[SciPy-Dev] ANN: Scipy 0.14.0 release candidate 1
Christoph Gohlke
cgohlke at uci.edu
Thu Apr 3 17:34:09 EDT 2014
On 4/3/2014 1:14 PM, Ralf Gommers wrote:
> Hi,
>
> I'm pleased to announce the availability of the first release candidate
> of Scipy 0.14.0. Please try this RC and report any issues on the
> scipy-dev mailing list. A significant number of fixes for scipy.sparse
> went in after the beta release, so users of that module may want to test
> this release carefully.
>
> Source tarballs, binaries and the full release notes can be found at
> https://sourceforge.net/projects/scipy/files/scipy/0.14.0rc1/. The final
> release will follow in one week if no new issues are found.
>
> A big thank you to everyone who contributed to this release!
>
> Ralf
>
>
Hi Ralf,
scipy.sparse.linalg fails many tests on Windows on all Python versions.
I attached the results for Python 2.7 with the official binaries
(scipy-0.14.0rc1-win32-superpack-python2.7, 32 errors) and my msvc/MKL
builds for 32 bit (scipy-0.14.0c1.win32-py2.7, 35 errors) and 64 bit
(scipy-0.14.0c1.win-amd64-py2.7, 4 errors, 10 failures). Other Python
versions also fail. The 64 bit failures/errors were previously reported
for Python 3.4 only at <https://github.com/scipy/scipy/issues/3306>.
I'll try to build and test with numpy 1.7.x and see if that helps.
Christoph
-------------- next part --------------
Running unit tests for scipy
NumPy version 1.8.1
NumPy is installed in X:\Python27\lib\site-packages\numpy
SciPy version 0.14.0rc1
SciPy is installed in X:\Python27\lib\site-packages\scipy
Python version 2.7.6 (default, Nov 10 2013, 19:24:18) [MSC v.1500 32 bit (Intel)]
nose version 1.3.1
X:\Python27\lib\site-packages\numpy\lib\utils.py:134: DeprecationWarning: `scipy.lib.blas` is deprecated, use `scipy.lin
alg.blas` instead!
warnings.warn(depdoc, DeprecationWarning)
X:\Python27\lib\site-packages\numpy\lib\utils.py:134: DeprecationWarning: `scipy.lib.lapack` is deprecated, use `scipy.l
inalg.lapack` instead!
warnings.warn(depdoc, DeprecationWarning)
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======================================================================
ERROR: test_twodiags (test_linsolve.TestLinsolve)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\tests\test_linsolve.py", line 72, in test_twodiags
x = spsolve(Asp,b)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 143, in spsolve
b, flag, options=options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_linsolve.TestSplu.test_spilu_smoketest
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\tests\test_linsolve.py", line 297, in test_spilu_smoket
est
self._smoketest(spilu, check, np.complex128)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\tests\test_linsolve.py", line 242, in _smoketest
lu = spxlu(A)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 309, in spilu
ilu=True, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_hermitian_modes(True, <std-hermitian>, 'D', 2, 'SM', None, 0.5, <class 'scipy.sparse.csr.csr_mat
rix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1467, in eigsh
OPinv=OPinv)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_hermitian_modes(True, <std-hermitian>, 'D', 2, 'LA', None, 0.5, <class 'scipy.sparse.csr.csr_mat
rix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1467, in eigsh
OPinv=OPinv)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_hermitian_modes(True, <gen-hermitian>, 'D', 2, 'LM', None, 0.5, <class 'scipy.sparse.csr.csr_mat
rix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 235, in eval_evec
eval, evec = eigs_func(ac, k, bc, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1467, in eigsh
OPinv=OPinv)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1046, in get_OPinv_matvec
return SpLuInv(OP.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_hermitian_modes(True, <gen-hermitian>, 'D', 2, 'SM', None, 0.5, <class 'scipy.sparse.csr.csr_mat
rix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 235, in eval_evec
eval, evec = eigs_func(ac, k, bc, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1467, in eigsh
OPinv=OPinv)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1046, in get_OPinv_matvec
return SpLuInv(OP.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <std-real-nonsym>, 'f', 2, 'LM', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'i')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <std-real-nonsym>, 'f', 2, 'LR', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'r')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <std-real-nonsym>, 'f', 2, 'LR', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'i')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <std-real-nonsym>, 'd', 2, 'LM', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'r')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <std-real-nonsym>, 'd', 2, 'LR', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'r')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <std-real-nonsym>, 'd', 2, 'LR', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'i')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <gen-real-nonsym>, 'd', 2, 'LM', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'i')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 235, in eval_evec
eval, evec = eigs_func(ac, k, bc, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1046, in get_OPinv_matvec
return SpLuInv(OP.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <gen-real-nonsym>, 'd', 2, 'LR', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'r')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 235, in eval_evec
eval, evec = eigs_func(ac, k, bc, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1046, in get_OPinv_matvec
return SpLuInv(OP.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <gen-real-nonsym>, 'd', 2, 'LI', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'r')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 235, in eval_evec
eval, evec = eigs_func(ac, k, bc, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1046, in get_OPinv_matvec
return SpLuInv(OP.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <gen-real-nonsym>, 'd', 2, 'LI', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'i')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 235, in eval_evec
eval, evec = eigs_func(ac, k, bc, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1046, in get_OPinv_matvec
return SpLuInv(OP.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_complex_nonsymmetric_modes(False, <std-cmplx-nonsym>, 'D', 2, 'LM', None, (0.1+0.1j), <class 'sc
ipy.sparse.csr.csr_matrix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_complex_nonsymmetric_modes(False, <std-cmplx-nonsym>, 'D', 2, 'LM', None, 0.1, <class 'scipy.spa
rse.csr.csr_matrix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_complex_nonsymmetric_modes(False, <std-cmplx-nonsym>, 'D', 2, 'LR', None, (0.1+0.1j), <class 'sc
ipy.sparse.csr.csr_matrix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_complex_nonsymmetric_modes(False, <std-cmplx-nonsym>, 'D', 2, 'LR', None, 0.1, <class 'scipy.spa
rse.csr.csr_matrix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_complex_nonsymmetric_modes(False, <std-cmplx-nonsym>, 'D', 2, 'LI', None, 0.1, <class 'scipy.spa
rse.csr.csr_matrix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_complex_nonsymmetric_modes(False, <std-cmplx-nonsym>, 'F', 2, 'LI', None, (0.1+0.1j), <class 'sc
ipy.sparse.csr.csr_matrix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_complex_nonsymmetric_modes(False, <gen-cmplx-nonsym>, 'D', 2, 'LM', None, (0.1+0.1j), <class 'sc
ipy.sparse.csr.csr_matrix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 235, in eval_evec
eval, evec = eigs_func(ac, k, bc, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1046, in get_OPinv_matvec
return SpLuInv(OP.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_complex_nonsymmetric_modes(False, <gen-cmplx-nonsym>, 'D', 2, 'LR', None, (0.1+0.1j), <class 'sc
ipy.sparse.csr.csr_matrix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 235, in eval_evec
eval, evec = eigs_func(ac, k, bc, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1046, in get_OPinv_matvec
return SpLuInv(OP.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_complex_nonsymmetric_modes(False, <gen-cmplx-nonsym>, 'D', 2, 'LR', None, 0.1, <class 'scipy.spa
rse.csr.csr_matrix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 235, in eval_evec
eval, evec = eigs_func(ac, k, bc, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1046, in get_OPinv_matvec
return SpLuInv(OP.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_complex_nonsymmetric_modes(False, <gen-cmplx-nonsym>, 'D', 2, 'LI', None, 0.1, <class 'scipy.spa
rse.csr.csr_matrix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 235, in eval_evec
eval, evec = eigs_func(ac, k, bc, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1046, in get_OPinv_matvec
return SpLuInv(OP.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_padecases_dtype_sparse_complex (test_matfuncs.TestExpM)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\tests\test_matfuncs.py", line 149, in test_padecases_dtype_spa
rse_complex
assert_array_almost_equal_nulp(expm(a).toarray(), e, nulp=100)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\matfuncs.py", line 599, in expm
return _solve_P_Q(U, V, structure=structure)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\matfuncs.py", line 657, in _solve_P_Q
return spsolve(Q, P)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 151, in spsolve
Afactsolve = factorized(A)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 366, in factorized
return splu(A).solve
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_base.TestCOO.test_solve
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\tests\test_base.py", line 1920, in test_solve
x = splu(A).solve(r)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_base.TestCOONonCanonical.test_solve
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\tests\test_base.py", line 1920, in test_solve
x = splu(A).solve(r)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_base.TestCSR.test_solve
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\tests\test_base.py", line 1920, in test_solve
x = splu(A).solve(r)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_base.TestDIA.test_solve
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\tests\test_base.py", line 1920, in test_solve
x = splu(A).solve(r)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_base.TestLIL.test_solve
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\tests\test_base.py", line 1920, in test_solve
x = splu(A).solve(r)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
----------------------------------------------------------------------
Ran 16538 tests in 164.003s
FAILED (KNOWNFAIL=277, SKIP=1145, errors=32)
-------------- next part --------------
Running unit tests for scipy
NumPy version 1.8.1
NumPy is installed in X:\Python27\lib\site-packages\numpy
SciPy version 0.14.0c1
SciPy is installed in X:\Python27\lib\site-packages\scipy
Python version 2.7.6 (default, Nov 10 2013, 19:24:18) [MSC v.1500 32 bit (Intel)]
nose version 1.3.1
X:\Python27\lib\site-packages\numpy\lib\utils.py:134: DeprecationWarning: `scipy.lib.blas` is deprecated, use `scipy.lin
alg.blas` instead!
warnings.warn(depdoc, DeprecationWarning)
X:\Python27\lib\site-packages\numpy\lib\utils.py:134: DeprecationWarning: `scipy.lib.lapack` is deprecated, use `scipy.l
inalg.lapack` instead!
warnings.warn(depdoc, DeprecationWarning)
........................................................................................................................
....................................................................................................................K...
..................................................................................................................K.....
........................................................................................................................
.........K..K................................X:\Python27\lib\site-packages\scipy\interpolate\tests\test_interpolate.py:8
33: RuntimeWarning: invalid value encountered in true_divide
res /= cres
........................................................................................................................
........................................................................................................................
........................................................................................................................
........................................................................................................................
........................................................................................................................
........................................................................................................................
........................................................................................................................
........................................................................................................................
........................................................................................................................
........................................................................................................................
....................SSSSSS......SSSSSS......SSSS........................................................................
....................0-th dimension must be fixed to 3 but got 15
..0-th dimension must be fixed to 3 but got 5
..........................S..........K..................................................................................
........................................................................................................................
....................................................................................K...................................
........................................................................................................................
................................K.......................................................................................
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........................................................................................................................
........................................................................................................................
........................................................................................................................
........................................................................................................................
............................X:\Python27\lib\site-packages\scipy\optimize\linesearch.py:358: RuntimeWarning: invalid valu
e encountered in greater
if (phi_a1 > phi0 + c1 * alpha1 * derphi0) or \
X:\Python27\lib\site-packages\scipy\optimize\linesearch.py:359: RuntimeWarning: invalid value encountered in greater_equ
al
((phi_a1 >= phi_a0) and (i > 1)):
........................K.....................X:\Python27\lib\site-packages\scipy\optimize\slsqp.py:334: RuntimeWarning:
invalid value encountered in greater
bnderr = where(bnds[:, 0] > bnds[:, 1])[0]
........................................................................................................................
........................................................................................................................
........................................................................................................................
........................................................................................................................
........................................................................................................................
......................................E.................................................................................
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...................................E..........EE..........E...........E.................E.E......E.E......E.E......E.E..
...............E......E.E...............................................................................................
........................................................................................................................
...........................................X:\Python27\lib\site-packages\numpy\linalg\linalg.py:2117: RuntimeWarning: in
valid value encountered in absolute
return add.reduce(abs(x), axis=col_axis).max(axis=row_axis)
..........................E.............................SS.........S....S...SSSSS.SSSSSSSSSS.....SSS..S.....S...K.......
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............SS................K......K.K...S..........S........................S........................................
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..........S........SSSSK...SSSS..S.........S........SS.........S...S...SSSSS.SSSSSSSSSS.....SSS........S................
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.S.........S........SS.........S...S...SSSSS.SSSSSSSSSS.....SSS..S.....S...K..............S........SSSSK...SSSS..S......
...S........SS.........S...S...SSSSS.SSSSSSSSSS.....SSS........S..................S........SSSSK...SSSS..S..........S...
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.SS......S...S...SSSSS.SSSSSSSSSS.....SSS..S.....S...........SS.....S........SSSS....SSSS..S.........S......K...........
.........S.KKK.K..K....K...........S.................SS................K......K.K...S..........S........................
S................................................SS..............................S.........S..............SSSSSSSSSSSSSS
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...............................S..............SSSSK...SSSS...................................S.........S.........K......
......SSKK......KS....S..KKSSSS.SSSSSSSSSS....KSSS..K.K......S...KKK...K...K......K.S..............SSSSK...SSSS..EK.....
..........................SK.............SSSSSSSSSSSSSSSSSSSSSSSSSSSSS..........S...S..SSS.SSSS.SSSSSSSSSS....SSSKKKSSS.
...SSSKKK......S....SSSKKKSSSKKK.................................................SSS.S..............SSSSK...SSSS..E.....
............................S.........S.........K............SSKK.......S...S..SSS.SSSS.SSSSSSSSSS....SSSKKKSSS..K.SSSKK
K......S....SSSKKKSSSKKK..........................................K......SSS.S..............SSSSK...SSSS..EK............
....................SK..................SSSSSSSSSSSSSSSSSSSSSSSSSSS.....................................................
..........KKKK.........................KKKK................KKKK....KKKK.................................................
........................................................................................................................
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........................................................................................................................
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........................................................................................................................
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S.K..............SSSSSSSSSSSSSSSSSSSSSSSSSSSSS.......S...S..SSS.SSSS.SSSSSSSSSS....SSSKKKSSS..S.SSSKKK......S....SSSKKKS
SSKKK..........................................SS.....SSS.S..............SSSS....SSSS...................................
S.........S....................K....SSSSSSSSSSSSSSSSSSSSSSSSSSSSSS.............SSS..KKK...............K..K....K.....SSSK
KK...................S.SSSKKK...........SSSKKKSSSKKK..........................................SS......SSS...........K...
..K....................K.K..............................................................................................
........................................................................................................................
..............................................................................................SSSSSSSSSSSSSSSSSSSS......
.........SSSSSSSSSSSSSSSSSSSSSSSSSSS..............SSS...................................SSSKKK.....................SSSKK
K............SSSKKK...SSSKKK..........................................SS.....SSS............K...........................
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..........................................S.............................................................................
........................................................................................X:\Python27\lib\site-packages\sc
ipy\stats\_distn_infrastructure.py:767: RuntimeWarning: invalid value encountered in greater
cond = logical_and(cond, (asarray(arg) > 0))
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:2858: RuntimeWarning: invalid value encountered in gr
eater_equal
cond1 = (k >= self.a) & (k < self.b)
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:2858: RuntimeWarning: invalid value encountered in le
ss
cond1 = (k >= self.a) & (k < self.b)
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:2859: RuntimeWarning: invalid value encountered in gr
eater_equal
cond2 = (k >= self.b)
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:2819: RuntimeWarning: invalid value encountered in gr
eater_equal
cond1 = (k >= self.a) & (k < self.b)
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:2819: RuntimeWarning: invalid value encountered in le
ss
cond1 = (k >= self.a) & (k < self.b)
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:2820: RuntimeWarning: invalid value encountered in gr
eater_equal
cond2 = (k >= self.b)
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:2939: RuntimeWarning: invalid value encountered in gr
eater_equal
cond1 = (k >= self.a) & (k <= self.b)
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:2939: RuntimeWarning: invalid value encountered in le
ss_equal
cond1 = (k >= self.a) & (k <= self.b)
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:2940: RuntimeWarning: invalid value encountered in le
ss
cond2 = (k < self.a) & cond0
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:2898: RuntimeWarning: invalid value encountered in gr
eater_equal
cond1 = (k >= self.a) & (k <= self.b)
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:2898: RuntimeWarning: invalid value encountered in le
ss_equal
cond1 = (k >= self.a) & (k <= self.b)
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:2899: RuntimeWarning: invalid value encountered in le
ss
cond2 = (k < self.a) & cond0
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:2746: RuntimeWarning: invalid value encountered in gr
eater_equal
cond1 = (k >= self.a) & (k <= self.b) & self._nonzero(k, *args)
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:2746: RuntimeWarning: invalid value encountered in le
ss_equal
cond1 = (k >= self.a) & (k <= self.b) & self._nonzero(k, *args)
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:2782: RuntimeWarning: invalid value encountered in gr
eater_equal
cond1 = (k >= self.a) & (k <= self.b) & self._nonzero(k, *args)
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:2782: RuntimeWarning: invalid value encountered in le
ss_equal
cond1 = (k >= self.a) & (k <= self.b) & self._nonzero(k, *args)
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:2979: RuntimeWarning: invalid value encountered in gr
eater
cond1 = (q > 0) & (q < 1)
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:2979: RuntimeWarning: invalid value encountered in le
ss
cond1 = (q > 0) & (q < 1)
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:2980: RuntimeWarning: invalid value encountered in eq
ual
cond2 = (q == 1) & cond0
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:2984: RuntimeWarning: invalid value encountered in eq
ual
place(output, (q == 0)*(cond == cond), self.a-1)
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:3019: RuntimeWarning: invalid value encountered in gr
eater
cond1 = (q > 0) & (q < 1)
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:3019: RuntimeWarning: invalid value encountered in le
ss
cond1 = (q > 0) & (q < 1)
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:3020: RuntimeWarning: invalid value encountered in eq
ual
cond2 = (q == 1) & cond0
X:\Python27\lib\site-packages\scipy\stats\_distn_infrastructure.py:3026: RuntimeWarning: invalid value encountered in eq
ual
place(output, (q == 0)*(cond == cond), self.b)
.........................................................................................................S..S...........
........................................................................................................................
........................................................................................................................
........................................................................................................................
...X:\Python27\lib\site-packages\numpy\ma\core.py:778: RuntimeWarning: invalid value encountered in absolute
return umath.absolute(a) * self.tolerance >= umath.absolute(b)
.............................................................S.SSS....SSSSSS............................................
.....................................................
======================================================================
ERROR: test_twodiags (test_linsolve.TestLinsolve)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\tests\test_linsolve.py", line 72, in test_twodiags
x = spsolve(Asp,b)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 143, in spsolve
b, flag, options=options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_hermitian_modes(True, <std-hermitian>, 'D', 2, 'LM', None, 0.5, <class 'scipy.sparse.csr.csr_mat
rix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1467, in eigsh
OPinv=OPinv)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_hermitian_modes(True, <std-hermitian>, 'D', 2, 'SM', None, 0.5, <class 'scipy.sparse.csr.csr_mat
rix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1467, in eigsh
OPinv=OPinv)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_hermitian_modes(True, <std-hermitian>, 'D', 2, 'LA', None, 0.5, <class 'scipy.sparse.csr.csr_mat
rix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1467, in eigsh
OPinv=OPinv)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_hermitian_modes(True, <std-hermitian>, 'D', 2, 'SA', None, 0.5, <class 'scipy.sparse.csr.csr_mat
rix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1467, in eigsh
OPinv=OPinv)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_hermitian_modes(True, <gen-hermitian>, 'D', 2, 'LM', None, 0.5, <class 'scipy.sparse.csr.csr_mat
rix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 235, in eval_evec
eval, evec = eigs_func(ac, k, bc, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1467, in eigsh
OPinv=OPinv)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1046, in get_OPinv_matvec
return SpLuInv(OP.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <std-real-nonsym>, 'f', 2, 'LM', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'i')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <std-real-nonsym>, 'f', 2, 'LR', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'r')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <std-real-nonsym>, 'f', 2, 'LR', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'i')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <std-real-nonsym>, 'f', 2, 'LI', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'r')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <std-real-nonsym>, 'f', 2, 'LI', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'i')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <std-real-nonsym>, 'd', 2, 'LM', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'r')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <std-real-nonsym>, 'd', 2, 'LM', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'i')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <std-real-nonsym>, 'd', 2, 'LR', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'r')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <std-real-nonsym>, 'd', 2, 'LR', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'i')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <gen-real-nonsym>, 'd', 2, 'LM', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'i')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 235, in eval_evec
eval, evec = eigs_func(ac, k, bc, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1046, in get_OPinv_matvec
return SpLuInv(OP.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <gen-real-nonsym>, 'd', 2, 'LR', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'r')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 235, in eval_evec
eval, evec = eigs_func(ac, k, bc, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1046, in get_OPinv_matvec
return SpLuInv(OP.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <gen-real-nonsym>, 'd', 2, 'LR', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'i')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 235, in eval_evec
eval, evec = eigs_func(ac, k, bc, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1046, in get_OPinv_matvec
return SpLuInv(OP.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_real_nonsymmetric_modes(False, <gen-real-nonsym>, 'd', 2, 'LI', None, (0.1+0.1j), <class 'scipy.
sparse.csr.csr_matrix'>, 'r')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 235, in eval_evec
eval, evec = eigs_func(ac, k, bc, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1046, in get_OPinv_matvec
return SpLuInv(OP.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_complex_nonsymmetric_modes(False, <std-cmplx-nonsym>, 'D', 2, 'LM', None, (0.1+0.1j), <class 'sc
ipy.sparse.csr.csr_matrix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_complex_nonsymmetric_modes(False, <std-cmplx-nonsym>, 'D', 2, 'LI', None, (0.1+0.1j), <class 'sc
ipy.sparse.csr.csr_matrix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_complex_nonsymmetric_modes(False, <std-cmplx-nonsym>, 'D', 2, 'LI', None, 0.1, <class 'scipy.spa
rse.csr.csr_matrix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_complex_nonsymmetric_modes(False, <std-cmplx-nonsym>, 'F', 2, 'LM', None, (0.1+0.1j), <class 'sc
ipy.sparse.csr.csr_matrix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_complex_nonsymmetric_modes(False, <std-cmplx-nonsym>, 'F', 2, 'LM', None, 0.1, <class 'scipy.spa
rse.csr.csr_matrix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_complex_nonsymmetric_modes(False, <std-cmplx-nonsym>, 'F', 2, 'LR', None, (0.1+0.1j), <class 'sc
ipy.sparse.csr.csr_matrix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_complex_nonsymmetric_modes(False, <std-cmplx-nonsym>, 'F', 2, 'LR', None, 0.1, <class 'scipy.spa
rse.csr.csr_matrix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_complex_nonsymmetric_modes(False, <std-cmplx-nonsym>, 'F', 2, 'LI', None, (0.1+0.1j), <class 'sc
ipy.sparse.csr.csr_matrix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_complex_nonsymmetric_modes(False, <std-cmplx-nonsym>, 'F', 2, 'LI', None, 0.1, <class 'scipy.spa
rse.csr.csr_matrix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 241, in eval_evec
eval, evec = eigs_func(ac, k, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1030, in get_OPinv_matvec
return SpLuInv(A.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_complex_nonsymmetric_modes(False, <gen-cmplx-nonsym>, 'D', 2, 'LR', None, 0.1, <class 'scipy.spa
rse.csr.csr_matrix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 235, in eval_evec
eval, evec = eigs_func(ac, k, bc, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1046, in get_OPinv_matvec
return SpLuInv(OP.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_complex_nonsymmetric_modes(False, <gen-cmplx-nonsym>, 'D', 2, 'LI', None, (0.1+0.1j), <class 'sc
ipy.sparse.csr.csr_matrix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 235, in eval_evec
eval, evec = eigs_func(ac, k, bc, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1046, in get_OPinv_matvec
return SpLuInv(OP.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_arpack.test_complex_nonsymmetric_modes(False, <gen-cmplx-nonsym>, 'D', 2, 'LI', None, 0.1, <class 'scipy.spa
rse.csr.csr_matrix'>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 235, in eval_evec
eval, evec = eigs_func(ac, k, bc, **kwargs)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1260, in eigs
symmetric=False, tol=tol)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1046, in get_OPinv_matvec
return SpLuInv(OP.tocsc()).matvec
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 898, in __init__
self.M_lu = splu(M)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_padecases_dtype_sparse_complex (test_matfuncs.TestExpM)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\tests\test_matfuncs.py", line 149, in test_padecases_dtype_spa
rse_complex
assert_array_almost_equal_nulp(expm(a).toarray(), e, nulp=100)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\matfuncs.py", line 605, in expm
return _solve_P_Q(U, V, structure=structure)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\matfuncs.py", line 657, in _solve_P_Q
return spsolve(Q, P)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 151, in spsolve
Afactsolve = factorized(A)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 366, in factorized
return splu(A).solve
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_base.TestBSRNonCanonical.test_solve
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\tests\test_base.py", line 1920, in test_solve
x = splu(A).solve(r)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_base.TestCOO.test_solve
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\tests\test_base.py", line 1920, in test_solve
x = splu(A).solve(r)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
======================================================================
ERROR: test_base.TestCOONonCanonical.test_solve
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27\lib\site-packages\scipy\sparse\tests\test_base.py", line 1920, in test_solve
x = splu(A).solve(r)
File "X:\Python27\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 242, in splu
ilu=False, options=_options)
ValueError: sparse matrix arrays must be 1-D C-contigous and of proper sizes and types
----------------------------------------------------------------------
Ran 16528 tests in 157.008s
FAILED (KNOWNFAIL=277, SKIP=1147, errors=35)
-------------- next part --------------
Running unit tests for scipy
NumPy version 1.8.1
NumPy is installed in X:\Python27-x64\lib\site-packages\numpy
SciPy version 0.14.0c1
SciPy is installed in X:\Python27-x64\lib\site-packages\scipy
Python version 2.7.6 (default, Nov 10 2013, 19:24:24) [MSC v.1500 64 bit (AMD64)]
nose version 1.3.1
X:\Python27-x64\lib\site-packages\numpy\lib\utils.py:134: DeprecationWarning: `scipy.lib.blas` is deprecated, use `scipy
.linalg.blas` instead!
warnings.warn(depdoc, DeprecationWarning)
X:\Python27-x64\lib\site-packages\numpy\lib\utils.py:134: DeprecationWarning: `scipy.lib.lapack` is deprecated, use `sci
py.linalg.lapack` instead!
warnings.warn(depdoc, DeprecationWarning)
........................................................................................................................
....................................................................................................................K...
..................................................................................................................K.....
........................................................................................................................
.........K..K................................X:\Python27-x64\lib\site-packages\scipy\interpolate\tests\test_interpolate.
py:833: RuntimeWarning: invalid value encountered in true_divide
res /= cres
........................................................................................................................
........................................................................................................................
........................................................................................................................
........................................................................................................................
........................................................................................................................
........................................................................................................................
........................................................................................................................
........................................................................................................................
........................................................................................................................
........................................................................................................................
....................SSSSSS......SSSSSS......SSSS........................................................................
....................0-th dimension must be fixed to 3 but got 15
..0-th dimension must be fixed to 3 but got 5
..........................S..........K..................................................................................
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............................X:\Python27-x64\lib\site-packages\scipy\optimize\linesearch.py:358: RuntimeWarning: invalid
value encountered in greater
if (phi_a1 > phi0 + c1 * alpha1 * derphi0) or \
X:\Python27-x64\lib\site-packages\scipy\optimize\linesearch.py:359: RuntimeWarning: invalid value encountered in greater
_equal
((phi_a1 >= phi_a0) and (i > 1)):
........................K.....................X:\Python27-x64\lib\site-packages\scipy\optimize\slsqp.py:334: RuntimeWarn
ing: invalid value encountered in greater
bnderr = where(bnds[:, 0] > bnds[:, 1])[0]
........................................................................................................................
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.K.K...S..........S........................S................................................SS..........................
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....S...K...KKK...KKK.....................................................S..............SSSSK...SSSS...................
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.....K.S..............SSSSK...SSSS...K...............................SK.............SSSSSSSSSSSSSSSSSSSSSSSSSSSSS.......
...S...S..SSS.SSSS.SSSSSSSSSS....SSSKKKSSS....SSSKKK......S....SSSKKKSSSKKK.............................................
....SSS.S..............SSSSK...SSSS....................................S.........S.........K............SSKK.......S...S
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S..............SSSSK...SSSS...K................................SK..................SSSSSSSSSSSSSSSSSSSSSSSSSSS..........
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SS....SSSKKKSSS..S.SSSKKK......S....SSSKKKSSSKKK..........................................SS.....SSS.S..............SSSS
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........................................................................................................................
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...........SSSKKK.....................SSSKKK............SSSKKK...SSSKKK..........................................SS.....
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........................................................................................................................
...........X:\Python27-x64\lib\site-packages\scipy\stats\_distn_infrastructure.py:767: RuntimeWarning: invalid value enc
ountered in greater
cond = logical_and(cond, (asarray(arg) > 0))
X:\Python27-x64\lib\site-packages\scipy\stats\_distn_infrastructure.py:2858: RuntimeWarning: invalid value encountered i
n greater_equal
cond1 = (k >= self.a) & (k < self.b)
X:\Python27-x64\lib\site-packages\scipy\stats\_distn_infrastructure.py:2858: RuntimeWarning: invalid value encountered i
n less
cond1 = (k >= self.a) & (k < self.b)
X:\Python27-x64\lib\site-packages\scipy\stats\_distn_infrastructure.py:2859: RuntimeWarning: invalid value encountered i
n greater_equal
cond2 = (k >= self.b)
X:\Python27-x64\lib\site-packages\scipy\stats\_distn_infrastructure.py:2819: RuntimeWarning: invalid value encountered i
n greater_equal
cond1 = (k >= self.a) & (k < self.b)
X:\Python27-x64\lib\site-packages\scipy\stats\_distn_infrastructure.py:2819: RuntimeWarning: invalid value encountered i
n less
cond1 = (k >= self.a) & (k < self.b)
X:\Python27-x64\lib\site-packages\scipy\stats\_distn_infrastructure.py:2820: RuntimeWarning: invalid value encountered i
n greater_equal
cond2 = (k >= self.b)
X:\Python27-x64\lib\site-packages\scipy\stats\_distn_infrastructure.py:2939: RuntimeWarning: invalid value encountered i
n greater_equal
cond1 = (k >= self.a) & (k <= self.b)
X:\Python27-x64\lib\site-packages\scipy\stats\_distn_infrastructure.py:2939: RuntimeWarning: invalid value encountered i
n less_equal
cond1 = (k >= self.a) & (k <= self.b)
X:\Python27-x64\lib\site-packages\scipy\stats\_distn_infrastructure.py:2940: RuntimeWarning: invalid value encountered i
n less
cond2 = (k < self.a) & cond0
X:\Python27-x64\lib\site-packages\scipy\stats\_distn_infrastructure.py:2898: RuntimeWarning: invalid value encountered i
n greater_equal
cond1 = (k >= self.a) & (k <= self.b)
X:\Python27-x64\lib\site-packages\scipy\stats\_distn_infrastructure.py:2898: RuntimeWarning: invalid value encountered i
n less_equal
cond1 = (k >= self.a) & (k <= self.b)
X:\Python27-x64\lib\site-packages\scipy\stats\_distn_infrastructure.py:2899: RuntimeWarning: invalid value encountered i
n less
cond2 = (k < self.a) & cond0
X:\Python27-x64\lib\site-packages\scipy\stats\_distn_infrastructure.py:2746: RuntimeWarning: invalid value encountered i
n greater_equal
cond1 = (k >= self.a) & (k <= self.b) & self._nonzero(k, *args)
X:\Python27-x64\lib\site-packages\scipy\stats\_distn_infrastructure.py:2746: RuntimeWarning: invalid value encountered i
n less_equal
cond1 = (k >= self.a) & (k <= self.b) & self._nonzero(k, *args)
X:\Python27-x64\lib\site-packages\scipy\stats\_distn_infrastructure.py:2782: RuntimeWarning: invalid value encountered i
n greater_equal
cond1 = (k >= self.a) & (k <= self.b) & self._nonzero(k, *args)
X:\Python27-x64\lib\site-packages\scipy\stats\_distn_infrastructure.py:2782: RuntimeWarning: invalid value encountered i
n less_equal
cond1 = (k >= self.a) & (k <= self.b) & self._nonzero(k, *args)
X:\Python27-x64\lib\site-packages\scipy\stats\_distn_infrastructure.py:2979: RuntimeWarning: invalid value encountered i
n greater
cond1 = (q > 0) & (q < 1)
X:\Python27-x64\lib\site-packages\scipy\stats\_distn_infrastructure.py:2979: RuntimeWarning: invalid value encountered i
n less
cond1 = (q > 0) & (q < 1)
X:\Python27-x64\lib\site-packages\scipy\stats\_distn_infrastructure.py:3019: RuntimeWarning: invalid value encountered i
n greater
cond1 = (q > 0) & (q < 1)
X:\Python27-x64\lib\site-packages\scipy\stats\_distn_infrastructure.py:3019: RuntimeWarning: invalid value encountered i
n less
cond1 = (q > 0) & (q < 1)
.........................................................................................................S..S...........
........................................................................................................................
........................................................................................................................
........................................................................................................................
...X:\Python27-x64\lib\site-packages\numpy\ma\core.py:778: RuntimeWarning: invalid value encountered in absolute
return umath.absolute(a) * self.tolerance >= umath.absolute(b)
.............................................................S.SSS....SSSSSS............................................
.....................................................
======================================================================
ERROR: test_arpack.test_symmetric_modes(True, <gen-symmetric>, 'f', 2, 'LM', None, None, <function aslinearoperator at 0
x00000000076D9B38>, None, 'normal')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 238, in eval_evec
eval, evec = eigs_func(ac, k, bc, **kwargs)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1568, in eigsh
params.iterate()
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 562, in iterate
self._raise_no_convergence()
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 369, in _raise_no_convergenc
e
raise ArpackNoConvergence(msg % (num_iter, k_ok, self.k), ev, vec)
ArpackNoConvergence: ARPACK error -1: No convergence (121 iterations, 0/2 eigenvectors converged)
======================================================================
ERROR: test_arpack.test_symmetric_modes(True, <gen-symmetric>, 'f', 2, 'SM', None, None, <function aslinearoperator at 0
x00000000076D9B38>, None, 'normal')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 238, in eval_evec
eval, evec = eigs_func(ac, k, bc, **kwargs)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1568, in eigsh
params.iterate()
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 562, in iterate
self._raise_no_convergence()
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 369, in _raise_no_convergenc
e
raise ArpackNoConvergence(msg % (num_iter, k_ok, self.k), ev, vec)
ArpackNoConvergence: ARPACK error -1: No convergence (121 iterations, 1/2 eigenvectors converged)
======================================================================
ERROR: test_arpack.test_symmetric_modes(True, <gen-symmetric>, 'f', 2, 'SA', None, None, <function aslinearoperator at 0
x00000000076D9B38>, None, 'normal')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 238, in eval_evec
eval, evec = eigs_func(ac, k, bc, **kwargs)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1568, in eigsh
params.iterate()
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 562, in iterate
self._raise_no_convergence()
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 369, in _raise_no_convergenc
e
raise ArpackNoConvergence(msg % (num_iter, k_ok, self.k), ev, vec)
ArpackNoConvergence: ARPACK error -1: No convergence (121 iterations, 1/2 eigenvectors converged)
======================================================================
ERROR: test_arpack.test_symmetric_modes(True, <gen-symmetric>, 'f', 2, 'BE', None, None, <function aslinearoperator at 0
x00000000076D9B38>, None, 'normal')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 238, in eval_evec
eval, evec = eigs_func(ac, k, bc, **kwargs)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 1568, in eigsh
params.iterate()
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 562, in iterate
self._raise_no_convergence()
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\arpack.py", line 369, in _raise_no_convergenc
e
raise ArpackNoConvergence(msg % (num_iter, k_ok, self.k), ev, vec)
ArpackNoConvergence: ARPACK error -1: No convergence (121 iterations, 0/2 eigenvectors converged)
======================================================================
FAIL: test_arpack.test_symmetric_modes(True, <gen-symmetric>, 'f', 2, 'LA', None, None, <function aslinearoperator at 0x
00000000076D9B38>, None, 'normal')
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 270, in eval_evec
assert_allclose_cc(eval, exact_eval, rtol=rtol, atol=atol, err_msg=err)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 130, in assert_al
lclose_cc
assert_allclose(actual, conj(desired), **kw)
File "X:\Python27-x64\lib\site-packages\numpy\testing\utils.py", line 1183, in assert_allclose
verbose=verbose, header=header)
File "X:\Python27-x64\lib\site-packages\numpy\testing\utils.py", line 644, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.00178814, atol=0.000357628
error for eigsh:general, typ=f, which=LA, sigma=None, mattype=aslinearoperator, OPpart=None, mode=normal
(mismatch 100.0%)
x: array([ 179.96405029, 249.00842285], dtype=float32)
y: array([ 5.23087454-0.j, 34.52712250-0.j], dtype=complex64)
======================================================================
FAIL: test_arpack.test_real_nonsymmetric_modes(False, <gen-real-nonsym>, 'f', 2, 'LM', None, None, <function aslinearope
rator at 0x00000000076D9B38>, None)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 270, in eval_evec
assert_allclose_cc(eval, exact_eval, rtol=rtol, atol=atol, err_msg=err)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 130, in assert_al
lclose_cc
assert_allclose(actual, conj(desired), **kw)
File "X:\Python27-x64\lib\site-packages\numpy\testing\utils.py", line 1183, in assert_allclose
verbose=verbose, header=header)
File "X:\Python27-x64\lib\site-packages\numpy\testing\utils.py", line 644, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.00178814, atol=0.000357628
error for eigs:general, typ=f, which=LM, sigma=None, mattype=aslinearoperator, OPpart=None, mode=normal
(mismatch 100.0%)
x: array([ 0.23179591+0.83416843j, 0.23179591-0.83416843j], dtype=complex64)
y: array([ 2.00296926-0.j, -13.60746479-0.j], dtype=complex64)
======================================================================
FAIL: test_arpack.test_real_nonsymmetric_modes(False, <gen-real-nonsym>, 'f', 2, 'LR', None, None, <function aslinearope
rator at 0x00000000076D9B38>, None)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 270, in eval_evec
assert_allclose_cc(eval, exact_eval, rtol=rtol, atol=atol, err_msg=err)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 130, in assert_al
lclose_cc
assert_allclose(actual, conj(desired), **kw)
File "X:\Python27-x64\lib\site-packages\numpy\testing\utils.py", line 1183, in assert_allclose
verbose=verbose, header=header)
File "X:\Python27-x64\lib\site-packages\numpy\testing\utils.py", line 644, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.00178814, atol=0.000357628
error for eigs:general, typ=f, which=LR, sigma=None, mattype=aslinearoperator, OPpart=None, mode=normal
(mismatch 100.0%)
x: array([ 0.60024601+0.j, 0.76261067+0.j], dtype=complex64)
y: array([ 0.77774024+1.81930017j, 2.00296926-0.j ], dtype=complex64)
======================================================================
FAIL: test_arpack.test_real_nonsymmetric_modes(False, <gen-real-nonsym>, 'f', 2, 'LI', None, None, <function aslinearope
rator at 0x00000000076D9B38>, None)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 270, in eval_evec
assert_allclose_cc(eval, exact_eval, rtol=rtol, atol=atol, err_msg=err)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\eigen\arpack\tests\test_arpack.py", line 130, in assert_al
lclose_cc
assert_allclose(actual, conj(desired), **kw)
File "X:\Python27-x64\lib\site-packages\numpy\testing\utils.py", line 1183, in assert_allclose
verbose=verbose, header=header)
File "X:\Python27-x64\lib\site-packages\numpy\testing\utils.py", line 644, in assert_array_compare
raise AssertionError(msg)
AssertionError:
Not equal to tolerance rtol=0.00178814, atol=0.000357628
error for eigs:general, typ=f, which=LI, sigma=None, mattype=aslinearoperator, OPpart=None, mode=normal
(mismatch 100.0%)
x: array([ 0.2973851+0.36813122j, 0.2973851-0.36813122j], dtype=complex64)
y: array([ 0.77774024-1.81930017j, 0.77774024+1.81930017j], dtype=complex64)
======================================================================
FAIL: test_iterative.test_convergence(<function gmres at 0x00000000076FAF98>, <poisson1d>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\isolve\tests\test_iterative.py", line 196, in check_conver
gence
assert_normclose(A.dot(x), b, tol=tol)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\isolve\tests\test_iterative.py", line 178, in assert_normc
lose
assert_(residual < tolerance, msg=msg)
File "X:\Python27-x64\lib\site-packages\numpy\testing\utils.py", line 44, in assert_
raise AssertionError(msg)
AssertionError: residual (129.548) not smaller than tolerance 1.43318
======================================================================
FAIL: test_iterative.test_convergence(<function gmres at 0x00000000076FAF98>, <neg-poisson1d>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\isolve\tests\test_iterative.py", line 196, in check_conver
gence
assert_normclose(A.dot(x), b, tol=tol)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\isolve\tests\test_iterative.py", line 178, in assert_normc
lose
assert_(residual < tolerance, msg=msg)
File "X:\Python27-x64\lib\site-packages\numpy\testing\utils.py", line 44, in assert_
raise AssertionError(msg)
AssertionError: residual (151.212) not smaller than tolerance 1.43318
======================================================================
FAIL: test_iterative.test_convergence(<function gmres at 0x00000000076FAF98>, <rand-diag>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\isolve\tests\test_iterative.py", line 196, in check_conver
gence
assert_normclose(A.dot(x), b, tol=tol)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\isolve\tests\test_iterative.py", line 178, in assert_normc
lose
assert_(residual < tolerance, msg=msg)
File "X:\Python27-x64\lib\site-packages\numpy\testing\utils.py", line 44, in assert_
raise AssertionError(msg)
AssertionError: residual (5.93818) not smaller than tolerance 0.168819
======================================================================
FAIL: test_iterative.test_convergence(<function gmres at 0x00000000076FAF98>, <rand>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\isolve\tests\test_iterative.py", line 196, in check_conver
gence
assert_normclose(A.dot(x), b, tol=tol)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\isolve\tests\test_iterative.py", line 178, in assert_normc
lose
assert_(residual < tolerance, msg=msg)
File "X:\Python27-x64\lib\site-packages\numpy\testing\utils.py", line 44, in assert_
raise AssertionError(msg)
AssertionError: residual (2.25456) not smaller than tolerance 0.0374166
======================================================================
FAIL: test_iterative.test_convergence(<function gmres at 0x00000000076FAF98>, <rand-sym>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\isolve\tests\test_iterative.py", line 196, in check_conver
gence
assert_normclose(A.dot(x), b, tol=tol)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\isolve\tests\test_iterative.py", line 178, in assert_normc
lose
assert_(residual < tolerance, msg=msg)
File "X:\Python27-x64\lib\site-packages\numpy\testing\utils.py", line 44, in assert_
raise AssertionError(msg)
AssertionError: residual (0.64031) not smaller than tolerance 0.0374166
======================================================================
FAIL: test_iterative.test_convergence(<function gmres at 0x00000000076FAF98>, <rand-sym-pd>)
----------------------------------------------------------------------
Traceback (most recent call last):
File "X:\Python27-x64\lib\site-packages\nose\case.py", line 197, in runTest
self.test(*self.arg)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\isolve\tests\test_iterative.py", line 196, in check_conver
gence
assert_normclose(A.dot(x), b, tol=tol)
File "X:\Python27-x64\lib\site-packages\scipy\sparse\linalg\isolve\tests\test_iterative.py", line 178, in assert_normc
lose
assert_(residual < tolerance, msg=msg)
File "X:\Python27-x64\lib\site-packages\numpy\testing\utils.py", line 44, in assert_
raise AssertionError(msg)
AssertionError: residual (8.30071) not smaller than tolerance 0.142829
----------------------------------------------------------------------
Ran 16528 tests in 172.190s
FAILED (KNOWNFAIL=277, SKIP=1147, errors=4, failures=10)
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