (n==3): if g1 is None or mu2 is None or mu is None: @@ -217,12 +217,12 @@ """ _doc_interval = \ """interval(alpha, %(shapes)s, loc=0, scale=1) - Endpoints of the range that contains alpha %% of the distribution + Endpoints of the range that contains alpha percent of the distribution """ _doc_allmethods = ''.join([docheaders['methods'], _doc_rvs, _doc_pdf, - _doc_logpdf, _doc_cdf, _doc_logcdf, _doc_sf, + _doc_logpdf, _doc_cdf, _doc_logcdf, _doc_sf, _doc_logsf, _doc_ppf, _doc_isf, _doc_moment, - _doc_stats, _doc_entropy, _doc_fit, + _doc_stats, _doc_entropy, _doc_fit, _doc_expect, _doc_median, _doc_mean, _doc_var, _doc_std, _doc_interval]) @@ -332,7 +332,7 @@ docdict_discrete['pmf'] = _doc_pmf docdict_discrete['logpmf'] = _doc_logpmf docdict_discrete['expect'] = _doc_expect_discrete -_doc_disc_methods = ['rvs', 'pmf', 'logpmf', 'cdf', 'logcdf', 'sf', 'logsf', +_doc_disc_methods = ['rvs', 'pmf', 'logpmf', 'cdf', 'logcdf', 'sf', 'logsf', 'ppf', 'isf', 'stats', 'entropy', 'fit', 'expect', 'median', 'mean', 'var', 'std', 'interval'] for obj in _doc_disc_methods: @@ -436,7 +436,7 @@ def cdf(self, x): return self.dist.cdf(x, *self.args, **self.kwds) - + def logcdf(self, x): return self.dist.logcdf(x, *self.args, **self.kwds) @@ -915,7 +915,7 @@ fit(data, , loc=0, scale=1) Parameter estimates for generic data - expect(func=None, args=(), loc=0, scale=1, lb=None, ub=None, + expect(func=None, args=(), loc=0, scale=1, lb=None, ub=None, conditional=False, **kwds) Expected value of a function with respect to the distribution. Additional kwd arguments passed to integrate.quad @@ -925,21 +925,21 @@ mean(, loc=0, scale=1) Mean of the distribution. - + std(, loc=0, scale=1) Standard deviation of the distribution. var(, loc=0, scale=1) Variance of the distribution. - + interval(alpha, , loc=0, scale=1) - Interval that with (alpha)% probability contains a random realization - of this distribution. + Interval that with `alpha` percent probability contains a random + realization of this distribution. __call__(, loc=0, scale=1) - calling a distribution instance creates a frozen RV object with the + Calling a distribution instance creates a frozen RV object with the same methods but holding the given shape, location, and scale fixed. - see Notes section + See Notes section. **Parameters for Methods** @@ -1000,7 +1000,7 @@ and re-defining at least the _pdf or the _cdf method (normalized to location 0 and scale 1) - which will be given clean arguments (in between a and b) and + which will be given clean arguments (in between a and b) and passing the argument check method If postive argument checking is not correct for your RV @@ -1721,7 +1721,7 @@ valk = _moment_from_stats(k, mu, mu2, g1, g2, self._munp, args) result += comb(n,k,exact=True)*(fac**k) * valk result += fac**n * val - return result * loc**n + return result * loc**n def _nnlf(self, x, *args): return -sum(self._logpdf(x, *args),axis=0) @@ -1752,7 +1752,7 @@ args = (1.0,)*self.numargs return args + self.fit_loc_scale(data, *args) - # Return the (possibly reduced) function to optimize in order to find MLE + # Return the (possibly reduced) function to optimize in order to find MLE # estimates for the .fit method def _reduce_func(self, args, kwds): args = list(args) @@ -1801,8 +1801,8 @@ such. One can hold some parameters fixed to specific values by passing in - keyword arguments ``f0``, ``f1``, ..., ``fn`` (for shape parameters) - and ``floc`` and ``fscale`` (for location and scale parameters, + keyword arguments ``f0``, ``f1``, ..., ``fn`` (for shape parameters) + and ``floc`` and ``fscale`` (for location and scale parameters, respectively). Parameters @@ -1962,8 +1962,8 @@ of the function, conditional on being in the given interval. Additional keyword arguments are passed to the integration routine. - + Returns ------- expected value : float @@ -1973,7 +1973,7 @@ This function has not been checked for it's behavior when the integral is not finite. The integration behavior is inherited from integrate.quad. """ - lockwds = {'loc': loc, + lockwds = {'loc': loc, 'scale':scale} if func is None: def fun(x, *args): @@ -4939,16 +4939,16 @@ generic.mean(, loc=0) Mean of the distribution. - + generic.std(, loc=0) Standard deviation of the distribution. generic.var(, loc=0) Variance of the distribution. - + generic.interval(alpha, , loc=0) - Interval that with (alpha)% probability contains a random realization - of this distribution. + Interval that with `alpha` percent probability contains a random + realization of this distribution. generic(, loc=0) calling a distribution instance returns a frozen distribution @@ -5684,7 +5684,7 @@ valk = _moment_from_stats(k, mu, mu2, g1, g2, self._munp, args) result += comb(n,k,exact=True)*(fac**k) * valk result += fac**n * val - return result * loc**n + return result * loc**n def freeze(self, *args, **kwds): From scipy-svn at scipy.org Sun Feb 13 09:53:16 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 13 Feb 2011 08:53:16 -0600 (CST) Subject: [Scipy-svn] r7143 - in trunk/scipy: integrate interpolate interpolate/src io odr optimize signal weave weave/doc weave/scxx Message-ID: <20110213145316.4F19537B09F@scipy.org> Author: warren.weckesser Date: 2011-02-13 08:53:15 -0600 (Sun, 13 Feb 2011) New Revision: 7143 Modified: trunk/scipy/integrate/multipack.h trunk/scipy/integrate/quadpack.py trunk/scipy/interpolate/fitpack.py trunk/scipy/interpolate/src/multipack.h trunk/scipy/io/idl.py trunk/scipy/odr/__odrpack.c trunk/scipy/odr/odrpack.py trunk/scipy/optimize/minpack.h trunk/scipy/signal/splinemodule.c trunk/scipy/weave/catalog.py trunk/scipy/weave/doc/tutorial.txt trunk/scipy/weave/doc/tutorial_original.html trunk/scipy/weave/ext_tools.py trunk/scipy/weave/inline_tools.py trunk/scipy/weave/scxx/object.h Log: Fixed spelling of 'occurred' and 'occurrence'. Modified: trunk/scipy/integrate/multipack.h =================================================================== --- trunk/scipy/integrate/multipack.h 2011-02-13 12:25:19 UTC (rev 7142) +++ trunk/scipy/integrate/multipack.h 2011-02-13 14:53:15 UTC (rev 7143) @@ -177,7 +177,7 @@ PyErr_Print(); tmpobj = PyObject_GetAttrString(func, "func_name"); if (tmpobj == NULL) goto fail; - str1 = PyString_FromString("Error occured while calling the Python function named "); + str1 = PyString_FromString("Error occurred while calling the Python function named "); if (str1 == NULL) { Py_DECREF(tmpobj); goto fail;} PyString_ConcatAndDel(&str1, tmpobj); PyErr_SetString(error_obj, PyString_AsString(str1)); Modified: trunk/scipy/integrate/quadpack.py =================================================================== --- trunk/scipy/integrate/quadpack.py 2011-02-13 12:25:19 UTC (rev 7142) +++ trunk/scipy/integrate/quadpack.py 2011-02-13 14:53:15 UTC (rev 7143) @@ -252,7 +252,7 @@ msgs = {80: "A Python error occurred possibly while calling the function.", 1: "The maximum number of subdivisions (%d) has been achieved.\n If increasing the limit yields no improvement it is advised to analyze \n the integrand in order to determine the difficulties. If the position of a \n local difficulty can be determined (singularity, discontinuity) one will \n probably gain from splitting up the interval and calling the integrator \n on the subranges. Perhaps a special-purpose integrator should be used." % limit, - 2: "The ocurrence of roundoff error is detected, which prevents \n the requested tolerance from being achieved. The error may be \n underestimated.", + 2: "The occurrence of roundoff error is detected, which prevents \n the requested tolerance from being achieved. The error may be \n underestimated.", 3: "Extremely bad integrand behavior occurs at some points of the\n integration interval.", 4: "The algorithm does not converge. Roundoff error is detected\n in the extrapolation table. It is assumed that the requested tolerance\n cannot be achieved, and that the returned result (if full_output = 1) is \n the best which can be obtained.", 5: "The integral is probably divergent, or slowly convergent.", Modified: trunk/scipy/interpolate/fitpack.py =================================================================== --- trunk/scipy/interpolate/fitpack.py 2011-02-13 12:25:19 UTC (rev 7142) +++ trunk/scipy/interpolate/fitpack.py 2011-02-13 14:53:15 UTC (rev 7143) @@ -98,7 +98,7 @@ the minimal least-squares solution of a rank deficient system of linear equations.""",ValueError], 'unknown':["""\ - An error occured""",TypeError]} + An error occurred""",TypeError]} _parcur_cache = {'t': array([],float), 'wrk': array([],float), 'iwrk':array([],int32), 'u': array([],float),'ub':0,'ue':1} Modified: trunk/scipy/interpolate/src/multipack.h =================================================================== --- trunk/scipy/interpolate/src/multipack.h 2011-02-13 12:25:19 UTC (rev 7142) +++ trunk/scipy/interpolate/src/multipack.h 2011-02-13 14:53:15 UTC (rev 7143) @@ -193,7 +193,7 @@ PyErr_Print(); tmpobj = PyObject_GetAttrString(func, "func_name"); if (tmpobj == NULL) goto fail; - str1 = PyString_FromString("Error occured while calling the Python function named "); + str1 = PyString_FromString("Error occurred while calling the Python function named "); if (str1 == NULL) { Py_DECREF(tmpobj); goto fail;} PyString_ConcatAndDel(&str1, tmpobj); PyErr_SetString(error_obj, PyString_AsString(str1)); Modified: trunk/scipy/io/idl.py =================================================================== --- trunk/scipy/io/idl.py 2011-02-13 12:25:19 UTC (rev 7142) +++ trunk/scipy/io/idl.py 2011-02-13 14:53:15 UTC (rev 7143) @@ -176,7 +176,7 @@ '''Read a variable with a specified data type''' if dtype==1: if _read_int32(f) <> 1: - raise Exception("Error occured while reading byte variable") + raise Exception("Error occurred while reading byte variable") return _read_byte(f) elif dtype==2: return _read_int16(f) @@ -265,7 +265,7 @@ if typecode == 1: nbytes = _read_int32(f) if nbytes <> array_desc['nbytes']: - raise Exception("Error occured while reading byte array") + raise Exception("Error occurred while reading byte array") # Read bytes as numpy array array = np.fromstring(f.read(array_desc['nbytes']), \ Modified: trunk/scipy/odr/__odrpack.c =================================================================== --- trunk/scipy/odr/__odrpack.c 2011-02-13 12:25:19 UTC (rev 7142) +++ trunk/scipy/odr/__odrpack.c 2011-02-13 14:53:15 UTC (rev 7143) @@ -116,7 +116,7 @@ str1 = PyString_FromString - ("Error occured while calling the Python function named "); + ("Error occurred while calling the Python function named "); if (str1 == NULL) { Py_DECREF(tmpobj); @@ -171,7 +171,7 @@ str1 = PyString_FromString - ("Error occured while calling the Python function named "); + ("Error occurred while calling the Python function named "); if (str1 == NULL) { Py_DECREF(tmpobj); @@ -249,7 +249,7 @@ str1 = PyString_FromString - ("Error occured while calling the Python function named "); + ("Error occurred while calling the Python function named "); if (str1 == NULL) { Py_DECREF(tmpobj); Modified: trunk/scipy/odr/odrpack.py =================================================================== --- trunk/scipy/odr/odrpack.py 2011-02-13 12:25:19 UTC (rev 7142) +++ trunk/scipy/odr/odrpack.py 2011-02-13 14:53:15 UTC (rev 7143) @@ -170,7 +170,7 @@ if I[1] != 0: problems.append('Derivatives possibly not correct') if I[2] != 0: - problems.append('Error occured in callback') + problems.append('Error occurred in callback') if I[3] != 0: problems.append('Problem is not full rank at solution') problems.append(stopreason) @@ -204,7 +204,7 @@ elif I[0] == 4: problems.append('Error in derivatives') elif I[0] == 5: - problems.append('Error occured in callback') + problems.append('Error occurred in callback') elif I[0] == 6: problems.append('Numerical error detected') Modified: trunk/scipy/optimize/minpack.h =================================================================== --- trunk/scipy/optimize/minpack.h 2011-02-13 12:25:19 UTC (rev 7142) +++ trunk/scipy/optimize/minpack.h 2011-02-13 14:53:15 UTC (rev 7143) @@ -156,7 +156,7 @@ PyErr_Print(); tmpobj = PyObject_GetAttrString(func, "func_name"); if (tmpobj == NULL) goto fail; - str1 = PyString_FromString("Error occured while calling the Python function named "); + str1 = PyString_FromString("Error occurred while calling the Python function named "); if (str1 == NULL) { Py_DECREF(tmpobj); goto fail;} PyString_ConcatAndDel(&str1, tmpobj); PyErr_SetString(error_obj, PyString_AsString(str1)); Modified: trunk/scipy/signal/splinemodule.c =================================================================== --- trunk/scipy/signal/splinemodule.c 2011-02-13 12:25:19 UTC (rev 7142) +++ trunk/scipy/signal/splinemodule.c 2011-02-13 14:53:15 UTC (rev 7143) @@ -97,7 +97,7 @@ } if (retval == -3) PYERR("Precision too high. Error did not converge."); - if (retval < 0) PYERR("Problem occured inside routine"); + if (retval < 0) PYERR("Problem occurred inside routine"); Py_DECREF(a_image); return PyArray_Return(ck); @@ -156,7 +156,7 @@ } if (retval == -3) PYERR("Precision too high. Error did not converge."); - if (retval < 0) PYERR("Problem occured inside routine"); + if (retval < 0) PYERR("Problem occurred inside routine"); Py_DECREF(a_image); return PyArray_Return(ck); @@ -242,7 +242,7 @@ PYERR("Incorrect type."); } - if (ret < 0) PYERR("Problem occured inside routine."); + if (ret < 0) PYERR("Problem occurred inside routine."); Py_DECREF(a_image); Py_DECREF(a_hrow); @@ -446,7 +446,7 @@ PYERR("Incorrect type."); } - if (ret < 0) PYERR("Problem occured inside routine."); + if (ret < 0) PYERR("Problem occurred inside routine."); Py_DECREF(a_sig); return PyArray_Return(out); Modified: trunk/scipy/weave/catalog.py =================================================================== --- trunk/scipy/weave/catalog.py 2011-02-13 12:25:19 UTC (rev 7142) +++ trunk/scipy/weave/catalog.py 2011-02-13 14:53:15 UTC (rev 7143) @@ -248,7 +248,7 @@ bases the name of the value returned by sys.platform and the version of python being run. If this isn't enough to descriminate on some platforms, we can try to add other info. It has - occured to me that if we get fancy enough to optimize for different + occurred to me that if we get fancy enough to optimize for different architectures, then chip type might be added to the catalog name also. """ version = '%d%d' % sys.version_info[:2] Modified: trunk/scipy/weave/doc/tutorial.txt =================================================================== --- trunk/scipy/weave/doc/tutorial.txt 2011-02-13 12:25:19 UTC (rev 7142) +++ trunk/scipy/weave/doc/tutorial.txt 2011-02-13 14:53:15 UTC (rev 7143) @@ -1165,7 +1165,7 @@ static PyObject* compiled_func(PyObject*self, PyObject* args) { py::object return_val; - int exception_occured = 0; + int exception_occurred = 0; PyObject *py__locals = NULL; PyObject *py__globals = NULL; PyObject *py_a; @@ -1187,10 +1187,10 @@ catch(...) { return_val = py::object(); - exception_occured = 1; + exception_occurred = 1; } /* cleanup code */ - if(!(PyObject*)return_val && !exception_occured) + if(!(PyObject*)return_val && !exception_occurred) { return_val = Py_None; } Modified: trunk/scipy/weave/doc/tutorial_original.html =================================================================== --- trunk/scipy/weave/doc/tutorial_original.html 2011-02-13 12:25:19 UTC (rev 7142) +++ trunk/scipy/weave/doc/tutorial_original.html 2011-02-13 14:53:15 UTC (rev 7143) @@ -1286,7 +1286,7 @@ And here is the extension function generated by inline: 

-static PyObject* compiled_func(PyObject*self, PyObject* args)
{
    py::object return_val;
    int exception_occured = 0;
    PyObject *py__locals = NULL;
    PyObject *py__globals = NULL;
    PyObject *py_a;
    py_a = NULL;

    if(!PyArg_ParseTuple(args,"OO:compiled_func",&py__locals,&py__globals))
        return NULL;
    try
    {
        PyObject* raw_locals = py_to_raw_dict(py__locals,"_locals");
        PyObject* raw_globals = py_to_raw_dict(py__globals,"_globals");
        /* argument conversion code */
        py_a = get_variable("a",raw_locals,raw_globals);
        int a = convert_to_int(py_a,"a");
        /* inline code */
        /* NDARRAY API VERSION 90907 */
        printf("%d\n",a);    /*I would like to fill in changed    locals and globals here...*/

    }
    catch(...)
    {
        return_val =  py::object();
        exception_occured = 1;
    }
    /* cleanup code */
    if(!(PyObject*)return_val && !exception_occured)
    {

        return_val = Py_None;
    }

    return return_val.disown();
}
+static PyObject* compiled_func(PyObject*self, PyObject* args)
{
py::object return_val;
int exception_occurred = 0;
PyObject *py__locals = NULL;
PyObject *py__globals = NULL;
PyObject *py_a;
py_a = NULL;

if(!PyArg_ParseTuple(args,"OO:compiled_func",&py__locals,&py__globals))
return NULL;
try
{
PyObject* raw_locals = py_to_raw_dict(py__locals,"_locals");
PyObject* raw_globals = py_to_raw_dict(py__globals,"_globals");
/* argument conversion code */
py_a = get_variable("a",raw_locals,raw_globals);
int a = convert_to_int(py_a,"a");
/* inline code */
/* NDARRAY API VERSION 90907 */
printf("%d\n",a); /*I would like to fill in changed locals and globals here...*/

}
catch(...)
{
return_val = py::object();
exception_occurred = 1;
}
/* cleanup code */
if(!(PyObject*)return_val && !exception_occurred)
{

return_val = Py_None;
}

return return_val.disown();
}

Every inline function takes exactly two arguments -- the local and global Modified: trunk/scipy/weave/ext_tools.py =================================================================== --- trunk/scipy/weave/ext_tools.py 2011-02-13 12:25:19 UTC (rev 7142) +++ trunk/scipy/weave/ext_tools.py 2011-02-13 14:53:15 UTC (rev 7143) @@ -42,7 +42,7 @@ """ declare_return = 'py::object return_val;\n' \ - 'int exception_occured = 0;\n' \ + 'int exception_occurred = 0;\n' \ 'PyObject *py_local_dict = NULL;\n' arg_string_list = self.arg_specs.variable_as_strings() + ['"local_dict"'] arg_strings = ','.join(arg_string_list) @@ -131,12 +131,12 @@ catch_code = "catch(...) \n" \ "{ \n" + \ " return_val = py::object(); \n" \ - " exception_occured = 1; \n" \ + " exception_occurred = 1; \n" \ "} \n" return_code = " /*cleanup code*/ \n" + \ cleanup_code + \ - ' if(!(PyObject*)return_val && !exception_occured)\n' \ + ' if(!(PyObject*)return_val && !exception_occurred)\n' \ ' {\n \n' \ ' return_val = Py_None; \n' \ ' }\n \n' \ Modified: trunk/scipy/weave/inline_tools.py =================================================================== --- trunk/scipy/weave/inline_tools.py 2011-02-13 12:25:19 UTC (rev 7142) +++ trunk/scipy/weave/inline_tools.py 2011-02-13 14:53:15 UTC (rev 7143) @@ -32,7 +32,7 @@ This code got a lot uglier when I added local_dict... """ declare_return = 'py::object return_val;\n' \ - 'int exception_occured = 0;\n' \ + 'int exception_occurred = 0;\n' \ 'PyObject *py__locals = NULL;\n' \ 'PyObject *py__globals = NULL;\n' @@ -100,11 +100,11 @@ catch_code = "catch(...) \n" \ "{ \n" + \ " return_val = py::object(); \n" \ - " exception_occured = 1; \n" \ + " exception_occurred = 1; \n" \ "} \n" return_code = " /* cleanup code */ \n" + \ cleanup_code + \ - " if(!(PyObject*)return_val && !exception_occured)\n" \ + " if(!(PyObject*)return_val && !exception_occurred)\n" \ " {\n \n" \ " return_val = Py_None; \n" \ " }\n \n" \ Modified: trunk/scipy/weave/scxx/object.h =================================================================== --- trunk/scipy/weave/scxx/object.h 2011-02-13 12:25:19 UTC (rev 7142) +++ trunk/scipy/weave/scxx/object.h 2011-02-13 14:53:15 UTC (rev 7143) @@ -617,7 +617,7 @@ object method = attr(nm); PyObject* result = PyEval_CallObjectWithKeywords(method,NULL,NULL); if (!result) - throw 1; // signal exception has occured. + throw 1; // signal exception has occurred. return object(lose_ref(result)); } @@ -625,7 +625,7 @@ object method = attr(nm); PyObject* result = PyEval_CallObjectWithKeywords(method,args_tup,NULL); if (!result) - throw 1; // signal exception has occured. + throw 1; // signal exception has occurred. return object(lose_ref(result)); } @@ -633,7 +633,7 @@ object method = attr(nm); PyObject* result = PyEval_CallObjectWithKeywords(method,args_tup,kw_dict); if (!result) - throw 1; // signal exception has occured. + throw 1; // signal exception has occurred. return object(lose_ref(result)); } From scipy-svn at scipy.org Tue Feb 15 14:22:32 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Tue, 15 Feb 2011 13:22:32 -0600 (CST) Subject: [Scipy-svn] r7144 - trunk/scipy/special Message-ID: <20110215192232.F33896EFD1@scipy.org> Author: ptvirtan Date: 2011-02-15 13:22:32 -0600 (Tue, 15 Feb 2011) New Revision: 7144 Modified: trunk/scipy/special/amos_wrappers.c Log: BUG: special: fix zbiry prototype to match the Fortran code (#1233) Modified: trunk/scipy/special/amos_wrappers.c =================================================================== --- trunk/scipy/special/amos_wrappers.c 2011-02-13 14:53:15 UTC (rev 7143) +++ trunk/scipy/special/amos_wrappers.c 2011-02-15 19:22:32 UTC (rev 7144) @@ -27,7 +27,7 @@ extern int F_FUNC(zairy,ZAIRY) (double*, double*, int*, int*, double*, double*, int*, int*); extern int F_FUNC(zbiry,ZBIRY) - (double*, double*, int*, int*, double*, double*, int*, int*); + (double*, double*, int*, int*, double*, double*, int*); extern int F_FUNC(zbesi,ZBESI) (double*, double*, double*, int*, int*, double*, double*, int*, int*); extern int F_FUNC(zbesj,ZBESJ) @@ -135,13 +135,15 @@ F_FUNC(zairy,ZAIRY)(CADDR(z), &id, &kode, F2C_CST(ai), &nz, &ierr); DO_MTHERR("airy:", ai); - F_FUNC(zbiry,ZBIRY)(CADDR(z), &id, &kode, F2C_CST(bi), &nz, &ierr); + nz = 0; + F_FUNC(zbiry,ZBIRY)(CADDR(z), &id, &kode, F2C_CST(bi), &ierr); DO_MTHERR("airy:", bi); id = 1; F_FUNC(zairy,ZAIRY)(CADDR(z), &id, &kode, F2C_CST(aip), &nz, &ierr); DO_MTHERR("airy:", aip); - F_FUNC(zbiry,ZBIRY)(CADDR(z), &id, &kode, F2C_CST(bip), &nz, &ierr); + nz = 0; + F_FUNC(zbiry,ZBIRY)(CADDR(z), &id, &kode, F2C_CST(bip), &ierr); DO_MTHERR("airy:", bip); return 0; } @@ -153,13 +155,15 @@ F_FUNC(zairy,ZAIRY)(CADDR(z), &id, &kode, F2C_CST(ai), &nz, &ierr); DO_MTHERR("airye:", ai); - F_FUNC(zbiry,ZBIRY)(CADDR(z), &id, &kode, F2C_CST(bi), &nz, &ierr); + nz = 0; + F_FUNC(zbiry,ZBIRY)(CADDR(z), &id, &kode, F2C_CST(bi), &ierr); DO_MTHERR("airye:", bi); id = 1; F_FUNC(zairy,ZAIRY)(CADDR(z), &id, &kode, F2C_CST(aip), &nz, &ierr); DO_MTHERR("airye:", aip); - F_FUNC(zbiry,ZBIRY)(CADDR(z), &id, &kode, F2C_CST(bip), &nz, &ierr); + nz = 0; + F_FUNC(zbiry,ZBIRY)(CADDR(z), &id, &kode, F2C_CST(bip), &ierr); DO_MTHERR("airye:", bip); return 0; } @@ -180,7 +184,8 @@ DO_MTHERR("airye:", &cai); *ai = cai.real; } - F_FUNC(zbiry,ZBIRY)(CADDR(cz), &id, &kode, CADDR(cbi), &nz, &ierr); + nz = 0; + F_FUNC(zbiry,ZBIRY)(CADDR(cz), &id, &kode, CADDR(cbi), &ierr); DO_MTHERR("airye:", &cbi); *bi = cbi.real; @@ -192,7 +197,8 @@ DO_MTHERR("airye:", &caip); *aip = caip.real; } - F_FUNC(zbiry,ZBIRY)(CADDR(cz), &id, &kode, CADDR(cbip), &nz, &ierr); + nz = 0; + F_FUNC(zbiry,ZBIRY)(CADDR(cz), &id, &kode, CADDR(cbip), &ierr); DO_MTHERR("airye:", &cbip); *bip = cbip.real; return 0; From scipy-svn at scipy.org Wed Feb 16 18:43:55 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Wed, 16 Feb 2011 17:43:55 -0600 (CST) Subject: [Scipy-svn] r7145 - in trunk/scipy/misc: . tests Message-ID: <20110216234355.846E737A18F@scipy.org> Author: warren.weckesser Date: 2011-02-16 17:43:54 -0600 (Wed, 16 Feb 2011) New Revision: 7145 Added: trunk/scipy/misc/tests/test_common.py Modified: trunk/scipy/misc/common.py Log: ENH: misc: In pade(), use 'linalg.solve' instead of multiplying by the inverse (ticket #1387) Modified: trunk/scipy/misc/common.py =================================================================== --- trunk/scipy/misc/common.py 2011-02-15 19:22:32 UTC (rev 7144) +++ trunk/scipy/misc/common.py 2011-02-16 23:43:54 UTC (rev 7145) @@ -323,19 +323,19 @@ from scipy import linalg an = asarray(an) N = len(an) - 1 - n = N-m - if (n < 0): + n = N - m + if n < 0: raise ValueError("Order of q must be smaller than len(an)-1.") - Akj = eye(N+1,n+1) - Bkj = zeros((N+1,m),'d') - for row in range(1,m+1): + Akj = eye(N+1, n+1) + Bkj = zeros((N+1, m), 'd') + for row in range(1, m+1): Bkj[row,:row] = -(an[:row])[::-1] - for row in range(m+1,N+1): + for row in range(m+1, N+1): Bkj[row,:] = -(an[row-m:row])[::-1] - C = hstack((Akj,Bkj)) - pq = dot(linalg.inv(C),an) + C = hstack((Akj, Bkj)) + pq = linalg.solve(C, an) p = pq[:n+1] - q = r_[1.0,pq[n+1:]] + q = r_[1.0, pq[n+1:]] return poly1d(p[::-1]), poly1d(q[::-1]) def lena(): Added: trunk/scipy/misc/tests/test_common.py =================================================================== --- trunk/scipy/misc/tests/test_common.py (rev 0) +++ trunk/scipy/misc/tests/test_common.py 2011-02-16 23:43:54 UTC (rev 7145) @@ -0,0 +1,32 @@ + +from numpy.testing import assert_array_equal, assert_array_almost_equal + +from scipy.misc import pade + + +def test_pade_trivial(): + nump, denomp = pade([1.0], 0) + assert_array_equal(nump.c, [1.0]) + assert_array_equal(denomp.c, [1.0]) + +def test_pade_4term_exp(): + # First four Taylor coefficients of exp(x). + # Unlike poly1d, the first array element is the zero-order term. + an = [1.0, 1.0, 0.5, 1.0/6] + + nump, denomp = pade(an, 0) + assert_array_almost_equal(nump.c, [1.0/6, 0.5, 1.0, 1.0]) + assert_array_almost_equal(denomp.c, [1.0]) + + nump, denomp = pade(an, 1) + assert_array_almost_equal(nump.c, [1.0/6, 2.0/3, 1.0]) + assert_array_almost_equal(denomp.c, [-1.0/3, 1.0]) + + nump, denomp = pade(an, 2) + assert_array_almost_equal(nump.c, [1.0/3, 1.0]) + assert_array_almost_equal(denomp.c, [1.0/6, -2.0/3, 1.0]) + + nump, denomp = pade(an, 3) + assert_array_almost_equal(nump.c, [1.0]) + assert_array_almost_equal(denomp.c, [-1.0/6, 0.5, -1.0, 1.0]) + From scipy-svn at scipy.org Thu Feb 17 14:26:36 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Thu, 17 Feb 2011 13:26:36 -0600 (CST) Subject: [Scipy-svn] r7146 - trunk/doc/source Message-ID: <20110217192636.8DDAB1B8CCE@scipy.org> Author: ptvirtan Date: 2011-02-17 13:26:35 -0600 (Thu, 17 Feb 2011) New Revision: 7146 Modified: trunk/doc/source/interpolate.rst Log: DOC: add RectBivariateSpline to the docs Modified: trunk/doc/source/interpolate.rst =================================================================== --- trunk/doc/source/interpolate.rst 2011-02-16 23:43:54 UTC (rev 7145) +++ trunk/doc/source/interpolate.rst 2011-02-17 19:26:35 UTC (rev 7146) @@ -87,9 +87,18 @@ .. seealso:: scipy.ndimage.map_coordinates +For data on a grid: + .. autosummary:: :toctree: generated/ + RectBivariateSpline + +For unstructured data: + +.. autosummary:: + :toctree: generated/ + BivariateSpline SmoothBivariateSpline LSQBivariateSpline From scipy-svn at scipy.org Sat Feb 19 03:57:32 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sat, 19 Feb 2011 02:57:32 -0600 (CST) Subject: [Scipy-svn] r7147 - in trunk/scipy: misc/tests ndimage spatial/tests Message-ID: <20110219085732.87E113635E@scipy.org> Author: rgommers Date: 2011-02-19 02:57:31 -0600 (Sat, 19 Feb 2011) New Revision: 7147 Modified: trunk/scipy/misc/tests/test_pilutil.py trunk/scipy/ndimage/io.py trunk/scipy/spatial/tests/test_distance.py Log: TST: explicit file close to avoid ResourceWarnings under Python 3.2. Thanks to Christoph Gohlke. Modified: trunk/scipy/misc/tests/test_pilutil.py =================================================================== --- trunk/scipy/misc/tests/test_pilutil.py 2011-02-17 19:26:35 UTC (rev 7146) +++ trunk/scipy/misc/tests/test_pilutil.py 2011-02-19 08:57:31 UTC (rev 7147) @@ -42,7 +42,9 @@ assert_equal(pilutil.bytescale(y),[0,127,255]) def tst_fromimage(filename, irange): - img = pilutil.fromimage(PIL.Image.open(filename)) + fp = open(filename, "rb") + img = pilutil.fromimage(PIL.Image.open(fp)) + fp.close() imin,imax = irange assert_(img.min() >= imin) assert_(img.max() <= imax) Modified: trunk/scipy/ndimage/io.py =================================================================== --- trunk/scipy/ndimage/io.py 2011-02-17 19:26:35 UTC (rev 7146) +++ trunk/scipy/ndimage/io.py 2011-02-19 08:57:31 UTC (rev 7147) @@ -34,8 +34,10 @@ " http://pypi.python.org/pypi/PIL/ for installation" " instructions.") - im = Image.open(fname) + fp = open(fname, "rb") + im = Image.open(fp) if flatten: im = im.convert('F') - return array(im) - + result = array(im) + fp.close() + return result Modified: trunk/scipy/spatial/tests/test_distance.py =================================================================== --- trunk/scipy/spatial/tests/test_distance.py 2011-02-17 19:26:35 UTC (rev 7146) +++ trunk/scipy/spatial/tests/test_distance.py 2011-02-19 08:57:31 UTC (rev 7147) @@ -88,7 +88,9 @@ for fn in _filenames: name = fn.replace(".txt", "").replace("-ml", "") fqfn = os.path.join(os.path.dirname(__file__), fn) - eo[name] = np.loadtxt(open(fqfn)) + fp = open(fqfn) + eo[name] = np.loadtxt(fp) + fp.close() #print "%s: %s %s" % (name, str(eo[name].shape), str(eo[name].dtype)) eo['pdist-boolean-inp'] = np.bool_(eo['pdist-boolean-inp']) From scipy-svn at scipy.org Sat Feb 19 04:11:40 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sat, 19 Feb 2011 03:11:40 -0600 (CST) Subject: [Scipy-svn] r7148 - in trunk: . tools tools/scipy-macosx-installer tools/scipy-macosx-installer/art Message-ID: <20110219091140.9604B3635F@scipy.org> Author: rgommers Date: 2011-02-19 03:11:40 -0600 (Sat, 19 Feb 2011) New Revision: 7148 Added: trunk/release.sh trunk/tools/scipy-macosx-installer/ trunk/tools/scipy-macosx-installer/README.txt trunk/tools/scipy-macosx-installer/art/ trunk/tools/scipy-macosx-installer/art/dmgbackground.png trunk/tools/scipy-macosx-installer/art/dmgbackground.svg trunk/tools/scipy-macosx-installer/new-create-dmg Modified: trunk/pavement.py Log: ENH: copy improvements to release scripts from 0.9.x branch. Modified: trunk/pavement.py =================================================================== --- trunk/pavement.py 2011-02-19 08:57:31 UTC (rev 7147) +++ trunk/pavement.py 2011-02-19 09:11:40 UTC (rev 7148) @@ -4,40 +4,62 @@ independent from the user system as possible (e.g. to make sure the sphinx doc is built against the built scipy, not an installed one). -Building a simple (no-superpack) windows installer from wine -============================================================ +The release is assumed to be done on OS X. See release.sh for a script that +employs the Paver tasks defined in this file, and builds everything required +for a release at once. -It assumes that blas/lapack are in c:\local\lib inside drive_c. Build python -2.5 and python 2.6 installers. +Building a Windows installer from Wine +====================================== + +The Python version the installer is for can be specified with the ``-p 2.6`` +switch (this works for all installer tasks). To build a simple (no SSE +instructions) installer, do:: + paver bdist_wininst_simple -You will have to configure your wine python locations (WINE_PYS). +This assumes that blas/lapack are in c:\local\lib inside drive_c. You will +have to make sure your Wine python locations (WINE_PYS) are configured +correctly. -The superpack requires all the atlas libraries for every arch to be installed +The superpack requires all the Atlas libraries for every arch to be installed (see SITECFG), and can then be built as follows:: paver bdist_superpack + +Building an installer for OS X +============================== + +For a simple installer, which is just an mpkg inside a dmg, do:: + + paver simple_dmg + +For a more fancy installer which includes documentation and looks better, do:: + + paver pdf # needs to be done only once + paver dmg + + Building changelog + notes ========================== Assumes you have git and the binaries/tarballs in installers/:: - paver write_release - paver write_note + paver write_release_and_log This automatically put the checksum into NOTES.txt, and write the Changelog which can be uploaded to sourceforge. + TODO ==== - - the script is messy, lots of global variables - make it more easily customizable (through command line args) - missing targets: install & test, sdist test, debian packaging - fix bdist_mpkg: we build the same source twice -> how to make sure we use the same underlying python for egg install in venv and for bdist_mpkg """ + import os import sys import subprocess @@ -69,68 +91,88 @@ finally: sys.path.pop(0) + +#----------------------------------- +# Things to be changed for a release +#----------------------------------- + +# Source of the release notes +RELEASE = 'doc/release/0.9.0-notes.rst' + +# Start/end of the log (from git) +LOG_START = 'svn/tags/0.8.0' +LOG_END = 'svn/0.9.x' + + +#------------------------------------------------------- +# Hardcoded build/install dirs, virtualenv options, etc. +#------------------------------------------------------- + # Default python version -PYVER="2.5" -DMG_DIR = "dmg-source" +PYVER="2.6" +# Paver options object, holds all default dirs +options(bootstrap=Bunch(bootstrap_dir="bootstrap"), + virtualenv=Bunch(packages_to_install=["sphinx==1.0.4", "numpydoc"], + no_site_packages=False), + sphinx=Bunch(builddir="build", sourcedir="source", docroot='doc'), + superpack=Bunch(builddir="build-superpack", + bindir=os.path.join("build-superpack","binaries")), + installers=Bunch(releasedir="release", + installersdir=os.path.join("release", "installers")), + doc=Bunch(doc_root="doc", + sdir=os.path.join("doc", "source"), + bdir=os.path.join("doc", "build"), + bdir_latex=os.path.join("doc", "build", "latex"), + destdir_pdf=os.path.join("build_doc", "pdf")), + html=Bunch(builddir=os.path.join("build", "html")), + dmg=Bunch(python_version=PYVER), + bdist_wininst_simple=Bunch(python_version=PYVER),) + +# Where we can find BLAS/LAPACK/ATLAS on Windows/Wine +SITECFG = {"sse3" : {'BLAS': 'None', 'LAPACK': 'None', 'ATLAS': r'C:\local\lib\yop\sse3'}, + "sse2" : {'BLAS': 'None', 'LAPACK': 'None', 'ATLAS': r'C:\local\lib\yop\sse2'}, + "nosse" : {'ATLAS': 'None', 'BLAS': r'C:\local\lib\yop\nosse', + 'LAPACK': r'C:\local\lib\yop\nosse'}} + # Wine config for win32 builds if sys.platform == "win32": WINE_PY25 = [r"C:\Python25\python.exe"] WINE_PY26 = [r"C:\Python26\python26.exe"] WINE_PY27 = [r"C:\Python27\python27.exe"] + WINE_PY31 = [r"C:\Python31\python.exe"] + WINDOWS_ENV = os.environ MAKENSIS = ["makensis"] elif sys.platform == "darwin": WINE_PY25 = ["wine", os.environ['HOME'] + "/.wine/drive_c/Python25/python.exe"] WINE_PY26 = ["wine", os.environ['HOME'] + "/.wine/drive_c/Python26/python.exe"] WINE_PY27 = ["wine", os.environ['HOME'] + "/.wine/drive_c/Python27/python.exe"] + WINE_PY31 = ["wine", os.environ['HOME'] + "/.wine/drive_c/Python31/python.exe"] + WINDOWS_ENV = os.environ + WINDOWS_ENV["DYLD_FALLBACK_LIBRARY_PATH"] = "/usr/X11/lib:/usr/lib" MAKENSIS = ["wine", "makensis"] else: WINE_PY25 = [os.environ['HOME'] + "/.wine/drive_c/Python25/python.exe"] WINE_PY26 = [os.environ['HOME'] + "/.wine/drive_c/Python26/python.exe"] WINE_PY27 = [os.environ['HOME'] + "/.wine/drive_c/Python27/python.exe"] + WINE_PY31 = [os.environ['HOME'] + "/.wine/drive_c/Python31/python.exe"], + WINDOWS_ENV = os.environ MAKENSIS = ["wine", "makensis"] -WINE_PYS = {'2.7' : WINE_PY27, '2.6' : WINE_PY26, '2.5': WINE_PY25} -SUPERPACK_BUILD = 'build-superpack' -SUPERPACK_BINDIR = os.path.join(SUPERPACK_BUILD, 'binaries') +WINE_PYS = {'3.1':WINE_PY31, '2.7':WINE_PY27, '2.6':WINE_PY26, '2.5':WINE_PY25} -# XXX: fix this in a sane way +# Framework Python locations on OS X MPKG_PYTHON = {"2.5": "/Library/Frameworks/Python.framework/Versions/2.5/bin/python", "2.6": "/Library/Frameworks/Python.framework/Versions/2.6/bin/python", - "2.7": "/Library/Frameworks/Python.framework/Versions/2.7/bin/python"} + "2.7": "/Library/Frameworks/Python.framework/Versions/2.7/bin/python", + "3.1": "/Library/Frameworks/Python.framework/Versions/3.1/bin/python3"} # Full path to the *static* gfortran runtime LIBGFORTRAN_A_PATH = "/usr/local/lib/libgfortran.a" -# Where to put built documentation (where it will picked up for copy to -# binaries) -PDF_DESTDIR = paver.path.path('build') / 'pdf' -HTML_DESTDIR = paver.path.path('build') / 'html' -DOC_ROOT = paver.path.path("doc") -DOC_SRC = DOC_ROOT / "source" -DOC_BLD = DOC_ROOT / "build" -DOC_BLD_LATEX = DOC_BLD / "latex" -# Source of the release notes -RELEASE = 'doc/release/0.9.0-notes.rst' +#-------------------------------------- +# Utility functions and bootstrap stuff +#-------------------------------------- -# Start/end of the log (from git) -LOG_START = 'svn/tags/0.8.0' -LOG_END = 'master' - -# Virtualenv bootstrap stuff -BOOTSTRAP_DIR = "bootstrap" -BOOTSTRAP_PYEXEC = "%s/bin/python" % BOOTSTRAP_DIR -BOOTSTRAP_SCRIPT = "%s/bootstrap.py" % BOOTSTRAP_DIR - -# Where to put the final installers, as put on sourceforge -RELEASE_DIR = 'release' -INSTALLERS_DIR = os.path.join(RELEASE_DIR, 'installers') - - -options(sphinx=Bunch(builddir="build", sourcedir="source", docroot='doc'), - virtualenv=Bunch(script_name=BOOTSTRAP_SCRIPT, - packages_to_install=["sphinx==1.0.4"]), - wininst=Bunch(pyver=PYVER, scratch=True)) - def parse_numpy_version(pyexec): if isinstance(pyexec, str): cmd = [pyexec, "-c", "'import numpy; print numpy.version.version'"] @@ -151,90 +193,63 @@ else: raise ValueError("Could not parse version (%s)" % out) -# Bootstrap stuff @task def bootstrap(): """create virtualenv in ./install""" - install = paver.path.path(BOOTSTRAP_DIR) - if not install.exists(): - install.mkdir() + try: + import virtualenv + except ImportError, e: + raise RuntimeError("virtualenv is needed for bootstrap") + + bdir = options.bootstrap_dir + if not os.path.exists(bdir): + os.makedirs(bdir) + bscript = "boostrap.py" + + options.virtualenv.script_name = os.path.join(options.bootstrap_dir, + bscript) + options.bootstrap.no_site_packages = False call_task('paver.virtual.bootstrap') - sh('cd %s; %s bootstrap.py' % (BOOTSTRAP_DIR, sys.executable)) + sh('cd %s; %s %s' % (bdir, sys.executable, bscript)) @task def clean(): """Remove build, dist, egg-info garbage.""" d = ['build', 'dist', 'scipy.egg-info'] for i in d: - paver.path.path(i).rmtree() + if os.path.exists(i): + shutil.rmtree(i) - (paver.path.path('doc') / options.sphinx.builddir).rmtree() + bdir = os.path.join('doc', options.sphinx.builddir) + if os.path.exists(bdir): + shutil.rmtree(bdir) @task def clean_bootstrap(): - paver.path.path('bootstrap').rmtree() + bdir = os.path.join(options.bootstrap.bootstrap_dir) + if os.path.exists(bdir): + shutil.rmtree(bdir) @task @needs('clean', 'clean_bootstrap') def nuke(): """Remove everything: build dir, installers, bootstrap dirs, etc...""" - d = [SUPERPACK_BUILD, INSTALLERS_DIR, DMG_DIR] - for i in d: - paver.path.path(i).rmtree() + for d in [options.superpack.builddir, options.installers.releasedir]: + if os.path.exists(d): + shutil.rmtree(d) -# NOTES/Changelog stuff -def compute_md5(): - released = paver.path.path(INSTALLERS_DIR).listdir() - checksums = [] - for f in released: - m = md5.md5(open(f, 'r').read()) - checksums.append('%s %s' % (m.hexdigest(), f)) +#-------------------- +# Documentation tasks +#-------------------- - return checksums - -def write_release_task(filename='NOTES.txt'): - source = paver.path.path(RELEASE) - target = paver.path.path(filename) - if target.exists(): - target.remove() - source.copy(target) - ftarget = open(str(target), 'a') - ftarget.writelines(""" -Checksums -========= - -""") - ftarget.writelines(['%s\n' % c for c in compute_md5()]) - -def write_log_task(filename='Changelog'): - st = subprocess.Popen( - ['git', 'svn', 'log', '%s..%s' % (LOG_START, LOG_END)], - stdout=subprocess.PIPE) - - out = st.communicate()[0] - a = open(filename, 'w') - a.writelines(out) - a.close() - @task -def write_release(): - write_release_task() - - at task -def write_log(): - write_log_task() - -#------------ -# Doc tasks -#------------ - at task def html(options): """Build scipy documentation and put it into build/docs""" # Don't use paver html target because of scipy bootstrapping problems subprocess.check_call(["make", "html"], cwd="doc") builtdocs = paver.path.path("doc") / options.sphinx.builddir / "html" - HTML_DESTDIR.rmtree() - builtdocs.copytree(HTML_DESTDIR) + options.html.builddir.rmtree() + builtdocs.copytree(options.html.builddir) @task def latex(): @@ -244,17 +259,21 @@ @task @needs('latex') def pdf(): + sdir = options.doc.sdir + bdir = options.doc.bdir + bdir_latex = options.doc.bdir_latex + destdir_pdf = options.doc.destdir_pdf + def build_pdf(): - subprocess.check_call(["make", "all-pdf"], cwd=str(DOC_BLD_LATEX)) + subprocess.check_call(["make", "all-pdf"], cwd=str(bdir_latex)) dry("Build pdf doc", build_pdf) - PDF_DESTDIR.rmtree() - PDF_DESTDIR.makedirs() + if os.path.exists(destdir_pdf): + shutil.rmtree(destdir_pdf) + os.makedirs(destdir_pdf) - user = DOC_BLD_LATEX / "scipy-user.pdf" - user.copy(PDF_DESTDIR / "userguide.pdf") - ref = DOC_BLD_LATEX / "scipy-ref.pdf" - ref.copy(PDF_DESTDIR / "reference.pdf") + ref = os.path.join(bdir_latex, "scipy-ref.pdf") + shutil.copy(ref, os.path.join(destdir_pdf, "reference.pdf")) def tarball_name(type='gztar'): root = 'scipy-%s' % FULLVERSION @@ -271,71 +290,47 @@ sh('python setup.py sdist --formats=gztar,zip') # Copy the superpack into installers dir - if not os.path.exists(INSTALLERS_DIR): - os.makedirs(INSTALLERS_DIR) + if not os.path.exists(options.installers.installersdir): + os.makedirs(options.installers.installersdir) for t in ['gztar', 'zip']: source = os.path.join('dist', tarball_name(t)) - target = os.path.join(INSTALLERS_DIR, tarball_name(t)) + target = os.path.join(options.installers.installersdir, tarball_name(t)) shutil.copy(source, target) -#------------------ -# Wine-based builds -#------------------ -SSE3_CFG = {'BLAS': 'None', 'LAPACK': 'None', 'ATLAS': r'C:\local\lib\yop\sse3'} -SSE2_CFG = {'BLAS': 'None', 'LAPACK': 'None', 'ATLAS': r'C:\local\lib\yop\sse2'} -NOSSE_CFG = {'ATLAS': 'None', 'BLAS': r'C:\local\lib\yop\nosse', 'LAPACK': r'C:\local\lib\yop\nosse'} -SITECFG = {"sse2" : SSE2_CFG, "sse3" : SSE3_CFG, "nosse" : NOSSE_CFG} +#--------------------------------------- +# Windows installers (Wine-based builds) +#--------------------------------------- -def internal_wininst_name(arch, ismsi=False): +def superpack_name(pyver, numver): + """Return the filename of the superpack installer.""" + return 'scipy-%s-win32-superpack-python%s.exe' % (numver, pyver) + +def internal_wininst_name(arch): """Return the name of the wininst as it will be inside the superpack (i.e. with the arch encoded.""" - if ismsi: - ext = '.msi' - else: - ext = '.exe' + ext = '.exe' return "scipy-%s-%s%s" % (FULLVERSION, arch, ext) -def wininst_name(pyver, ismsi=False): +def wininst_name(pyver): """Return the name of the installer built by wininst command.""" - # Yeah, the name logic is harcoded in distutils. We have to reproduce it - # here - if ismsi: - ext = '.msi' - else: - ext = '.exe' - name = "scipy-%s.win32-py%s%s" % (FULLVERSION, pyver, ext) - return name + ext = '.exe' + return "scipy-%s.win32-py%s%s" % (FULLVERSION, pyver, ext) -def bdist_wininst_arch(pyver, arch, scratch=True): +def bdist_wininst_arch(pyver, arch): """Arch specific wininst build.""" - if scratch: - paver.path.path('build').rmtree() + if os.path.exists("build"): + shutil.rmtree("build") + _bdist_wininst(pyver, SITECFG[arch]) - if not os.path.exists(SUPERPACK_BINDIR): - os.makedirs(SUPERPACK_BINDIR) - env = os.environ.copy() - for k, v in SITECFG[arch].items(): - env[k] = v - _bdist_wininst(pyver, env) - source = os.path.join('dist', wininst_name(pyver)) - target = os.path.join(SUPERPACK_BINDIR, internal_wininst_name(arch)) - if os.path.exists(target): - os.remove(target) - os.rename(source, target) - -def superpack_name(pyver, numver): - """Return the filename of the superpack installer.""" - return 'scipy-%s-win32-superpack-python%s.exe' % (numver, pyver) - def prepare_nsis_script(pyver, numver): - if not os.path.exists(SUPERPACK_BUILD): - os.makedirs(SUPERPACK_BUILD) + if not os.path.exists(options.superpack.builddir): + os.makedirs(options.superpack.builddir) tpl = os.path.join('tools/win32/build_scripts/nsis_scripts', 'scipy-superinstaller.nsi.in') source = open(tpl, 'r') - target = open(os.path.join(SUPERPACK_BUILD, 'scipy-superinstaller.nsi'), 'w') + target = open(os.path.join(options.superpack.builddir, 'scipy-superinstaller.nsi'), 'w') installer_name = superpack_name(pyver, numver) cnt = "".join(source.readlines()) @@ -343,40 +338,58 @@ for arch in ['nosse', 'sse2', 'sse3']: cnt = cnt.replace('@%s_BINARY@' % arch.upper(), internal_wininst_name(arch)) - target.write(cnt) @task def bdist_wininst_nosse(options): """Build the nosse wininst installer.""" - bdist_wininst_arch(options.wininst.pyver, 'nosse', scratch=options.wininst.scratch) + bdist_wininst_arch(options.python_version, 'nosse') @task def bdist_wininst_sse2(options): """Build the sse2 wininst installer.""" - bdist_wininst_arch(options.wininst.pyver, 'sse2', scratch=options.wininst.scratch) + bdist_wininst_arch(options.python_version, 'sse2') @task def bdist_wininst_sse3(options): """Build the sse3 wininst installer.""" - bdist_wininst_arch(options.wininst.pyver, 'sse3', scratch=options.wininst.scratch) + bdist_wininst_arch(options.python_version, 'sse3') @task - at needs('bdist_wininst_nosse', 'bdist_wininst_sse2', 'bdist_wininst_sse3') + at cmdopts([("python-version=", "p", "python version")]) def bdist_superpack(options): """Build all arch specific wininst installers.""" - prepare_nsis_script(options.wininst.pyver, FULLVERSION) + pyver = options.python_version + def copy_bdist(arch): + # Copy the wininst in dist into the release directory + if int(pyver[0]) >= 3: + source = os.path.join('build', 'py3k', 'dist', wininst_name(pyver)) + else: + source = os.path.join('dist', wininst_name(pyver)) + target = os.path.join(options.superpack.bindir, internal_wininst_name(arch)) + if os.path.exists(target): + os.remove(target) + if not os.path.exists(os.path.dirname(target)): + os.makedirs(os.path.dirname(target)) + os.rename(source, target) + + bdist_wininst_arch(pyver, 'nosse') + copy_bdist("nosse") + bdist_wininst_arch(pyver, 'sse2') + copy_bdist("sse2") + bdist_wininst_arch(pyver, 'sse3') + copy_bdist("sse3") + + prepare_nsis_script(pyver, FULLVERSION) subprocess.check_call(MAKENSIS + ['scipy-superinstaller.nsi'], - cwd=SUPERPACK_BUILD) + cwd=options.superpack.builddir) # Copy the superpack into installers dir - if not os.path.exists(INSTALLERS_DIR): - os.makedirs(INSTALLERS_DIR) + if not os.path.exists(options.installers.installersdir): + os.makedirs(options.installers.installersdir) - source = os.path.join(SUPERPACK_BUILD, - superpack_name(options.wininst.pyver, FULLVERSION)) - target = os.path.join(INSTALLERS_DIR, - superpack_name(options.wininst.pyver, FULLVERSION)) + source = os.path.join(options.superpack.builddir, superpack_name(pyver, FULLVERSION)) + target = os.path.join(options.installers.installersdir, superpack_name(pyver, FULLVERSION)) shutil.copy(source, target) @task @@ -389,20 +402,37 @@ env[k] = v _bdist_wininst(options.bdist_wininst_simple.python_version, env) -def _bdist_wininst(pyver, cfg_env): - log = open('build.log', 'w') - try: - ret = subprocess.call(WINE_PYS[pyver] + ['setup.py', 'build', '-c', 'mingw32', 'bdist_wininst'], - env=cfg_env, stdout=log, stderr=subprocess.STDOUT) - finally: - log.close() +def _bdist_wininst(pyver, cfg_env=None): + cmd = WINE_PYS[pyver] + ['setup.py', 'build', '-c', 'mingw32', 'bdist_wininst'] + if cfg_env: + for k, v in WINDOWS_ENV.items(): + cfg_env[k] = v + else: + cfg_env = WINDOWS_ENV + subprocess.check_call(cmd, env=cfg_env) - if ret: - raise RuntimeError("Error while building windows installer, see build.log") -#------------------- -# Mac OS X installer -#------------------- +#-------------------- +# Mac OS X installers +#-------------------- + +def dmg_name(fullversion, pyver, osxver=None): + """Return name for dmg installer. + + Notes + ----- + Python 2.7 has two binaries, one for 10.3 (ppc, i386) and one for 10.6 + (i386, x86_64). All other Python versions at python.org at the moment + have binaries for 10.3 only. The "macosx%s" part of the dmg name should + correspond to the python.org naming scheme. + """ + # assume that for the py2.7/osx10.6 build the deployment target is set + # (should be done in the release script). + if not osxver: + osxver = os.environ.get('MACOSX_DEPLOYMENT_TARGET', '10.3') + return "scipy-%s-py%s-python.org-macosx%s.dmg" % (fullversion, pyver, + osxver) + def macosx_version(): if not sys.platform == 'darwin': raise ValueError("Not darwin ??") @@ -416,17 +446,8 @@ def mpkg_name(pyver): maj, min = macosx_version()[:2] - return "scipy-%s-py%s-macosx%s.%s.mpkg" % \ - (FULLVERSION, pyver, maj, min) + return "scipy-%s-py%s-macosx%s.%s.mpkg" % (FULLVERSION, pyver, maj, min) -def dmg_name(pyver): - #maj, min = macosx_version()[:2] - #pyver = ".".join([str(i) for i in sys.version_info[:2]]) - #return "scipy-%s-py%s-macosx%s.%s.dmg" % \ - # (FULLVERSION, pyver, maj, min) - return "scipy-%s-py%s-python.org.dmg" % \ - (FULLVERSION, pyver) - def prepare_static_gfortran_runtime(d): if not os.path.exists(d): os.makedirs(d) @@ -447,59 +468,79 @@ def _build_mpkg(pyver): numver = parse_numpy_version(MPKG_PYTHON[pyver]) numverstr = ".".join(["%i" % i for i in numver]) - if pyver == "2.5" and not numver[:2] == (1, 2): - raise ValueError("Scipy 0.7.x should be built against numpy 1.2.x for python 2.5 (detected %s)" % numverstr) - elif pyver == "2.6" and not numver[:2] == (1, 3): - raise ValueError("Scipy 0.7.x should be built against numpy 1.3.x for python 2.6 (detected %s)" % numverstr) + if not numver == (1, 5, 1): + raise ValueError("Scipy 0.9.x should be built against numpy 1.5.1, (detected %s)" % numverstr) prepare_static_gfortran_runtime("build") - ldflags = "-undefined dynamic_lookup -bundle -arch i386 -arch ppc -Wl,-search_paths_first" + # account for differences between Python 2.7.1 versions from python.org + if os.environ.get('MACOSX_DEPLOYMENT_TARGET', None) == "10.6": + ldflags = "-undefined dynamic_lookup -bundle -arch i386 -arch x86_64 -Wl,-search_paths_first" + else: + ldflags = "-undefined dynamic_lookup -bundle -arch i386 -arch ppc -Wl,-search_paths_first" ldflags += " -L%s" % os.path.join(os.path.dirname(__file__), "build") + + if pyver == "2.5": + sh("CC=gcc-4.0 LDFLAGS='%s' %s setupegg.py bdist_mpkg" % (ldflags, MPKG_PYTHON[pyver])) sh("LDFLAGS='%s' %s setupegg.py bdist_mpkg" % (ldflags, MPKG_PYTHON[pyver])) + @task - at needs("bdist_mpkg", "pdf") + at cmdopts([("python_version=", "p", "python version")]) def dmg(): - pyver = ".".join([str(i) for i in sys.version_info[:2]]) + try: + pyver = options.dmg.python_version + except: + pyver = PYVER + idirs = options.installers.installersdir - dmg_n = dmg_name() + # Check if doc exists. If not, say so and quit. + ref = os.path.join(options.doc.destdir_pdf, "reference.pdf") + if not os.path.exists(ref): + warnings.warn("Docs need to be built first! \n%s not found." % docpath) + + dmg_n = dmg_name(FULLVERSION, pyver) dmg = paver.path.path('scipy-macosx-installer') / dmg_n if dmg.exists(): dmg.remove() + call_task("clean") + _build_mpkg(pyver) + + macosx_installer_dir = "tools/scipy-macosx-installer" + dmg = os.path.join(macosx_installer_dir, dmg_name(FULLVERSION, pyver)) + if os.path.exists(dmg): + os.remove(dmg) + # Clean the image source - content = DMG_CONTENT - content.rmtree() - content.mkdir() + content = os.path.join(macosx_installer_dir, 'content') + if os.path.exists(content): + shutil.rmtree(content) + os.makedirs(content) # Copy mpkg into image source - mpkg_n = mpkg_name() - mpkg_tn = "scipy-%s-py%s.mpkg" % (FULLVERSION, pyver) - mpkg_source = paver.path.path("dist") / mpkg_n - mpkg_target = content / mpkg_tn - mpkg_source.copytree(content / mpkg_tn) + mpkg_source = os.path.join("dist", mpkg_name(pyver)) + mpkg_target = os.path.join(content, "scipy-%s-py%s.mpkg" % (FULLVERSION, pyver)) + shutil.copytree(mpkg_source, mpkg_target) # Copy docs into image source + pdf_docs = os.path.join(content, "Documentation") + if os.path.exists(pdf_docs): + shutil.rmtree(pdf_docs) + os.makedirs(pdf_docs) + shutil.copy(ref, os.path.join(pdf_docs, "reference.pdf")) - #html_docs = HTML_DESTDIR - #html_docs.copytree(content / "Documentation" / "html") + # Build the dmg + cmd = ["./new-create-dmg", "--pkgname", os.path.basename(mpkg_target), + "--volname", "scipy", os.path.basename(dmg), "./content"] + st = subprocess.check_call(cmd, cwd=macosx_installer_dir) - pdf_docs = DMG_CONTENT / "Documentation" - pdf_docs.rmtree() - pdf_docs.makedirs() + source = dmg + target = os.path.join(idirs, os.path.basename(dmg)) + if not os.path.exists(os.path.dirname(target)): + os.makedirs(os.path.dirname(target)) + shutil.copy(source, target) - user = PDF_DESTDIR / "userguide.pdf" - user.copy(pdf_docs / "userguide.pdf") - ref = PDF_DESTDIR / "reference.pdf" - ref.copy(pdf_docs / "reference.pdf") - # Build the dmg - cmd = ["./create-dmg", "--window-size", "500", "500", "--background", - "art/dmgbackground.png", "--icon-size", "128", "--icon", mpkg_tn, - "125", "320", "--icon", "Documentation", "375", "320", "--volname", "scipy", - dmg_n, "./content"] - subprocess.check_call(cmd, cwd="scipy-macosx-installer") - @task @cmdopts([('python_version=', 'p', 'Python version to build the installer against')]) def simple_dmg(): @@ -508,7 +549,7 @@ except AttributeError: pyver = PYVER - src_dir = DMG_DIR + src_dir = "dmg-source" # Clean the source dir if os.path.exists(src_dir): @@ -526,7 +567,7 @@ def _create_dmg(pyver, src_dir, volname=None): # Build the dmg - image_name = dmg_name(pyver) + image_name = dmg_name(FULLVERSION, pyver) image = paver.path.path(image_name) image.remove() cmd = ["hdiutil", "create", image_name, "-srcdir", src_dir] @@ -534,7 +575,55 @@ cmd.extend(["-volname", "'%s'" % volname]) sh(" ".join(cmd)) + +#---------------------------- +# Release notes and Changelog +#---------------------------- + +def compute_md5(): + released = paver.path.path(options.installers.installersdir).listdir() + checksums = [] + for f in released: + if not f.endswith('DS_Store'): + m = md5.md5(open(f, 'r').read()) + checksums.append('%s %s' % (m.hexdigest(), f)) + + return checksums + +def write_release_task(filename='NOTES.txt'): + source = paver.path.path(RELEASE) + target = paver.path.path(filename) + if target.exists(): + target.remove() + source.copy(target) + ftarget = open(str(target), 'a') + ftarget.writelines(""" +Checksums +========= + +""") + ftarget.writelines(['%s\n' % c for c in compute_md5()]) + + +def write_log_task(filename='Changelog'): + st = subprocess.Popen( + ['git', 'svn', 'log', '%s..%s' % (LOG_START, LOG_END)], + stdout=subprocess.PIPE) + + out = st.communicate()[0] + a = open(filename, 'w') + a.writelines(out) + a.close() + @task -def write_note_changelog(): - write_release_task(os.path.join(RELEASE_DIR, 'NOTES.txt')) - write_log_task(os.path.join(RELEASE_DIR, 'Changelog')) +def write_release(): + write_release_task() + + at task +def write_log(): + write_log_task() + + at task +def write_release_and_log(): + write_release_task(os.path.join(options.installers.releasedir, 'NOTES.txt')) + write_log_task(os.path.join(options.installers.releasedir, 'Changelog')) Added: trunk/release.sh =================================================================== --- trunk/release.sh (rev 0) +++ trunk/release.sh 2011-02-19 09:11:40 UTC (rev 7148) @@ -0,0 +1,57 @@ +#! /bin/sh +# script to build tarballs, mac os x and windows installers on mac os x + +# Check we're using the correct g++/c++ for the 64-bit 2.7 dmg. +# We do this because for Python 2.6 we use a symlink on the PATH to select +# /usr/bin/g++-4.0, while for Python 2.7 we need the default 4.2 version. +export PATH=~/Code/tmp/gpp40temp/:$PATH +gpp="$(g++ --version | grep "4.0")" +if [ -z "$gpp" ]; then + echo "Wrong g++ version, we need 4.0 to compile scipy with Python 2.6" + exit 1 +fi + +# bootstrap needed to ensure we build the docs from the right scipy version +paver bootstrap +source bootstrap/bin/activate +python setupsconsegg.py install + +# we need to copy Sphinx extensions from the numpy source tree +mkdir doc/sphinxext +cp -R ../numpy/doc/sphinxext/ doc/sphinxext/ + +# build docs +paver pdf + +#------------------------------------------------------------------ +# Build tarballs, Windows and 64-bit OS X installers (on OS X 10.6) +#------------------------------------------------------------------ + +paver sdist + +export MACOSX_DEPLOYMENT_TARGET=10.6 +export PATH=~/Code/tmp/gpp42temp/:$PATH +gpp="$(g++ --version | grep "4.2")" +if [ -z "$gpp" ]; then + echo "Wrong g++ version, we need 4.2 for 64-bit binary for Python 2.7" + exit 1 +fi +paver dmg -p 2.7 # 32/64-bit version + +paver bdist_superpack -p 2.7 +paver bdist_superpack -p 2.6 +paver bdist_superpack -p 2.5 +paver bdist_superpack -p 3.1 + + +#-------------------------------------------- +# Build 32-bit OS X installers (on OS X 10.5) +#-------------------------------------------- +#export MACOSX_DEPLOYMENT_TARGET=10.3 +#paver dmg -p 2.6 +#paver dmg -p 2.7 # 32-bit version +#export CC=/usr/bin/gcc-4.0 # necessary on 10.6, not sure about 10.5 +#paver dmg -p 2.5 + + +paver write_release_and_log Added: trunk/tools/scipy-macosx-installer/README.txt =================================================================== --- trunk/tools/scipy-macosx-installer/README.txt (rev 0) +++ trunk/tools/scipy-macosx-installer/README.txt 2011-02-19 09:11:40 UTC (rev 7148) @@ -0,0 +1,11 @@ +This is a set of scripts used to build a scipy .dmg installer with +documentation. + +The actual content of the dmg is to be put in content: documentation go into +the Documentation subdir, and the .mpkg installer for numpuy itself in the +content directory. The name of the installer should match exactly the one in +the scipy script (otherwise, the background will not appear correctly). + +The artwork is done in inkscape. + +The main script (new-create-dmg) was taken from stackoverflow. Added: trunk/tools/scipy-macosx-installer/art/dmgbackground.png =================================================================== --- trunk/tools/scipy-macosx-installer/art/dmgbackground.png (rev 0) +++ trunk/tools/scipy-macosx-installer/art/dmgbackground.png 2011-02-19 09:11:40 UTC (rev 7148) @@ -0,0 +1,506 @@ +?PNG + + +IHDR???????iCCPICC Profilex?T?kA?6n??"Zk?x?"IY?hE?6?bk ??E?d3I?n6??&??????*?E????z?d/J?ZE(??(b?-??nL?????~??7?}ov? +r?4??? +?R?il|Bj???? A4%U??N$A?s?{??z?[V?{?w?w???????@?G??*??q +Y??????inf???O??????b??N?????~N??>?!? ??F????????a?????=5??`???5?_M'?Tq?. +????V?J?p?8?da?sZHO?Ln???}&???wVQ?y?g????E??0  ? +HPEa??P@?<14?r?#??{2u$j?tbD?A{6?=?Q??/?y x x x x x ?????????????N??ooooo?? +x x x x x ? x@?'????????????t??????f?N??ooooo?? +x x x x x ? x@?'????????????t??????f?;??B?Rb?:?8????jL?q???? ??L??;7???:??IlGVb?????D>?)??k{yyW??=?}Q?9?sQ????8???~h?;F???@~??TEEG,????J'???|2?2K.]p?90&??G??Q?9*??8??$???B??? ?52????r?c??gF???g??vv????E??E?-???????????]?h?qL{?,?"?=\^=7?H?????GK"u????T"&iL?gF???4zLry?$?Ay2??d?II#?/P??1?t??L?vu?}@?#P?????\N??????!?????I?P<H??C?Sl??????3?????@?&?V|'?q??B???c??[?[?[?[?Z???4n??c at -???l[c|$wY,?yc.?>S?? ???w|?-Y?? ??<8[?,%?????3?.?H*????*)++e?,S&?tJR?$@^A????,?\r?1???f?????`@??????G?ep???t?Q?aw????I:?-K&??????C???????????7???7.8.>???????y???"7?V&????qu???*???&?k?H?????~??.??)???XCwz??x.{j>?z+h)?? + N????"}X????Ke:??-?5V?KUUe,SQ ?.???:??d`?9?qN?#??9g,?qe?8?h???(?c@???9z +????????%?}2??????????.??????DVR?!,?[? +?zd$??xj???;??Y\G?@????J???? +,??K`$y?]????`:?k??O?km<~Pm?{8[??A<{?P??."D??u?N?&??J>v???S7?%??I?t???V?c?? +??????9??yon???b6@l?????p$?v@?A? ?9(?^W??I +????Q?_?:?:x?[??+4p????jM%+?:/{;?? ?T??1?qa??LJ??+???Q???'MM?X???U??????8??????+??9? ??cQ????e???i??????s?J??_l???M??>??MU???<_7?!H@l?~.?????.f ??N??8]??f?X???????l '?{?d??-?j????????>? +??h6L?&?/??B?B??dy?qR?q?p<}?????????Xssc???E?????n8G?;? ??M,???F?:Q=`.$?pV??M<?X&? +U???Z?.? ??19]???,#?u-?(???????c?|? ????9?1???;?0^"P2_ ??????;???????!?jj??7??wc??Yr???h6l?>@?`??R?X????????>;>??D?x$x`:^??&S?b?4D?1?^?X8???U??oo~p?????I????e????????\??L?0/?-0% ?m%\; ?Q-??8??=2Y?C????????}??????n1?o&t%HCt,??4&???r?1ZX~?M???yV;??0?"???d????K7}$???*?t???q?f??x????U?Y?#?J<F1)??H? +? +JOE????${?%]B?????d???!?[?,` ?Td??"??????H???d?fDO? ?B???? +a?^;ww?b6??9~???6l?,??b???L?fP+h???q?`t???3?0??????????//??OA??c???Y3w???,?e? ???YDca#"??3???3M??Z_??nh??2???2e1.tkk????+?*??#??? ?MV?$?f?l???f??_?}??Q?)??C1?}?? 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trunk/tools/scipy-macosx-installer/new-create-dmg (rev 0) +++ trunk/tools/scipy-macosx-installer/new-create-dmg 2011-02-19 09:11:40 UTC (rev 7148) @@ -0,0 +1,107 @@ +#! /bin/bash +SRC_FOLDER=content +VOLUME_NAME=scipy +DMG_TEMP_NAME=scipy.tmp.dmg +title="${VOLUME_NAME}" +applicationName=scipy-0.9.0b1-py2.6.mpkg +finalDMGName=scipy.dmg +backgroundPictureName=dmgbackground.png + +# dmgbackground.png was exported from Inkscape as 600x600 px (Page), then +# resized in Preview to 500x500 px. +WINX=100 +WINY=100 +WINW=600 +WINH=600 +ICON_SIZE=128 + +BACKGROUND_FILE=art/dmgbackground.png +SCIPY_MPKG="" + +while test "${1:0:1}" = "-"; do + case $1 in + --pkgname) + SCIPY_MPKG="$2" + shift; shift;; + --volname) + VOLUME_NAME="$2" + shift; shift;; + -h | --help) + usage;; + --version) + version; exit 0;; + --pure-version) + pure_version; exit 0;; + -*) + echo "Unknown option $1. Run with --help for help." + exit 1;; + esac +done + +test -z "$2" && { + echo "Not enough arguments. Invoke with --help for help." + exit 1 +} + +# Check for mandatory options +if [ -e $SCIPY_MPKG ] +then + echo "--pkgname is mandatory" +fi + +BACKGROUND_FILE_NAME="$(basename $BACKGROUND_FILE)" +BACKGROUND_CLAUSE="set background picture of opts to file \".background:$BACKGROUND_FILE_NAME\"" + +DOCUMENTATION_PATH="Documentation" + +DMG_PATH="$1" +DMG_DIRNAME="$(dirname "$DMG_PATH")" +DMG_DIR="$(cd $DMG_DIRNAME > /dev/null; pwd)" +DMG_NAME="$(basename "$DMG_PATH")" +DMG_TEMP_NAME="$DMG_DIR/rw.${DMG_NAME}" +SRC_FOLDER="$(cd "$2" > /dev/null; pwd)" +DMG_SIZE=24m +test -z "$VOLUME_NAME" && VOLUME_NAME="$(basename "$DMG_PATH" .dmg)" + +# Create the image +echo "Creating disk image..." +test -f "${DMG_TEMP_NAME}" && rm -f "${DMG_TEMP_NAME}" +hdiutil create -srcfolder "$SRC_FOLDER" -volname "${VOLUME_NAME}" -fs HFS+ -fsargs "-c c=64,a=16,e=16" -format UDRW -size "${DMG_SIZE}" "${DMG_TEMP_NAME}" +device=$(hdiutil attach -readwrite -noverify -noautoopen "${DMG_TEMP_NAME}" | egrep '^/dev/' | sed 1q | awk '{print $1}') + +# Copy background image +mkdir /Volumes/"${VOLUME_NAME}"/.background +cp $BACKGROUND_FILE /Volumes/"${VOLUME_NAME}"/.background/"${BACKGROUND_FILE_NAME}" + +# Set background image + icon size + icon position +# XXX: the close/open after icon positioning is to circumvent a bug in Snow +# Leopard. Without it, the icon position is not changed +echo ' + tell application "Finder" + tell disk "'${VOLUME_NAME}'" + open + set current view of container window to icon view + set toolbar visible of container window to false + set statusbar visible of container window to false + set the bounds of container window to {100, 100, 600, 600} + set theViewOptions to the icon view options of container window + set arrangement of theViewOptions to not arranged + set icon size of theViewOptions to 128 + set background picture of theViewOptions to file ".background:'${BACKGROUND_FILE_NAME}'" + set position of item "'${SCIPY_MPKG}'" of container window to {125, 320} + set position of item "'${DOCUMENTATION_PATH}'" of container window to {375, 320} + close + open + update without registering applications + delay 5 + end tell + end tell +' | osascript + +rm -f "${DMG_NAME}" +chmod -Rf go-w /Volumes/"${VOLUME_NAME}" +sync +sync +hdiutil detach ${device} +hdiutil convert "${DMG_TEMP_NAME}" -format UDZO -imagekey zlib-level=9 -o "${DMG_NAME}" +rm -f ${DMG_TEMP_NAME} Property changes on: trunk/tools/scipy-macosx-installer/new-create-dmg ___________________________________________________________________ Added: svn:executable + * From scipy-svn at scipy.org Sat Feb 19 06:09:31 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sat, 19 Feb 2011 05:09:31 -0600 (CST) Subject: [Scipy-svn] r7149 - branches/0.9.x Message-ID: <20110219110931.14E9C6F0B6@scipy.org> Author: rgommers Date: 2011-02-19 05:09:30 -0600 (Sat, 19 Feb 2011) New Revision: 7149 Modified: branches/0.9.x/setup.py Log: REL: set released=False Modified: branches/0.9.x/setup.py =================================================================== --- branches/0.9.x/setup.py 2011-02-19 09:11:40 UTC (rev 7148) +++ branches/0.9.x/setup.py 2011-02-19 11:09:30 UTC (rev 7149) @@ -45,7 +45,7 @@ MAJOR = 0 MINOR = 9 MICRO = 0 -ISRELEASED = True +ISRELEASED = False VERSION = '%d.%d.%drc3' % (MAJOR, MINOR, MICRO) # BEFORE importing distutils, remove MANIFEST. distutils doesn't properly From scipy-svn at scipy.org Sat Feb 19 08:26:06 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sat, 19 Feb 2011 07:26:06 -0600 (CST) Subject: [Scipy-svn] r7150 - in trunk: doc/source/tutorial scipy/signal scipy/stats Message-ID: <20110219132606.71A466EFD2@scipy.org> Author: rgommers Date: 2011-02-19 07:26:05 -0600 (Sat, 19 Feb 2011) New Revision: 7150 Modified: trunk/doc/source/tutorial/special.rst trunk/scipy/signal/filter_design.py trunk/scipy/signal/ltisys.py trunk/scipy/stats/distributions.py Log: DOC: correct some errors in plot generation for doc build. Modified: trunk/doc/source/tutorial/special.rst =================================================================== --- trunk/doc/source/tutorial/special.rst 2011-02-19 11:09:30 UTC (rev 7149) +++ trunk/doc/source/tutorial/special.rst 2011-02-19 13:26:05 UTC (rev 7150) @@ -33,6 +33,7 @@ drum head anchored at the edge: .. plot:: + >>> from scipy import * >>> from scipy.special import jn, jn_zeros >>> def drumhead_height(n, k, distance, angle, t): Modified: trunk/scipy/signal/filter_design.py =================================================================== --- trunk/scipy/signal/filter_design.py 2011-02-19 11:09:30 UTC (rev 7149) +++ trunk/scipy/signal/filter_design.py 2011-02-19 13:26:05 UTC (rev 7150) @@ -138,8 +138,9 @@ Examples -------- - >>> b = firwin(80, 0.5, window=('kaiser', 8)) - >>> h, w = freqz(b) + >>> import scipy.signal + >>> b = sp.signal.firwin(80, 0.5, window=('kaiser', 8)) + >>> h, w = sp.signal.freqz(b) >>> import matplotlib.pyplot as plt >>> fig = plt.figure() Modified: trunk/scipy/signal/ltisys.py =================================================================== --- trunk/scipy/signal/ltisys.py 2011-02-19 11:09:30 UTC (rev 7149) +++ trunk/scipy/signal/ltisys.py 2011-02-19 13:26:05 UTC (rev 7150) @@ -634,8 +634,9 @@ Second order system with a repeated root: x''(t) + 2*x(t) + x(t) = u(t) + >>> import scipy.signal >>> system = ([1.0], [1.0, 2.0, 1.0]) - >>> t, y = impulse2(system) + >>> t, y = sp.signal.impulse2(system) >>> import matplotlib.pyplot as plt >>> plt.plot(t, y) Modified: trunk/scipy/stats/distributions.py =================================================================== --- trunk/scipy/stats/distributions.py 2011-02-19 11:09:30 UTC (rev 7149) +++ trunk/scipy/stats/distributions.py 2011-02-19 13:26:05 UTC (rev 7150) @@ -267,7 +267,7 @@ _doc_default_example = \ """Examples -------- ->>> import matplotlib.pyplot as plt +>>> from scipy.stats import %(name)s >>> numargs = %(name)s.numargs >>> [ %(shapes)s ] = [0.9,] * numargs >>> rv = %(name)s(%(shapes)s) From scipy-svn at scipy.org Sat Feb 19 08:26:38 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sat, 19 Feb 2011 07:26:38 -0600 (CST) Subject: [Scipy-svn] r7151 - in trunk/scipy: interpolate io/arff io/matlab odr optimize signal sparse sparse/linalg/eigen/lobpcg Message-ID: <20110219132638.D339F6EFD2@scipy.org> Author: rgommers Date: 2011-02-19 07:26:38 -0600 (Sat, 19 Feb 2011) New Revision: 7151 Modified: trunk/scipy/interpolate/polyint.py trunk/scipy/io/arff/arffread.py trunk/scipy/io/matlab/mio5.py trunk/scipy/odr/odrpack.py trunk/scipy/optimize/minpack.py trunk/scipy/signal/fir_filter_design.py trunk/scipy/sparse/base.py trunk/scipy/sparse/coo.py trunk/scipy/sparse/csgraph.py trunk/scipy/sparse/extract.py trunk/scipy/sparse/linalg/eigen/lobpcg/lobpcg.py Log: DOC: replace add docstring sections "Example" with "Examples". Modified: trunk/scipy/interpolate/polyint.py =================================================================== --- trunk/scipy/interpolate/polyint.py 2011-02-19 13:26:05 UTC (rev 7150) +++ trunk/scipy/interpolate/polyint.py 2011-02-19 13:26:38 UTC (rev 7151) @@ -68,7 +68,7 @@ is indicated by the repeated zero in the xi array; the corresponding yi values are 0, the function value, and 2, the derivative value. - For another example, given xi, yi, and a derivative ypi for each + For another example, given xi, yi, and a derivative ypi for each point, appropriate arrays can be constructed as: >>> xi_k, yi_k = np.repeat(xi, 2), np.ravel(np.dstack((yi,ypi))) @@ -180,8 +180,8 @@ the middle dimension will be dropped; if R is 1 then the last dimension will be dropped. - Example - ------- + Examples + -------- >>> KroghInterpolator([0,0,0],[1,2,3]).derivatives(0) array([1.0,2.0,3.0]) >>> KroghInterpolator([0,0,0],[1,2,3]).derivatives([0,0]) @@ -893,7 +893,7 @@ w1 = 2*hk[1:] + hk[:-1] w2 = hk[1:] + 2*hk[:-1] whmean = 1.0/(w1+w2)*(w1/mk[1:] + w2/mk[:-1]) - + dk = np.zeros_like(y) dk[1:-1][condition] = 0.0 dk[1:-1][~condition] = 1.0/whmean[~condition] @@ -904,16 +904,16 @@ dk[0] = _edge_case(mk[0],dk[1]) dk[-1] = _edge_case(mk[-1],dk[-2]) return dk - + def pchip(x, y): - """PCHIP 1-d monotonic cubic interpolation - + """PCHIP 1-d monotonic cubic interpolation + Description ----------- x and y are arrays of values used to approximate some function f: y = f(x) - This class factory function returns a callable class whose __call__ method + This class factory function returns a callable class whose __call__ method uses monotonic cubic, interpolation to find the value of new points. Parameters @@ -924,10 +924,10 @@ y : array A 1-D array of real values. y's length along the interpolation axis must be equal to the length of x. - + Assumes x is sorted in monotonic order (e.g. x[1] > x[0]) """ derivs = _find_derivatives(x,y) return PiecewisePolynomial(x, zip(y, derivs), orders=3, direction=None) - + Modified: trunk/scipy/io/arff/arffread.py =================================================================== --- trunk/scipy/io/arff/arffread.py 2011-02-19 13:26:05 UTC (rev 7150) +++ trunk/scipy/io/arff/arffread.py 2011-02-19 13:26:38 UTC (rev 7151) @@ -119,7 +119,7 @@ ------- slen : int length of longest component - + Examples -------- maxnomlen("{floup, bouga, fl, ratata}") returns 6 (the size of @@ -176,7 +176,7 @@ Given a raw string attribute, try to get the name and type of the attribute. Constraints: - + * The first line must start with @attribute (case insensitive, and space like characters before @attribute are allowed) * Works also if the attribute is spread on multilines. @@ -204,7 +204,7 @@ >>> iterable = iter([0] * 10) # dummy iterator >>> tokenize_attribute(iterable, r"@attribute floupi real") ('floupi', 'real', 0) - + If attribute is r"'floupi 2' real", will return 'floupi 2' as name, and real as value. @@ -397,8 +397,8 @@ Knows about attributes names and types. - Example - ------- + Examples + -------- data, meta = loadarff('iris.arff') # This will print the attributes names of the iris.arff dataset for i in meta: @@ -644,8 +644,8 @@ # make sure nose does not find this as a test test_weka.__test__ = False - + def floupi(filename): data, meta = loadarff(filename) from attrselect import print_dataset_info Modified: trunk/scipy/io/matlab/mio5.py =================================================================== --- trunk/scipy/io/matlab/mio5.py 2011-02-19 13:26:05 UTC (rev 7150) +++ trunk/scipy/io/matlab/mio5.py 2011-02-19 13:26:38 UTC (rev 7151) @@ -106,13 +106,13 @@ class MatFile5Reader(MatFileReader): ''' Reader for Mat 5 mat files Adds the following attribute to base class - + uint16_codec - char codec to use for uint16 char arrays (defaults to system default codec) Uses variable reader that has the following stardard interface (see abstract class in ``miobase``:: - + __init__(self, file_reader) read_header(self) array_from_header(self) @@ -121,7 +121,7 @@ set_stream(self, stream) read_full_tag(self) - + ''' @docfiller def __init__(self, @@ -188,7 +188,7 @@ # reader because we use the matrix_reader object to contain # compressed matrices (so they have their own stream) self._file_reader = VarReader5(self) - # reader for matrix streams + # reader for matrix streams self._matrix_reader = VarReader5(self) def read_var_header(self): @@ -232,7 +232,7 @@ raise TypeError('Expecting miMATRIX type here, got %d' % mdtype) header = self._matrix_reader.read_header() return header, next_pos - + def read_var_array(self, header, process=True): ''' Read array, given `header` @@ -242,13 +242,13 @@ object with fields defining variable header process : {True, False} bool, optional If True, apply recursive post-processing during loading of - array. - + array. + Returns ------- arr : array array with post-processing applied or not according to - `process`. + `process`. ''' return self._matrix_reader.array_from_header(header, process) @@ -333,8 +333,8 @@ file with something like ``open('test.mat', 'wb').write(var_file_obj.read())`` - Example - ------- + Examples + -------- >>> import scipy.io BytesIO is from the ``io`` module in python 3, and is ``cStringIO`` for @@ -445,7 +445,7 @@ dtype = [] values = [] for field, value in source.items(): - if (isinstance(field, basestring) and + if (isinstance(field, basestring) and not field[0] in '_0123456789'): dtype.append((field,object)) values.append(value) @@ -520,7 +520,7 @@ self.file_stream.write(asbytes('\x00') * (8-bc_mod_8)) def write_header(self, - shape, + shape, mclass, is_complex=False, is_logical=False, @@ -561,7 +561,7 @@ # reset the one-shot store to defaults self._var_name = '' self._var_is_global = False - + def update_matrix_tag(self, start_pos): curr_pos = self.file_stream.tell() self.file_stream.seek(start_pos) @@ -571,7 +571,7 @@ def write_top(self, arr, name, is_global): """ Write variable at top level of mat file - + Parameters ---------- arr : array-like @@ -588,7 +588,7 @@ self._var_name = name # write the header and data self.write(arr) - + def write(self, arr): ''' Write `arr` to stream at top and sub levels @@ -760,7 +760,7 @@ global_vars=None, long_field_names=False, oned_as=None): - ''' Initialize writer for matlab 5 format files + ''' Initialize writer for matlab 5 format files Parameters ---------- Modified: trunk/scipy/odr/odrpack.py =================================================================== --- trunk/scipy/odr/odrpack.py 2011-02-19 13:26:05 UTC (rev 7150) +++ trunk/scipy/odr/odrpack.py 2011-02-19 13:26:38 UTC (rev 7151) @@ -301,8 +301,8 @@ """ Update the metadata dictionary with the keywords and data provided by keywords. - Example - ------- + Examples + -------- data.set_meta(lab="Ph 7; Lab 26", title="Ag110 + Ag108 Decay") """ @@ -513,8 +513,8 @@ """ Update the metadata dictionary with the keywords and data provided here. - Example - ------- + Examples + -------- set_meta(name="Exponential", equation="y = a exp(b x) + c") """ Modified: trunk/scipy/optimize/minpack.py =================================================================== --- trunk/scipy/optimize/minpack.py 2011-02-19 13:26:05 UTC (rev 7150) +++ trunk/scipy/optimize/minpack.py 2011-02-19 13:26:38 UTC (rev 7151) @@ -479,8 +479,8 @@ Uses Steffensen's Method using Aitken's Del^2 convergence acceleration. See Burden, Faires, "Numerical Analysis", 5th edition, pg. 80 - Example - ------- + Examples + -------- >>> from numpy import sqrt, array >>> from scipy.optimize import fixed_point >>> def func(x, c1, c2): Modified: trunk/scipy/signal/fir_filter_design.py =================================================================== --- trunk/scipy/signal/fir_filter_design.py 2011-02-19 13:26:05 UTC (rev 7150) +++ trunk/scipy/signal/fir_filter_design.py 2011-02-19 13:26:38 UTC (rev 7151) @@ -23,7 +23,7 @@ def kaiser_beta(a): """Compute the Kaiser parameter `beta`, given the attenuation `a`. - + Parameters ---------- a : float @@ -34,7 +34,7 @@ ------- beta : float The `beta` parameter to be used in the formula for a Kaiser window. - + References ---------- Oppenheim, Schafer, "Discrete-Time Signal Processing", p.475-476. @@ -50,7 +50,7 @@ def kaiser_atten(numtaps, width): """Compute the attenuation of a Kaiser FIR filter. - + Given the number of taps `N` and the transition width `width`, compute the attenuation `a` in dB, given by Kaiser's formula: @@ -68,7 +68,7 @@ ------- a : float The attenuation of the ripple, in dB. - + See Also -------- kaiserord, kaiser_beta @@ -123,7 +123,7 @@ beta = kaiser_beta(A) # Kaiser's formula (as given in Oppenheim and Schafer) is for the filter - # order, so we have to add 1 to get the number of taps. + # order, so we have to add 1 to get the number of taps. numtaps = (A - 7.95) / 2.285 / (np.pi * width) + 1 return int(ceil(numtaps)), beta @@ -133,11 +133,11 @@ scale=True, nyq=1.0): """ FIR filter design using the window method. - + This function computes the coefficients of a finite impulse response filter. The filter will have linear phase; it will be Type I if `numtaps` is odd and Type II if `numtaps` is even. - + Type II filters always have zero response at the Nyquist rate, so a ValueError exception is raised if firwin is called with `numtaps` even and having a passband whose right end is at the Nyquist rate. @@ -199,33 +199,33 @@ Examples -------- - + Low-pass from 0 to f:: - + >>> firwin(numtaps, f) - + Use a specific window function:: - + >>> firwin(numtaps, f, window='nuttall') - + High-pass ('stop' from 0 to f):: - + >>> firwin(numtaps, f, pass_zero=False) Band-pass:: - + >>> firwin(numtaps, [f1, f2], pass_zero=False) - + Band-stop:: - - >>> firwin(numtaps, [f1, f2]) + >>> firwin(numtaps, [f1, f2]) + Multi-band (passbands are [0, f1], [f2, f3] and [f4, 1]):: >>>firwin(numtaps, [f1, f2, f3, f4]) - + Multi-band (passbands are [f1, f2] and [f3,f4]):: - + >>> firwin(numtaps, [f1, f2, f3, f4], pass_zero=False) See also @@ -280,7 +280,7 @@ from signaltools import get_window win = get_window(window, numtaps, fftbins=False) h *= win - + # Now handle scaling if desired. if scale: # Get the first passband. @@ -294,7 +294,7 @@ c = np.cos(np.pi * m * scale_frequency) s = np.sum(h * c) h /= s - + return h @@ -320,7 +320,7 @@ The frequency sampling points. Typically 0.0 to 1.0 with 1.0 being Nyquist. The Nyquist frequency can be redefined with the argument `nyq`. - + The values in `freq` must be nondecreasing. A value can be repeated once to implement a discontinuity. The first value in `freq` must be 0, and the last value must be `nyq`. @@ -349,8 +349,8 @@ taps : numpy 1D array of length `numtaps` The filter coefficients of the FIR filter. - Example - ------- + Examples + -------- A lowpass FIR filter with a response that is 1 on [0.0, 0.5], and that decreases linearly on [0.5, 1.0] from 1 to 0: @@ -375,7 +375,7 @@ is odd and Type II if `numtaps` is even. Because Type II filters always have a zero at the Nyquist frequency, `numtaps` must be odd if `gain[-1]` is not zero. - + .. versionadded:: 0.9.0 References @@ -383,7 +383,7 @@ .. [1] Oppenheim, A. V. and Schafer, R. W., "Discrete-Time Signal Processing", Prentice-Hall, Englewood Cliffs, New Jersey (1989). (See, for example, Section 7.4.) - + .. [2] Smith, Steven W., "The Scientist and Engineer's Guide to Digital Signal Processing", Ch. 17. http://www.dspguide.com/ch17/1.htm @@ -393,7 +393,7 @@ raise ValueError('freq and gain must be of same length.') if nfreqs is not None and numtaps >= nfreqs: - raise ValueError('ntaps must be less than nfreqs, but firwin2 was ' + raise ValueError('ntaps must be less than nfreqs, but firwin2 was ' 'called with ntaps=%d and nfreqs=%s' % (numtaps, nfreqs)) if freq[0] != 0 or freq[-1] != nyq: @@ -437,7 +437,7 @@ wind = get_window(window, numtaps, fftbins=False) else: wind = 1 - + # Keep only the first `numtaps` coefficients in `out`, and multiply by # the window. out = out_full[:numtaps] * wind Modified: trunk/scipy/sparse/base.py =================================================================== --- trunk/scipy/sparse/base.py 2011-02-19 13:26:05 UTC (rev 7150) +++ trunk/scipy/sparse/base.py 2011-02-19 13:26:38 UTC (rev 7151) @@ -409,9 +409,8 @@ Returns a tuple of arrays (row,col) containing the indices of the non-zero elements of the matrix. - Example - ------- - + Examples + -------- >>> from scipy.sparse import csr_matrix >>> A = csr_matrix([[1,2,0],[0,0,3],[4,0,5]]) >>> A.nonzero() Modified: trunk/scipy/sparse/coo.py =================================================================== --- trunk/scipy/sparse/coo.py 2011-02-19 13:26:05 UTC (rev 7150) +++ trunk/scipy/sparse/coo.py 2011-02-19 13:26:38 UTC (rev 7151) @@ -226,8 +226,8 @@ Duplicate entries will be summed together. - Example - ------- + Examples + -------- >>> from numpy import array >>> from scipy.sparse import coo_matrix >>> row = array([0,0,1,3,1,0,0]) @@ -264,8 +264,8 @@ Duplicate entries will be summed together. - Example - ------- + Examples + -------- >>> from numpy import array >>> from scipy.sparse import coo_matrix >>> row = array([0,0,1,3,1,0,0]) Modified: trunk/scipy/sparse/csgraph.py =================================================================== --- trunk/scipy/sparse/csgraph.py 2011-02-19 13:26:05 UTC (rev 7150) +++ trunk/scipy/sparse/csgraph.py 2011-02-19 13:26:38 UTC (rev 7151) @@ -41,14 +41,12 @@ Notes ------ - The matrix is assumed to be symmetric and the upper triangular part of the matrix is used. The matrix is converted to a CSR matrix unless it is already a CSR. - Example - ------- - + Examples + -------- >>> from scipy.sparse import cs_graph_components >>> import numpy as np >>> D = np.eye(4) @@ -64,7 +62,7 @@ shape = x.shape except AttributeError: raise ValueError(_msg0) - + if not ((len(x.shape) == 2) and (x.shape[0] == x.shape[1])): raise ValueError(_msg1 % x.shape) @@ -72,7 +70,7 @@ x = x.tocsr() else: x = csr_matrix(x) - + label = np.empty((shape[0],), dtype=x.indptr.dtype) n_comp = _cs_graph_components(shape[0], x.indptr, x.indices, label) Modified: trunk/scipy/sparse/extract.py =================================================================== --- trunk/scipy/sparse/extract.py 2011-02-19 13:26:05 UTC (rev 7150) +++ trunk/scipy/sparse/extract.py 2011-02-19 13:26:38 UTC (rev 7151) @@ -23,8 +23,8 @@ of the nonzero matrix entries. - Example - ------- + Examples + -------- >>> from scipy.sparse import csr_matrix >>> A = csr_matrix([[7.0, 8.0, 0],[0, 0, 9.0]]) >>> find(A) Modified: trunk/scipy/sparse/linalg/eigen/lobpcg/lobpcg.py =================================================================== --- trunk/scipy/sparse/linalg/eigen/lobpcg/lobpcg.py 2011-02-19 13:26:05 UTC (rev 7150) +++ trunk/scipy/sparse/linalg/eigen/lobpcg/lobpcg.py 2011-02-19 13:26:38 UTC (rev 7151) @@ -91,9 +91,8 @@ a function and makes an operator performing matrix * blockvector products. - Example - ------- - + Examples + -------- >>> A = makeOperator( arrayA, (n, n) ) >>> vectorB = A( vectorX ) From scipy-svn at scipy.org Sat Feb 19 08:30:19 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sat, 19 Feb 2011 07:30:19 -0600 (CST) Subject: [Scipy-svn] r7152 - in branches/0.9.x/scipy: interpolate spatial Message-ID: <20110219133019.E62326EFD2@scipy.org> Author: rgommers Date: 2011-02-19 07:30:19 -0600 (Sat, 19 Feb 2011) New Revision: 7152 Modified: branches/0.9.x/scipy/interpolate/interpnd.pyx branches/0.9.x/scipy/spatial/qhull.pxd branches/0.9.x/scipy/spatial/qhull.pyx Log: BUG: spatial/interpnd: never deallocate memory in a different Cython module Different Cython modules end up as different DLL/.so files, and apparently on some platforms freeing memory allocated in a different DLL is not allowed. This seems to be true at least on Windows 7 + 32-bit Python. Modified: branches/0.9.x/scipy/interpolate/interpnd.pyx =================================================================== --- branches/0.9.x/scipy/interpolate/interpnd.pyx 2011-02-19 13:26:38 UTC (rev 7151) +++ branches/0.9.x/scipy/interpolate/interpnd.pyx 2011-02-19 13:30:19 UTC (rev 7152) @@ -31,10 +31,6 @@ # Numpy etc. #------------------------------------------------------------------------------ -cdef extern from "stdlib.h": - void *malloc(int size) nogil - void free(void *ptr) nogil - cdef extern from "math.h": double sqrt(double x) nogil double fabs(double a) nogil @@ -164,7 +160,7 @@ """ LinearNDInterpolator(points, values) - Piecewise linear interpolant in N dimensions. + Piecewise linear interpolant in N dimensions. .. versionadded:: 0.9 @@ -205,13 +201,13 @@ cdef double c[NPY_MAXDIMS] cdef ${CDTYPE} fill_value cdef int i, j, k, m, ndim, isimplex, inside, start, nvalues - cdef qhull.DelaunayInfo_t *info + cdef qhull.DelaunayInfo_t info ndim = xi.shape[1] start = 0 fill_value = self.fill_value - info = qhull._get_delaunay_info(self.tri, 1, 0) + qhull._get_delaunay_info(&info, self.tri, 1, 0) out = np.zeros((xi.shape[0], self.values.shape[1]), dtype=np.${DTYPE}) nvalues = out.shape[1] @@ -223,7 +219,7 @@ # 1) Find the simplex - isimplex = qhull._find_simplex(info, c, + isimplex = qhull._find_simplex(&info, c, (xi.data) + i*ndim, &start, eps) @@ -258,7 +254,6 @@ out[i,k].imag += c[j] * values[m, k].imag % endif - free(info) return out % endfor @@ -431,7 +426,7 @@ change = max(fabs(y[it.vertex*2 + 0] + r[0]), fabs(y[it.vertex*2 + 1] + r[1])) - + y[it.vertex*2 + 0] = -r[0] y[it.vertex*2 + 1] = -r[1] @@ -448,7 +443,7 @@ def estimate_gradients_2d_global(tri, y, maxiter=400, tol=1e-6): cdef np.ndarray[np.double_t, ndim=2] data cdef np.ndarray[np.double_t, ndim=3] grad - cdef qhull.DelaunayInfo_t *info + cdef qhull.DelaunayInfo_t info cdef int k, ret, nvalues y = np.asanyarray(y) @@ -476,13 +471,13 @@ data = y grad = yi - info = qhull._get_delaunay_info(tri, 0, 1) + qhull._get_delaunay_info(&info, tri, 0, 1) nvalues = data.shape[0] for k in xrange(nvalues): with nogil: ret = _estimate_gradients_2d_global( - info, + &info, data.data + info.npoints*k, maxiter, tol, @@ -493,7 +488,6 @@ "the results may be inaccurate", GradientEstimationWarning) - free(info) return yi.transpose(1, 0, 2).reshape(y_shape + (2,)) @@ -742,7 +736,7 @@ """ CloughTocher2DInterpolator(points, values, tol=1e-6) - Piecewise cubic, C1 smooth, curvature-minimizing interpolant in 2D. + Piecewise cubic, C1 smooth, curvature-minimizing interpolant in 2D. .. versionadded:: 0.9 @@ -821,13 +815,13 @@ cdef ${CDTYPE} w cdef ${CDTYPE} fill_value cdef int i, j, k, m, ndim, isimplex, inside, start, nvalues - cdef qhull.DelaunayInfo_t *info + cdef qhull.DelaunayInfo_t info ndim = xi.shape[1] start = 0 fill_value = self.fill_value - info = qhull._get_delaunay_info(self.tri, 1, 1) + qhull._get_delaunay_info(&info, self.tri, 1, 1) out = np.zeros((xi.shape[0], self.values.shape[1]), dtype=np.${DTYPE}) nvalues = out.shape[1] @@ -838,7 +832,7 @@ for i in xrange(xi.shape[0]): # 1) Find the simplex - isimplex = qhull._find_simplex(info, c, + isimplex = qhull._find_simplex(&info, c, (xi.data) + i*ndim, &start, eps) @@ -870,7 +864,7 @@ df[2*j+1].imag = grad[vertices[isimplex,j],k,1].imag % endif - w = _clough_tocher_2d_single_${DTYPE}(info, isimplex, c, + w = _clough_tocher_2d_single_${DTYPE}(&info, isimplex, c, f, df) % if DTYPE == "double": out[i,k] = w @@ -879,7 +873,6 @@ out[i,k].imag = w.imag % endif - free(info) return out % endfor Modified: branches/0.9.x/scipy/spatial/qhull.pxd =================================================================== --- branches/0.9.x/scipy/spatial/qhull.pxd 2011-02-19 13:26:38 UTC (rev 7151) +++ branches/0.9.x/scipy/spatial/qhull.pxd 2011-02-19 13:30:19 UTC (rev 7152) @@ -9,10 +9,6 @@ # Distributed under the same BSD license as Scipy. # -cdef extern from "stdlib.h": - void *malloc(int size) - void free(void *ptr) - cdef extern from "numpy/ndarrayobject.h": cdef enum: NPY_MAXDIMS @@ -32,8 +28,9 @@ double *max_bound double *min_bound -cdef DelaunayInfo_t *_get_delaunay_info(obj, int compute_transform, - int compute_vertex_to_simplex) +cdef void _get_delaunay_info(DelaunayInfo_t *, obj, + int compute_transform, + int compute_vertex_to_simplex) # # N-D geometry Modified: branches/0.9.x/scipy/spatial/qhull.pyx =================================================================== --- branches/0.9.x/scipy/spatial/qhull.pyx 2011-02-19 13:26:38 UTC (rev 7151) +++ branches/0.9.x/scipy/spatial/qhull.pyx 2011-02-19 13:30:19 UTC (rev 7152) @@ -593,22 +593,15 @@ cdef class RidgeIter2D(object): cdef RidgeIter2D_t it cdef object delaunay - cdef DelaunayInfo_t *info + cdef DelaunayInfo_t info def __init__(self, delaunay, ivertex): - self.info = NULL if delaunay.ndim != 2: raise ValueError("RidgeIter2D supports only 2-D") self.delaunay = delaunay - self.info = _get_delaunay_info(delaunay, 0, 1) - _RidgeIter2D_init(&self.it, self.info, ivertex) + _get_delaunay_info(&self.info, delaunay, 0, 1) + _RidgeIter2D_init(&self.it, &self.info, ivertex) - def __del__(self): - if self.info != NULL: - free(self.info) - self.info = NULL - self.delaunay = None - def __iter__(self): return self @@ -1067,7 +1060,7 @@ directed search in N dimensions. """ - cdef DelaunayInfo_t *info + cdef DelaunayInfo_t info cdef int isimplex cdef double c[NPY_MAXDIMS] cdef double eps @@ -1090,23 +1083,21 @@ eps = np.finfo(np.double).eps * 10 out = np.zeros((xi.shape[0],), dtype=np.intc) out_ = out - info = _get_delaunay_info(self, 1, 0) + _get_delaunay_info(&info, self, 1, 0) if bruteforce: for k in xrange(x.shape[0]): isimplex = _find_simplex_bruteforce( - info, c, + &info, c, x.data + info.ndim*k, eps) out_[k] = isimplex else: for k in xrange(x.shape[0]): - isimplex = _find_simplex(info, c, x.data + info.ndim*k, + isimplex = _find_simplex(&info, c, x.data + info.ndim*k, &start, eps) out_[k] = isimplex - free(info) - return out.reshape(xi_shape[:-1]) def plane_distance(self, xi): @@ -1118,7 +1109,7 @@ """ cdef np.ndarray[np.double_t, ndim=2] x cdef np.ndarray[np.double_t, ndim=2] out_ - cdef DelaunayInfo_t *info + cdef DelaunayInfo_t info cdef double z[NPY_MAXDIMS+1] cdef int i, j, k @@ -1130,18 +1121,16 @@ xi = xi.reshape(np.prod(xi.shape[:-1]), xi.shape[-1]) x = np.ascontiguousarray(xi.astype(np.double)) - info = _get_delaunay_info(self, 0, 0) + _get_delaunay_info(&info, self, 0, 0) out = np.zeros((x.shape[0], info.nsimplex), dtype=np.double) out_ = out for i in xrange(x.shape[0]): for j in xrange(info.nsimplex): - _lift_point(info, (x.data) + info.ndim*i, z) - out_[i,j] = _distplane(info, j, z) + _lift_point(&info, (x.data) + info.ndim*i, z) + out_[i,j] = _distplane(&info, j, z) - free(info) - return out.reshape(xi_shape[:-1] + (self.nsimplex,)) def lift_points(tri, x): @@ -1180,10 +1169,10 @@ # Delaunay triangulation interface, for low-level C #------------------------------------------------------------------------------ -cdef DelaunayInfo_t *_get_delaunay_info(obj, - int compute_transform, - int compute_vertex_to_simplex): - cdef DelaunayInfo_t *info +cdef void _get_delaunay_info(DelaunayInfo_t *info, + obj, + int compute_transform, + int compute_vertex_to_simplex): cdef np.ndarray[np.double_t, ndim=3] transform cdef np.ndarray[np.npy_int, ndim=1] vertex_to_simplex cdef np.ndarray[np.double_t, ndim=2] points = obj.points @@ -1193,7 +1182,6 @@ cdef np.ndarray[np.double_t, ndim=1] min_bound = obj.min_bound cdef np.ndarray[np.double_t, ndim=1] max_bound = obj.max_bound - info = malloc(sizeof(DelaunayInfo_t)) info.ndim = points.shape[1] info.npoints = points.shape[0] info.nsimplex = vertices.shape[0] @@ -1215,5 +1203,3 @@ info.vertex_to_simplex = NULL info.min_bound = min_bound.data info.max_bound = max_bound.data - - return info From scipy-svn at scipy.org Sat Feb 19 08:30:39 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sat, 19 Feb 2011 07:30:39 -0600 (CST) Subject: [Scipy-svn] r7153 - in branches/0.9.x/scipy: interpolate spatial Message-ID: <20110219133039.9AAF86EFD2@scipy.org> Author: rgommers Date: 2011-02-19 07:30:39 -0600 (Sat, 19 Feb 2011) New Revision: 7153 Modified: branches/0.9.x/scipy/interpolate/interpnd.c branches/0.9.x/scipy/spatial/qhull.c Log: GEN: spatial/interpolate: regenerate qhull/interpnd Cython modules Modified: branches/0.9.x/scipy/interpolate/interpnd.c =================================================================== --- branches/0.9.x/scipy/interpolate/interpnd.c 2011-02-19 13:30:19 UTC (rev 7152) +++ branches/0.9.x/scipy/interpolate/interpnd.c 2011-02-19 13:30:39 UTC (rev 7153) @@ -761,7 +761,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_get_array_base(PyArrayObject *); -static __pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t *(*__pyx_f_5scipy_7spatial_5qhull__get_delaunay_info)(PyObject *, int, int); +static void (*__pyx_f_5scipy_7spatial_5qhull__get_delaunay_info)(__pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t *, PyObject *, int, int); static int (*__pyx_f_5scipy_7spatial_5qhull__barycentric_inside)(int, double *, double *, double *, double); static void (*__pyx_f_5scipy_7spatial_5qhull__barycentric_coordinate_single)(int, double *, double *, double *, int); static void (*__pyx_f_5scipy_7spatial_5qhull__barycentric_coordinates)(int, double *, double *, double *); @@ -821,14 +821,14 @@ static char __pyx_k_24[] = "scipy.spatial.qhull"; static char __pyx_k_25[] = "*"; static char __pyx_k_26[] = "\n Common routines for interpolators.\n\n .. versionadded:: 0.9\n\n "; -static char __pyx_k_27[] = "\n LinearNDInterpolator(points, values)\n\n Piecewise linear interpolant in N dimensions. \n\n .. versionadded:: 0.9\n\n Parameters\n ----------\n points : ndarray of floats, shape (npoints, ndims)\n Data point coordinates.\n values : ndarray of float or complex, shape (npoints, ...)\n Data values.\n fill_value : float, optional\n Value used to fill in for requested points outside of the\n convex hull of the input points. If not provided, then\n the default is ``nan``.\n\n Notes\n -----\n The interpolant is constructed by triangulating the input data\n with Qhull [Qhull]_, and on each triangle performing linear\n barycentric interpolation.\n\n References\n ----------\n .. [Qhull] http://www.qhull.org/\n\n "; +static char __pyx_k_27[] = "\n LinearNDInterpolator(points, values)\n\n Piecewise linear interpolant in N dimensions.\n\n .. versionadded:: 0.9\n\n Parameters\n ----------\n points : ndarray of floats, shape (npoints, ndims)\n Data point coordinates.\n values : ndarray of float or complex, shape (npoints, ...)\n Data values.\n fill_value : float, optional\n Value used to fill in for requested points outside of the\n convex hull of the input points. If not provided, then\n the default is ``nan``.\n\n Notes\n -----\n The interpolant is constructed by triangulating the input data\n with Qhull [Qhull]_, and on each triangle performing linear\n barycentric interpolation.\n\n References\n ----------\n .. [Qhull] http://www.qhull.org/\n\n "; static char __pyx_k_28[] = "LinearNDInterpolator"; -static char __pyx_k_29[] = "\n CloughTocher2DInterpolator(points, values, tol=1e-6)\n\n Piecewise cubic, C1 smooth, curvature-minimizing interpolant in 2D. \n\n .. versionadded:: 0.9\n\n Parameters\n ----------\n points : ndarray of floats, shape (npoints, ndims)\n Data point coordinates.\n values : ndarray of float or complex, shape (npoints, ...)\n Data values.\n fill_value : float, optional\n Value used to fill in for requested points outside of the\n convex hull of the input points. If not provided, then\n the default is ``nan``.\n tol : float, optional\n Absolute/relative tolerance for gradient estimation.\n maxiter : int, optional\n Maximum number of iterations in gradient estimation.\n\n Notes\n -----\n The interpolant is constructed by triangulating the input data\n with Qhull [Qhull]_, and constructing a piecewise cubic\n interpolating Bezier polynomial on each triangle, using a\n Clough-Tocher scheme [CT]_. The interpolant is guaranteed to be\n continuously differentiable.\n\n The gradients of the interpolant are chosen so that the curvature\n of the interpolating surface is approximatively minimized. The\n gradients necessary for this are estimated using the global\n algorithm described in [Nielson83,Renka84]_.\n\n References\n ----------\n\n .. [Qhull] http://www.qhull.org/\n\n .. [CT] See, for example,\n P. Alfeld,\n ''A trivariate Clough-Tocher scheme for tetrahedral data''.\n Computer Aided Geometric Design, 1, 169 (1984);\n G. Farin,\n ''Triangular Bernstein-Bezier patches''.\n Computer Aided Geometric Design, 3, 83 (1986).\n\n .. [Nielson83] G. Nielson,\n ''A method for interpolating scattered data based upon a minimum norm\n network''.\n Math. Comp., 40, 253 (1983).\n\n .. [Renka84] R. J. Renka and A. K. Cline.\n ''A Triangle-based C1 interpolation method.'',\n Rocky Mountain J. Math., 14, 223 (1984).\n\n "; +static char __pyx_k_29[] = "\n CloughTocher2DInterpolator(points, values, tol=1e-6)\n\n Piecewise cubic, C1 smooth, curvature-minimizing interpolant in 2D.\n\n .. versionadded:: 0.9\n\n Parameters\n ----------\n points : ndarray of floats, shape (npoints, ndims)\n Data point coordinates.\n values : ndarray of float or complex, shape (npoints, ...)\n Data values.\n fill_value : float, optional\n Value used to fill in for requested points outside of the\n convex hull of the input points. If not provided, then\n the default is ``nan``.\n tol : float, optional\n Absolute/relative tolerance for gradient estimation.\n maxiter : int, optional\n Maximum number of iterations in gradient estimation.\n\n Notes\n -----\n The interpolant is constructed by triangulating the input data\n with Qhull [Qhull]_, and constructing a piecewise cubic\n interpolating Bezier polynomial on each triangle, using a\n Clough-Tocher scheme [CT]_. The interpolant is guaranteed to be\n continuously differentiable.\n\n The gradients of the interpolant are chosen so that the curvature\n of the interpolating surface is approximatively minimized. The\n gradients necessary for this are estimated using the global\n algorithm described in [Nielson83,Renka84]_.\n\n References\n ----------\n\n .. [Qhull] http://www.qhull.org/\n\n .. [CT] See, for example,\n P. Alfeld,\n ''A trivariate Clough-Tocher scheme for tetrahedral data''.\n Computer Aided Geometric Design, 1, 169 (1984);\n G. Farin,\n ''Triangular Bernstein-Bezier patches''.\n Computer Aided Geometric Design, 3, 83 (1986).\n\n .. [Nielson83] G. Nielson,\n ''A method for interpolating scattered data based upon a minimum norm\n network''.\n Math. Comp., 40, 253 (1983).\n\n .. [Renka84] R. J. Renka and A. K. Cline.\n ''A Triangle-based C1 interpolation method.'',\n Rocky Mountain J. Math., 14, 223 (1984).\n\n "; static char __pyx_k_30[] = "CloughTocher2DInterpolator"; -static char __pyx_k_31[] = "NDInterpolatorBase.__init__ (line 58)"; -static char __pyx_k_32[] = "NDInterpolatorBase._check_init_shape (line 91)"; -static char __pyx_k_33[] = "NDInterpolatorBase.__call__ (line 112)"; -static char __pyx_k_34[] = "_ndim_coords_from_arrays (line 137)"; +static char __pyx_k_31[] = "NDInterpolatorBase.__init__ (line 54)"; +static char __pyx_k_32[] = "NDInterpolatorBase._check_init_shape (line 87)"; +static char __pyx_k_33[] = "NDInterpolatorBase.__call__ (line 108)"; +static char __pyx_k_34[] = "_ndim_coords_from_arrays (line 133)"; static char __pyx_k__B[] = "B"; static char __pyx_k__H[] = "H"; static char __pyx_k__I[] = "I"; @@ -1086,13 +1086,13 @@ values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__points); if (likely(values[1])) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("__init__", 0, 3, 5, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 58; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("__init__", 0, 3, 5, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 54; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 2: values[2] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__values); if (likely(values[2])) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("__init__", 0, 3, 5, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 58; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("__init__", 0, 3, 5, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 54; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 3: if (kw_args > 0) { @@ -1106,7 +1106,7 @@ } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "__init__") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 58; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "__init__") < 0)) {__pyx_filename = __pyx_f[0]; 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__pyx_lineno = 74; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - __pyx_t_1 = PyTuple_New(1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 78; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyTuple_New(1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 74; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); PyTuple_SET_ITEM(__pyx_t_1, 0, __pyx_t_6); __Pyx_GIVEREF(__pyx_t_6); __pyx_t_6 = 0; - __pyx_t_6 = PyObject_Call(__pyx_t_4, __pyx_t_1, NULL); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 78; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyObject_Call(__pyx_t_4, __pyx_t_1, NULL); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 74; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - __pyx_t_1 = PyTuple_New(2); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyTuple_New(2); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 73; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); PyTuple_SET_ITEM(__pyx_t_1, 0, __pyx_t_2); __Pyx_GIVEREF(__pyx_t_2); @@ -1322,34 +1322,34 @@ __Pyx_GIVEREF(__pyx_t_6); __pyx_t_2 = 0; __pyx_t_6 = 0; - __pyx_t_6 = PyObject_Call(__pyx_t_3, __pyx_t_1, NULL); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyObject_Call(__pyx_t_3, __pyx_t_1, NULL); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 73; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - if (PyObject_SetAttr(__pyx_v_self, __pyx_n_s__values, __pyx_t_6) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyObject_SetAttr(__pyx_v_self, __pyx_n_s__values, __pyx_t_6) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 73; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; } __pyx_L6:; - __pyx_t_6 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 81; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); - __pyx_t_1 = PyObject_GetAttr(__pyx_t_6, __pyx_n_s__issubdtype); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 81; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_t_6, __pyx_n_s__issubdtype); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; - __pyx_t_6 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__values); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 81; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__values); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); - __pyx_t_3 = PyObject_GetAttr(__pyx_t_6, __pyx_n_s__dtype); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 81; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_GetAttr(__pyx_t_6, __pyx_n_s__dtype); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; - __pyx_t_6 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 81; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); - __pyx_t_2 = PyObject_GetAttr(__pyx_t_6, __pyx_n_s__complexfloating); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 81; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyObject_GetAttr(__pyx_t_6, __pyx_n_s__complexfloating); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; - __pyx_t_6 = PyTuple_New(2); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 81; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyTuple_New(2); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; 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__pyx_t_2 = 0; - __pyx_t_2 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__is_complex); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 82; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__is_complex); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 78; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); - __pyx_t_5 = __Pyx_PyObject_IsTrue(__pyx_t_2); if (unlikely(__pyx_t_5 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 82; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = __Pyx_PyObject_IsTrue(__pyx_t_2); if (unlikely(__pyx_t_5 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 78; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; if (__pyx_t_5) { - __pyx_t_2 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__values); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__values); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 79; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); - __pyx_t_6 = PyObject_GetAttr(__pyx_t_2, __pyx_n_s__astype); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyObject_GetAttr(__pyx_t_2, __pyx_n_s__astype); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 79; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - __pyx_t_2 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 79; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); - __pyx_t_1 = PyObject_GetAttr(__pyx_t_2, __pyx_n_s__complex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_t_2, __pyx_n_s__complex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 79; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - __pyx_t_2 = PyTuple_New(1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyTuple_New(1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 79; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); PyTuple_SET_ITEM(__pyx_t_2, 0, __pyx_t_1); __Pyx_GIVEREF(__pyx_t_1); __pyx_t_1 = 0; - __pyx_t_1 = PyObject_Call(__pyx_t_6, __pyx_t_2, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_Call(__pyx_t_6, __pyx_t_2, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 79; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - if (PyObject_SetAttr(__pyx_v_self, __pyx_n_s__values, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyObject_SetAttr(__pyx_v_self, __pyx_n_s__values, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 79; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - __pyx_t_1 = PyTuple_New(1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 84; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyTuple_New(1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 80; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_INCREF(__pyx_v_fill_value); PyTuple_SET_ITEM(__pyx_t_1, 0, __pyx_v_fill_value); __Pyx_GIVEREF(__pyx_v_fill_value); - __pyx_t_2 = PyObject_Call(((PyObject*)&PyComplex_Type), __pyx_t_1, NULL); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 84; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyObject_Call(((PyObject*)&PyComplex_Type), __pyx_t_1, NULL); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 80; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - if (PyObject_SetAttr(__pyx_v_self, __pyx_n_s__fill_value, __pyx_t_2) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 84; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyObject_SetAttr(__pyx_v_self, __pyx_n_s__fill_value, __pyx_t_2) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 80; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; goto __pyx_L7; } { - __pyx_t_2 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__values); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; 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goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyObject_IsTrue(__pyx_t_1); if (unlikely(__pyx_t_4 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 94; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; if (__pyx_t_4) { - __pyx_t_1 = PyTuple_New(1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 99; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyTuple_New(1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 95; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_INCREF(((PyObject *)__pyx_kp_s_4)); PyTuple_SET_ITEM(__pyx_t_1, 0, ((PyObject *)__pyx_kp_s_4)); __Pyx_GIVEREF(((PyObject *)__pyx_kp_s_4)); - __pyx_t_3 = PyObject_Call(__pyx_builtin_ValueError, __pyx_t_1, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 99; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_Call(__pyx_builtin_ValueError, __pyx_t_1, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; 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__pyx_lineno = 135; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = PyTuple_New(1); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 131; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_3); __Pyx_GIVEREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyObject_Call(__pyx_t_1, __pyx_t_4, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 135; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_Call(__pyx_t_1, __pyx_t_4, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 131; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; @@ -2112,7 +2112,7 @@ __pyx_t_1 = PyTuple_Check(__pyx_v_points); if (__pyx_t_1) { - __pyx_t_2 = PyObject_Length(__pyx_v_points); if (unlikely(__pyx_t_2 == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 142; 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if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 146; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_7 = PyObject_Call(__pyx_t_6, ((PyObject *)__pyx_t_5), NULL); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 142; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_7); __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; __Pyx_DECREF(((PyObject *)__pyx_t_5)); __pyx_t_5 = 0; @@ -2151,10 +2151,10 @@ __pyx_t_7 = 0; - __pyx_t_8 = PyObject_Length(__pyx_v_p); if (unlikely(__pyx_t_8 == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_t_7 = PyInt_FromSsize_t(__pyx_t_8); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = PyObject_Length(__pyx_v_p); if (unlikely(__pyx_t_8 == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 143; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_7 = PyInt_FromSsize_t(__pyx_t_8); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 143; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_7); - __pyx_t_5 = PyTuple_New(2); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = PyTuple_New(2); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 143; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); __Pyx_INCREF(__pyx_int_1); PyTuple_SET_ITEM(__pyx_t_5, 0, __pyx_int_1); @@ -2162,13 +2162,13 @@ PyTuple_SET_ITEM(__pyx_t_5, 1, __pyx_t_7); __Pyx_GIVEREF(__pyx_t_7); __pyx_t_7 = 0; - __pyx_t_7 = PyObject_Call(__pyx_builtin_xrange, __pyx_t_5, NULL); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_7 = PyObject_Call(__pyx_builtin_xrange, __pyx_t_5, NULL); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 143; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_7); __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; if (PyList_CheckExact(__pyx_t_7) || PyTuple_CheckExact(__pyx_t_7)) { __pyx_t_2 = 0; __pyx_t_5 = __pyx_t_7; __Pyx_INCREF(__pyx_t_5); } else { - __pyx_t_2 = -1; __pyx_t_5 = PyObject_GetIter(__pyx_t_7); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = -1; __pyx_t_5 = PyObject_GetIter(__pyx_t_7); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 143; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); } __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; @@ -2182,7 +2182,7 @@ } else { __pyx_t_7 = PyIter_Next(__pyx_t_5); if (!__pyx_t_7) { - if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 143; __pyx_clineno = __LINE__; goto __pyx_L1_error;} break; } __Pyx_GOTREF(__pyx_t_7); @@ -2192,36 +2192,36 @@ __pyx_t_7 = 0; - __pyx_t_7 = PyObject_GetItem(__pyx_v_p, __pyx_v_j); if (!__pyx_t_7) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 148; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_7 = PyObject_GetItem(__pyx_v_p, __pyx_v_j); if (!__pyx_t_7) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 144; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_7); - __pyx_t_6 = PyObject_GetAttr(__pyx_t_7, __pyx_n_s__shape); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 148; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyObject_GetAttr(__pyx_t_7, __pyx_n_s__shape); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 144; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; - __pyx_t_7 = __Pyx_GetItemInt(__pyx_v_p, 0, sizeof(long), PyInt_FromLong); if (!__pyx_t_7) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 148; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_7 = __Pyx_GetItemInt(__pyx_v_p, 0, sizeof(long), PyInt_FromLong); if (!__pyx_t_7) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 144; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_7); - __pyx_t_9 = PyObject_GetAttr(__pyx_t_7, __pyx_n_s__shape); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 148; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PyObject_GetAttr(__pyx_t_7, __pyx_n_s__shape); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 144; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; - __pyx_t_7 = PyObject_RichCompare(__pyx_t_6, __pyx_t_9, Py_NE); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 148; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_7 = PyObject_RichCompare(__pyx_t_6, __pyx_t_9, Py_NE); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 144; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_7); __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; - __pyx_t_4 = __Pyx_PyObject_IsTrue(__pyx_t_7); if (unlikely(__pyx_t_4 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 148; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyObject_IsTrue(__pyx_t_7); if (unlikely(__pyx_t_4 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 144; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; if (__pyx_t_4) { - __pyx_t_7 = PyTuple_New(1); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 149; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_7 = PyTuple_New(1); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_7); __Pyx_INCREF(((PyObject *)__pyx_kp_s_8)); PyTuple_SET_ITEM(__pyx_t_7, 0, ((PyObject *)__pyx_kp_s_8)); __Pyx_GIVEREF(((PyObject *)__pyx_kp_s_8)); - __pyx_t_9 = PyObject_Call(__pyx_builtin_ValueError, __pyx_t_7, NULL); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 149; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PyObject_Call(__pyx_builtin_ValueError, __pyx_t_7, NULL); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; __Pyx_Raise(__pyx_t_9, 0, 0); __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 149; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} goto __pyx_L9; } __pyx_L9:; @@ -2229,37 +2229,37 @@ __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; - __pyx_t_5 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 150; __pyx_clineno = __LINE__; 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if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 156; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_7 = PyObject_GetAttr(__pyx_v_points, __pyx_n_s__reshape); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 152; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_7); - __pyx_t_6 = PyTuple_New(2); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 156; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyTuple_New(2); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 152; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); __Pyx_INCREF(__pyx_int_neg_1); PyTuple_SET_ITEM(__pyx_t_6, 0, __pyx_int_neg_1); @@ -2362,7 +2362,7 @@ __Pyx_INCREF(__pyx_int_1); PyTuple_SET_ITEM(__pyx_t_6, 1, __pyx_int_1); __Pyx_GIVEREF(__pyx_int_1); - __pyx_t_5 = PyObject_Call(__pyx_t_7, __pyx_t_6, NULL); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 156; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = PyObject_Call(__pyx_t_7, __pyx_t_6, NULL); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 152; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; @@ -2438,13 +2438,13 @@ values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__points); if (likely(values[1])) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("__init__", 0, 3, 4, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 194; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("__init__", 0, 3, 4, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 190; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 2: values[2] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__values); if (likely(values[2])) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("__init__", 0, 3, 4, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 194; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("__init__", 0, 3, 4, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 190; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 3: if (kw_args > 0) { @@ -2453,7 +2453,7 @@ } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "__init__") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 194; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "__init__") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 190; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } __pyx_v_self = values[0]; __pyx_v_points = values[1]; @@ -2474,7 +2474,7 @@ } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; - __Pyx_RaiseArgtupleInvalid("__init__", 0, 3, 4, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 194; __pyx_clineno = __LINE__; 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goto __pyx_L1_error;} + __pyx_t_7 = PyNumber_Multiply(__pyx_t_9, __pyx_int_100); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 262; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_7); __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; __Pyx_DECREF(__pyx_v_eps); @@ -3330,8 +3327,8 @@ __pyx_v_i = __pyx_t_11; - __pyx_t_16 = __pyx_PyFloat_AsDouble(__pyx_v_eps); if (unlikely((__pyx_t_16 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L7;} - __pyx_v_isimplex = __pyx_f_5scipy_7spatial_5qhull__find_simplex(__pyx_v_info, __pyx_v_c, (((double *)__pyx_v_xi->data) + (__pyx_v_i * __pyx_v_ndim)), (&__pyx_v_start), __pyx_t_16); + __pyx_t_16 = __pyx_PyFloat_AsDouble(__pyx_v_eps); if (unlikely((__pyx_t_16 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 271; __pyx_clineno = __LINE__; goto __pyx_L7;} + __pyx_v_isimplex = __pyx_f_5scipy_7spatial_5qhull__find_simplex((&__pyx_v_info), __pyx_v_c, (((double *)__pyx_v_xi->data) + (__pyx_v_i * __pyx_v_ndim)), (&__pyx_v_start), __pyx_t_16); 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if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 491; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyObject_RichCompare(__pyx_t_1, __pyx_t_3, Py_NE); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 485; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_4 = __Pyx_PyObject_IsTrue(__pyx_t_2); if (unlikely(__pyx_t_4 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 491; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyObject_IsTrue(__pyx_t_2); if (unlikely(__pyx_t_4 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 485; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; if (__pyx_t_4) { - __pyx_t_2 = PyTuple_New(1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 492; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyTuple_New(1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 486; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_INCREF(((PyObject *)__pyx_kp_s_11)); PyTuple_SET_ITEM(__pyx_t_2, 0, ((PyObject *)__pyx_kp_s_11)); __Pyx_GIVEREF(((PyObject *)__pyx_kp_s_11)); - __pyx_t_3 = PyObject_Call(__pyx_builtin_ValueError, __pyx_t_2, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 492; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_Call(__pyx_builtin_ValueError, __pyx_t_2, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 486; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; __Pyx_Raise(__pyx_t_3, 0, 0); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 492; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 486; __pyx_clineno = __LINE__; 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__pyx_lineno = 504; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyObject_IsTrue(__pyx_t_5); if (unlikely(__pyx_t_4 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 498; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; if (__pyx_t_4) { - __pyx_t_5 = PySlice_New(Py_None, Py_None, Py_None); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 505; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = PySlice_New(Py_None, Py_None, Py_None); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 499; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); - __pyx_t_3 = PyTuple_New(2); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 505; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyTuple_New(2); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 499; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); 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- __pyx_t_3 = PyObject_GetAttr(__pyx_v_tri, __pyx_n_s__npoints); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 507; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_GetAttr(__pyx_v_tri, __pyx_n_s__npoints); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 501; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - __pyx_t_2 = PyTuple_New(2); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 507; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyTuple_New(2); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 501; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); PyTuple_SET_ITEM(__pyx_t_2, 0, __pyx_t_3); __Pyx_GIVEREF(__pyx_t_3); @@ -4032,11 +4026,11 @@ PyTuple_SET_ITEM(__pyx_t_2, 1, __pyx_int_neg_1); __Pyx_GIVEREF(__pyx_int_neg_1); __pyx_t_3 = 0; - __pyx_t_3 = PyObject_Call(__pyx_t_5, __pyx_t_2, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; 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goto __pyx_L1_error;} + __pyx_t_2 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 502; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); - __pyx_t_3 = PyObject_GetAttr(__pyx_t_2, __pyx_n_s__ascontiguousarray); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 508; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_GetAttr(__pyx_t_2, __pyx_n_s__ascontiguousarray); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 502; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - __pyx_t_2 = PyTuple_New(1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 508; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyTuple_New(1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 502; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_INCREF(__pyx_v_y); PyTuple_SET_ITEM(__pyx_t_2, 0, __pyx_v_y); __Pyx_GIVEREF(__pyx_v_y); - __pyx_t_5 = PyObject_Call(__pyx_t_3, __pyx_t_2, NULL); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 508; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = PyObject_Call(__pyx_t_3, __pyx_t_2, NULL); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 502; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - __pyx_t_2 = PyObject_GetAttr(__pyx_t_5, __pyx_n_s__astype); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 508; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyObject_GetAttr(__pyx_t_5, __pyx_n_s__astype); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 502; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; - __pyx_t_5 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 508; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 502; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); - __pyx_t_3 = PyObject_GetAttr(__pyx_t_5, __pyx_n_s__double); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 508; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_GetAttr(__pyx_t_5, __pyx_n_s__double); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 502; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; - __pyx_t_5 = PyTuple_New(1); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 508; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = PyTuple_New(1); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 502; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); PyTuple_SET_ITEM(__pyx_t_5, 0, __pyx_t_3); __Pyx_GIVEREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyObject_Call(__pyx_t_2, __pyx_t_5, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 508; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_Call(__pyx_t_2, __pyx_t_5, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 502; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; @@ -4080,22 +4074,22 @@ __pyx_t_3 = 0; - __pyx_t_3 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 509; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - __pyx_t_5 = PyObject_GetAttr(__pyx_t_3, __pyx_n_s__empty); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 509; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = PyObject_GetAttr(__pyx_t_3, __pyx_n_s__empty); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyObject_GetAttr(__pyx_v_y, __pyx_n_s__shape); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 509; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_GetAttr(__pyx_v_y, __pyx_n_s__shape); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - __pyx_t_2 = __Pyx_GetItemInt(__pyx_t_3, 0, sizeof(long), PyInt_FromLong); if (!__pyx_t_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 509; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = __Pyx_GetItemInt(__pyx_t_3, 0, sizeof(long), PyInt_FromLong); if (!__pyx_t_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyObject_GetAttr(__pyx_v_y, __pyx_n_s__shape); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 509; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_GetAttr(__pyx_v_y, __pyx_n_s__shape); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - __pyx_t_1 = __Pyx_GetItemInt(__pyx_t_3, 1, sizeof(long), PyInt_FromLong); if (!__pyx_t_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 509; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_GetItemInt(__pyx_t_3, 1, sizeof(long), PyInt_FromLong); if (!__pyx_t_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyTuple_New(3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 509; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyTuple_New(3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); PyTuple_SET_ITEM(__pyx_t_3, 0, __pyx_t_2); __Pyx_GIVEREF(__pyx_t_2); @@ -4106,12 +4100,12 @@ __Pyx_GIVEREF(__pyx_int_2); __pyx_t_2 = 0; __pyx_t_1 = 0; - __pyx_t_1 = PyTuple_New(1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 509; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyTuple_New(1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); PyTuple_SET_ITEM(__pyx_t_1, 0, __pyx_t_3); __Pyx_GIVEREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyObject_Call(__pyx_t_5, __pyx_t_1, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 509; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_Call(__pyx_t_5, __pyx_t_1, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; @@ -4120,7 +4114,7 @@ __pyx_t_3 = 0; - if (!(likely(((__pyx_v_y) == Py_None) || likely(__Pyx_TypeTest(__pyx_v_y, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 511; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_v_y) == Py_None) || likely(__Pyx_TypeTest(__pyx_v_y, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 505; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_6 = ((PyArrayObject *)__pyx_v_y); { __Pyx_BufFmt_StackElem __pyx_stack[1]; @@ -4137,7 +4131,7 @@ } __pyx_bstride_0_data = __pyx_bstruct_data.strides[0]; __pyx_bstride_1_data = __pyx_bstruct_data.strides[1]; __pyx_bshape_0_data = __pyx_bstruct_data.shape[0]; __pyx_bshape_1_data = __pyx_bstruct_data.shape[1]; - if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 511; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 505; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_6 = 0; __Pyx_INCREF(__pyx_v_y); @@ -4145,7 +4139,7 @@ __pyx_v_data = ((PyArrayObject *)__pyx_v_y); - if (!(likely(((__pyx_v_yi) == Py_None) || likely(__Pyx_TypeTest(__pyx_v_yi, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 512; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_v_yi) == Py_None) || likely(__Pyx_TypeTest(__pyx_v_yi, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 506; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_11 = ((PyArrayObject *)__pyx_v_yi); 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__Pyx_INCREF(Py_None); __pyx_bstruct_values.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1062; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1055; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_bstride_0_values = __pyx_bstruct_values.strides[0]; __pyx_bstride_1_values = __pyx_bstruct_values.strides[1]; __pyx_bshape_0_values = __pyx_bstruct_values.shape[0]; __pyx_bshape_1_values = __pyx_bstruct_values.shape[1]; } @@ -5286,15 +5277,15 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__grad); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1063; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__grad); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1056; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1063; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1056; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_3 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_grad, (PyObject*)__pyx_t_3, &__Pyx_TypeInfo_nn___pyx_t_5numpy_double_t, PyBUF_FORMAT| PyBUF_STRIDES, 3, 0, __pyx_stack) == -1)) { __pyx_v_grad = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_bstruct_grad.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1063; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1056; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_bstride_0_grad = __pyx_bstruct_grad.strides[0]; __pyx_bstride_1_grad = __pyx_bstruct_grad.strides[1]; __pyx_bstride_2_grad = __pyx_bstruct_grad.strides[2]; __pyx_bshape_0_grad = __pyx_bstruct_grad.shape[0]; __pyx_bshape_1_grad = __pyx_bstruct_grad.shape[1]; __pyx_bshape_2_grad = __pyx_bstruct_grad.shape[2]; } @@ -5304,15 +5295,15 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__points); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1065; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__points); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1058; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1065; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1058; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_4 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_points, (PyObject*)__pyx_t_4, &__Pyx_TypeInfo_nn___pyx_t_5numpy_double_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) { __pyx_v_points = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_bstruct_points.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1065; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1058; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_bstride_0_points = __pyx_bstruct_points.strides[0]; __pyx_bstride_1_points = __pyx_bstruct_points.strides[1]; __pyx_bshape_0_points = __pyx_bstruct_points.shape[0]; __pyx_bshape_1_points = __pyx_bstruct_points.shape[1]; } @@ -5322,18 +5313,18 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__tri); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1066; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__tri); 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{ __Pyx_BufFmt_StackElem __pyx_stack[1]; if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_vertices, (PyObject*)__pyx_t_6, &__Pyx_TypeInfo_nn_npy_int, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) { __pyx_v_vertices = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_bstruct_vertices.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1066; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1059; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_bstride_0_vertices = __pyx_bstruct_vertices.strides[0]; __pyx_bstride_1_vertices = __pyx_bstruct_vertices.strides[1]; __pyx_bshape_0_vertices = __pyx_bstruct_vertices.shape[0]; __pyx_bshape_1_vertices = __pyx_bstruct_vertices.shape[1]; } @@ -5349,35 +5340,35 @@ __pyx_v_start = 0; - __pyx_t_5 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__fill_value); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1077; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__fill_value); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1070; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); - __pyx_t_7 = __pyx_PyFloat_AsDouble(__pyx_t_5); if (unlikely((__pyx_t_7 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1077; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_7 = __pyx_PyFloat_AsDouble(__pyx_t_5); if (unlikely((__pyx_t_7 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1070; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; __pyx_v_fill_value = __pyx_t_7; - __pyx_t_5 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__tri); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1079; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__tri); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1072; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); 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__pyx_t_5 = 0; - __pyx_t_5 = __Pyx_PyInt_to_py_Py_intptr_t((__pyx_v_xi->dimensions[0])); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1081; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = __Pyx_PyInt_to_py_Py_intptr_t((__pyx_v_xi->dimensions[0])); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1074; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); - __pyx_t_8 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__values); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1081; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__values); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1074; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_8); - __pyx_t_9 = PyObject_GetAttr(__pyx_t_8, __pyx_n_s__shape); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1081; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PyObject_GetAttr(__pyx_t_8, __pyx_n_s__shape); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1074; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); __Pyx_DECREF(__pyx_t_8); __pyx_t_8 = 0; - __pyx_t_8 = __Pyx_GetItemInt(__pyx_t_9, 1, sizeof(long), PyInt_FromLong); if (!__pyx_t_8) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1081; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = __Pyx_GetItemInt(__pyx_t_9, 1, sizeof(long), PyInt_FromLong); if (!__pyx_t_8) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1074; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_8); __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; - __pyx_t_9 = PyTuple_New(2); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1081; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PyTuple_New(2); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1074; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); PyTuple_SET_ITEM(__pyx_t_9, 0, __pyx_t_5); __Pyx_GIVEREF(__pyx_t_5); @@ -5385,26 +5376,26 @@ __Pyx_GIVEREF(__pyx_t_8); __pyx_t_5 = 0; __pyx_t_8 = 0; - __pyx_t_8 = PyTuple_New(1); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1081; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = PyTuple_New(1); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1074; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_8); PyTuple_SET_ITEM(__pyx_t_8, 0, __pyx_t_9); __Pyx_GIVEREF(__pyx_t_9); __pyx_t_9 = 0; - __pyx_t_9 = PyDict_New(); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1081; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PyDict_New(); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1074; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(((PyObject *)__pyx_t_9)); - __pyx_t_5 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1081; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1074; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); - __pyx_t_10 = PyObject_GetAttr(__pyx_t_5, __pyx_n_s__double); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1081; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_10 = PyObject_GetAttr(__pyx_t_5, __pyx_n_s__double); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1074; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_10); __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; - if (PyDict_SetItem(__pyx_t_9, ((PyObject *)__pyx_n_s__dtype), __pyx_t_10) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1081; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_t_9, ((PyObject *)__pyx_n_s__dtype), __pyx_t_10) < 0) {__pyx_filename = __pyx_f[0]; 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__pyx_lineno = 1074; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_11 = ((PyArrayObject *)__pyx_t_10); { __Pyx_BufFmt_StackElem __pyx_stack[1]; @@ -5421,7 +5412,7 @@ } __pyx_bstride_0_out = __pyx_bstruct_out.strides[0]; __pyx_bstride_1_out = __pyx_bstruct_out.strides[1]; __pyx_bshape_0_out = __pyx_bstruct_out.shape[0]; __pyx_bshape_1_out = __pyx_bstruct_out.shape[1]; - if (unlikely(__pyx_t_12 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1081; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__pyx_t_12 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1074; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_11 = 0; __Pyx_DECREF(((PyObject *)__pyx_v_out)); @@ -5432,29 +5423,29 @@ __pyx_v_nvalues = (__pyx_v_out->dimensions[1]); - __pyx_t_10 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1084; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_10 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1077; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_10); - __pyx_t_9 = PyObject_GetAttr(__pyx_t_10, __pyx_n_s__finfo); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1084; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PyObject_GetAttr(__pyx_t_10, __pyx_n_s__finfo); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1077; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); __Pyx_DECREF(__pyx_t_10); __pyx_t_10 = 0; - __pyx_t_10 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1084; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_10 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1077; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_10); - __pyx_t_8 = PyObject_GetAttr(__pyx_t_10, __pyx_n_s__double); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1084; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = PyObject_GetAttr(__pyx_t_10, __pyx_n_s__double); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1077; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_8); __Pyx_DECREF(__pyx_t_10); __pyx_t_10 = 0; - __pyx_t_10 = PyTuple_New(1); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1084; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_10 = PyTuple_New(1); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1077; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_10); PyTuple_SET_ITEM(__pyx_t_10, 0, __pyx_t_8); __Pyx_GIVEREF(__pyx_t_8); __pyx_t_8 = 0; - __pyx_t_8 = PyObject_Call(__pyx_t_9, __pyx_t_10, NULL); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1084; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = PyObject_Call(__pyx_t_9, __pyx_t_10, NULL); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1077; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_8); __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; __Pyx_DECREF(__pyx_t_10); __pyx_t_10 = 0; - __pyx_t_10 = PyObject_GetAttr(__pyx_t_8, __pyx_n_s__eps); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1084; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_10 = PyObject_GetAttr(__pyx_t_8, __pyx_n_s__eps); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1077; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_10); __Pyx_DECREF(__pyx_t_8); __pyx_t_8 = 0; - __pyx_t_8 = PyNumber_Multiply(__pyx_t_10, __pyx_int_100); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1084; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = PyNumber_Multiply(__pyx_t_10, __pyx_int_100); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1077; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_8); __Pyx_DECREF(__pyx_t_10); __pyx_t_10 = 0; __Pyx_DECREF(__pyx_v_eps); @@ -5472,8 +5463,8 @@ __pyx_v_i = __pyx_t_12; - __pyx_t_7 = __pyx_PyFloat_AsDouble(__pyx_v_eps); if (unlikely((__pyx_t_7 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1092; __pyx_clineno = __LINE__; goto __pyx_L7;} - __pyx_v_isimplex = __pyx_f_5scipy_7spatial_5qhull__find_simplex(__pyx_v_info, __pyx_v_c, (((double *)__pyx_v_xi->data) + (__pyx_v_i * __pyx_v_ndim)), (&__pyx_v_start), __pyx_t_7); + __pyx_t_7 = __pyx_PyFloat_AsDouble(__pyx_v_eps); if (unlikely((__pyx_t_7 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1085; __pyx_clineno = __LINE__; goto __pyx_L7;} + __pyx_v_isimplex = __pyx_f_5scipy_7spatial_5qhull__find_simplex((&__pyx_v_info), __pyx_v_c, (((double *)__pyx_v_xi->data) + (__pyx_v_i * __pyx_v_ndim)), (&__pyx_v_start), __pyx_t_7); __pyx_t_17 = (__pyx_v_isimplex == -1); @@ -5547,7 +5538,7 @@ } - __pyx_v_w = __pyx_f_8interpnd__clough_tocher_2d_single_double(__pyx_v_info, __pyx_v_isimplex, __pyx_v_c, __pyx_v_f, __pyx_v_df); 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{__pyx_filename = __pyx_f[0]; __pyx_lineno = 1109; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_L3_error:; __Pyx_AddTraceback("interpnd.CloughTocher2DInterpolator._evaluate_complex"); __Pyx_RefNannyFinishContext(); @@ -5788,24 +5776,24 @@ __pyx_bstruct_points.buf = NULL; __pyx_bstruct_vertices.buf = NULL; __pyx_bstruct_xi.buf = NULL; - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_xi), __pyx_ptype_5numpy_ndarray, 1, "xi", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1117; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_xi), __pyx_ptype_5numpy_ndarray, 1, "xi", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1109; __pyx_clineno = __LINE__; goto __pyx_L1_error;} { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_xi, (PyObject*)__pyx_v_xi, &__Pyx_TypeInfo_nn___pyx_t_5numpy_double_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1117; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_xi, (PyObject*)__pyx_v_xi, &__Pyx_TypeInfo_nn___pyx_t_5numpy_double_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1109; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_bstride_0_xi = __pyx_bstruct_xi.strides[0]; __pyx_bstride_1_xi = __pyx_bstruct_xi.strides[1]; __pyx_bshape_0_xi = __pyx_bstruct_xi.shape[0]; __pyx_bshape_1_xi = __pyx_bstruct_xi.shape[1]; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__values); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1118; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__values); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1110; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1118; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1110; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_2 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[2]; if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_values, (PyObject*)__pyx_t_2, &__Pyx_TypeInfo_nn___pyx_t_5numpy_complex_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) { __pyx_v_values = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_bstruct_values.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1118; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1110; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_bstride_0_values = __pyx_bstruct_values.strides[0]; __pyx_bstride_1_values = __pyx_bstruct_values.strides[1]; __pyx_bshape_0_values = __pyx_bstruct_values.shape[0]; 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__Pyx_INCREF(Py_None); __pyx_bstruct_grad.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1119; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1111; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_bstride_0_grad = __pyx_bstruct_grad.strides[0]; __pyx_bstride_1_grad = __pyx_bstruct_grad.strides[1]; __pyx_bstride_2_grad = __pyx_bstruct_grad.strides[2]; __pyx_bshape_0_grad = __pyx_bstruct_grad.shape[0]; __pyx_bshape_1_grad = __pyx_bstruct_grad.shape[1]; __pyx_bshape_2_grad = __pyx_bstruct_grad.shape[2]; } @@ -5833,15 +5821,15 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__points); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1121; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__points); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1113; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); 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__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - if (!(likely(((__pyx_t_5) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_5, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1122; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_5) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_5, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1114; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_6 = ((PyArrayObject *)__pyx_t_5); { __Pyx_BufFmt_StackElem __pyx_stack[1]; if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_vertices, (PyObject*)__pyx_t_6, &__Pyx_TypeInfo_nn_npy_int, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) { __pyx_v_vertices = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_bstruct_vertices.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1122; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1114; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_bstride_0_vertices = __pyx_bstruct_vertices.strides[0]; 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goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; __pyx_v_fill_value = __pyx_t_7; - __pyx_t_5 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__tri); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1135; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__tri); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1127; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); - __pyx_v_info = __pyx_f_5scipy_7spatial_5qhull__get_delaunay_info(__pyx_t_5, 1, 1); + __pyx_f_5scipy_7spatial_5qhull__get_delaunay_info((&__pyx_v_info), __pyx_t_5, 1, 1); __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; - __pyx_t_5 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1137; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1129; 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__pyx_lineno = 1132; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_10); __Pyx_DECREF(__pyx_t_8); __pyx_t_8 = 0; - __pyx_t_8 = PyNumber_Multiply(__pyx_t_10, __pyx_int_100); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1140; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = PyNumber_Multiply(__pyx_t_10, __pyx_int_100); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1132; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_8); __Pyx_DECREF(__pyx_t_10); __pyx_t_10 = 0; __Pyx_DECREF(__pyx_v_eps); @@ -6001,8 +5989,8 @@ __pyx_v_i = __pyx_t_12; - __pyx_t_17 = __pyx_PyFloat_AsDouble(__pyx_v_eps); if (unlikely((__pyx_t_17 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1148; __pyx_clineno = __LINE__; goto __pyx_L7;} - __pyx_v_isimplex = __pyx_f_5scipy_7spatial_5qhull__find_simplex(__pyx_v_info, __pyx_v_c, (((double *)__pyx_v_xi->data) + (__pyx_v_i * __pyx_v_ndim)), (&__pyx_v_start), __pyx_t_17); 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if (!__pyx_builtin_object) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 50; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_builtin_Warning = __Pyx_GetName(__pyx_b, __pyx_n_s__Warning); if (!__pyx_builtin_Warning) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 305; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_builtin_ValueError = __Pyx_GetName(__pyx_b, __pyx_n_s__ValueError); if (!__pyx_builtin_ValueError) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 97; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_object = __Pyx_GetName(__pyx_b, __pyx_n_s__object); if (!__pyx_builtin_object) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_Warning = __Pyx_GetName(__pyx_b, __pyx_n_s__Warning); if (!__pyx_builtin_Warning) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 299; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_ValueError = __Pyx_GetName(__pyx_b, __pyx_n_s__ValueError); if (!__pyx_builtin_ValueError) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 93; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #if PY_MAJOR_VERSION >= 3 - __pyx_builtin_xrange = __Pyx_GetName(__pyx_b, __pyx_n_s__range); if (!__pyx_builtin_xrange) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_xrange = __Pyx_GetName(__pyx_b, __pyx_n_s__range); if (!__pyx_builtin_xrange) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 143; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #else - __pyx_builtin_xrange = __Pyx_GetName(__pyx_b, __pyx_n_s__xrange); if (!__pyx_builtin_xrange) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_xrange = __Pyx_GetName(__pyx_b, __pyx_n_s__xrange); if (!__pyx_builtin_xrange) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 143; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #endif - __pyx_builtin_enumerate = __Pyx_GetName(__pyx_b, __pyx_n_s__enumerate); if (!__pyx_builtin_enumerate) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 151; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_enumerate = __Pyx_GetName(__pyx_b, __pyx_n_s__enumerate); if (!__pyx_builtin_enumerate) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_builtin_range = __Pyx_GetName(__pyx_b, __pyx_n_s__range); if (!__pyx_builtin_range) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 219; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_builtin_RuntimeError = __Pyx_GetName(__pyx_b, __pyx_n_s__RuntimeError); if (!__pyx_builtin_RuntimeError) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 787; __pyx_clineno = __LINE__; goto __pyx_L1_error;} return 0; @@ -7574,7 +7559,7 @@ __pyx_ptype_5numpy_ufunc = __Pyx_ImportType("numpy", "ufunc", sizeof(PyUFuncObject), 0); if (unlikely(!__pyx_ptype_5numpy_ufunc)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 849; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_1 = __Pyx_ImportModule("scipy.spatial.qhull"); if (!__pyx_t_1) {__pyx_filename = __pyx_f[0]; 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__pyx_lineno = 1109; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; - if (PyObject_SetAttr(__pyx_m, __pyx_n_s_30, __pyx_t_5) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 991; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyObject_SetAttr(__pyx_m, __pyx_n_s_30, __pyx_t_5) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 984; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; __Pyx_DECREF(((PyObject *)__pyx_t_3)); __pyx_t_3 = 0; Modified: branches/0.9.x/scipy/spatial/qhull.c =================================================================== --- branches/0.9.x/scipy/spatial/qhull.c 2011-02-19 13:30:19 UTC (rev 7152) +++ branches/0.9.x/scipy/spatial/qhull.c 2011-02-19 13:30:39 UTC (rev 7153) @@ -196,9 +196,9 @@ #endif #include #define __PYX_HAVE_API__scipy__spatial__qhull -#include "stdlib.h" #include "numpy/ndarrayobject.h" #include "stdio.h" +#include "stdlib.h" #include "numpy/arrayobject.h" #include "numpy/ufuncobject.h" #include "math.h" @@ -410,7 +410,7 @@ PyObject_HEAD __pyx_t_5scipy_7spatial_5qhull_RidgeIter2D_t it; PyObject *delaunay; - __pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t *info; + __pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t info; }; #ifndef CYTHON_REFNANNY @@ -769,7 +769,7 @@ static PyTypeObject *__pyx_ptype_5scipy_7spatial_5qhull_RidgeIter2D = 0; -static __pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t *__pyx_f_5scipy_7spatial_5qhull__get_delaunay_info(PyObject *, int, int); +static void __pyx_f_5scipy_7spatial_5qhull__get_delaunay_info(__pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t *, PyObject *, int, int); static int __pyx_f_5scipy_7spatial_5qhull__barycentric_inside(int, double *, double *, double *, double); static void __pyx_f_5scipy_7spatial_5qhull__barycentric_coordinate_single(int, double *, double *, double *, int); static void __pyx_f_5scipy_7spatial_5qhull__barycentric_coordinates(int, double *, double *, double *); @@ -816,13 +816,13 @@ static char __pyx_k_21[] = "_construct_delaunay (line 134)"; static char __pyx_k_22[] = "_qhull_get_facet_array (line 197)"; static char __pyx_k_23[] = "_get_barycentric_transforms (line 278)"; 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__pyx_lineno = 975; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_GetAttr(__pyx_t_1, __pyx_n_s__empty); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 968; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__npoints); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 975; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__npoints); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 968; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_4 = PyTuple_New(1); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 975; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = PyTuple_New(1); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 968; __pyx_clineno = __LINE__; 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__pyx_lineno = 975; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 968; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); - __pyx_t_6 = PyObject_GetAttr(__pyx_t_5, __pyx_n_s__intc); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 975; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyObject_GetAttr(__pyx_t_5, __pyx_n_s__intc); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 968; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; - if (PyDict_SetItem(__pyx_t_4, ((PyObject *)__pyx_n_s__dtype), __pyx_t_6) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 975; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_t_4, ((PyObject *)__pyx_n_s__dtype), __pyx_t_6) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 968; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; - __pyx_t_6 = PyEval_CallObjectWithKeywords(__pyx_t_3, __pyx_t_1, ((PyObject *)__pyx_t_4)); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 975; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyEval_CallObjectWithKeywords(__pyx_t_3, __pyx_t_1, ((PyObject *)__pyx_t_4)); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 968; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0; - if (PyObject_SetAttr(__pyx_v_self, __pyx_n_s___vertex_to_simplex, __pyx_t_6) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 975; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyObject_SetAttr(__pyx_v_self, __pyx_n_s___vertex_to_simplex, __pyx_t_6) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 968; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; - __pyx_t_6 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s___vertex_to_simplex); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 976; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s___vertex_to_simplex); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 969; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); - __pyx_t_4 = PyObject_GetAttr(__pyx_t_6, __pyx_n_s__fill); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 976; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = PyObject_GetAttr(__pyx_t_6, __pyx_n_s__fill); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 969; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; - __pyx_t_6 = PyTuple_New(1); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 976; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyTuple_New(1); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 969; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); __Pyx_INCREF(__pyx_int_neg_1); PyTuple_SET_ITEM(__pyx_t_6, 0, __pyx_int_neg_1); __Pyx_GIVEREF(__pyx_int_neg_1); - __pyx_t_1 = PyObject_Call(__pyx_t_4, __pyx_t_6, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 976; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_Call(__pyx_t_4, __pyx_t_6, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 969; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s___vertex_to_simplex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 978; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s___vertex_to_simplex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 971; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 978; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 971; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_7 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; @@ -4435,7 +4398,7 @@ } __pyx_bstride_0_arr = __pyx_bstruct_arr.strides[0]; __pyx_bshape_0_arr = __pyx_bstruct_arr.shape[0]; - if (unlikely(__pyx_t_8 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 978; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__pyx_t_8 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 971; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_7 = 0; __Pyx_DECREF(((PyObject *)__pyx_v_arr)); @@ -4443,9 +4406,9 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__vertices); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 979; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__vertices); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 972; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 979; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 972; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_12 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; @@ -4462,7 +4425,7 @@ } __pyx_bstride_0_vertices = __pyx_bstruct_vertices.strides[0]; __pyx_bstride_1_vertices = __pyx_bstruct_vertices.strides[1]; __pyx_bshape_0_vertices = __pyx_bstruct_vertices.shape[0]; __pyx_bshape_1_vertices = __pyx_bstruct_vertices.shape[1]; - if (unlikely(__pyx_t_8 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 979; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__pyx_t_8 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 972; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_12 = 0; __Pyx_DECREF(((PyObject *)__pyx_v_vertices)); @@ -4470,16 +4433,16 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__nsimplex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 981; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__nsimplex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 974; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_8 = __Pyx_PyInt_AsInt(__pyx_t_1); if (unlikely((__pyx_t_8 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 981; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = __Pyx_PyInt_AsInt(__pyx_t_1); if (unlikely((__pyx_t_8 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 974; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __pyx_v_nsimplex = __pyx_t_8; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__ndim); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 982; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__ndim); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 975; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_8 = __Pyx_PyInt_AsInt(__pyx_t_1); if (unlikely((__pyx_t_8 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 982; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = __Pyx_PyInt_AsInt(__pyx_t_1); if (unlikely((__pyx_t_8 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 975; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __pyx_v_ndim = __pyx_t_8; @@ -4507,7 +4470,7 @@ } else if (unlikely(__pyx_t_17 >= __pyx_bshape_1_vertices)) __pyx_t_18 = 1; if (unlikely(__pyx_t_18 != -1)) { __Pyx_RaiseBufferIndexError(__pyx_t_18); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 986; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 979; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_v_ivertex = (*__Pyx_BufPtrStrided2d(npy_int *, __pyx_bstruct_vertices.buf, __pyx_t_16, __pyx_bstride_0_vertices, __pyx_t_17, __pyx_bstride_1_vertices)); @@ -4520,7 +4483,7 @@ } else if (unlikely(__pyx_t_18 >= __pyx_bshape_0_arr)) __pyx_t_19 = 0; if (unlikely(__pyx_t_19 != -1)) { __Pyx_RaiseBufferIndexError(__pyx_t_19); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 987; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 980; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_2 = ((*__Pyx_BufPtrStrided1d(npy_int *, __pyx_bstruct_arr.buf, __pyx_t_18, __pyx_bstride_0_arr)) == -1); if (__pyx_t_2) { @@ -4534,7 +4497,7 @@ } else if (unlikely(__pyx_t_19 >= __pyx_bshape_0_arr)) __pyx_t_20 = 0; if (unlikely(__pyx_t_20 != -1)) { __Pyx_RaiseBufferIndexError(__pyx_t_20); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 988; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 981; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } *__Pyx_BufPtrStrided1d(npy_int *, __pyx_bstruct_arr.buf, __pyx_t_19, __pyx_bstride_0_arr) = __pyx_v_isimplex; goto __pyx_L10; @@ -4548,7 +4511,7 @@ __Pyx_XDECREF(__pyx_r); - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s___vertex_to_simplex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 990; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s___vertex_to_simplex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 983; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __pyx_r = __pyx_t_1; __pyx_t_1 = 0; @@ -4653,9 +4616,9 @@ __pyx_bstruct_vertices.buf = NULL; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__neighbors); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1010; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__neighbors); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1003; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1010; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1003; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_2 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; @@ -4672,7 +4635,7 @@ } __pyx_bstride_0_neighbors = __pyx_bstruct_neighbors.strides[0]; __pyx_bstride_1_neighbors = __pyx_bstruct_neighbors.strides[1]; __pyx_bshape_0_neighbors = __pyx_bstruct_neighbors.shape[0]; __pyx_bshape_1_neighbors = __pyx_bstruct_neighbors.shape[1]; - if (unlikely(__pyx_t_3 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1010; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__pyx_t_3 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1003; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_2 = 0; __Pyx_DECREF(((PyObject *)__pyx_v_neighbors)); @@ -4680,9 +4643,9 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__vertices); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1011; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__vertices); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1004; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1011; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1004; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_7 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; @@ -4699,7 +4662,7 @@ } __pyx_bstride_0_vertices = __pyx_bstruct_vertices.strides[0]; __pyx_bstride_1_vertices = __pyx_bstruct_vertices.strides[1]; __pyx_bshape_0_vertices = __pyx_bstruct_vertices.shape[0]; __pyx_bshape_1_vertices = __pyx_bstruct_vertices.shape[1]; - if (unlikely(__pyx_t_3 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1011; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__pyx_t_3 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1004; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_7 = 0; __Pyx_DECREF(((PyObject *)__pyx_v_vertices)); @@ -4707,16 +4670,16 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__ndim); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1012; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__ndim); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1005; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_3 = __Pyx_PyInt_AsInt(__pyx_t_1); if (unlikely((__pyx_t_3 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1012; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_AsInt(__pyx_t_1); if (unlikely((__pyx_t_3 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1005; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __pyx_v_ndim = __pyx_t_3; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__nsimplex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1013; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__nsimplex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1006; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_3 = __Pyx_PyInt_AsInt(__pyx_t_1); if (unlikely((__pyx_t_3 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1013; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_AsInt(__pyx_t_1); if (unlikely((__pyx_t_3 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1006; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __pyx_v_nsimplex = __pyx_t_3; @@ -4724,16 +4687,16 @@ __pyx_v_msize = 10; - __pyx_t_1 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1016; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1009; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_8 = PyObject_GetAttr(__pyx_t_1, __pyx_n_s__empty); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1016; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = PyObject_GetAttr(__pyx_t_1, __pyx_n_s__empty); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1009; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_8); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - __pyx_t_1 = PyInt_FromLong(__pyx_v_msize); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1016; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyInt_FromLong(__pyx_v_msize); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1009; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_9 = PyInt_FromLong(__pyx_v_ndim); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1016; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PyInt_FromLong(__pyx_v_ndim); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1009; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); - __pyx_t_10 = PyTuple_New(2); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1016; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_10 = PyTuple_New(2); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1009; __pyx_clineno = __LINE__; 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if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1016; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1009; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_11 = PyObject_GetAttr(__pyx_t_1, __pyx_n_s__intc); if (unlikely(!__pyx_t_11)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1016; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_11 = PyObject_GetAttr(__pyx_t_1, __pyx_n_s__intc); if (unlikely(!__pyx_t_11)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1009; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_11); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - if (PyDict_SetItem(__pyx_t_10, ((PyObject *)__pyx_n_s__dtype), __pyx_t_11) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1016; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_t_10, ((PyObject *)__pyx_n_s__dtype), __pyx_t_11) < 0) {__pyx_filename = __pyx_f[0]; 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goto __pyx_L1_error;} + if (unlikely(__pyx_t_20 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1024; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_12 = 0; __Pyx_INCREF(Py_None); @@ -4886,13 +4849,13 @@ __pyx_v_msize = ((2 * __pyx_v_msize) + 1); - __pyx_t_11 = PyObject_GetAttr(__pyx_v_out, __pyx_n_s__resize); if (unlikely(!__pyx_t_11)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1033; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_11 = PyObject_GetAttr(__pyx_v_out, __pyx_n_s__resize); if (unlikely(!__pyx_t_11)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1026; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_11); - __pyx_t_10 = PyInt_FromLong(__pyx_v_msize); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1033; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_10 = PyInt_FromLong(__pyx_v_msize); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1026; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_10); 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__pyx_t_10 = 0; @@ -5030,7 +4993,7 @@ PyObject *__pyx_v_self = 0; PyObject *__pyx_v_xi = 0; PyObject *__pyx_v_bruteforce = 0; - __pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t *__pyx_v_info; + __pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t __pyx_v_info; int __pyx_v_isimplex; double __pyx_v_c[NPY_MAXDIMS]; double __pyx_v_eps; @@ -5089,7 +5052,7 @@ values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__xi); if (likely(values[1])) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("find_simplex", 0, 2, 3, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1040; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("find_simplex", 0, 2, 3, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1033; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 2: if (kw_args > 0) { @@ -5098,7 +5061,7 @@ } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "find_simplex") < 0)) {__pyx_filename = __pyx_f[0]; 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__pyx_lineno = 1091; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_12 = PyObject_GetAttr(__pyx_t_1, __pyx_n_s__intc); if (unlikely(!__pyx_t_12)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1084; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_12); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - if (PyDict_SetItem(__pyx_t_2, ((PyObject *)__pyx_n_s__dtype), __pyx_t_12) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1091; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_t_2, ((PyObject *)__pyx_n_s__dtype), __pyx_t_12) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1084; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_12); __pyx_t_12 = 0; - __pyx_t_12 = PyEval_CallObjectWithKeywords(__pyx_t_5, __pyx_t_3, ((PyObject *)__pyx_t_2)); if (unlikely(!__pyx_t_12)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1091; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_12 = PyEval_CallObjectWithKeywords(__pyx_t_5, __pyx_t_3, ((PyObject *)__pyx_t_2)); if (unlikely(!__pyx_t_12)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1084; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_12); __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; @@ -5360,7 +5323,7 @@ __pyx_t_12 = 0; - if (!(likely(((__pyx_v_out) == Py_None) || likely(__Pyx_TypeTest(__pyx_v_out, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1092; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_v_out) == Py_None) || likely(__Pyx_TypeTest(__pyx_v_out, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1085; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_13 = ((PyArrayObject *)__pyx_v_out); { __Pyx_BufFmt_StackElem __pyx_stack[1]; @@ -5377,7 +5340,7 @@ } __pyx_bstride_0_out_ = __pyx_bstruct_out_.strides[0]; __pyx_bshape_0_out_ = __pyx_bstruct_out_.shape[0]; - if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1092; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1085; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_13 = 0; __Pyx_INCREF(__pyx_v_out); @@ -5385,10 +5348,10 @@ __pyx_v_out_ = ((PyArrayObject *)__pyx_v_out); - __pyx_v_info = __pyx_f_5scipy_7spatial_5qhull__get_delaunay_info(__pyx_v_self, 1, 0); + __pyx_f_5scipy_7spatial_5qhull__get_delaunay_info((&__pyx_v_info), __pyx_v_self, 1, 0); - __pyx_t_4 = __Pyx_PyObject_IsTrue(__pyx_v_bruteforce); if (unlikely(__pyx_t_4 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1095; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyObject_IsTrue(__pyx_v_bruteforce); if (unlikely(__pyx_t_4 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1088; __pyx_clineno = __LINE__; goto __pyx_L1_error;} if (__pyx_t_4) { @@ -5397,7 +5360,7 @@ __pyx_v_k = __pyx_t_7; - __pyx_v_isimplex = __pyx_f_5scipy_7spatial_5qhull__find_simplex_bruteforce(__pyx_v_info, __pyx_v_c, (((double *)__pyx_v_x->data) + (__pyx_v_info->ndim * __pyx_v_k)), __pyx_v_eps); + __pyx_v_isimplex = __pyx_f_5scipy_7spatial_5qhull__find_simplex_bruteforce((&__pyx_v_info), __pyx_v_c, (((double *)__pyx_v_x->data) + (__pyx_v_info.ndim * __pyx_v_k)), __pyx_v_eps); __pyx_t_15 = __pyx_v_k; @@ -5408,7 +5371,7 @@ } else if (unlikely(__pyx_t_15 >= __pyx_bshape_0_out_)) __pyx_t_16 = 0; if (unlikely(__pyx_t_16 != -1)) { __Pyx_RaiseBufferIndexError(__pyx_t_16); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1101; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1094; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } *__Pyx_BufPtrStrided1d(npy_int *, __pyx_bstruct_out_.buf, __pyx_t_15, __pyx_bstride_0_out_) = __pyx_v_isimplex; } @@ -5422,7 +5385,7 @@ __pyx_v_k = __pyx_t_7; - __pyx_v_isimplex = __pyx_f_5scipy_7spatial_5qhull__find_simplex(__pyx_v_info, __pyx_v_c, (((double *)__pyx_v_x->data) + (__pyx_v_info->ndim * __pyx_v_k)), (&__pyx_v_start), __pyx_v_eps); + __pyx_v_isimplex = __pyx_f_5scipy_7spatial_5qhull__find_simplex((&__pyx_v_info), __pyx_v_c, (((double *)__pyx_v_x->data) + (__pyx_v_info.ndim * __pyx_v_k)), (&__pyx_v_start), __pyx_v_eps); __pyx_t_16 = __pyx_v_k; @@ -5433,7 +5396,7 @@ } else if (unlikely(__pyx_t_16 >= __pyx_bshape_0_out_)) __pyx_t_17 = 0; if (unlikely(__pyx_t_17 != -1)) { __Pyx_RaiseBufferIndexError(__pyx_t_17); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1106; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1099; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } *__Pyx_BufPtrStrided1d(npy_int *, __pyx_bstruct_out_.buf, __pyx_t_16, __pyx_bstride_0_out_) = __pyx_v_isimplex; } @@ -5441,20 +5404,17 @@ __pyx_L7:; - free(__pyx_v_info); - - __Pyx_XDECREF(__pyx_r); - __pyx_t_12 = PyObject_GetAttr(__pyx_v_out, __pyx_n_s__reshape); if (unlikely(!__pyx_t_12)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1110; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_12 = PyObject_GetAttr(__pyx_v_out, __pyx_n_s__reshape); if (unlikely(!__pyx_t_12)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1101; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_12); - __pyx_t_2 = PySequence_GetSlice(__pyx_v_xi_shape, 0, -1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1110; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PySequence_GetSlice(__pyx_v_xi_shape, 0, -1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1101; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); - __pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1110; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1101; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); PyTuple_SET_ITEM(__pyx_t_3, 0, __pyx_t_2); __Pyx_GIVEREF(__pyx_t_2); __pyx_t_2 = 0; - __pyx_t_2 = PyObject_Call(__pyx_t_12, __pyx_t_3, NULL); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1110; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyObject_Call(__pyx_t_12, __pyx_t_3, NULL); 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__pyx_lineno = 1135; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_t_2, ((PyObject *)__pyx_n_s__dtype), __pyx_t_11) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1126; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_11); __pyx_t_11 = 0; - __pyx_t_11 = PyEval_CallObjectWithKeywords(__pyx_t_1, __pyx_t_3, ((PyObject *)__pyx_t_2)); if (unlikely(!__pyx_t_11)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1135; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_11 = PyEval_CallObjectWithKeywords(__pyx_t_1, __pyx_t_3, ((PyObject *)__pyx_t_2)); if (unlikely(!__pyx_t_11)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1126; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_11); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; @@ -5770,7 +5730,7 @@ __pyx_t_11 = 0; - if (!(likely(((__pyx_v_out) == Py_None) || likely(__Pyx_TypeTest(__pyx_v_out, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1136; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_v_out) == Py_None) || likely(__Pyx_TypeTest(__pyx_v_out, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1127; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_12 = ((PyArrayObject *)__pyx_v_out); { __Pyx_BufFmt_StackElem __pyx_stack[1]; @@ -5787,7 +5747,7 @@ } __pyx_bstride_0_out_ = __pyx_bstruct_out_.strides[0]; __pyx_bstride_1_out_ = __pyx_bstruct_out_.strides[1]; __pyx_bshape_0_out_ = __pyx_bstruct_out_.shape[0]; __pyx_bshape_1_out_ = __pyx_bstruct_out_.shape[1]; - if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1136; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1127; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_12 = 0; __Pyx_INCREF(__pyx_v_out); @@ -5800,12 +5760,12 @@ __pyx_v_i = __pyx_t_7; - __pyx_t_14 = __pyx_v_info->nsimplex; + __pyx_t_14 = __pyx_v_info.nsimplex; for (__pyx_t_15 = 0; __pyx_t_15 < __pyx_t_14; __pyx_t_15+=1) { __pyx_v_j = __pyx_t_15; - __pyx_f_5scipy_7spatial_5qhull__lift_point(__pyx_v_info, (((double *)__pyx_v_x->data) + (__pyx_v_info->ndim * __pyx_v_i)), __pyx_v_z); + __pyx_f_5scipy_7spatial_5qhull__lift_point((&__pyx_v_info), (((double *)__pyx_v_x->data) + (__pyx_v_info.ndim * __pyx_v_i)), __pyx_v_z); __pyx_t_16 = __pyx_v_i; @@ -5821,38 +5781,35 @@ } else if (unlikely(__pyx_t_17 >= __pyx_bshape_1_out_)) __pyx_t_18 = 1; if (unlikely(__pyx_t_18 != -1)) { __Pyx_RaiseBufferIndexError(__pyx_t_18); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1141; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1132; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } - *__Pyx_BufPtrStrided2d(__pyx_t_5numpy_double_t *, __pyx_bstruct_out_.buf, __pyx_t_16, __pyx_bstride_0_out_, __pyx_t_17, __pyx_bstride_1_out_) = __pyx_f_5scipy_7spatial_5qhull__distplane(__pyx_v_info, __pyx_v_j, __pyx_v_z); + *__Pyx_BufPtrStrided2d(__pyx_t_5numpy_double_t *, __pyx_bstruct_out_.buf, __pyx_t_16, __pyx_bstride_0_out_, __pyx_t_17, __pyx_bstride_1_out_) = __pyx_f_5scipy_7spatial_5qhull__distplane((&__pyx_v_info), __pyx_v_j, __pyx_v_z); } } - free(__pyx_v_info); - - __Pyx_XDECREF(__pyx_r); - __pyx_t_11 = PyObject_GetAttr(__pyx_v_out, __pyx_n_s__reshape); if (unlikely(!__pyx_t_11)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_11 = PyObject_GetAttr(__pyx_v_out, __pyx_n_s__reshape); if (unlikely(!__pyx_t_11)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1134; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_11); - __pyx_t_2 = PySequence_GetSlice(__pyx_v_xi_shape, 0, -1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PySequence_GetSlice(__pyx_v_xi_shape, 0, -1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1134; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); - __pyx_t_3 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__nsimplex); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__nsimplex); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1134; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - __pyx_t_1 = PyTuple_New(1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyTuple_New(1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1134; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); PyTuple_SET_ITEM(__pyx_t_1, 0, __pyx_t_3); __Pyx_GIVEREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyNumber_Add(__pyx_t_2, __pyx_t_1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyNumber_Add(__pyx_t_2, __pyx_t_1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1134; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - __pyx_t_1 = PyTuple_New(1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyTuple_New(1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1134; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); PyTuple_SET_ITEM(__pyx_t_1, 0, __pyx_t_3); __Pyx_GIVEREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyObject_Call(__pyx_t_11, __pyx_t_1, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_Call(__pyx_t_11, __pyx_t_1, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1134; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_11); __pyx_t_11 = 0; __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; @@ -5926,11 +5883,11 @@ values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__x); if (likely(values[1])) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("lift_points", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1147; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lift_points", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1136; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "lift_points") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1147; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "lift_points") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1136; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } __pyx_v_tri = values[0]; __pyx_v_x = values[1]; @@ -5942,7 +5899,7 @@ } goto __pyx_L4_argument_unpacking_done; 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__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; - if (PyObject_SetItem(__pyx_v_z, __pyx_t_2, __pyx_t_4) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1158; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyObject_SetItem(__pyx_v_z, __pyx_t_2, __pyx_t_4) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1147; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; @@ -6137,11 +6094,11 @@ values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__xi); if (likely(values[1])) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("tsearch", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1162; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("tsearch", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1151; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "tsearch") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1162; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "tsearch") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1151; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } __pyx_v_tri = values[0]; __pyx_v_xi = values[1]; @@ -6153,7 +6110,7 @@ } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; - __Pyx_RaiseArgtupleInvalid("tsearch", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1162; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("tsearch", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1151; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_L3_error:; __Pyx_AddTraceback("scipy.spatial.qhull.tsearch"); __Pyx_RefNannyFinishContext(); @@ -6162,14 +6119,14 @@ __Pyx_XDECREF(__pyx_r); - __pyx_t_1 = PyObject_GetAttr(__pyx_v_tri, __pyx_n_s__find_simplex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1176; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_tri, __pyx_n_s__find_simplex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1165; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_2 = PyTuple_New(1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1176; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyTuple_New(1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1165; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_INCREF(__pyx_v_xi); PyTuple_SET_ITEM(__pyx_t_2, 0, __pyx_v_xi); __Pyx_GIVEREF(__pyx_v_xi); - __pyx_t_3 = PyObject_Call(__pyx_t_1, __pyx_t_2, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1176; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_Call(__pyx_t_1, __pyx_t_2, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1165; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; @@ -6193,8 +6150,7 @@ -static __pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t *__pyx_f_5scipy_7spatial_5qhull__get_delaunay_info(PyObject *__pyx_v_obj, int __pyx_v_compute_transform, int __pyx_v_compute_vertex_to_simplex) { - __pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t *__pyx_v_info; +static void __pyx_f_5scipy_7spatial_5qhull__get_delaunay_info(__pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t *__pyx_v_info, PyObject *__pyx_v_obj, int __pyx_v_compute_transform, int __pyx_v_compute_vertex_to_simplex) { PyArrayObject *__pyx_v_transform; PyArrayObject *__pyx_v_vertex_to_simplex; PyArrayObject *__pyx_v_points = 0; @@ -6239,7 +6195,6 @@ Py_ssize_t __pyx_bstride_1_equations = 0; Py_ssize_t __pyx_bshape_0_equations = 0; Py_ssize_t __pyx_bshape_1_equations = 0; - __pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t *__pyx_r; PyObject *__pyx_t_1 = NULL; PyArrayObject *__pyx_t_2 = NULL; PyArrayObject *__pyx_t_3 = NULL; @@ -6267,15 +6222,15 @@ __pyx_bstruct_max_bound.buf = NULL; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_obj, __pyx_n_s__points); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1189; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_obj, __pyx_n_s__points); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1178; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1189; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1178; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_2 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_points, (PyObject*)__pyx_t_2, &__Pyx_TypeInfo_nn___pyx_t_5numpy_double_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) { __pyx_v_points = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_bstruct_points.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1189; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1178; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_bstride_0_points = __pyx_bstruct_points.strides[0]; __pyx_bstride_1_points = __pyx_bstruct_points.strides[1]; __pyx_bshape_0_points = __pyx_bstruct_points.shape[0]; __pyx_bshape_1_points = __pyx_bstruct_points.shape[1]; } @@ -6285,15 +6240,15 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_obj, __pyx_n_s__vertices); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1190; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_obj, __pyx_n_s__vertices); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1179; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1190; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1179; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_3 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_vertices, (PyObject*)__pyx_t_3, &__Pyx_TypeInfo_nn_npy_int, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) { __pyx_v_vertices = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_bstruct_vertices.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1190; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1179; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_bstride_0_vertices = __pyx_bstruct_vertices.strides[0]; __pyx_bstride_1_vertices = __pyx_bstruct_vertices.strides[1]; __pyx_bshape_0_vertices = __pyx_bstruct_vertices.shape[0]; __pyx_bshape_1_vertices = __pyx_bstruct_vertices.shape[1]; } @@ -6303,15 +6258,15 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_obj, __pyx_n_s__neighbors); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1191; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_obj, __pyx_n_s__neighbors); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1180; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1191; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1180; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_4 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_neighbors, (PyObject*)__pyx_t_4, &__Pyx_TypeInfo_nn_npy_int, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) { __pyx_v_neighbors = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_bstruct_neighbors.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1191; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1180; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_bstride_0_neighbors = __pyx_bstruct_neighbors.strides[0]; __pyx_bstride_1_neighbors = __pyx_bstruct_neighbors.strides[1]; __pyx_bshape_0_neighbors = __pyx_bstruct_neighbors.shape[0]; __pyx_bshape_1_neighbors = __pyx_bstruct_neighbors.shape[1]; } @@ -6321,15 +6276,15 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_obj, __pyx_n_s__equations); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1192; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_obj, __pyx_n_s__equations); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1181; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1192; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1181; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_5 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_equations, (PyObject*)__pyx_t_5, &__Pyx_TypeInfo_nn___pyx_t_5numpy_double_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) { __pyx_v_equations = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_bstruct_equations.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1192; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1181; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_bstride_0_equations = __pyx_bstruct_equations.strides[0]; __pyx_bstride_1_equations = __pyx_bstruct_equations.strides[1]; __pyx_bshape_0_equations = __pyx_bstruct_equations.shape[0]; __pyx_bshape_1_equations = __pyx_bstruct_equations.shape[1]; } @@ -6339,15 +6294,15 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_obj, __pyx_n_s__min_bound); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1193; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_obj, __pyx_n_s__min_bound); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1182; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1193; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1182; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_6 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_min_bound, (PyObject*)__pyx_t_6, &__Pyx_TypeInfo_nn___pyx_t_5numpy_double_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { __pyx_v_min_bound = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_bstruct_min_bound.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1193; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1182; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_bstride_0_min_bound = __pyx_bstruct_min_bound.strides[0]; __pyx_bshape_0_min_bound = __pyx_bstruct_min_bound.shape[0]; } @@ -6357,15 +6312,15 @@ __pyx_t_1 = 0; 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goto __pyx_L1_error;} + __pyx_t_4 = PyMethod_New(__pyx_t_2, 0, __pyx_t_3); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1136; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - if (PyObject_SetAttr(__pyx_t_3, __pyx_n_s__lift_points, __pyx_t_4) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1147; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyObject_SetAttr(__pyx_t_3, __pyx_n_s__lift_points, __pyx_t_4) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1136; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; - if (PyObject_SetAttr(__pyx_m, __pyx_n_s__Delaunay, __pyx_t_3) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 862; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyObject_SetAttr(__pyx_m, __pyx_n_s__Delaunay, __pyx_t_3) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 855; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; __Pyx_DECREF(((PyObject *)__pyx_t_1)); __pyx_t_1 = 0; From scipy-svn at scipy.org Sat Feb 19 08:32:35 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sat, 19 Feb 2011 07:32:35 -0600 (CST) Subject: [Scipy-svn] r7154 - branches/0.9.x Message-ID: <20110219133235.716226EFD2@scipy.org> Author: rgommers Date: 2011-02-19 07:32:35 -0600 (Sat, 19 Feb 2011) New Revision: 7154 Modified: branches/0.9.x/setup.py Log: REL: set version number to 0.9.0rc4. Modified: branches/0.9.x/setup.py =================================================================== --- branches/0.9.x/setup.py 2011-02-19 13:30:39 UTC (rev 7153) +++ branches/0.9.x/setup.py 2011-02-19 13:32:35 UTC (rev 7154) @@ -45,8 +45,8 @@ MAJOR = 0 MINOR = 9 MICRO = 0 -ISRELEASED = False -VERSION = '%d.%d.%drc3' % (MAJOR, MINOR, MICRO) +ISRELEASED = True +VERSION = '%d.%d.%drc4' % (MAJOR, MINOR, MICRO) # BEFORE importing distutils, remove MANIFEST. distutils doesn't properly # update it when the contents of directories change. From scipy-svn at scipy.org Sat Feb 19 08:33:44 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sat, 19 Feb 2011 07:33:44 -0600 (CST) Subject: [Scipy-svn] r7155 - tags Message-ID: <20110219133344.6681D6EFD2@scipy.org> Author: rgommers Date: 2011-02-19 07:33:44 -0600 (Sat, 19 Feb 2011) New Revision: 7155 Added: tags/0.9.0rc4/ Log: Create tag 0.9.0rc4 From scipy-svn at scipy.org Sat Feb 19 22:38:13 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sat, 19 Feb 2011 21:38:13 -0600 (CST) Subject: [Scipy-svn] r7156 - trunk/scipy/interpolate Message-ID: <20110220033813.6ECF06EFD6@scipy.org> Author: rgommers Date: 2011-02-19 21:38:12 -0600 (Sat, 19 Feb 2011) New Revision: 7156 Modified: trunk/scipy/interpolate/polyint.py Log: BUG: remove ASCII form feed character that causes a problem with Py 3.2rc3. Thanks to Christoph Gohlke for testing and the patch. Modified: trunk/scipy/interpolate/polyint.py =================================================================== --- trunk/scipy/interpolate/polyint.py 2011-02-19 13:33:44 UTC (rev 7155) +++ trunk/scipy/interpolate/polyint.py 2011-02-20 03:38:12 UTC (rev 7156) @@ -380,7 +380,6 @@ return np.poly1d((d/factorial(np.arange(degree+1)))[::-1]) - class BarycentricInterpolator(object): """The interpolating polynomial for a set of points From scipy-svn at scipy.org Sun Feb 20 04:33:27 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 20 Feb 2011 03:33:27 -0600 (CST) Subject: [Scipy-svn] r7157 - branches/0.9.x Message-ID: <20110220093327.A40FA42E05A@scipy.org> Author: rgommers Date: 2011-02-20 03:33:26 -0600 (Sun, 20 Feb 2011) New Revision: 7157 Modified: branches/0.9.x/setup.py Log: REL: set released=False, version=0.9.0rc5 Modified: branches/0.9.x/setup.py =================================================================== --- branches/0.9.x/setup.py 2011-02-20 03:38:12 UTC (rev 7156) +++ branches/0.9.x/setup.py 2011-02-20 09:33:26 UTC (rev 7157) @@ -45,8 +45,8 @@ MAJOR = 0 MINOR = 9 MICRO = 0 -ISRELEASED = True -VERSION = '%d.%d.%drc4' % (MAJOR, MINOR, MICRO) +ISRELEASED = False +VERSION = '%d.%d.%drc5' % (MAJOR, MINOR, MICRO) # BEFORE importing distutils, remove MANIFEST. distutils doesn't properly # update it when the contents of directories change. From scipy-svn at scipy.org Sun Feb 20 04:34:10 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 20 Feb 2011 03:34:10 -0600 (CST) Subject: [Scipy-svn] r7158 - branches/0.9.x/scipy/special Message-ID: <20110220093410.D3D9442E05A@scipy.org> Author: rgommers Date: 2011-02-20 03:34:10 -0600 (Sun, 20 Feb 2011) New Revision: 7158 Modified: branches/0.9.x/scipy/special/amos_wrappers.c Log: BUG: special: fix zbiry prototype to match the Fortran code (#1233) (backport of r7144) Modified: branches/0.9.x/scipy/special/amos_wrappers.c =================================================================== --- branches/0.9.x/scipy/special/amos_wrappers.c 2011-02-20 09:33:26 UTC (rev 7157) +++ branches/0.9.x/scipy/special/amos_wrappers.c 2011-02-20 09:34:10 UTC (rev 7158) @@ -27,7 +27,7 @@ extern int F_FUNC(zairy,ZAIRY) (double*, double*, int*, int*, double*, double*, int*, int*); extern int F_FUNC(zbiry,ZBIRY) - (double*, double*, int*, int*, double*, double*, int*, int*); + (double*, double*, int*, int*, double*, double*, int*); extern int F_FUNC(zbesi,ZBESI) (double*, double*, double*, int*, int*, double*, double*, int*, int*); extern int F_FUNC(zbesj,ZBESJ) @@ -135,13 +135,15 @@ F_FUNC(zairy,ZAIRY)(CADDR(z), &id, &kode, F2C_CST(ai), &nz, &ierr); DO_MTHERR("airy:", ai); - F_FUNC(zbiry,ZBIRY)(CADDR(z), &id, &kode, F2C_CST(bi), &nz, &ierr); + nz = 0; + F_FUNC(zbiry,ZBIRY)(CADDR(z), &id, &kode, F2C_CST(bi), &ierr); DO_MTHERR("airy:", bi); id = 1; F_FUNC(zairy,ZAIRY)(CADDR(z), &id, &kode, F2C_CST(aip), &nz, &ierr); DO_MTHERR("airy:", aip); - F_FUNC(zbiry,ZBIRY)(CADDR(z), &id, &kode, F2C_CST(bip), &nz, &ierr); + nz = 0; + F_FUNC(zbiry,ZBIRY)(CADDR(z), &id, &kode, F2C_CST(bip), &ierr); DO_MTHERR("airy:", bip); return 0; } @@ -153,13 +155,15 @@ F_FUNC(zairy,ZAIRY)(CADDR(z), &id, &kode, F2C_CST(ai), &nz, &ierr); DO_MTHERR("airye:", ai); - F_FUNC(zbiry,ZBIRY)(CADDR(z), &id, &kode, F2C_CST(bi), &nz, &ierr); + nz = 0; + F_FUNC(zbiry,ZBIRY)(CADDR(z), &id, &kode, F2C_CST(bi), &ierr); DO_MTHERR("airye:", bi); id = 1; F_FUNC(zairy,ZAIRY)(CADDR(z), &id, &kode, F2C_CST(aip), &nz, &ierr); DO_MTHERR("airye:", aip); - F_FUNC(zbiry,ZBIRY)(CADDR(z), &id, &kode, F2C_CST(bip), &nz, &ierr); + nz = 0; + F_FUNC(zbiry,ZBIRY)(CADDR(z), &id, &kode, F2C_CST(bip), &ierr); DO_MTHERR("airye:", bip); return 0; } @@ -180,7 +184,8 @@ DO_MTHERR("airye:", &cai); *ai = cai.real; } - F_FUNC(zbiry,ZBIRY)(CADDR(cz), &id, &kode, CADDR(cbi), &nz, &ierr); + nz = 0; + F_FUNC(zbiry,ZBIRY)(CADDR(cz), &id, &kode, CADDR(cbi), &ierr); DO_MTHERR("airye:", &cbi); *bi = cbi.real; @@ -192,7 +197,8 @@ DO_MTHERR("airye:", &caip); *aip = caip.real; } - F_FUNC(zbiry,ZBIRY)(CADDR(cz), &id, &kode, CADDR(cbip), &nz, &ierr); + nz = 0; + F_FUNC(zbiry,ZBIRY)(CADDR(cz), &id, &kode, CADDR(cbip), &ierr); DO_MTHERR("airye:", &cbip); *bip = cbip.real; return 0; From scipy-svn at scipy.org Sun Feb 20 04:34:38 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 20 Feb 2011 03:34:38 -0600 (CST) Subject: [Scipy-svn] r7159 - branches/0.9.x/scipy/interpolate Message-ID: <20110220093438.1433042E05A@scipy.org> Author: rgommers Date: 2011-02-20 03:34:37 -0600 (Sun, 20 Feb 2011) New Revision: 7159 Modified: branches/0.9.x/scipy/interpolate/polyint.py Log: BUG: remove ASCII form feed character that causes a problem with Py 3.2rc3. Thanks to Christoph Gohlke for testing and the patch. (backport of r7156) Modified: branches/0.9.x/scipy/interpolate/polyint.py =================================================================== --- branches/0.9.x/scipy/interpolate/polyint.py 2011-02-20 09:34:10 UTC (rev 7158) +++ branches/0.9.x/scipy/interpolate/polyint.py 2011-02-20 09:34:37 UTC (rev 7159) @@ -380,7 +380,6 @@ return np.poly1d((d/factorial(np.arange(degree+1)))[::-1]) - class BarycentricInterpolator(object): """The interpolating polynomial for a set of points From scipy-svn at scipy.org Sun Feb 20 04:35:12 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 20 Feb 2011 03:35:12 -0600 (CST) Subject: [Scipy-svn] r7160 - in branches/0.9.x/scipy: misc/tests ndimage spatial/tests Message-ID: <20110220093512.DA29042E05A@scipy.org> Author: rgommers Date: 2011-02-20 03:35:12 -0600 (Sun, 20 Feb 2011) New Revision: 7160 Modified: branches/0.9.x/scipy/misc/tests/test_pilutil.py branches/0.9.x/scipy/ndimage/io.py branches/0.9.x/scipy/spatial/tests/test_distance.py Log: TST: explicit file close to avoid ResourceWarnings under Python 3.2. Thanks to Christoph Gohlke. (backport of r7147) Modified: branches/0.9.x/scipy/misc/tests/test_pilutil.py =================================================================== --- branches/0.9.x/scipy/misc/tests/test_pilutil.py 2011-02-20 09:34:37 UTC (rev 7159) +++ branches/0.9.x/scipy/misc/tests/test_pilutil.py 2011-02-20 09:35:12 UTC (rev 7160) @@ -42,7 +42,9 @@ assert_equal(pilutil.bytescale(y),[0,127,255]) def tst_fromimage(filename, irange): - img = pilutil.fromimage(PIL.Image.open(filename)) + fp = open(filename, "rb") + img = pilutil.fromimage(PIL.Image.open(fp)) + fp.close() imin,imax = irange assert_(img.min() >= imin) assert_(img.max() <= imax) Modified: branches/0.9.x/scipy/ndimage/io.py =================================================================== --- branches/0.9.x/scipy/ndimage/io.py 2011-02-20 09:34:37 UTC (rev 7159) +++ branches/0.9.x/scipy/ndimage/io.py 2011-02-20 09:35:12 UTC (rev 7160) @@ -34,8 +34,10 @@ " http://pypi.python.org/pypi/PIL/ for installation" " instructions.") - im = Image.open(fname) + fp = open(fname, "rb") + im = Image.open(fp) if flatten: im = im.convert('F') - return array(im) - + result = array(im) + fp.close() + return result Modified: branches/0.9.x/scipy/spatial/tests/test_distance.py =================================================================== --- branches/0.9.x/scipy/spatial/tests/test_distance.py 2011-02-20 09:34:37 UTC (rev 7159) +++ branches/0.9.x/scipy/spatial/tests/test_distance.py 2011-02-20 09:35:12 UTC (rev 7160) @@ -88,7 +88,9 @@ for fn in _filenames: name = fn.replace(".txt", "").replace("-ml", "") fqfn = os.path.join(os.path.dirname(__file__), fn) - eo[name] = np.loadtxt(open(fqfn)) + fp = open(fqfn) + eo[name] = np.loadtxt(fp) + fp.close() #print "%s: %s %s" % (name, str(eo[name].shape), str(eo[name].dtype)) eo['pdist-boolean-inp'] = np.bool_(eo['pdist-boolean-inp']) From scipy-svn at scipy.org Sun Feb 20 04:35:39 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 20 Feb 2011 03:35:39 -0600 (CST) Subject: [Scipy-svn] r7161 - branches/0.9.x Message-ID: <20110220093539.8ABA342E05A@scipy.org> Author: rgommers Date: 2011-02-20 03:35:39 -0600 (Sun, 20 Feb 2011) New Revision: 7161 Modified: branches/0.9.x/setup.py Log: REL: set released=True in setup.py (for 0.9.0rc5). Modified: branches/0.9.x/setup.py =================================================================== --- branches/0.9.x/setup.py 2011-02-20 09:35:12 UTC (rev 7160) +++ branches/0.9.x/setup.py 2011-02-20 09:35:39 UTC (rev 7161) @@ -45,7 +45,7 @@ MAJOR = 0 MINOR = 9 MICRO = 0 -ISRELEASED = False +ISRELEASED = True VERSION = '%d.%d.%drc5' % (MAJOR, MINOR, MICRO) # BEFORE importing distutils, remove MANIFEST. distutils doesn't properly From scipy-svn at scipy.org Sun Feb 20 04:39:36 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 20 Feb 2011 03:39:36 -0600 (CST) Subject: [Scipy-svn] r7162 - tags Message-ID: <20110220093936.3CFD642E05A@scipy.org> Author: rgommers Date: 2011-02-20 03:39:36 -0600 (Sun, 20 Feb 2011) New Revision: 7162 Added: tags/0.9.0rc5/ Log: Create tag 0.9.0rc5 From scipy-svn at scipy.org Sun Feb 20 04:58:05 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 20 Feb 2011 03:58:05 -0600 (CST) Subject: [Scipy-svn] r7163 - trunk/tools/win32 Message-ID: <20110220095805.107F242E05A@scipy.org> Author: rgommers Date: 2011-02-20 03:58:04 -0600 (Sun, 20 Feb 2011) New Revision: 7163 Added: trunk/tools/win32/detect_cpu_extensions_wine.py Log: ENH: Add script that checks all files in scipy win32 install for SSE instructions. Should be run once for each new release. See also #1170 for an issue that has occurred with SSE instructions in the nosse binary in the superpack installer. Added: trunk/tools/win32/detect_cpu_extensions_wine.py =================================================================== --- trunk/tools/win32/detect_cpu_extensions_wine.py (rev 0) +++ trunk/tools/win32/detect_cpu_extensions_wine.py 2011-02-20 09:58:04 UTC (rev 7163) @@ -0,0 +1,153 @@ +#!/usr/bin/python +""" +Detect which x86 CPU extension instructions the given scipy install uses. +This file can be used in the release process to check that the nosse installer +does not contain SSE instructions. This has happened before, see for example +ticket #1170. + +Is meant to be run on OS X with Wine. Make sure objdump.exe is installed. + +See also tools/win32build/misc/x86analysis.py in numpy for a similar script +that checks a single file. + +""" +import subprocess +import sys +import os +from optparse import OptionParser + + +OBJDUMP = os.environ['HOME'] + '/.wine/drive_c/MinGW/bin/objdump.exe' +SCIPY_PY25 = os.environ['HOME'] + '/.wine/drive_c/Python25/Lib/site-packages/scipy/' +SCIPY_PY26 = os.environ['HOME'] + '/.wine/drive_c/Python26/Lib/site-packages/scipy/' +SCIPY_PY27 = os.environ['HOME'] + '/.wine/drive_c/Python27/Lib/site-packages/scipy/' +SCIPY_PY31 = os.environ['HOME'] + '/.wine/drive_c/Python31/Lib/site-packages/scipy/' +NUMPY_PY25 = os.environ['HOME'] + '/.wine/drive_c/Python25/Lib/site-packages/numpy/' +NUMPY_PY26 = os.environ['HOME'] + '/.wine/drive_c/Python26/Lib/site-packages/numpy/' +NUMPY_PY27 = os.environ['HOME'] + '/.wine/drive_c/Python27/Lib/site-packages/numpy/' +NUMPY_PY31 = os.environ['HOME'] + '/.wine/drive_c/Python31/Lib/site-packages/numpy/' +SSE3_LIBS = os.environ['HOME'] + '/.wine/drive_c/local/lib/yop/sse3' +SSE2_LIBS = os.environ['HOME'] + '/.wine/drive_c/local/lib/yop/sse2' +NOSSE_LIBS = os.environ['HOME'] + '/.wine/drive_c/local/lib/yop/nosse' + +# The install to check +basepath = SCIPY_PY25 + + +def main(): + # a set of all unique CPU extension codes found + allcodes = set() + # walk the SciPy tree and check all binary files + for root, dirs, files in os.walk(basepath): + for fl in files: + if os.path.splitext(fl)[1] in ['.a', '.pyd', '.so']: + full_fpath = os.path.join(root, fl) + codes = single_file_checkext(full_fpath) + for code in codes: + allcodes.add(code) + write_summary(allcodes) + + +def single_file_checkext(fname, striproot=True): + if striproot == True: + sys.stdout.write('%s: ' % fname.replace(basepath, '')) + else: + sys.stdout.write('%s: ' % fname) + sys.stdout.flush() + codes = process(path_as_windows(fname)) + sys.stdout.write(" ".join(codes)) + sys.stdout.write("\n") + return codes + + +def path_as_windows(fpath): + """Return the file path as Wine expects.""" + winepath = 'C:\\' + fpath.split('drive_c')[1] + return winepath + + +def write_summary(allcodes): + """Write a summary of all found codes to stdout.""" + print """\n +---------------------------------------------------------------------------- +Checked all binary files for CPU extension codes. Found the following codes:""" + for code in allcodes: + print code + print """ +---------------------------------------------------------------------------- +""" + + +def process(fn): + p = subprocess.Popen(['wine', OBJDUMP, '-d', fn], stdout=subprocess.PIPE) + codes = {} + for line in p.stdout: + r = line.split("\t") + if len(r) != 3: + continue + instr = r[2].split()[0].lower() + if instr in INSTRS: + codes[INSTRS[instr]] = True + print instr + codes = codes.keys() + codes.sort() + return codes + +#------------------------------------------------------------------------------ +# Instruction lists +#------------------------------------------------------------------------------ + +# x86 +EXTS_x86 = dict( + _486='bswap cmpxch cpuid invd invlpg wbinvd xadd', + pentium='cmpxchg8b rdmsr rdtsc wrmsr', + pentium_mmx='rdpmc', + pentium_pro='cmova cmovae cmovb cmovbe cmovc cmove cmovg cmovge cmovl cmovle cmovna cmovnae cmovnb cmovnbe cmovnc cmovne cmovng cmovnge cmovnl cmovnle cmovno cmovnp cmovns cmovnz cmovo cmovp cmovpe cmovpo cmovs cmovz sysenter sysexit rdpmc ud2', + amd_k6_2='syscall sysret', + sse='maskmovq movntps movntq prefetch0 prefetch1 prefetch2 prefetchnta sfence', + sse2='clflush lfence maskmovdqu mfence movntdq movnti movntpd pause', + sse3='lddqu', + sse3_intel='monitor mwait', + intel_vt='vmptrld vmptrst vmclear vmread vmwrite vmcall vmlaunch vmresume vmxoff vmxon', + amd_v='clgi skinit stgi vmload vmmcall vmrun vmsave', + x86_64='cmpxchg16b rdtscp', + sse4a='lzcnt popcnt', +) + + +# x87 +EXTS_x87 = dict( + pentium_pro='fcmovb, fcmovbe, fcmove, fcmovnb, fcmovnbe, fcmovne, fcmovnu, fcmovu fcomi fcomip fucomi fucomip', + sse='fxrstor fxsave', + sse3='fisttp', + undocumented='ffreep', +) + +# SIMD +EXTS_simd = dict( + mmx='emms movd movq packssdw packsswb packuswb paddb paddd paddsb paddsw paddusb paddusw paddw pand pandn pcmpeqb pcmpeqd pcmpeqw pcmpgtb pcmpgtd pcmpgtw pmaddwd pmulhw pmullw por pslld psllq psllw psrad psraw psrld psrlq psrlw psubb psubd psubsb psubsw psubusb psubusw psubw punpckhbw punpckhdq punpckhwd punpcklbw punpckldq punpcklwd pxor', + emmx='paveb paddsiw pmagw pdistib psubsiw pmvzb pmulhrw pmvnzb pmvlzb pmvgezb pmulhriw pmachriw', + _3dnow='femms pavgusb pf2id pfacc pfadd pfcmpeq pfcmpge pfcmpgt pfmax pfmin pfmul pfrcp pfrcpit1 pfrcpit2 pfrsqit1 pfrsqrt pfsub pfsubr pi2fd pmulhrw prefetch prefetchw', + _3dnowplus='pf2iw pfnacc pfpnacc pi2fw pswapd', + _3dnowplus_geodegx='pfrsqrtv pfrcpv', + sse='addps addss cmpps cmpss comiss cvtpi2ps cvtps2pi cvtsi2ss cvtss2si cvttps2pi cvttss2si divps divss ldmxcsr maxps maxss minps minss movaps movhlps movhps movlhps movlps movmskps movntps movss movups mulps mulss rcpps rcpss rsqrtps rsqrtss shufps sqrtps sqrtss stmxcsr subps subss ucomiss unpckhps unpcklps andnps andps orps pavgb pavgw pextrw pinsrw pmaxsw pmaxub pminsw pminub pmovmskb pmulhuw psadbw pshufw xorps', + sse2='addpd addsd andnpd andpd cmppd cmpsd comisd cvtdq2pd cvtdq2ps cvtpd2dq cvtpd2pi cvtpd2ps cvtpi2pd cvtps2dq cvtps2pd cvtsd2si cvtsd2ss cvtsi2sd cvtss2sd cvttpd2dq cvttpd2pi cvtps2dq cvttsd2si divpd divsd maxpd maxsd minpd minsd movapd movhpd movlpd movmskpd movsd movupd mulpd mulsd orpd shufpd sqrtpd sqrtsd subpd subsd ucomisd unpckhpd unpcklpd xorpd movdq2q movdqa movdqu movq2dq paddq psubq pmuludq pshufhw pshuflw pshufd pslldq psrldq punpckhqdq punpcklqdq', + sse3='addsubpd addsubps haddpd haddps hsubpd hsubps movddup movshdup movsldup', + ssse3='psignw psignd psignb pshufb pmulhrsw pmaddubsw phsubw phsubsw phsubd phaddw phaddsw phaddd palignr pabsw pabsd pabsb', + sse4_1='mpsadbw phminposuw pmulld pmuldq dpps dppd blendps blendpd blendvps blendvpd pblendvb pblendw pminsb pmaxsb pminuw pmaxuw pminud pmaxud pminsd pmaxsd roundps roundss roundpd roundsd insertps pinsrb pinsrd/pinsrq extractps pextrb pextrw pextrd/pextrq pmovsxbw pmovzxbw pmovsxbd pmovzxbd pmovsxbq pmovzxbq pmovsxwd pmovzxwd pmovsxwq pmovzxwq pmovsxdq pmovzxdq ptest pcmpeqq packusdw movntdqa', + sse4a='extrq insertq movntsd movntss', + sse4_2='crc32 pcmpestri pcmpestrm pcmpistri pcmpistrm pcmpgtq', + fma='vfmaddpd vfmaddps vfmaddsd vfmaddss vfmaddsubpd vfmaddsubps vfmsubaddpd vfmsubaddps vfmsubpd vfmsubps vfmsubsd vfmsubss vfnmaddpd fndmaddps vfnmaddsd vfnmadss vfnmsubpd vfnmsubpd vfnmsubps vfnmsubsd vfnmsubss', +) + +INSTRS = dict() +for ext in [EXTS_x86, EXTS_x87, EXTS_simd]: + for key, value in ext.items(): + if key.startswith('_'): + key = key[1:] + for v in value.split(): + INSTRS[v] = key + +#------------------------------------------------------------------------------ + +if __name__ == "__main__": main() From scipy-svn at scipy.org Sun Feb 20 08:30:34 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 20 Feb 2011 07:30:34 -0600 (CST) Subject: [Scipy-svn] r7164 - in trunk: doc/source/tutorial doc/source/tutorial/examples scipy/cluster scipy/spatial scipy/stats Message-ID: <20110220133034.978DB1B89B0@scipy.org> Author: rgommers Date: 2011-02-20 07:30:33 -0600 (Sun, 20 Feb 2011) New Revision: 7164 Modified: trunk/doc/source/tutorial/examples/1-1 trunk/doc/source/tutorial/optimize.rst trunk/scipy/cluster/hierarchy.py trunk/scipy/cluster/vq.py trunk/scipy/spatial/ckdtree.c trunk/scipy/spatial/ckdtree.pyx trunk/scipy/stats/mstats_basic.py trunk/scipy/stats/stats.py Log: DOC: improve formatting of docs, eliminate old-style section headers. Modified: trunk/doc/source/tutorial/examples/1-1 =================================================================== --- trunk/doc/source/tutorial/examples/1-1 2011-02-20 09:58:04 UTC (rev 7163) +++ trunk/doc/source/tutorial/examples/1-1 2011-02-20 13:30:33 UTC (rev 7164) @@ -4,52 +4,52 @@ Minimize a function using the downhill simplex algorithm. -:Parameters: +Parameters +---------- +func : callable func(x,*args) + The objective function to be minimized. +x0 : ndarray + Initial guess. +args : tuple + Extra arguments passed to func, i.e. ``f(x,*args)``. +callback : callable + Called after each iteration, as callback(xk), where xk is the + current parameter vector. - func : callable func(x,*args) - The objective function to be minimized. - x0 : ndarray - Initial guess. - args : tuple - Extra arguments passed to func, i.e. ``f(x,*args)``. - callback : callable - Called after each iteration, as callback(xk), where xk is the - current parameter vector. +Returns +------- +xopt : ndarray + Parameter that minimizes function. +fopt : float + Value of function at minimum: ``fopt = func(xopt)``. +iter : int + Number of iterations performed. +funcalls : int + Number of function calls made. +warnflag : int + 1 : Maximum number of function evaluations made. + 2 : Maximum number of iterations reached. +allvecs : list + Solution at each iteration. -:Returns: (xopt, {fopt, iter, funcalls, warnflag}) +Other parameters +---------------- +xtol : float + Relative error in xopt acceptable for convergence. +ftol : number + Relative error in func(xopt) acceptable for convergence. +maxiter : int + Maximum number of iterations to perform. +maxfun : number + Maximum number of function evaluations to make. +full_output : bool + Set to True if fopt and warnflag outputs are desired. +disp : bool + Set to True to print convergence messages. +retall : bool + Set to True to return list of solutions at each iteration. - xopt : ndarray - Parameter that minimizes function. - fopt : float - Value of function at minimum: ``fopt = func(xopt)``. - iter : int - Number of iterations performed. - funcalls : int - Number of function calls made. - warnflag : int - 1 : Maximum number of function evaluations made. - 2 : Maximum number of iterations reached. - allvecs : list - Solution at each iteration. - -*Other Parameters*: - - xtol : float - Relative error in xopt acceptable for convergence. - ftol : number - Relative error in func(xopt) acceptable for convergence. - maxiter : int - Maximum number of iterations to perform. - maxfun : number - Maximum number of function evaluations to make. - full_output : bool - Set to True if fval and warnflag outputs are desired. - disp : bool - Set to True to print convergence messages. - retall : bool - Set to True to return list of solutions at each iteration. - -:Notes: - - Uses a Nelder-Mead simplex algorithm to find the minimum of - function of one or more variables. +Notes +----- +Uses a Nelder-Mead simplex algorithm to find the minimum of function of +one or more variables. Modified: trunk/doc/source/tutorial/optimize.rst =================================================================== --- trunk/doc/source/tutorial/optimize.rst 2011-02-20 09:58:04 UTC (rev 7163) +++ trunk/doc/source/tutorial/optimize.rst 2011-02-20 13:30:33 UTC (rev 7164) @@ -385,16 +385,21 @@ from numpy import array, asfarray, finfo,ones, sqrt, zeros - def testfunc(d,*args): + def testfunc(d, *args): """ - Arguments: - d - A list of two elements, where d[0] represents x and - d[1] represents y in the following equation. - sign - A multiplier for f. Since we want to optimize it, and the scipy - optimizers can only minimize functions, we need to multiply it by - -1 to achieve the desired solution - Returns: - 2*x*y + 2*x - x**2 - 2*y**2 + Parameters + ---------- + d : list + A list of two elements, where d[0] represents x and + d[1] represents y in the following equation. + sign : float + A multiplier for f. Since we want to optimize it, and the scipy + optimizers can only minimize functions, we need to multiply it by + -1 to achieve the desired solution. + Returns + ------- + res : float + The result, equal to ``2*x*y + 2*x - x**2 - 2*y**2``. """ try: Modified: trunk/scipy/cluster/hierarchy.py =================================================================== --- trunk/scipy/cluster/hierarchy.py 2011-02-20 09:58:04 UTC (rev 7163) +++ trunk/scipy/cluster/hierarchy.py 2011-02-20 13:30:33 UTC (rev 7164) @@ -216,17 +216,21 @@ matrix ``y``. See ``linkage`` for more information on the return structure and algorithm. - :Parameters: - y : ndarray - The upper triangular of the distance matrix. The result of - ``pdist`` is returned in this form. + Parameters + ---------- + y : ndarray + The upper triangular of the distance matrix. The result of + ``pdist`` is returned in this form. - :Returns: - Z : ndarray - The linkage matrix. + Returns + ------- + Z : ndarray + The linkage matrix. - :SeeAlso: - - linkage: for advanced creation of hierarchical clusterings. + See Also + -------- + linkage: for advanced creation of hierarchical clusterings. + """ return linkage(y, method='single', metric='euclidean') @@ -236,16 +240,19 @@ condensed distance matrix ``y``. See ``linkage`` for more information on the return structure and algorithm. - :Parameters: - y : ndarray - The upper triangular of the distance matrix. The result of - ``pdist`` is returned in this form. + Parameters + ---------- + y : ndarray + The upper triangular of the distance matrix. The result of + ``pdist`` is returned in this form. - :Returns: - Z : ndarray - A linkage matrix containing the hierarchical clustering. See - the ``linkage`` function documentation for more information - on its structure. + Returns + ------- + Z : ndarray + A linkage matrix containing the hierarchical clustering. See + the ``linkage`` function documentation for more information + on its structure. + """ return linkage(y, method='complete', metric='euclidean') @@ -255,19 +262,23 @@ ``y``. See ``linkage`` for more information on the return structure and algorithm. - :Parameters: - y : ndarray - The upper triangular of the distance matrix. The result of - ``pdist`` is returned in this form. + Parameters + ---------- + y : ndarray + The upper triangular of the distance matrix. The result of + ``pdist`` is returned in this form. - :Returns: - Z : ndarray - A linkage matrix containing the hierarchical clustering. See - the ``linkage`` function documentation for more information - on its structure. + Returns + ------- + Z : ndarray + A linkage matrix containing the hierarchical clustering. See + the ``linkage`` function documentation for more information + on its structure. - :SeeAlso: - - linkage: for advanced creation of hierarchical clusterings. + See Also + -------- + linkage: for advanced creation of hierarchical clusterings. + """ return linkage(y, method='average', metric='euclidean') @@ -277,19 +288,23 @@ ``y``. See ``linkage`` for more information on the return structure and algorithm. - :Parameters: - y : ndarray - The upper triangular of the distance matrix. The result of - ``pdist`` is returned in this form. + Parameters + ---------- + y : ndarray + The upper triangular of the distance matrix. The result of + ``pdist`` is returned in this form. - :Returns: - Z : ndarray - A linkage matrix containing the hierarchical clustering. See - the ``linkage`` function documentation for more information - on its structure. + Returns + ------- + Z : ndarray + A linkage matrix containing the hierarchical clustering. See + the ``linkage`` function documentation for more information + on its structure. - :SeeAlso: - - linkage: for advanced creation of hierarchical clusterings. + See Also + -------- + linkage: for advanced creation of hierarchical clusterings. + """ return linkage(y, method='weighted', metric='euclidean') @@ -312,23 +327,27 @@ using Euclidean distance as the distance metric. See ``linkage`` for more information on the return structure and algorithm. - :Parameters: - Q : ndarray - A condensed or redundant distance matrix. A condensed - distance matrix is a flat array containing the upper - triangular of the distance matrix. This is the form that - ``pdist`` returns. Alternatively, a collection of - m observation vectors in n dimensions may be passed as - a m by n array. + Parameters + ---------- + Q : ndarray + A condensed or redundant distance matrix. A condensed + distance matrix is a flat array containing the upper + triangular of the distance matrix. This is the form that + ``pdist`` returns. Alternatively, a collection of + m observation vectors in n dimensions may be passed as + a m by n array. - :Returns: - Z : ndarray - A linkage matrix containing the hierarchical clustering. See - the ``linkage`` function documentation for more information - on its structure. + Returns + ------- + Z : ndarray + A linkage matrix containing the hierarchical clustering. See + the ``linkage`` function documentation for more information + on its structure. - :SeeAlso: - - linkage: for advanced creation of hierarchical clusterings. + See Also + -------- + linkage: for advanced creation of hierarchical clusterings. + """ return linkage(y, method='centroid', metric='euclidean') @@ -351,21 +370,25 @@ using Euclidean distance as the distance metric. See linkage for more information on the return structure and algorithm. - :Parameters: - Q : ndarray - A condensed or redundant distance matrix. A condensed - distance matrix is a flat array containing the upper - triangular of the distance matrix. This is the form that - ``pdist`` returns. Alternatively, a collection of - m observation vectors in n dimensions may be passed as - a m by n array. + Parameters + ---------- + Q : ndarray + A condensed or redundant distance matrix. A condensed + distance matrix is a flat array containing the upper + triangular of the distance matrix. This is the form that + ``pdist`` returns. Alternatively, a collection of + m observation vectors in n dimensions may be passed as + a m by n array. - :Returns: - - Z : ndarray - The hierarchical clustering encoded as a linkage matrix. + Returns + ------- + Z : ndarray + The hierarchical clustering encoded as a linkage matrix. - :SeeAlso: - - linkage: for advanced creation of hierarchical clusterings. + See Also + -------- + linkage: for advanced creation of hierarchical clusterings. + """ return linkage(y, method='median', metric='euclidean') @@ -387,21 +410,25 @@ Euclidean distance as the distance metric. See linkage for more information on the return structure and algorithm. - :Parameters: - Q : ndarray - A condensed or redundant distance matrix. A condensed - distance matrix is a flat array containing the upper - triangular of the distance matrix. This is the form that - ``pdist`` returns. Alternatively, a collection of - m observation vectors in n dimensions may be passed as - a m by n array. + Parameters + ---------- + Q : ndarray + A condensed or redundant distance matrix. A condensed + distance matrix is a flat array containing the upper + triangular of the distance matrix. This is the form that + ``pdist`` returns. Alternatively, a collection of + m observation vectors in n dimensions may be passed as + a m by n array. - :Returns: - - Z : ndarray - The hierarchical clustering encoded as a linkage matrix. + Returns + ------- + Z : ndarray + The hierarchical clustering encoded as a linkage matrix. - :SeeAlso: - - linkage: for advanced creation of hierarchical clusterings. + See Also + -------- + linkage: for advanced creation of hierarchical clusterings. + """ return linkage(y, method='ward', metric='euclidean') @@ -532,26 +559,27 @@ implementation may chose a different minimum than the MATLAB(TM) version. - :Parameters: - - y : ndarray - A condensed or redundant distance matrix. A condensed - distance matrix is a flat array containing the upper - triangular of the distance matrix. This is the form that - ``pdist`` returns. Alternatively, a collection of - :math:`m` observation vectors in n dimensions may be passed as - an :math:`m` by :math:`n` array. - - method : string - The linkage algorithm to use. See the ``Linkage Methods`` - section below for full descriptions. - - metric : string - The distance metric to use. See the ``distance.pdist`` - function for a list of valid distance metrics. + Parameters + ---------- + y : ndarray + A condensed or redundant distance matrix. A condensed + distance matrix is a flat array containing the upper + triangular of the distance matrix. This is the form that + ``pdist`` returns. Alternatively, a collection of + :math:`m` observation vectors in n dimensions may be passed as + an :math:`m` by :math:`n` array. + method : str + The linkage algorithm to use. See the ``Linkage Methods`` + section below for full descriptions. + metric : str + The distance metric to use. See the ``distance.pdist`` + function for a list of valid distance metrics. - :Returns: + Returns + ------- + Z : ndarray + The hierarchical clustering encoded as a linkage matrix. - - Z : ndarray - The hierarchical clustering encoded as a linkage matrix. - """ if not isinstance(method, str): raise TypeError("Argument 'method' must be a string.") @@ -599,9 +627,10 @@ The to_tree function converts a matrix returned by the linkage function into an easy-to-use tree representation. - :SeeAlso: + See Also + -------- + to_tree: for converting a linkage matrix ``Z`` into a tree object. - - to_tree: for converting a linkage matrix ``Z`` into a tree object. """ def __init__(self, id, left=None, right=None, dist=0, count=1): @@ -624,18 +653,18 @@ self.count = left.count + right.count def get_id(self): - r""" + """ The identifier of the target node. For :math:`0 \leq i < n`, :math:`i` corresponds to original observation :math:`i`. For :math:`n \leq i` < :math:`2n-1`, :math:`i` corresponds to non-singleton cluster formed at iteration :math:`i-n`. - :Returns: + Returns + ------- + id : int + The identifier of the target node. - id : int - The identifier of the target node. - """ return self.id @@ -645,10 +674,11 @@ the cluster node nd. If the target node is a leaf, 1 is returned. - :Returns: + Returns + ------- + c : int + The number of leaf nodes below the target node. - c : int - The number of leaf nodes below the target node. """ return self.count @@ -657,9 +687,11 @@ Returns a reference to the left child tree object. If the node is a leaf, None is returned. - :Returns: - left : ClusterNode - The left child of the target node. + Returns + ------- + left : ClusterNode + The left child of the target node. + """ return self.left @@ -668,9 +700,10 @@ Returns a reference to the right child tree object. If the node is a leaf, None is returned. - :Returns: - right : ClusterNode - The left child of the target node. + Returns + ------- + right : ClusterNode + The left child of the target node. """ return self.right @@ -678,9 +711,10 @@ """ Returns True iff the target node is a leaf. - :Returns: - leafness : bool - True if the target node is a leaf node. + Returns + ------- + leafness : bool + True if the target node is a leaf node. """ return self.left is None @@ -698,18 +732,20 @@ returns a list of the node ids corresponding to the leaf nodes of the tree as they appear from left to right. - :Parameters: + Parameters + ---------- + func : function + Applied to each leaf ClusterNode object in the pre-order + traversal. Given the i'th leaf node in the pre-order + traversal ``n[i]``, the result of func(n[i]) is stored in + L[i]. If not provided, the index of the original observation + to which the node corresponds is used. - - func : function - Applied to each leaf ClusterNode object in the pre-order - traversal. Given the i'th leaf node in the pre-order - traversal ``n[i]``, the result of func(n[i]) is stored in - L[i]. If not provided, the index of the original observation - to which the node corresponds is used. + Returns + ------- + L : list + The pre-order traversal. - :Returns: - - L : list - The pre-order traversal. """ # Do a preorder traversal, caching the result. To avoid having to do @@ -763,25 +799,26 @@ user. ClusterNodes are not used as input to any of the functions in this library. - :Parameters: + Parameters + ---------- + Z : ndarray + The linkage matrix in proper form (see the ``linkage`` + function documentation). - - Z : ndarray - The linkage matrix in proper form (see the ``linkage`` - function documentation). + rd : bool, optional + When ``False``, a reference to the root ClusterNode object is + returned. Otherwise, a tuple (r,d) is returned. ``r`` is a + reference to the root node while ``d`` is a dictionary + mapping cluster ids to ClusterNode references. If a cluster id is + less than n, then it corresponds to a singleton cluster + (leaf node). See ``linkage`` for more information on the + assignment of cluster ids to clusters. - - r : bool - When ``False``, a reference to the root ClusterNode object is - returned. Otherwise, a tuple (r,d) is returned. ``r`` is a - reference to the root node while ``d`` is a dictionary - mapping cluster ids to ClusterNode references. If a cluster id is - less than n, then it corresponds to a singleton cluster - (leaf node). See ``linkage`` for more information on the - assignment of cluster ids to clusters. + Returns + ------- + L : list + The pre-order traversal. - :Returns: - - L : list - The pre-order traversal. - """ Z = np.asarray(Z, order='c') @@ -845,27 +882,32 @@ ``i`` and ``j`` is simply the distance between clusters ``s`` and ``t``. - :Parameters: - - Z : ndarray - The hierarchical clustering encoded as an array - (see ``linkage`` function). + Parameters + ---------- + Z : ndarray + The hierarchical clustering encoded as an array + (see ``linkage`` function). - - Y : ndarray (optional) - Calculates the cophenetic correlation coefficient ``c`` of a - hierarchical clustering defined by the linkage matrix ``Z`` - of a set of :math:`n` observations in :math:`m` - dimensions. ``Y`` is the condensed distance matrix from which - ``Z`` was generated. + Y : ndarray (optional) + Calculates the cophenetic correlation coefficient ``c`` of a + hierarchical clustering defined by the linkage matrix ``Z`` + of a set of :math:`n` observations in :math:`m` + dimensions. ``Y`` is the condensed distance matrix from which + ``Z`` was generated. - :Returns: (c, {d}) - - c : ndarray - The cophentic correlation distance (if ``y`` is passed). + Returns + ------- + res : tuple + A tuple (c, {d}): - - d : ndarray - The cophenetic distance matrix in condensed form. The - :math:`ij` th entry is the cophenetic distance between - original observations :math:`i` and :math:`j`. + - c : ndarray + The cophentic correlation distance (if ``y`` is passed). + - d : ndarray + The cophenetic distance matrix in condensed form. The + :math:`ij` th entry is the cophenetic distance between + original observations :math:`i` and :math:`j`. + """ Z = np.asarray(Z, order='c') @@ -899,38 +941,38 @@ return (c, zz) def inconsistent(Z, d=2): - r""" + """ Calculates inconsistency statistics on a linkage. Note: This function behaves similarly to the MATLAB(TM) inconsistent function. - :Parameters: - - d : int - The number of links up to ``d`` levels below each - non-singleton cluster + Parameters + ---------- + d : int + The number of links up to ``d`` levels below each + non-singleton cluster. + Z : ndarray + The :math:`(n-1)` by 4 matrix encoding the linkage + (hierarchical clustering). See ``linkage`` documentation + for more information on its form. - - Z : ndarray - The :math:`(n-1)` by 4 matrix encoding the linkage - (hierarchical clustering). See ``linkage`` documentation - for more information on its form. + Returns + ------- + R : ndarray + A :math:`(n-1)` by 5 matrix where the ``i``'th row + contains the link statistics for the non-singleton cluster + ``i``. The link statistics are computed over the link + heights for links :math:`d` levels below the cluster + ``i``. ``R[i,0]`` and ``R[i,1]`` are the mean and standard + deviation of the link heights, respectively; ``R[i,2]`` is + the number of links included in the calculation; and + ``R[i,3]`` is the inconsistency coefficient, + .. math:: - :Returns: - - R : ndarray - A :math:`(n-1)` by 5 matrix where the ``i``'th row - contains the link statistics for the non-singleton cluster - ``i``. The link statistics are computed over the link - heights for links :math:`d` levels below the cluster - ``i``. ``R[i,0]`` and ``R[i,1]`` are the mean and standard - deviation of the link heights, respectively; ``R[i,2]`` is - the number of links included in the calculation; and - ``R[i,3]`` is the inconsistency coefficient, + \frac{\mathtt{Z[i,2]}-\mathtt{R[i,0]}} {R[i,1]}. - .. math:: - - \frac{\mathtt{Z[i,2]}-\mathtt{R[i,0]}} - {R[i,1]}. """ Z = np.asarray(Z, order='c') @@ -967,15 +1009,16 @@ This function is useful when loading in linkages from legacy data files generated by MATLAB. - :Arguments: + Parameters + ---------- + Z : ndarray + A linkage matrix generated by MATLAB(TM). - - Z : ndarray - A linkage matrix generated by MATLAB(TM) + Returns + ------- + ZS : ndarray + A linkage matrix compatible with this library. - :Returns: - - - ZS : ndarray - A linkage matrix compatible with this library. """ Z = np.asarray(Z, dtype=np.double, order='c') Zs = Z.shape @@ -1006,14 +1049,17 @@ matrix has the last column removed and the cluster indices are converted to ``1..N`` indexing. - :Arguments: - - Z : ndarray - A linkage matrix generated by this library. + Parameters + ---------- + Z : ndarray + A linkage matrix generated by this library. - :Returns: - - ZM : ndarray - A linkage matrix compatible with MATLAB(TM)'s hierarchical - clustering functions. + Returns + ------- + ZM : ndarray + A linkage matrix compatible with MATLAB(TM)'s hierarchical + clustering functions. + """ Z = np.asarray(Z, order='c', dtype=np.double) Zs = Z.shape @@ -1033,13 +1079,16 @@ joined, the distance between them is no less than the distance between any previously joined clusters. - :Arguments: - - Z : ndarray - The linkage matrix to check for monotonicity. + Parameters + ---------- + Z : ndarray + The linkage matrix to check for monotonicity. - :Returns: - - b : bool - A boolean indicating whether the linkage is monotonic. + Returns + ------- + b : bool + A boolean indicating whether the linkage is monotonic. + """ Z = np.asarray(Z, order='c') is_valid_linkage(Z, throw=True, name='Z') @@ -1048,32 +1097,31 @@ return (Z[1:,2]>=Z[:-1,2]).all() def is_valid_im(R, warning=False, throw=False, name=None): - """ + """Returns True if the inconsistency matrix passed is valid. - Returns True if the inconsistency matrix passed is valid. It must - be a :math:`n` by 4 numpy array of doubles. The standard + It must be a :math:`n` by 4 numpy array of doubles. The standard deviations ``R[:,1]`` must be nonnegative. The link counts ``R[:,2]`` must be positive and no greater than :math:`n-1`. - :Arguments: - - R : ndarray - The inconsistency matrix to check for validity. + Parameters + ---------- + R : ndarray + The inconsistency matrix to check for validity. + warning : bool, optional + When ``True``, issues a Python warning if the linkage + matrix passed is invalid. + throw : bool, optional + When ``True``, throws a Python exception if the linkage + matrix passed is invalid. + name : str, optional + This string refers to the variable name of the invalid + linkage matrix. - - warning : bool - When ``True``, issues a Python warning if the linkage - matrix passed is invalid. + Returns + ------- + b : bool + True if the inconsistency matrix is valid. - - throw : bool - When ``True``, throws a Python exception if the linkage - matrix passed is invalid. - - - name : string - This string refers to the variable name of the invalid - linkage matrix. - - :Returns: - - b : bool - True iff the inconsistency matrix is valid. """ R = np.asarray(R, order='c') valid = True @@ -1127,7 +1175,7 @@ return valid def is_valid_linkage(Z, warning=False, throw=False, name=None): - r""" + """ Checks the validity of a linkage matrix. A linkage matrix is valid if it is a two dimensional nd-array (type double) with :math:`n` rows and 4 columns. The first two columns must contain indices @@ -1137,23 +1185,24 @@ (i.e. a cluster cannot join another cluster unless the cluster being joined has been generated.) - :Arguments: - - - warning : bool - When ``True``, issues a Python warning if the linkage - matrix passed is invalid. - - - throw : bool - When ``True``, throws a Python exception if the linkage - matrix passed is invalid. - - - name : string + Parameters + ---------- + Z : array_like + Linkage matrix. + warning : bool, optional + When ``True``, issues a Python warning if the linkage + matrix passed is invalid. + throw : bool, optional + When ``True``, throws a Python exception if the linkage + matrix passed is invalid. + name : str, optional This string refers to the variable name of the invalid linkage matrix. - :Returns: - - b : bool - True iff the inconsistency matrix is valid. + Returns + ------- + b : bool + True iff the inconsistency matrix is valid. """ Z = np.asarray(Z, order='c') @@ -1253,13 +1302,16 @@ Returns the number of original observations of the linkage matrix passed. - :Arguments: - - Z : ndarray - The linkage matrix on which to perform the operation. + Parameters + ---------- + Z : ndarray + The linkage matrix on which to perform the operation. - :Returns: - - n : int - The number of original observations in the linkage. + Returns + ------- + n : int + The number of original observations in the linkage. + """ Z = np.asarray(Z, order='c') is_valid_linkage(Z, throw=True, name='Z') @@ -1277,17 +1329,19 @@ extensive use of linkage and distance matrices that must correspond to the same set of original observations. - :Arguments: - - Z : ndarray - The linkage matrix to check for correspondance. + Parameters + ---------- + Z : ndarray + The linkage matrix to check for correspondance. + Y : ndarray + The condensed distance matrix to check for correspondance. - - Y : ndarray - The condensed distance matrix to check for correspondance. + Returns + ------- + b : bool + A boolean indicating whether the linkage matrix and distance + matrix could possibly correspond to one another. - :Returns: - - b : bool - A boolean indicating whether the linkage matrix and distance - matrix could possibly correspond to one another. """ is_valid_linkage(Z, throw=True) distance.is_valid_y(Y, throw=True) @@ -1483,14 +1537,17 @@ vector index) as they appear in the tree from left to right. Z is a linkage matrix. - :Arguments: - - Z : ndarray - The hierarchical clustering encoded as a matrix. See - ``linkage`` for more information. + Parameters + ---------- + Z : ndarray + The hierarchical clustering encoded as a matrix. See + ``linkage`` for more information. - :Returns: - - L : ndarray - The list of leaf node ids. + Returns + ------- + L : ndarray + The list of leaf node ids. + """ Z = np.asarray(Z, order='c') is_valid_linkage(Z, throw=True, name='Z') @@ -1712,8 +1769,9 @@ Changes the list of matplotlib color codes to use when coloring links with the dendrogram color_threshold feature. - :Arguments: - - palette : A list of matplotlib color codes. The order of + Parameters + ---------- + palette : A list of matplotlib color codes. The order of the color codes is the order in which the colors are cycled through when color thresholding in the dendrogram. @@ -1737,7 +1795,7 @@ leaf_font_size=None, leaf_rotation=None, leaf_label_func=None, no_leaves=False, show_contracted=False, link_color_func=None): - r""" + """ Plots the hiearchical clustering defined by the linkage Z as a dendrogram. The dendrogram illustrates how each cluster is composed by drawing a U-shaped link between a non-singleton @@ -1747,14 +1805,15 @@ children clusters. It is expected that the distances in Z[:,2] be monotonic, otherwise crossings appear in the dendrogram. - :Arguments: - - - Z : ndarray + Parameters + ---------- + Z : ndarray The linkage matrix encoding the hierarchical clustering to render as a dendrogram. See the ``linkage`` function for more information on the format of ``Z``. - - - truncate_mode : string + p : int, optional + The ``p`` parameter for ``truncate_mode``. + truncate_mode : str, optional The dendrogram can be hard to read when the original observation matrix from which the linkage is derived is large. Truncation is used to condense the dendrogram. There @@ -1773,162 +1832,146 @@ * 'level'/'mtica': no more than ``p`` levels of the dendrogram tree are displayed. This corresponds to Mathematica(TM) behavior. + color_threshold : double, optional + For brevity, let :math:`t` be the ``color_threshold``. + Colors all the descendent links below a cluster node + :math:`k` the same color if :math:`k` is the first node below + the cut threshold :math:`t`. All links connecting nodes with + distances greater than or equal to the threshold are colored + blue. If :math:`t` is less than or equal to zero, all nodes + are colored blue. If ``color_threshold`` is ``None`` or + 'default', corresponding with MATLAB(TM) behavior, the + threshold is set to ``0.7*max(Z[:,2])``. + get_leaves : bool, optional + Includes a list ``R['leaves']=H`` in the result + dictionary. For each :math:`i`, ``H[i] == j``, cluster node + :math:`j` appears in the :math:`i` th position in the + left-to-right traversal of the leaves, where :math:`j < 2n-1` + and :math:`i < n`. + orientation : str, optional + The direction to plot the dendrogram, which can be any + of the following strings - - p : int - The ``p`` parameter for ``truncate_mode``. -` - - color_threshold : double - For brevity, let :math:`t` be the ``color_threshold``. - Colors all the descendent links below a cluster node - :math:`k` the same color if :math:`k` is the first node below - the cut threshold :math:`t`. All links connecting nodes with - distances greater than or equal to the threshold are colored - blue. If :math:`t` is less than or equal to zero, all nodes - are colored blue. If ``color_threshold`` is ``None`` or - 'default', corresponding with MATLAB(TM) behavior, the - threshold is set to ``0.7*max(Z[:,2])``. + * 'top': plots the root at the top, and plot descendent + links going downwards. (default). - - get_leaves : bool - Includes a list ``R['leaves']=H`` in the result - dictionary. For each :math:`i`, ``H[i] == j``, cluster node - :math:`j` appears in the :math:`i` th position in the - left-to-right traversal of the leaves, where :math:`j < 2n-1` - and :math:`i < n`. + * 'bottom': plots the root at the bottom, and plot descendent + links going upwards. - - orientation : string - The direction to plot the dendrogram, which can be any - of the following strings + * 'left': plots the root at the left, and plot descendent + links going right. - * 'top': plots the root at the top, and plot descendent - links going downwards. (default). - - * 'bottom': plots the root at the bottom, and plot descendent - links going upwards. - - * 'left': plots the root at the left, and plot descendent - links going right. - - * 'right': plots the root at the right, and plot descendent + * 'right': plots the root at the right, and plot descendent links going left. - - labels : ndarray - By default ``labels`` is ``None`` so the index of the - original observation is used to label the leaf nodes. + labels : ndarray, optional + By default ``labels`` is ``None`` so the index of the + original observation is used to label the leaf nodes. + Otherwise, this is an :math:`n` -sized list (or tuple). The + ``labels[i]`` value is the text to put under the :math:`i` th + leaf node only if it corresponds to an original observation + and not a non-singleton cluster. + count_sort : str or bool, optional + For each node n, the order (visually, from left-to-right) n's + two descendent links are plotted is determined by this + parameter, which can be any of the following values: - Otherwise, this is an :math:`n` -sized list (or tuple). The - ``labels[i]`` value is the text to put under the :math:`i` th - leaf node only if it corresponds to an original observation - and not a non-singleton cluster. + * False: nothing is done. - - count_sort : string/bool - For each node n, the order (visually, from left-to-right) n's - two descendent links are plotted is determined by this - parameter, which can be any of the following values: + * 'ascending'/True: the child with the minimum number of + original objects in its cluster is plotted first. - * False: nothing is done. + * 'descendent': the child with the maximum number of + original objects in its cluster is plotted first. - * 'ascending'/True: the child with the minimum number of - original objects in its cluster is plotted first. + Note ``distance_sort`` and ``count_sort`` cannot both be + ``True``. - * 'descendent': the child with the maximum number of - original objects in its cluster is plotted first. + distance_sort : str or bool, optional + For each node n, the order (visually, from left-to-right) n's + two descendent links are plotted is determined by this + parameter, which can be any of the following values: - Note ``distance_sort`` and ``count_sort`` cannot both be - ``True``. + * False: nothing is done. - - distance_sort : string/bool - For each node n, the order (visually, from left-to-right) n's - two descendent links are plotted is determined by this - parameter, which can be any of the following values: + * 'ascending'/True: the child with the minimum distance + between its direct descendents is plotted first. - * False: nothing is done. + * 'descending': the child with the maximum distance + between its direct descendents is plotted first. - * 'ascending'/True: the child with the minimum distance - between its direct descendents is plotted first. + Note ``distance_sort`` and ``count_sort`` cannot both be + ``True``. - * 'descending': the child with the maximum distance - between its direct descendents is plotted first. - - Note ``distance_sort`` and ``count_sort`` cannot both be - ``True``. - - - show_leaf_counts : bool - + show_leaf_counts : bool, optional When ``True``, leaf nodes representing :math:`k>1` original observation are labeled with the number of observations they contain in parentheses. + no_plot : bool, optional + When ``True``, the final rendering is not performed. This is + useful if only the data structures computed for the rendering + are needed or if matplotlib is not available. + no_labels : bool, optional + When ``True``, no labels appear next to the leaf nodes in the + rendering of the dendrogram. + leaf_label_rotation : double, optional + Specifies the angle (in degrees) to rotate the leaf + labels. When unspecified, the rotation based on the number of + nodes in the dendrogram. (Default=0) + leaf_font_size : int, optional + Specifies the font size (in points) of the leaf labels. When + unspecified, the size based on the number of nodes in the + dendrogram. + leaf_label_func : lambda or function, optional + When leaf_label_func is a callable function, for each + leaf with cluster index :math:`k < 2n-1`. The function + is expected to return a string with the label for the + leaf. - - no_plot : bool - When ``True``, the final rendering is not performed. This is - useful if only the data structures computed for the rendering - are needed or if matplotlib is not available. + Indices :math:`k < n` correspond to original observations + while indices :math:`k \geq n` correspond to non-singleton + clusters. - - no_labels : bool - When ``True``, no labels appear next to the leaf nodes in the - rendering of the dendrogram. + For example, to label singletons with their node id and + non-singletons with their id, count, and inconsistency + coefficient, simply do:: - - leaf_label_rotation : double + # First define the leaf label function. + def llf(id): + if id < n: + return str(id) + else: + return '[%d %d %1.2f]' % (id, count, R[n-id,3]) - Specifies the angle (in degrees) to rotate the leaf - labels. When unspecified, the rotation based on the number of - nodes in the dendrogram. (Default=0) + # The text for the leaf nodes is going to be big so force + # a rotation of 90 degrees. + dendrogram(Z, leaf_label_func=llf, leaf_rotation=90) - - leaf_font_size : int - Specifies the font size (in points) of the leaf labels. When - unspecified, the size based on the number of nodes in the - dendrogram. + show_contracted : bool + When ``True`` the heights of non-singleton nodes contracted + into a leaf node are plotted as crosses along the link + connecting that leaf node. This really is only useful when + truncation is used (see ``truncate_mode`` parameter). + link_color_func : lambda/function + When a callable function, + link_color_function is called with each non-singleton id + corresponding to each U-shaped link it will paint. The + function is expected to return the color to paint the link, + encoded as a matplotlib color string code. - - leaf_label_func : lambda or function + For example:: - When leaf_label_func is a callable function, for each - leaf with cluster index :math:`k < 2n-1`. The function - is expected to return a string with the label for the - leaf. + dendrogram(Z, link_color_func=lambda k: colors[k]) - Indices :math:`k < n` correspond to original observations - while indices :math:`k \geq n` correspond to non-singleton - clusters. + colors the direct links below each untruncated non-singleton node + ``k`` using ``colors[k]``. - For example, to label singletons with their node id and - non-singletons with their id, count, and inconsistency - coefficient, simply do:: + Returns + ------- + R : dict + A dictionary of data structures computed to render the + dendrogram. Its has the following keys: - # First define the leaf label function. - def llf(id): - if id < n: - return str(id) - else: - return '[%d %d %1.2f]' % (id, count, R[n-id,3]) - - # The text for the leaf nodes is going to be big so force - # a rotation of 90 degrees. - dendrogram(Z, leaf_label_func=llf, leaf_rotation=90) - - - show_contracted : bool - When ``True`` the heights of non-singleton nodes contracted - into a leaf node are plotted as crosses along the link - connecting that leaf node. This really is only useful when - truncation is used (see ``truncate_mode`` parameter). - - - link_color_func : lambda/function When a callable function, - link_color_function is called with each non-singleton id - corresponding to each U-shaped link it will paint. The - function is expected to return the color to paint the link, - encoded as a matplotlib color string code. - - For example:: - - dendrogram(Z, link_color_func=lambda k: colors[k]) - - colors the direct links below each untruncated non-singleton node - ``k`` using ``colors[k]``. - - :Returns: - - - R : dict - A dictionary of data structures computed to render the - dendrogram. Its has the following keys: - - 'icoords': a list of lists ``[I1, I2, ..., Ip]`` where ``Ik`` is a list of 4 independent variable coordinates corresponding to the line that represents the k'th link @@ -1948,6 +1991,7 @@ :math:`i` th leaf node corresponds to an original observation. Otherwise, it corresponds to a non-singleton cluster. + """ # Features under consideration. @@ -2110,7 +2154,9 @@ i is non-singleton, otherwise the independent coordinate of the leaf node if i is a leaf node. - Returns a tuple (left, w, h, md) + Returns + ------- + A tuple (left, w, h, md), where: * left is the independent variable coordinate of the center of the the U of the subtree @@ -2319,25 +2365,24 @@ return ( ((uiva + uivb) / 2), uwa+uwb, h, max_dist) def is_isomorphic(T1, T2): - r""" + """ Determines if two different cluster assignments ``T1`` and ``T2`` are equivalent. - :Arguments: - - T1 : ndarray - An assignment of singleton cluster ids to flat cluster - ids. + Parameters + ---------- + T1 : ndarray + An assignment of singleton cluster ids to flat cluster ids. + T2 : ndarray + An assignment of singleton cluster ids to flat cluster ids. - - T2 : ndarray - An assignment of singleton cluster ids to flat cluster - ids. + Returns + ------- + b : bool + Whether the flat cluster assignments ``T1`` and ``T2`` are + equivalent. - :Returns: - - b : boolean - Whether the flat cluster assignments ``T1`` and ``T2`` are - equivalent. - """ T1 = np.asarray(T1, order='c') T2 = np.asarray(T2, order='c') @@ -2367,24 +2412,27 @@ return True def maxdists(Z): - r""" + """ MD = maxdists(Z) - Returns the maximum distance between any cluster for each - non-singleton cluster. + Returns the maximum distance between any cluster for each + non-singleton cluster. - :Arguments: - - Z : ndarray - The hierarchical clustering encoded as a matrix. See - ``linkage`` for more information. + Parameters + ---------- + Z : ndarray + The hierarchical clustering encoded as a matrix. See + ``linkage`` for more information. - :Returns: - - MD : ndarray - A ``(n-1)`` sized numpy array of doubles; ``MD[i]`` represents - the maximum distance between any cluster (including - singletons) below and including the node with index i. More - specifically, ``MD[i] = Z[Q(i)-n, 2].max()`` where ``Q(i)`` is the - set of all node indices below and including node i. + Returns + ------- + MD : ndarray + A ``(n-1)`` sized numpy array of doubles; ``MD[i]`` represents + the maximum distance between any cluster (including + singletons) below and including the node with index i. More + specifically, ``MD[i] = Z[Q(i)-n, 2].max()`` where ``Q(i)`` is the + set of all node indices below and including node i. + """ Z = np.asarray(Z, order='c', dtype=np.double) is_valid_linkage(Z, throw=True, name='Z') @@ -2396,21 +2444,23 @@ return MD def maxinconsts(Z, R): - r""" + """ Returns the maximum inconsistency coefficient for each non-singleton cluster and its descendents. - :Arguments: - - Z : ndarray - The hierarchical clustering encoded as a matrix. See - ``linkage`` for more information. + Parameters + ---------- + Z : ndarray + The hierarchical clustering encoded as a matrix. See + ``linkage`` for more information. + R : ndarray + The inconsistency matrix. - - R : ndarray - The inconsistency matrix. + Returns + ------- + MI : ndarray + A monotonic ``(n-1)``-sized numpy array of doubles. - :Returns: - - MI : ndarray - A monotonic ``(n-1)``-sized numpy array of doubles. """ Z = np.asarray(Z, order='c') R = np.asarray(R, order='c') @@ -2426,29 +2476,29 @@ return MI def maxRstat(Z, R, i): - r""" + """ Returns the maximum statistic for each non-singleton cluster and its descendents. - :Arguments: - - Z : ndarray - The hierarchical clustering encoded as a matrix. See - ``linkage`` for more information. + Parameters + ---------- + Z : ndarray + The hierarchical clustering encoded as a matrix. See + ``linkage`` for more information. + R : ndarray + The inconsistency matrix. + i : int + The column of ``R`` to use as the statistic. - - R : ndarray - The inconsistency matrix. + Returns + ------- + MR : ndarray + Calculates the maximum statistic for the i'th column of the + inconsistency matrix ``R`` for each non-singleton cluster + node. ``MR[j]`` is the maximum over ``R[Q(j)-n, i]`` where + ``Q(j)`` the set of all node ids corresponding to nodes below + and including ``j``. - - i : int - The column of ``R`` to use as the statistic. - - :Returns: - - - MR : ndarray - Calculates the maximum statistic for the i'th column of the - inconsistency matrix ``R`` for each non-singleton cluster - node. ``MR[j]`` is the maximum over ``R[Q(j)-n, i]`` where - ``Q(j)`` the set of all node ids corresponding to nodes below - and including ``j``. """ Z = np.asarray(Z, order='c') R = np.asarray(R, order='c') @@ -2469,7 +2519,7 @@ return MR def leaders(Z, T): - r""" + """ (L, M) = leaders(Z, T): Returns the root nodes in a hierarchical clustering corresponding @@ -2492,35 +2542,37 @@ this condition is violated, ``T`` is not a valid cluster assignment vector, and an exception will be thrown. + Parameters + ---------- + Z : ndarray + The hierarchical clustering encoded as a matrix. See + ``linkage`` for more information. + T : ndarray + The flat cluster assignment vector. - :Arguments: - - Z : ndarray - The hierarchical clustering encoded as a matrix. See - ``linkage`` for more information. + Returns + ------- + A tuple (L, M) with - - T : ndarray - The flat cluster assignment vector. + L : ndarray + The leader linkage node id's stored as a k-element 1D + array where :math:`k` is the number of flat clusters found + in ``T``. - :Returns: (L, M) + ``L[j]=i`` is the linkage cluster node id that is the + leader of flat cluster with id M[j]. If ``i < n``, ``i`` + corresponds to an original observation, otherwise it + corresponds to a non-singleton cluster. - - L : ndarray - The leader linkage node id's stored as a k-element 1D - array where :math:`k` is the number of flat clusters found - in ``T``. + For example: if ``L[3]=2`` and ``M[3]=8``, the flat cluster with + id 8's leader is linkage node 2. - ``L[j]=i`` is the linkage cluster node id that is the - leader of flat cluster with id M[j]. If ``i < n``, ``i`` - corresponds to an original observation, otherwise it - corresponds to a non-singleton cluster. + M : ndarray + The leader linkage node id's stored as a k-element 1D + array where :math:`k` is the number of flat clusters found + in ``T``. This allows the set of flat cluster ids to be + any arbitrary set of :math:`k` integers. - For example: if ``L[3]=2`` and ``M[3]=8``, the flat cluster with - id 8's leader is linkage node 2. - - - M : ndarray - The leader linkage node id's stored as a k-element 1D - array where :math:`k` is the number of flat clusters found - in ``T``. This allows the set of flat cluster ids to be - any arbitrary set of :math:`k` integers. """ Z = np.asarray(Z, order='c') T = np.asarray(T, order='c') Modified: trunk/scipy/cluster/vq.py =================================================================== --- trunk/scipy/cluster/vq.py 2011-02-20 09:58:04 UTC (rev 7163) +++ trunk/scipy/cluster/vq.py 2011-02-20 13:30:33 UTC (rev 7164) @@ -102,28 +102,29 @@ divided by its standard deviation across all observations to give it unit variance. - :Parameters: - obs : ndarray - Each row of the array is an observation. The - columns are the features seen during each observation. - :: + Parameters + ---------- + obs : ndarray + Each row of the array is an observation. The + columns are the features seen during each observation. + :: - # f0 f1 f2 - obs = [[ 1., 1., 1.], #o0 - [ 2., 2., 2.], #o1 - [ 3., 3., 3.], #o2 - [ 4., 4., 4.]]) #o3 + # f0 f1 f2 + obs = [[ 1., 1., 1.], #o0 + [ 2., 2., 2.], #o1 + [ 3., 3., 3.], #o2 + [ 4., 4., 4.]]) #o3 - XXX perhaps should have an axis variable here. + XXX perhaps should have an axis variable here. - :Returns: - result : ndarray - Contains the values in obs scaled by the standard devation - of each column. + Returns + ------- + result : ndarray + Contains the values in `obs` scaled by the standard devation + of each column. Examples -------- - >>> from numpy import array >>> from scipy.cluster.vq import whiten >>> features = array([[ 1.9,2.3,1.7], @@ -151,29 +152,31 @@ book can be created with the k-means algorithm or a different encoding algorithm. - :Parameters: - obs : ndarray - Each row of the NxM array is an observation. The columns are the - "features" seen during each observation. The features must be - whitened first using the whiten function or something equivalent. - code_book : ndarray. - The code book is usually generated using the k-means algorithm. - Each row of the array holds a different code, and the columns are - the features of the code. + Parameters + ---------- + obs : ndarray + Each row of the NxM array is an observation. The columns are the + "features" seen during each observation. The features must be + whitened first using the whiten function or something equivalent. + code_book : ndarray + The code book is usually generated using the k-means algorithm. + Each row of the array holds a different code, and the columns are + the features of the code. - :: + :: - # f0 f1 f2 f3 - code_book = [[ 1., 2., 3., 4.], #c0 - [ 1., 2., 3., 4.], #c1 - [ 1., 2., 3., 4.]]) #c2 + # f0 f1 f2 f3 + code_book = [[ 1., 2., 3., 4.], #c0 + [ 1., 2., 3., 4.], #c1 + [ 1., 2., 3., 4.]]) #c2 - :Returns: - code : ndarray - A length N array holding the code book index for each observation. - dist : ndarray - The distortion (distance) between the observation and its nearest - code. + Returns + ------- + code : ndarray + A length N array holding the code book index for each observation. + dist : ndarray + The distortion (distance) between the observation and its nearest + code. Notes ----- @@ -214,27 +217,30 @@ The algorithm computes the euclidian distance between each observation and every frame in the code_book. - :Parameters: - obs : ndarray - Expects a rank 2 array. Each row is one observation. - code_book : ndarray - Code book to use. Same format than obs. Should have same number of - features (eg columns) than obs. + Parameters + ---------- + obs : ndarray + Expects a rank 2 array. Each row is one observation. + code_book : ndarray + Code book to use. Same format than obs. Should have same number of + features (eg columns) than obs. - :Note: - This function is slower than the C version but works for - all input types. If the inputs have the wrong types for the - C versions of the function, this one is called as a last resort. + Returns + ------- + code : ndarray + code[i] gives the label of the ith obversation, that its code is + code_book[code[i]]. + mind_dist : ndarray + min_dist[i] gives the distance between the ith observation and its + corresponding code. - It is about 20 times slower than the C version. + Notes + ----- + This function is slower than the C version but works for + all input types. If the inputs have the wrong types for the + C versions of the function, this one is called as a last resort. - :Returns: - code : ndarray - code[i] gives the label of the ith obversation, that its code is - code_book[code[i]]. - mind_dist : ndarray - min_dist[i] gives the distance between the ith observation and its - corresponding code. + It is about 20 times slower than the C version. """ # n = number of observations @@ -269,19 +275,21 @@ def _py_vq_1d(obs, code_book): """ Python version of vq algorithm for rank 1 only. - :Parameters: - obs : ndarray - Expects a rank 1 array. Each item is one observation. - code_book : ndarray - Code book to use. Same format than obs. Should rank 1 too. + Parameters + ---------- + obs : ndarray + Expects a rank 1 array. Each item is one observation. + code_book : ndarray + Code book to use. Same format than obs. Should rank 1 too. - :Returns: - code : ndarray - code[i] gives the label of the ith obversation, that its code is - code_book[code[i]]. - mind_dist : ndarray - min_dist[i] gives the distance between the ith observation and its - corresponding code. + Returns + ------- + code : ndarray + code[i] gives the label of the ith obversation, that its code is + code_book[code[i]]. + mind_dist : ndarray + min_dist[i] gives the distance between the ith observation and its + corresponding code. """ raise RuntimeError("_py_vq_1d buggy, do not use rank 1 arrays for now") @@ -302,26 +310,29 @@ The algorithm simply computes the euclidian distance between each observation and every frame in the code_book/ - :Parameters: - obs : ndarray - Expect a rank 2 array. Each row is one observation. - code_book : ndarray - Code book to use. Same format than obs. Should have same number of - features (eg columns) than obs. + Parameters + ---------- + obs : ndarray + Expect a rank 2 array. Each row is one observation. + code_book : ndarray + Code book to use. Same format than obs. Should have same number of + features (eg columns) than obs. - :Note: - This could be faster when number of codebooks is small, but it - becomes a real memory hog when codebook is large. It requires - N by M by O storage where N=number of obs, M = number of - features, and O = number of codes. + Returns + ------- + code : ndarray + code[i] gives the label of the ith obversation, that its code is + code_book[code[i]]. + mind_dist : ndarray + min_dist[i] gives the distance between the ith observation and its + corresponding code. - :Returns: - code : ndarray - code[i] gives the label of the ith obversation, that its code is - code_book[code[i]]. - mind_dist : ndarray - min_dist[i] gives the distance between the ith observation and its - corresponding code. + Notes + ----- + This could be faster when number of codebooks is small, but it + becomes a real memory hog when codebook is large. It requires + N by M by O storage where N=number of obs, M = number of + features, and O = number of codes. """ d = shape(obs)[1] @@ -344,21 +355,22 @@ def _kmeans(obs, guess, thresh=1e-5): """ "raw" version of k-means. - :Returns: - code_book : - the lowest distortion codebook found. - avg_dist : - the average distance a observation is from a code in the book. - Lower means the code_book matches the data better. + Returns + ------- + code_book : + the lowest distortion codebook found. + avg_dist : + the average distance a observation is from a code in the book. + Lower means the code_book matches the data better. - :SeeAlso: - - kmeans : wrapper around k-means + See Also + -------- + kmeans : wrapper around k-means XXX should have an axis variable here. Examples -------- - Note: not whitened in this example. >>> from numpy import array @@ -518,13 +530,14 @@ This is done by taking the k first values of a random permutation of 1..N where N is the number of observation. - :Parameters: - data : ndarray - Expect a rank 1 or 2 array. Rank 1 are assumed to describe one - dimensional data, rank 2 multidimensional data, in which case one - row is one observation. - k : int - Number of samples to generate. + Parameters + ---------- + data : ndarray + Expect a rank 1 or 2 array. Rank 1 are assumed to describe one + dimensional data, rank 2 multidimensional data, in which case one + row is one observation. + k : int + Number of samples to generate. """ if data.ndim > 1: @@ -543,13 +556,14 @@ More precisely, it returns k observations sampled from a Gaussian random variable which mean and covariances are the one estimated from data. - :Parameters: - data : ndarray - Expect a rank 1 or 2 array. Rank 1 are assumed to describe one - dimensional data, rank 2 multidimensional data, in which case one - row is one observation. - k : int - Number of samples to generate. + Parameters + ---------- + data : ndarray + Expect a rank 1 or 2 array. Rank 1 are assumed to describe one + dimensional data, rank 2 multidimensional data, in which case one + row is one observation. + k : int + Number of samples to generate. """ def init_rank1(data): @@ -598,44 +612,47 @@ observations and centroids. Several initialization methods are included. - :Parameters: - data : ndarray - A M by N array of M observations in N dimensions or a length - M array of M one-dimensional observations. - k : int or ndarray - The number of clusters to form as well as the number of - centroids to generate. If minit initialization string is - 'matrix', or if a ndarray is given instead, it is - interpreted as initial cluster to use instead. - iter : int - Number of iterations of the k-means algrithm to run. Note - that this differs in meaning from the iters parameter to - the kmeans function. - thresh : float - (not used yet). - minit : string - Method for initialization. Available methods are 'random', - 'points', 'uniform', and 'matrix': + Parameters + ---------- + data : ndarray + A M by N array of M observations in N dimensions or a length + M array of M one-dimensional observations. + k : int or ndarray + The number of clusters to form as well as the number of + centroids to generate. If minit initialization string is + 'matrix', or if a ndarray is given instead, it is + interpreted as initial cluster to use instead. + iter : int + Number of iterations of the k-means algrithm to run. Note + that this differs in meaning from the iters parameter to + the kmeans function. + thresh : float + (not used yet). + minit : string + Method for initialization. Available methods are 'random', + 'points', 'uniform', and 'matrix': - 'random': generate k centroids from a Gaussian with mean and - variance estimated from the data. + 'random': generate k centroids from a Gaussian with mean and + variance estimated from the data. - 'points': choose k observations (rows) at random from data for - the initial centroids. + 'points': choose k observations (rows) at random from data for + the initial centroids. - 'uniform': generate k observations from the data from a uniform - distribution defined by the data set (unsupported). + 'uniform': generate k observations from the data from a uniform + distribution defined by the data set (unsupported). - 'matrix': interpret the k parameter as a k by M (or length k - array for one-dimensional data) array of initial centroids. + 'matrix': interpret the k parameter as a k by M (or length k + array for one-dimensional data) array of initial centroids. - :Returns: - centroid : ndarray - A k by N array of centroids found at the last iteration of - k-means. - label : ndarray - label[i] is the code or index of the centroid the - i'th observation is closest to. + Returns + ------- + centroid : ndarray + A k by N array of centroids found at the last iteration of + k-means. + label : ndarray + label[i] is the code or index of the centroid the + i'th observation is closest to. + """ if missing not in _valid_miss_meth.keys(): raise ValueError("Unkown missing method: %s" % str(missing)) @@ -690,7 +707,9 @@ def _kmeans2(data, code, niter, nc, missing): """ "raw" version of kmeans2. Do not use directly. - Run k-means with a given initial codebook. """ + Run k-means with a given initial codebook. + + """ for i in range(niter): # Compute the nearest neighbour for each obs # using the current code book Modified: trunk/scipy/spatial/ckdtree.c =================================================================== --- trunk/scipy/spatial/ckdtree.c 2011-02-20 09:58:04 UTC (rev 7163) +++ trunk/scipy/spatial/ckdtree.c 2011-02-20 13:30:33 UTC (rev 7164) @@ -1,4 +1,4 @@ -/* Generated by Cython 0.12.1 on Wed Jun 16 17:30:37 2010 */ +/* Generated by Cython 0.12.1 on Sun Feb 20 19:40:58 2011 */ #define PY_SSIZE_T_CLEAN #include "Python.h" @@ -375,7 +375,7 @@ typedef npy_cdouble __pyx_t_5numpy_complex_t; -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":15 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":15 * * # priority queue * cdef union heapcontents: # <<<<<<<<<<<<<< @@ -388,7 +388,7 @@ char *ptrdata; }; -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":19 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":19 * char* ptrdata * * cdef struct heapitem: # <<<<<<<<<<<<<< @@ -401,7 +401,7 @@ union __pyx_t_5scipy_7spatial_7ckdtree_heapcontents contents; }; -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":23 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":23 * heapcontents contents * * cdef struct heap: # <<<<<<<<<<<<<< @@ -415,7 +415,7 @@ int space; }; -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":139 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":139 * * # Tree structure * cdef struct innernode: # <<<<<<<<<<<<<< @@ -431,7 +431,7 @@ struct __pyx_t_5scipy_7spatial_7ckdtree_innernode *greater; }; -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":145 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":145 * innernode* less * innernode* greater * cdef struct leafnode: # <<<<<<<<<<<<<< @@ -446,7 +446,7 @@ int end_idx; }; -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":153 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":153 * # this is the standard trick for variable-size arrays: * # malloc sizeof(nodeinfo)+self.m*sizeof(double) bytes. * cdef struct nodeinfo: # <<<<<<<<<<<<<< @@ -459,7 +459,7 @@ double side_distances[0]; }; -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":157 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":157 * double side_distances[0] * * cdef class cKDTree: # <<<<<<<<<<<<<< @@ -865,8 +865,7 @@ static char __pyx_k_10[] = "unknown dtype code in numpy.pxd (%d)"; static char __pyx_k_11[] = "Format string allocated too short, see comment in numpy.pxd"; static char __pyx_k_12[] = "Format string allocated too short."; -static char __pyx_k_13[] = "cKDTree.__init__ (line 195)"; -static char __pyx_k_14[] = "cKDTree.query (line 516)"; +static char __pyx_k_13[] = "cKDTree.query (line 514)"; static char __pyx_k__B[] = "B"; static char __pyx_k__H[] = "H"; static char __pyx_k__I[] = "I"; @@ -937,7 +936,6 @@ static char __pyx_k__ptrdata[] = "ptrdata"; static char __pyx_k__reshape[] = "reshape"; static char __pyx_k__strides[] = "strides"; -static char __pyx_k____init__[] = "__init__"; static char __pyx_k____main__[] = "__main__"; static char __pyx_k____test__[] = "__test__"; static char __pyx_k__contents[] = "contents"; @@ -964,7 +962,6 @@ static PyObject *__pyx_kp_u_11; static PyObject *__pyx_kp_u_12; static PyObject *__pyx_kp_u_13; -static PyObject *__pyx_kp_u_14; static PyObject *__pyx_kp_s_2; static PyObject *__pyx_n_s_3; static PyObject *__pyx_kp_s_5; @@ -976,7 +973,6 @@ static PyObject *__pyx_n_s__ValueError; static PyObject *__pyx_n_s____build; static PyObject *__pyx_n_s____free_tree; -static PyObject *__pyx_n_s____init__; static PyObject *__pyx_n_s____main__; static PyObject *__pyx_n_s____query; static PyObject *__pyx_n_s____test__; @@ -1053,7 +1049,7 @@ static PyObject *__pyx_int_15; static double __pyx_k_4; -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":28 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":28 * int space * * cdef inline heapcreate(heap* self,int initial_size): # <<<<<<<<<<<<<< @@ -1065,7 +1061,7 @@ PyObject *__pyx_r = NULL; __Pyx_RefNannySetupContext("heapcreate"); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":29 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":29 * * cdef inline heapcreate(heap* self,int initial_size): * self.space = initial_size # <<<<<<<<<<<<<< @@ -1074,7 +1070,7 @@ */ __pyx_v_self->space = __pyx_v_initial_size; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":30 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":30 * cdef inline heapcreate(heap* self,int initial_size): * self.space = initial_size * self.heap = stdlib.malloc(sizeof(heapitem)*self.space) # <<<<<<<<<<<<<< @@ -1083,7 +1079,7 @@ */ __pyx_v_self->heap = ((struct __pyx_t_5scipy_7spatial_7ckdtree_heapitem *)malloc(((sizeof(struct __pyx_t_5scipy_7spatial_7ckdtree_heapitem)) * __pyx_v_self->space))); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":31 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":31 * self.space = initial_size * self.heap = stdlib.malloc(sizeof(heapitem)*self.space) * self.n=0 # <<<<<<<<<<<<<< @@ -1098,7 +1094,7 @@ return __pyx_r; } -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":33 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":33 * self.n=0 * * cdef inline heapdestroy(heap* self): # <<<<<<<<<<<<<< @@ -1110,7 +1106,7 @@ PyObject *__pyx_r = NULL; __Pyx_RefNannySetupContext("heapdestroy"); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":34 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":34 * * cdef inline heapdestroy(heap* self): * stdlib.free(self.heap) # <<<<<<<<<<<<<< @@ -1125,7 +1121,7 @@ return __pyx_r; } -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":36 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":36 * stdlib.free(self.heap) * * cdef inline heapresize(heap* self, int new_space): # <<<<<<<<<<<<<< @@ -1141,7 +1137,7 @@ PyObject *__pyx_t_4 = NULL; __Pyx_RefNannySetupContext("heapresize"); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":37 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":37 * * cdef inline heapresize(heap* self, int new_space): * if new_spacen); if (__pyx_t_1) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":38 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":38 * cdef inline heapresize(heap* self, int new_space): * if new_spacespace = __pyx_v_new_space; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":40 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":40 * raise ValueError("Heap containing %d items cannot be resized to %d" % (self.n, new_space)) * self.space = new_space * self.heap = stdlib.realloc(self.heap,new_space*sizeof(heapitem)) # <<<<<<<<<<<<<< @@ -1220,7 +1216,7 @@ return __pyx_r; } -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":42 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":42 * self.heap = stdlib.realloc(self.heap,new_space*sizeof(heapitem)) * * cdef inline heappush(heap* self, heapitem item): # <<<<<<<<<<<<<< @@ -1238,7 +1234,7 @@ int __pyx_t_4; __Pyx_RefNannySetupContext("heappush"); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":46 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":46 * cdef heapitem t * * self.n += 1 # <<<<<<<<<<<<<< @@ -1247,7 +1243,7 @@ */ __pyx_v_self->n += 1; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":47 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":47 * * self.n += 1 * if self.n>self.space: # <<<<<<<<<<<<<< @@ -1257,7 +1253,7 @@ __pyx_t_1 = (__pyx_v_self->n > __pyx_v_self->space); if (__pyx_t_1) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":48 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":48 * self.n += 1 * if self.n>self.space: * heapresize(self,2*self.space+1) # <<<<<<<<<<<<<< @@ -1271,7 +1267,7 @@ } __pyx_L3:; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":50 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":50 * heapresize(self,2*self.space+1) * * i = self.n-1 # <<<<<<<<<<<<<< @@ -1280,7 +1276,7 @@ */ __pyx_v_i = (__pyx_v_self->n - 1); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":51 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":51 * * i = self.n-1 * self.heap[i] = item # <<<<<<<<<<<<<< @@ -1289,7 +1285,7 @@ */ (__pyx_v_self->heap[__pyx_v_i]) = __pyx_v_item; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":52 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":52 * i = self.n-1 * self.heap[i] = item * while i>0 and self.heap[i].priority0 and self.heap[i].priorityheap[__Pyx_div_long((__pyx_v_i - 1), 2)]); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":54 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":54 * while i>0 and self.heap[i].priorityheap[__Pyx_div_long((__pyx_v_i - 1), 2)]) = (__pyx_v_self->heap[__pyx_v_i]); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":55 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":55 * t = self.heap[(i-1)//2] * self.heap[(i-1)//2] = self.heap[i] * self.heap[i] = t # <<<<<<<<<<<<<< @@ -1333,7 +1329,7 @@ */ (__pyx_v_self->heap[__pyx_v_i]) = __pyx_v_t; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":56 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":56 * self.heap[(i-1)//2] = self.heap[i] * self.heap[i] = t * i = (i-1)//2 # <<<<<<<<<<<<<< @@ -1355,7 +1351,7 @@ return __pyx_r; } -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":58 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":58 * i = (i-1)//2 * * cdef heapitem heappeek(heap* self): # <<<<<<<<<<<<<< @@ -1367,7 +1363,7 @@ struct __pyx_t_5scipy_7spatial_7ckdtree_heapitem __pyx_r; __Pyx_RefNannySetupContext("heappeek"); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":59 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":59 * * cdef heapitem heappeek(heap* self): * return self.heap[0] # <<<<<<<<<<<<<< @@ -1382,7 +1378,7 @@ return __pyx_r; } -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":61 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":61 * return self.heap[0] * * cdef heapremove(heap* self): # <<<<<<<<<<<<<< @@ -1404,7 +1400,7 @@ int __pyx_t_5; __Pyx_RefNannySetupContext("heapremove"); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":65 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":65 * cdef int i, j, k, l * * self.heap[0] = self.heap[self.n-1] # <<<<<<<<<<<<<< @@ -1413,7 +1409,7 @@ */ (__pyx_v_self->heap[0]) = (__pyx_v_self->heap[(__pyx_v_self->n - 1)]); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":66 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":66 * * self.heap[0] = self.heap[self.n-1] * self.n -= 1 # <<<<<<<<<<<<<< @@ -1422,7 +1418,7 @@ */ __pyx_v_self->n -= 1; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":67 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":67 * self.heap[0] = self.heap[self.n-1] * self.n -= 1 * if self.n < self.space//4 and self.space>40: #FIXME: magic number # <<<<<<<<<<<<<< @@ -1438,7 +1434,7 @@ } if (__pyx_t_3) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":68 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":68 * self.n -= 1 * if self.n < self.space//4 and self.space>40: #FIXME: magic number * heapresize(self,self.space//2+1) # <<<<<<<<<<<<<< @@ -1452,7 +1448,7 @@ } __pyx_L3:; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":70 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":70 * heapresize(self,self.space//2+1) * * i=0 # <<<<<<<<<<<<<< @@ -1461,7 +1457,7 @@ */ __pyx_v_i = 0; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":71 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":71 * * i=0 * j=1 # <<<<<<<<<<<<<< @@ -1470,7 +1466,7 @@ */ __pyx_v_j = 1; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":72 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":72 * i=0 * j=1 * k=2 # <<<<<<<<<<<<<< @@ -1479,7 +1475,7 @@ */ __pyx_v_k = 2; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":73 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":73 * j=1 * k=2 * while ((j self.heap[j].priority or # <<<<<<<<<<<<<< @@ -1504,7 +1500,7 @@ } if (!__pyx_t_2) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":75 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":75 * while ((j self.heap[j].priority or * kn); if (__pyx_t_3) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":76 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":76 * self.heap[i].priority > self.heap[j].priority or * k self.heap[k].priority)): # <<<<<<<<<<<<<< @@ -1532,7 +1528,7 @@ } if (!__pyx_t_3) break; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":77 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":77 * k self.heap[k].priority)): * if kself.heap[k].priority: # <<<<<<<<<<<<<< @@ -1548,7 +1544,7 @@ } if (__pyx_t_5) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":78 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":78 * self.heap[i].priority > self.heap[k].priority)): * if kself.heap[k].priority: * l = k # <<<<<<<<<<<<<< @@ -1560,7 +1556,7 @@ } /*else*/ { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":80 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":80 * l = k * else: * l = j # <<<<<<<<<<<<<< @@ -1571,7 +1567,7 @@ } __pyx_L6:; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":81 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":81 * else: * l = j * t = self.heap[l] # <<<<<<<<<<<<<< @@ -1580,7 +1576,7 @@ */ __pyx_v_t = (__pyx_v_self->heap[__pyx_v_l]); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":82 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":82 * l = j * t = self.heap[l] * self.heap[l] = self.heap[i] # <<<<<<<<<<<<<< @@ -1589,7 +1585,7 @@ */ (__pyx_v_self->heap[__pyx_v_l]) = (__pyx_v_self->heap[__pyx_v_i]); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":83 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":83 * t = self.heap[l] * self.heap[l] = self.heap[i] * self.heap[i] = t # <<<<<<<<<<<<<< @@ -1598,7 +1594,7 @@ */ (__pyx_v_self->heap[__pyx_v_i]) = __pyx_v_t; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":84 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":84 * self.heap[l] = self.heap[i] * self.heap[i] = t * i = l # <<<<<<<<<<<<<< @@ -1607,7 +1603,7 @@ */ __pyx_v_i = __pyx_v_l; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":85 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":85 * self.heap[i] = t * i = l * j = 2*i+1 # <<<<<<<<<<<<<< @@ -1616,7 +1612,7 @@ */ __pyx_v_j = ((2 * __pyx_v_i) + 1); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":86 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":86 * i = l * j = 2*i+1 * k = 2*i+2 # <<<<<<<<<<<<<< @@ -1638,7 +1634,7 @@ return __pyx_r; } -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":88 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":88 * k = 2*i+2 * * cdef heapitem heappop(heap* self): # <<<<<<<<<<<<<< @@ -1652,7 +1648,7 @@ PyObject *__pyx_t_1 = NULL; __Pyx_RefNannySetupContext("heappop"); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":90 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":90 * cdef heapitem heappop(heap* self): * cdef heapitem it * it = heappeek(self) # <<<<<<<<<<<<<< @@ -1661,7 +1657,7 @@ */ __pyx_v_it = __pyx_f_5scipy_7spatial_7ckdtree_heappeek(__pyx_v_self); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":91 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":91 * cdef heapitem it * it = heappeek(self) * heapremove(self) # <<<<<<<<<<<<<< @@ -1672,7 +1668,7 @@ __Pyx_GOTREF(__pyx_t_1); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":92 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":92 * it = heappeek(self) * heapremove(self) * return it # <<<<<<<<<<<<<< @@ -1691,7 +1687,7 @@ return __pyx_r; } -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":99 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":99 * * # utility functions * cdef inline double dmax(double x, double y): # <<<<<<<<<<<<<< @@ -1704,7 +1700,7 @@ int __pyx_t_1; __Pyx_RefNannySetupContext("dmax"); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":100 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":100 * # utility functions * cdef inline double dmax(double x, double y): * if x>y: # <<<<<<<<<<<<<< @@ -1714,7 +1710,7 @@ __pyx_t_1 = (__pyx_v_x > __pyx_v_y); if (__pyx_t_1) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":101 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":101 * cdef inline double dmax(double x, double y): * if x>y: * return x # <<<<<<<<<<<<<< @@ -1727,7 +1723,7 @@ } /*else*/ { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":103 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":103 * return x * else: * return y # <<<<<<<<<<<<<< @@ -1745,7 +1741,7 @@ return __pyx_r; } -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":104 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":104 * else: * return y * cdef inline double dabs(double x): # <<<<<<<<<<<<<< @@ -1758,7 +1754,7 @@ int __pyx_t_1; __Pyx_RefNannySetupContext("dabs"); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":105 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":105 * return y * cdef inline double dabs(double x): * if x>0: # <<<<<<<<<<<<<< @@ -1768,7 +1764,7 @@ __pyx_t_1 = (__pyx_v_x > 0); if (__pyx_t_1) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":106 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":106 * cdef inline double dabs(double x): * if x>0: * return x # <<<<<<<<<<<<<< @@ -1781,7 +1777,7 @@ } /*else*/ { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":108 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":108 * return x * else: * return -x # <<<<<<<<<<<<<< @@ -1799,7 +1795,7 @@ return __pyx_r; } -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":109 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":109 * else: * return -x * cdef inline double _distance_p(double*x,double*y,double p,int k,double upperbound): # <<<<<<<<<<<<<< @@ -1816,7 +1812,7 @@ int __pyx_t_3; __Pyx_RefNannySetupContext("_distance_p"); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":118 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":118 * cdef int i * cdef double r * r = 0 # <<<<<<<<<<<<<< @@ -1825,7 +1821,7 @@ */ __pyx_v_r = 0; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":119 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":119 * cdef double r * r = 0 * if p==infinity: # <<<<<<<<<<<<<< @@ -1835,7 +1831,7 @@ __pyx_t_1 = (__pyx_v_p == __pyx_v_5scipy_7spatial_7ckdtree_infinity); if (__pyx_t_1) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":120 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":120 * r = 0 * if p==infinity: * for i in range(k): # <<<<<<<<<<<<<< @@ -1846,7 +1842,7 @@ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":121 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":121 * if p==infinity: * for i in range(k): * r = dmax(r,dabs(x[i]-y[i])) # <<<<<<<<<<<<<< @@ -1855,7 +1851,7 @@ */ __pyx_v_r = __pyx_f_5scipy_7spatial_7ckdtree_dmax(__pyx_v_r, __pyx_f_5scipy_7spatial_7ckdtree_dabs(((__pyx_v_x[__pyx_v_i]) - (__pyx_v_y[__pyx_v_i])))); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":122 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":122 * for i in range(k): * r = dmax(r,dabs(x[i]-y[i])) * if r>upperbound: # <<<<<<<<<<<<<< @@ -1865,7 +1861,7 @@ __pyx_t_1 = (__pyx_v_r > __pyx_v_upperbound); if (__pyx_t_1) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":123 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":123 * r = dmax(r,dabs(x[i]-y[i])) * if r>upperbound: * return r # <<<<<<<<<<<<<< @@ -1881,7 +1877,7 @@ goto __pyx_L3; } - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":124 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":124 * if r>upperbound: * return r * elif p==1: # <<<<<<<<<<<<<< @@ -1891,7 +1887,7 @@ __pyx_t_1 = (__pyx_v_p == 1); if (__pyx_t_1) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":125 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":125 * return r * elif p==1: * for i in range(k): # <<<<<<<<<<<<<< @@ -1902,7 +1898,7 @@ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":126 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":126 * elif p==1: * for i in range(k): * r += dabs(x[i]-y[i]) # <<<<<<<<<<<<<< @@ -1911,7 +1907,7 @@ */ __pyx_v_r += __pyx_f_5scipy_7spatial_7ckdtree_dabs(((__pyx_v_x[__pyx_v_i]) - (__pyx_v_y[__pyx_v_i]))); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":127 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":127 * for i in range(k): * r += dabs(x[i]-y[i]) * if r>upperbound: # <<<<<<<<<<<<<< @@ -1921,7 +1917,7 @@ __pyx_t_1 = (__pyx_v_r > __pyx_v_upperbound); if (__pyx_t_1) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":128 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":128 * r += dabs(x[i]-y[i]) * if r>upperbound: * return r # <<<<<<<<<<<<<< @@ -1938,7 +1934,7 @@ } /*else*/ { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":130 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":130 * return r * else: * for i in range(k): # <<<<<<<<<<<<<< @@ -1949,7 +1945,7 @@ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":131 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":131 * else: * for i in range(k): * r += dabs(x[i]-y[i])**p # <<<<<<<<<<<<<< @@ -1958,7 +1954,7 @@ */ __pyx_v_r += pow(__pyx_f_5scipy_7spatial_7ckdtree_dabs(((__pyx_v_x[__pyx_v_i]) - (__pyx_v_y[__pyx_v_i]))), __pyx_v_p); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":132 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":132 * for i in range(k): * r += dabs(x[i]-y[i])**p * if r>upperbound: # <<<<<<<<<<<<<< @@ -1968,7 +1964,7 @@ __pyx_t_1 = (__pyx_v_r > __pyx_v_upperbound); if (__pyx_t_1) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":133 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":133 * r += dabs(x[i]-y[i])**p * if r>upperbound: * return r # <<<<<<<<<<<<<< @@ -1984,7 +1980,7 @@ } __pyx_L3:; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":134 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":134 * if r>upperbound: * return r * return r # <<<<<<<<<<<<<< @@ -2000,16 +1996,15 @@ return __pyx_r; } -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":195 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":207 * cdef object indices * cdef np.int32_t* raw_indices * def __init__(cKDTree self, data, int leafsize=10): # <<<<<<<<<<<<<< - * """Construct a kd-tree. - * + * cdef np.ndarray[double, ndim=2] inner_data + * cdef np.ndarray[double, ndim=1] inner_maxes */ static int __pyx_pf_5scipy_7spatial_7ckdtree_7cKDTree___init__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ -static char __pyx_doc_5scipy_7spatial_7ckdtree_7cKDTree___init__[] = "Construct a kd-tree.\n\n Parameters:\n ===========\n\n data : array-like, shape (n,m)\n The n data points of dimension mto be indexed. This array is \n not copied unless this is necessary to produce a contiguous \n array of doubles, and so modifying this data will result in \n bogus results.\n leafsize : positive integer\n The number of points at which the algorithm switches over to\n brute-force.\n "; static int __pyx_pf_5scipy_7spatial_7ckdtree_7cKDTree___init__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { PyObject *__pyx_v_data = 0; int __pyx_v_leafsize; @@ -2071,18 +2066,18 @@ } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "__init__") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 195; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "__init__") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 207; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } __pyx_v_data = values[0]; if (values[1]) { - __pyx_v_leafsize = __Pyx_PyInt_AsInt(values[1]); if (unlikely((__pyx_v_leafsize == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 195; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_leafsize = __Pyx_PyInt_AsInt(values[1]); if (unlikely((__pyx_v_leafsize == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 207; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } else { __pyx_v_leafsize = ((int)10); } } else { __pyx_v_leafsize = ((int)10); switch (PyTuple_GET_SIZE(__pyx_args)) { - case 2: __pyx_v_leafsize = __Pyx_PyInt_AsInt(PyTuple_GET_ITEM(__pyx_args, 1)); if (unlikely((__pyx_v_leafsize == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 195; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + case 2: __pyx_v_leafsize = __Pyx_PyInt_AsInt(PyTuple_GET_ITEM(__pyx_args, 1)); if (unlikely((__pyx_v_leafsize == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 207; __pyx_clineno = __LINE__; goto __pyx_L3_error;} case 1: __pyx_v_data = PyTuple_GET_ITEM(__pyx_args, 0); break; default: goto __pyx_L5_argtuple_error; @@ -2090,7 +2085,7 @@ } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; - __Pyx_RaiseArgtupleInvalid("__init__", 0, 1, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 195; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("__init__", 0, 1, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 207; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_L3_error:; __Pyx_AddTraceback("scipy.spatial.ckdtree.cKDTree.__init__"); return -1; @@ -2106,33 +2101,33 @@ __pyx_bstruct_inner_mins.buf = NULL; __pyx_bstruct_inner_indices.buf = NULL; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":214 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":212 * cdef np.ndarray[double, ndim=1] inner_mins * cdef np.ndarray[np.int32_t, ndim=1] inner_indices * self.data = np.ascontiguousarray(data,dtype=np.float) # <<<<<<<<<<<<<< * self.n, self.m = np.shape(self.data) * self.leafsize = leafsize */ - __pyx_t_1 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); 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__pyx_lineno = 221; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PyObject_Call(__pyx_t_3, __pyx_t_5, NULL); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 219; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; @@ -2377,14 +2372,14 @@ ((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->indices = __pyx_t_9; __pyx_t_9 = 0; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":223 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":221 * self.indices = np.ascontiguousarray(np.arange(self.n,dtype=np.int32)) * * inner_data = self.data # <<<<<<<<<<<<<< * self.raw_data = inner_data.data * inner_maxes = self.maxes */ - if (!(likely(((((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->data) == Py_None) || likely(__Pyx_TypeTest(((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->data, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 223; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->data) == Py_None) || likely(__Pyx_TypeTest(((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->data, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 221; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_10 = ((PyArrayObject *)((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->data); { __Pyx_BufFmt_StackElem __pyx_stack[1]; @@ -2401,14 +2396,14 @@ } __pyx_bstride_0_inner_data = __pyx_bstruct_inner_data.strides[0]; __pyx_bstride_1_inner_data = __pyx_bstruct_inner_data.strides[1]; __pyx_bshape_0_inner_data = __pyx_bstruct_inner_data.shape[0]; __pyx_bshape_1_inner_data = __pyx_bstruct_inner_data.shape[1]; - if (unlikely(__pyx_t_6 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 223; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__pyx_t_6 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 221; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_10 = 0; __Pyx_INCREF(((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->data); __Pyx_DECREF(((PyObject *)__pyx_v_inner_data)); __pyx_v_inner_data = ((PyArrayObject *)((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->data); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":224 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":222 * * inner_data = self.data * self.raw_data = inner_data.data # <<<<<<<<<<<<<< @@ -2417,14 +2412,14 @@ */ ((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->raw_data = ((double *)__pyx_v_inner_data->data); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":225 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":223 * inner_data = self.data * self.raw_data = inner_data.data * inner_maxes = self.maxes # <<<<<<<<<<<<<< * self.raw_maxes = inner_maxes.data * inner_mins = self.mins */ - if (!(likely(((((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->maxes) == Py_None) || likely(__Pyx_TypeTest(((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->maxes, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 225; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->maxes) == Py_None) || likely(__Pyx_TypeTest(((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->maxes, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 223; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_14 = ((PyArrayObject *)((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->maxes); { __Pyx_BufFmt_StackElem __pyx_stack[1]; @@ -2441,14 +2436,14 @@ } __pyx_bstride_0_inner_maxes = __pyx_bstruct_inner_maxes.strides[0]; __pyx_bshape_0_inner_maxes = __pyx_bstruct_inner_maxes.shape[0]; - if (unlikely(__pyx_t_6 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 225; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__pyx_t_6 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 223; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_14 = 0; __Pyx_INCREF(((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->maxes); 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__pyx_lineno = 227; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->mins) == Py_None) || likely(__Pyx_TypeTest(((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->mins, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 225; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_15 = ((PyArrayObject *)((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->mins); { __Pyx_BufFmt_StackElem __pyx_stack[1]; @@ -2481,14 +2476,14 @@ } __pyx_bstride_0_inner_mins = __pyx_bstruct_inner_mins.strides[0]; __pyx_bshape_0_inner_mins = __pyx_bstruct_inner_mins.shape[0]; - if (unlikely(__pyx_t_6 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 227; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__pyx_t_6 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 225; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_15 = 0; __Pyx_INCREF(((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->mins); 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__pyx_lineno = 229; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->indices) == Py_None) || likely(__Pyx_TypeTest(((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->indices, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 227; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_16 = ((PyArrayObject *)((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->indices); { __Pyx_BufFmt_StackElem __pyx_stack[1]; @@ -2521,14 +2516,14 @@ } __pyx_bstride_0_inner_indices = __pyx_bstruct_inner_indices.strides[0]; __pyx_bshape_0_inner_indices = __pyx_bstruct_inner_indices.shape[0]; - if (unlikely(__pyx_t_6 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 229; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__pyx_t_6 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 227; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_16 = 0; __Pyx_INCREF(((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->indices); __Pyx_DECREF(((PyObject *)__pyx_v_inner_indices)); __pyx_v_inner_indices = ((PyArrayObject *)((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->indices); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":230 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":228 * self.raw_mins = inner_mins.data * inner_indices = self.indices * self.raw_indices = inner_indices.data # <<<<<<<<<<<<<< @@ -2537,7 +2532,7 @@ */ ((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->raw_indices = ((__pyx_t_5numpy_int32_t *)__pyx_v_inner_indices->data); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":232 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":230 * self.raw_indices = inner_indices.data * * self.tree = self.__build(0, self.n, self.raw_maxes, self.raw_mins) # <<<<<<<<<<<<<< @@ -2581,7 +2576,7 @@ return __pyx_r; } -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":234 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":232 * self.tree = self.__build(0, self.n, self.raw_maxes, self.raw_mins) * * cdef innernode* __build(cKDTree self, int start_idx, int end_idx, double* maxes, double* mins): # <<<<<<<<<<<<<< @@ -2611,7 +2606,7 @@ __Pyx_RefNannySetupContext("__build"); 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- /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":243 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":241 * n = stdlib.malloc(sizeof(leafnode)) * n.split_dim = -1 * n.start_idx = start_idx # <<<<<<<<<<<<<< @@ -2648,7 +2643,7 @@ */ __pyx_v_n->start_idx = __pyx_v_start_idx; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":244 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":242 * n.split_dim = -1 * n.start_idx = start_idx * n.end_idx = end_idx # <<<<<<<<<<<<<< @@ -2657,7 +2652,7 @@ */ __pyx_v_n->end_idx = __pyx_v_end_idx; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":245 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":243 * n.start_idx = start_idx * n.end_idx = end_idx * return n # <<<<<<<<<<<<<< @@ -2670,7 +2665,7 @@ } /*else*/ { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":247 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":245 * return n * else: * d = 0 # <<<<<<<<<<<<<< @@ -2679,7 +2674,7 @@ */ __pyx_v_d = 0; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":248 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":246 * else: * d = 0 * size = 0 # <<<<<<<<<<<<<< @@ -2688,7 +2683,7 @@ */ __pyx_v_size = 0; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":249 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":247 * d = 0 * size = 0 * for i in range(self.m): # <<<<<<<<<<<<<< @@ -2699,7 +2694,7 @@ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":250 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":248 * size = 0 * for i in range(self.m): * if maxes[i]-mins[i] > size: # <<<<<<<<<<<<<< @@ -2709,7 +2704,7 @@ __pyx_t_1 = (((__pyx_v_maxes[__pyx_v_i]) - (__pyx_v_mins[__pyx_v_i])) > __pyx_v_size); if (__pyx_t_1) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":251 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":249 * for i in range(self.m): * if maxes[i]-mins[i] > size: * d = i # <<<<<<<<<<<<<< @@ -2718,7 +2713,7 @@ */ __pyx_v_d = __pyx_v_i; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":252 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":250 * if maxes[i]-mins[i] > size: * d = i * size = maxes[i]-mins[i] # <<<<<<<<<<<<<< @@ -2731,7 +2726,7 @@ __pyx_L6:; } - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":253 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":251 * d = i * size = maxes[i]-mins[i] * maxval = maxes[d] # <<<<<<<<<<<<<< @@ -2740,7 +2735,7 @@ */ __pyx_v_maxval = (__pyx_v_maxes[__pyx_v_d]); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":254 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":252 * size = maxes[i]-mins[i] * maxval = maxes[d] * minval = mins[d] # <<<<<<<<<<<<<< @@ -2749,7 +2744,7 @@ */ __pyx_v_minval = (__pyx_v_mins[__pyx_v_d]); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":255 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":253 * maxval = maxes[d] * minval = mins[d] * if maxval==minval: # <<<<<<<<<<<<<< @@ -2759,7 +2754,7 @@ __pyx_t_1 = (__pyx_v_maxval == __pyx_v_minval); if (__pyx_t_1) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":257 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":255 * if maxval==minval: * # all points are identical; warn user? * n = stdlib.malloc(sizeof(leafnode)) # <<<<<<<<<<<<<< @@ -2768,7 +2763,7 @@ */ __pyx_v_n = ((struct __pyx_t_5scipy_7spatial_7ckdtree_leafnode *)malloc((sizeof(struct __pyx_t_5scipy_7spatial_7ckdtree_leafnode)))); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":258 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":256 * # all points are identical; warn user? * n = stdlib.malloc(sizeof(leafnode)) * n.split_dim = -1 # <<<<<<<<<<<<<< @@ -2777,7 +2772,7 @@ */ __pyx_v_n->split_dim = -1; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":259 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":257 * n = stdlib.malloc(sizeof(leafnode)) * n.split_dim = -1 * n.start_idx = start_idx # <<<<<<<<<<<<<< @@ -2786,7 +2781,7 @@ */ __pyx_v_n->start_idx = __pyx_v_start_idx; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":260 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":258 * n.split_dim = -1 * n.start_idx = start_idx * n.end_idx = end_idx # <<<<<<<<<<<<<< @@ -2795,7 +2790,7 @@ */ __pyx_v_n->end_idx = __pyx_v_end_idx; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":261 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":259 * n.start_idx = start_idx * n.end_idx = end_idx * return n # <<<<<<<<<<<<<< @@ -2808,7 +2803,7 @@ } __pyx_L7:; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":263 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":261 * return n * * split = (maxval+minval)/2 # <<<<<<<<<<<<<< @@ -2817,7 +2812,7 @@ */ __pyx_v_split = ((__pyx_v_maxval + __pyx_v_minval) / 2); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":265 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":263 * split = (maxval+minval)/2 * * p = start_idx # <<<<<<<<<<<<<< @@ -2826,7 +2821,7 @@ */ __pyx_v_p = __pyx_v_start_idx; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":266 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":264 * * p = start_idx * q = end_idx-1 # <<<<<<<<<<<<<< @@ -2835,7 +2830,7 @@ */ __pyx_v_q = (__pyx_v_end_idx - 1); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":267 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":265 * p = start_idx * q = end_idx-1 * while p<=q: # <<<<<<<<<<<<<< @@ -2846,7 +2841,7 @@ __pyx_t_1 = (__pyx_v_p <= __pyx_v_q); if (!__pyx_t_1) break; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":268 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":266 * q = end_idx-1 * while p<=q: * if self.raw_data[self.raw_indices[p]*self.m+d]raw_data[(((__pyx_v_self->raw_indices[__pyx_v_p]) * __pyx_v_self->m) + __pyx_v_d)]) < __pyx_v_split); if (__pyx_t_1) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":269 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":267 * while p<=q: * if self.raw_data[self.raw_indices[p]*self.m+d]=split: # <<<<<<<<<<<<<< @@ -2877,7 +2872,7 @@ __pyx_t_1 = ((__pyx_v_self->raw_data[(((__pyx_v_self->raw_indices[__pyx_v_q]) * __pyx_v_self->m) + __pyx_v_d)]) >= __pyx_v_split); if (__pyx_t_1) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":271 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":269 * p+=1 * elif self.raw_data[self.raw_indices[q]*self.m+d]>=split: * q-=1 # <<<<<<<<<<<<<< @@ -2889,7 +2884,7 @@ } /*else*/ { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":273 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":271 * q-=1 * else: * t = self.raw_indices[p] # <<<<<<<<<<<<<< @@ -2898,7 +2893,7 @@ */ __pyx_v_t = (__pyx_v_self->raw_indices[__pyx_v_p]); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":274 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":272 * else: * t = self.raw_indices[p] * self.raw_indices[p] = self.raw_indices[q] # <<<<<<<<<<<<<< @@ -2907,7 +2902,7 @@ */ (__pyx_v_self->raw_indices[__pyx_v_p]) = (__pyx_v_self->raw_indices[__pyx_v_q]); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":275 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":273 * t = self.raw_indices[p] * self.raw_indices[p] = self.raw_indices[q] * self.raw_indices[q] = t # <<<<<<<<<<<<<< @@ -2916,7 +2911,7 @@ */ (__pyx_v_self->raw_indices[__pyx_v_q]) = __pyx_v_t; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":276 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":274 * self.raw_indices[p] = self.raw_indices[q] * self.raw_indices[q] = t * p+=1 # <<<<<<<<<<<<<< @@ -2925,7 +2920,7 @@ */ __pyx_v_p += 1; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":277 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":275 * self.raw_indices[q] = t * p+=1 * q-=1 # <<<<<<<<<<<<<< @@ -2937,7 +2932,7 @@ __pyx_L10:; } - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":280 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":278 * * # slide midpoint if necessary * if p==start_idx: # <<<<<<<<<<<<<< @@ -2947,7 +2942,7 @@ __pyx_t_1 = (__pyx_v_p == __pyx_v_start_idx); if (__pyx_t_1) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":282 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":280 * if p==start_idx: * # no points less than split * j = start_idx # <<<<<<<<<<<<<< @@ -2956,7 +2951,7 @@ */ __pyx_v_j = __pyx_v_start_idx; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":283 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":281 * # no points less than split * j = start_idx * split = self.raw_data[self.raw_indices[j]*self.m+d] # <<<<<<<<<<<<<< @@ -2965,7 +2960,7 @@ */ __pyx_v_split = (__pyx_v_self->raw_data[(((__pyx_v_self->raw_indices[__pyx_v_j]) * __pyx_v_self->m) + __pyx_v_d)]); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":284 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":282 * j = start_idx * split = self.raw_data[self.raw_indices[j]*self.m+d] * for i in range(start_idx+1, end_idx): # <<<<<<<<<<<<<< @@ -2976,7 +2971,7 @@ for (__pyx_t_3 = (__pyx_v_start_idx + 1); __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":285 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":283 * split = self.raw_data[self.raw_indices[j]*self.m+d] * for i in range(start_idx+1, end_idx): * if self.raw_data[self.raw_indices[i]*self.m+d]raw_data[(((__pyx_v_self->raw_indices[__pyx_v_i]) * __pyx_v_self->m) + __pyx_v_d)]) < __pyx_v_split); if (__pyx_t_1) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":286 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":284 * for i in range(start_idx+1, end_idx): * if self.raw_data[self.raw_indices[i]*self.m+d]raw_indices[__pyx_v_start_idx]); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":289 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":287 * split = self.raw_data[self.raw_indices[j]*self.m+d] * t = self.raw_indices[start_idx] * self.raw_indices[start_idx] = self.raw_indices[j] # <<<<<<<<<<<<<< @@ -3026,7 +3021,7 @@ */ (__pyx_v_self->raw_indices[__pyx_v_start_idx]) = (__pyx_v_self->raw_indices[__pyx_v_j]); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":290 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":288 * t = self.raw_indices[start_idx] * self.raw_indices[start_idx] = self.raw_indices[j] * self.raw_indices[j] = t # <<<<<<<<<<<<<< @@ -3035,7 +3030,7 @@ */ (__pyx_v_self->raw_indices[__pyx_v_j]) = __pyx_v_t; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":291 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":289 * self.raw_indices[start_idx] = self.raw_indices[j] * self.raw_indices[j] = t * p = start_idx+1 # <<<<<<<<<<<<<< @@ -3044,7 +3039,7 @@ */ __pyx_v_p = (__pyx_v_start_idx + 1); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":292 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":290 * self.raw_indices[j] = t * p = start_idx+1 * q = start_idx # <<<<<<<<<<<<<< @@ -3055,7 +3050,7 @@ goto __pyx_L11; } - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":293 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":291 * p = start_idx+1 * q = start_idx * elif p==end_idx: # <<<<<<<<<<<<<< @@ -3065,7 +3060,7 @@ __pyx_t_1 = (__pyx_v_p == __pyx_v_end_idx); if (__pyx_t_1) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":295 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":293 * elif p==end_idx: * # no points greater than split * j = end_idx-1 # <<<<<<<<<<<<<< @@ -3074,7 +3069,7 @@ */ __pyx_v_j = (__pyx_v_end_idx - 1); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":296 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":294 * # no points greater than split * j = end_idx-1 * split = self.raw_data[self.raw_indices[j]*self.m+d] # <<<<<<<<<<<<<< @@ -3083,7 +3078,7 @@ */ __pyx_v_split = (__pyx_v_self->raw_data[(((__pyx_v_self->raw_indices[__pyx_v_j]) * __pyx_v_self->m) + __pyx_v_d)]); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":297 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":295 * j = end_idx-1 * split = self.raw_data[self.raw_indices[j]*self.m+d] * for i in range(start_idx, end_idx-1): # <<<<<<<<<<<<<< @@ -3094,7 +3089,7 @@ for (__pyx_t_2 = __pyx_v_start_idx; __pyx_t_2 < __pyx_t_4; __pyx_t_2+=1) { __pyx_v_i = __pyx_t_2; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":298 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":296 * split = self.raw_data[self.raw_indices[j]*self.m+d] * for i in range(start_idx, end_idx-1): * if self.raw_data[self.raw_indices[i]*self.m+d]>split: # <<<<<<<<<<<<<< @@ -3104,7 +3099,7 @@ __pyx_t_1 = ((__pyx_v_self->raw_data[(((__pyx_v_self->raw_indices[__pyx_v_i]) * __pyx_v_self->m) + __pyx_v_d)]) > __pyx_v_split); if (__pyx_t_1) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":299 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":297 * for i in range(start_idx, end_idx-1): * if self.raw_data[self.raw_indices[i]*self.m+d]>split: * j = i # <<<<<<<<<<<<<< @@ -3113,7 +3108,7 @@ */ __pyx_v_j = __pyx_v_i; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":300 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":298 * if self.raw_data[self.raw_indices[i]*self.m+d]>split: * j = i * split = self.raw_data[self.raw_indices[j]*self.m+d] # <<<<<<<<<<<<<< @@ -3126,7 +3121,7 @@ __pyx_L17:; } - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":301 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":299 * j = i * split = self.raw_data[self.raw_indices[j]*self.m+d] * t = self.raw_indices[end_idx-1] # <<<<<<<<<<<<<< @@ -3135,7 +3130,7 @@ */ __pyx_v_t = (__pyx_v_self->raw_indices[(__pyx_v_end_idx - 1)]); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":302 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":300 * split = self.raw_data[self.raw_indices[j]*self.m+d] * t = self.raw_indices[end_idx-1] * self.raw_indices[end_idx-1] = self.raw_indices[j] # <<<<<<<<<<<<<< @@ -3144,7 +3139,7 @@ */ (__pyx_v_self->raw_indices[(__pyx_v_end_idx - 1)]) = (__pyx_v_self->raw_indices[__pyx_v_j]); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":303 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":301 * t = self.raw_indices[end_idx-1] * self.raw_indices[end_idx-1] = self.raw_indices[j] * self.raw_indices[j] = t # <<<<<<<<<<<<<< @@ -3153,7 +3148,7 @@ */ (__pyx_v_self->raw_indices[__pyx_v_j]) = __pyx_v_t; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":304 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":302 * self.raw_indices[end_idx-1] = self.raw_indices[j] * self.raw_indices[j] = t * p = end_idx-1 # <<<<<<<<<<<<<< @@ -3162,7 +3157,7 @@ */ __pyx_v_p = (__pyx_v_end_idx - 1); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":305 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":303 * self.raw_indices[j] = t * p = end_idx-1 * q = end_idx-2 # <<<<<<<<<<<<<< @@ -3174,7 +3169,7 @@ } __pyx_L11:; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":308 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":306 * * # construct new node representation * ni = stdlib.malloc(sizeof(innernode)) # <<<<<<<<<<<<<< @@ -3183,7 +3178,7 @@ */ __pyx_v_ni = ((struct __pyx_t_5scipy_7spatial_7ckdtree_innernode *)malloc((sizeof(struct __pyx_t_5scipy_7spatial_7ckdtree_innernode)))); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":310 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":308 * ni = stdlib.malloc(sizeof(innernode)) * * mids = stdlib.malloc(sizeof(double)*self.m) # <<<<<<<<<<<<<< @@ -3192,7 +3187,7 @@ */ __pyx_v_mids = ((double *)malloc(((sizeof(double)) * __pyx_v_self->m))); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":311 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":309 * * mids = stdlib.malloc(sizeof(double)*self.m) * for i in range(self.m): # <<<<<<<<<<<<<< @@ -3203,7 +3198,7 @@ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":312 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":310 * mids = stdlib.malloc(sizeof(double)*self.m) * for i in range(self.m): * mids[i] = maxes[i] # <<<<<<<<<<<<<< @@ -3213,7 +3208,7 @@ (__pyx_v_mids[__pyx_v_i]) = (__pyx_v_maxes[__pyx_v_i]); } - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":313 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":311 * for i in range(self.m): * mids[i] = maxes[i] * mids[d] = split # <<<<<<<<<<<<<< @@ -3222,7 +3217,7 @@ */ (__pyx_v_mids[__pyx_v_d]) = __pyx_v_split; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":314 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":312 * mids[i] = maxes[i] * mids[d] = split * ni.less = self.__build(start_idx,p,mids,mins) # <<<<<<<<<<<<<< @@ -3231,7 +3226,7 @@ */ __pyx_v_ni->less = ((struct __pyx_vtabstruct_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self->__pyx_vtab)->__build(__pyx_v_self, __pyx_v_start_idx, __pyx_v_p, __pyx_v_mids, __pyx_v_mins); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":316 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":314 * ni.less = self.__build(start_idx,p,mids,mins) * * for i in range(self.m): # <<<<<<<<<<<<<< @@ -3242,7 +3237,7 @@ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":317 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":315 * * for i in range(self.m): * mids[i] = mins[i] # <<<<<<<<<<<<<< @@ -3252,7 +3247,7 @@ (__pyx_v_mids[__pyx_v_i]) = (__pyx_v_mins[__pyx_v_i]); } - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":318 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":316 * for i in range(self.m): * mids[i] = mins[i] * mids[d] = split # <<<<<<<<<<<<<< @@ -3261,7 +3256,7 @@ */ (__pyx_v_mids[__pyx_v_d]) = __pyx_v_split; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":319 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":317 * mids[i] = mins[i] * mids[d] = split * ni.greater = self.__build(p,end_idx,maxes,mids) # <<<<<<<<<<<<<< @@ -3270,7 +3265,7 @@ */ __pyx_v_ni->greater = ((struct __pyx_vtabstruct_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self->__pyx_vtab)->__build(__pyx_v_self, __pyx_v_p, __pyx_v_end_idx, __pyx_v_maxes, __pyx_v_mids); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":321 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":319 * ni.greater = self.__build(p,end_idx,maxes,mids) * * stdlib.free(mids) # <<<<<<<<<<<<<< @@ -3279,7 +3274,7 @@ */ free(__pyx_v_mids); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":323 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":321 * stdlib.free(mids) * * ni.split_dim = d # <<<<<<<<<<<<<< @@ -3288,7 +3283,7 @@ */ __pyx_v_ni->split_dim = __pyx_v_d; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":324 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":322 * * ni.split_dim = d * ni.split = split # <<<<<<<<<<<<<< @@ -3297,7 +3292,7 @@ */ __pyx_v_ni->split = __pyx_v_split; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":326 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":324 * ni.split = split * * return ni # <<<<<<<<<<<<<< @@ -3316,7 +3311,7 @@ return __pyx_r; } -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":328 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":326 * return ni * * cdef __free_tree(cKDTree self, innernode* node): # <<<<<<<<<<<<<< @@ -3331,7 +3326,7 @@ __Pyx_RefNannySetupContext("__free_tree"); __Pyx_INCREF((PyObject *)__pyx_v_self); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":329 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":327 * * cdef __free_tree(cKDTree self, innernode* node): * if node.split_dim!=-1: # <<<<<<<<<<<<<< @@ -3341,32 +3336,32 @@ __pyx_t_1 = (__pyx_v_node->split_dim != -1); if (__pyx_t_1) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":330 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":328 * cdef __free_tree(cKDTree self, innernode* node): * if node.split_dim!=-1: * self.__free_tree(node.less) # <<<<<<<<<<<<<< * self.__free_tree(node.greater) * stdlib.free(node) */ - __pyx_t_2 = ((struct __pyx_vtabstruct_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self->__pyx_vtab)->__free_tree(__pyx_v_self, __pyx_v_node->less); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 330; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = ((struct __pyx_vtabstruct_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self->__pyx_vtab)->__free_tree(__pyx_v_self, __pyx_v_node->less); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 328; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":331 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":329 * if node.split_dim!=-1: * self.__free_tree(node.less) * self.__free_tree(node.greater) # <<<<<<<<<<<<<< * stdlib.free(node) * */ - __pyx_t_2 = ((struct __pyx_vtabstruct_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self->__pyx_vtab)->__free_tree(__pyx_v_self, __pyx_v_node->greater); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 331; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = ((struct __pyx_vtabstruct_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self->__pyx_vtab)->__free_tree(__pyx_v_self, __pyx_v_node->greater); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 329; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; goto __pyx_L3; } __pyx_L3:; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":332 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":330 * self.__free_tree(node.less) * self.__free_tree(node.greater) * stdlib.free(node) # <<<<<<<<<<<<<< @@ -3388,7 +3383,7 @@ return __pyx_r; } -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":334 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":332 * stdlib.free(node) * * def __dealloc__(cKDTree self): # <<<<<<<<<<<<<< @@ -3403,7 +3398,7 @@ __Pyx_RefNannySetupContext("__dealloc__"); __Pyx_INCREF((PyObject *)__pyx_v_self); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":335 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":333 * * def __dealloc__(cKDTree self): * if (self.tree) == 0: # <<<<<<<<<<<<<< @@ -3413,7 +3408,7 @@ __pyx_t_1 = (((int)((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->tree) == 0); if (__pyx_t_1) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":337 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":335 * if (self.tree) == 0: * # should happen only if __init__ was never called * return # <<<<<<<<<<<<<< @@ -3425,14 +3420,14 @@ } __pyx_L5:; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":338 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":336 * # should happen only if __init__ was never called * return * self.__free_tree(self.tree) # <<<<<<<<<<<<<< * * cdef void __query(cKDTree self, */ - __pyx_t_2 = ((struct __pyx_vtabstruct_5scipy_7spatial_7ckdtree_cKDTree *)((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->__pyx_vtab)->__free_tree(((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self), ((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->tree); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 338; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = ((struct __pyx_vtabstruct_5scipy_7spatial_7ckdtree_cKDTree *)((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->__pyx_vtab)->__free_tree(((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self), ((struct __pyx_obj_5scipy_7spatial_7ckdtree_cKDTree *)__pyx_v_self)->tree); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 336; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; @@ -3445,7 +3440,7 @@ __Pyx_RefNannyFinishContext(); } -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":340 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":338 * self.__free_tree(self.tree) * * cdef void __query(cKDTree self, # <<<<<<<<<<<<<< @@ -3483,29 +3478,29 @@ __Pyx_RefNannySetupContext("__query"); __Pyx_INCREF((PyObject *)__pyx_v_self); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":371 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":369 * # distances between the nearest side of the cell and the target * # the head node of the cell * heapcreate(&q,12) # <<<<<<<<<<<<<< * * # priority queue for the nearest neighbors */ - __pyx_t_1 = __pyx_f_5scipy_7spatial_7ckdtree_heapcreate((&__pyx_v_q), 12); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 371; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __pyx_f_5scipy_7spatial_7ckdtree_heapcreate((&__pyx_v_q), 12); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 369; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":376 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":374 * # furthest known neighbor first * # entries are (-distance**p, i) * heapcreate(&neighbors,k) # <<<<<<<<<<<<<< * * # set up first nodeinfo */ - __pyx_t_1 = __pyx_f_5scipy_7spatial_7ckdtree_heapcreate((&__pyx_v_neighbors), __pyx_v_k); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 376; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __pyx_f_5scipy_7spatial_7ckdtree_heapcreate((&__pyx_v_neighbors), __pyx_v_k); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 374; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":379 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":377 * * # set up first nodeinfo * inf = stdlib.malloc(sizeof(nodeinfo)+self.m*sizeof(double)) # <<<<<<<<<<<<<< @@ -3514,7 +3509,7 @@ */ __pyx_v_inf = ((struct __pyx_t_5scipy_7spatial_7ckdtree_nodeinfo *)malloc(((sizeof(struct __pyx_t_5scipy_7spatial_7ckdtree_nodeinfo)) + (__pyx_v_self->m * (sizeof(double)))))); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":380 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":378 * # set up first nodeinfo * inf = stdlib.malloc(sizeof(nodeinfo)+self.m*sizeof(double)) * inf.node = self.tree # <<<<<<<<<<<<<< @@ -3523,7 +3518,7 @@ */ __pyx_v_inf->node = __pyx_v_self->tree; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":381 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":379 * inf = stdlib.malloc(sizeof(nodeinfo)+self.m*sizeof(double)) * inf.node = self.tree * for i in range(self.m): # <<<<<<<<<<<<<< @@ -3534,7 +3529,7 @@ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":382 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":380 * inf.node = self.tree * for i in range(self.m): * inf.side_distances[i] = 0 # <<<<<<<<<<<<<< @@ -3543,7 +3538,7 @@ */ (__pyx_v_inf->side_distances[__pyx_v_i]) = 0; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":383 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":381 * for i in range(self.m): * inf.side_distances[i] = 0 * t = x[i]-self.raw_maxes[i] # <<<<<<<<<<<<<< @@ -3552,7 +3547,7 @@ */ __pyx_v_t = ((__pyx_v_x[__pyx_v_i]) - (__pyx_v_self->raw_maxes[__pyx_v_i])); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":384 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":382 * inf.side_distances[i] = 0 * t = x[i]-self.raw_maxes[i] * if t>inf.side_distances[i]: # <<<<<<<<<<<<<< @@ -3562,7 +3557,7 @@ __pyx_t_4 = (__pyx_v_t > (__pyx_v_inf->side_distances[__pyx_v_i])); if (__pyx_t_4) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":385 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":383 * t = x[i]-self.raw_maxes[i] * if t>inf.side_distances[i]: * inf.side_distances[i] = t # <<<<<<<<<<<<<< @@ -3574,7 +3569,7 @@ } /*else*/ { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":387 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":385 * inf.side_distances[i] = t * else: * t = self.raw_mins[i]-x[i] # <<<<<<<<<<<<<< @@ -3583,7 +3578,7 @@ */ __pyx_v_t = ((__pyx_v_self->raw_mins[__pyx_v_i]) - (__pyx_v_x[__pyx_v_i])); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":388 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":386 * else: * t = self.raw_mins[i]-x[i] * if t>inf.side_distances[i]: # <<<<<<<<<<<<<< @@ -3593,7 +3588,7 @@ __pyx_t_4 = (__pyx_v_t > (__pyx_v_inf->side_distances[__pyx_v_i])); if (__pyx_t_4) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":389 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":387 * t = self.raw_mins[i]-x[i] * if t>inf.side_distances[i]: * inf.side_distances[i] = t # <<<<<<<<<<<<<< @@ -3607,7 +3602,7 @@ } __pyx_L5:; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":390 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":388 * if t>inf.side_distances[i]: * inf.side_distances[i] = t * if p!=1 and p!=infinity: # <<<<<<<<<<<<<< @@ -3623,7 +3618,7 @@ } if (__pyx_t_6) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":391 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":389 * inf.side_distances[i] = t * if p!=1 and p!=infinity: * inf.side_distances[i]=inf.side_distances[i]**p # <<<<<<<<<<<<<< @@ -3636,7 +3631,7 @@ __pyx_L7:; } - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":394 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":392 * * # compute first distance * min_distance = 0. # <<<<<<<<<<<<<< @@ -3645,7 +3640,7 @@ */ __pyx_v_min_distance = 0.0; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":395 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":393 * # compute first distance * min_distance = 0. * for i in range(self.m): # <<<<<<<<<<<<<< @@ -3656,7 +3651,7 @@ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":396 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":394 * min_distance = 0. * for i in range(self.m): * if p==infinity: # <<<<<<<<<<<<<< @@ -3666,7 +3661,7 @@ __pyx_t_6 = (__pyx_v_p == __pyx_v_5scipy_7spatial_7ckdtree_infinity); if (__pyx_t_6) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":397 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":395 * for i in range(self.m): * if p==infinity: * min_distance = dmax(min_distance,inf.side_distances[i]) # <<<<<<<<<<<<<< @@ -3678,7 +3673,7 @@ } /*else*/ { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":399 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":397 * min_distance = dmax(min_distance,inf.side_distances[i]) * else: * min_distance += inf.side_distances[i] # <<<<<<<<<<<<<< @@ -3690,7 +3685,7 @@ __pyx_L10:; } - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":402 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":400 * * # fiddle approximation factor * if eps==0: # <<<<<<<<<<<<<< @@ -3700,7 +3695,7 @@ __pyx_t_6 = (__pyx_v_eps == 0); if (__pyx_t_6) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":403 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":401 * # fiddle approximation factor * if eps==0: * epsfac=1 # <<<<<<<<<<<<<< @@ -3711,7 +3706,7 @@ goto __pyx_L11; } - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":404 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":402 * if eps==0: * epsfac=1 * elif p==infinity: # <<<<<<<<<<<<<< @@ -3721,7 +3716,7 @@ __pyx_t_6 = (__pyx_v_p == __pyx_v_5scipy_7spatial_7ckdtree_infinity); if (__pyx_t_6) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":405 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":403 * epsfac=1 * elif p==infinity: * epsfac = 1/(1+eps) # <<<<<<<<<<<<<< @@ -3731,14 +3726,14 @@ __pyx_t_7 = (1 + __pyx_v_eps); if (unlikely(__pyx_t_7 == 0)) { PyErr_Format(PyExc_ZeroDivisionError, "float division"); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 405; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 403; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_v_epsfac = (1 / __pyx_t_7); goto __pyx_L11; } /*else*/ { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":407 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":405 * epsfac = 1/(1+eps) * else: * epsfac = 1/(1+eps)**p # <<<<<<<<<<<<<< @@ -3748,13 +3743,13 @@ __pyx_t_7 = pow((1 + __pyx_v_eps), __pyx_v_p); if (unlikely(__pyx_t_7 == 0)) { PyErr_Format(PyExc_ZeroDivisionError, "float division"); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 407; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 405; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_v_epsfac = (1 / __pyx_t_7); } __pyx_L11:; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":410 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":408 * * # internally we represent all distances as distance**p * if p!=infinity and distance_upper_bound!=infinity: # <<<<<<<<<<<<<< @@ -3770,7 +3765,7 @@ } if (__pyx_t_5) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":411 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":409 * # internally we represent all distances as distance**p * if p!=infinity and distance_upper_bound!=infinity: * distance_upper_bound = distance_upper_bound**p # <<<<<<<<<<<<<< @@ -3782,7 +3777,7 @@ } __pyx_L12:; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":413 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":411 * distance_upper_bound = distance_upper_bound**p * * while True: # <<<<<<<<<<<<<< @@ -3793,7 +3788,7 @@ __pyx_t_5 = 1; if (!__pyx_t_5) break; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":414 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":412 * * while True: * if inf.node.split_dim==-1: # <<<<<<<<<<<<<< @@ -3803,7 +3798,7 @@ __pyx_t_5 = (__pyx_v_inf->node->split_dim == -1); if (__pyx_t_5) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":415 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":413 * while True: * if inf.node.split_dim==-1: * node = inf.node # <<<<<<<<<<<<<< @@ -3812,7 +3807,7 @@ */ __pyx_v_node = ((struct __pyx_t_5scipy_7spatial_7ckdtree_leafnode *)__pyx_v_inf->node); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":418 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":416 * * # brute-force * for i in range(node.start_idx,node.end_idx): # <<<<<<<<<<<<<< @@ -3823,7 +3818,7 @@ for (__pyx_t_3 = __pyx_v_node->start_idx; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":421 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":419 * d = _distance_p( * self.raw_data+self.raw_indices[i]*self.m, * x,p,self.m,distance_upper_bound) # <<<<<<<<<<<<<< @@ -3832,7 +3827,7 @@ */ __pyx_v_d = __pyx_f_5scipy_7spatial_7ckdtree__distance_p((__pyx_v_self->raw_data + ((__pyx_v_self->raw_indices[__pyx_v_i]) * __pyx_v_self->m)), __pyx_v_x, __pyx_v_p, __pyx_v_self->m, __pyx_v_distance_upper_bound); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":423 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":421 * x,p,self.m,distance_upper_bound) * * if draw_indices[__pyx_v_i]); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":429 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":427 * neighbor.priority = -d * neighbor.contents.intdata = self.raw_indices[i] * heappush(&neighbors,neighbor) # <<<<<<<<<<<<<< * * # adjust upper bound for efficiency */ - __pyx_t_1 = __pyx_f_5scipy_7spatial_7ckdtree_heappush((&__pyx_v_neighbors), __pyx_v_neighbor); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 429; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __pyx_f_5scipy_7spatial_7ckdtree_heappush((&__pyx_v_neighbors), __pyx_v_neighbor); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 427; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":432 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":430 * * # adjust upper bound for efficiency * if neighbors.n==k: # <<<<<<<<<<<<<< @@ -3905,7 +3900,7 @@ __pyx_t_5 = (__pyx_v_neighbors.n == __pyx_v_k); if (__pyx_t_5) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":433 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":431 * # adjust upper bound for efficiency * if neighbors.n==k: * distance_upper_bound = -heappeek(&neighbors).priority # <<<<<<<<<<<<<< @@ -3921,7 +3916,7 @@ __pyx_L18:; } - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":435 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":433 * distance_upper_bound = -heappeek(&neighbors).priority * # done with this node, get another * stdlib.free(inf) # <<<<<<<<<<<<<< @@ -3930,7 +3925,7 @@ */ free(__pyx_v_inf); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":436 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":434 * # done with this node, get another * stdlib.free(inf) * if q.n==0: # <<<<<<<<<<<<<< @@ -3940,7 +3935,7 @@ __pyx_t_5 = (__pyx_v_q.n == 0); if (__pyx_t_5) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":438 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":436 * if q.n==0: * # no more nodes to visit * break # <<<<<<<<<<<<<< @@ -3952,7 +3947,7 @@ } /*else*/ { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":440 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":438 * break * else: * it = heappop(&q) # <<<<<<<<<<<<<< @@ -3961,7 +3956,7 @@ */ __pyx_v_it = __pyx_f_5scipy_7spatial_7ckdtree_heappop((&__pyx_v_q)); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":441 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":439 * else: * it = heappop(&q) * inf = it.contents.ptrdata # <<<<<<<<<<<<<< @@ -3970,7 +3965,7 @@ */ __pyx_v_inf = ((struct __pyx_t_5scipy_7spatial_7ckdtree_nodeinfo *)__pyx_v_it.contents.ptrdata); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":442 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":440 * it = heappop(&q) * inf = it.contents.ptrdata * min_distance = it.priority # <<<<<<<<<<<<<< @@ -3984,7 +3979,7 @@ } /*else*/ { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":444 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":442 * min_distance = it.priority * else: * inode = inf.node # <<<<<<<<<<<<<< @@ -3993,7 +3988,7 @@ */ __pyx_v_inode = ((struct __pyx_t_5scipy_7spatial_7ckdtree_innernode *)__pyx_v_inf->node); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":449 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":447 * # but since the distance_upper_bound decreases, we might get * # here even if the cell's too far * if min_distance>distance_upper_bound*epsfac: # <<<<<<<<<<<<<< @@ -4003,7 +3998,7 @@ __pyx_t_5 = (__pyx_v_min_distance > (__pyx_v_distance_upper_bound * __pyx_v_epsfac)); if (__pyx_t_5) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":451 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":449 * if min_distance>distance_upper_bound*epsfac: * # since this is the nearest cell, we're done, bail out * stdlib.free(inf) # <<<<<<<<<<<<<< @@ -4012,7 +4007,7 @@ */ free(__pyx_v_inf); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":453 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":451 * stdlib.free(inf) * # free all the nodes still on the heap * for i in range(q.n): # <<<<<<<<<<<<<< @@ -4023,7 +4018,7 @@ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":454 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":452 * # free all the nodes still on the heap * for i in range(q.n): * stdlib.free(q.heap[i].contents.ptrdata) # <<<<<<<<<<<<<< @@ -4033,7 +4028,7 @@ free((__pyx_v_q.heap[__pyx_v_i]).contents.ptrdata); } - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":455 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":453 * for i in range(q.n): * stdlib.free(q.heap[i].contents.ptrdata) * break # <<<<<<<<<<<<<< @@ -4045,7 +4040,7 @@ } __pyx_L22:; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":458 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":456 * * # set up children for searching * if x[inode.split_dim]split_dim]) < __pyx_v_inode->split); if (__pyx_t_5) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":459 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":457 * # set up children for searching * if x[inode.split_dim]less; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":460 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":458 * if x[inode.split_dim]greater; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":463 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":461 * else: * near = inode.greater * far = inode.less # <<<<<<<<<<<<<< @@ -4096,7 +4091,7 @@ } __pyx_L25:; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":468 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":466 * # we're going here next, so no point pushing it on the queue * # no need to recompute the distance or the side_distances * inf.node = near # <<<<<<<<<<<<<< @@ -4105,7 +4100,7 @@ */ __pyx_v_inf->node = __pyx_v_near; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":473 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":471 * # on the split value; compute its distance and side_distances * # and push it on the queue if it's near enough * inf2 = stdlib.malloc(sizeof(nodeinfo)+self.m*sizeof(double)) # <<<<<<<<<<<<<< @@ -4114,7 +4109,7 @@ */ __pyx_v_inf2 = ((struct __pyx_t_5scipy_7spatial_7ckdtree_nodeinfo *)malloc(((sizeof(struct __pyx_t_5scipy_7spatial_7ckdtree_nodeinfo)) + (__pyx_v_self->m * (sizeof(double)))))); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":474 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":472 * # and push it on the queue if it's near enough * inf2 = stdlib.malloc(sizeof(nodeinfo)+self.m*sizeof(double)) * it2.contents.ptrdata = inf2 # <<<<<<<<<<<<<< @@ -4123,7 +4118,7 @@ */ __pyx_v_it2.contents.ptrdata = ((char *)__pyx_v_inf2); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":475 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":473 * inf2 = stdlib.malloc(sizeof(nodeinfo)+self.m*sizeof(double)) * it2.contents.ptrdata = inf2 * inf2.node = far # <<<<<<<<<<<<<< @@ -4132,7 +4127,7 @@ */ __pyx_v_inf2->node = __pyx_v_far; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":477 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":475 * inf2.node = far * # most side distances unchanged * for i in range(self.m): # <<<<<<<<<<<<<< @@ -4143,7 +4138,7 @@ for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":478 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":476 * # most side distances unchanged * for i in range(self.m): * inf2.side_distances[i] = inf.side_distances[i] # <<<<<<<<<<<<<< @@ -4153,7 +4148,7 @@ (__pyx_v_inf2->side_distances[__pyx_v_i]) = (__pyx_v_inf->side_distances[__pyx_v_i]); } - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":482 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":480 * # one side distance changes * # we can adjust the minimum distance without recomputing * if p == infinity: # <<<<<<<<<<<<<< @@ -4163,7 +4158,7 @@ __pyx_t_5 = (__pyx_v_p == __pyx_v_5scipy_7spatial_7ckdtree_infinity); if (__pyx_t_5) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":485 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":483 * # we never use side_distances in the l_infinity case * # inf2.side_distances[inode.split_dim] = dabs(inode.split-x[inode.split_dim]) * far_min_distance = dmax(min_distance, dabs(inode.split-x[inode.split_dim])) # <<<<<<<<<<<<<< @@ -4174,7 +4169,7 @@ goto __pyx_L28; } - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":486 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":484 * # inf2.side_distances[inode.split_dim] = dabs(inode.split-x[inode.split_dim]) * far_min_distance = dmax(min_distance, dabs(inode.split-x[inode.split_dim])) * elif p == 1: # <<<<<<<<<<<<<< @@ -4184,7 +4179,7 @@ __pyx_t_5 = (__pyx_v_p == 1); if (__pyx_t_5) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":487 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":485 * far_min_distance = dmax(min_distance, dabs(inode.split-x[inode.split_dim])) * elif p == 1: * inf2.side_distances[inode.split_dim] = dabs(inode.split-x[inode.split_dim]) # <<<<<<<<<<<<<< @@ -4193,7 +4188,7 @@ */ (__pyx_v_inf2->side_distances[__pyx_v_inode->split_dim]) = __pyx_f_5scipy_7spatial_7ckdtree_dabs((__pyx_v_inode->split - (__pyx_v_x[__pyx_v_inode->split_dim]))); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":488 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":486 * elif p == 1: * inf2.side_distances[inode.split_dim] = dabs(inode.split-x[inode.split_dim]) * far_min_distance = min_distance - inf.side_distances[inode.split_dim] + inf2.side_distances[inode.split_dim] # <<<<<<<<<<<<<< @@ -4205,7 +4200,7 @@ } /*else*/ { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":490 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":488 * far_min_distance = min_distance - inf.side_distances[inode.split_dim] + inf2.side_distances[inode.split_dim] * else: * inf2.side_distances[inode.split_dim] = dabs(inode.split-x[inode.split_dim])**p # <<<<<<<<<<<<<< @@ -4214,7 +4209,7 @@ */ (__pyx_v_inf2->side_distances[__pyx_v_inode->split_dim]) = pow(__pyx_f_5scipy_7spatial_7ckdtree_dabs((__pyx_v_inode->split - (__pyx_v_x[__pyx_v_inode->split_dim]))), __pyx_v_p); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":491 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":489 * else: * inf2.side_distances[inode.split_dim] = dabs(inode.split-x[inode.split_dim])**p * far_min_distance = min_distance - inf.side_distances[inode.split_dim] + inf2.side_distances[inode.split_dim] # <<<<<<<<<<<<<< @@ -4225,7 +4220,7 @@ } __pyx_L28:; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":493 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":491 * far_min_distance = min_distance - inf.side_distances[inode.split_dim] + inf2.side_distances[inode.split_dim] * * it2.priority = far_min_distance # <<<<<<<<<<<<<< @@ -4234,7 +4229,7 @@ */ __pyx_v_it2.priority = __pyx_v_far_min_distance; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":497 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":495 * * # far child might be too far, if so, don't bother pushing it * if far_min_distance<=distance_upper_bound*epsfac: # <<<<<<<<<<<<<< @@ -4244,21 +4239,21 @@ __pyx_t_5 = (__pyx_v_far_min_distance <= (__pyx_v_distance_upper_bound * __pyx_v_epsfac)); if (__pyx_t_5) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":498 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":496 * # far child might be too far, if so, don't bother pushing it * if far_min_distance<=distance_upper_bound*epsfac: * heappush(&q,it2) # <<<<<<<<<<<<<< * else: * stdlib.free(inf2) */ - __pyx_t_1 = __pyx_f_5scipy_7spatial_7ckdtree_heappush((&__pyx_v_q), __pyx_v_it2); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 498; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __pyx_f_5scipy_7spatial_7ckdtree_heappush((&__pyx_v_q), __pyx_v_it2); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 496; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; goto __pyx_L29; } /*else*/ { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":500 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":498 * heappush(&q,it2) * else: * stdlib.free(inf2) # <<<<<<<<<<<<<< @@ -4267,7 +4262,7 @@ */ free(__pyx_v_inf2); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":502 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":500 * stdlib.free(inf2) * # just in case * it2.contents.ptrdata = 0 # <<<<<<<<<<<<<< @@ -4282,16 +4277,16 @@ } __pyx_L14_break:; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":505 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":503 * * # fill output arrays with sorted neighbors * for i in range(neighbors.n-1,-1,-1): # <<<<<<<<<<<<<< * neighbor = heappop(&neighbors) # FIXME: neighbors may be realloced * result_indices[i] = neighbor.contents.intdata */ - __pyx_t_1 = PyInt_FromLong((__pyx_v_neighbors.n - 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 505; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyInt_FromLong((__pyx_v_neighbors.n - 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_9 = PyTuple_New(3); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 505; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PyTuple_New(3); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); PyTuple_SET_ITEM(__pyx_t_9, 0, __pyx_t_1); __Pyx_GIVEREF(__pyx_t_1); @@ -4302,13 +4297,13 @@ PyTuple_SET_ITEM(__pyx_t_9, 2, __pyx_int_neg_1); __Pyx_GIVEREF(__pyx_int_neg_1); __pyx_t_1 = 0; - __pyx_t_1 = PyObject_Call(__pyx_builtin_range, __pyx_t_9, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 505; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_Call(__pyx_builtin_range, __pyx_t_9, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; if (PyList_CheckExact(__pyx_t_1) || PyTuple_CheckExact(__pyx_t_1)) { __pyx_t_8 = 0; __pyx_t_9 = __pyx_t_1; __Pyx_INCREF(__pyx_t_9); } else { - __pyx_t_8 = -1; __pyx_t_9 = PyObject_GetIter(__pyx_t_1); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 505; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = -1; __pyx_t_9 = PyObject_GetIter(__pyx_t_1); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); } __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; @@ -4322,16 +4317,16 @@ } else { __pyx_t_1 = PyIter_Next(__pyx_t_9); if (!__pyx_t_1) { - if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 505; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} break; } __Pyx_GOTREF(__pyx_t_1); } - __pyx_t_2 = __Pyx_PyInt_AsInt(__pyx_t_1); if (unlikely((__pyx_t_2 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 505; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = __Pyx_PyInt_AsInt(__pyx_t_1); if (unlikely((__pyx_t_2 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __pyx_v_i = __pyx_t_2; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":506 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":504 * # fill output arrays with sorted neighbors * for i in range(neighbors.n-1,-1,-1): * neighbor = heappop(&neighbors) # FIXME: neighbors may be realloced # <<<<<<<<<<<<<< @@ -4340,7 +4335,7 @@ */ __pyx_v_neighbor = __pyx_f_5scipy_7spatial_7ckdtree_heappop((&__pyx_v_neighbors)); - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":507 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":505 * for i in range(neighbors.n-1,-1,-1): * neighbor = heappop(&neighbors) # FIXME: neighbors may be realloced * result_indices[i] = neighbor.contents.intdata # <<<<<<<<<<<<<< @@ -4349,7 +4344,7 @@ */ (__pyx_v_result_indices[__pyx_v_i]) = __pyx_v_neighbor.contents.intdata; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":508 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":506 * neighbor = heappop(&neighbors) # FIXME: neighbors may be realloced * result_indices[i] = neighbor.contents.intdata * if p==1 or p==infinity: # <<<<<<<<<<<<<< @@ -4365,7 +4360,7 @@ } if (__pyx_t_4) { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":509 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":507 * result_indices[i] = neighbor.contents.intdata * if p==1 or p==infinity: * result_distances[i] = -neighbor.priority # <<<<<<<<<<<<<< @@ -4377,7 +4372,7 @@ } /*else*/ { - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":511 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":509 * result_distances[i] = -neighbor.priority * else: * result_distances[i] = (-neighbor.priority)**(1./p) # <<<<<<<<<<<<<< @@ -4386,7 +4381,7 @@ */ if (unlikely(__pyx_v_p == 0)) { PyErr_Format(PyExc_ZeroDivisionError, "float division"); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 511; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 509; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } (__pyx_v_result_distances[__pyx_v_i]) = pow((-__pyx_v_neighbor.priority), (1.0 / __pyx_v_p)); } @@ -4394,25 +4389,25 @@ } __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":513 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":511 * result_distances[i] = (-neighbor.priority)**(1./p) * * heapdestroy(&q) # <<<<<<<<<<<<<< * heapdestroy(&neighbors) * */ - __pyx_t_9 = __pyx_f_5scipy_7spatial_7ckdtree_heapdestroy((&__pyx_v_q)); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 513; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = __pyx_f_5scipy_7spatial_7ckdtree_heapdestroy((&__pyx_v_q)); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 511; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":514 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":512 * * heapdestroy(&q) * heapdestroy(&neighbors) # <<<<<<<<<<<<<< * * def query(cKDTree self, object x, int k=1, double eps=0, double p=2, */ - __pyx_t_9 = __pyx_f_5scipy_7spatial_7ckdtree_heapdestroy((&__pyx_v_neighbors)); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 514; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = __pyx_f_5scipy_7spatial_7ckdtree_heapdestroy((&__pyx_v_neighbors)); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 512; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; @@ -4426,16 +4421,16 @@ __Pyx_RefNannyFinishContext(); } -/* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":516 +/* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":514 * heapdestroy(&neighbors) * * def query(cKDTree self, object x, int k=1, double eps=0, double p=2, # <<<<<<<<<<<<<< * double distance_upper_bound=infinity): - * """query the kd-tree for nearest neighbors + * """Query the kd-tree for nearest neighbors. */ static PyObject *__pyx_pf_5scipy_7spatial_7ckdtree_7cKDTree_query(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ -static char __pyx_doc_5scipy_7spatial_7ckdtree_7cKDTree_query[] = "query the kd-tree for nearest neighbors\n\n Parameters:\n ===========\n\n x : array-like, last dimension self.m\n An array of points to query.\n k : integer\n The number of nearest neighbors to return.\n eps : nonnegative float\n Return approximate nearest neighbors; the kth returned value \n is guaranteed to be no further than (1+eps) times the \n distance to the real kth nearest neighbor.\n p : float, 1<=p<=infinity\n Which Minkowski p-norm to use. \n 1 is the sum-of-absolute-values \"Manhattan\" distance\n 2 is the usual Euclidean distance\n infinity is the maximum-coordinate-difference distance\n distance_upper_bound : nonnegative float\n Return only neighbors within this distance. This is used to prune\n tree searches, so if you are doing a series of nearest-neighbor\n queries, it may help to supply the distance to the nearest neighbor\n of the most recent point.\n\n Returns:\n ========\n \n d : array of floats\n The distances to the nearest neighbors. \n If x has shape tuple+(self.m,), then d has shape tuple+(k,).\n Missing neighbors are indicated with infinite distances.\n i : array of integers\n The locations of the neighbors in self.data.\n If x has shape tuple+(self.m,), then i has shape tuple+(k,).\n Missing neighbors are indicated with self.n.\n "; +static char __pyx_doc_5scipy_7spatial_7ckdtree_7cKDTree_query[] = "Query the kd-tree for nearest neighbors.\n\n Parameters\n ----------\n x : array_like, last dimension self.m\n An array of points to query.\n k : int\n The number of nearest neighbors to return.\n eps : nonnegative float\n Return approximate nearest neighbors; the kth returned value \n is guaranteed to be no further than (1+eps) times the \n distance to the real kth nearest neighbor.\n p : float, 1<=p<=infinity\n Which Minkowski p-norm to use. \n 1 is the sum-of-absolute-values \"Manhattan\" distance\n 2 is the usual Euclidean distance\n infinity is the maximum-coordinate-difference distance\n distance_upper_bound : nonnegative float\n Return only neighbors within this distance. This is used to prune\n tree searches, so if you are doing a series of nearest-neighbor\n queries, it may help to supply the distance to the nearest neighbor\n of the most recent point.\n\n Returns\n -------\n d : ndarray of floats\n The distances to the nearest neighbors. \n If x has shape tuple+(self.m,), then d has shape tuple+(k,).\n Missing neighbors are indicated with infinite distances.\n i : ndarray of ints\n The locations of the neighbors in self.data.\n If x has shape tuple+(self.m,), then i has shape tuple+(k,).\n Missing neighbors are indicated with self.n.\n\n "; static PyObject *__pyx_pf_5scipy_7spatial_7ckdtree_7cKDTree_query(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { PyObject *__pyx_v_x = 0; int __pyx_v_k; @@ -4525,26 +4520,26 @@ } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "query") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 516; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "query") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 514; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } __pyx_v_x = values[0]; if (values[1]) { - __pyx_v_k = __Pyx_PyInt_AsInt(values[1]); if (unlikely((__pyx_v_k == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 516; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_k = __Pyx_PyInt_AsInt(values[1]); if (unlikely((__pyx_v_k == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 514; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } else { __pyx_v_k = ((int)1); } if (values[2]) { - __pyx_v_eps = __pyx_PyFloat_AsDouble(values[2]); if (unlikely((__pyx_v_eps == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 516; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_eps = __pyx_PyFloat_AsDouble(values[2]); if (unlikely((__pyx_v_eps == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 514; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } else { __pyx_v_eps = ((double)0); } if (values[3]) { - __pyx_v_p = __pyx_PyFloat_AsDouble(values[3]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 516; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_p = __pyx_PyFloat_AsDouble(values[3]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 514; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } else { __pyx_v_p = ((double)2); } if (values[4]) { - __pyx_v_distance_upper_bound = __pyx_PyFloat_AsDouble(values[4]); if (unlikely((__pyx_v_distance_upper_bound == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 517; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __pyx_v_distance_upper_bound = __pyx_PyFloat_AsDouble(values[4]); if (unlikely((__pyx_v_distance_upper_bound == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; 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if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 594; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyTuple_New(2); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 591; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_INCREF(((PyObject *)__pyx_v_ii)); PyTuple_SET_ITEM(__pyx_t_3, 0, ((PyObject *)__pyx_v_ii)); @@ -5410,11 +5405,11 @@ PyTuple_SET_ITEM(__pyx_t_3, 1, __pyx_t_5); __Pyx_GIVEREF(__pyx_t_5); __pyx_t_5 = 0; - __pyx_t_5 = PyObject_Call(__pyx_t_1, __pyx_t_3, NULL); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 594; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = PyObject_Call(__pyx_t_1, __pyx_t_3, NULL); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 591; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyTuple_New(2); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 594; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyTuple_New(2); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 591; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); PyTuple_SET_ITEM(__pyx_t_3, 0, __pyx_t_12); __Pyx_GIVEREF(__pyx_t_12); @@ -5465,7 +5460,7 @@ return __pyx_r; } -/* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":187 +/* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":187 * # experimental exception made for __getbuffer__ and __releasebuffer__ * # -- the details of this may change. * def __getbuffer__(ndarray self, Py_buffer* info, int flags): # <<<<<<<<<<<<<< @@ -5501,7 +5496,7 @@ __Pyx_GIVEREF(__pyx_v_info->obj); __Pyx_INCREF((PyObject *)__pyx_v_self); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":193 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":193 * # of flags * cdef int copy_shape, i, ndim * cdef int endian_detector = 1 # <<<<<<<<<<<<<< @@ -5510,7 +5505,7 @@ */ __pyx_v_endian_detector = 1; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":194 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":194 * cdef int copy_shape, i, ndim * cdef int endian_detector = 1 * cdef bint little_endian = ((&endian_detector)[0] != 0) # <<<<<<<<<<<<<< @@ -5519,7 +5514,7 @@ */ __pyx_v_little_endian = ((((char *)(&__pyx_v_endian_detector))[0]) != 0); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":196 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":196 * cdef bint little_endian = ((&endian_detector)[0] != 0) * * ndim = PyArray_NDIM(self) # <<<<<<<<<<<<<< @@ -5528,7 +5523,7 @@ */ __pyx_v_ndim = PyArray_NDIM(((PyArrayObject *)__pyx_v_self)); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":198 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":198 * ndim = PyArray_NDIM(self) * * if sizeof(npy_intp) != sizeof(Py_ssize_t): # <<<<<<<<<<<<<< @@ -5538,7 +5533,7 @@ __pyx_t_1 = ((sizeof(npy_intp)) != (sizeof(Py_ssize_t))); if (__pyx_t_1) { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":199 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":199 * * if sizeof(npy_intp) != sizeof(Py_ssize_t): * copy_shape = 1 # <<<<<<<<<<<<<< @@ -5550,7 +5545,7 @@ } /*else*/ { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":201 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":201 * copy_shape = 1 * else: * copy_shape = 0 # <<<<<<<<<<<<<< @@ -5561,7 +5556,7 @@ } __pyx_L5:; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":203 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":203 * copy_shape = 0 * * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) # <<<<<<<<<<<<<< @@ -5571,7 +5566,7 @@ __pyx_t_1 = ((__pyx_v_flags & PyBUF_C_CONTIGUOUS) == PyBUF_C_CONTIGUOUS); if (__pyx_t_1) { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":204 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":204 * * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)): # <<<<<<<<<<<<<< @@ -5585,7 +5580,7 @@ } if (__pyx_t_3) { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":205 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":205 * if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)): * raise ValueError(u"ndarray is not C contiguous") # <<<<<<<<<<<<<< @@ -5607,7 +5602,7 @@ } __pyx_L6:; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":207 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":207 * raise ValueError(u"ndarray is not C contiguous") * * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) # <<<<<<<<<<<<<< @@ -5617,7 +5612,7 @@ __pyx_t_3 = ((__pyx_v_flags & PyBUF_F_CONTIGUOUS) == PyBUF_F_CONTIGUOUS); if (__pyx_t_3) { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":208 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":208 * * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)): # <<<<<<<<<<<<<< @@ -5631,7 +5626,7 @@ } if (__pyx_t_2) { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":209 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":209 * if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) * and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)): * raise ValueError(u"ndarray is not Fortran contiguous") # <<<<<<<<<<<<<< @@ -5653,7 +5648,7 @@ } __pyx_L7:; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":211 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":211 * raise ValueError(u"ndarray is not Fortran contiguous") * * info.buf = PyArray_DATA(self) # <<<<<<<<<<<<<< @@ -5662,7 +5657,7 @@ */ __pyx_v_info->buf = PyArray_DATA(((PyArrayObject *)__pyx_v_self)); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":212 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":212 * * info.buf = PyArray_DATA(self) * info.ndim = ndim # <<<<<<<<<<<<<< @@ -5671,7 +5666,7 @@ */ __pyx_v_info->ndim = __pyx_v_ndim; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":213 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":213 * info.buf = PyArray_DATA(self) * info.ndim = ndim * if copy_shape: # <<<<<<<<<<<<<< @@ -5681,7 +5676,7 @@ __pyx_t_6 = __pyx_v_copy_shape; if (__pyx_t_6) { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":216 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":216 * # Allocate new buffer for strides and shape info. This is allocated * # as one block, strides first. * info.strides = stdlib.malloc(sizeof(Py_ssize_t) * ndim * 2) # <<<<<<<<<<<<<< @@ -5690,7 +5685,7 @@ */ __pyx_v_info->strides = ((Py_ssize_t *)malloc((((sizeof(Py_ssize_t)) * __pyx_v_ndim) * 2))); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":217 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":217 * # as one block, strides first. * info.strides = stdlib.malloc(sizeof(Py_ssize_t) * ndim * 2) * info.shape = info.strides + ndim # <<<<<<<<<<<<<< @@ -5699,7 +5694,7 @@ */ __pyx_v_info->shape = (__pyx_v_info->strides + __pyx_v_ndim); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":218 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":218 * info.strides = stdlib.malloc(sizeof(Py_ssize_t) * ndim * 2) * info.shape = info.strides + ndim * for i in range(ndim): # <<<<<<<<<<<<<< @@ -5710,7 +5705,7 @@ for (__pyx_t_7 = 0; __pyx_t_7 < __pyx_t_6; __pyx_t_7+=1) { __pyx_v_i = __pyx_t_7; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":219 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":219 * info.shape = info.strides + ndim * for i in range(ndim): * info.strides[i] = PyArray_STRIDES(self)[i] # <<<<<<<<<<<<<< @@ -5719,7 +5714,7 @@ */ (__pyx_v_info->strides[__pyx_v_i]) = (PyArray_STRIDES(((PyArrayObject *)__pyx_v_self))[__pyx_v_i]); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":220 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":220 * for i in range(ndim): * info.strides[i] = PyArray_STRIDES(self)[i] * info.shape[i] = PyArray_DIMS(self)[i] # <<<<<<<<<<<<<< @@ -5732,7 +5727,7 @@ } /*else*/ { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":222 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":222 * info.shape[i] = PyArray_DIMS(self)[i] * else: * info.strides = PyArray_STRIDES(self) # <<<<<<<<<<<<<< @@ -5741,7 +5736,7 @@ */ __pyx_v_info->strides = ((Py_ssize_t *)PyArray_STRIDES(((PyArrayObject *)__pyx_v_self))); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":223 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":223 * else: * info.strides = PyArray_STRIDES(self) * info.shape = PyArray_DIMS(self) # <<<<<<<<<<<<<< @@ -5752,7 +5747,7 @@ } __pyx_L8:; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":224 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":224 * info.strides = PyArray_STRIDES(self) * info.shape = PyArray_DIMS(self) * info.suboffsets = NULL # <<<<<<<<<<<<<< @@ -5761,7 +5756,7 @@ */ __pyx_v_info->suboffsets = NULL; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":225 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":225 * info.shape = PyArray_DIMS(self) * info.suboffsets = NULL * info.itemsize = PyArray_ITEMSIZE(self) # <<<<<<<<<<<<<< @@ -5770,7 +5765,7 @@ */ __pyx_v_info->itemsize = PyArray_ITEMSIZE(((PyArrayObject *)__pyx_v_self)); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":226 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":226 * info.suboffsets = NULL * info.itemsize = PyArray_ITEMSIZE(self) * info.readonly = not PyArray_ISWRITEABLE(self) # <<<<<<<<<<<<<< @@ -5779,7 +5774,7 @@ */ __pyx_v_info->readonly = (!PyArray_ISWRITEABLE(((PyArrayObject *)__pyx_v_self))); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":229 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":229 * * cdef int t * cdef char* f = NULL # <<<<<<<<<<<<<< @@ -5788,7 +5783,7 @@ */ __pyx_v_f = NULL; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":230 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":230 * cdef int t * cdef char* f = NULL * cdef dtype descr = self.descr # <<<<<<<<<<<<<< @@ -5798,7 +5793,7 @@ __Pyx_INCREF(((PyObject *)((PyArrayObject *)__pyx_v_self)->descr)); __pyx_v_descr = ((PyArrayObject *)__pyx_v_self)->descr; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":234 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":234 * cdef int offset * * cdef bint hasfields = PyDataType_HASFIELDS(descr) # <<<<<<<<<<<<<< @@ -5807,7 +5802,7 @@ */ __pyx_v_hasfields = PyDataType_HASFIELDS(__pyx_v_descr); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":236 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":236 * cdef bint hasfields = PyDataType_HASFIELDS(descr) * * if not hasfields and not copy_shape: # <<<<<<<<<<<<<< @@ -5823,7 +5818,7 @@ } if (__pyx_t_1) { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":238 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":238 * if not hasfields and not copy_shape: * # do not call releasebuffer * info.obj = None # <<<<<<<<<<<<<< @@ -5839,7 +5834,7 @@ } /*else*/ { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":241 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":241 * else: * # need to call releasebuffer * info.obj = self # <<<<<<<<<<<<<< @@ -5854,7 +5849,7 @@ } __pyx_L11:; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":243 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":243 * info.obj = self * * if not hasfields: # <<<<<<<<<<<<<< @@ -5864,7 +5859,7 @@ __pyx_t_1 = (!__pyx_v_hasfields); if (__pyx_t_1) { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":244 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":244 * * if not hasfields: * t = descr.type_num # <<<<<<<<<<<<<< @@ -5873,7 +5868,7 @@ */ __pyx_v_t = __pyx_v_descr->type_num; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":245 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":245 * if not hasfields: * t = descr.type_num * if ((descr.byteorder == '>' and little_endian) or # <<<<<<<<<<<<<< @@ -5888,7 +5883,7 @@ } if (!__pyx_t_2) { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":246 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":246 * t = descr.type_num * if ((descr.byteorder == '>' and little_endian) or * (descr.byteorder == '<' and not little_endian)): # <<<<<<<<<<<<<< @@ -5908,7 +5903,7 @@ } if (__pyx_t_1) { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":247 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":247 * if ((descr.byteorder == '>' and little_endian) or * (descr.byteorder == '<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") # <<<<<<<<<<<<<< @@ -5930,7 +5925,7 @@ } __pyx_L13:; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":248 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":248 * (descr.byteorder == '<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") * if t == NPY_BYTE: f = "b" # <<<<<<<<<<<<<< @@ -5943,7 +5938,7 @@ goto __pyx_L14; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":249 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":249 * raise ValueError(u"Non-native byte order not supported") * if t == NPY_BYTE: f = "b" * elif t == NPY_UBYTE: f = "B" # <<<<<<<<<<<<<< @@ -5956,7 +5951,7 @@ goto __pyx_L14; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":250 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":250 * if t == NPY_BYTE: f = "b" * elif t == NPY_UBYTE: f = "B" * elif t == NPY_SHORT: f = "h" # <<<<<<<<<<<<<< @@ -5969,7 +5964,7 @@ goto __pyx_L14; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":251 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":251 * elif t == NPY_UBYTE: f = "B" * elif t == NPY_SHORT: f = "h" * elif t == NPY_USHORT: f = "H" # <<<<<<<<<<<<<< @@ -5982,7 +5977,7 @@ goto __pyx_L14; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":252 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":252 * elif t == NPY_SHORT: f = "h" * elif t == NPY_USHORT: f = "H" * elif t == NPY_INT: f = "i" # <<<<<<<<<<<<<< @@ -5995,7 +5990,7 @@ goto __pyx_L14; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":253 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":253 * elif t == NPY_USHORT: f = "H" * elif t == NPY_INT: f = "i" * elif t == NPY_UINT: f = "I" # <<<<<<<<<<<<<< @@ -6008,7 +6003,7 @@ goto __pyx_L14; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":254 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":254 * elif t == NPY_INT: f = "i" * elif t == NPY_UINT: f = "I" * elif t == NPY_LONG: f = "l" # <<<<<<<<<<<<<< @@ -6021,7 +6016,7 @@ goto __pyx_L14; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":255 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":255 * elif t == NPY_UINT: f = "I" * elif t == NPY_LONG: f = "l" * elif t == NPY_ULONG: f = "L" # <<<<<<<<<<<<<< @@ -6034,7 +6029,7 @@ goto __pyx_L14; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":256 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":256 * elif t == NPY_LONG: f = "l" * elif t == NPY_ULONG: f = "L" * elif t == NPY_LONGLONG: f = "q" # <<<<<<<<<<<<<< @@ -6047,7 +6042,7 @@ goto __pyx_L14; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":257 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":257 * elif t == NPY_ULONG: f = "L" * elif t == NPY_LONGLONG: f = "q" * elif t == NPY_ULONGLONG: f = "Q" # <<<<<<<<<<<<<< @@ -6060,7 +6055,7 @@ goto __pyx_L14; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":258 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":258 * elif t == NPY_LONGLONG: f = "q" * elif t == NPY_ULONGLONG: f = "Q" * elif t == NPY_FLOAT: f = "f" # <<<<<<<<<<<<<< @@ -6073,7 +6068,7 @@ goto __pyx_L14; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":259 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":259 * elif t == NPY_ULONGLONG: f = "Q" * elif t == NPY_FLOAT: f = "f" * elif t == NPY_DOUBLE: f = "d" # <<<<<<<<<<<<<< @@ -6086,7 +6081,7 @@ goto __pyx_L14; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":260 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":260 * elif t == NPY_FLOAT: f = "f" * elif t == NPY_DOUBLE: f = "d" * elif t == NPY_LONGDOUBLE: f = "g" # <<<<<<<<<<<<<< @@ -6099,7 +6094,7 @@ goto __pyx_L14; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":261 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":261 * elif t == NPY_DOUBLE: f = "d" * elif t == NPY_LONGDOUBLE: f = "g" * elif t == NPY_CFLOAT: f = "Zf" # <<<<<<<<<<<<<< @@ -6112,7 +6107,7 @@ goto __pyx_L14; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":262 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":262 * elif t == NPY_LONGDOUBLE: f = "g" * elif t == NPY_CFLOAT: f = "Zf" * elif t == NPY_CDOUBLE: f = "Zd" # <<<<<<<<<<<<<< @@ -6125,7 +6120,7 @@ goto __pyx_L14; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":263 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":263 * elif t == NPY_CFLOAT: f = "Zf" * elif t == NPY_CDOUBLE: f = "Zd" * elif t == NPY_CLONGDOUBLE: f = "Zg" # <<<<<<<<<<<<<< @@ -6138,7 +6133,7 @@ goto __pyx_L14; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":264 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":264 * elif t == NPY_CDOUBLE: f = "Zd" * elif t == NPY_CLONGDOUBLE: f = "Zg" * elif t == NPY_OBJECT: f = "O" # <<<<<<<<<<<<<< @@ -6152,7 +6147,7 @@ } /*else*/ { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":266 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":266 * elif t == NPY_OBJECT: f = "O" * else: * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) # <<<<<<<<<<<<<< @@ -6178,7 +6173,7 @@ } __pyx_L14:; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":267 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":267 * else: * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) * info.format = f # <<<<<<<<<<<<<< @@ -6187,7 +6182,7 @@ */ __pyx_v_info->format = __pyx_v_f; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":268 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":268 * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) * info.format = f * return # <<<<<<<<<<<<<< @@ -6200,7 +6195,7 @@ } /*else*/ { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":270 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":270 * return * else: * info.format = stdlib.malloc(_buffer_format_string_len) # <<<<<<<<<<<<<< @@ -6209,7 +6204,7 @@ */ __pyx_v_info->format = ((char *)malloc(255)); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":271 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":271 * else: * info.format = stdlib.malloc(_buffer_format_string_len) * info.format[0] = '^' # Native data types, manual alignment # <<<<<<<<<<<<<< @@ -6218,7 +6213,7 @@ */ (__pyx_v_info->format[0]) = '^'; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":272 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":272 * info.format = stdlib.malloc(_buffer_format_string_len) * info.format[0] = '^' # Native data types, manual alignment * offset = 0 # <<<<<<<<<<<<<< @@ -6227,7 +6222,7 @@ */ __pyx_v_offset = 0; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":275 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":275 * f = _util_dtypestring(descr, info.format + 1, * info.format + _buffer_format_string_len, * &offset) # <<<<<<<<<<<<<< @@ -6237,7 +6232,7 @@ __pyx_t_9 = __pyx_f_5numpy__util_dtypestring(__pyx_v_descr, (__pyx_v_info->format + 1), (__pyx_v_info->format + 255), (&__pyx_v_offset)); if (unlikely(__pyx_t_9 == NULL)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 273; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_v_f = __pyx_t_9; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":276 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":276 * info.format + _buffer_format_string_len, * &offset) * f[0] = 0 # Terminate format string # <<<<<<<<<<<<<< @@ -6270,7 +6265,7 @@ return __pyx_r; } -/* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":278 +/* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":278 * f[0] = 0 # Terminate format string * * def __releasebuffer__(ndarray self, Py_buffer* info): # <<<<<<<<<<<<<< @@ -6284,7 +6279,7 @@ __Pyx_RefNannySetupContext("__releasebuffer__"); __Pyx_INCREF((PyObject *)__pyx_v_self); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":279 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":279 * * def __releasebuffer__(ndarray self, Py_buffer* info): * if PyArray_HASFIELDS(self): # <<<<<<<<<<<<<< @@ -6294,7 +6289,7 @@ __pyx_t_1 = PyArray_HASFIELDS(((PyArrayObject *)__pyx_v_self)); if (__pyx_t_1) { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":280 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":280 * def __releasebuffer__(ndarray self, Py_buffer* info): * if PyArray_HASFIELDS(self): * stdlib.free(info.format) # <<<<<<<<<<<<<< @@ -6306,7 +6301,7 @@ } __pyx_L5:; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":281 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":281 * if PyArray_HASFIELDS(self): * stdlib.free(info.format) * if sizeof(npy_intp) != sizeof(Py_ssize_t): # <<<<<<<<<<<<<< @@ -6316,7 +6311,7 @@ __pyx_t_1 = ((sizeof(npy_intp)) != (sizeof(Py_ssize_t))); if (__pyx_t_1) { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":282 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":282 * stdlib.free(info.format) * if sizeof(npy_intp) != sizeof(Py_ssize_t): * stdlib.free(info.strides) # <<<<<<<<<<<<<< @@ -6332,7 +6327,7 @@ __Pyx_RefNannyFinishContext(); } -/* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":755 +/* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":755 * ctypedef npy_cdouble complex_t * * cdef inline object PyArray_MultiIterNew1(a): # <<<<<<<<<<<<<< @@ -6345,7 +6340,7 @@ PyObject *__pyx_t_1 = NULL; __Pyx_RefNannySetupContext("PyArray_MultiIterNew1"); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":756 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":756 * * cdef inline object PyArray_MultiIterNew1(a): * return PyArray_MultiIterNew(1, a) # <<<<<<<<<<<<<< @@ -6371,7 +6366,7 @@ return __pyx_r; } -/* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":758 +/* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":758 * return PyArray_MultiIterNew(1, a) * * cdef inline object PyArray_MultiIterNew2(a, b): # <<<<<<<<<<<<<< @@ -6384,7 +6379,7 @@ PyObject *__pyx_t_1 = NULL; __Pyx_RefNannySetupContext("PyArray_MultiIterNew2"); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":759 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":759 * * cdef inline object PyArray_MultiIterNew2(a, b): * return PyArray_MultiIterNew(2, a, b) # <<<<<<<<<<<<<< @@ -6410,7 +6405,7 @@ return __pyx_r; } -/* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":761 +/* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":761 * return PyArray_MultiIterNew(2, a, b) * * cdef inline object PyArray_MultiIterNew3(a, b, c): # <<<<<<<<<<<<<< @@ -6423,7 +6418,7 @@ PyObject *__pyx_t_1 = NULL; __Pyx_RefNannySetupContext("PyArray_MultiIterNew3"); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":762 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":762 * * cdef inline object PyArray_MultiIterNew3(a, b, c): * return PyArray_MultiIterNew(3, a, b, c) # <<<<<<<<<<<<<< @@ -6449,7 +6444,7 @@ return __pyx_r; } -/* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":764 +/* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":764 * return PyArray_MultiIterNew(3, a, b, c) * * cdef inline object PyArray_MultiIterNew4(a, b, c, d): # <<<<<<<<<<<<<< @@ -6462,7 +6457,7 @@ PyObject *__pyx_t_1 = NULL; __Pyx_RefNannySetupContext("PyArray_MultiIterNew4"); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":765 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":765 * * cdef inline object PyArray_MultiIterNew4(a, b, c, d): * return PyArray_MultiIterNew(4, a, b, c, d) # <<<<<<<<<<<<<< @@ -6488,7 +6483,7 @@ return __pyx_r; } -/* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":767 +/* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":767 * return PyArray_MultiIterNew(4, a, b, c, d) * * cdef inline object PyArray_MultiIterNew5(a, b, c, d, e): # <<<<<<<<<<<<<< @@ -6501,7 +6496,7 @@ PyObject *__pyx_t_1 = NULL; __Pyx_RefNannySetupContext("PyArray_MultiIterNew5"); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":768 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":768 * * cdef inline object PyArray_MultiIterNew5(a, b, c, d, e): * return PyArray_MultiIterNew(5, a, b, c, d, e) # <<<<<<<<<<<<<< @@ -6527,7 +6522,7 @@ return __pyx_r; } -/* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":770 +/* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":770 * return PyArray_MultiIterNew(5, a, b, c, d, e) * * cdef inline char* _util_dtypestring(dtype descr, char* f, char* end, int* offset) except NULL: # <<<<<<<<<<<<<< @@ -6562,7 +6557,7 @@ __pyx_v_new_offset = Py_None; __Pyx_INCREF(Py_None); __pyx_v_t = Py_None; __Pyx_INCREF(Py_None); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":777 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":777 * cdef int delta_offset * cdef tuple i * cdef int endian_detector = 1 # <<<<<<<<<<<<<< @@ -6571,7 +6566,7 @@ */ __pyx_v_endian_detector = 1; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":778 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":778 * cdef tuple i * cdef int endian_detector = 1 * cdef bint little_endian = ((&endian_detector)[0] != 0) # <<<<<<<<<<<<<< @@ -6580,7 +6575,7 @@ */ __pyx_v_little_endian = ((((char *)(&__pyx_v_endian_detector))[0]) != 0); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":781 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":781 * cdef tuple fields * * for childname in descr.names: # <<<<<<<<<<<<<< @@ -6599,7 +6594,7 @@ __pyx_v_childname = __pyx_t_3; __pyx_t_3 = 0; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":782 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":782 * * for childname in descr.names: * fields = descr.fields[childname] # <<<<<<<<<<<<<< @@ -6613,7 +6608,7 @@ __pyx_v_fields = ((PyObject *)__pyx_t_3); __pyx_t_3 = 0; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":783 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":783 * for childname in descr.names: * fields = descr.fields[childname] * child, new_offset = fields # <<<<<<<<<<<<<< @@ -6636,7 +6631,7 @@ {__pyx_filename = __pyx_f[1]; __pyx_lineno = 783; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":785 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":785 * child, new_offset = fields * * if (end - f) - (new_offset - offset[0]) < 15: # <<<<<<<<<<<<<< @@ -6661,7 +6656,7 @@ __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; if (__pyx_t_6) { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":786 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":786 * * if (end - f) - (new_offset - offset[0]) < 15: * raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") # <<<<<<<<<<<<<< @@ -6683,7 +6678,7 @@ } __pyx_L5:; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":788 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":788 * raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") * * if ((child.byteorder == '>' and little_endian) or # <<<<<<<<<<<<<< @@ -6698,7 +6693,7 @@ } if (!__pyx_t_7) { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":789 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":789 * * if ((child.byteorder == '>' and little_endian) or * (child.byteorder == '<' and not little_endian)): # <<<<<<<<<<<<<< @@ -6718,7 +6713,7 @@ } if (__pyx_t_6) { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":790 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":790 * if ((child.byteorder == '>' and little_endian) or * (child.byteorder == '<' and not little_endian)): * raise ValueError(u"Non-native byte order not supported") # <<<<<<<<<<<<<< @@ -6740,7 +6735,7 @@ } __pyx_L6:; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":800 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":800 * * # Output padding bytes * while offset[0] < new_offset: # <<<<<<<<<<<<<< @@ -6757,7 +6752,7 @@ __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; if (!__pyx_t_6) break; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":801 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":801 * # Output padding bytes * while offset[0] < new_offset: * f[0] = 120 # "x"; pad byte # <<<<<<<<<<<<<< @@ -6766,7 +6761,7 @@ */ (__pyx_v_f[0]) = 120; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":802 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":802 * while offset[0] < new_offset: * f[0] = 120 # "x"; pad byte * f += 1 # <<<<<<<<<<<<<< @@ -6775,7 +6770,7 @@ */ __pyx_v_f += 1; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":803 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":803 * f[0] = 120 # "x"; pad byte * f += 1 * offset[0] += 1 # <<<<<<<<<<<<<< @@ -6785,7 +6780,7 @@ (__pyx_v_offset[0]) += 1; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":805 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":805 * offset[0] += 1 * * offset[0] += child.itemsize # <<<<<<<<<<<<<< @@ -6794,7 +6789,7 @@ */ (__pyx_v_offset[0]) += __pyx_v_child->elsize; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":807 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":807 * offset[0] += child.itemsize * * if not PyDataType_HASFIELDS(child): # <<<<<<<<<<<<<< @@ -6804,7 +6799,7 @@ __pyx_t_6 = (!PyDataType_HASFIELDS(__pyx_v_child)); if (__pyx_t_6) { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":808 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":808 * * if not PyDataType_HASFIELDS(child): * t = child.type_num # <<<<<<<<<<<<<< @@ -6817,7 +6812,7 @@ __pyx_v_t = __pyx_t_3; __pyx_t_3 = 0; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":809 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":809 * if not PyDataType_HASFIELDS(child): * t = child.type_num * if end - f < 5: # <<<<<<<<<<<<<< @@ -6827,7 +6822,7 @@ __pyx_t_6 = ((__pyx_v_end - __pyx_v_f) < 5); if (__pyx_t_6) { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":810 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":810 * t = child.type_num * if end - f < 5: * raise RuntimeError(u"Format string allocated too short.") # <<<<<<<<<<<<<< @@ -6849,7 +6844,7 @@ } __pyx_L10:; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":813 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":813 * * # Until ticket #99 is fixed, use integers to avoid warnings * if t == NPY_BYTE: f[0] = 98 #"b" # <<<<<<<<<<<<<< @@ -6868,7 +6863,7 @@ goto __pyx_L11; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":814 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":814 * # Until ticket #99 is fixed, use integers to avoid warnings * if t == NPY_BYTE: f[0] = 98 #"b" * elif t == NPY_UBYTE: f[0] = 66 #"B" # <<<<<<<<<<<<<< @@ -6887,7 +6882,7 @@ goto __pyx_L11; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":815 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":815 * if t == NPY_BYTE: f[0] = 98 #"b" * elif t == NPY_UBYTE: f[0] = 66 #"B" * elif t == NPY_SHORT: f[0] = 104 #"h" # <<<<<<<<<<<<<< @@ -6906,7 +6901,7 @@ goto __pyx_L11; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":816 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":816 * elif t == NPY_UBYTE: f[0] = 66 #"B" * elif t == NPY_SHORT: f[0] = 104 #"h" * elif t == NPY_USHORT: f[0] = 72 #"H" # <<<<<<<<<<<<<< @@ -6925,7 +6920,7 @@ goto __pyx_L11; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":817 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":817 * elif t == NPY_SHORT: f[0] = 104 #"h" * elif t == NPY_USHORT: f[0] = 72 #"H" * elif t == NPY_INT: f[0] = 105 #"i" # <<<<<<<<<<<<<< @@ -6944,7 +6939,7 @@ goto __pyx_L11; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":818 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":818 * elif t == NPY_USHORT: f[0] = 72 #"H" * elif t == NPY_INT: f[0] = 105 #"i" * elif t == NPY_UINT: f[0] = 73 #"I" # <<<<<<<<<<<<<< @@ -6963,7 +6958,7 @@ goto __pyx_L11; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":819 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":819 * elif t == NPY_INT: f[0] = 105 #"i" * elif t == NPY_UINT: f[0] = 73 #"I" * elif t == NPY_LONG: f[0] = 108 #"l" # <<<<<<<<<<<<<< @@ -6982,7 +6977,7 @@ goto __pyx_L11; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":820 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":820 * elif t == NPY_UINT: f[0] = 73 #"I" * elif t == NPY_LONG: f[0] = 108 #"l" * elif t == NPY_ULONG: f[0] = 76 #"L" # <<<<<<<<<<<<<< @@ -7001,7 +6996,7 @@ goto __pyx_L11; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":821 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":821 * elif t == NPY_LONG: f[0] = 108 #"l" * elif t == NPY_ULONG: f[0] = 76 #"L" * elif t == NPY_LONGLONG: f[0] = 113 #"q" # <<<<<<<<<<<<<< @@ -7020,7 +7015,7 @@ goto __pyx_L11; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":822 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":822 * elif t == NPY_ULONG: f[0] = 76 #"L" * elif t == NPY_LONGLONG: f[0] = 113 #"q" * elif t == NPY_ULONGLONG: f[0] = 81 #"Q" # <<<<<<<<<<<<<< @@ -7039,7 +7034,7 @@ goto __pyx_L11; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":823 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":823 * elif t == NPY_LONGLONG: f[0] = 113 #"q" * elif t == NPY_ULONGLONG: f[0] = 81 #"Q" * elif t == NPY_FLOAT: f[0] = 102 #"f" # <<<<<<<<<<<<<< @@ -7058,7 +7053,7 @@ goto __pyx_L11; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":824 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":824 * elif t == NPY_ULONGLONG: f[0] = 81 #"Q" * elif t == NPY_FLOAT: f[0] = 102 #"f" * elif t == NPY_DOUBLE: f[0] = 100 #"d" # <<<<<<<<<<<<<< @@ -7077,7 +7072,7 @@ goto __pyx_L11; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":825 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":825 * elif t == NPY_FLOAT: f[0] = 102 #"f" * elif t == NPY_DOUBLE: f[0] = 100 #"d" * elif t == NPY_LONGDOUBLE: f[0] = 103 #"g" # <<<<<<<<<<<<<< @@ -7096,7 +7091,7 @@ goto __pyx_L11; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":826 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":826 * elif t == NPY_DOUBLE: f[0] = 100 #"d" * elif t == NPY_LONGDOUBLE: f[0] = 103 #"g" * elif t == NPY_CFLOAT: f[0] = 90; f[1] = 102; f += 1 # Zf # <<<<<<<<<<<<<< @@ -7117,7 +7112,7 @@ goto __pyx_L11; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":827 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":827 * elif t == NPY_LONGDOUBLE: f[0] = 103 #"g" * elif t == NPY_CFLOAT: f[0] = 90; f[1] = 102; f += 1 # Zf * elif t == NPY_CDOUBLE: f[0] = 90; f[1] = 100; f += 1 # Zd # <<<<<<<<<<<<<< @@ -7138,7 +7133,7 @@ goto __pyx_L11; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":828 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":828 * elif t == NPY_CFLOAT: f[0] = 90; f[1] = 102; f += 1 # Zf * elif t == NPY_CDOUBLE: f[0] = 90; f[1] = 100; f += 1 # Zd * elif t == NPY_CLONGDOUBLE: f[0] = 90; f[1] = 103; f += 1 # Zg # <<<<<<<<<<<<<< @@ -7159,7 +7154,7 @@ goto __pyx_L11; } - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":829 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":829 * elif t == NPY_CDOUBLE: f[0] = 90; f[1] = 100; f += 1 # Zd * elif t == NPY_CLONGDOUBLE: f[0] = 90; f[1] = 103; f += 1 # Zg * elif t == NPY_OBJECT: f[0] = 79 #"O" # <<<<<<<<<<<<<< @@ -7179,7 +7174,7 @@ } /*else*/ { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":831 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":831 * elif t == NPY_OBJECT: f[0] = 79 #"O" * else: * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) # <<<<<<<<<<<<<< @@ -7202,7 +7197,7 @@ } __pyx_L11:; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":832 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":832 * else: * raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) * f += 1 # <<<<<<<<<<<<<< @@ -7214,7 +7209,7 @@ } /*else*/ { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":836 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":836 * # Cython ignores struct boundary information ("T{...}"), * # so don't output it * f = _util_dtypestring(child, f, end, offset) # <<<<<<<<<<<<<< @@ -7228,7 +7223,7 @@ } __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":837 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":837 * # so don't output it * f = _util_dtypestring(child, f, end, offset) * return f # <<<<<<<<<<<<<< @@ -7258,7 +7253,7 @@ return __pyx_r; } -/* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":952 +/* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":952 * * * cdef inline void set_array_base(ndarray arr, object base): # <<<<<<<<<<<<<< @@ -7273,7 +7268,7 @@ __Pyx_INCREF((PyObject *)__pyx_v_arr); __Pyx_INCREF(__pyx_v_base); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":954 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":954 * cdef inline void set_array_base(ndarray arr, object base): * cdef PyObject* baseptr * if base is None: # <<<<<<<<<<<<<< @@ -7283,7 +7278,7 @@ __pyx_t_1 = (__pyx_v_base == Py_None); if (__pyx_t_1) { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":955 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":955 * cdef PyObject* baseptr * if base is None: * baseptr = NULL # <<<<<<<<<<<<<< @@ -7295,7 +7290,7 @@ } /*else*/ { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":957 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":957 * baseptr = NULL * else: * Py_INCREF(base) # important to do this before decref below! # <<<<<<<<<<<<<< @@ -7304,7 +7299,7 @@ */ Py_INCREF(__pyx_v_base); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":958 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":958 * else: * Py_INCREF(base) # important to do this before decref below! * baseptr = base # <<<<<<<<<<<<<< @@ -7315,7 +7310,7 @@ } __pyx_L3:; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":959 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":959 * Py_INCREF(base) # important to do this before decref below! * baseptr = base * Py_XDECREF(arr.base) # <<<<<<<<<<<<<< @@ -7324,7 +7319,7 @@ */ Py_XDECREF(__pyx_v_arr->base); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":960 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":960 * baseptr = base * Py_XDECREF(arr.base) * arr.base = baseptr # <<<<<<<<<<<<<< @@ -7338,7 +7333,7 @@ __Pyx_RefNannyFinishContext(); } -/* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":962 +/* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":962 * arr.base = baseptr * * cdef inline object get_array_base(ndarray arr): # <<<<<<<<<<<<<< @@ -7352,7 +7347,7 @@ __Pyx_RefNannySetupContext("get_array_base"); __Pyx_INCREF((PyObject *)__pyx_v_arr); - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":963 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":963 * * cdef inline object get_array_base(ndarray arr): * if arr.base is NULL: # <<<<<<<<<<<<<< @@ -7362,7 +7357,7 @@ __pyx_t_1 = (__pyx_v_arr->base == NULL); if (__pyx_t_1) { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":964 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":964 * cdef inline object get_array_base(ndarray arr): * if arr.base is NULL: * return None # <<<<<<<<<<<<<< @@ -7377,7 +7372,7 @@ } /*else*/ { - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/numpy.pxd":966 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/numpy.pxd":966 * return None * else: * return arr.base # <<<<<<<<<<<<<< @@ -7599,7 +7594,7 @@ 0, /*tp_setattro*/ &__pyx_tp_as_buffer_cKDTree, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ - __Pyx_DOCSTR("kd-tree for quick nearest-neighbor lookup\n\n This class provides an index into a set of k-dimensional points\n which can be used to rapidly look up the nearest neighbors of any\n point. \n\n The algorithm used is described in Maneewongvatana and Mount 1999. \n The general idea is that the kd-tree is a binary trie, each of whose\n nodes represents an axis-aligned hyperrectangle. Each node specifies\n an axis and splits the set of points based on whether their coordinate\n along that axis is greater than or less than a particular value. \n\n During construction, the axis and splitting point are chosen by the \n \"sliding midpoint\" rule, which ensures that the cells do not all\n become long and thin. \n\n The tree can be queried for the r closest neighbors of any given point \n (optionally returning only those within some maximum distance of the \n point). It can also be queried, with a substantial gain in efficiency, \n for the r approximate closest neighbors.\n\n For large dimensions (20 is already large) do not expect this to run \n significantly faster than brute force. High-dimensional nearest-neighbor\n queries are a substantial open problem in computer science.\n "), /*tp_doc*/ + __Pyx_DOCSTR("kd-tree for quick nearest-neighbor lookup\n\n This class provides an index into a set of k-dimensional points\n which can be used to rapidly look up the nearest neighbors of any\n point. \n\n The algorithm used is described in Maneewongvatana and Mount 1999. \n The general idea is that the kd-tree is a binary trie, each of whose\n nodes represents an axis-aligned hyperrectangle. Each node specifies\n an axis and splits the set of points based on whether their coordinate\n along that axis is greater than or less than a particular value. \n\n During construction, the axis and splitting point are chosen by the \n \"sliding midpoint\" rule, which ensures that the cells do not all\n become long and thin. \n\n The tree can be queried for the r closest neighbors of any given point \n (optionally returning only those within some maximum distance of the \n point). It can also be queried, with a substantial gain in efficiency, \n for the r approximate closest neighbors.\n\n For large dimensions (20 is already large) do not expect this to run \n significantly faster than brute force. High-dimensional nearest-neighbor\n queries are a substantial open problem in computer science.\n\n Parameters\n ----------\n data : array-like, shape (n,m)\n The n data points of dimension mto be indexed. This array is \n not copied unless this is necessary to produce a contiguous \n array of doubles, and so modifying this data will result in \n bogus results.\n leafsize : positive integer\n The number of points at which the algorithm switches over to\n brute-force.\n\n "), /*tp_doc*/ __pyx_tp_traverse_5scipy_7spatial_7ckdtree_cKDTree, /*tp_traverse*/ __pyx_tp_clear_5scipy_7spatial_7ckdtree_cKDTree, /*tp_clear*/ 0, /*tp_richcompare*/ @@ -7656,7 +7651,6 @@ {&__pyx_kp_u_11, __pyx_k_11, sizeof(__pyx_k_11), 0, 1, 0, 0}, {&__pyx_kp_u_12, __pyx_k_12, sizeof(__pyx_k_12), 0, 1, 0, 0}, {&__pyx_kp_u_13, __pyx_k_13, sizeof(__pyx_k_13), 0, 1, 0, 0}, - {&__pyx_kp_u_14, __pyx_k_14, sizeof(__pyx_k_14), 0, 1, 0, 0}, {&__pyx_kp_s_2, __pyx_k_2, sizeof(__pyx_k_2), 0, 0, 1, 0}, {&__pyx_n_s_3, __pyx_k_3, sizeof(__pyx_k_3), 0, 0, 1, 1}, {&__pyx_kp_s_5, __pyx_k_5, sizeof(__pyx_k_5), 0, 0, 1, 0}, @@ -7668,7 +7662,6 @@ {&__pyx_n_s__ValueError, __pyx_k__ValueError, sizeof(__pyx_k__ValueError), 0, 0, 1, 1}, {&__pyx_n_s____build, __pyx_k____build, sizeof(__pyx_k____build), 0, 0, 1, 1}, {&__pyx_n_s____free_tree, __pyx_k____free_tree, sizeof(__pyx_k____free_tree), 0, 0, 1, 1}, - {&__pyx_n_s____init__, __pyx_k____init__, sizeof(__pyx_k____init__), 0, 0, 1, 1}, {&__pyx_n_s____main__, __pyx_k____main__, sizeof(__pyx_k____main__), 0, 0, 1, 1}, {&__pyx_n_s____query, __pyx_k____query, sizeof(__pyx_k____query), 0, 0, 1, 1}, {&__pyx_n_s____test__, __pyx_k____test__, sizeof(__pyx_k____test__), 0, 0, 1, 1}, @@ -7844,7 +7837,7 @@ /*--- Function import code ---*/ /*--- Execution code ---*/ - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":3 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":3 * # Copyright Anne M. Archibald 2008 * # Released under the scipy license * import numpy as np # <<<<<<<<<<<<<< @@ -7856,7 +7849,7 @@ if (PyObject_SetAttr(__pyx_m, __pyx_n_s__np, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 3; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":7 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":7 * cimport stdlib * * import kdtree # <<<<<<<<<<<<<< @@ -7868,7 +7861,7 @@ if (PyObject_SetAttr(__pyx_m, __pyx_n_s__kdtree, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 7; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":9 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":9 * import kdtree * * cdef double infinity = np.inf # <<<<<<<<<<<<<< @@ -7884,16 +7877,16 @@ __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; __pyx_v_5scipy_7spatial_7ckdtree_infinity = __pyx_t_3; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":517 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":515 * * def query(cKDTree self, object x, int k=1, double eps=0, double p=2, * double distance_upper_bound=infinity): # <<<<<<<<<<<<<< - * """query the kd-tree for nearest neighbors + * """Query the kd-tree for nearest neighbors. * */ __pyx_k_4 = __pyx_v_5scipy_7spatial_7ckdtree_infinity; - /* "/Users/mb312/dev_trees/scipy-work/scipy/spatial/ckdtree.pyx":1 + /* "/Users/rgommers/Code/scipy/scipy/spatial/ckdtree.pyx":1 * # Copyright Anne M. Archibald 2008 # <<<<<<<<<<<<<< * # Released under the scipy license * import numpy as np @@ -7902,7 +7895,7 @@ __Pyx_GOTREF(((PyObject *)__pyx_t_2)); __pyx_t_1 = PyObject_GetAttr(__pyx_m, __pyx_n_s__cKDTree); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_4 = PyObject_GetAttr(__pyx_t_1, __pyx_n_s____init__); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = PyObject_GetAttr(__pyx_t_1, __pyx_n_s__query); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __pyx_t_1 = __Pyx_GetAttrString(__pyx_t_4, "__doc__"); @@ -7910,20 +7903,10 @@ __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; if (PyDict_SetItem(__pyx_t_2, ((PyObject *)__pyx_kp_u_13), __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_m, __pyx_n_s__cKDTree); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __Pyx_GOTREF(__pyx_t_1); - __pyx_t_4 = PyObject_GetAttr(__pyx_t_1, __pyx_n_s__query); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __Pyx_GOTREF(__pyx_t_4); - __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - __pyx_t_1 = __Pyx_GetAttrString(__pyx_t_4, "__doc__"); - __Pyx_GOTREF(__pyx_t_1); - __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; - if (PyDict_SetItem(__pyx_t_2, ((PyObject *)__pyx_kp_u_14), __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; if (PyObject_SetAttr(__pyx_m, __pyx_n_s____test__, ((PyObject *)__pyx_t_2)) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(((PyObject *)__pyx_t_2)); __pyx_t_2 = 0; - /* "/Users/mb312/usr/local/lib/python2.6/site-packages/Cython/Includes/stdlib.pxd":2 + /* "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/Cython-0.12.1-py2.6-macosx-10.3-fat.egg/Cython/Includes/stdlib.pxd":2 * * cdef extern from "stdlib.h" nogil: # <<<<<<<<<<<<<< * void free(void *ptr) Modified: trunk/scipy/spatial/ckdtree.pyx =================================================================== --- trunk/scipy/spatial/ckdtree.pyx 2011-02-20 09:58:04 UTC (rev 7163) +++ trunk/scipy/spatial/ckdtree.pyx 2011-02-20 13:30:33 UTC (rev 7164) @@ -179,6 +179,18 @@ For large dimensions (20 is already large) do not expect this to run significantly faster than brute force. High-dimensional nearest-neighbor queries are a substantial open problem in computer science. + + Parameters + ---------- + data : array-like, shape (n,m) + The n data points of dimension mto be indexed. This array is + not copied unless this is necessary to produce a contiguous + array of doubles, and so modifying this data will result in + bogus results. + leafsize : positive integer + The number of points at which the algorithm switches over to + brute-force. + """ cdef innernode* tree @@ -193,20 +205,6 @@ cdef object indices cdef np.int32_t* raw_indices def __init__(cKDTree self, data, int leafsize=10): - """Construct a kd-tree. - - Parameters: - =========== - - data : array-like, shape (n,m) - The n data points of dimension mto be indexed. This array is - not copied unless this is necessary to produce a contiguous - array of doubles, and so modifying this data will result in - bogus results. - leafsize : positive integer - The number of points at which the algorithm switches over to - brute-force. - """ cdef np.ndarray[double, ndim=2] inner_data cdef np.ndarray[double, ndim=1] inner_maxes cdef np.ndarray[double, ndim=1] inner_mins @@ -515,14 +513,13 @@ def query(cKDTree self, object x, int k=1, double eps=0, double p=2, double distance_upper_bound=infinity): - """query the kd-tree for nearest neighbors + """Query the kd-tree for nearest neighbors. - Parameters: - =========== - - x : array-like, last dimension self.m + Parameters + ---------- + x : array_like, last dimension self.m An array of points to query. - k : integer + k : int The number of nearest neighbors to return. eps : nonnegative float Return approximate nearest neighbors; the kth returned value @@ -539,17 +536,17 @@ queries, it may help to supply the distance to the nearest neighbor of the most recent point. - Returns: - ======== - - d : array of floats + Returns + ------- + d : ndarray of floats The distances to the nearest neighbors. If x has shape tuple+(self.m,), then d has shape tuple+(k,). Missing neighbors are indicated with infinite distances. - i : array of integers + i : ndarray of ints The locations of the neighbors in self.data. If x has shape tuple+(self.m,), then i has shape tuple+(k,). Missing neighbors are indicated with self.n. + """ cdef np.ndarray[int, ndim=2] ii cdef np.ndarray[double, ndim=2] dd Modified: trunk/scipy/stats/mstats_basic.py =================================================================== --- trunk/scipy/stats/mstats_basic.py 2011-02-20 09:58:04 UTC (rev 7163) +++ trunk/scipy/stats/mstats_basic.py 2011-02-20 13:30:33 UTC (rev 7164) @@ -907,8 +907,12 @@ def ks_twosamp_old(data1, data2): """ Computes the Kolmogorov-Smirnov statistic on 2 samples. - Returns: KS D-value, p-value - #""" + + Returns + ------- + KS D-value, p-value + + """ (data1, data2) = [ma.asarray(d).compressed() for d in (data1,data2)] return stats.ks_2samp(data1,data2) @@ -920,12 +924,12 @@ def threshold(a, threshmin=None, threshmax=None, newval=0): """Clip array to a given value. -Similar to numpy.clip(), except that values less than threshmin or -greater than threshmax are replaced by newval, instead of by -threshmin and threshmax respectively. + Similar to numpy.clip(), except that values less than threshmin or + greater than threshmax are replaced by newval, instead of by + threshmin and threshmax respectively. -Parameters ----------- + Parameters + ---------- a : ndarray Input data threshmin : {None, float} optional @@ -935,11 +939,11 @@ newval : {0, float} optional Value outside the thresholds. -Returns -------- + Returns + ------- a, with values less (greater) than threshmin (threshmax) replaced with newval. -""" + """ a = ma.array(a, copy=True) mask = np.zeros(a.shape, dtype=bool) if threshmin is not None: @@ -1082,6 +1086,7 @@ def trim(a, limits=None, inclusive=(True,True), relative=False, axis=None): """Trims an array by masking the data outside some given limits. + Returns a masked version of the input array. %s Modified: trunk/scipy/stats/stats.py =================================================================== --- trunk/scipy/stats/stats.py 2011-02-20 09:58:04 UTC (rev 7163) +++ trunk/scipy/stats/stats.py 2011-02-20 13:30:33 UTC (rev 7164) @@ -1656,14 +1656,18 @@ def obrientransform(*args): """ -Computes a transform on input data (any number of columns). Used to -test for homogeneity of variance prior to running one-way stats. Each -array in *args is one level of a factor. If an F_oneway() run on the -transformed data and found significant, variances are unequal. From -Maxwell and Delaney, p.112. + Computes a transform on input data (any number of columns). -Returns: transformed data for use in an ANOVA -""" + Used to test for homogeneity of variance prior to running one-way stats. + Each array in *args is one level of a factor. If an F_oneway() run on the + transformed data and found significant, variances are unequal. From + Maxwell and Delaney, p.112. + + Returns + ------- + Transformed data for use in an ANOVA + + """ TINY = 1e-10 k = len(args) n = zeros(k) @@ -1696,7 +1700,6 @@ Calculates the signal-to-noise ratio, defined as the ratio between the mean and the standard deviation. - Parameters ---------- a: array-like @@ -1707,7 +1710,6 @@ ddof : integer, optional, default 0 degrees of freedom correction for standard deviation - Returns ------- array containing the value of the ratio of the mean to the standard @@ -3389,7 +3391,10 @@ Sciences. New York: McGraw-Hill. Code adapted from |Stat rankind.c code. - Returns: T correction factor for U or H + Returns + ------- + T correction factor for U or H + """ sorted,posn = fastsort(asarray(rankvals)) n = len(sorted) @@ -3651,7 +3656,10 @@ I. Non-inferential methods and statistical models. Phil Trans Royal Soc Lond B 354: 1239-1260. - Returns: statistic, p-value ??? + Returns + ------- + statistic, p-value ??? + """ if len(para) != len(data): raise ValueError("data and para must be same length in aglm") From scipy-svn at scipy.org Sun Feb 20 11:53:11 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 20 Feb 2011 10:53:11 -0600 (CST) Subject: [Scipy-svn] r7165 - in trunk/scipy: interpolate spatial Message-ID: <20110220165311.1CDB11B89B0@scipy.org> Author: ptvirtan Date: 2011-02-20 10:53:10 -0600 (Sun, 20 Feb 2011) New Revision: 7165 Modified: trunk/scipy/interpolate/interpnd.pyx trunk/scipy/spatial/qhull.pxd trunk/scipy/spatial/qhull.pyx Log: BUG: spatial/interpnd: never deallocate memory in a different Cython module Different Cython modules end up as different DLL/.so files, and apparently on some platforms freeing memory allocated in a different DLL is not allowed. This seems to be true at least on Windows 7 + 32-bit Python. Modified: trunk/scipy/interpolate/interpnd.pyx =================================================================== --- trunk/scipy/interpolate/interpnd.pyx 2011-02-20 13:30:33 UTC (rev 7164) +++ trunk/scipy/interpolate/interpnd.pyx 2011-02-20 16:53:10 UTC (rev 7165) @@ -31,10 +31,6 @@ # Numpy etc. #------------------------------------------------------------------------------ -cdef extern from "stdlib.h": - void *malloc(int size) nogil - void free(void *ptr) nogil - cdef extern from "math.h": double sqrt(double x) nogil double fabs(double a) nogil @@ -164,7 +160,7 @@ """ LinearNDInterpolator(points, values) - Piecewise linear interpolant in N dimensions. + Piecewise linear interpolant in N dimensions. .. versionadded:: 0.9 @@ -205,13 +201,13 @@ cdef double c[NPY_MAXDIMS] cdef ${CDTYPE} fill_value cdef int i, j, k, m, ndim, isimplex, inside, start, nvalues - cdef qhull.DelaunayInfo_t *info + cdef qhull.DelaunayInfo_t info ndim = xi.shape[1] start = 0 fill_value = self.fill_value - info = qhull._get_delaunay_info(self.tri, 1, 0) + qhull._get_delaunay_info(&info, self.tri, 1, 0) out = np.zeros((xi.shape[0], self.values.shape[1]), dtype=np.${DTYPE}) nvalues = out.shape[1] @@ -223,7 +219,7 @@ # 1) Find the simplex - isimplex = qhull._find_simplex(info, c, + isimplex = qhull._find_simplex(&info, c, (xi.data) + i*ndim, &start, eps) @@ -258,7 +254,6 @@ out[i,k].imag += c[j] * values[m, k].imag % endif - free(info) return out % endfor @@ -431,7 +426,7 @@ change = max(fabs(y[it.vertex*2 + 0] + r[0]), fabs(y[it.vertex*2 + 1] + r[1])) - + y[it.vertex*2 + 0] = -r[0] y[it.vertex*2 + 1] = -r[1] @@ -448,7 +443,7 @@ def estimate_gradients_2d_global(tri, y, maxiter=400, tol=1e-6): cdef np.ndarray[np.double_t, ndim=2] data cdef np.ndarray[np.double_t, ndim=3] grad - cdef qhull.DelaunayInfo_t *info + cdef qhull.DelaunayInfo_t info cdef int k, ret, nvalues y = np.asanyarray(y) @@ -476,13 +471,13 @@ data = y grad = yi - info = qhull._get_delaunay_info(tri, 0, 1) + qhull._get_delaunay_info(&info, tri, 0, 1) nvalues = data.shape[0] for k in xrange(nvalues): with nogil: ret = _estimate_gradients_2d_global( - info, + &info, data.data + info.npoints*k, maxiter, tol, @@ -493,7 +488,6 @@ "the results may be inaccurate", GradientEstimationWarning) - free(info) return yi.transpose(1, 0, 2).reshape(y_shape + (2,)) @@ -742,7 +736,7 @@ """ CloughTocher2DInterpolator(points, values, tol=1e-6) - Piecewise cubic, C1 smooth, curvature-minimizing interpolant in 2D. + Piecewise cubic, C1 smooth, curvature-minimizing interpolant in 2D. .. versionadded:: 0.9 @@ -821,13 +815,13 @@ cdef ${CDTYPE} w cdef ${CDTYPE} fill_value cdef int i, j, k, m, ndim, isimplex, inside, start, nvalues - cdef qhull.DelaunayInfo_t *info + cdef qhull.DelaunayInfo_t info ndim = xi.shape[1] start = 0 fill_value = self.fill_value - info = qhull._get_delaunay_info(self.tri, 1, 1) + qhull._get_delaunay_info(&info, self.tri, 1, 1) out = np.zeros((xi.shape[0], self.values.shape[1]), dtype=np.${DTYPE}) nvalues = out.shape[1] @@ -838,7 +832,7 @@ for i in xrange(xi.shape[0]): # 1) Find the simplex - isimplex = qhull._find_simplex(info, c, + isimplex = qhull._find_simplex(&info, c, (xi.data) + i*ndim, &start, eps) @@ -870,7 +864,7 @@ df[2*j+1].imag = grad[vertices[isimplex,j],k,1].imag % endif - w = _clough_tocher_2d_single_${DTYPE}(info, isimplex, c, + w = _clough_tocher_2d_single_${DTYPE}(&info, isimplex, c, f, df) % if DTYPE == "double": out[i,k] = w @@ -879,7 +873,6 @@ out[i,k].imag = w.imag % endif - free(info) return out % endfor Modified: trunk/scipy/spatial/qhull.pxd =================================================================== --- trunk/scipy/spatial/qhull.pxd 2011-02-20 13:30:33 UTC (rev 7164) +++ trunk/scipy/spatial/qhull.pxd 2011-02-20 16:53:10 UTC (rev 7165) @@ -9,10 +9,6 @@ # Distributed under the same BSD license as Scipy. # -cdef extern from "stdlib.h": - void *malloc(int size) - void free(void *ptr) - cdef extern from "numpy/ndarrayobject.h": cdef enum: NPY_MAXDIMS @@ -32,8 +28,9 @@ double *max_bound double *min_bound -cdef DelaunayInfo_t *_get_delaunay_info(obj, int compute_transform, - int compute_vertex_to_simplex) +cdef void _get_delaunay_info(DelaunayInfo_t *, obj, + int compute_transform, + int compute_vertex_to_simplex) # # N-D geometry Modified: trunk/scipy/spatial/qhull.pyx =================================================================== --- trunk/scipy/spatial/qhull.pyx 2011-02-20 13:30:33 UTC (rev 7164) +++ trunk/scipy/spatial/qhull.pyx 2011-02-20 16:53:10 UTC (rev 7165) @@ -593,22 +593,15 @@ cdef class RidgeIter2D(object): cdef RidgeIter2D_t it cdef object delaunay - cdef DelaunayInfo_t *info + cdef DelaunayInfo_t info def __init__(self, delaunay, ivertex): - self.info = NULL if delaunay.ndim != 2: raise ValueError("RidgeIter2D supports only 2-D") self.delaunay = delaunay - self.info = _get_delaunay_info(delaunay, 0, 1) - _RidgeIter2D_init(&self.it, self.info, ivertex) + _get_delaunay_info(&self.info, delaunay, 0, 1) + _RidgeIter2D_init(&self.it, &self.info, ivertex) - def __del__(self): - if self.info != NULL: - free(self.info) - self.info = NULL - self.delaunay = None - def __iter__(self): return self @@ -1067,7 +1060,7 @@ directed search in N dimensions. """ - cdef DelaunayInfo_t *info + cdef DelaunayInfo_t info cdef int isimplex cdef double c[NPY_MAXDIMS] cdef double eps @@ -1090,23 +1083,21 @@ eps = np.finfo(np.double).eps * 10 out = np.zeros((xi.shape[0],), dtype=np.intc) out_ = out - info = _get_delaunay_info(self, 1, 0) + _get_delaunay_info(&info, self, 1, 0) if bruteforce: for k in xrange(x.shape[0]): isimplex = _find_simplex_bruteforce( - info, c, + &info, c, x.data + info.ndim*k, eps) out_[k] = isimplex else: for k in xrange(x.shape[0]): - isimplex = _find_simplex(info, c, x.data + info.ndim*k, + isimplex = _find_simplex(&info, c, x.data + info.ndim*k, &start, eps) out_[k] = isimplex - free(info) - return out.reshape(xi_shape[:-1]) def plane_distance(self, xi): @@ -1118,7 +1109,7 @@ """ cdef np.ndarray[np.double_t, ndim=2] x cdef np.ndarray[np.double_t, ndim=2] out_ - cdef DelaunayInfo_t *info + cdef DelaunayInfo_t info cdef double z[NPY_MAXDIMS+1] cdef int i, j, k @@ -1130,18 +1121,16 @@ xi = xi.reshape(np.prod(xi.shape[:-1]), xi.shape[-1]) x = np.ascontiguousarray(xi.astype(np.double)) - info = _get_delaunay_info(self, 0, 0) + _get_delaunay_info(&info, self, 0, 0) out = np.zeros((x.shape[0], info.nsimplex), dtype=np.double) out_ = out for i in xrange(x.shape[0]): for j in xrange(info.nsimplex): - _lift_point(info, (x.data) + info.ndim*i, z) - out_[i,j] = _distplane(info, j, z) + _lift_point(&info, (x.data) + info.ndim*i, z) + out_[i,j] = _distplane(&info, j, z) - free(info) - return out.reshape(xi_shape[:-1] + (self.nsimplex,)) def lift_points(tri, x): @@ -1180,10 +1169,10 @@ # Delaunay triangulation interface, for low-level C #------------------------------------------------------------------------------ -cdef DelaunayInfo_t *_get_delaunay_info(obj, - int compute_transform, - int compute_vertex_to_simplex): - cdef DelaunayInfo_t *info +cdef void _get_delaunay_info(DelaunayInfo_t *info, + obj, + int compute_transform, + int compute_vertex_to_simplex): cdef np.ndarray[np.double_t, ndim=3] transform cdef np.ndarray[np.npy_int, ndim=1] vertex_to_simplex cdef np.ndarray[np.double_t, ndim=2] points = obj.points @@ -1193,7 +1182,6 @@ cdef np.ndarray[np.double_t, ndim=1] min_bound = obj.min_bound cdef np.ndarray[np.double_t, ndim=1] max_bound = obj.max_bound - info = malloc(sizeof(DelaunayInfo_t)) info.ndim = points.shape[1] info.npoints = points.shape[0] info.nsimplex = vertices.shape[0] @@ -1215,5 +1203,3 @@ info.vertex_to_simplex = NULL info.min_bound = min_bound.data info.max_bound = max_bound.data - - return info From scipy-svn at scipy.org Sun Feb 20 11:53:20 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 20 Feb 2011 10:53:20 -0600 (CST) Subject: [Scipy-svn] r7166 - in trunk/scipy: interpolate spatial Message-ID: <20110220165320.9BB3C1B89B0@scipy.org> Author: ptvirtan Date: 2011-02-20 10:53:20 -0600 (Sun, 20 Feb 2011) New Revision: 7166 Modified: trunk/scipy/interpolate/interpnd.c trunk/scipy/spatial/qhull.c Log: GEN: spatial/interpolate: regenerate qhull/interpnd Cython modules Modified: trunk/scipy/interpolate/interpnd.c =================================================================== --- trunk/scipy/interpolate/interpnd.c 2011-02-20 16:53:10 UTC (rev 7165) +++ trunk/scipy/interpolate/interpnd.c 2011-02-20 16:53:20 UTC (rev 7166) @@ -761,7 +761,7 @@ static CYTHON_INLINE PyObject *__pyx_f_5numpy_get_array_base(PyArrayObject *); -static __pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t *(*__pyx_f_5scipy_7spatial_5qhull__get_delaunay_info)(PyObject *, int, int); +static void (*__pyx_f_5scipy_7spatial_5qhull__get_delaunay_info)(__pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t *, PyObject *, int, int); static int (*__pyx_f_5scipy_7spatial_5qhull__barycentric_inside)(int, double *, double *, double *, double); static void (*__pyx_f_5scipy_7spatial_5qhull__barycentric_coordinate_single)(int, double *, double *, double *, int); static void (*__pyx_f_5scipy_7spatial_5qhull__barycentric_coordinates)(int, double *, double *, double *); @@ -821,14 +821,14 @@ static char __pyx_k_24[] = "scipy.spatial.qhull"; static char __pyx_k_25[] = "*"; static char __pyx_k_26[] = "\n Common routines for interpolators.\n\n .. versionadded:: 0.9\n\n "; -static char __pyx_k_27[] = "\n LinearNDInterpolator(points, values)\n\n Piecewise linear interpolant in N dimensions. \n\n .. versionadded:: 0.9\n\n Parameters\n ----------\n points : ndarray of floats, shape (npoints, ndims)\n Data point coordinates.\n values : ndarray of float or complex, shape (npoints, ...)\n Data values.\n fill_value : float, optional\n Value used to fill in for requested points outside of the\n convex hull of the input points. If not provided, then\n the default is ``nan``.\n\n Notes\n -----\n The interpolant is constructed by triangulating the input data\n with Qhull [Qhull]_, and on each triangle performing linear\n barycentric interpolation.\n\n References\n ----------\n .. [Qhull] http://www.qhull.org/\n\n "; +static char __pyx_k_27[] = "\n LinearNDInterpolator(points, values)\n\n Piecewise linear interpolant in N dimensions.\n\n .. versionadded:: 0.9\n\n Parameters\n ----------\n points : ndarray of floats, shape (npoints, ndims)\n Data point coordinates.\n values : ndarray of float or complex, shape (npoints, ...)\n Data values.\n fill_value : float, optional\n Value used to fill in for requested points outside of the\n convex hull of the input points. If not provided, then\n the default is ``nan``.\n\n Notes\n -----\n The interpolant is constructed by triangulating the input data\n with Qhull [Qhull]_, and on each triangle performing linear\n barycentric interpolation.\n\n References\n ----------\n .. [Qhull] http://www.qhull.org/\n\n "; static char __pyx_k_28[] = "LinearNDInterpolator"; -static char __pyx_k_29[] = "\n CloughTocher2DInterpolator(points, values, tol=1e-6)\n\n Piecewise cubic, C1 smooth, curvature-minimizing interpolant in 2D. \n\n .. versionadded:: 0.9\n\n Parameters\n ----------\n points : ndarray of floats, shape (npoints, ndims)\n Data point coordinates.\n values : ndarray of float or complex, shape (npoints, ...)\n Data values.\n fill_value : float, optional\n Value used to fill in for requested points outside of the\n convex hull of the input points. If not provided, then\n the default is ``nan``.\n tol : float, optional\n Absolute/relative tolerance for gradient estimation.\n maxiter : int, optional\n Maximum number of iterations in gradient estimation.\n\n Notes\n -----\n The interpolant is constructed by triangulating the input data\n with Qhull [Qhull]_, and constructing a piecewise cubic\n interpolating Bezier polynomial on each triangle, using a\n Clough-Tocher scheme [CT]_. The interpolant is guaranteed to be\n continuously differentiable.\n\n The gradients of the interpolant are chosen so that the curvature\n of the interpolating surface is approximatively minimized. The\n gradients necessary for this are estimated using the global\n algorithm described in [Nielson83,Renka84]_.\n\n References\n ----------\n\n .. [Qhull] http://www.qhull.org/\n\n .. [CT] See, for example,\n P. Alfeld,\n ''A trivariate Clough-Tocher scheme for tetrahedral data''.\n Computer Aided Geometric Design, 1, 169 (1984);\n G. Farin,\n ''Triangular Bernstein-Bezier patches''.\n Computer Aided Geometric Design, 3, 83 (1986).\n\n .. [Nielson83] G. Nielson,\n ''A method for interpolating scattered data based upon a minimum norm\n network''.\n Math. Comp., 40, 253 (1983).\n\n .. [Renka84] R. J. Renka and A. K. Cline.\n ''A Triangle-based C1 interpolation method.'',\n Rocky Mountain J. Math., 14, 223 (1984).\n\n "; +static char __pyx_k_29[] = "\n CloughTocher2DInterpolator(points, values, tol=1e-6)\n\n Piecewise cubic, C1 smooth, curvature-minimizing interpolant in 2D.\n\n .. versionadded:: 0.9\n\n Parameters\n ----------\n points : ndarray of floats, shape (npoints, ndims)\n Data point coordinates.\n values : ndarray of float or complex, shape (npoints, ...)\n Data values.\n fill_value : float, optional\n Value used to fill in for requested points outside of the\n convex hull of the input points. If not provided, then\n the default is ``nan``.\n tol : float, optional\n Absolute/relative tolerance for gradient estimation.\n maxiter : int, optional\n Maximum number of iterations in gradient estimation.\n\n Notes\n -----\n The interpolant is constructed by triangulating the input data\n with Qhull [Qhull]_, and constructing a piecewise cubic\n interpolating Bezier polynomial on each triangle, using a\n Clough-Tocher scheme [CT]_. The interpolant is guaranteed to be\n continuously differentiable.\n\n The gradients of the interpolant are chosen so that the curvature\n of the interpolating surface is approximatively minimized. The\n gradients necessary for this are estimated using the global\n algorithm described in [Nielson83,Renka84]_.\n\n References\n ----------\n\n .. [Qhull] http://www.qhull.org/\n\n .. [CT] See, for example,\n P. Alfeld,\n ''A trivariate Clough-Tocher scheme for tetrahedral data''.\n Computer Aided Geometric Design, 1, 169 (1984);\n G. Farin,\n ''Triangular Bernstein-Bezier patches''.\n Computer Aided Geometric Design, 3, 83 (1986).\n\n .. [Nielson83] G. Nielson,\n ''A method for interpolating scattered data based upon a minimum norm\n network''.\n Math. Comp., 40, 253 (1983).\n\n .. [Renka84] R. J. Renka and A. K. Cline.\n ''A Triangle-based C1 interpolation method.'',\n Rocky Mountain J. Math., 14, 223 (1984).\n\n "; static char __pyx_k_30[] = "CloughTocher2DInterpolator"; -static char __pyx_k_31[] = "NDInterpolatorBase.__init__ (line 58)"; -static char __pyx_k_32[] = "NDInterpolatorBase._check_init_shape (line 91)"; -static char __pyx_k_33[] = "NDInterpolatorBase.__call__ (line 112)"; -static char __pyx_k_34[] = "_ndim_coords_from_arrays (line 137)"; +static char __pyx_k_31[] = "NDInterpolatorBase.__init__ (line 54)"; +static char __pyx_k_32[] = "NDInterpolatorBase._check_init_shape (line 87)"; +static char __pyx_k_33[] = "NDInterpolatorBase.__call__ (line 108)"; +static char __pyx_k_34[] = "_ndim_coords_from_arrays (line 133)"; static char __pyx_k__B[] = "B"; static char __pyx_k__H[] = "H"; static char __pyx_k__I[] = "I"; @@ -1086,13 +1086,13 @@ values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__points); if (likely(values[1])) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("__init__", 0, 3, 5, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 58; __pyx_clineno = __LINE__; 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- __pyx_t_1 = PyTuple_New(2); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyTuple_New(2); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 73; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); PyTuple_SET_ITEM(__pyx_t_1, 0, __pyx_t_2); __Pyx_GIVEREF(__pyx_t_2); @@ -1322,34 +1322,34 @@ __Pyx_GIVEREF(__pyx_t_6); __pyx_t_2 = 0; __pyx_t_6 = 0; - __pyx_t_6 = PyObject_Call(__pyx_t_3, __pyx_t_1, NULL); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyObject_Call(__pyx_t_3, __pyx_t_1, NULL); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 73; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - if (PyObject_SetAttr(__pyx_v_self, __pyx_n_s__values, __pyx_t_6) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyObject_SetAttr(__pyx_v_self, __pyx_n_s__values, __pyx_t_6) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 73; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; } __pyx_L6:; - __pyx_t_6 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 81; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); - __pyx_t_1 = PyObject_GetAttr(__pyx_t_6, __pyx_n_s__issubdtype); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 81; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_t_6, __pyx_n_s__issubdtype); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; - __pyx_t_6 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__values); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 81; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__values); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); - __pyx_t_3 = PyObject_GetAttr(__pyx_t_6, __pyx_n_s__dtype); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 81; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_GetAttr(__pyx_t_6, __pyx_n_s__dtype); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; - __pyx_t_6 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 81; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); - __pyx_t_2 = PyObject_GetAttr(__pyx_t_6, __pyx_n_s__complexfloating); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 81; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyObject_GetAttr(__pyx_t_6, __pyx_n_s__complexfloating); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; - __pyx_t_6 = PyTuple_New(2); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 81; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyTuple_New(2); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; 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goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 122; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_2 = PyObject_GetAttr(__pyx_t_1, __pyx_n_s__ascontiguousarray); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 126; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyObject_GetAttr(__pyx_t_1, __pyx_n_s__ascontiguousarray); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 122; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_xi, __pyx_n_s__astype); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 126; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_xi, __pyx_n_s__astype); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 122; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_3 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 126; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 122; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - __pyx_t_4 = PyObject_GetAttr(__pyx_t_3, __pyx_n_s__double); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 126; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = PyObject_GetAttr(__pyx_t_3, __pyx_n_s__double); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 122; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 126; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 122; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); PyTuple_SET_ITEM(__pyx_t_3, 0, __pyx_t_4); __Pyx_GIVEREF(__pyx_t_4); __pyx_t_4 = 0; - __pyx_t_4 = PyObject_Call(__pyx_t_1, __pyx_t_3, NULL); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 126; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = PyObject_Call(__pyx_t_1, __pyx_t_3, NULL); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 122; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 126; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 122; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); PyTuple_SET_ITEM(__pyx_t_3, 0, __pyx_t_4); __Pyx_GIVEREF(__pyx_t_4); __pyx_t_4 = 0; - __pyx_t_4 = PyObject_Call(__pyx_t_2, __pyx_t_3, NULL); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 126; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = PyObject_Call(__pyx_t_2, __pyx_t_3, NULL); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 122; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; @@ -1953,34 +1953,34 @@ __pyx_t_4 = 0; - __pyx_t_4 = PyObject_GetAttr(__pyx_v_xi, __pyx_n_s__shape); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 127; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = PyObject_GetAttr(__pyx_v_xi, __pyx_n_s__shape); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 123; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_v_shape); __pyx_v_shape = __pyx_t_4; __pyx_t_4 = 0; - __pyx_t_4 = PyObject_GetAttr(__pyx_v_xi, __pyx_n_s__reshape); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 128; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = PyObject_GetAttr(__pyx_v_xi, __pyx_n_s__reshape); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 124; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); - __pyx_t_3 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 128; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 124; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - __pyx_t_2 = PyObject_GetAttr(__pyx_t_3, __pyx_n_s__prod); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 128; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyObject_GetAttr(__pyx_t_3, __pyx_n_s__prod); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 124; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PySequence_GetSlice(__pyx_v_shape, 0, -1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 128; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PySequence_GetSlice(__pyx_v_shape, 0, -1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 124; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - __pyx_t_1 = PyTuple_New(1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 128; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyTuple_New(1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 124; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); PyTuple_SET_ITEM(__pyx_t_1, 0, __pyx_t_3); __Pyx_GIVEREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyObject_Call(__pyx_t_2, __pyx_t_1, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 128; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_Call(__pyx_t_2, __pyx_t_1, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 124; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - __pyx_t_1 = __Pyx_GetItemInt(__pyx_v_shape, -1, sizeof(long), PyInt_FromLong); if (!__pyx_t_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 128; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_GetItemInt(__pyx_v_shape, -1, sizeof(long), PyInt_FromLong); if (!__pyx_t_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 124; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_2 = PyTuple_New(2); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 128; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyTuple_New(2); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 124; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); PyTuple_SET_ITEM(__pyx_t_2, 0, __pyx_t_3); __Pyx_GIVEREF(__pyx_t_3); @@ -1988,7 +1988,7 @@ __Pyx_GIVEREF(__pyx_t_1); __pyx_t_3 = 0; __pyx_t_1 = 0; - __pyx_t_1 = PyObject_Call(__pyx_t_4, __pyx_t_2, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 128; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_Call(__pyx_t_4, __pyx_t_2, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 124; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; @@ -1997,21 +1997,21 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__is_complex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 130; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__is_complex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 126; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_5 = __Pyx_PyObject_IsTrue(__pyx_t_1); if (unlikely(__pyx_t_5 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 130; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = __Pyx_PyObject_IsTrue(__pyx_t_1); if (unlikely(__pyx_t_5 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 126; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; if (__pyx_t_5) { - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s___evaluate_complex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 131; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s___evaluate_complex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 127; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_2 = PyTuple_New(1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 131; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyTuple_New(1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 127; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_INCREF(__pyx_v_xi); PyTuple_SET_ITEM(__pyx_t_2, 0, __pyx_v_xi); __Pyx_GIVEREF(__pyx_v_xi); - __pyx_t_4 = PyObject_Call(__pyx_t_1, __pyx_t_2, NULL); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 131; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = PyObject_Call(__pyx_t_1, __pyx_t_2, NULL); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 127; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; @@ -2023,14 +2023,14 @@ { - __pyx_t_4 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s___evaluate_double); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 133; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s___evaluate_double); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 129; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); - __pyx_t_2 = PyTuple_New(1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 133; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyTuple_New(1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 129; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_INCREF(__pyx_v_xi); PyTuple_SET_ITEM(__pyx_t_2, 0, __pyx_v_xi); __Pyx_GIVEREF(__pyx_v_xi); - __pyx_t_1 = PyObject_Call(__pyx_t_4, __pyx_t_2, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 133; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_Call(__pyx_t_4, __pyx_t_2, NULL); 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goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); - __pyx_t_4 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__values_shape); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 135; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__values_shape); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 131; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); - __pyx_t_3 = PyNumber_Add(__pyx_t_2, __pyx_t_4); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 135; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyNumber_Add(__pyx_t_2, __pyx_t_4); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 131; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; - __pyx_t_4 = PyTuple_New(1); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; 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if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 146; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_7 = PyObject_Call(__pyx_t_6, ((PyObject *)__pyx_t_5), NULL); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 142; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_7); __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; __Pyx_DECREF(((PyObject *)__pyx_t_5)); __pyx_t_5 = 0; @@ -2151,10 +2151,10 @@ __pyx_t_7 = 0; - __pyx_t_8 = PyObject_Length(__pyx_v_p); if (unlikely(__pyx_t_8 == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_t_7 = PyInt_FromSsize_t(__pyx_t_8); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = PyObject_Length(__pyx_v_p); if (unlikely(__pyx_t_8 == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 143; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_7 = PyInt_FromSsize_t(__pyx_t_8); 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goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_7); __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; if (PyList_CheckExact(__pyx_t_7) || PyTuple_CheckExact(__pyx_t_7)) { __pyx_t_2 = 0; __pyx_t_5 = __pyx_t_7; __Pyx_INCREF(__pyx_t_5); } else { - __pyx_t_2 = -1; __pyx_t_5 = PyObject_GetIter(__pyx_t_7); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = -1; __pyx_t_5 = PyObject_GetIter(__pyx_t_7); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 143; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); } __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; @@ -2182,7 +2182,7 @@ } else { __pyx_t_7 = PyIter_Next(__pyx_t_5); if (!__pyx_t_7) { - if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 143; __pyx_clineno = __LINE__; goto __pyx_L1_error;} break; } __Pyx_GOTREF(__pyx_t_7); @@ -2192,36 +2192,36 @@ __pyx_t_7 = 0; - __pyx_t_7 = PyObject_GetItem(__pyx_v_p, __pyx_v_j); if (!__pyx_t_7) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 148; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_7 = PyObject_GetItem(__pyx_v_p, __pyx_v_j); if (!__pyx_t_7) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 144; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_7); - __pyx_t_6 = PyObject_GetAttr(__pyx_t_7, __pyx_n_s__shape); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 148; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyObject_GetAttr(__pyx_t_7, __pyx_n_s__shape); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 144; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; - __pyx_t_7 = __Pyx_GetItemInt(__pyx_v_p, 0, sizeof(long), PyInt_FromLong); if (!__pyx_t_7) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 148; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_7 = __Pyx_GetItemInt(__pyx_v_p, 0, sizeof(long), PyInt_FromLong); if (!__pyx_t_7) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 144; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_7); - __pyx_t_9 = PyObject_GetAttr(__pyx_t_7, __pyx_n_s__shape); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 148; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PyObject_GetAttr(__pyx_t_7, __pyx_n_s__shape); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 144; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; - __pyx_t_7 = PyObject_RichCompare(__pyx_t_6, __pyx_t_9, Py_NE); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 148; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_7 = PyObject_RichCompare(__pyx_t_6, __pyx_t_9, Py_NE); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; 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__Pyx_GIVEREF(((PyObject *)__pyx_kp_s_8)); - __pyx_t_9 = PyObject_Call(__pyx_builtin_ValueError, __pyx_t_7, NULL); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 149; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PyObject_Call(__pyx_builtin_ValueError, __pyx_t_7, NULL); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; __Pyx_Raise(__pyx_t_9, 0, 0); __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 149; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} goto __pyx_L9; } __pyx_L9:; @@ -2229,37 +2229,37 @@ __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; - __pyx_t_5 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 150; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 146; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); - __pyx_t_9 = PyObject_GetAttr(__pyx_t_5, __pyx_n_s__empty); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 150; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PyObject_GetAttr(__pyx_t_5, __pyx_n_s__empty); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 146; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; - __pyx_t_5 = __Pyx_GetItemInt(__pyx_v_p, 0, sizeof(long), PyInt_FromLong); if (!__pyx_t_5) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 150; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = __Pyx_GetItemInt(__pyx_v_p, 0, sizeof(long), PyInt_FromLong); if (!__pyx_t_5) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 146; __pyx_clineno = __LINE__; 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if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 156; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_7 = PyObject_GetAttr(__pyx_v_points, __pyx_n_s__reshape); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 152; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_7); - __pyx_t_6 = PyTuple_New(2); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 156; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyTuple_New(2); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 152; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); __Pyx_INCREF(__pyx_int_neg_1); PyTuple_SET_ITEM(__pyx_t_6, 0, __pyx_int_neg_1); @@ -2362,7 +2362,7 @@ __Pyx_INCREF(__pyx_int_1); PyTuple_SET_ITEM(__pyx_t_6, 1, __pyx_int_1); __Pyx_GIVEREF(__pyx_int_1); - __pyx_t_5 = PyObject_Call(__pyx_t_7, __pyx_t_6, NULL); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 156; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = PyObject_Call(__pyx_t_7, __pyx_t_6, NULL); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 152; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; @@ -2438,13 +2438,13 @@ values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__points); if (likely(values[1])) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("__init__", 0, 3, 4, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 194; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("__init__", 0, 3, 4, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 190; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 2: values[2] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__values); if (likely(values[2])) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("__init__", 0, 3, 4, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 194; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("__init__", 0, 3, 4, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 190; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 3: if (kw_args > 0) { @@ -2453,7 +2453,7 @@ } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "__init__") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 194; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "__init__") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 190; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } __pyx_v_self = values[0]; __pyx_v_points = values[1]; @@ -2474,7 +2474,7 @@ } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; - __Pyx_RaiseArgtupleInvalid("__init__", 0, 3, 4, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 194; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("__init__", 0, 3, 4, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 190; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_L3_error:; __Pyx_AddTraceback("interpnd.LinearNDInterpolator.__init__"); __Pyx_RefNannyFinishContext(); @@ -2482,12 +2482,12 @@ __pyx_L4_argument_unpacking_done:; - __pyx_t_1 = __Pyx_GetName(__pyx_m, __pyx_n_s__NDInterpolatorBase); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 195; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_GetName(__pyx_m, __pyx_n_s__NDInterpolatorBase); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 191; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_2 = PyObject_GetAttr(__pyx_t_1, __pyx_n_s____init__); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 195; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyObject_GetAttr(__pyx_t_1, __pyx_n_s____init__); 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__Pyx_INCREF(Py_None); __pyx_bstruct_points.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 202; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 198; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_bstride_0_points = __pyx_bstruct_points.strides[0]; __pyx_bstride_1_points = __pyx_bstruct_points.strides[1]; __pyx_bshape_0_points = __pyx_bstruct_points.shape[0]; __pyx_bshape_1_points = __pyx_bstruct_points.shape[1]; } @@ -2717,18 +2717,18 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__tri); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 203; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__tri); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 199; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_4 = PyObject_GetAttr(__pyx_t_1, __pyx_n_s__vertices); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; 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goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_xi), __pyx_ptype_5numpy_ndarray, 1, "xi", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 243; __pyx_clineno = __LINE__; goto __pyx_L1_error;} { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_xi, (PyObject*)__pyx_v_xi, &__Pyx_TypeInfo_nn___pyx_t_5numpy_double_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 248; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_xi, (PyObject*)__pyx_v_xi, &__Pyx_TypeInfo_nn___pyx_t_5numpy_double_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 243; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_bstride_0_xi = __pyx_bstruct_xi.strides[0]; __pyx_bstride_1_xi = __pyx_bstruct_xi.strides[1]; __pyx_bshape_0_xi = __pyx_bstruct_xi.shape[0]; __pyx_bshape_1_xi = __pyx_bstruct_xi.shape[1]; 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if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 491; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyObject_RichCompare(__pyx_t_1, __pyx_t_3, Py_NE); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 485; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_4 = __Pyx_PyObject_IsTrue(__pyx_t_2); if (unlikely(__pyx_t_4 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 491; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyObject_IsTrue(__pyx_t_2); if (unlikely(__pyx_t_4 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 485; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; if (__pyx_t_4) { - __pyx_t_2 = PyTuple_New(1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 492; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyTuple_New(1); 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__pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_GetAttr(__pyx_v_y, __pyx_n_s__dtype); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 488; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - __pyx_t_1 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 494; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 488; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_5 = PyObject_GetAttr(__pyx_t_1, __pyx_n_s__complexfloating); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 494; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = PyObject_GetAttr(__pyx_t_1, __pyx_n_s__complexfloating); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 488; __pyx_clineno = __LINE__; 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if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 489; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_2 = PyTuple_New(2); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 495; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyTuple_New(2); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 489; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_INCREF(__pyx_v_tri); PyTuple_SET_ITEM(__pyx_t_2, 0, __pyx_v_tri); @@ -3902,11 +3896,11 @@ PyTuple_SET_ITEM(__pyx_t_2, 1, __pyx_t_1); __Pyx_GIVEREF(__pyx_t_1); __pyx_t_1 = 0; - __pyx_t_1 = PyDict_New(); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 495; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyDict_New(); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 489; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(((PyObject *)__pyx_t_1)); 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__pyx_lineno = 504; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyObject_IsTrue(__pyx_t_5); if (unlikely(__pyx_t_4 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 498; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; if (__pyx_t_4) { - __pyx_t_5 = PySlice_New(Py_None, Py_None, Py_None); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 505; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = PySlice_New(Py_None, Py_None, Py_None); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 499; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); - __pyx_t_3 = PyTuple_New(2); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 505; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyTuple_New(2); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 499; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); 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__Pyx_INCREF(__pyx_v_y); PyTuple_SET_ITEM(__pyx_t_2, 0, __pyx_v_y); __Pyx_GIVEREF(__pyx_v_y); - __pyx_t_5 = PyObject_Call(__pyx_t_3, __pyx_t_2, NULL); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 508; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = PyObject_Call(__pyx_t_3, __pyx_t_2, NULL); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 502; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - __pyx_t_2 = PyObject_GetAttr(__pyx_t_5, __pyx_n_s__astype); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 508; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyObject_GetAttr(__pyx_t_5, __pyx_n_s__astype); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 502; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; - __pyx_t_5 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 508; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 502; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); - __pyx_t_3 = PyObject_GetAttr(__pyx_t_5, __pyx_n_s__double); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 508; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_GetAttr(__pyx_t_5, __pyx_n_s__double); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 502; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; - __pyx_t_5 = PyTuple_New(1); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 508; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = PyTuple_New(1); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 502; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); PyTuple_SET_ITEM(__pyx_t_5, 0, __pyx_t_3); __Pyx_GIVEREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyObject_Call(__pyx_t_2, __pyx_t_5, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 508; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_Call(__pyx_t_2, __pyx_t_5, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 502; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; @@ -4080,22 +4074,22 @@ __pyx_t_3 = 0; - __pyx_t_3 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 509; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - __pyx_t_5 = PyObject_GetAttr(__pyx_t_3, __pyx_n_s__empty); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 509; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = PyObject_GetAttr(__pyx_t_3, __pyx_n_s__empty); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyObject_GetAttr(__pyx_v_y, __pyx_n_s__shape); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 509; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_GetAttr(__pyx_v_y, __pyx_n_s__shape); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - __pyx_t_2 = __Pyx_GetItemInt(__pyx_t_3, 0, sizeof(long), PyInt_FromLong); if (!__pyx_t_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 509; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = __Pyx_GetItemInt(__pyx_t_3, 0, sizeof(long), PyInt_FromLong); if (!__pyx_t_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyObject_GetAttr(__pyx_v_y, __pyx_n_s__shape); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 509; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_GetAttr(__pyx_v_y, __pyx_n_s__shape); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - __pyx_t_1 = __Pyx_GetItemInt(__pyx_t_3, 1, sizeof(long), PyInt_FromLong); if (!__pyx_t_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 509; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_GetItemInt(__pyx_t_3, 1, sizeof(long), PyInt_FromLong); if (!__pyx_t_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyTuple_New(3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 509; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyTuple_New(3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); PyTuple_SET_ITEM(__pyx_t_3, 0, __pyx_t_2); __Pyx_GIVEREF(__pyx_t_2); @@ -4106,12 +4100,12 @@ __Pyx_GIVEREF(__pyx_int_2); __pyx_t_2 = 0; __pyx_t_1 = 0; - __pyx_t_1 = PyTuple_New(1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 509; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyTuple_New(1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); PyTuple_SET_ITEM(__pyx_t_1, 0, __pyx_t_3); __Pyx_GIVEREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyObject_Call(__pyx_t_5, __pyx_t_1, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 509; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_Call(__pyx_t_5, __pyx_t_1, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; @@ -4120,7 +4114,7 @@ __pyx_t_3 = 0; - if (!(likely(((__pyx_v_y) == Py_None) || likely(__Pyx_TypeTest(__pyx_v_y, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 511; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_v_y) == Py_None) || likely(__Pyx_TypeTest(__pyx_v_y, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 505; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_6 = ((PyArrayObject *)__pyx_v_y); { __Pyx_BufFmt_StackElem __pyx_stack[1]; 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__Pyx_INCREF(Py_None); __pyx_bstruct_values.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1062; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1055; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_bstride_0_values = __pyx_bstruct_values.strides[0]; __pyx_bstride_1_values = __pyx_bstruct_values.strides[1]; __pyx_bshape_0_values = __pyx_bstruct_values.shape[0]; __pyx_bshape_1_values = __pyx_bstruct_values.shape[1]; } @@ -5286,15 +5277,15 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__grad); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1063; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__grad); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1056; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1063; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1056; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_3 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_grad, (PyObject*)__pyx_t_3, &__Pyx_TypeInfo_nn___pyx_t_5numpy_double_t, PyBUF_FORMAT| PyBUF_STRIDES, 3, 0, __pyx_stack) == -1)) { __pyx_v_grad = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_bstruct_grad.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1063; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1056; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_bstride_0_grad = __pyx_bstruct_grad.strides[0]; __pyx_bstride_1_grad = __pyx_bstruct_grad.strides[1]; __pyx_bstride_2_grad = __pyx_bstruct_grad.strides[2]; 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__pyx_t_5 = 0; - __pyx_t_5 = __Pyx_PyInt_to_py_Py_intptr_t((__pyx_v_xi->dimensions[0])); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1081; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = __Pyx_PyInt_to_py_Py_intptr_t((__pyx_v_xi->dimensions[0])); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1074; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); - __pyx_t_8 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__values); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1081; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__values); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1074; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_8); - __pyx_t_9 = PyObject_GetAttr(__pyx_t_8, __pyx_n_s__shape); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1081; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PyObject_GetAttr(__pyx_t_8, __pyx_n_s__shape); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1074; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); __Pyx_DECREF(__pyx_t_8); __pyx_t_8 = 0; - __pyx_t_8 = __Pyx_GetItemInt(__pyx_t_9, 1, sizeof(long), PyInt_FromLong); if (!__pyx_t_8) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1081; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = __Pyx_GetItemInt(__pyx_t_9, 1, sizeof(long), PyInt_FromLong); if (!__pyx_t_8) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1074; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_8); __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; - __pyx_t_9 = PyTuple_New(2); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1081; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PyTuple_New(2); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1074; __pyx_clineno = __LINE__; 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if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1081; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1074; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); - __pyx_t_10 = PyObject_GetAttr(__pyx_t_5, __pyx_n_s__double); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1081; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_10 = PyObject_GetAttr(__pyx_t_5, __pyx_n_s__double); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1074; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_10); __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; - if (PyDict_SetItem(__pyx_t_9, ((PyObject *)__pyx_n_s__dtype), __pyx_t_10) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1081; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_t_9, ((PyObject *)__pyx_n_s__dtype), __pyx_t_10) < 0) {__pyx_filename = __pyx_f[0]; 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__pyx_lineno = 1074; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_11 = ((PyArrayObject *)__pyx_t_10); { __Pyx_BufFmt_StackElem __pyx_stack[1]; @@ -5421,7 +5412,7 @@ } __pyx_bstride_0_out = __pyx_bstruct_out.strides[0]; __pyx_bstride_1_out = __pyx_bstruct_out.strides[1]; __pyx_bshape_0_out = __pyx_bstruct_out.shape[0]; __pyx_bshape_1_out = __pyx_bstruct_out.shape[1]; - if (unlikely(__pyx_t_12 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1081; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__pyx_t_12 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1074; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_11 = 0; __Pyx_DECREF(((PyObject *)__pyx_v_out)); @@ -5432,29 +5423,29 @@ __pyx_v_nvalues = (__pyx_v_out->dimensions[1]); - __pyx_t_10 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1084; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_10 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1077; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_10); - __pyx_t_9 = PyObject_GetAttr(__pyx_t_10, __pyx_n_s__finfo); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1084; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PyObject_GetAttr(__pyx_t_10, __pyx_n_s__finfo); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1077; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); __Pyx_DECREF(__pyx_t_10); __pyx_t_10 = 0; - __pyx_t_10 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1084; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_10 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1077; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_10); - __pyx_t_8 = PyObject_GetAttr(__pyx_t_10, __pyx_n_s__double); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1084; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = PyObject_GetAttr(__pyx_t_10, __pyx_n_s__double); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1077; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_8); __Pyx_DECREF(__pyx_t_10); __pyx_t_10 = 0; - __pyx_t_10 = PyTuple_New(1); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1084; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_10 = PyTuple_New(1); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1077; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_10); PyTuple_SET_ITEM(__pyx_t_10, 0, __pyx_t_8); __Pyx_GIVEREF(__pyx_t_8); __pyx_t_8 = 0; - __pyx_t_8 = PyObject_Call(__pyx_t_9, __pyx_t_10, NULL); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1084; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = PyObject_Call(__pyx_t_9, __pyx_t_10, NULL); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1077; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_8); __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; __Pyx_DECREF(__pyx_t_10); __pyx_t_10 = 0; - __pyx_t_10 = PyObject_GetAttr(__pyx_t_8, __pyx_n_s__eps); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1084; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_10 = PyObject_GetAttr(__pyx_t_8, __pyx_n_s__eps); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1077; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_10); __Pyx_DECREF(__pyx_t_8); __pyx_t_8 = 0; - __pyx_t_8 = PyNumber_Multiply(__pyx_t_10, __pyx_int_100); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1084; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = PyNumber_Multiply(__pyx_t_10, __pyx_int_100); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1077; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_8); __Pyx_DECREF(__pyx_t_10); __pyx_t_10 = 0; __Pyx_DECREF(__pyx_v_eps); @@ -5472,8 +5463,8 @@ __pyx_v_i = __pyx_t_12; - __pyx_t_7 = __pyx_PyFloat_AsDouble(__pyx_v_eps); if (unlikely((__pyx_t_7 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1092; __pyx_clineno = __LINE__; goto __pyx_L7;} - __pyx_v_isimplex = __pyx_f_5scipy_7spatial_5qhull__find_simplex(__pyx_v_info, __pyx_v_c, (((double *)__pyx_v_xi->data) + (__pyx_v_i * __pyx_v_ndim)), (&__pyx_v_start), __pyx_t_7); + __pyx_t_7 = __pyx_PyFloat_AsDouble(__pyx_v_eps); if (unlikely((__pyx_t_7 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1085; __pyx_clineno = __LINE__; goto __pyx_L7;} + __pyx_v_isimplex = __pyx_f_5scipy_7spatial_5qhull__find_simplex((&__pyx_v_info), __pyx_v_c, (((double *)__pyx_v_xi->data) + (__pyx_v_i * __pyx_v_ndim)), (&__pyx_v_start), __pyx_t_7); __pyx_t_17 = (__pyx_v_isimplex == -1); @@ -5547,7 +5538,7 @@ } - __pyx_v_w = __pyx_f_8interpnd__clough_tocher_2d_single_double(__pyx_v_info, __pyx_v_isimplex, __pyx_v_c, __pyx_v_f, __pyx_v_df); + __pyx_v_w = __pyx_f_8interpnd__clough_tocher_2d_single_double((&__pyx_v_info), __pyx_v_isimplex, __pyx_v_c, __pyx_v_f, __pyx_v_df); __pyx_t_23 = __pyx_v_i; @@ -5574,9 +5565,6 @@ } - free(((void *)__pyx_v_info)); - - __Pyx_XDECREF(__pyx_r); __Pyx_INCREF(((PyObject *)__pyx_v_out)); __pyx_r = ((PyObject *)__pyx_v_out); @@ -5645,7 +5633,7 @@ int __pyx_v_isimplex; int __pyx_v_start; int __pyx_v_nvalues; - __pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t *__pyx_v_info; + __pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t __pyx_v_info; PyObject *__pyx_v_eps; Py_buffer __pyx_bstruct_xi; Py_ssize_t __pyx_bstride_0_xi = 0; @@ -5758,11 +5746,11 @@ values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__xi); if (likely(values[1])) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("_evaluate_complex", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1117; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("_evaluate_complex", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1109; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "_evaluate_complex") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1117; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "_evaluate_complex") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1109; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } __pyx_v_self = values[0]; __pyx_v_xi = ((PyArrayObject *)values[1]); @@ -5774,7 +5762,7 @@ } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; - __Pyx_RaiseArgtupleInvalid("_evaluate_complex", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1117; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("_evaluate_complex", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1109; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_L3_error:; __Pyx_AddTraceback("interpnd.CloughTocher2DInterpolator._evaluate_complex"); __Pyx_RefNannyFinishContext(); @@ -5788,24 +5776,24 @@ __pyx_bstruct_points.buf = NULL; __pyx_bstruct_vertices.buf = NULL; __pyx_bstruct_xi.buf = NULL; - if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_xi), __pyx_ptype_5numpy_ndarray, 1, "xi", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1117; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_xi), __pyx_ptype_5numpy_ndarray, 1, "xi", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1109; __pyx_clineno = __LINE__; goto __pyx_L1_error;} { __Pyx_BufFmt_StackElem __pyx_stack[1]; - if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_xi, (PyObject*)__pyx_v_xi, &__Pyx_TypeInfo_nn___pyx_t_5numpy_double_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1117; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_xi, (PyObject*)__pyx_v_xi, &__Pyx_TypeInfo_nn___pyx_t_5numpy_double_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1109; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_bstride_0_xi = __pyx_bstruct_xi.strides[0]; __pyx_bstride_1_xi = __pyx_bstruct_xi.strides[1]; __pyx_bshape_0_xi = __pyx_bstruct_xi.shape[0]; __pyx_bshape_1_xi = __pyx_bstruct_xi.shape[1]; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__values); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1118; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__values); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1110; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1118; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1110; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_2 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[2]; if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_values, (PyObject*)__pyx_t_2, &__Pyx_TypeInfo_nn___pyx_t_5numpy_complex_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) { __pyx_v_values = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_bstruct_values.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1118; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1110; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_bstride_0_values = __pyx_bstruct_values.strides[0]; __pyx_bstride_1_values = __pyx_bstruct_values.strides[1]; __pyx_bshape_0_values = __pyx_bstruct_values.shape[0]; 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__pyx_lineno = 1132; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_10); __Pyx_DECREF(__pyx_t_8); __pyx_t_8 = 0; - __pyx_t_8 = PyNumber_Multiply(__pyx_t_10, __pyx_int_100); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1140; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = PyNumber_Multiply(__pyx_t_10, __pyx_int_100); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1132; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_8); __Pyx_DECREF(__pyx_t_10); __pyx_t_10 = 0; __Pyx_DECREF(__pyx_v_eps); @@ -6001,8 +5989,8 @@ __pyx_v_i = __pyx_t_12; - __pyx_t_17 = __pyx_PyFloat_AsDouble(__pyx_v_eps); if (unlikely((__pyx_t_17 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1148; __pyx_clineno = __LINE__; goto __pyx_L7;} - __pyx_v_isimplex = __pyx_f_5scipy_7spatial_5qhull__find_simplex(__pyx_v_info, __pyx_v_c, (((double *)__pyx_v_xi->data) + (__pyx_v_i * __pyx_v_ndim)), (&__pyx_v_start), __pyx_t_17); 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if (!__pyx_builtin_object) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 50; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_builtin_Warning = __Pyx_GetName(__pyx_b, __pyx_n_s__Warning); if (!__pyx_builtin_Warning) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 305; __pyx_clineno = __LINE__; goto __pyx_L1_error;} - __pyx_builtin_ValueError = __Pyx_GetName(__pyx_b, __pyx_n_s__ValueError); if (!__pyx_builtin_ValueError) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 97; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_object = __Pyx_GetName(__pyx_b, __pyx_n_s__object); if (!__pyx_builtin_object) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_Warning = __Pyx_GetName(__pyx_b, __pyx_n_s__Warning); if (!__pyx_builtin_Warning) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 299; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_ValueError = __Pyx_GetName(__pyx_b, __pyx_n_s__ValueError); if (!__pyx_builtin_ValueError) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 93; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #if PY_MAJOR_VERSION >= 3 - __pyx_builtin_xrange = __Pyx_GetName(__pyx_b, __pyx_n_s__range); if (!__pyx_builtin_xrange) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_xrange = __Pyx_GetName(__pyx_b, __pyx_n_s__range); if (!__pyx_builtin_xrange) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 143; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #else - __pyx_builtin_xrange = __Pyx_GetName(__pyx_b, __pyx_n_s__xrange); if (!__pyx_builtin_xrange) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_xrange = __Pyx_GetName(__pyx_b, __pyx_n_s__xrange); if (!__pyx_builtin_xrange) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 143; __pyx_clineno = __LINE__; goto __pyx_L1_error;} #endif - __pyx_builtin_enumerate = __Pyx_GetName(__pyx_b, __pyx_n_s__enumerate); if (!__pyx_builtin_enumerate) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 151; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_builtin_enumerate = __Pyx_GetName(__pyx_b, __pyx_n_s__enumerate); if (!__pyx_builtin_enumerate) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_builtin_range = __Pyx_GetName(__pyx_b, __pyx_n_s__range); if (!__pyx_builtin_range) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 219; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_builtin_RuntimeError = __Pyx_GetName(__pyx_b, __pyx_n_s__RuntimeError); if (!__pyx_builtin_RuntimeError) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 787; __pyx_clineno = __LINE__; goto __pyx_L1_error;} return 0; @@ -7574,7 +7559,7 @@ __pyx_ptype_5numpy_ufunc = __Pyx_ImportType("numpy", "ufunc", sizeof(PyUFuncObject), 0); if (unlikely(!__pyx_ptype_5numpy_ufunc)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 849; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_1 = __Pyx_ImportModule("scipy.spatial.qhull"); if (!__pyx_t_1) {__pyx_filename = __pyx_f[0]; 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__pyx_lineno = 1109; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; - if (PyObject_SetAttr(__pyx_m, __pyx_n_s_30, __pyx_t_5) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 991; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyObject_SetAttr(__pyx_m, __pyx_n_s_30, __pyx_t_5) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 984; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; __Pyx_DECREF(((PyObject *)__pyx_t_3)); __pyx_t_3 = 0; Modified: trunk/scipy/spatial/qhull.c =================================================================== --- trunk/scipy/spatial/qhull.c 2011-02-20 16:53:10 UTC (rev 7165) +++ trunk/scipy/spatial/qhull.c 2011-02-20 16:53:20 UTC (rev 7166) @@ -196,9 +196,9 @@ #endif #include #define __PYX_HAVE_API__scipy__spatial__qhull -#include "stdlib.h" #include "numpy/ndarrayobject.h" #include "stdio.h" +#include "stdlib.h" #include "numpy/arrayobject.h" #include "numpy/ufuncobject.h" #include "math.h" @@ -410,7 +410,7 @@ PyObject_HEAD __pyx_t_5scipy_7spatial_5qhull_RidgeIter2D_t it; PyObject *delaunay; - __pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t *info; + __pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t info; }; #ifndef CYTHON_REFNANNY @@ -769,7 +769,7 @@ static PyTypeObject *__pyx_ptype_5scipy_7spatial_5qhull_RidgeIter2D = 0; -static __pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t *__pyx_f_5scipy_7spatial_5qhull__get_delaunay_info(PyObject *, int, int); +static void __pyx_f_5scipy_7spatial_5qhull__get_delaunay_info(__pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t *, PyObject *, int, int); static int __pyx_f_5scipy_7spatial_5qhull__barycentric_inside(int, double *, double *, double *, double); static void __pyx_f_5scipy_7spatial_5qhull__barycentric_coordinate_single(int, double *, double *, double *, int); static void __pyx_f_5scipy_7spatial_5qhull__barycentric_coordinates(int, double *, double *, double *); @@ -816,13 +816,13 @@ static char __pyx_k_21[] = "_construct_delaunay (line 134)"; static char __pyx_k_22[] = "_qhull_get_facet_array (line 197)"; static char __pyx_k_23[] = "_get_barycentric_transforms (line 278)"; 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__pyx_lineno = 975; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_GetAttr(__pyx_t_1, __pyx_n_s__empty); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 968; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__npoints); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 975; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__npoints); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 968; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_4 = PyTuple_New(1); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 975; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = PyTuple_New(1); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 968; __pyx_clineno = __LINE__; 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__pyx_lineno = 975; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_5 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 968; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_5); - __pyx_t_6 = PyObject_GetAttr(__pyx_t_5, __pyx_n_s__intc); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 975; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyObject_GetAttr(__pyx_t_5, __pyx_n_s__intc); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 968; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; - if (PyDict_SetItem(__pyx_t_4, ((PyObject *)__pyx_n_s__dtype), __pyx_t_6) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 975; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_t_4, ((PyObject *)__pyx_n_s__dtype), __pyx_t_6) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 968; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; - __pyx_t_6 = PyEval_CallObjectWithKeywords(__pyx_t_3, __pyx_t_1, ((PyObject *)__pyx_t_4)); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 975; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyEval_CallObjectWithKeywords(__pyx_t_3, __pyx_t_1, ((PyObject *)__pyx_t_4)); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 968; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0; - if (PyObject_SetAttr(__pyx_v_self, __pyx_n_s___vertex_to_simplex, __pyx_t_6) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 975; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyObject_SetAttr(__pyx_v_self, __pyx_n_s___vertex_to_simplex, __pyx_t_6) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 968; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; - __pyx_t_6 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s___vertex_to_simplex); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 976; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s___vertex_to_simplex); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 969; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); - __pyx_t_4 = PyObject_GetAttr(__pyx_t_6, __pyx_n_s__fill); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 976; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = PyObject_GetAttr(__pyx_t_6, __pyx_n_s__fill); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 969; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; - __pyx_t_6 = PyTuple_New(1); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 976; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_6 = PyTuple_New(1); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 969; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_6); __Pyx_INCREF(__pyx_int_neg_1); PyTuple_SET_ITEM(__pyx_t_6, 0, __pyx_int_neg_1); __Pyx_GIVEREF(__pyx_int_neg_1); - __pyx_t_1 = PyObject_Call(__pyx_t_4, __pyx_t_6, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 976; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_Call(__pyx_t_4, __pyx_t_6, NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 969; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s___vertex_to_simplex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 978; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s___vertex_to_simplex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 971; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 978; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 971; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_7 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; @@ -4435,7 +4398,7 @@ } __pyx_bstride_0_arr = __pyx_bstruct_arr.strides[0]; __pyx_bshape_0_arr = __pyx_bstruct_arr.shape[0]; - if (unlikely(__pyx_t_8 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 978; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__pyx_t_8 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 971; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_7 = 0; __Pyx_DECREF(((PyObject *)__pyx_v_arr)); @@ -4443,9 +4406,9 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__vertices); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 979; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__vertices); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 972; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 979; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 972; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_12 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; @@ -4462,7 +4425,7 @@ } __pyx_bstride_0_vertices = __pyx_bstruct_vertices.strides[0]; __pyx_bstride_1_vertices = __pyx_bstruct_vertices.strides[1]; __pyx_bshape_0_vertices = __pyx_bstruct_vertices.shape[0]; __pyx_bshape_1_vertices = __pyx_bstruct_vertices.shape[1]; - if (unlikely(__pyx_t_8 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 979; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__pyx_t_8 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 972; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_12 = 0; __Pyx_DECREF(((PyObject *)__pyx_v_vertices)); @@ -4470,16 +4433,16 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__nsimplex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 981; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__nsimplex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 974; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_8 = __Pyx_PyInt_AsInt(__pyx_t_1); if (unlikely((__pyx_t_8 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 981; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = __Pyx_PyInt_AsInt(__pyx_t_1); if (unlikely((__pyx_t_8 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 974; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __pyx_v_nsimplex = __pyx_t_8; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__ndim); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 982; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__ndim); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 975; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_8 = __Pyx_PyInt_AsInt(__pyx_t_1); if (unlikely((__pyx_t_8 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 982; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = __Pyx_PyInt_AsInt(__pyx_t_1); if (unlikely((__pyx_t_8 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 975; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __pyx_v_ndim = __pyx_t_8; @@ -4507,7 +4470,7 @@ } else if (unlikely(__pyx_t_17 >= __pyx_bshape_1_vertices)) __pyx_t_18 = 1; if (unlikely(__pyx_t_18 != -1)) { __Pyx_RaiseBufferIndexError(__pyx_t_18); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 986; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 979; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_v_ivertex = (*__Pyx_BufPtrStrided2d(npy_int *, __pyx_bstruct_vertices.buf, __pyx_t_16, __pyx_bstride_0_vertices, __pyx_t_17, __pyx_bstride_1_vertices)); @@ -4520,7 +4483,7 @@ } else if (unlikely(__pyx_t_18 >= __pyx_bshape_0_arr)) __pyx_t_19 = 0; if (unlikely(__pyx_t_19 != -1)) { __Pyx_RaiseBufferIndexError(__pyx_t_19); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 987; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 980; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_2 = ((*__Pyx_BufPtrStrided1d(npy_int *, __pyx_bstruct_arr.buf, __pyx_t_18, __pyx_bstride_0_arr)) == -1); if (__pyx_t_2) { @@ -4534,7 +4497,7 @@ } else if (unlikely(__pyx_t_19 >= __pyx_bshape_0_arr)) __pyx_t_20 = 0; if (unlikely(__pyx_t_20 != -1)) { __Pyx_RaiseBufferIndexError(__pyx_t_20); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 988; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 981; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } *__Pyx_BufPtrStrided1d(npy_int *, __pyx_bstruct_arr.buf, __pyx_t_19, __pyx_bstride_0_arr) = __pyx_v_isimplex; goto __pyx_L10; @@ -4548,7 +4511,7 @@ __Pyx_XDECREF(__pyx_r); - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s___vertex_to_simplex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 990; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s___vertex_to_simplex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 983; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); __pyx_r = __pyx_t_1; __pyx_t_1 = 0; @@ -4653,9 +4616,9 @@ __pyx_bstruct_vertices.buf = NULL; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__neighbors); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1010; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__neighbors); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1003; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1010; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1003; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_2 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; @@ -4672,7 +4635,7 @@ } __pyx_bstride_0_neighbors = __pyx_bstruct_neighbors.strides[0]; __pyx_bstride_1_neighbors = __pyx_bstruct_neighbors.strides[1]; __pyx_bshape_0_neighbors = __pyx_bstruct_neighbors.shape[0]; __pyx_bshape_1_neighbors = __pyx_bstruct_neighbors.shape[1]; - if (unlikely(__pyx_t_3 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1010; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__pyx_t_3 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1003; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_2 = 0; __Pyx_DECREF(((PyObject *)__pyx_v_neighbors)); @@ -4680,9 +4643,9 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__vertices); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1011; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__vertices); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1004; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1011; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1004; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_7 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; @@ -4699,7 +4662,7 @@ } __pyx_bstride_0_vertices = __pyx_bstruct_vertices.strides[0]; __pyx_bstride_1_vertices = __pyx_bstruct_vertices.strides[1]; __pyx_bshape_0_vertices = __pyx_bstruct_vertices.shape[0]; __pyx_bshape_1_vertices = __pyx_bstruct_vertices.shape[1]; - if (unlikely(__pyx_t_3 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1011; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__pyx_t_3 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1004; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_7 = 0; __Pyx_DECREF(((PyObject *)__pyx_v_vertices)); @@ -4707,16 +4670,16 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__ndim); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1012; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__ndim); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1005; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_3 = __Pyx_PyInt_AsInt(__pyx_t_1); if (unlikely((__pyx_t_3 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1012; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_AsInt(__pyx_t_1); if (unlikely((__pyx_t_3 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1005; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __pyx_v_ndim = __pyx_t_3; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__nsimplex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1013; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__nsimplex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1006; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_3 = __Pyx_PyInt_AsInt(__pyx_t_1); if (unlikely((__pyx_t_3 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1013; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = __Pyx_PyInt_AsInt(__pyx_t_1); if (unlikely((__pyx_t_3 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1006; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __pyx_v_nsimplex = __pyx_t_3; @@ -4724,16 +4687,16 @@ __pyx_v_msize = 10; - __pyx_t_1 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1016; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1009; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_8 = PyObject_GetAttr(__pyx_t_1, __pyx_n_s__empty); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1016; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_8 = PyObject_GetAttr(__pyx_t_1, __pyx_n_s__empty); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1009; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_8); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - __pyx_t_1 = PyInt_FromLong(__pyx_v_msize); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1016; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyInt_FromLong(__pyx_v_msize); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1009; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_9 = PyInt_FromLong(__pyx_v_ndim); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1016; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_9 = PyInt_FromLong(__pyx_v_ndim); if (unlikely(!__pyx_t_9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1009; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_9); - __pyx_t_10 = PyTuple_New(2); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1016; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_10 = PyTuple_New(2); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1009; __pyx_clineno = __LINE__; 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if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1016; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1009; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_11 = PyObject_GetAttr(__pyx_t_1, __pyx_n_s__intc); if (unlikely(!__pyx_t_11)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1016; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_11 = PyObject_GetAttr(__pyx_t_1, __pyx_n_s__intc); if (unlikely(!__pyx_t_11)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1009; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_11); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - if (PyDict_SetItem(__pyx_t_10, ((PyObject *)__pyx_n_s__dtype), __pyx_t_11) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1016; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_t_10, ((PyObject *)__pyx_n_s__dtype), __pyx_t_11) < 0) {__pyx_filename = __pyx_f[0]; 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goto __pyx_L1_error;} + if (unlikely(__pyx_t_20 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1024; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_12 = 0; __Pyx_INCREF(Py_None); @@ -4886,13 +4849,13 @@ __pyx_v_msize = ((2 * __pyx_v_msize) + 1); - __pyx_t_11 = PyObject_GetAttr(__pyx_v_out, __pyx_n_s__resize); if (unlikely(!__pyx_t_11)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1033; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_11 = PyObject_GetAttr(__pyx_v_out, __pyx_n_s__resize); if (unlikely(!__pyx_t_11)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1026; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_11); - __pyx_t_10 = PyInt_FromLong(__pyx_v_msize); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1033; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_10 = PyInt_FromLong(__pyx_v_msize); if (unlikely(!__pyx_t_10)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1026; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_10); 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__pyx_t_10 = 0; @@ -5030,7 +4993,7 @@ PyObject *__pyx_v_self = 0; PyObject *__pyx_v_xi = 0; PyObject *__pyx_v_bruteforce = 0; - __pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t *__pyx_v_info; + __pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t __pyx_v_info; int __pyx_v_isimplex; double __pyx_v_c[NPY_MAXDIMS]; double __pyx_v_eps; @@ -5089,7 +5052,7 @@ values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__xi); if (likely(values[1])) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("find_simplex", 0, 2, 3, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1040; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("find_simplex", 0, 2, 3, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1033; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } case 2: if (kw_args > 0) { @@ -5098,7 +5061,7 @@ } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "find_simplex") < 0)) {__pyx_filename = __pyx_f[0]; 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__pyx_lineno = 1091; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_12 = PyObject_GetAttr(__pyx_t_1, __pyx_n_s__intc); if (unlikely(!__pyx_t_12)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1084; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_12); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - if (PyDict_SetItem(__pyx_t_2, ((PyObject *)__pyx_n_s__dtype), __pyx_t_12) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1091; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_t_2, ((PyObject *)__pyx_n_s__dtype), __pyx_t_12) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1084; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_12); __pyx_t_12 = 0; - __pyx_t_12 = PyEval_CallObjectWithKeywords(__pyx_t_5, __pyx_t_3, ((PyObject *)__pyx_t_2)); if (unlikely(!__pyx_t_12)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1091; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_12 = PyEval_CallObjectWithKeywords(__pyx_t_5, __pyx_t_3, ((PyObject *)__pyx_t_2)); if (unlikely(!__pyx_t_12)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1084; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_12); __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; @@ -5360,7 +5323,7 @@ __pyx_t_12 = 0; - if (!(likely(((__pyx_v_out) == Py_None) || likely(__Pyx_TypeTest(__pyx_v_out, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1092; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_v_out) == Py_None) || likely(__Pyx_TypeTest(__pyx_v_out, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1085; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_13 = ((PyArrayObject *)__pyx_v_out); { __Pyx_BufFmt_StackElem __pyx_stack[1]; @@ -5377,7 +5340,7 @@ } __pyx_bstride_0_out_ = __pyx_bstruct_out_.strides[0]; __pyx_bshape_0_out_ = __pyx_bstruct_out_.shape[0]; - if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1092; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1085; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_13 = 0; __Pyx_INCREF(__pyx_v_out); @@ -5385,10 +5348,10 @@ __pyx_v_out_ = ((PyArrayObject *)__pyx_v_out); - __pyx_v_info = __pyx_f_5scipy_7spatial_5qhull__get_delaunay_info(__pyx_v_self, 1, 0); + __pyx_f_5scipy_7spatial_5qhull__get_delaunay_info((&__pyx_v_info), __pyx_v_self, 1, 0); - __pyx_t_4 = __Pyx_PyObject_IsTrue(__pyx_v_bruteforce); if (unlikely(__pyx_t_4 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1095; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_4 = __Pyx_PyObject_IsTrue(__pyx_v_bruteforce); if (unlikely(__pyx_t_4 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1088; __pyx_clineno = __LINE__; goto __pyx_L1_error;} if (__pyx_t_4) { @@ -5397,7 +5360,7 @@ __pyx_v_k = __pyx_t_7; - __pyx_v_isimplex = __pyx_f_5scipy_7spatial_5qhull__find_simplex_bruteforce(__pyx_v_info, __pyx_v_c, (((double *)__pyx_v_x->data) + (__pyx_v_info->ndim * __pyx_v_k)), __pyx_v_eps); + __pyx_v_isimplex = __pyx_f_5scipy_7spatial_5qhull__find_simplex_bruteforce((&__pyx_v_info), __pyx_v_c, (((double *)__pyx_v_x->data) + (__pyx_v_info.ndim * __pyx_v_k)), __pyx_v_eps); __pyx_t_15 = __pyx_v_k; @@ -5408,7 +5371,7 @@ } else if (unlikely(__pyx_t_15 >= __pyx_bshape_0_out_)) __pyx_t_16 = 0; if (unlikely(__pyx_t_16 != -1)) { __Pyx_RaiseBufferIndexError(__pyx_t_16); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1101; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1094; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } *__Pyx_BufPtrStrided1d(npy_int *, __pyx_bstruct_out_.buf, __pyx_t_15, __pyx_bstride_0_out_) = __pyx_v_isimplex; } @@ -5422,7 +5385,7 @@ __pyx_v_k = __pyx_t_7; - __pyx_v_isimplex = __pyx_f_5scipy_7spatial_5qhull__find_simplex(__pyx_v_info, __pyx_v_c, (((double *)__pyx_v_x->data) + (__pyx_v_info->ndim * __pyx_v_k)), (&__pyx_v_start), __pyx_v_eps); + __pyx_v_isimplex = __pyx_f_5scipy_7spatial_5qhull__find_simplex((&__pyx_v_info), __pyx_v_c, (((double *)__pyx_v_x->data) + (__pyx_v_info.ndim * __pyx_v_k)), (&__pyx_v_start), __pyx_v_eps); __pyx_t_16 = __pyx_v_k; @@ -5433,7 +5396,7 @@ } else if (unlikely(__pyx_t_16 >= __pyx_bshape_0_out_)) __pyx_t_17 = 0; if (unlikely(__pyx_t_17 != -1)) { __Pyx_RaiseBufferIndexError(__pyx_t_17); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1106; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1099; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } *__Pyx_BufPtrStrided1d(npy_int *, __pyx_bstruct_out_.buf, __pyx_t_16, __pyx_bstride_0_out_) = __pyx_v_isimplex; } @@ -5441,20 +5404,17 @@ __pyx_L7:; - free(__pyx_v_info); - - __Pyx_XDECREF(__pyx_r); - __pyx_t_12 = PyObject_GetAttr(__pyx_v_out, __pyx_n_s__reshape); if (unlikely(!__pyx_t_12)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1110; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_12 = PyObject_GetAttr(__pyx_v_out, __pyx_n_s__reshape); if (unlikely(!__pyx_t_12)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1101; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_12); - __pyx_t_2 = PySequence_GetSlice(__pyx_v_xi_shape, 0, -1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1110; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PySequence_GetSlice(__pyx_v_xi_shape, 0, -1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1101; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); - __pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1110; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1101; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); PyTuple_SET_ITEM(__pyx_t_3, 0, __pyx_t_2); __Pyx_GIVEREF(__pyx_t_2); __pyx_t_2 = 0; - __pyx_t_2 = PyObject_Call(__pyx_t_12, __pyx_t_3, NULL); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1110; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyObject_Call(__pyx_t_12, __pyx_t_3, NULL); 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__pyx_lineno = 1135; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyDict_SetItem(__pyx_t_2, ((PyObject *)__pyx_n_s__dtype), __pyx_t_11) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1126; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_11); __pyx_t_11 = 0; - __pyx_t_11 = PyEval_CallObjectWithKeywords(__pyx_t_1, __pyx_t_3, ((PyObject *)__pyx_t_2)); if (unlikely(!__pyx_t_11)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1135; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_11 = PyEval_CallObjectWithKeywords(__pyx_t_1, __pyx_t_3, ((PyObject *)__pyx_t_2)); if (unlikely(!__pyx_t_11)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1126; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_11); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; @@ -5770,7 +5730,7 @@ __pyx_t_11 = 0; - if (!(likely(((__pyx_v_out) == Py_None) || likely(__Pyx_TypeTest(__pyx_v_out, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1136; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_v_out) == Py_None) || likely(__Pyx_TypeTest(__pyx_v_out, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1127; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_12 = ((PyArrayObject *)__pyx_v_out); { __Pyx_BufFmt_StackElem __pyx_stack[1]; @@ -5787,7 +5747,7 @@ } __pyx_bstride_0_out_ = __pyx_bstruct_out_.strides[0]; __pyx_bstride_1_out_ = __pyx_bstruct_out_.strides[1]; __pyx_bshape_0_out_ = __pyx_bstruct_out_.shape[0]; __pyx_bshape_1_out_ = __pyx_bstruct_out_.shape[1]; - if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1136; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1127; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } __pyx_t_12 = 0; __Pyx_INCREF(__pyx_v_out); @@ -5800,12 +5760,12 @@ __pyx_v_i = __pyx_t_7; - __pyx_t_14 = __pyx_v_info->nsimplex; + __pyx_t_14 = __pyx_v_info.nsimplex; for (__pyx_t_15 = 0; __pyx_t_15 < __pyx_t_14; __pyx_t_15+=1) { __pyx_v_j = __pyx_t_15; - __pyx_f_5scipy_7spatial_5qhull__lift_point(__pyx_v_info, (((double *)__pyx_v_x->data) + (__pyx_v_info->ndim * __pyx_v_i)), __pyx_v_z); + __pyx_f_5scipy_7spatial_5qhull__lift_point((&__pyx_v_info), (((double *)__pyx_v_x->data) + (__pyx_v_info.ndim * __pyx_v_i)), __pyx_v_z); __pyx_t_16 = __pyx_v_i; @@ -5821,38 +5781,35 @@ } else if (unlikely(__pyx_t_17 >= __pyx_bshape_1_out_)) __pyx_t_18 = 1; if (unlikely(__pyx_t_18 != -1)) { __Pyx_RaiseBufferIndexError(__pyx_t_18); - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1141; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1132; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } - *__Pyx_BufPtrStrided2d(__pyx_t_5numpy_double_t *, __pyx_bstruct_out_.buf, __pyx_t_16, __pyx_bstride_0_out_, __pyx_t_17, __pyx_bstride_1_out_) = __pyx_f_5scipy_7spatial_5qhull__distplane(__pyx_v_info, __pyx_v_j, __pyx_v_z); + *__Pyx_BufPtrStrided2d(__pyx_t_5numpy_double_t *, __pyx_bstruct_out_.buf, __pyx_t_16, __pyx_bstride_0_out_, __pyx_t_17, __pyx_bstride_1_out_) = __pyx_f_5scipy_7spatial_5qhull__distplane((&__pyx_v_info), __pyx_v_j, __pyx_v_z); } } - free(__pyx_v_info); - - __Pyx_XDECREF(__pyx_r); - __pyx_t_11 = PyObject_GetAttr(__pyx_v_out, __pyx_n_s__reshape); if (unlikely(!__pyx_t_11)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_11 = PyObject_GetAttr(__pyx_v_out, __pyx_n_s__reshape); if (unlikely(!__pyx_t_11)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1134; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_11); - __pyx_t_2 = PySequence_GetSlice(__pyx_v_xi_shape, 0, -1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PySequence_GetSlice(__pyx_v_xi_shape, 0, -1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1134; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); - __pyx_t_3 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__nsimplex); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_GetAttr(__pyx_v_self, __pyx_n_s__nsimplex); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1134; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); - __pyx_t_1 = PyTuple_New(1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyTuple_New(1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1134; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); PyTuple_SET_ITEM(__pyx_t_1, 0, __pyx_t_3); __Pyx_GIVEREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyNumber_Add(__pyx_t_2, __pyx_t_1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyNumber_Add(__pyx_t_2, __pyx_t_1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1134; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; - __pyx_t_1 = PyTuple_New(1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyTuple_New(1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1134; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); PyTuple_SET_ITEM(__pyx_t_1, 0, __pyx_t_3); __Pyx_GIVEREF(__pyx_t_3); __pyx_t_3 = 0; - __pyx_t_3 = PyObject_Call(__pyx_t_11, __pyx_t_1, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1145; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_Call(__pyx_t_11, __pyx_t_1, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1134; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_11); __pyx_t_11 = 0; __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; @@ -5926,11 +5883,11 @@ values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__x); if (likely(values[1])) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("lift_points", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1147; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("lift_points", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1136; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "lift_points") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1147; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "lift_points") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1136; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } __pyx_v_tri = values[0]; __pyx_v_x = values[1]; @@ -5942,7 +5899,7 @@ } goto __pyx_L4_argument_unpacking_done; 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__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0; - if (PyObject_SetItem(__pyx_v_z, __pyx_t_2, __pyx_t_4) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1158; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyObject_SetItem(__pyx_v_z, __pyx_t_2, __pyx_t_4) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1147; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; @@ -6137,11 +6094,11 @@ values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__xi); if (likely(values[1])) kw_args--; else { - __Pyx_RaiseArgtupleInvalid("tsearch", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1162; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("tsearch", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1151; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } } if (unlikely(kw_args > 0)) { - if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "tsearch") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1162; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, PyTuple_GET_SIZE(__pyx_args), "tsearch") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1151; __pyx_clineno = __LINE__; goto __pyx_L3_error;} } __pyx_v_tri = values[0]; __pyx_v_xi = values[1]; @@ -6153,7 +6110,7 @@ } goto __pyx_L4_argument_unpacking_done; __pyx_L5_argtuple_error:; - __Pyx_RaiseArgtupleInvalid("tsearch", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1162; __pyx_clineno = __LINE__; goto __pyx_L3_error;} + __Pyx_RaiseArgtupleInvalid("tsearch", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1151; __pyx_clineno = __LINE__; goto __pyx_L3_error;} __pyx_L3_error:; __Pyx_AddTraceback("scipy.spatial.qhull.tsearch"); __Pyx_RefNannyFinishContext(); @@ -6162,14 +6119,14 @@ __Pyx_XDECREF(__pyx_r); - __pyx_t_1 = PyObject_GetAttr(__pyx_v_tri, __pyx_n_s__find_simplex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1176; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_tri, __pyx_n_s__find_simplex); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1165; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - __pyx_t_2 = PyTuple_New(1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1176; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_2 = PyTuple_New(1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1165; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_2); __Pyx_INCREF(__pyx_v_xi); PyTuple_SET_ITEM(__pyx_t_2, 0, __pyx_v_xi); __Pyx_GIVEREF(__pyx_v_xi); - __pyx_t_3 = PyObject_Call(__pyx_t_1, __pyx_t_2, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1176; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_3 = PyObject_Call(__pyx_t_1, __pyx_t_2, NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1165; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_3); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; @@ -6193,8 +6150,7 @@ -static __pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t *__pyx_f_5scipy_7spatial_5qhull__get_delaunay_info(PyObject *__pyx_v_obj, int __pyx_v_compute_transform, int __pyx_v_compute_vertex_to_simplex) { - __pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t *__pyx_v_info; +static void __pyx_f_5scipy_7spatial_5qhull__get_delaunay_info(__pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t *__pyx_v_info, PyObject *__pyx_v_obj, int __pyx_v_compute_transform, int __pyx_v_compute_vertex_to_simplex) { PyArrayObject *__pyx_v_transform; PyArrayObject *__pyx_v_vertex_to_simplex; PyArrayObject *__pyx_v_points = 0; @@ -6239,7 +6195,6 @@ Py_ssize_t __pyx_bstride_1_equations = 0; Py_ssize_t __pyx_bshape_0_equations = 0; Py_ssize_t __pyx_bshape_1_equations = 0; - __pyx_t_5scipy_7spatial_5qhull_DelaunayInfo_t *__pyx_r; PyObject *__pyx_t_1 = NULL; PyArrayObject *__pyx_t_2 = NULL; PyArrayObject *__pyx_t_3 = NULL; @@ -6267,15 +6222,15 @@ __pyx_bstruct_max_bound.buf = NULL; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_obj, __pyx_n_s__points); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1189; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_obj, __pyx_n_s__points); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1178; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1189; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1178; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_2 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_points, (PyObject*)__pyx_t_2, &__Pyx_TypeInfo_nn___pyx_t_5numpy_double_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) { __pyx_v_points = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_bstruct_points.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1189; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1178; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_bstride_0_points = __pyx_bstruct_points.strides[0]; __pyx_bstride_1_points = __pyx_bstruct_points.strides[1]; __pyx_bshape_0_points = __pyx_bstruct_points.shape[0]; __pyx_bshape_1_points = __pyx_bstruct_points.shape[1]; } @@ -6285,15 +6240,15 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_obj, __pyx_n_s__vertices); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1190; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_obj, __pyx_n_s__vertices); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1179; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1190; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1179; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_3 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_vertices, (PyObject*)__pyx_t_3, &__Pyx_TypeInfo_nn_npy_int, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) { __pyx_v_vertices = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_bstruct_vertices.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1190; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1179; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_bstride_0_vertices = __pyx_bstruct_vertices.strides[0]; __pyx_bstride_1_vertices = __pyx_bstruct_vertices.strides[1]; __pyx_bshape_0_vertices = __pyx_bstruct_vertices.shape[0]; __pyx_bshape_1_vertices = __pyx_bstruct_vertices.shape[1]; } @@ -6303,15 +6258,15 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_obj, __pyx_n_s__neighbors); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1191; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_obj, __pyx_n_s__neighbors); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1180; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1191; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1180; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_4 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_neighbors, (PyObject*)__pyx_t_4, &__Pyx_TypeInfo_nn_npy_int, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) { __pyx_v_neighbors = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_bstruct_neighbors.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1191; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1180; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_bstride_0_neighbors = __pyx_bstruct_neighbors.strides[0]; __pyx_bstride_1_neighbors = __pyx_bstruct_neighbors.strides[1]; __pyx_bshape_0_neighbors = __pyx_bstruct_neighbors.shape[0]; __pyx_bshape_1_neighbors = __pyx_bstruct_neighbors.shape[1]; } @@ -6321,15 +6276,15 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_obj, __pyx_n_s__equations); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1192; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_obj, __pyx_n_s__equations); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1181; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1192; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1181; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_5 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_equations, (PyObject*)__pyx_t_5, &__Pyx_TypeInfo_nn___pyx_t_5numpy_double_t, PyBUF_FORMAT| PyBUF_STRIDES, 2, 0, __pyx_stack) == -1)) { __pyx_v_equations = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_bstruct_equations.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1192; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1181; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_bstride_0_equations = __pyx_bstruct_equations.strides[0]; __pyx_bstride_1_equations = __pyx_bstruct_equations.strides[1]; __pyx_bshape_0_equations = __pyx_bstruct_equations.shape[0]; __pyx_bshape_1_equations = __pyx_bstruct_equations.shape[1]; } @@ -6339,15 +6294,15 @@ __pyx_t_1 = 0; - __pyx_t_1 = PyObject_GetAttr(__pyx_v_obj, __pyx_n_s__min_bound); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1193; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + __pyx_t_1 = PyObject_GetAttr(__pyx_v_obj, __pyx_n_s__min_bound); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1182; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_1); - if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1193; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (!(likely(((__pyx_t_1) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_1, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1182; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __pyx_t_6 = ((PyArrayObject *)__pyx_t_1); { __Pyx_BufFmt_StackElem __pyx_stack[1]; if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_bstruct_min_bound, (PyObject*)__pyx_t_6, &__Pyx_TypeInfo_nn___pyx_t_5numpy_double_t, PyBUF_FORMAT| PyBUF_STRIDES, 1, 0, __pyx_stack) == -1)) { __pyx_v_min_bound = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_bstruct_min_bound.buf = NULL; - {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1193; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1182; __pyx_clineno = __LINE__; goto __pyx_L1_error;} } else {__pyx_bstride_0_min_bound = __pyx_bstruct_min_bound.strides[0]; __pyx_bshape_0_min_bound = __pyx_bstruct_min_bound.shape[0]; } @@ -6357,15 +6312,15 @@ __pyx_t_1 = 0; 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goto __pyx_L1_error;} + __pyx_t_4 = PyMethod_New(__pyx_t_2, 0, __pyx_t_3); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1136; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_GOTREF(__pyx_t_4); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; - if (PyObject_SetAttr(__pyx_t_3, __pyx_n_s__lift_points, __pyx_t_4) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1147; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyObject_SetAttr(__pyx_t_3, __pyx_n_s__lift_points, __pyx_t_4) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1136; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0; - if (PyObject_SetAttr(__pyx_m, __pyx_n_s__Delaunay, __pyx_t_3) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 862; __pyx_clineno = __LINE__; goto __pyx_L1_error;} + if (PyObject_SetAttr(__pyx_m, __pyx_n_s__Delaunay, __pyx_t_3) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 855; __pyx_clineno = __LINE__; goto __pyx_L1_error;} __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0; __Pyx_DECREF(((PyObject *)__pyx_t_1)); __pyx_t_1 = 0; From scipy-svn at scipy.org Sun Feb 20 12:00:52 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 20 Feb 2011 11:00:52 -0600 (CST) Subject: [Scipy-svn] r7167 - trunk/scipy/interpolate Message-ID: <20110220170052.7B3231B89B0@scipy.org> Author: ptvirtan Date: 2011-02-20 11:00:52 -0600 (Sun, 20 Feb 2011) New Revision: 7167 Modified: trunk/scipy/interpolate/ndgriddata.py Log: DOC: interpolate: note that for 1D data, input points must be sorted Modified: trunk/scipy/interpolate/ndgriddata.py =================================================================== --- trunk/scipy/interpolate/ndgriddata.py 2011-02-20 16:53:20 UTC (rev 7166) +++ trunk/scipy/interpolate/ndgriddata.py 2011-02-20 17:00:52 UTC (rev 7167) @@ -76,6 +76,9 @@ points : ndarray of floats, shape (npoints, ndims) Data point coordinates. Can either be a ndarray of size (npoints, ndim), or a tuple of `ndim` arrays. + + For interpolation of 1-D data, the points *must* be sorted + in ascending order. values : ndarray of float or complex, shape (npoints, ...) Data values. xi : ndarray of float, shape (..., ndim) From scipy-svn at scipy.org Sun Feb 20 12:02:32 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 20 Feb 2011 11:02:32 -0600 (CST) Subject: [Scipy-svn] r7168 - branches/0.9.x/scipy/interpolate Message-ID: <20110220170232.D03C81B89B0@scipy.org> Author: ptvirtan Date: 2011-02-20 11:02:32 -0600 (Sun, 20 Feb 2011) New Revision: 7168 Modified: branches/0.9.x/scipy/interpolate/ndgriddata.py Log: DOC: interpolate: note that for 1D data, input points must be sorted Modified: branches/0.9.x/scipy/interpolate/ndgriddata.py =================================================================== --- branches/0.9.x/scipy/interpolate/ndgriddata.py 2011-02-20 17:00:52 UTC (rev 7167) +++ branches/0.9.x/scipy/interpolate/ndgriddata.py 2011-02-20 17:02:32 UTC (rev 7168) @@ -76,6 +76,9 @@ points : ndarray of floats, shape (npoints, ndims) Data point coordinates. Can either be a ndarray of size (npoints, ndim), or a tuple of `ndim` arrays. + + For interpolation of 1-D data, the points *must* be sorted + in ascending order. values : ndarray of float or complex, shape (npoints, ...) Data values. xi : ndarray of float, shape (..., ndim) From scipy-svn at scipy.org Sun Feb 20 18:34:22 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 20 Feb 2011 17:34:22 -0600 (CST) Subject: [Scipy-svn] r7169 - in trunk/scipy/sparse/linalg/eigen/arpack: . tests Message-ID: <20110220233422.6C7206EFDE@scipy.org> Author: ptvirtan Date: 2011-02-20 17:34:21 -0600 (Sun, 20 Feb 2011) New Revision: 7169 Modified: trunk/scipy/sparse/linalg/eigen/arpack/arpack.py trunk/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py Log: BUG: sparse/arpack: raise correct exception if WHICH parameter wrong Thanks to Fabian Pedregosa for the patch. Modified: trunk/scipy/sparse/linalg/eigen/arpack/arpack.py =================================================================== --- trunk/scipy/sparse/linalg/eigen/arpack/arpack.py 2011-02-20 17:02:32 UTC (rev 7168) +++ trunk/scipy/sparse/linalg/eigen/arpack/arpack.py 2011-02-20 23:34:21 UTC (rev 7169) @@ -136,6 +136,13 @@ "DSEUPD.") } +# accepted values of parameter WHICH in _SEUPD +_SEUPD_WHICH = ['LM', 'SM', 'LA', 'SA', 'BE'] + +# accepted values of parameter WHICH in _NAUPD +_NEUPD_WHICH = ['LM', 'SM', 'LR', 'SR', 'LI', 'SI'] + + class ArpackError(RuntimeError): """ ARPACK error @@ -231,8 +238,8 @@ class _SymmetricArpackParams(_ArpackParams): def __init__(self, n, k, tp, matvec, sigma=None, ncv=None, v0=None, maxiter=None, which="LM", tol=0): - if not which in ['LM', 'SM', 'LA', 'SA', 'BE']: - raise ValueError("which must be one of %s" % ' '.join(whiches)) + if which not in _SEUPD_WHICH: + raise ValueError("which must be one of %s" % ' '.join(_SEUPD_WHICH)) if k >= n: raise ValueError("k must be less than rank(A), k=%d" % k) @@ -304,8 +311,8 @@ class _UnsymmetricArpackParams(_ArpackParams): def __init__(self, n, k, tp, matvec, sigma=None, ncv=None, v0=None, maxiter=None, which="LM", tol=0): - if not which in ["LM", "SM", "LR", "SR", "LI", "SI"]: - raise ValueError("Parameter which must be one of %s" % ' '.join(whiches)) + if which not in _NEUPD_WHICH: + raise ValueError("Parameter which must be one of %s" % ' '.join(_NEUPD_WHICH)) if k >= n-1: raise ValueError("k must be less than rank(A)-1, k=%d" % k) Modified: trunk/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py =================================================================== --- trunk/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py 2011-02-20 17:02:32 UTC (rev 7168) +++ trunk/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py 2011-02-20 23:34:21 UTC (rev 7169) @@ -353,6 +353,13 @@ A = csc_matrix(np.zeros((2,3))) assert_raises(ValueError, eigs, A) + +def test_eigen_bad_kwargs(): + # Test eigen on wrong keyword argument + A = csc_matrix(np.zeros((2,2))) + assert_raises(ValueError, eigs, A, which='XX') + + def test_eigs_operator(): # Check inferring LinearOperator dtype fft_op = LinearOperator((6, 6), np.fft.fft) From scipy-svn at scipy.org Mon Feb 21 08:14:32 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Mon, 21 Feb 2011 07:14:32 -0600 (CST) Subject: [Scipy-svn] r7170 - trunk/scipy/weave/tests Message-ID: <20110221131432.11CC16EFE1@scipy.org> Author: rgommers Date: 2011-02-21 07:14:32 -0600 (Mon, 21 Feb 2011) New Revision: 7170 Modified: trunk/scipy/weave/tests/test_catalog.py Log: BUG: fix weave.catalog error on Windows Vista. Thanks to Christoph Gohlke. Modified: trunk/scipy/weave/tests/test_catalog.py =================================================================== --- trunk/scipy/weave/tests/test_catalog.py 2011-02-20 23:34:21 UTC (rev 7169) +++ trunk/scipy/weave/tests/test_catalog.py 2011-02-21 13:14:32 UTC (rev 7170) @@ -104,8 +104,9 @@ def test_create_catalog(self): pardir = self.get_test_dir(erase=1) cat = catalog.get_catalog(pardir,'c') + assert_(cat is not None) + cat.close() self.remove_dir(pardir) - assert_(cat is not None) class TestCatalog(TestCase): From scipy-svn at scipy.org Sun Feb 27 04:36:44 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 27 Feb 2011 03:36:44 -0600 (CST) Subject: [Scipy-svn] r7171 - trunk/scipy/spatial Message-ID: <20110227093644.B53773635D@scipy.org> Author: rgommers Date: 2011-02-27 03:36:43 -0600 (Sun, 27 Feb 2011) New Revision: 7171 Modified: trunk/scipy/spatial/distance.py Log: DOC: BUG: Correct formulas in spatial.distance. Closes #1391. Modified: trunk/scipy/spatial/distance.py =================================================================== --- trunk/scipy/spatial/distance.py 2011-02-21 13:14:32 UTC (rev 7170) +++ trunk/scipy/spatial/distance.py 2011-02-27 09:36:43 UTC (rev 7171) @@ -271,8 +271,8 @@ .. math:: - \frac{1-uv^T} - {||u||_2 ||v||_2}. + 1 - \frac{uv^T} + {||u||_2 ||v||_2}. Parameters ---------- @@ -298,8 +298,8 @@ .. math:: - \frac{1 - (u - \bar{u}){(v - \bar{v})}^T} - {{||(u - \bar{u})||}_2 {||(v - \bar{v})||}_2^T} + 1 - frac{(u - \bar{u}){(v - \bar{v})}^T} + {{||(u - \bar{u})||}_2 {||(v - \bar{v})||}_2^T} where :math:`\bar{u}` is the mean of a vectors elements and ``n`` is the common dimensionality of ``u`` and ``v``. @@ -905,8 +905,8 @@ .. math:: - \frac{1 - uv^T} - {{|u|}_2 {|v|}_2} + 1 - \frac{uv^T} + {{|u|}_2 {|v|}_2} where |*|_2 is the 2 norm of its argument *. @@ -916,8 +916,8 @@ .. math:: - \frac{1 - (u - \bar{u})(v - \bar{v})^T} - {{|(u - \bar{u})|}{|(v - \bar{v})|}^T} + 1 - \frac{(u - \bar{u})(v - \bar{v})^T} + {{|(u - \bar{u})|}{|(v - \bar{v})|}^T} where :math:`\bar{v}` is the mean of the elements of vector v. From scipy-svn at scipy.org Sun Feb 27 06:30:06 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 27 Feb 2011 05:30:06 -0600 (CST) Subject: [Scipy-svn] r7172 - trunk/tools Message-ID: <20110227113006.AD3CC6F06E@scipy.org> Author: rgommers Date: 2011-02-27 05:30:06 -0600 (Sun, 27 Feb 2011) New Revision: 7172 Modified: trunk/tools/py3tool.py Log: ENH: do not make backup copies when running 2to3. Backups are not used and were being included in installers by default. Thanks to Christoph Gohlke for the patch. Modified: trunk/tools/py3tool.py =================================================================== --- trunk/tools/py3tool.py 2011-02-27 09:36:43 UTC (rev 7171) +++ trunk/tools/py3tool.py 2011-02-27 11:30:06 UTC (rev 7172) @@ -329,7 +329,7 @@ _old_stdout = sys.stdout try: sys.stdout = StringIO() - lib2to3.main.main("lib2to3.fixes", ['-w'] + flags.split()+filenames) + lib2to3.main.main("lib2to3.fixes", ['-w', '-n'] + flags.split()+filenames) finally: sys.stdout = _old_stdout From scipy-svn at scipy.org Sun Feb 27 07:06:00 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 27 Feb 2011 06:06:00 -0600 (CST) Subject: [Scipy-svn] r7173 - branches/0.9.x Message-ID: <20110227120600.082533635D@scipy.org> Author: rgommers Date: 2011-02-27 06:06:00 -0600 (Sun, 27 Feb 2011) New Revision: 7173 Modified: branches/0.9.x/setup.py Log: REL: set released=False. Modified: branches/0.9.x/setup.py =================================================================== --- branches/0.9.x/setup.py 2011-02-27 11:30:06 UTC (rev 7172) +++ branches/0.9.x/setup.py 2011-02-27 12:06:00 UTC (rev 7173) @@ -45,7 +45,7 @@ MAJOR = 0 MINOR = 9 MICRO = 0 -ISRELEASED = True +ISRELEASED = False VERSION = '%d.%d.%drc5' % (MAJOR, MINOR, MICRO) # BEFORE importing distutils, remove MANIFEST. distutils doesn't properly From scipy-svn at scipy.org Sun Feb 27 07:06:21 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 27 Feb 2011 06:06:21 -0600 (CST) Subject: [Scipy-svn] r7174 - branches/0.9.x/scipy/weave/tests Message-ID: <20110227120621.E1A773635E@scipy.org> Author: rgommers Date: 2011-02-27 06:06:21 -0600 (Sun, 27 Feb 2011) New Revision: 7174 Modified: branches/0.9.x/scipy/weave/tests/test_catalog.py Log: BUG: fix weave.catalog error on Windows Vista. Thanks to Christoph Gohlke. Modified: branches/0.9.x/scipy/weave/tests/test_catalog.py =================================================================== --- branches/0.9.x/scipy/weave/tests/test_catalog.py 2011-02-27 12:06:00 UTC (rev 7173) +++ branches/0.9.x/scipy/weave/tests/test_catalog.py 2011-02-27 12:06:21 UTC (rev 7174) @@ -104,8 +104,9 @@ def test_create_catalog(self): pardir = self.get_test_dir(erase=1) cat = catalog.get_catalog(pardir,'c') + assert_(cat is not None) + cat.close() self.remove_dir(pardir) - assert_(cat is not None) class TestCatalog(TestCase): From scipy-svn at scipy.org Sun Feb 27 07:06:38 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 27 Feb 2011 06:06:38 -0600 (CST) Subject: [Scipy-svn] r7175 - branches/0.9.x/tools Message-ID: <20110227120638.61C613635D@scipy.org> Author: rgommers Date: 2011-02-27 06:06:38 -0600 (Sun, 27 Feb 2011) New Revision: 7175 Modified: branches/0.9.x/tools/py3tool.py Log: ENH: do not make backup copies when running 2to3. Backups are not used and were being included in installers by default. Thanks to Christoph Gohlke for the patch. Modified: branches/0.9.x/tools/py3tool.py =================================================================== --- branches/0.9.x/tools/py3tool.py 2011-02-27 12:06:21 UTC (rev 7174) +++ branches/0.9.x/tools/py3tool.py 2011-02-27 12:06:38 UTC (rev 7175) @@ -329,7 +329,7 @@ _old_stdout = sys.stdout try: sys.stdout = StringIO() - lib2to3.main.main("lib2to3.fixes", ['-w'] + flags.split()+filenames) + lib2to3.main.main("lib2to3.fixes", ['-w', '-n'] + flags.split()+filenames) finally: sys.stdout = _old_stdout From scipy-svn at scipy.org Sun Feb 27 07:06:53 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 27 Feb 2011 06:06:53 -0600 (CST) Subject: [Scipy-svn] r7176 - branches/0.9.x Message-ID: <20110227120653.886FA3635E@scipy.org> Author: rgommers Date: 2011-02-27 06:06:53 -0600 (Sun, 27 Feb 2011) New Revision: 7176 Modified: branches/0.9.x/setup.py Log: REL: set version to 0.9.0. Modified: branches/0.9.x/setup.py =================================================================== --- branches/0.9.x/setup.py 2011-02-27 12:06:38 UTC (rev 7175) +++ branches/0.9.x/setup.py 2011-02-27 12:06:53 UTC (rev 7176) @@ -45,8 +45,8 @@ MAJOR = 0 MINOR = 9 MICRO = 0 -ISRELEASED = False -VERSION = '%d.%d.%drc5' % (MAJOR, MINOR, MICRO) +ISRELEASED = True +VERSION = '%d.%d.%d' % (MAJOR, MINOR, MICRO) # BEFORE importing distutils, remove MANIFEST. distutils doesn't properly # update it when the contents of directories change. From scipy-svn at scipy.org Sun Feb 27 07:08:15 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 27 Feb 2011 06:08:15 -0600 (CST) Subject: [Scipy-svn] r7177 - tags Message-ID: <20110227120815.8E5533635D@scipy.org> Author: rgommers Date: 2011-02-27 06:08:15 -0600 (Sun, 27 Feb 2011) New Revision: 7177 Added: tags/0.9.0/ Log: Create tag 0.9.0 From scipy-svn at scipy.org Sun Feb 27 07:09:34 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Sun, 27 Feb 2011 06:09:34 -0600 (CST) Subject: [Scipy-svn] r7178 - branches/0.9.x Message-ID: <20110227120934.DA5566F06F@scipy.org> Author: rgommers Date: 2011-02-27 06:09:34 -0600 (Sun, 27 Feb 2011) New Revision: 7178 Modified: branches/0.9.x/setup.py Log: REL: set version to 0.9.1.dev Modified: branches/0.9.x/setup.py =================================================================== --- branches/0.9.x/setup.py 2011-02-27 12:08:15 UTC (rev 7177) +++ branches/0.9.x/setup.py 2011-02-27 12:09:34 UTC (rev 7178) @@ -44,8 +44,8 @@ MAJOR = 0 MINOR = 9 -MICRO = 0 -ISRELEASED = True +MICRO = 1 +ISRELEASED = False VERSION = '%d.%d.%d' % (MAJOR, MINOR, MICRO) # BEFORE importing distutils, remove MANIFEST. distutils doesn't properly From scipy-svn at scipy.org Mon Feb 28 01:55:58 2011 From: scipy-svn at scipy.org (scipy-svn at scipy.org) Date: Mon, 28 Feb 2011 00:55:58 -0600 (CST) Subject: [Scipy-svn] r7179 - trunk/doc/release Message-ID: <20110228065558.6258742E061@scipy.org> Author: rgommers Date: 2011-02-28 00:55:57 -0600 (Mon, 28 Feb 2011) New Revision: 7179 Modified: trunk/doc/release/0.10.0-notes.rst trunk/doc/release/0.9.0-notes.rst Log: DOC: update 0.9.0 release notes from 0.9.x branch, and fix reST error in 0.10.0 notes. Modified: trunk/doc/release/0.10.0-notes.rst =================================================================== --- trunk/doc/release/0.10.0-notes.rst 2011-02-27 12:09:34 UTC (rev 7178) +++ trunk/doc/release/0.10.0-notes.rst 2011-02-28 06:55:57 UTC (rev 7179) @@ -1,6 +1,6 @@ -========================= +========================== SciPy 0.10.0 Release Notes -========================= +========================== .. note:: Scipy 0.10.0 is not released yet! Modified: trunk/doc/release/0.9.0-notes.rst =================================================================== --- trunk/doc/release/0.9.0-notes.rst 2011-02-27 12:09:34 UTC (rev 7178) +++ trunk/doc/release/0.9.0-notes.rst 2011-02-28 06:55:57 UTC (rev 7179) @@ -2,11 +2,9 @@ SciPy 0.9.0 Release Notes ========================= -.. note:: Scipy 0.9.0 is not released yet! - .. contents:: -SciPy 0.9.0 is the culmination of XXX months of hard work. It contains +SciPy 0.9.0 is the culmination of 6 months of hard work. It contains many new features, numerous bug-fixes, improved test coverage and better documentation. There have been a number of deprecations and API changes in this release, which are documented below. All users @@ -22,9 +20,7 @@ major milestone in the development of SciPy, after which changing the package structure or API will be much more difficult. Whilst these pre-1.0 releases are considered to have "Beta" status, we are -committed to making them as bug-free as possible. For example, in -addition to fixing numerous bugs in this release, we have also doubled -the number of unit tests since the last release. +committed to making them as bug-free as possible. However, until the 1.0 release, we are aggressively reviewing and refining the functionality, organization, and interface. This is being @@ -34,11 +30,24 @@ project - everything - from which algorithms we implement, to details about our function's call signatures. + Python 3 ======== -Scipy 0.9.0 has full support for Python 3. +Scipy 0.9.0 is the first SciPy release to support Python 3. The only module +that is not yet ported is ``scipy.weave``. + +Scipy source code location to be changed +======================================== + +Soon after this release, Scipy will stop using SVN as the version control +system, and move to Git. The development source code for Scipy can from then on +be found at + + http://github.com/scipy/scipy + + New features ============