[Scipy-svn] r4846 - in branches/refactor_fft: . scipy scipy/cluster scipy/interpolate scipy/io/matlab scipy/io/matlab/tests scipy/ndimage scipy/optimize/tests scipy/sparse scipy/sparse/linalg scipy/sparse/linalg/isolve scipy/sparse/linalg/isolve/tests scipy/sparse/sparsetools scipy/sparse/tests scipy/stats scipy/stats/tests
scipy-svn at scipy.org
scipy-svn at scipy.org
Sun Oct 26 07:03:13 EDT 2008
Author: cdavid
Date: 2008-10-26 06:02:22 -0500 (Sun, 26 Oct 2008)
New Revision: 4846
Modified:
branches/refactor_fft/
branches/refactor_fft/scipy/__init__.py
branches/refactor_fft/scipy/cluster/distance.py
branches/refactor_fft/scipy/cluster/hierarchy.py
branches/refactor_fft/scipy/interpolate/interpolate_wrapper.py
branches/refactor_fft/scipy/interpolate/setup.py
branches/refactor_fft/scipy/io/matlab/byteordercodes.py
branches/refactor_fft/scipy/io/matlab/mio.py
branches/refactor_fft/scipy/io/matlab/mio5.py
branches/refactor_fft/scipy/io/matlab/miobase.py
branches/refactor_fft/scipy/io/matlab/tests/test_byteordercodes.py
branches/refactor_fft/scipy/io/matlab/tests/test_mio.py
branches/refactor_fft/scipy/ndimage/filters.py
branches/refactor_fft/scipy/optimize/tests/test_nnls.py
branches/refactor_fft/scipy/sparse/base.py
branches/refactor_fft/scipy/sparse/bsr.py
branches/refactor_fft/scipy/sparse/compressed.py
branches/refactor_fft/scipy/sparse/construct.py
branches/refactor_fft/scipy/sparse/coo.py
branches/refactor_fft/scipy/sparse/csc.py
branches/refactor_fft/scipy/sparse/csr.py
branches/refactor_fft/scipy/sparse/dia.py
branches/refactor_fft/scipy/sparse/dok.py
branches/refactor_fft/scipy/sparse/lil.py
branches/refactor_fft/scipy/sparse/linalg/interface.py
branches/refactor_fft/scipy/sparse/linalg/isolve/iterative.py
branches/refactor_fft/scipy/sparse/linalg/isolve/tests/test_iterative.py
branches/refactor_fft/scipy/sparse/sparsetools/bsr.py
branches/refactor_fft/scipy/sparse/sparsetools/coo.py
branches/refactor_fft/scipy/sparse/sparsetools/csc.py
branches/refactor_fft/scipy/sparse/sparsetools/csr.py
branches/refactor_fft/scipy/sparse/sparsetools/dia.py
branches/refactor_fft/scipy/sparse/sputils.py
branches/refactor_fft/scipy/sparse/tests/test_base.py
branches/refactor_fft/scipy/sparse/tests/test_sputils.py
branches/refactor_fft/scipy/stats/distributions.py
branches/refactor_fft/scipy/stats/stats.py
branches/refactor_fft/scipy/stats/tests/test_stats.py
Log:
Merged revisions 4828-4845 via svnmerge from
http://svn.scipy.org/svn/scipy/trunk
........
r4829 | cdavid | 2008-10-25 16:36:42 +0900 (Sat, 25 Oct 2008) | 1 line
Remove double TestMedian, which shadows some median tests.
........
r4830 | cdavid | 2008-10-25 18:13:05 +0900 (Sat, 25 Oct 2008) | 1 line
Add old median test to new median test.
........
r4831 | cdavid | 2008-10-25 18:13:34 +0900 (Sat, 25 Oct 2008) | 1 line
Add regression test for #760.
........
r4832 | cdavid | 2008-10-25 18:26:32 +0900 (Sat, 25 Oct 2008) | 1 line
BUG: Fix bug 760. median was using old numpy.median behavior wrt axis argument.
........
r4833 | cdavid | 2008-10-25 19:29:28 +0900 (Sat, 25 Oct 2008) | 1 line
Forgot to add one file for #760 fix.
........
r4834 | wnbell | 2008-10-26 06:26:45 +0900 (Sun, 26 Oct 2008) | 2 lines
removed sum_duplicates option from coo_matrix.tocsr() and coo_matrix.tocsc()
........
r4835 | wnbell | 2008-10-26 07:19:48 +0900 (Sun, 26 Oct 2008) | 3 lines
sparse matrices now conform to spmatrix( (M,N) ) -> empty M-by-N matrix
added tests for invalid shapes in case above
........
r4836 | wnbell | 2008-10-26 07:34:36 +0900 (Sun, 26 Oct 2008) | 2 lines
cleaned up lil_matrix imports
........
r4837 | wnbell | 2008-10-26 07:43:44 +0900 (Sun, 26 Oct 2008) | 2 lines
cleaned up dia_matrix imports
........
r4838 | wnbell | 2008-10-26 08:13:09 +0900 (Sun, 26 Oct 2008) | 2 lines
cleaned up bsr_matrix imports
........
r4839 | wnbell | 2008-10-26 08:30:38 +0900 (Sun, 26 Oct 2008) | 2 lines
cleaned up coo_matrix imports
........
r4840 | wnbell | 2008-10-26 10:16:01 +0900 (Sun, 26 Oct 2008) | 3 lines
cleaned up sp_matrix imports
cleaned up multiplication handlers
........
r4841 | wnbell | 2008-10-26 10:33:39 +0900 (Sun, 26 Oct 2008) | 2 lines
cleaned up csr_matrix and csc_matrix imports
........
r4842 | wnbell | 2008-10-26 10:43:51 +0900 (Sun, 26 Oct 2008) | 2 lines
cleaned up imports in construction.py
........
r4845 | jarrod.millman | 2008-10-26 18:20:24 +0900 (Sun, 26 Oct 2008) | 2 lines
ran reindent
........
Property changes on: branches/refactor_fft
___________________________________________________________________
Name: svnmerge-integrated
- /branches/build_with_scons:1-3868 /branches/scipy.scons:1-3533 /branches/sparse_build_reduce_mem:1-4005 /branches/testing_cleanup:1-3662 /trunk:1-4827
+ /branches/build_with_scons:1-3868 /branches/scipy.scons:1-3533 /branches/sparse_build_reduce_mem:1-4005 /branches/testing_cleanup:1-3662 /trunk:1-4845
Modified: branches/refactor_fft/scipy/__init__.py
===================================================================
--- branches/refactor_fft/scipy/__init__.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/__init__.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -74,7 +74,7 @@
# Remove subpackage names from __all__ such that they are not imported via
# "from scipy import *". This works around a numpy bug present in < 1.2.
subpackages = """cluster constants fftpack integrate interpolate io lib linalg
-linsolve maxentropy misc ndimage odr optimize signal sparse special
+linsolve maxentropy misc ndimage odr optimize signal sparse special
splinalg stats stsci weave""".split()
for name in subpackages:
try:
Modified: branches/refactor_fft/scipy/cluster/distance.py
===================================================================
--- branches/refactor_fft/scipy/cluster/distance.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/cluster/distance.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -954,8 +954,8 @@
d(u,v) = \sum_u {|u_i-v_i|}
{|u_i|+|v_i|}
-
+
12. ``Y = pdist(X, 'braycurtis')``
Computes the Bray-Curtis distance between the points. The
@@ -1285,8 +1285,8 @@
it is known that ``X - X.T1`` is small and ``diag(X)`` is
close to zero. These values are ignored any way so they do
not disrupt the squareform transformation.
-
+
Calling Conventions
-------------------
@@ -1692,8 +1692,8 @@
d(u,v) = \sum_u {|u_i-v_i|}
{|u_i|+|v_i|}
-
+
12. ``Y = cdist(X, 'braycurtis')``
Computes the Bray-Curtis distance between the points. The
Modified: branches/refactor_fft/scipy/cluster/hierarchy.py
===================================================================
--- branches/refactor_fft/scipy/cluster/hierarchy.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/cluster/hierarchy.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -345,7 +345,7 @@
Performs centroid/UPGMC linkage on the condensed distance
matrix ``y``. See ``linkage`` for more information on the return
- structure and algorithm.
+ structure and algorithm.
2. Z = centroid(X)
@@ -427,7 +427,7 @@
def linkage(y, method='single', metric='euclidean'):
- """
+ """
Performs hierarchical/agglomerative clustering on the
condensed distance matrix y. y must be a {n \choose 2} sized
vector where n is the number of original observations paired
@@ -665,7 +665,7 @@
The number of leaf nodes (original observations) belonging to
the cluster node nd. If the target node is a leaf, 1 is
returned.
-
+
:Returns:
c : int
@@ -713,7 +713,7 @@
the list.
For example, the statement:
-
+
ids = root.preOrder(lambda x: x.id)
returns a list of the node ids corresponding to the leaf nodes
@@ -730,7 +730,7 @@
:Returns:
- L : list
- The pre-order traversal.
+ The pre-order traversal.
"""
# Do a preorder traversal, caching the result. To avoid having to do
@@ -773,7 +773,7 @@
Converts a hierarchical clustering encoded in the matrix Z (by
linkage) into an easy-to-use tree object. The reference r to the
root cnode object is returned.
-
+
Each cnode object has a left, right, dist, id, and count
attribute. The left and right attributes point to cnode objects
that were combined to generate the cluster. If both are None then
@@ -885,12 +885,12 @@
hierarchical clustering defined by the linkage matrix ``Z``
of a set of :math:`$n$` observations in :math:`$m$`
dimensions. ``Y`` is the condensed distance matrix from which
- ``Z`` was generated.
+ ``Z`` was generated.
:Returns:
- c : ndarray
The cophentic correlation distance (if ``y`` is passed).
-
+
- d : ndarray
The cophenetic distance matrix in condensed form. The
:math:`$ij$`th entry is the cophenetic distance between
@@ -964,8 +964,8 @@
The :math:`$(n-1)$` by 4 matrix encoding the linkage
(hierarchical clustering). See ``linkage`` documentation
for more information on its form.
-
+
:Returns:
- R : ndarray
A :math:`$(n-1)$` by 5 matrix where the ``i``'th row
Modified: branches/refactor_fft/scipy/interpolate/interpolate_wrapper.py
===================================================================
--- branches/refactor_fft/scipy/interpolate/interpolate_wrapper.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/interpolate/interpolate_wrapper.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -119,20 +119,20 @@
return new_y
def block(x, y, new_x):
- """ Essentially a step function.
-
- For each new_x[i], finds largest j such that
- x[j] < new_x[j], and returns y[j].
- """
- # find index of values in x that preceed values in x
- # This code is a little strange -- we really want a routine that
- # returns the index of values where x[j] < x[index]
- TINY = 1e-10
- indices = np.searchsorted(x, new_x+TINY)-1
+ """ Essentially a step function.
+
+ For each new_x[i], finds largest j such that
+ x[j] < new_x[j], and returns y[j].
+ """
+ # find index of values in x that preceed values in x
+ # This code is a little strange -- we really want a routine that
+ # returns the index of values where x[j] < x[index]
+ TINY = 1e-10
+ indices = np.searchsorted(x, new_x+TINY)-1
- # If the value is at the front of the list, it'll have -1.
- # In this case, we will use the first (0), element in the array.
- # take requires the index array to be an Int
- indices = np.atleast_1d(np.clip(indices, 0, np.Inf).astype(np.int))
- new_y = np.take(y, indices, axis=-1)
- return new_y
\ No newline at end of file
+ # If the value is at the front of the list, it'll have -1.
+ # In this case, we will use the first (0), element in the array.
+ # take requires the index array to be an Int
+ indices = np.atleast_1d(np.clip(indices, 0, np.Inf).astype(np.int))
+ new_y = np.take(y, indices, axis=-1)
+ return new_y
Modified: branches/refactor_fft/scipy/interpolate/setup.py
===================================================================
--- branches/refactor_fft/scipy/interpolate/setup.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/interpolate/setup.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -22,9 +22,9 @@
)
config.add_extension('_interpolate',
- sources=['src/_interpolate.cpp'],
- include_dirs = ['src'],
- depends = ['src/interpolate.h'])
+ sources=['src/_interpolate.cpp'],
+ include_dirs = ['src'],
+ depends = ['src/interpolate.h'])
config.add_data_dir('tests')
Modified: branches/refactor_fft/scipy/io/matlab/byteordercodes.py
===================================================================
--- branches/refactor_fft/scipy/io/matlab/byteordercodes.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/io/matlab/byteordercodes.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -18,21 +18,21 @@
'swapped': ('swapped', 'S')}
def to_numpy_code(code):
- ''' Convert various order codings to numpy format
+ ''' Convert various order codings to numpy format
Parameters
----------
code : {'little','big','l','b','le','be','<','>',
'native','=',
'swapped', 's'} string
code is converted to lower case before parsing
-
+
Returns
-------
out_code : {'<','>'} string
- where '<' is the numpy dtype code for little
+ where '<' is the numpy dtype code for little
endian, and '>' is the code for big endian
-
+
Examples
--------
>>> import sys
@@ -64,5 +64,3 @@
else:
raise ValueError(
'We cannot handle byte order %s' % code)
-
-
Modified: branches/refactor_fft/scipy/io/matlab/mio.py
===================================================================
--- branches/refactor_fft/scipy/io/matlab/mio.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/io/matlab/mio.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -68,7 +68,7 @@
raise NotImplementedError('Please use PyTables for matlab v7.3 (HDF) files')
else:
raise TypeError('Did not recognize version %s' % mv)
-
+
def loadmat(file_name, mdict=None, appendmat=True, basename='raw', **kwargs):
''' Load Matlab(tm) file
@@ -96,8 +96,8 @@
(implies squeeze_me=False, chars_as_strings=False,
mat_dtype=True)
struct_as_record - whether to load matlab structs as numpy record arrays, or
- as old-style numpy arrays with dtype=object.
- (warns if not set, and defaults to False. non-recarrays
+ as old-style numpy arrays with dtype=object.
+ (warns if not set, and defaults to False. non-recarrays
cannot be exported via savemat.)
v4 (Level 1.0), v6 and v7.1 matfiles are supported.
Modified: branches/refactor_fft/scipy/io/matlab/mio5.py
===================================================================
--- branches/refactor_fft/scipy/io/matlab/mio5.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/io/matlab/mio5.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -202,7 +202,7 @@
mod8 = byte_count % 8
if mod8:
self.mat_stream.seek(8 - mod8, 1)
-
+
if mdtype in self.codecs: # encoded char data
codec = self.codecs[mdtype]
if not codec:
@@ -216,7 +216,7 @@
buffer=raw_str)
if copy:
el = el.copy()
-
+
return el
def matrix_getter_factory(self):
@@ -428,7 +428,7 @@
tupdims = tuple(self.header['dims'][::-1])
length = np.product(tupdims)
if self.struct_as_record:
- result = np.empty(length, dtype=[(field_name, object)
+ result = np.empty(length, dtype=[(field_name, object)
for field_name in field_names])
for i in range(length):
for field_name in field_names:
@@ -442,14 +442,14 @@
for name in field_names:
item.__dict__[name] = self.read_element()
result[i] = item
-
+
return result.reshape(tupdims).T
class MatlabObject(object):
''' Class to contain read data from matlab objects '''
def __init__(self, classname, field_names):
self.__dict__['classname'] = classname
- self.__dict__['mobj_recarray'] = np.empty((1,1), dtype=[(field_name, object)
+ self.__dict__['mobj_recarray'] = np.empty((1,1), dtype=[(field_name, object)
for field_name in field_names])
def __getattr__(self, name):
@@ -464,8 +464,8 @@
self.__dict__['mobj_recarray'][0,0][name] = value
else:
self.__dict__[name] = value
-
+
class Mat5ObjectMatrixGetter(Mat5MatrixGetter):
def get_array(self):
'''Matlab ojects are essentially structs, with an extra field, the classname.'''
@@ -495,7 +495,7 @@
class MatFile5Reader(MatFileReader):
''' Reader for Mat 5 mat files
Adds the following attribute to base class
-
+
uint16_codec - char codec to use for uint16 char arrays
(defaults to system default codec)
'''
@@ -513,9 +513,9 @@
'''
mat_stream : file-like
object with file API, open for reading
- byte_order : {None, string}
+ byte_order : {None, string}
specification of byte order, one of:
- ('native', '=', 'little', '<', 'BIG', '>')
+ ('native', '=', 'little', '<', 'BIG', '>')
mat_dtype : {True, False} boolean
If True, return arrays in same dtype as loaded into matlab
otherwise return with dtype with which they were saved
@@ -527,7 +527,7 @@
If True, returns matrices as would be loaded by matlab
(implies squeeze_me=False, chars_as_strings=False
mat_dtype=True, struct_as_record=True)
- struct_as_record : {False, True} boolean
+ struct_as_record : {False, True} boolean
If True, return strutures as numpy records,
otherwise, return as custom object (for
compatibility with scipy 0.6)
@@ -766,8 +766,8 @@
def __init__(self, file_stream, arr, name, is_global=False, unicode_strings=False):
super(Mat5CompositeWriter, self).__init__(file_stream, arr, name, is_global)
self.unicode_strings = unicode_strings
-
+
class Mat5CellWriter(Mat5CompositeWriter):
def write(self):
self.write_header(mclass=mxCELL_CLASS)
@@ -797,12 +797,12 @@
class Mat5StructWriter(Mat5CompositeWriter):
def write(self):
self.write_header(mclass=mxSTRUCT_CLASS)
-
+
# write fieldnames
fieldnames = [f[0] for f in self.arr.dtype.descr]
self.write_element(np.array([32], dtype='i4'))
self.write_element(np.array(fieldnames, dtype='S32'), mdtype=miINT8)
-
+
A = np.atleast_2d(self.arr).flatten('F')
MWG = Mat5WriterGetter(self.file_stream, self.unicode_strings)
for el in A:
@@ -826,7 +826,7 @@
fieldnames = [f[0] for f in self.arr.dtype.descr]
self.write_element(np.array([32], dtype='i4'))
self.write_element(np.array(fieldnames, dtype='S32'), mdtype=miINT8)
-
+
A = np.atleast_2d(self.arr).flatten('F')
MWG = Mat5WriterGetter(self.file_stream, self.unicode_strings)
for el in A:
@@ -835,7 +835,7 @@
MW.write()
self.update_matrix_tag()
-
+
class Mat5WriterGetter(object):
''' Wraps stream and options, provides methods for getting Writer objects '''
def __init__(self, stream, unicode_strings):
@@ -854,12 +854,12 @@
if spsparse:
if spsparse.issparse(arr):
return Mat5SparseWriter(self.stream, arr, name, is_global)
-
+
if isinstance(arr, MatlabFunctionMatrix):
return Mat5FunctionWriter(self.stream, arr, name, is_global, self.unicode_strings)
if isinstance(arr, MatlabObject):
return Mat5ObjectWriter(self.stream, arr, name, is_global, self.unicode_strings)
-
+
arr = np.array(arr)
if arr.dtype.hasobject:
if arr.dtype.fields == None:
Modified: branches/refactor_fft/scipy/io/matlab/miobase.py
===================================================================
--- branches/refactor_fft/scipy/io/matlab/miobase.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/io/matlab/miobase.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -29,7 +29,7 @@
#. 0,x -> version 4 format mat files
#. 1,x -> version 5 format mat files
#. 2,x -> version 7.3 format mat files (HDF format)
-
+
Parameters
----------
fileobj : {file-like}
@@ -54,7 +54,7 @@
if 0 in mopt_bytes:
fileobj.seek(0)
return (0,0)
-
+
# For 5 format or 7.3 format we need to read an integer in the
# header. Bytes 124 through 128 contain a version integer and an
# endian test string
@@ -144,9 +144,9 @@
'''
mat_stream : file-like
object with file API, open for reading
- byte_order : {None, string}
+ byte_order : {None, string}
specification of byte order, one of:
- ('native', '=', 'little', '<', 'BIG', '>')
+ ('native', '=', 'little', '<', 'BIG', '>')
mat_dtype : {True, False} boolean
If True, return arrays in same dtype as loaded into matlab
otherwise return with dtype with which they were saved
@@ -158,7 +158,7 @@
If True, returns matrices as would be loaded by matlab
(implies squeeze_me=False, chars_as_strings=False
mat_dtype=True)
-
+
'''
# Initialize stream
self.mat_stream = mat_stream
@@ -234,7 +234,7 @@
def matrix_getter_factory(self):
assert False, 'Not implemented'
-
+
def file_header(self):
return {}
Modified: branches/refactor_fft/scipy/io/matlab/tests/test_byteordercodes.py
===================================================================
--- branches/refactor_fft/scipy/io/matlab/tests/test_byteordercodes.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/io/matlab/tests/test_byteordercodes.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -11,13 +11,13 @@
def test_native():
native_is_le = sys.byteorder == 'little'
assert sibc.sys_is_le == native_is_le
-
+
def test_to_numpy():
if sys.byteorder == 'little':
assert sibc.to_numpy_code('native') == '<'
assert sibc.to_numpy_code('swapped') == '>'
else:
- assert sibc.to_numpy_code('native') == '>'
+ assert sibc.to_numpy_code('native') == '>'
assert sibc.to_numpy_code('swapped') == '<'
assert sibc.to_numpy_code('native') == sibc.to_numpy_code('=')
assert sibc.to_numpy_code('big') == '>'
@@ -26,5 +26,3 @@
for code in ('big', '>', 'b', 'B', 'be'):
assert sibc.to_numpy_code(code) == '>'
assert_raises(ValueError, sibc.to_numpy_code, 'silly string')
-
-
Modified: branches/refactor_fft/scipy/io/matlab/tests/test_mio.py
===================================================================
--- branches/refactor_fft/scipy/io/matlab/tests/test_mio.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/io/matlab/tests/test_mio.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -70,7 +70,7 @@
assert k in matdict, "Missing key at %s" % k_label
_check_level(k_label, expected, matdict[k])
-# Round trip tests
+# Round trip tests
def _rt_check_case(name, expected, format):
mat_stream = StringIO()
savemat(mat_stream, expected, format=format)
@@ -155,7 +155,7 @@
'expected': {'testsparsefloat': SP.csc_matrix(array([[-1+2j,0,2],[0,-3j,0]]))},
},
]
-st = array([(u'Rats live on no evil star.', array([sqrt(2),exp(1),pi]), (1+1j)*array([sqrt(2),exp(1),pi]))],
+st = array([(u'Rats live on no evil star.', array([sqrt(2),exp(1),pi]), (1+1j)*array([sqrt(2),exp(1),pi]))],
dtype=[(n, object) for n in ['stringfield', 'doublefield', 'complexfield']])
case_table5.append(
{'name': 'struct',
@@ -253,7 +253,7 @@
assert_array_almost_equal(actual['x'].todense(),
expected['x'].todense())
-
+
def test_mat73():
# Check any hdf5 files raise an error
filenames = glob(
Modified: branches/refactor_fft/scipy/ndimage/filters.py
===================================================================
--- branches/refactor_fft/scipy/ndimage/filters.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/ndimage/filters.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -45,7 +45,7 @@
def moredoc(*args):
def decorate(f):
if f.__doc__ is not None:
- for a in args:
+ for a in args:
f.__doc__ += a
return f
return decorate
Modified: branches/refactor_fft/scipy/optimize/tests/test_nnls.py
===================================================================
--- branches/refactor_fft/scipy/optimize/tests/test_nnls.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/optimize/tests/test_nnls.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -22,6 +22,3 @@
if __name__ == "__main__":
run_module_suite()
-
-
-
Modified: branches/refactor_fft/scipy/sparse/base.py
===================================================================
--- branches/refactor_fft/scipy/sparse/base.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/sparse/base.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -5,9 +5,7 @@
from warnings import warn
-import numpy
-from numpy import asarray, asmatrix, asanyarray, ones, deprecate, ravel, \
- matrix
+import numpy as np
from sputils import isdense, isscalarlike, isintlike
@@ -70,7 +68,7 @@
raise TypeError('invalid shape')
if not (shape[0] >= 1 and shape[1] >= 1):
- raise TypeError('invalid shape')
+ raise ValueError('invalid shape')
if (self._shape != shape) and (self._shape is not None):
try:
@@ -100,7 +98,7 @@
return self
else:
for fp_type in fp_types:
- if self.dtype <= numpy.dtype(fp_type):
+ if self.dtype <= np.dtype(fp_type):
return self.astype(fp_type)
raise TypeError,'cannot upcast [%s] to a floating \
@@ -137,15 +135,15 @@
format = 'und'
return format
- @deprecate
+ @np.deprecate
def rowcol(self, num):
return (None, None)
- @deprecate
+ @np.deprecate
def getdata(self, num):
return None
- @deprecate
+ @np.deprecate
def listprint(self, start, stop):
"""Provides a way to print over a single index.
"""
@@ -212,10 +210,12 @@
else:
return getattr(self,'to' + format)()
- # default operations use the CSR format as a base
- # and operations return in csr format
- # thus, a new sparse matrix format just needs to define
- # a tocsr method
+ ###################################################################
+ # NOTE: All arithmetic operations use csr_matrix by default.
+ # Therefore a new sparse matrix format just needs to define a
+ # .tocsr() method to provide arithmetic support. Any of these
+ # methods can be overridden for efficiency.
+ ####################################################################
def multiply(self, other):
"""Point-wise multiplication by another matrix
@@ -239,13 +239,34 @@
return self.tocsr().__rsub__(other)
# old __mul__ interfaces
- def matvec(self, other):
+ @np.deprecate
+ def matvec(self,other):
return self * other
- def matmat(self, other):
+
+ @np.deprecate
+ def matmat(self,other):
return self * other
+
+ @np.deprecate
def dot(self, other):
return self * other
+ @np.deprecate
+ def rmatvec(self, other, conjugate=True):
+ """Multiplies the vector 'other' by the sparse matrix, returning a
+ dense vector as a result.
+
+ If 'conjugate' is True:
+ - returns A.transpose().conj() * other
+ Otherwise:
+ - returns A.transpose() * other.
+
+ """
+ if conjugate:
+ return self.conj().transpose() * other
+ else:
+ return self.transpose() * other
+
def __mul__(self, other):
"""interpret other and call one of the following
@@ -268,18 +289,18 @@
other.shape
except AttributeError:
# If it's a list or whatever, treat it like a matrix
- other = asanyarray(other)
+ other = np.asanyarray(other)
- if isdense(other) and asarray(other).squeeze().ndim <= 1:
+ if isdense(other) and np.asarray(other).squeeze().ndim <= 1:
##
# dense row or column vector
if other.shape != (N,) and other.shape != (N,1):
raise ValueError('dimension mismatch')
- result = self._mul_vector(ravel(other))
+ result = self._mul_vector(np.ravel(other))
- if isinstance(other, matrix):
- result = asmatrix(result)
+ if isinstance(other, np.matrix):
+ result = np.asmatrix(result)
if other.ndim == 2 and other.shape[1] == 1:
# If 'other' was an (nx1) column vector, reshape the result
@@ -294,10 +315,10 @@
if other.shape[0] != self.shape[1]:
raise ValueError('dimension mismatch')
- result = self._mul_dense_matrix(asarray(other))
+ result = self._mul_dense_matrix(np.asarray(other))
- if isinstance(other, matrix):
- result = asmatrix(result)
+ if isinstance(other, np.matrix):
+ result = np.asmatrix(result)
return result
else:
@@ -316,9 +337,21 @@
def _mul_sparse_matrix(self, other):
return self.tocsr()._mul_sparse_matrix(other)
- def __rmul__(self, other):
- return self.tocsr().__rmul__(other)
+ def __rmul__(self, other): # other * self
+ if isscalarlike(other):
+ return self.__mul__(other)
+ else:
+ # Don't use asarray unless we have to
+ try:
+ tr = other.transpose()
+ except AttributeError:
+ tr = np.asarray(other).transpose()
+ return (self.transpose() * tr).transpose()
+ ####################
+ # Other Arithmetic #
+ ####################
+
def __truediv__(self, other):
if isscalarlike(other):
return self * (1./other)
@@ -349,12 +382,12 @@
def __pow__(self, other):
if self.shape[0] != self.shape[1]:
- raise TypeError,'matrix is not square'
+ raise TypeError('matrix is not square')
if isintlike(other):
other = int(other)
if other < 0:
- raise ValueError,'exponent must be >= 0'
+ raise ValueError('exponent must be >= 0')
if other == 0:
from construct import identity
@@ -367,7 +400,7 @@
result = result*self
return result
elif isscalarlike(other):
- raise ValueError,'exponent must be an integer'
+ raise ValueError('exponent must be an integer')
elif isspmatrix(other):
warn('Using ** for elementwise multiplication is deprecated.'\
'Use .multiply() instead', DeprecationWarning)
@@ -460,36 +493,11 @@
a[0, i] = 1
return a * self
-
- def rmatvec(self, other, conjugate=True):
- """Multiplies the vector 'other' by the sparse matrix, returning a
- dense vector as a result.
-
- If 'conjugate' is True:
- - returns A.transpose().conj() * other
- Otherwise:
- - returns A.transpose() * other.
-
- """
- return self.tocsr().rmatvec(other, conjugate=conjugate)
-
- #def rmatmat(self, other, conjugate=True):
- # """ If 'conjugate' is True:
- # returns other * A.transpose().conj(),
- # where 'other' is a matrix. Otherwise:
- # returns other * A.transpose().
- # """
- # other = csc_matrix(other)
- # if conjugate:
- # return other.matmat(self.transpose()).conj()
- # else:
- # return other.matmat(self.transpose())
-
#def __array__(self):
# return self.toarray()
def todense(self):
- return asmatrix(self.toarray())
+ return np.asmatrix(self.toarray())
def toarray(self):
return self.tocoo().toarray()
@@ -522,13 +530,13 @@
m, n = self.shape
if axis == 0:
# sum over columns
- return asmatrix(ones((1, m), dtype=self.dtype)) * self
+ return np.asmatrix(np.ones((1, m), dtype=self.dtype)) * self
elif axis == 1:
# sum over rows
- return self * asmatrix(ones((n, 1), dtype=self.dtype))
+ return self * np.asmatrix(np.ones((n, 1), dtype=self.dtype))
elif axis is None:
# sum over rows and columns
- return ( self * asmatrix(ones((n, 1), dtype=self.dtype)) ).sum()
+ return ( self * np.asmatrix(np.ones((n, 1), dtype=self.dtype)) ).sum()
else:
raise ValueError, "axis out of bounds"
Modified: branches/refactor_fft/scipy/sparse/bsr.py
===================================================================
--- branches/refactor_fft/scipy/sparse/bsr.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/sparse/bsr.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -6,8 +6,7 @@
from warnings import warn
-from numpy import zeros, intc, array, asarray, arange, diff, tile, rank, \
- ravel, empty, empty_like
+import numpy as np
from data import _data_matrix
from compressed import _cs_matrix
@@ -97,10 +96,10 @@
if isspmatrix(arg1):
- if arg1.format == self.format and copy:
+ if isspmatrix_bsr(arg1) and copy:
arg1 = arg1.copy()
else:
- arg1 = getattr(arg1,'to' + self.format)(blocksize=blocksize)
+ arg1 = arg1.tobsr(blocksize=blocksize)
self._set_self( arg1 )
elif isinstance(arg1,tuple):
@@ -113,16 +112,16 @@
blocksize = (1,1)
else:
if not isshape(blocksize):
- raise ValueError,'invalid blocksize=%s',blocksize
+ raise ValueError('invalid blocksize=%s' % blocksize)
blocksize = tuple(blocksize)
- self.data = zeros( (0,) + blocksize, getdtype(dtype, default=float) )
- self.indices = zeros( 0, dtype=intc )
+ self.data = np.zeros( (0,) + blocksize, getdtype(dtype, default=float) )
+ self.indices = np.zeros( 0, dtype=np.intc )
R,C = blocksize
if (M % R) != 0 or (N % C) != 0:
raise ValueError, 'shape must be multiple of blocksize'
- self.indptr = zeros(M/R + 1, dtype=intc )
+ self.indptr = np.zeros(M/R + 1, dtype=np.intc )
elif len(arg1) == 2:
# (data,(row,col)) format
@@ -132,21 +131,20 @@
elif len(arg1) == 3:
# (data,indices,indptr) format
(data, indices, indptr) = arg1
- self.indices = array(indices, copy=copy)
- self.indptr = array(indptr, copy=copy)
- self.data = array(data, copy=copy, \
- dtype=getdtype(dtype, data))
+ self.indices = np.array(indices, copy=copy)
+ self.indptr = np.array(indptr, copy=copy)
+ self.data = np.array(data, copy=copy, dtype=getdtype(dtype, data))
else:
- raise ValueError,'unrecognized bsr_matrix constructor usage'
+ raise ValueError('unrecognized bsr_matrix constructor usage')
else:
#must be dense
try:
- arg1 = asarray(arg1)
+ arg1 = np.asarray(arg1)
except:
- raise ValueError, "unrecognized form for" \
- " %s_matrix constructor" % self.format
+ raise ValueError("unrecognized form for" \
+ " %s_matrix constructor" % self.format)
from coo import coo_matrix
- arg1 = self.__class__( coo_matrix(arg1), blocksize=blocksize )
+ arg1 = coo_matrix(arg1).tobsr(blocksize=blocksize)
self._set_self( arg1 )
if shape is not None:
@@ -193,14 +191,14 @@
% self.indices.dtype.name )
# only support 32-bit ints for now
- self.indptr = asarray(self.indptr,intc)
- self.indices = asarray(self.indices,intc)
+ self.indptr = np.asarray(self.indptr, np.intc)
+ self.indices = np.asarray(self.indices, np.intc)
self.data = to_native(self.data)
# check array shapes
- if (rank(self.indices) != 1) or (rank(self.indptr) != 1):
+ if np.rank(self.indices) != 1 or np.rank(self.indptr) != 1:
raise ValueError,"indices, and indptr should be rank 1"
- if rank(self.data) != 3:
+ if np.rank(self.data) != 3:
raise ValueError,"data should be rank 3"
# check index pointer
@@ -260,9 +258,9 @@
"""
M,N = self.shape
R,C = self.blocksize
- y = empty( min(M,N), dtype=upcast(self.dtype) )
+ y = np.empty(min(M,N), dtype=upcast(self.dtype))
sparsetools.bsr_diagonal(M/R, N/C, R, C, \
- self.indptr, self.indices, ravel(self.data), y)
+ self.indptr, self.indices, np.ravel(self.data), y)
return y
##########################
@@ -292,7 +290,7 @@
M,N = self.shape
R,C = self.blocksize
- result = zeros( self.shape[0], dtype=upcast(self.dtype, other.dtype) )
+ result = np.zeros(self.shape[0], dtype=upcast(self.dtype, other.dtype))
bsr_matvec(M/R, N/C, R, C, \
self.indptr, self.indices, self.data.ravel(),
@@ -305,7 +303,7 @@
M,N = self.shape
n_vecs = other.shape[1] #number of column vectors
- result = zeros( (M,n_vecs), dtype=upcast(self.dtype,other.dtype) )
+ result = np.zeros((M,n_vecs), dtype=upcast(self.dtype,other.dtype))
bsr_matvecs(M/R, N/C, n_vecs, R, C, \
self.indptr, self.indices, self.data.ravel(), \
@@ -313,17 +311,11 @@
return result
- #def _mul_dense_matrix(self, other):
- # # TODO make sparse * dense matrix multiplication more efficient
- # # matvec each column of other
- # result = hstack( [ self * col.reshape(-1,1) for col in asarray(other).T ] )
- # return result
-
def _mul_sparse_matrix(self, other):
M, K1 = self.shape
K2, N = other.shape
- indptr = empty_like( self.indptr )
+ indptr = np.empty_like( self.indptr )
R,n = self.blocksize
@@ -336,7 +328,7 @@
from csr import isspmatrix_csr
if isspmatrix_csr(other) and n == 1:
- other = other.tobsr(blocksize=(n,C),copy=False) #convert to this format
+ other = other.tobsr(blocksize=(n,C), copy=False) #lightweight conversion
else:
other = other.tobsr(blocksize=(n,C))
@@ -346,15 +338,16 @@
indptr)
bnnz = indptr[-1]
- indices = empty( bnnz, dtype=intc)
- data = empty( R*C*bnnz, dtype=upcast(self.dtype,other.dtype))
+ indices = np.empty(bnnz, dtype=np.intc)
+ data = np.empty(R*C*bnnz, dtype=upcast(self.dtype,other.dtype))
bsr_matmat_pass2( M/R, N/C, R, C, n, \
- self.indptr, self.indices, ravel(self.data), \
- other.indptr, other.indices, ravel(other.data), \
+ self.indptr, self.indices, np.ravel(self.data), \
+ other.indptr, other.indices, np.ravel(other.data), \
indptr, indices, data)
data = data.reshape(-1,R,C)
+
#TODO eliminate zeros
return bsr_matrix((data,indices,indptr),shape=(M,N),blocksize=(R,C))
@@ -391,13 +384,13 @@
M,N = self.shape
R,C = self.blocksize
- row = (R * arange(M/R)).repeat(diff(self.indptr))
+ row = (R * np.arange(M/R)).repeat(np.diff(self.indptr))
row = row.repeat(R*C).reshape(-1,R,C)
- row += tile( arange(R).reshape(-1,1), (1,C) )
+ row += np.tile(np.arange(R).reshape(-1,1), (1,C))
row = row.reshape(-1)
col = (C * self.indices).repeat(R*C).reshape(-1,R,C)
- col += tile( arange(C), (R,1) )
+ col += np.tile(np.arange(C), (R,1))
col = col.reshape(-1)
data = self.data.reshape(-1)
@@ -406,7 +399,7 @@
data = data.copy()
from coo import coo_matrix
- return coo_matrix( (data,(row,col)), shape=self.shape )
+ return coo_matrix((data,(row,col)), shape=self.shape)
def transpose(self):
@@ -416,17 +409,17 @@
NBLK = self.nnz/(R*C)
if self.nnz == 0:
- return bsr_matrix((N,M),blocksize=(C,R))
+ return bsr_matrix((N,M), blocksize=(C,R))
- indptr = empty( N/C + 1, dtype=self.indptr.dtype)
- indices = empty( NBLK, dtype=self.indices.dtype)
- data = empty( (NBLK,C,R), dtype=self.data.dtype)
+ indptr = np.empty( N/C + 1, dtype=self.indptr.dtype)
+ indices = np.empty( NBLK, dtype=self.indices.dtype)
+ data = np.empty( (NBLK,C,R), dtype=self.data.dtype)
bsr_transpose(M/R, N/C, R, C, \
self.indptr, self.indices, self.data.ravel(), \
indptr, indices, data.ravel())
- return bsr_matrix( (data,indices,indptr), shape=(N,M) )
+ return bsr_matrix((data,indices,indptr), shape=(N,M))
##############################################################
@@ -510,13 +503,13 @@
R,C = self.blocksize
max_bnnz = len(self.data) + len(other.data)
- indptr = empty_like(self.indptr)
- indices = empty( max_bnnz, dtype=intc )
- data = empty( R*C*max_bnnz, dtype=upcast(self.dtype,other.dtype) )
+ indptr = np.empty_like(self.indptr)
+ indices = np.empty(max_bnnz, dtype=np.intc)
+ data = np.empty(R*C*max_bnnz, dtype=upcast(self.dtype,other.dtype))
fn(in_shape[0]/R, in_shape[1]/C, R, C, \
- self.indptr, self.indices, ravel(self.data),
- other.indptr, other.indices, ravel(other.data),
+ self.indptr, self.indices, np.ravel(self.data),
+ other.indptr, other.indices, np.ravel(other.data),
indptr, indices, data)
actual_bnnz = indptr[-1]
Modified: branches/refactor_fft/scipy/sparse/compressed.py
===================================================================
--- branches/refactor_fft/scipy/sparse/compressed.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/sparse/compressed.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -5,8 +5,7 @@
from warnings import warn
-from numpy import array, asarray, zeros, rank, intc, empty, isscalar, \
- empty_like, where, concatenate, deprecate, diff, multiply
+import numpy as np
from base import spmatrix, isspmatrix, SparseEfficiencyWarning
from data import _data_matrix
@@ -15,7 +14,6 @@
isscalarlike, isintlike
-
class _cs_matrix(_data_matrix):
"""base matrix class for compressed row and column oriented matrices"""
@@ -43,9 +41,9 @@
# create empty matrix
self.shape = arg1 #spmatrix checks for errors here
M, N = self.shape
- self.data = zeros(0, getdtype(dtype, default=float))
- self.indices = zeros(0, intc)
- self.indptr = zeros(self._swap((M,N))[0] + 1, dtype=intc)
+ self.data = np.zeros(0, getdtype(dtype, default=float))
+ self.indices = np.zeros(0, np.intc)
+ self.indptr = np.zeros(self._swap((M,N))[0] + 1, dtype=np.intc)
else:
if len(arg1) == 2:
# (data, ij) format
@@ -55,9 +53,9 @@
elif len(arg1) == 3:
# (data, indices, indptr) format
(data, indices, indptr) = arg1
- self.indices = array(indices, copy=copy)
- self.indptr = array(indptr, copy=copy)
- self.data = array(data, copy=copy, dtype=getdtype(dtype, data))
+ self.indices = np.array(indices, copy=copy)
+ self.indptr = np.array(indptr, copy=copy)
+ self.data = np.array(data, copy=copy, dtype=getdtype(dtype, data))
else:
raise ValueError, "unrecognized %s_matrix constructor usage" %\
self.format
@@ -65,7 +63,7 @@
else:
#must be dense
try:
- arg1 = asarray(arg1)
+ arg1 = np.asarray(arg1)
except:
raise ValueError, "unrecognized %s_matrix constructor usage" % \
self.format
@@ -128,14 +126,13 @@
% self.indices.dtype.name )
# only support 32-bit ints for now
- self.indptr = asarray(self.indptr,dtype=intc)
- self.indices = asarray(self.indices,dtype=intc)
+ self.indptr = np.asarray(self.indptr, dtype=np.intc)
+ self.indices = np.asarray(self.indices, dtype=np.intc)
self.data = to_native(self.data)
# check array shapes
- if (rank(self.data) != 1) or (rank(self.indices) != 1) or \
- (rank(self.indptr) != 1):
- raise ValueError,"data, indices, and indptr should be rank 1"
+ if np.rank(self.data) != 1 or np.rank(self.indices) != 1 or np.rank(self.indptr) != 1:
+ raise ValueError('data, indices, and indptr should be rank 1')
# check index pointer
if (len(self.indptr) != major_dim + 1 ):
@@ -164,7 +161,7 @@
if self.indices.min() < 0:
raise ValueError, "%s index values must be >= 0" % \
minor_name
- if diff(self.indptr).min() < 0:
+ if np.diff(self.indptr).min() < 0:
raise ValueError,'index pointer values must form a " \
"non-decreasing sequence'
@@ -225,18 +222,6 @@
raise NotImplementedError
- def __rmul__(self, other): # other * self
- if isscalarlike(other):
- return self.__mul__(other)
- else:
- # Don't use asarray unless we have to
- try:
- tr = other.transpose()
- except AttributeError:
- tr = asarray(other).transpose()
- return (self.transpose() * tr).transpose()
-
-
def __truediv__(self,other):
if isscalarlike(other):
return self * (1./other)
@@ -258,7 +243,7 @@
raise ValueError('inconsistent shapes')
if isdense(other):
- return multiply(self.todense(),other)
+ return np.multiply(self.todense(),other)
else:
other = self.__class__(other)
return self._binopt(other,'_elmul_')
@@ -272,7 +257,7 @@
M,N = self.shape
#output array
- result = zeros( self.shape[0], dtype=upcast(self.dtype,other.dtype) )
+ result = np.zeros( self.shape[0], dtype=upcast(self.dtype,other.dtype) )
# csr_matvec or csc_matvec
fn = getattr(sparsetools,self.format + '_matvec')
@@ -285,7 +270,7 @@
M,N = self.shape
n_vecs = other.shape[1] #number of column vectors
- result = zeros( (M,n_vecs), dtype=upcast(self.dtype,other.dtype) )
+ result = np.zeros( (M,n_vecs), dtype=upcast(self.dtype,other.dtype) )
# csr_matvecs or csc_matvecs
fn = getattr(sparsetools,self.format + '_matvecs')
@@ -299,7 +284,7 @@
K2, N = other.shape
major_axis = self._swap((M,N))[0]
- indptr = empty( major_axis + 1, dtype=intc )
+ indptr = np.empty(major_axis + 1, dtype=np.intc)
other = self.__class__(other) #convert to this format
fn = getattr(sparsetools, self.format + '_matmat_pass1')
@@ -308,8 +293,8 @@
indptr)
nnz = indptr[-1]
- indices = empty( nnz, dtype=intc)
- data = empty( nnz, dtype=upcast(self.dtype,other.dtype))
+ indices = np.empty(nnz, dtype=np.intc)
+ data = np.empty(nnz, dtype=upcast(self.dtype,other.dtype))
fn = getattr(sparsetools, self.format + '_matmat_pass2')
fn( M, N, self.indptr, self.indices, self.data, \
@@ -318,125 +303,8 @@
return self.__class__((data,indices,indptr),shape=(M,N))
- def matvec(self,other):
- return self * other
- def matmat(self,other):
- return self * other
-
- #def matmat(self, other):
- # if isspmatrix(other):
- # M, K1 = self.shape
- # K2, N = other.shape
- # if (K1 != K2):
- # raise ValueError, "shape mismatch error"
-
- # #return self._binopt(other,'mu',in_shape=(M,N),out_shape=(M,N))
-
- # major_axis = self._swap((M,N))[0]
- # indptr = empty( major_axis + 1, dtype=intc )
-
- # other = self.__class__(other) #convert to this format
- # fn = getattr(sparsetools, self.format + '_matmat_pass1')
- # fn( M, N, self.indptr, self.indices, \
- # other.indptr, other.indices, \
- # indptr)
-
- # nnz = indptr[-1]
- # indices = empty( nnz, dtype=intc)
- # data = empty( nnz, dtype=upcast(self.dtype,other.dtype))
-
- # fn = getattr(sparsetools, self.format + '_matmat_pass2')
- # fn( M, N, self.indptr, self.indices, self.data, \
- # other.indptr, other.indices, other.data, \
- # indptr, indices, data)
-
- # return self.__class__((data,indices,indptr),shape=(M,N))
-
-
- # elif isdense(other):
- # # TODO make sparse * dense matrix multiplication more efficient
- #
- # # matvec each column of other
- # result = hstack( [ self * col.reshape(-1,1) for col in asarray(other).T ] )
- # if isinstance(other, matrix):
- # result = asmatrix(result)
- # return result
-
- # else:
- # raise TypeError, "need a dense or sparse matrix"
-
-
- #def matvec(self, other):
- # """Sparse matrix vector product (self * other)
-
- # 'other' may be a rank 1 array of length N or a rank 2 array
- # or matrix with shape (N,1).
-
- # """
- # #If the optional 'output' parameter is defined, it will
- # #be used to store the result. Otherwise, a new vector
- # #will be allocated.
-
- # if isdense(other):
- # M,N = self.shape
-
- # if other.shape != (N,) and other.shape != (N,1):
- # raise ValueError, "dimension mismatch"
-
- # # csrmux, cscmux
- # fn = getattr(sparsetools,self.format + '_matvec')
-
- # #output array
- # y = zeros( self.shape[0], dtype=upcast(self.dtype,other.dtype) )
-
- # #if output is None:
- # # y = empty( self.shape[0], dtype=upcast(self.dtype,other.dtype) )
- # #else:
- # # if output.shape != (M,) and output.shape != (M,1):
- # # raise ValueError, "output array has improper dimensions"
- # # if not output.flags.c_contiguous:
- # # raise ValueError, "output array must be contiguous"
- # # if output.dtype != upcast(self.dtype,other.dtype):
- # # raise ValueError, "output array has dtype=%s "\
- # # "dtype=%s is required" % \
- # # (output.dtype,upcast(self.dtype,other.dtype))
- # # y = output
-
- # fn(self.shape[0], self.shape[1], \
- # self.indptr, self.indices, self.data, numpy.ravel(other), y)
-
- # if isinstance(other, matrix):
- # y = asmatrix(y)
-
- # if other.ndim == 2 and other.shape[1] == 1:
- # # If 'other' was an (nx1) column vector, reshape the result
- # y = y.reshape(-1,1)
-
- # return y
-
- # elif isspmatrix(other):
- # raise TypeError, "use matmat() for sparse * sparse"
-
- # else:
- # raise TypeError, "need a dense vector"
-
- def rmatvec(self, other, conjugate=True):
- """Multiplies the vector 'other' by the sparse matrix, returning a
- dense vector as a result.
-
- If 'conjugate' is True:
- - returns A.transpose().conj() * other
- Otherwise:
- - returns A.transpose() * other.
-
- """
- if conjugate:
- return self.transpose().conj().matvec( other )
- else:
- return self.transpose().matvec( other )
-
- @deprecate
+ @np.deprecate
def getdata(self, ind):
return self.data[ind]
@@ -445,7 +313,7 @@
"""
#TODO support k-th diagonal
fn = getattr(sparsetools, self.format + "_diagonal")
- y = empty( min(self.shape), dtype=upcast(self.dtype) )
+ y = np.empty( min(self.shape), dtype=upcast(self.dtype) )
fn(self.shape[0], self.shape[1], self.indptr, self.indices, self.data, y)
return y
@@ -506,7 +374,7 @@
start = self.indptr[major_index]
end = self.indptr[major_index+1]
- indxs = where(minor_index == self.indices[start:end])[0]
+ indxs = np.where(minor_index == self.indices[start:end])[0]
num_matches = len(indxs)
@@ -539,7 +407,7 @@
index = self.indices[indices] - start
data = self.data[indices]
- indptr = array([0, len(indices)])
+ indptr = np.array([0, len(indices)])
return self.__class__((data, index, indptr), shape=shape, \
dtype=self.dtype)
@@ -563,7 +431,7 @@
return i0, i1
- elif isscalar( sl ):
+ elif np.isscalar( sl ):
if sl < 0:
sl += num
@@ -612,7 +480,7 @@
start = self.indptr[major_index]
end = self.indptr[major_index+1]
- indxs = where(minor_index == self.indices[start:end])[0]
+ indxs = np.where(minor_index == self.indices[start:end])[0]
num_matches = len(indxs)
@@ -627,10 +495,10 @@
newindx = self.indices[start:end].searchsorted(minor_index)
newindx += start
- val = array([val],dtype=self.data.dtype)
- minor_index = array([minor_index],dtype=self.indices.dtype)
- self.data = concatenate((self.data[:newindx],val,self.data[newindx:]))
- self.indices = concatenate((self.indices[:newindx],minor_index,self.indices[newindx:]))
+ val = np.array([val],dtype=self.data.dtype)
+ minor_index = np.array([minor_index],dtype=self.indices.dtype)
+ self.data = np.concatenate((self.data[:newindx],val,self.data[newindx:]))
+ self.indices = np.concatenate((self.indices[:newindx],minor_index,self.indices[newindx:]))
self.indptr[major_index+1:] += 1
@@ -670,7 +538,7 @@
data = data.copy()
minor_indices = minor_indices.copy()
- major_indices = empty(len(minor_indices),dtype=intc)
+ major_indices = np.empty(len(minor_indices), dtype=np.intc)
sparsetools.expandptr(major_dim,self.indptr,major_indices)
@@ -814,9 +682,9 @@
fn = getattr(sparsetools, self.format + op + self.format)
maxnnz = self.nnz + other.nnz
- indptr = empty_like(self.indptr)
- indices = empty( maxnnz, dtype=intc )
- data = empty( maxnnz, dtype=upcast(self.dtype,other.dtype) )
+ indptr = np.empty_like(self.indptr)
+ indices = np.empty(maxnnz, dtype=np.intc)
+ data = np.empty(maxnnz, dtype=upcast(self.dtype,other.dtype))
fn(in_shape[0], in_shape[1], \
self.indptr, self.indices, self.data,
Modified: branches/refactor_fft/scipy/sparse/construct.py
===================================================================
--- branches/refactor_fft/scipy/sparse/construct.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/sparse/construct.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -9,9 +9,7 @@
from warnings import warn
-import numpy
-from numpy import ones, arange, intc, asarray, rank, zeros, \
- cumsum, concatenate, empty
+import numpy as np
from sputils import upcast
@@ -84,28 +82,28 @@
"""
if format in ['csr','csc']:
- indptr = arange(n+1, dtype=intc)
- indices = arange(n, dtype=intc)
- data = ones(n, dtype=dtype)
+ indptr = np.arange(n+1, dtype=np.intc)
+ indices = np.arange(n, dtype=np.intc)
+ data = np.ones(n, dtype=dtype)
cls = eval('%s_matrix' % format)
return cls((data,indices,indptr),(n,n))
elif format == 'coo':
- row = arange(n, dtype=intc)
- col = arange(n, dtype=intc)
- data = ones(n, dtype=dtype)
+ row = np.arange(n, dtype=np.intc)
+ col = np.arange(n, dtype=np.intc)
+ data = np.ones(n, dtype=dtype)
return coo_matrix((data,(row,col)),(n,n))
elif format == 'dia':
- data = ones(n, dtype=dtype)
+ data = np.ones(n, dtype=dtype)
diags = [0]
- return dia_matrix( (data,diags), shape=(n,n) )
+ return dia_matrix((data,diags), shape=(n,n))
else:
- return identity( n, dtype=dtype, format='csr').asformat(format)
+ return identity(n, dtype=dtype, format='csr').asformat(format)
def eye(m, n, k=0, dtype='d', format=None):
"""eye(m, n) returns a sparse (m x n) matrix where the k-th diagonal
is all ones and everything else is zeros.
"""
- diags = ones((1, m), dtype=dtype)
+ diags = np.ones((1, m), dtype=dtype)
return spdiags(diags, k, m, n).asformat(format)
def kron(A, B, format=None):
@@ -148,7 +146,7 @@
#B is fairly dense, use BSR
A = csr_matrix(A,copy=True)
- output_shape = (A.shape[0]*B.shape[0],A.shape[1]*B.shape[1])
+ output_shape = (A.shape[0]*B.shape[0], A.shape[1]*B.shape[1])
if A.nnz == 0 or B.nnz == 0:
# kronecker product is the zero matrix
@@ -158,11 +156,11 @@
data = A.data.repeat(B.size).reshape(-1,B.shape[0],B.shape[1])
data = data * B
- return bsr_matrix((data,A.indices,A.indptr),shape=output_shape)
+ return bsr_matrix((data,A.indices,A.indptr), shape=output_shape)
else:
#use COO
A = coo_matrix(A)
- output_shape = (A.shape[0]*B.shape[0],A.shape[1]*B.shape[1])
+ output_shape = (A.shape[0]*B.shape[0], A.shape[1]*B.shape[1])
if A.nnz == 0 or B.nnz == 0:
# kronecker product is the zero matrix
@@ -231,7 +229,7 @@
return (L+R).asformat(format) #since L + R is not always same format
-def hstack( blocks, format=None, dtype=None ):
+def hstack(blocks, format=None, dtype=None):
"""Stack sparse matrices horizontally (column wise)
Parameters
@@ -256,7 +254,7 @@
"""
return bmat([blocks], format=format, dtype=dtype)
-def vstack( blocks, format=None, dtype=None ):
+def vstack(blocks, format=None, dtype=None):
"""Stack sparse matrices vertically (row wise)
Parameters
@@ -282,7 +280,7 @@
"""
return bmat([ [b] for b in blocks ], format=format, dtype=dtype)
-def bmat( blocks, format=None, dtype=None ):
+def bmat(blocks, format=None, dtype=None):
"""Build a sparse matrix from sparse sub-blocks
Parameters
@@ -313,16 +311,16 @@
"""
- blocks = asarray(blocks, dtype='object')
+ blocks = np.asarray(blocks, dtype='object')
- if rank(blocks) != 2:
+ if np.rank(blocks) != 2:
raise ValueError('blocks must have rank 2')
M,N = blocks.shape
- block_mask = zeros( blocks.shape, dtype='bool' )
- brow_lengths = zeros( blocks.shape[0], dtype=int )
- bcol_lengths = zeros( blocks.shape[1], dtype=int )
+ block_mask = np.zeros(blocks.shape, dtype=np.bool)
+ brow_lengths = np.zeros(blocks.shape[0], dtype=np.intc)
+ bcol_lengths = np.zeros(blocks.shape[1], dtype=np.intc)
# convert everything to COO format
for i in range(M):
@@ -355,12 +353,12 @@
if dtype is None:
dtype = upcast( *tuple([A.dtype for A in blocks[block_mask]]) )
- row_offsets = concatenate(([0],cumsum(brow_lengths)))
- col_offsets = concatenate(([0],cumsum(bcol_lengths)))
+ row_offsets = np.concatenate(([0], np.cumsum(brow_lengths)))
+ col_offsets = np.concatenate(([0], np.cumsum(bcol_lengths)))
- data = empty(nnz, dtype=dtype)
- row = empty(nnz, dtype=intc)
- col = empty(nnz, dtype=intc)
+ data = np.empty(nnz, dtype=dtype)
+ row = np.empty(nnz, dtype=np.intc)
+ col = np.empty(nnz, dtype=np.intc)
nnz = 0
for i in range(M):
@@ -376,8 +374,8 @@
nnz += A.nnz
- shape = (sum(brow_lengths),sum(bcol_lengths))
- return coo_matrix( (data, (row, col)), shape=shape ).asformat(format)
+ shape = (np.sum(brow_lengths), np.sum(bcol_lengths))
+ return coo_matrix((data, (row, col)), shape=shape).asformat(format)
@@ -387,13 +385,11 @@
__all__ += [ 'speye','spidentity', 'spkron', 'lil_eye', 'lil_diags' ]
-from numpy import deprecate
+spkron = np.deprecate(kron, oldname='spkron', newname='scipy.sparse.kron')
+speye = np.deprecate(eye, oldname='speye', newname='scipy.sparse.eye')
+spidentity = np.deprecate(identity, oldname='spidentity', newname='scipy.sparse.identity')
-spkron = deprecate(kron, oldname='spkron', newname='scipy.sparse.kron')
-speye = deprecate(eye, oldname='speye', newname='scipy.sparse.eye')
-spidentity = deprecate(identity, oldname='spidentity', newname='scipy.sparse.identity')
-
def lil_eye((r,c), k=0, dtype='d'):
"""Generate a lil_matrix of dimensions (r,c) with the k-th
diagonal set to 1.
@@ -413,13 +409,11 @@
warn("lil_eye is deprecated." \
"use scipy.sparse.eye(r, c, k, format='lil') instead", \
DeprecationWarning)
- return eye(r,c,k,dtype=dtype,format='lil')
+ return eye(r, c, k, dtype=dtype, format='lil')
-from numpy import clip
-from itertools import izip
#TODO remove this function
-def lil_diags(diags,offsets,(m,n),dtype='d'):
+def lil_diags(diags, offsets, (m,n), dtype='d'):
"""Generate a lil_matrix with the given diagonals.
Parameters
@@ -449,7 +443,7 @@
raise ValueError("Number of diagonals provided should "
"agree with offsets.")
- sort_indices = numpy.argsort(offsets_unsorted)
+ sort_indices = np.argsort(offsets_unsorted)
diags = [diags_unsorted[k] for k in sort_indices]
offsets = [offsets_unsorted[k] for k in sort_indices]
@@ -459,8 +453,10 @@
"diagonal %s." % k)
out = lil_matrix((m,n),dtype=dtype)
+
+ from itertools import izip
for k,diag in izip(offsets,diags):
- for ix,c in enumerate(xrange(clip(k,0,n),clip(m+k,0,n))):
+ for ix,c in enumerate(xrange(np.clip(k,0,n),np.clip(m+k,0,n))):
out.rows[c-k].append(c)
out.data[c-k].append(diag[ix])
return out
Modified: branches/refactor_fft/scipy/sparse/coo.py
===================================================================
--- branches/refactor_fft/scipy/sparse/coo.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/sparse/coo.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -4,11 +4,9 @@
__all__ = ['coo_matrix', 'isspmatrix_coo']
-from itertools import izip
from warnings import warn
-from numpy import array, asarray, empty, intc, zeros, unique, searchsorted,\
- atleast_2d, rank, deprecate, hstack
+import numpy as np
from sparsetools import coo_tocsr, coo_todense, coo_matvec
from base import isspmatrix
@@ -108,9 +106,9 @@
if isshape(arg1):
M, N = arg1
self.shape = (M,N)
- self.row = array([], dtype=intc)
- self.col = array([], dtype=intc)
- self.data = array([], getdtype(dtype, default=float))
+ self.row = np.array([], dtype=np.intc)
+ self.col = np.array([], dtype=np.intc)
+ self.data = np.array([], getdtype(dtype, default=float))
else:
try:
obj, ij = arg1
@@ -123,9 +121,9 @@
except TypeError:
raise TypeError('invalid input format')
- self.row = array(ij[0], copy=copy, dtype=intc)
- self.col = array(ij[1], copy=copy, dtype=intc)
- self.data = array( obj, copy=copy)
+ self.row = np.array(ij[0], copy=copy, dtype=np.intc)
+ self.col = np.array(ij[1], copy=copy, dtype=np.intc)
+ self.data = np.array( obj, copy=copy)
if shape is None:
if len(self.row) == 0 or len(self.col) == 0:
@@ -145,9 +143,9 @@
warn('coo_matrix(None, shape=(M,N)) is deprecated, ' \
'use coo_matrix( (M,N) ) instead', DeprecationWarning)
self.shape = shape
- self.data = array([], getdtype(dtype, default=float))
- self.row = array([], dtype=intc)
- self.col = array([], dtype=intc)
+ self.data = np.array([], getdtype(dtype, default=float))
+ self.row = np.array([], dtype=np.intc)
+ self.col = np.array([], dtype=np.intc)
else:
if isspmatrix(arg1):
if isspmatrix_coo(arg1) and copy:
@@ -164,11 +162,11 @@
else:
#dense argument
try:
- M = atleast_2d(asarray(arg1))
+ M = np.atleast_2d(np.asarray(arg1))
except:
raise TypeError('invalid input format')
- if len(M.shape) != 2:
+ if np.rank(M) != 2:
raise TypeError('expected rank <= 2 array or matrix')
self.shape = M.shape
self.row,self.col = (M != 0).nonzero()
@@ -178,10 +176,10 @@
def getnnz(self):
nnz = len(self.data)
- if (nnz != len(self.row)) or (nnz != len(self.col)):
+ if nnz != len(self.row) or nnz != len(self.col):
raise ValueError('row, column, and data array must all be the same length')
- if rank(self.data) != 1 or rank(self.row) != 1 or rank(self.col) != 1:
+ if np.rank(self.data) != 1 or np.rank(self.row) != 1 or np.rank(self.col) != 1:
raise ValueError('row, column, and data arrays must have rank 1')
return nnz
@@ -200,8 +198,8 @@
% self.col.dtype.name )
# only support 32-bit ints for now
- self.row = asarray(self.row, dtype=intc)
- self.col = asarray(self.col, dtype=intc)
+ self.row = np.asarray(self.row, dtype=np.intc)
+ self.col = np.asarray(self.col, dtype=np.intc)
self.data = to_native(self.data)
if nnz > 0:
@@ -215,73 +213,100 @@
raise ValueError('negative column index found')
- @deprecate
+ @np.deprecate
def rowcol(self, num):
return (self.row[num], self.col[num])
- @deprecate
+ @np.deprecate
def getdata(self, num):
return self.data[num]
- def transpose(self,copy=False):
+ def transpose(self, copy=False):
M,N = self.shape
- return coo_matrix((self.data,(self.col,self.row)),(N,M),copy=copy)
+ return coo_matrix((self.data, (self.col, self.row)), shape=(N,M), copy=copy)
def toarray(self):
- B = zeros(self.shape, dtype=self.dtype)
+ B = np.zeros(self.shape, dtype=self.dtype)
M,N = self.shape
- coo_todense(M, N, self.nnz, self.row, self.col, self.data, B.ravel() )
+ coo_todense(M, N, self.nnz, self.row, self.col, self.data, B.ravel())
return B
- def tocsc(self,sum_duplicates=True):
+ def tocsc(self):
"""Return a copy of this matrix in Compressed Sparse Column format
- By default sum_duplicates=True and any duplicate
- matrix entries are added together.
+ Duplicate entries will be summed together.
+ Example
+ -------
+ >>> from numpy import array
+ >>> from scipy.sparse import coo_matrix
+ >>> row = array([0,0,1,3,1,0,0])
+ >>> col = array([0,2,1,3,1,0,0])
+ >>> data = array([1,1,1,1,1,1,1])
+ >>> A = coo_matrix( (data,(row,col)), shape=(4,4)).tocsc()
+ >>> A.todense()
+ matrix([[3, 0, 1, 0],
+ [0, 2, 0, 0],
+ [0, 0, 0, 0],
+ [0, 0, 0, 1]])
+
"""
from csc import csc_matrix
if self.nnz == 0:
return csc_matrix(self.shape, dtype=self.dtype)
else:
- indptr = empty(self.shape[1] + 1,dtype=intc)
- indices = empty(self.nnz, dtype=intc)
- data = empty(self.nnz, dtype=upcast(self.dtype))
+ M,N = self.shape
+ indptr = np.empty(N + 1, dtype=np.intc)
+ indices = np.empty(self.nnz, dtype=np.intc)
+ data = np.empty(self.nnz, dtype=upcast(self.dtype))
- coo_tocsr(self.shape[1], self.shape[0], self.nnz, \
+ coo_tocsr(N, M, self.nnz, \
self.col, self.row, self.data, \
indptr, indices, data)
- A = csc_matrix((data, indices, indptr), self.shape)
- if sum_duplicates:
- A.sum_duplicates()
+ A = csc_matrix((data, indices, indptr), shape=self.shape)
+ A.sum_duplicates()
+
return A
- def tocsr(self,sum_duplicates=True):
+ def tocsr(self):
"""Return a copy of this matrix in Compressed Sparse Row format
- By default sum_duplicates=True and any duplicate
- matrix entries are added together.
+ Duplicate entries will be summed together.
+ Example
+ -------
+ >>> from numpy import array
+ >>> from scipy.sparse import coo_matrix
+ >>> row = array([0,0,1,3,1,0,0])
+ >>> col = array([0,2,1,3,1,0,0])
+ >>> data = array([1,1,1,1,1,1,1])
+ >>> A = coo_matrix( (data,(row,col)), shape=(4,4)).tocsr()
+ >>> A.todense()
+ matrix([[3, 0, 1, 0],
+ [0, 2, 0, 0],
+ [0, 0, 0, 0],
+ [0, 0, 0, 1]])
+
"""
from csr import csr_matrix
if self.nnz == 0:
return csr_matrix(self.shape, dtype=self.dtype)
else:
- indptr = empty(self.shape[0] + 1,dtype=intc)
- indices = empty(self.nnz, dtype=intc)
- data = empty(self.nnz, dtype=upcast(self.dtype))
+ M,N = self.shape
+ indptr = np.empty(M + 1, dtype=np.intc)
+ indices = np.empty(self.nnz, dtype=np.intc)
+ data = np.empty(self.nnz, dtype=upcast(self.dtype))
- coo_tocsr(self.shape[0], self.shape[1], self.nnz, \
+ coo_tocsr(M, N, self.nnz, \
self.row, self.col, self.data, \
indptr, indices, data)
- A = csr_matrix((data, indices, indptr), self.shape)
- if sum_duplicates:
- A.sum_duplicates()
+ A = csr_matrix((data, indices, indptr), shape=self.shape)
+ A.sum_duplicates()
+
return A
-
def tocoo(self, copy=False):
if copy:
return self.copy()
@@ -292,7 +317,7 @@
from dia import dia_matrix
ks = self.col - self.row #the diagonal for each nonzero
- diags = unique(ks)
+ diags = np.unique(ks)
if len(diags) > 100:
#probably undesired, should we do something?
@@ -300,15 +325,16 @@
pass
#initialize and fill in data array
- data = zeros( (len(diags), self.col.max()+1), dtype=self.dtype)
- data[ searchsorted(diags,ks), self.col ] = self.data
+ data = np.zeros( (len(diags), self.col.max()+1), dtype=self.dtype)
+ data[ np.searchsorted(diags,ks), self.col ] = self.data
- return dia_matrix((data,diags),shape=self.shape)
+ return dia_matrix((data,diags), shape=self.shape)
def todok(self):
+ from itertools import izip
from dok import dok_matrix
- dok = dok_matrix((self.shape),dtype=self.dtype)
+ dok = dok_matrix((self.shape), dtype=self.dtype)
dok.update( izip(izip(self.row,self.col),self.data) )
@@ -334,12 +360,12 @@
def _mul_vector(self, other):
#output array
- result = zeros( self.shape[0], dtype=upcast(self.dtype,other.dtype) )
+ result = np.zeros( self.shape[0], dtype=upcast(self.dtype,other.dtype) )
coo_matvec(self.nnz, self.row, self.col, self.data, other, result)
return result
def _mul_dense_matrix(self, other):
- return hstack( [ self._mul_vector(col).reshape(-1,1) for col in other.T ] )
+ return np.hstack( [ self._mul_vector(col).reshape(-1,1) for col in other.T ] )
from sputils import _isinstance
Modified: branches/refactor_fft/scipy/sparse/csc.py
===================================================================
--- branches/refactor_fft/scipy/sparse/csc.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/sparse/csc.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -6,7 +6,8 @@
from warnings import warn
-from numpy import asarray, intc, empty, searchsorted, deprecate
+import numpy as np
+
from sparsetools import csc_tocsr
from sputils import upcast, isintlike
@@ -96,11 +97,11 @@
for r in xrange(self.shape[0]):
yield csr[r,:]
- @deprecate
+ @np.deprecate
def rowcol(self, ind):
#TODO remove after 0.7
row = self.indices[ind]
- col = searchsorted(self.indptr, ind+1)-1
+ col = np.searchsorted(self.indptr, ind+1) - 1
return (row, col)
def tocsc(self, copy=False):
@@ -110,16 +111,17 @@
return self
def tocsr(self):
- indptr = empty(self.shape[0] + 1, dtype=intc)
- indices = empty(self.nnz, dtype=intc)
- data = empty(self.nnz, dtype=upcast(self.dtype))
+ M,N = self.shape
+ indptr = np.empty(M + 1, dtype=np.intc)
+ indices = np.empty(self.nnz, dtype=np.intc)
+ data = np.empty(self.nnz, dtype=upcast(self.dtype))
- csc_tocsr(self.shape[0], self.shape[1], \
+ csc_tocsr(M, N, \
self.indptr, self.indices, self.data, \
indptr, indices, data)
from csr import csr_matrix
- A = csr_matrix((data, indices, indptr), self.shape)
+ A = csr_matrix((data, indices, indptr), shape=self.shape)
A.has_sorted_indices = True
return A
@@ -137,8 +139,8 @@
if isintlike(col) or isinstance(col,slice):
return self.T[col,row].T
else:
- row = asarray(row, dtype='intc')
- col = asarray(col, dtype='intc')
+ row = np.asarray(row, dtype=np.intc)
+ col = np.asarray(col, dtype=np.intc)
if len(row.shape) == 1:
return self.T[col,row]
elif len(row.shape) == 2:
Modified: branches/refactor_fft/scipy/sparse/csr.py
===================================================================
--- branches/refactor_fft/scipy/sparse/csr.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/sparse/csr.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -7,8 +7,7 @@
from warnings import warn
-from numpy import asarray, asmatrix, zeros, intc, empty, isscalar, array, \
- searchsorted, where, deprecate, arange, ones, ravel
+import numpy as np
from sparsetools import csr_tocsc, csr_tobsr, csr_count_blocks, \
get_csr_submatrix
@@ -91,13 +90,13 @@
def transpose(self, copy=False):
from csc import csc_matrix
M,N = self.shape
- return csc_matrix((self.data,self.indices,self.indptr),(N,M),copy=copy)
+ return csc_matrix((self.data,self.indices,self.indptr), shape=(N,M), copy=copy)
- @deprecate
+ @np.deprecate
def rowcol(self, ind):
#TODO remove after 0.7
col = self.indices[ind]
- row = searchsorted(self.indptr, ind+1)-1
+ row = np.searchsorted(self.indptr, ind+1)-1
return (row, col)
@@ -105,7 +104,7 @@
from lil import lil_matrix
lil = lil_matrix(self.shape,dtype=self.dtype)
- self.sort_indices() #lil_matrix needs sorted rows
+ self.sort_indices() #lil_matrix needs sorted column indices
ptr,ind,dat = self.indptr,self.indices,self.data
rows, data = lil.rows, lil.data
@@ -125,28 +124,30 @@
return self
def tocsc(self):
- indptr = empty(self.shape[1] + 1, dtype=intc)
- indices = empty(self.nnz, dtype=intc)
- data = empty(self.nnz, dtype=upcast(self.dtype))
+ indptr = np.empty(self.shape[1] + 1, dtype=np.intc)
+ indices = np.empty(self.nnz, dtype=np.intc)
+ data = np.empty(self.nnz, dtype=upcast(self.dtype))
csr_tocsc(self.shape[0], self.shape[1], \
self.indptr, self.indices, self.data, \
indptr, indices, data)
from csc import csc_matrix
- A = csc_matrix((data, indices, indptr), self.shape)
+ A = csc_matrix((data, indices, indptr), shape=self.shape)
A.has_sorted_indices = True
return A
- def tobsr(self,blocksize=None,copy=True):
+ def tobsr(self, blocksize=None, copy=True):
from bsr import bsr_matrix
if blocksize is None:
from spfuncs import estimate_blocksize
return self.tobsr(blocksize=estimate_blocksize(self))
+
elif blocksize == (1,1):
arg1 = (self.data.reshape(-1,1,1),self.indices,self.indptr)
- return bsr_matrix( arg1, shape=self.shape, copy=copy )
+ return bsr_matrix(arg1, shape=self.shape, copy=copy )
+
else:
R,C = blocksize
M,N = self.shape
@@ -156,14 +157,14 @@
blks = csr_count_blocks(M,N,R,C,self.indptr,self.indices)
- indptr = empty( M/R + 1, dtype=intc )
- indices = empty( blks, dtype=intc )
- data = zeros( (blks,R,C), dtype=self.dtype)
+ indptr = np.empty(M/R + 1, dtype=np.intc)
+ indices = np.empty(blks, dtype=np.intc)
+ data = np.zeros((blks,R,C), dtype=self.dtype)
csr_tobsr(M, N, R, C, self.indptr, self.indices, self.data, \
indptr, indices, data.ravel() )
- return bsr_matrix( (data,indices,indptr), shape=self.shape )
+ return bsr_matrix((data,indices,indptr), shape=self.shape)
# these functions are used by the parent class (_cs_matrix)
# to remove redudancy between csc_matrix and csr_matrix
@@ -176,7 +177,7 @@
def __getitem__(self, key):
def asindices(x):
try:
- x = asarray(x,dtype='intc')
+ x = np.asarray(x, dtype=np.intc)
except:
raise IndexError('invalid index')
else:
@@ -201,11 +202,11 @@
indices = indices.copy()
indices[indices < 0] += N
- indptr = arange(len(indices) + 1, dtype='intc')
- data = ones(len(indices), dtype=self.dtype)
+ indptr = np.arange(len(indices) + 1, dtype=np.intc)
+ data = np.ones(len(indices), dtype=self.dtype)
shape = (len(indices),N)
- return csr_matrix( (data,indices,indptr), shape=shape)
+ return csr_matrix((data,indices,indptr), shape=shape)
if isinstance(key, tuple):
@@ -245,10 +246,10 @@
val = []
for i,j in zip(row,col):
val.append(self._get_single_element(i,j))
- return asmatrix(val)
+ return np.asmatrix(val)
elif len(row.shape) == 2:
- row = ravel(row) #[[[1],[2]],[1,2]]
+ row = np.ravel(row) #[[[1],[2]],[1,2]]
P = extractor(row, self.shape[0])
return (P*self)[:,col]
@@ -276,7 +277,7 @@
start = self.indptr[row]
end = self.indptr[row+1]
- indxs = where(col == self.indices[start:end])[0]
+ indxs = np.where(col == self.indices[start:end])[0]
num_matches = len(indxs)
@@ -288,7 +289,7 @@
else:
raise ValueError('nonzero entry (%d,%d) occurs more than once' % (row,col) )
- def _get_row_slice(self, i, cslice ):
+ def _get_row_slice(self, i, cslice):
"""Returns a copy of row self[i, cslice]
"""
if i < 0:
@@ -315,7 +316,7 @@
index = self.indices[indices] - start
data = self.data[indices]
- indptr = array([0, len(indices)])
+ indptr = np.array([0, len(indices)])
return csr_matrix( (data, index, indptr), shape=(1, stop-start) )
def _get_submatrix( self, row_slice, col_slice ):
Modified: branches/refactor_fft/scipy/sparse/dia.py
===================================================================
--- branches/refactor_fft/scipy/sparse/dia.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/sparse/dia.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -2,10 +2,9 @@
__docformat__ = "restructuredtext en"
-__all__ = ['dia_matrix','isspmatrix_dia']
+__all__ = ['dia_matrix', 'isspmatrix_dia']
-from numpy import asarray, zeros, arange, array, intc, atleast_1d, \
- atleast_2d, unique, hstack
+import numpy as np
from base import isspmatrix, _formats
from data import _data_matrix
@@ -72,9 +71,9 @@
if isshape(arg1):
# It's a tuple of matrix dimensions (M, N)
# create empty matrix
- self.shape = arg1 #spmatrix checks for errors here
- self.data = zeros( (0,0), getdtype(dtype, default=float))
- self.offsets = zeros( (0), dtype=intc)
+ self.shape = arg1 #spmatrix checks for errors here
+ self.data = np.zeros( (0,0), getdtype(dtype, default=float))
+ self.offsets = np.zeros( (0), dtype=np.intc)
else:
try:
# Try interpreting it as (data, offsets)
@@ -84,16 +83,16 @@
else:
if shape is None:
raise ValueError('expected a shape argument')
- self.data = atleast_2d(array(arg1[0],dtype=dtype,copy=copy))
- self.offsets = atleast_1d(array(arg1[1],dtype='i',copy=copy))
+ self.data = np.atleast_2d(np.array(arg1[0], dtype=dtype, copy=copy))
+ self.offsets = np.atleast_1d(np.array(arg1[1], dtype=np.intc, copy=copy))
self.shape = shape
else:
#must be dense, convert to COO first, then to DIA
try:
- arg1 = asarray(arg1)
+ arg1 = np.asarray(arg1)
except:
- raise ValueError, "unrecognized form for" \
- " %s_matrix constructor" % self.format
+ raise ValueError("unrecognized form for" \
+ " %s_matrix constructor" % self.format)
from coo import coo_matrix
A = coo_matrix(arg1).todia()
self.data = A.data
@@ -113,7 +112,7 @@
'does not match the number of offsets (%d)' \
% (self.data.shape[0], len(self.offsets)))
- if len(unique(self.offsets)) != len(self.offsets):
+ if len(np.unique(self.offsets)) != len(self.offsets):
raise ValueError('offset array contains duplicate values')
def __repr__(self):
@@ -143,7 +142,7 @@
def _mul_vector(self, other):
x = other
- y = zeros( self.shape[0], dtype=upcast(self.dtype,x.dtype))
+ y = np.zeros( self.shape[0], dtype=upcast(self.dtype,x.dtype))
L = self.data.shape[1]
@@ -154,7 +153,7 @@
return y
def _mul_dense_matrix(self, other):
- return hstack( [ self._mul_vector(col).reshape(-1,1) for col in other.T ] )
+ return np.hstack( [ self._mul_vector(col).reshape(-1,1) for col in other.T ] )
def todia(self,copy=False):
if copy:
@@ -164,17 +163,17 @@
def tocsr(self):
#this could be faster
- return self.tocoo().tocsr(sum_duplicates=False)
+ return self.tocoo().tocsr()
def tocsc(self):
#this could be faster
- return self.tocoo().tocsc(sum_duplicates=False)
+ return self.tocoo().tocsc()
def tocoo(self):
num_data = len(self.data)
len_data = self.data.shape[1]
- row = arange(len_data).reshape(1,-1).repeat(num_data,axis=0)
+ row = np.arange(len_data).reshape(1,-1).repeat(num_data,axis=0)
col = row.copy()
for i,k in enumerate(self.offsets):
@@ -187,10 +186,9 @@
mask &= (col < self.shape[1])
mask &= data != 0
row,col,data = row[mask],col[mask],data[mask]
- #row,col,data = row.reshape(-1),col.reshape(-1),data.reshape(-1)
from coo import coo_matrix
- return coo_matrix((data,(row,col)),shape=self.shape)
+ return coo_matrix((data,(row,col)), shape=self.shape)
# needed by _data_matrix
def _with_data(self, data, copy=True):
@@ -198,7 +196,7 @@
but with different data. By default the structure arrays are copied.
"""
if copy:
- return dia_matrix( (data,self.offsets.copy()), shape=self.shape)
+ return dia_matrix( (data, self.offsets.copy()), shape=self.shape)
else:
return dia_matrix( (data,self.offsets), shape=self.shape)
Modified: branches/refactor_fft/scipy/sparse/dok.py
===================================================================
--- branches/refactor_fft/scipy/sparse/dok.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/sparse/dok.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -13,9 +13,11 @@
from sputils import isdense, getdtype, isshape, isintlike, isscalarlike
class dok_matrix(spmatrix, dict):
- """Dictionary Of Keys based matrix. This is an efficient
- structure for constructing sparse matrices incrementally.
+ """Dictionary Of Keys based sparse matrix.
+ This is an efficient structure for constructing sparse
+ matrices incrementally.
+
This can be instatiated in several ways:
dok_matrix(D)
with a dense matrix, D
@@ -474,7 +476,7 @@
base[newkey] = self[key]
return base, ext
-
+# TODO update these w/ new multiplication handlers
# def matvec(self, other):
# if isdense(other):
# if other.shape[0] != self.shape[1]:
Modified: branches/refactor_fft/scipy/sparse/lil.py
===================================================================
--- branches/refactor_fft/scipy/sparse/lil.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/sparse/lil.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -5,34 +5,30 @@
__all__ = ['lil_matrix','isspmatrix_lil']
-import copy
from bisect import bisect_left
-import numpy
-from numpy import isscalar, asmatrix, asarray, intc, concatenate, array, \
- cumsum, zeros, unravel_index
+import numpy as np
from base import spmatrix, isspmatrix
-from sputils import getdtype,isshape,issequence,isscalarlike
+from sputils import getdtype, isshape, issequence, isscalarlike
class lil_matrix(spmatrix):
- """Row-based linked list matrix
+ """Row-based linked list sparse matrix
+ This is an efficient structure for constructing sparse
+ matrices incrementally.
This can be instantiated in several ways:
- csc_matrix(D)
+ lil_matrix(D)
with a dense matrix or rank-2 ndarray D
- csc_matrix(S)
+ lil_matrix(S)
with another sparse matrix S (equivalent to S.tocsc())
- csc_matrix((M, N), [dtype])
+ lil_matrix((M, N), [dtype])
to construct an empty matrix with shape (M, N)
dtype is optional, defaulting to dtype='d'.
- csc_matrix((data, ij), [shape=(M, N)])
- where ``data`` and ``ij`` satisfy ``a[ij[0, k], ij[1, k]] = data[k]``
-
Notes
-----
@@ -60,54 +56,39 @@
"""
- def __init__(self, A=None, shape=None, dtype=None, copy=False):
- """ Create a new list-of-lists sparse matrix. An optional
- argument A is accepted, which initializes the lil_matrix with it.
- This can be a tuple of dimensions (M, N) or a dense array /
- matrix to copy, or a sparse matrix.
- """
+ def __init__(self, arg1, shape=None, dtype=None, copy=False):
spmatrix.__init__(self)
- self.dtype = getdtype(dtype, A, default=float)
+ self.dtype = getdtype(dtype, arg1, default=float)
# First get the shape
- if A is None:
- if not isshape(shape):
- raise TypeError("need a valid shape")
- M, N = shape
- self.shape = (M,N)
- self.rows = numpy.empty((M,), dtype=object)
- self.data = numpy.empty((M,), dtype=object)
- for i in range(M):
- self.rows[i] = []
- self.data[i] = []
- elif isspmatrix(A):
- if isspmatrix_lil(A) and copy:
- A = A.copy()
+ if isspmatrix(arg1):
+ if isspmatrix_lil(arg1) and copy:
+ A = arg1.copy()
else:
- A = A.tolil()
+ A = arg1.tolil()
self.shape = A.shape
self.dtype = A.dtype
self.rows = A.rows
self.data = A.data
- elif isinstance(A,tuple):
- if isshape(A):
+ elif isinstance(arg1,tuple):
+ if isshape(arg1):
if shape is not None:
raise ValueError('invalid use of shape parameter')
- M, N = A
+ M, N = arg1
self.shape = (M,N)
- self.rows = numpy.empty((M,), dtype=object)
- self.data = numpy.empty((M,), dtype=object)
+ self.rows = np.empty((M,), dtype=object)
+ self.data = np.empty((M,), dtype=object)
for i in range(M):
self.rows[i] = []
self.data[i] = []
else:
- raise TypeError,'unrecognized lil_matrix constructor usage'
+ raise TypeError('unrecognized lil_matrix constructor usage')
else:
#assume A is dense
try:
- A = asmatrix(A)
+ A = np.asmatrix(arg1)
except TypeError:
- raise TypeError, "unsupported matrix type"
+ raise TypeError('unsupported matrix type')
else:
from csr import csr_matrix
A = csr_matrix(A).tolil()
@@ -177,7 +158,7 @@
j += self.shape[1]
if j < 0 or j > self.shape[1]:
- raise IndexError,'column index out of bounds'
+ raise IndexError('column index out of bounds')
pos = bisect_left(row, j)
if pos != len(data) and row[pos] == j:
@@ -210,10 +191,10 @@
try:
i, j = index
except (AssertionError, TypeError):
- raise IndexError, "invalid index"
+ raise IndexError('invalid index')
- if isscalar(i):
- if isscalar(j):
+ if np.isscalar(i):
+ if np.isscalar(j):
return self._get1(i, j)
if isinstance(j, slice):
j = self._slicetoseq(j, self.shape[1])
@@ -224,7 +205,7 @@
elif issequence(i) or isinstance(i, slice):
if isinstance(i, slice):
i = self._slicetoseq(i, self.shape[0])
- if isscalar(j):
+ if np.isscalar(j):
return self.__class__([[self._get1(ii, j)] for ii in i])
if isinstance(j, slice):
j = self._slicetoseq(j, self.shape[1])
@@ -249,7 +230,7 @@
j += self.shape[1]
if j < 0 or j >= self.shape[1]:
- raise IndexError,'column index out of bounds'
+ raise IndexError('column index out of bounds')
pos = bisect_left(row, j)
if x != 0:
@@ -274,22 +255,22 @@
if issequence(j):
if isinstance(x, spmatrix):
x = x.todense()
- x = numpy.asarray(x).squeeze()
- if isscalar(x) or x.size == 1:
+ x = np.asarray(x).squeeze()
+ if np.isscalar(x) or x.size == 1:
for jj in j:
self._insertat2(row, data, jj, x)
else:
# x must be one D. maybe check these things out
for jj, xx in zip(j, x):
self._insertat2(row, data, jj, xx)
- elif isscalar(j):
+ elif np.isscalar(j):
self._insertat2(row, data, j, x)
else:
- raise ValueError, "invalid column value: %s" % str(j)
+ raise ValueError('invalid column value: %s' % str(j))
def __setitem__(self, index, x):
- if isscalar(x):
+ if np.isscalar(x):
x = self.dtype.type(x)
elif not isinstance(x, spmatrix):
x = lil_matrix(x)
@@ -297,7 +278,7 @@
try:
i, j = index
except (ValueError, TypeError):
- raise IndexError, "invalid index"
+ raise IndexError('invalid index')
if isspmatrix(x):
if (isinstance(i, slice) and (i == slice(None))) and \
@@ -308,12 +289,12 @@
self.data = x.data
return
- if isscalar(i):
+ if np.isscalar(i):
row = self.rows[i]
data = self.data[i]
self._insertat3(row, data, j, x)
elif issequence(i) and issequence(j):
- if isscalar(x):
+ if np.isscalar(x):
for ii, jj in zip(i, j):
self._insertat(ii, jj, x)
else:
@@ -322,32 +303,32 @@
elif isinstance(i, slice) or issequence(i):
rows = self.rows[i]
datas = self.data[i]
- if isscalar(x):
+ if np.isscalar(x):
for row, data in zip(rows, datas):
self._insertat3(row, data, j, x)
else:
for row, data, xx in zip(rows, datas, x):
self._insertat3(row, data, j, xx)
else:
- raise ValueError, "invalid index value: %s" % str((i, j))
+ raise ValueError('invalid index value: %s' % str((i, j)))
def _mul_scalar(self, other):
if other == 0:
# Multiply by zero: return the zero matrix
- new = lil_matrix(shape=self.shape, dtype=self.dtype)
+ new = lil_matrix(self.shape, dtype=self.dtype)
else:
new = self.copy()
# Multiply this scalar by every element.
- new.data = numpy.array([[val*other for val in rowvals] for
- rowvals in new.data], dtype=object)
+ new.data = np.array([[val*other for val in rowvals] for
+ rowvals in new.data], dtype=object)
return new
def __truediv__(self, other): # self / other
if isscalarlike(other):
new = self.copy()
# Divide every element by this scalar
- new.data = numpy.array([[val/other for val in rowvals] for
- rowvals in new.data], dtype=object)
+ new.data = np.array([[val/other for val in rowvals] for
+ rowvals in new.data], dtype=object)
return new
else:
return self.tocsr() / other
@@ -357,7 +338,7 @@
# """Point-wise multiplication by another lil_matrix.
#
# """
-# if isscalar(other):
+# if np.isscalar(other):
# return self.__mul__(other)
#
# if isspmatrix_lil(other):
@@ -386,37 +367,23 @@
# "with another lil_matrix.")
def copy(self):
+ from copy import deepcopy
new = lil_matrix(self.shape, dtype=self.dtype)
- new.data = copy.deepcopy(self.data)
- new.rows = copy.deepcopy(self.rows)
+ new.data = deepcopy(self.data)
+ new.rows = deepcopy(self.rows)
return new
def reshape(self,shape):
- new = lil_matrix(shape,dtype=self.dtype)
+ new = lil_matrix(shape, dtype=self.dtype)
j_max = self.shape[1]
for i,row in enumerate(self.rows):
for col,j in enumerate(row):
- new_r,new_c = unravel_index(i*j_max + j,shape)
+ new_r,new_c = np.unravel_index(i*j_max + j,shape)
new[new_r,new_c] = self[i,j]
return new
- def __add__(self, other):
- if isscalar(other) and other != 0:
- raise ValueError("Refusing to destroy sparsity. "
- "Use x.todense() + c instead.")
- else:
- return spmatrix.__add__(self, other)
-
- def __rmul__(self, other): # other * self
- if isscalarlike(other):
- # Multiplication by a scalar is symmetric
- return self.__mul__(other)
- else:
- return spmatrix.__rmul__(self, other)
-
-
def toarray(self):
- d = zeros(self.shape, dtype=self.dtype)
+ d = np.zeros(self.shape, dtype=self.dtype)
for i, row in enumerate(self.rows):
for pos, j in enumerate(row):
d[i, j] = self.data[i][pos]
@@ -435,20 +402,20 @@
""" Return Compressed Sparse Row format arrays for this matrix.
"""
- indptr = asarray([len(x) for x in self.rows], dtype=intc)
- indptr = concatenate( ( array([0],dtype=intc), cumsum(indptr) ) )
+ indptr = np.asarray([len(x) for x in self.rows], dtype=np.intc)
+ indptr = np.concatenate( (np.array([0], dtype=np.intc), np.cumsum(indptr)) )
nnz = indptr[-1]
indices = []
for x in self.rows:
indices.extend(x)
- indices = asarray(indices,dtype=intc)
+ indices = np.asarray(indices, dtype=np.intc)
data = []
for x in self.data:
data.extend(x)
- data = asarray(data,dtype=self.dtype)
+ data = np.asarray(data, dtype=self.dtype)
from csr import csr_matrix
return csr_matrix((data, indices, indptr), shape=self.shape)
Modified: branches/refactor_fft/scipy/sparse/linalg/interface.py
===================================================================
--- branches/refactor_fft/scipy/sparse/linalg/interface.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/sparse/linalg/interface.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -127,8 +127,14 @@
matmat=matmat, dtype=A.dtype)
elif isspmatrix(A):
- return LinearOperator(A.shape, A.matvec, rmatvec=A.rmatvec,
- matmat=A.dot, dtype=A.dtype)
+ def matvec(v):
+ return A * v
+ def rmatvec(v):
+ return A.conj().transpose() * v
+ def matmat(V):
+ return A * V
+ return LinearOperator(A.shape, matvec, rmatvec=rmatvec,
+ matmat=matmat, dtype=A.dtype)
else:
if hasattr(A,'shape') and hasattr(A,'matvec'):
Modified: branches/refactor_fft/scipy/sparse/linalg/isolve/iterative.py
===================================================================
--- branches/refactor_fft/scipy/sparse/linalg/isolve/iterative.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/sparse/linalg/isolve/iterative.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -400,7 +400,7 @@
b or use xtype='f','d','F',or 'D'
callback -- an optional user-supplied function to call after each
iteration. It is called as callback(rk), where rk is the
- the current relative residual
+ the current relative residual
"""
A,M,x,b,postprocess = make_system(A,M,x0,b,xtype)
@@ -442,7 +442,7 @@
if resid_ready and callback is not None:
callback(resid)
resid_ready = False
-
+
break
elif (ijob == 1):
work[slice2] *= sclr2
@@ -452,7 +452,7 @@
if not first_pass and old_ijob==3:
resid_ready = True
- first_pass = False
+ first_pass = False
elif (ijob == 3):
work[slice2] *= sclr2
work[slice2] += sclr1*matvec(work[slice1])
@@ -466,7 +466,7 @@
info = -1
ftflag = False
bnrm2, resid, info = stoptest(work[slice1], b, bnrm2, tol, info)
-
+
old_ijob = ijob
ijob = 2
Modified: branches/refactor_fft/scipy/sparse/linalg/isolve/tests/test_iterative.py
===================================================================
--- branches/refactor_fft/scipy/sparse/linalg/isolve/tests/test_iterative.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/sparse/linalg/isolve/tests/test_iterative.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -61,7 +61,7 @@
#data[1,:] = -1
#A = spdiags( data, [0,-1], 10, 10, format='csr')
#self.cases.append( (A,False,True) )
-
+
def test_maxiter(self):
"""test whether maxiter is respected"""
@@ -76,7 +76,7 @@
residuals.append( norm(b - A*x) )
x, info = solver(A, b, x0=x0, tol=1e-8, maxiter=3, callback=callback)
-
+
assert(len(residuals) in [2,3])
# TODO enforce this condition instead!
@@ -169,8 +169,8 @@
class TestGMRES(TestCase):
- def test_callback(self):
-
+ def test_callback(self):
+
def store_residual(r, rvec):
rvec[rvec.nonzero()[0].max()+1] = r
Modified: branches/refactor_fft/scipy/sparse/sparsetools/bsr.py
===================================================================
--- branches/refactor_fft/scipy/sparse/sparsetools/bsr.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/sparse/sparsetools/bsr.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -51,484 +51,483 @@
def bsr_diagonal(*args):
- """
- bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- signed char Ax, signed char Yx)
- bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned char Ax, unsigned char Yx)
- bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- short Ax, short Yx)
- bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned short Ax, unsigned short Yx)
- bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- int Ax, int Yx)
- bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned int Ax, unsigned int Yx)
- bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- long long Ax, long long Yx)
- bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned long long Ax, unsigned long long Yx)
- bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- float Ax, float Yx)
- bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- double Ax, double Yx)
- bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- long double Ax, long double Yx)
- bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- npy_cfloat_wrapper Ax, npy_cfloat_wrapper Yx)
- bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- npy_cdouble_wrapper Ax, npy_cdouble_wrapper Yx)
- bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- npy_clongdouble_wrapper Ax, npy_clongdouble_wrapper Yx)
"""
- return _bsr.bsr_diagonal(*args)
+ bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ signed char Ax, signed char Yx)
+ bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned char Ax, unsigned char Yx)
+ bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ short Ax, short Yx)
+ bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned short Ax, unsigned short Yx)
+ bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ int Ax, int Yx)
+ bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned int Ax, unsigned int Yx)
+ bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ long long Ax, long long Yx)
+ bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned long long Ax, unsigned long long Yx)
+ bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ float Ax, float Yx)
+ bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ double Ax, double Yx)
+ bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ long double Ax, long double Yx)
+ bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ npy_cfloat_wrapper Ax, npy_cfloat_wrapper Yx)
+ bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ npy_cdouble_wrapper Ax, npy_cdouble_wrapper Yx)
+ bsr_diagonal(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ npy_clongdouble_wrapper Ax, npy_clongdouble_wrapper Yx)
+ """
+ return _bsr.bsr_diagonal(*args)
def bsr_scale_rows(*args):
- """
- bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- signed char Ax, signed char Xx)
- bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned char Ax, unsigned char Xx)
- bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- short Ax, short Xx)
- bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned short Ax, unsigned short Xx)
- bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- int Ax, int Xx)
- bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned int Ax, unsigned int Xx)
- bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- long long Ax, long long Xx)
- bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned long long Ax, unsigned long long Xx)
- bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- float Ax, float Xx)
- bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- double Ax, double Xx)
- bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- long double Ax, long double Xx)
- bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- npy_cfloat_wrapper Ax, npy_cfloat_wrapper Xx)
- bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- npy_cdouble_wrapper Ax, npy_cdouble_wrapper Xx)
- bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- npy_clongdouble_wrapper Ax, npy_clongdouble_wrapper Xx)
"""
- return _bsr.bsr_scale_rows(*args)
+ bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ signed char Ax, signed char Xx)
+ bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned char Ax, unsigned char Xx)
+ bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ short Ax, short Xx)
+ bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned short Ax, unsigned short Xx)
+ bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ int Ax, int Xx)
+ bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned int Ax, unsigned int Xx)
+ bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ long long Ax, long long Xx)
+ bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned long long Ax, unsigned long long Xx)
+ bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ float Ax, float Xx)
+ bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ double Ax, double Xx)
+ bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ long double Ax, long double Xx)
+ bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ npy_cfloat_wrapper Ax, npy_cfloat_wrapper Xx)
+ bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ npy_cdouble_wrapper Ax, npy_cdouble_wrapper Xx)
+ bsr_scale_rows(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ npy_clongdouble_wrapper Ax, npy_clongdouble_wrapper Xx)
+ """
+ return _bsr.bsr_scale_rows(*args)
def bsr_scale_columns(*args):
- """
- bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- signed char Ax, signed char Xx)
- bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned char Ax, unsigned char Xx)
- bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- short Ax, short Xx)
- bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned short Ax, unsigned short Xx)
- bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- int Ax, int Xx)
- bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned int Ax, unsigned int Xx)
- bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- long long Ax, long long Xx)
- bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned long long Ax, unsigned long long Xx)
- bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- float Ax, float Xx)
- bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- double Ax, double Xx)
- bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- long double Ax, long double Xx)
- bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- npy_cfloat_wrapper Ax, npy_cfloat_wrapper Xx)
- bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- npy_cdouble_wrapper Ax, npy_cdouble_wrapper Xx)
- bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- npy_clongdouble_wrapper Ax, npy_clongdouble_wrapper Xx)
"""
- return _bsr.bsr_scale_columns(*args)
+ bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ signed char Ax, signed char Xx)
+ bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned char Ax, unsigned char Xx)
+ bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ short Ax, short Xx)
+ bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned short Ax, unsigned short Xx)
+ bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ int Ax, int Xx)
+ bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned int Ax, unsigned int Xx)
+ bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ long long Ax, long long Xx)
+ bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned long long Ax, unsigned long long Xx)
+ bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ float Ax, float Xx)
+ bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ double Ax, double Xx)
+ bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ long double Ax, long double Xx)
+ bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ npy_cfloat_wrapper Ax, npy_cfloat_wrapper Xx)
+ bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ npy_cdouble_wrapper Ax, npy_cdouble_wrapper Xx)
+ bsr_scale_columns(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ npy_clongdouble_wrapper Ax, npy_clongdouble_wrapper Xx)
+ """
+ return _bsr.bsr_scale_columns(*args)
def bsr_transpose(*args):
- """
- bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- signed char Ax, int Bp, int Bj, signed char Bx)
- bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned char Ax, int Bp, int Bj, unsigned char Bx)
- bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- short Ax, int Bp, int Bj, short Bx)
- bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned short Ax, int Bp, int Bj, unsigned short Bx)
- bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- int Ax, int Bp, int Bj, int Bx)
- bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned int Ax, int Bp, int Bj, unsigned int Bx)
- bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- long long Ax, int Bp, int Bj, long long Bx)
- bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned long long Ax, int Bp, int Bj, unsigned long long Bx)
- bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- float Ax, int Bp, int Bj, float Bx)
- bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- double Ax, int Bp, int Bj, double Bx)
- bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- long double Ax, int Bp, int Bj, long double Bx)
- bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- npy_cfloat_wrapper Ax, int Bp, int Bj, npy_cfloat_wrapper Bx)
- bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- npy_cdouble_wrapper Ax, int Bp, int Bj, npy_cdouble_wrapper Bx)
- bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- npy_clongdouble_wrapper Ax, int Bp, int Bj,
- npy_clongdouble_wrapper Bx)
"""
- return _bsr.bsr_transpose(*args)
+ bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ signed char Ax, int Bp, int Bj, signed char Bx)
+ bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned char Ax, int Bp, int Bj, unsigned char Bx)
+ bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ short Ax, int Bp, int Bj, short Bx)
+ bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned short Ax, int Bp, int Bj, unsigned short Bx)
+ bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ int Ax, int Bp, int Bj, int Bx)
+ bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned int Ax, int Bp, int Bj, unsigned int Bx)
+ bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ long long Ax, int Bp, int Bj, long long Bx)
+ bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned long long Ax, int Bp, int Bj, unsigned long long Bx)
+ bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ float Ax, int Bp, int Bj, float Bx)
+ bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ double Ax, int Bp, int Bj, double Bx)
+ bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ long double Ax, int Bp, int Bj, long double Bx)
+ bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ npy_cfloat_wrapper Ax, int Bp, int Bj, npy_cfloat_wrapper Bx)
+ bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ npy_cdouble_wrapper Ax, int Bp, int Bj, npy_cdouble_wrapper Bx)
+ bsr_transpose(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ npy_clongdouble_wrapper Ax, int Bp, int Bj,
+ npy_clongdouble_wrapper Bx)
+ """
+ return _bsr.bsr_transpose(*args)
def bsr_matmat_pass2(*args):
- """
- bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
- int Aj, signed char Ax, int Bp, int Bj, signed char Bx,
- int Cp, int Cj, signed char Cx)
- bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
- int Aj, unsigned char Ax, int Bp, int Bj, unsigned char Bx,
- int Cp, int Cj, unsigned char Cx)
- bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
- int Aj, short Ax, int Bp, int Bj, short Bx,
- int Cp, int Cj, short Cx)
- bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
- int Aj, unsigned short Ax, int Bp, int Bj,
- unsigned short Bx, int Cp, int Cj, unsigned short Cx)
- bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
- int Aj, int Ax, int Bp, int Bj, int Bx, int Cp,
- int Cj, int Cx)
- bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
- int Aj, unsigned int Ax, int Bp, int Bj, unsigned int Bx,
- int Cp, int Cj, unsigned int Cx)
- bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
- int Aj, long long Ax, int Bp, int Bj, long long Bx,
- int Cp, int Cj, long long Cx)
- bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
- int Aj, unsigned long long Ax, int Bp, int Bj,
- unsigned long long Bx, int Cp, int Cj, unsigned long long Cx)
- bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
- int Aj, float Ax, int Bp, int Bj, float Bx,
- int Cp, int Cj, float Cx)
- bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
- int Aj, double Ax, int Bp, int Bj, double Bx,
- int Cp, int Cj, double Cx)
- bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
- int Aj, long double Ax, int Bp, int Bj, long double Bx,
- int Cp, int Cj, long double Cx)
- bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
- int Aj, npy_cfloat_wrapper Ax, int Bp, int Bj,
- npy_cfloat_wrapper Bx, int Cp, int Cj, npy_cfloat_wrapper Cx)
- bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
- int Aj, npy_cdouble_wrapper Ax, int Bp, int Bj,
- npy_cdouble_wrapper Bx, int Cp, int Cj,
- npy_cdouble_wrapper Cx)
- bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
- int Aj, npy_clongdouble_wrapper Ax, int Bp,
- int Bj, npy_clongdouble_wrapper Bx, int Cp,
- int Cj, npy_clongdouble_wrapper Cx)
"""
- return _bsr.bsr_matmat_pass2(*args)
+ bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
+ int Aj, signed char Ax, int Bp, int Bj, signed char Bx,
+ int Cp, int Cj, signed char Cx)
+ bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
+ int Aj, unsigned char Ax, int Bp, int Bj, unsigned char Bx,
+ int Cp, int Cj, unsigned char Cx)
+ bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
+ int Aj, short Ax, int Bp, int Bj, short Bx,
+ int Cp, int Cj, short Cx)
+ bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
+ int Aj, unsigned short Ax, int Bp, int Bj,
+ unsigned short Bx, int Cp, int Cj, unsigned short Cx)
+ bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
+ int Aj, int Ax, int Bp, int Bj, int Bx, int Cp,
+ int Cj, int Cx)
+ bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
+ int Aj, unsigned int Ax, int Bp, int Bj, unsigned int Bx,
+ int Cp, int Cj, unsigned int Cx)
+ bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
+ int Aj, long long Ax, int Bp, int Bj, long long Bx,
+ int Cp, int Cj, long long Cx)
+ bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
+ int Aj, unsigned long long Ax, int Bp, int Bj,
+ unsigned long long Bx, int Cp, int Cj, unsigned long long Cx)
+ bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
+ int Aj, float Ax, int Bp, int Bj, float Bx,
+ int Cp, int Cj, float Cx)
+ bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
+ int Aj, double Ax, int Bp, int Bj, double Bx,
+ int Cp, int Cj, double Cx)
+ bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
+ int Aj, long double Ax, int Bp, int Bj, long double Bx,
+ int Cp, int Cj, long double Cx)
+ bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
+ int Aj, npy_cfloat_wrapper Ax, int Bp, int Bj,
+ npy_cfloat_wrapper Bx, int Cp, int Cj, npy_cfloat_wrapper Cx)
+ bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
+ int Aj, npy_cdouble_wrapper Ax, int Bp, int Bj,
+ npy_cdouble_wrapper Bx, int Cp, int Cj,
+ npy_cdouble_wrapper Cx)
+ bsr_matmat_pass2(int n_brow, int n_bcol, int R, int C, int N, int Ap,
+ int Aj, npy_clongdouble_wrapper Ax, int Bp,
+ int Bj, npy_clongdouble_wrapper Bx, int Cp,
+ int Cj, npy_clongdouble_wrapper Cx)
+ """
+ return _bsr.bsr_matmat_pass2(*args)
def bsr_matvec(*args):
- """
- bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- signed char Ax, signed char Xx, signed char Yx)
- bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned char Ax, unsigned char Xx, unsigned char Yx)
- bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- short Ax, short Xx, short Yx)
- bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned short Ax, unsigned short Xx, unsigned short Yx)
- bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- int Ax, int Xx, int Yx)
- bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned int Ax, unsigned int Xx, unsigned int Yx)
- bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- long long Ax, long long Xx, long long Yx)
- bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned long long Ax, unsigned long long Xx,
- unsigned long long Yx)
- bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- float Ax, float Xx, float Yx)
- bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- double Ax, double Xx, double Yx)
- bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- long double Ax, long double Xx, long double Yx)
- bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- npy_cfloat_wrapper Ax, npy_cfloat_wrapper Xx,
- npy_cfloat_wrapper Yx)
- bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- npy_cdouble_wrapper Ax, npy_cdouble_wrapper Xx,
- npy_cdouble_wrapper Yx)
- bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- npy_clongdouble_wrapper Ax, npy_clongdouble_wrapper Xx,
- npy_clongdouble_wrapper Yx)
"""
- return _bsr.bsr_matvec(*args)
+ bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ signed char Ax, signed char Xx, signed char Yx)
+ bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned char Ax, unsigned char Xx, unsigned char Yx)
+ bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ short Ax, short Xx, short Yx)
+ bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned short Ax, unsigned short Xx, unsigned short Yx)
+ bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ int Ax, int Xx, int Yx)
+ bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned int Ax, unsigned int Xx, unsigned int Yx)
+ bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ long long Ax, long long Xx, long long Yx)
+ bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned long long Ax, unsigned long long Xx,
+ unsigned long long Yx)
+ bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ float Ax, float Xx, float Yx)
+ bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ double Ax, double Xx, double Yx)
+ bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ long double Ax, long double Xx, long double Yx)
+ bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ npy_cfloat_wrapper Ax, npy_cfloat_wrapper Xx,
+ npy_cfloat_wrapper Yx)
+ bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ npy_cdouble_wrapper Ax, npy_cdouble_wrapper Xx,
+ npy_cdouble_wrapper Yx)
+ bsr_matvec(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ npy_clongdouble_wrapper Ax, npy_clongdouble_wrapper Xx,
+ npy_clongdouble_wrapper Yx)
+ """
+ return _bsr.bsr_matvec(*args)
def bsr_matvecs(*args):
- """
- bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
- int Aj, signed char Ax, signed char Xx,
- signed char Yx)
- bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
- int Aj, unsigned char Ax, unsigned char Xx,
- unsigned char Yx)
- bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
- int Aj, short Ax, short Xx, short Yx)
- bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
- int Aj, unsigned short Ax, unsigned short Xx,
- unsigned short Yx)
- bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
- int Aj, int Ax, int Xx, int Yx)
- bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
- int Aj, unsigned int Ax, unsigned int Xx,
- unsigned int Yx)
- bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
- int Aj, long long Ax, long long Xx, long long Yx)
- bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
- int Aj, unsigned long long Ax, unsigned long long Xx,
- unsigned long long Yx)
- bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
- int Aj, float Ax, float Xx, float Yx)
- bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
- int Aj, double Ax, double Xx, double Yx)
- bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
- int Aj, long double Ax, long double Xx,
- long double Yx)
- bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
- int Aj, npy_cfloat_wrapper Ax, npy_cfloat_wrapper Xx,
- npy_cfloat_wrapper Yx)
- bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
- int Aj, npy_cdouble_wrapper Ax, npy_cdouble_wrapper Xx,
- npy_cdouble_wrapper Yx)
- bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
- int Aj, npy_clongdouble_wrapper Ax, npy_clongdouble_wrapper Xx,
- npy_clongdouble_wrapper Yx)
"""
- return _bsr.bsr_matvecs(*args)
+ bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
+ int Aj, signed char Ax, signed char Xx,
+ signed char Yx)
+ bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
+ int Aj, unsigned char Ax, unsigned char Xx,
+ unsigned char Yx)
+ bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
+ int Aj, short Ax, short Xx, short Yx)
+ bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
+ int Aj, unsigned short Ax, unsigned short Xx,
+ unsigned short Yx)
+ bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
+ int Aj, int Ax, int Xx, int Yx)
+ bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
+ int Aj, unsigned int Ax, unsigned int Xx,
+ unsigned int Yx)
+ bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
+ int Aj, long long Ax, long long Xx, long long Yx)
+ bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
+ int Aj, unsigned long long Ax, unsigned long long Xx,
+ unsigned long long Yx)
+ bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
+ int Aj, float Ax, float Xx, float Yx)
+ bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
+ int Aj, double Ax, double Xx, double Yx)
+ bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
+ int Aj, long double Ax, long double Xx,
+ long double Yx)
+ bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
+ int Aj, npy_cfloat_wrapper Ax, npy_cfloat_wrapper Xx,
+ npy_cfloat_wrapper Yx)
+ bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
+ int Aj, npy_cdouble_wrapper Ax, npy_cdouble_wrapper Xx,
+ npy_cdouble_wrapper Yx)
+ bsr_matvecs(int n_brow, int n_bcol, int n_vecs, int R, int C, int Ap,
+ int Aj, npy_clongdouble_wrapper Ax, npy_clongdouble_wrapper Xx,
+ npy_clongdouble_wrapper Yx)
+ """
+ return _bsr.bsr_matvecs(*args)
def bsr_elmul_bsr(*args):
- """
- bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- signed char Ax, int Bp, int Bj, signed char Bx,
- int Cp, int Cj, signed char Cx)
- bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- unsigned char Ax, int Bp, int Bj, unsigned char Bx,
- int Cp, int Cj, unsigned char Cx)
- bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- short Ax, int Bp, int Bj, short Bx, int Cp,
- int Cj, short Cx)
- bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- unsigned short Ax, int Bp, int Bj, unsigned short Bx,
- int Cp, int Cj, unsigned short Cx)
- bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- int Ax, int Bp, int Bj, int Bx, int Cp, int Cj,
- int Cx)
- bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- unsigned int Ax, int Bp, int Bj, unsigned int Bx,
- int Cp, int Cj, unsigned int Cx)
- bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- long long Ax, int Bp, int Bj, long long Bx,
- int Cp, int Cj, long long Cx)
- bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- unsigned long long Ax, int Bp, int Bj, unsigned long long Bx,
- int Cp, int Cj, unsigned long long Cx)
- bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- float Ax, int Bp, int Bj, float Bx, int Cp,
- int Cj, float Cx)
- bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- double Ax, int Bp, int Bj, double Bx, int Cp,
- int Cj, double Cx)
- bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- long double Ax, int Bp, int Bj, long double Bx,
- int Cp, int Cj, long double Cx)
- bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- npy_cfloat_wrapper Ax, int Bp, int Bj, npy_cfloat_wrapper Bx,
- int Cp, int Cj, npy_cfloat_wrapper Cx)
- bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- npy_cdouble_wrapper Ax, int Bp, int Bj, npy_cdouble_wrapper Bx,
- int Cp, int Cj, npy_cdouble_wrapper Cx)
- bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- npy_clongdouble_wrapper Ax, int Bp, int Bj,
- npy_clongdouble_wrapper Bx, int Cp, int Cj, npy_clongdouble_wrapper Cx)
"""
- return _bsr.bsr_elmul_bsr(*args)
+ bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ signed char Ax, int Bp, int Bj, signed char Bx,
+ int Cp, int Cj, signed char Cx)
+ bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ unsigned char Ax, int Bp, int Bj, unsigned char Bx,
+ int Cp, int Cj, unsigned char Cx)
+ bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ short Ax, int Bp, int Bj, short Bx, int Cp,
+ int Cj, short Cx)
+ bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ unsigned short Ax, int Bp, int Bj, unsigned short Bx,
+ int Cp, int Cj, unsigned short Cx)
+ bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ int Ax, int Bp, int Bj, int Bx, int Cp, int Cj,
+ int Cx)
+ bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ unsigned int Ax, int Bp, int Bj, unsigned int Bx,
+ int Cp, int Cj, unsigned int Cx)
+ bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ long long Ax, int Bp, int Bj, long long Bx,
+ int Cp, int Cj, long long Cx)
+ bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ unsigned long long Ax, int Bp, int Bj, unsigned long long Bx,
+ int Cp, int Cj, unsigned long long Cx)
+ bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ float Ax, int Bp, int Bj, float Bx, int Cp,
+ int Cj, float Cx)
+ bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ double Ax, int Bp, int Bj, double Bx, int Cp,
+ int Cj, double Cx)
+ bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ long double Ax, int Bp, int Bj, long double Bx,
+ int Cp, int Cj, long double Cx)
+ bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ npy_cfloat_wrapper Ax, int Bp, int Bj, npy_cfloat_wrapper Bx,
+ int Cp, int Cj, npy_cfloat_wrapper Cx)
+ bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ npy_cdouble_wrapper Ax, int Bp, int Bj, npy_cdouble_wrapper Bx,
+ int Cp, int Cj, npy_cdouble_wrapper Cx)
+ bsr_elmul_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ npy_clongdouble_wrapper Ax, int Bp, int Bj,
+ npy_clongdouble_wrapper Bx, int Cp, int Cj, npy_clongdouble_wrapper Cx)
+ """
+ return _bsr.bsr_elmul_bsr(*args)
def bsr_eldiv_bsr(*args):
- """
- bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- signed char Ax, int Bp, int Bj, signed char Bx,
- int Cp, int Cj, signed char Cx)
- bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- unsigned char Ax, int Bp, int Bj, unsigned char Bx,
- int Cp, int Cj, unsigned char Cx)
- bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- short Ax, int Bp, int Bj, short Bx, int Cp,
- int Cj, short Cx)
- bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- unsigned short Ax, int Bp, int Bj, unsigned short Bx,
- int Cp, int Cj, unsigned short Cx)
- bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- int Ax, int Bp, int Bj, int Bx, int Cp, int Cj,
- int Cx)
- bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- unsigned int Ax, int Bp, int Bj, unsigned int Bx,
- int Cp, int Cj, unsigned int Cx)
- bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- long long Ax, int Bp, int Bj, long long Bx,
- int Cp, int Cj, long long Cx)
- bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- unsigned long long Ax, int Bp, int Bj, unsigned long long Bx,
- int Cp, int Cj, unsigned long long Cx)
- bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- float Ax, int Bp, int Bj, float Bx, int Cp,
- int Cj, float Cx)
- bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- double Ax, int Bp, int Bj, double Bx, int Cp,
- int Cj, double Cx)
- bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- long double Ax, int Bp, int Bj, long double Bx,
- int Cp, int Cj, long double Cx)
- bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- npy_cfloat_wrapper Ax, int Bp, int Bj, npy_cfloat_wrapper Bx,
- int Cp, int Cj, npy_cfloat_wrapper Cx)
- bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- npy_cdouble_wrapper Ax, int Bp, int Bj, npy_cdouble_wrapper Bx,
- int Cp, int Cj, npy_cdouble_wrapper Cx)
- bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- npy_clongdouble_wrapper Ax, int Bp, int Bj,
- npy_clongdouble_wrapper Bx, int Cp, int Cj, npy_clongdouble_wrapper Cx)
"""
- return _bsr.bsr_eldiv_bsr(*args)
+ bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ signed char Ax, int Bp, int Bj, signed char Bx,
+ int Cp, int Cj, signed char Cx)
+ bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ unsigned char Ax, int Bp, int Bj, unsigned char Bx,
+ int Cp, int Cj, unsigned char Cx)
+ bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ short Ax, int Bp, int Bj, short Bx, int Cp,
+ int Cj, short Cx)
+ bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ unsigned short Ax, int Bp, int Bj, unsigned short Bx,
+ int Cp, int Cj, unsigned short Cx)
+ bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ int Ax, int Bp, int Bj, int Bx, int Cp, int Cj,
+ int Cx)
+ bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ unsigned int Ax, int Bp, int Bj, unsigned int Bx,
+ int Cp, int Cj, unsigned int Cx)
+ bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ long long Ax, int Bp, int Bj, long long Bx,
+ int Cp, int Cj, long long Cx)
+ bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ unsigned long long Ax, int Bp, int Bj, unsigned long long Bx,
+ int Cp, int Cj, unsigned long long Cx)
+ bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ float Ax, int Bp, int Bj, float Bx, int Cp,
+ int Cj, float Cx)
+ bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ double Ax, int Bp, int Bj, double Bx, int Cp,
+ int Cj, double Cx)
+ bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ long double Ax, int Bp, int Bj, long double Bx,
+ int Cp, int Cj, long double Cx)
+ bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ npy_cfloat_wrapper Ax, int Bp, int Bj, npy_cfloat_wrapper Bx,
+ int Cp, int Cj, npy_cfloat_wrapper Cx)
+ bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ npy_cdouble_wrapper Ax, int Bp, int Bj, npy_cdouble_wrapper Bx,
+ int Cp, int Cj, npy_cdouble_wrapper Cx)
+ bsr_eldiv_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ npy_clongdouble_wrapper Ax, int Bp, int Bj,
+ npy_clongdouble_wrapper Bx, int Cp, int Cj, npy_clongdouble_wrapper Cx)
+ """
+ return _bsr.bsr_eldiv_bsr(*args)
def bsr_plus_bsr(*args):
- """
- bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- signed char Ax, int Bp, int Bj, signed char Bx,
- int Cp, int Cj, signed char Cx)
- bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- unsigned char Ax, int Bp, int Bj, unsigned char Bx,
- int Cp, int Cj, unsigned char Cx)
- bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- short Ax, int Bp, int Bj, short Bx, int Cp,
- int Cj, short Cx)
- bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- unsigned short Ax, int Bp, int Bj, unsigned short Bx,
- int Cp, int Cj, unsigned short Cx)
- bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- int Ax, int Bp, int Bj, int Bx, int Cp, int Cj,
- int Cx)
- bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- unsigned int Ax, int Bp, int Bj, unsigned int Bx,
- int Cp, int Cj, unsigned int Cx)
- bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- long long Ax, int Bp, int Bj, long long Bx,
- int Cp, int Cj, long long Cx)
- bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- unsigned long long Ax, int Bp, int Bj, unsigned long long Bx,
- int Cp, int Cj, unsigned long long Cx)
- bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- float Ax, int Bp, int Bj, float Bx, int Cp,
- int Cj, float Cx)
- bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- double Ax, int Bp, int Bj, double Bx, int Cp,
- int Cj, double Cx)
- bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- long double Ax, int Bp, int Bj, long double Bx,
- int Cp, int Cj, long double Cx)
- bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- npy_cfloat_wrapper Ax, int Bp, int Bj, npy_cfloat_wrapper Bx,
- int Cp, int Cj, npy_cfloat_wrapper Cx)
- bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- npy_cdouble_wrapper Ax, int Bp, int Bj, npy_cdouble_wrapper Bx,
- int Cp, int Cj, npy_cdouble_wrapper Cx)
- bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- npy_clongdouble_wrapper Ax, int Bp, int Bj,
- npy_clongdouble_wrapper Bx, int Cp, int Cj, npy_clongdouble_wrapper Cx)
"""
- return _bsr.bsr_plus_bsr(*args)
+ bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ signed char Ax, int Bp, int Bj, signed char Bx,
+ int Cp, int Cj, signed char Cx)
+ bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ unsigned char Ax, int Bp, int Bj, unsigned char Bx,
+ int Cp, int Cj, unsigned char Cx)
+ bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ short Ax, int Bp, int Bj, short Bx, int Cp,
+ int Cj, short Cx)
+ bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ unsigned short Ax, int Bp, int Bj, unsigned short Bx,
+ int Cp, int Cj, unsigned short Cx)
+ bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ int Ax, int Bp, int Bj, int Bx, int Cp, int Cj,
+ int Cx)
+ bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ unsigned int Ax, int Bp, int Bj, unsigned int Bx,
+ int Cp, int Cj, unsigned int Cx)
+ bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ long long Ax, int Bp, int Bj, long long Bx,
+ int Cp, int Cj, long long Cx)
+ bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ unsigned long long Ax, int Bp, int Bj, unsigned long long Bx,
+ int Cp, int Cj, unsigned long long Cx)
+ bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ float Ax, int Bp, int Bj, float Bx, int Cp,
+ int Cj, float Cx)
+ bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ double Ax, int Bp, int Bj, double Bx, int Cp,
+ int Cj, double Cx)
+ bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ long double Ax, int Bp, int Bj, long double Bx,
+ int Cp, int Cj, long double Cx)
+ bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ npy_cfloat_wrapper Ax, int Bp, int Bj, npy_cfloat_wrapper Bx,
+ int Cp, int Cj, npy_cfloat_wrapper Cx)
+ bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ npy_cdouble_wrapper Ax, int Bp, int Bj, npy_cdouble_wrapper Bx,
+ int Cp, int Cj, npy_cdouble_wrapper Cx)
+ bsr_plus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ npy_clongdouble_wrapper Ax, int Bp, int Bj,
+ npy_clongdouble_wrapper Bx, int Cp, int Cj, npy_clongdouble_wrapper Cx)
+ """
+ return _bsr.bsr_plus_bsr(*args)
def bsr_minus_bsr(*args):
- """
- bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- signed char Ax, int Bp, int Bj, signed char Bx,
- int Cp, int Cj, signed char Cx)
- bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- unsigned char Ax, int Bp, int Bj, unsigned char Bx,
- int Cp, int Cj, unsigned char Cx)
- bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- short Ax, int Bp, int Bj, short Bx, int Cp,
- int Cj, short Cx)
- bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- unsigned short Ax, int Bp, int Bj, unsigned short Bx,
- int Cp, int Cj, unsigned short Cx)
- bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- int Ax, int Bp, int Bj, int Bx, int Cp, int Cj,
- int Cx)
- bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- unsigned int Ax, int Bp, int Bj, unsigned int Bx,
- int Cp, int Cj, unsigned int Cx)
- bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- long long Ax, int Bp, int Bj, long long Bx,
- int Cp, int Cj, long long Cx)
- bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- unsigned long long Ax, int Bp, int Bj, unsigned long long Bx,
- int Cp, int Cj, unsigned long long Cx)
- bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- float Ax, int Bp, int Bj, float Bx, int Cp,
- int Cj, float Cx)
- bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- double Ax, int Bp, int Bj, double Bx, int Cp,
- int Cj, double Cx)
- bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- long double Ax, int Bp, int Bj, long double Bx,
- int Cp, int Cj, long double Cx)
- bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- npy_cfloat_wrapper Ax, int Bp, int Bj, npy_cfloat_wrapper Bx,
- int Cp, int Cj, npy_cfloat_wrapper Cx)
- bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- npy_cdouble_wrapper Ax, int Bp, int Bj, npy_cdouble_wrapper Bx,
- int Cp, int Cj, npy_cdouble_wrapper Cx)
- bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- npy_clongdouble_wrapper Ax, int Bp, int Bj,
- npy_clongdouble_wrapper Bx, int Cp, int Cj, npy_clongdouble_wrapper Cx)
"""
- return _bsr.bsr_minus_bsr(*args)
+ bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ signed char Ax, int Bp, int Bj, signed char Bx,
+ int Cp, int Cj, signed char Cx)
+ bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ unsigned char Ax, int Bp, int Bj, unsigned char Bx,
+ int Cp, int Cj, unsigned char Cx)
+ bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ short Ax, int Bp, int Bj, short Bx, int Cp,
+ int Cj, short Cx)
+ bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ unsigned short Ax, int Bp, int Bj, unsigned short Bx,
+ int Cp, int Cj, unsigned short Cx)
+ bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ int Ax, int Bp, int Bj, int Bx, int Cp, int Cj,
+ int Cx)
+ bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ unsigned int Ax, int Bp, int Bj, unsigned int Bx,
+ int Cp, int Cj, unsigned int Cx)
+ bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ long long Ax, int Bp, int Bj, long long Bx,
+ int Cp, int Cj, long long Cx)
+ bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ unsigned long long Ax, int Bp, int Bj, unsigned long long Bx,
+ int Cp, int Cj, unsigned long long Cx)
+ bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ float Ax, int Bp, int Bj, float Bx, int Cp,
+ int Cj, float Cx)
+ bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ double Ax, int Bp, int Bj, double Bx, int Cp,
+ int Cj, double Cx)
+ bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ long double Ax, int Bp, int Bj, long double Bx,
+ int Cp, int Cj, long double Cx)
+ bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ npy_cfloat_wrapper Ax, int Bp, int Bj, npy_cfloat_wrapper Bx,
+ int Cp, int Cj, npy_cfloat_wrapper Cx)
+ bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ npy_cdouble_wrapper Ax, int Bp, int Bj, npy_cdouble_wrapper Bx,
+ int Cp, int Cj, npy_cdouble_wrapper Cx)
+ bsr_minus_bsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ npy_clongdouble_wrapper Ax, int Bp, int Bj,
+ npy_clongdouble_wrapper Bx, int Cp, int Cj, npy_clongdouble_wrapper Cx)
+ """
+ return _bsr.bsr_minus_bsr(*args)
def bsr_sort_indices(*args):
- """
- bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- signed char Ax)
- bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned char Ax)
- bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- short Ax)
- bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned short Ax)
- bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- int Ax)
- bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned int Ax)
- bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- long long Ax)
- bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- unsigned long long Ax)
- bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- float Ax)
- bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- double Ax)
- bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- long double Ax)
- bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- npy_cfloat_wrapper Ax)
- bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- npy_cdouble_wrapper Ax)
- bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
- npy_clongdouble_wrapper Ax)
"""
- return _bsr.bsr_sort_indices(*args)
-
+ bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ signed char Ax)
+ bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned char Ax)
+ bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ short Ax)
+ bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned short Ax)
+ bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ int Ax)
+ bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned int Ax)
+ bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ long long Ax)
+ bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ unsigned long long Ax)
+ bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ float Ax)
+ bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ double Ax)
+ bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ long double Ax)
+ bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ npy_cfloat_wrapper Ax)
+ bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ npy_cdouble_wrapper Ax)
+ bsr_sort_indices(int n_brow, int n_bcol, int R, int C, int Ap, int Aj,
+ npy_clongdouble_wrapper Ax)
+ """
+ return _bsr.bsr_sort_indices(*args)
Modified: branches/refactor_fft/scipy/sparse/sparsetools/coo.py
===================================================================
--- branches/refactor_fft/scipy/sparse/sparsetools/coo.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/sparse/sparsetools/coo.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -50,135 +50,134 @@
def coo_count_diagonals(*args):
- """coo_count_diagonals(int nnz, int Ai, int Aj) -> int"""
- return _coo.coo_count_diagonals(*args)
+ """coo_count_diagonals(int nnz, int Ai, int Aj) -> int"""
+ return _coo.coo_count_diagonals(*args)
def coo_tocsr(*args):
- """
- coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, signed char Ax,
- int Bp, int Bj, signed char Bx)
- coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned char Ax,
- int Bp, int Bj, unsigned char Bx)
- coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, short Ax,
- int Bp, int Bj, short Bx)
- coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned short Ax,
- int Bp, int Bj, unsigned short Bx)
- coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, int Ax,
- int Bp, int Bj, int Bx)
- coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned int Ax,
- int Bp, int Bj, unsigned int Bx)
- coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, long long Ax,
- int Bp, int Bj, long long Bx)
- coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned long long Ax,
- int Bp, int Bj, unsigned long long Bx)
- coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, float Ax,
- int Bp, int Bj, float Bx)
- coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, double Ax,
- int Bp, int Bj, double Bx)
- coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, long double Ax,
- int Bp, int Bj, long double Bx)
- coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, npy_cfloat_wrapper Ax,
- int Bp, int Bj, npy_cfloat_wrapper Bx)
- coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, npy_cdouble_wrapper Ax,
- int Bp, int Bj, npy_cdouble_wrapper Bx)
- coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, npy_clongdouble_wrapper Ax,
- int Bp, int Bj, npy_clongdouble_wrapper Bx)
"""
- return _coo.coo_tocsr(*args)
+ coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, signed char Ax,
+ int Bp, int Bj, signed char Bx)
+ coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned char Ax,
+ int Bp, int Bj, unsigned char Bx)
+ coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, short Ax,
+ int Bp, int Bj, short Bx)
+ coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned short Ax,
+ int Bp, int Bj, unsigned short Bx)
+ coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, int Ax,
+ int Bp, int Bj, int Bx)
+ coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned int Ax,
+ int Bp, int Bj, unsigned int Bx)
+ coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, long long Ax,
+ int Bp, int Bj, long long Bx)
+ coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned long long Ax,
+ int Bp, int Bj, unsigned long long Bx)
+ coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, float Ax,
+ int Bp, int Bj, float Bx)
+ coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, double Ax,
+ int Bp, int Bj, double Bx)
+ coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, long double Ax,
+ int Bp, int Bj, long double Bx)
+ coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, npy_cfloat_wrapper Ax,
+ int Bp, int Bj, npy_cfloat_wrapper Bx)
+ coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, npy_cdouble_wrapper Ax,
+ int Bp, int Bj, npy_cdouble_wrapper Bx)
+ coo_tocsr(int n_row, int n_col, int nnz, int Ai, int Aj, npy_clongdouble_wrapper Ax,
+ int Bp, int Bj, npy_clongdouble_wrapper Bx)
+ """
+ return _coo.coo_tocsr(*args)
def coo_tocsc(*args):
- """
- coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, signed char Ax,
- int Bp, int Bi, signed char Bx)
- coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned char Ax,
- int Bp, int Bi, unsigned char Bx)
- coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, short Ax,
- int Bp, int Bi, short Bx)
- coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned short Ax,
- int Bp, int Bi, unsigned short Bx)
- coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, int Ax,
- int Bp, int Bi, int Bx)
- coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned int Ax,
- int Bp, int Bi, unsigned int Bx)
- coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, long long Ax,
- int Bp, int Bi, long long Bx)
- coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned long long Ax,
- int Bp, int Bi, unsigned long long Bx)
- coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, float Ax,
- int Bp, int Bi, float Bx)
- coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, double Ax,
- int Bp, int Bi, double Bx)
- coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, long double Ax,
- int Bp, int Bi, long double Bx)
- coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, npy_cfloat_wrapper Ax,
- int Bp, int Bi, npy_cfloat_wrapper Bx)
- coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, npy_cdouble_wrapper Ax,
- int Bp, int Bi, npy_cdouble_wrapper Bx)
- coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, npy_clongdouble_wrapper Ax,
- int Bp, int Bi, npy_clongdouble_wrapper Bx)
"""
- return _coo.coo_tocsc(*args)
+ coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, signed char Ax,
+ int Bp, int Bi, signed char Bx)
+ coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned char Ax,
+ int Bp, int Bi, unsigned char Bx)
+ coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, short Ax,
+ int Bp, int Bi, short Bx)
+ coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned short Ax,
+ int Bp, int Bi, unsigned short Bx)
+ coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, int Ax,
+ int Bp, int Bi, int Bx)
+ coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned int Ax,
+ int Bp, int Bi, unsigned int Bx)
+ coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, long long Ax,
+ int Bp, int Bi, long long Bx)
+ coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned long long Ax,
+ int Bp, int Bi, unsigned long long Bx)
+ coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, float Ax,
+ int Bp, int Bi, float Bx)
+ coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, double Ax,
+ int Bp, int Bi, double Bx)
+ coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, long double Ax,
+ int Bp, int Bi, long double Bx)
+ coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, npy_cfloat_wrapper Ax,
+ int Bp, int Bi, npy_cfloat_wrapper Bx)
+ coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, npy_cdouble_wrapper Ax,
+ int Bp, int Bi, npy_cdouble_wrapper Bx)
+ coo_tocsc(int n_row, int n_col, int nnz, int Ai, int Aj, npy_clongdouble_wrapper Ax,
+ int Bp, int Bi, npy_clongdouble_wrapper Bx)
+ """
+ return _coo.coo_tocsc(*args)
def coo_todense(*args):
- """
- coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, signed char Ax,
- signed char Bx)
- coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned char Ax,
- unsigned char Bx)
- coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, short Ax,
- short Bx)
- coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned short Ax,
- unsigned short Bx)
- coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, int Ax,
- int Bx)
- coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned int Ax,
- unsigned int Bx)
- coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, long long Ax,
- long long Bx)
- coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned long long Ax,
- unsigned long long Bx)
- coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, float Ax,
- float Bx)
- coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, double Ax,
- double Bx)
- coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, long double Ax,
- long double Bx)
- coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, npy_cfloat_wrapper Ax,
- npy_cfloat_wrapper Bx)
- coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, npy_cdouble_wrapper Ax,
- npy_cdouble_wrapper Bx)
- coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, npy_clongdouble_wrapper Ax,
- npy_clongdouble_wrapper Bx)
"""
- return _coo.coo_todense(*args)
+ coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, signed char Ax,
+ signed char Bx)
+ coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned char Ax,
+ unsigned char Bx)
+ coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, short Ax,
+ short Bx)
+ coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned short Ax,
+ unsigned short Bx)
+ coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, int Ax,
+ int Bx)
+ coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned int Ax,
+ unsigned int Bx)
+ coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, long long Ax,
+ long long Bx)
+ coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, unsigned long long Ax,
+ unsigned long long Bx)
+ coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, float Ax,
+ float Bx)
+ coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, double Ax,
+ double Bx)
+ coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, long double Ax,
+ long double Bx)
+ coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, npy_cfloat_wrapper Ax,
+ npy_cfloat_wrapper Bx)
+ coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, npy_cdouble_wrapper Ax,
+ npy_cdouble_wrapper Bx)
+ coo_todense(int n_row, int n_col, int nnz, int Ai, int Aj, npy_clongdouble_wrapper Ax,
+ npy_clongdouble_wrapper Bx)
+ """
+ return _coo.coo_todense(*args)
def coo_matvec(*args):
- """
- coo_matvec(int nnz, int Ai, int Aj, signed char Ax, signed char Xx,
- signed char Yx)
- coo_matvec(int nnz, int Ai, int Aj, unsigned char Ax, unsigned char Xx,
- unsigned char Yx)
- coo_matvec(int nnz, int Ai, int Aj, short Ax, short Xx, short Yx)
- coo_matvec(int nnz, int Ai, int Aj, unsigned short Ax, unsigned short Xx,
- unsigned short Yx)
- coo_matvec(int nnz, int Ai, int Aj, int Ax, int Xx, int Yx)
- coo_matvec(int nnz, int Ai, int Aj, unsigned int Ax, unsigned int Xx,
- unsigned int Yx)
- coo_matvec(int nnz, int Ai, int Aj, long long Ax, long long Xx,
- long long Yx)
- coo_matvec(int nnz, int Ai, int Aj, unsigned long long Ax, unsigned long long Xx,
- unsigned long long Yx)
- coo_matvec(int nnz, int Ai, int Aj, float Ax, float Xx, float Yx)
- coo_matvec(int nnz, int Ai, int Aj, double Ax, double Xx, double Yx)
- coo_matvec(int nnz, int Ai, int Aj, long double Ax, long double Xx,
- long double Yx)
- coo_matvec(int nnz, int Ai, int Aj, npy_cfloat_wrapper Ax, npy_cfloat_wrapper Xx,
- npy_cfloat_wrapper Yx)
- coo_matvec(int nnz, int Ai, int Aj, npy_cdouble_wrapper Ax, npy_cdouble_wrapper Xx,
- npy_cdouble_wrapper Yx)
- coo_matvec(int nnz, int Ai, int Aj, npy_clongdouble_wrapper Ax,
- npy_clongdouble_wrapper Xx, npy_clongdouble_wrapper Yx)
"""
- return _coo.coo_matvec(*args)
-
+ coo_matvec(int nnz, int Ai, int Aj, signed char Ax, signed char Xx,
+ signed char Yx)
+ coo_matvec(int nnz, int Ai, int Aj, unsigned char Ax, unsigned char Xx,
+ unsigned char Yx)
+ coo_matvec(int nnz, int Ai, int Aj, short Ax, short Xx, short Yx)
+ coo_matvec(int nnz, int Ai, int Aj, unsigned short Ax, unsigned short Xx,
+ unsigned short Yx)
+ coo_matvec(int nnz, int Ai, int Aj, int Ax, int Xx, int Yx)
+ coo_matvec(int nnz, int Ai, int Aj, unsigned int Ax, unsigned int Xx,
+ unsigned int Yx)
+ coo_matvec(int nnz, int Ai, int Aj, long long Ax, long long Xx,
+ long long Yx)
+ coo_matvec(int nnz, int Ai, int Aj, unsigned long long Ax, unsigned long long Xx,
+ unsigned long long Yx)
+ coo_matvec(int nnz, int Ai, int Aj, float Ax, float Xx, float Yx)
+ coo_matvec(int nnz, int Ai, int Aj, double Ax, double Xx, double Yx)
+ coo_matvec(int nnz, int Ai, int Aj, long double Ax, long double Xx,
+ long double Yx)
+ coo_matvec(int nnz, int Ai, int Aj, npy_cfloat_wrapper Ax, npy_cfloat_wrapper Xx,
+ npy_cfloat_wrapper Yx)
+ coo_matvec(int nnz, int Ai, int Aj, npy_cdouble_wrapper Ax, npy_cdouble_wrapper Xx,
+ npy_cdouble_wrapper Yx)
+ coo_matvec(int nnz, int Ai, int Aj, npy_clongdouble_wrapper Ax,
+ npy_clongdouble_wrapper Xx, npy_clongdouble_wrapper Yx)
+ """
+ return _coo.coo_matvec(*args)
Modified: branches/refactor_fft/scipy/sparse/sparsetools/csc.py
===================================================================
--- branches/refactor_fft/scipy/sparse/sparsetools/csc.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/sparse/sparsetools/csc.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -50,357 +50,356 @@
def csc_matmat_pass1(*args):
- """
- csc_matmat_pass1(int n_row, int n_col, int Ap, int Ai, int Bp, int Bi,
- int Cp)
"""
- return _csc.csc_matmat_pass1(*args)
+ csc_matmat_pass1(int n_row, int n_col, int Ap, int Ai, int Bp, int Bi,
+ int Cp)
+ """
+ return _csc.csc_matmat_pass1(*args)
def csc_diagonal(*args):
- """
- csc_diagonal(int n_row, int n_col, int Ap, int Aj, signed char Ax,
- signed char Yx)
- csc_diagonal(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
- unsigned char Yx)
- csc_diagonal(int n_row, int n_col, int Ap, int Aj, short Ax, short Yx)
- csc_diagonal(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
- unsigned short Yx)
- csc_diagonal(int n_row, int n_col, int Ap, int Aj, int Ax, int Yx)
- csc_diagonal(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
- unsigned int Yx)
- csc_diagonal(int n_row, int n_col, int Ap, int Aj, long long Ax,
- long long Yx)
- csc_diagonal(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
- unsigned long long Yx)
- csc_diagonal(int n_row, int n_col, int Ap, int Aj, float Ax, float Yx)
- csc_diagonal(int n_row, int n_col, int Ap, int Aj, double Ax, double Yx)
- csc_diagonal(int n_row, int n_col, int Ap, int Aj, long double Ax,
- long double Yx)
- csc_diagonal(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
- npy_cfloat_wrapper Yx)
- csc_diagonal(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
- npy_cdouble_wrapper Yx)
- csc_diagonal(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
- npy_clongdouble_wrapper Yx)
"""
- return _csc.csc_diagonal(*args)
+ csc_diagonal(int n_row, int n_col, int Ap, int Aj, signed char Ax,
+ signed char Yx)
+ csc_diagonal(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
+ unsigned char Yx)
+ csc_diagonal(int n_row, int n_col, int Ap, int Aj, short Ax, short Yx)
+ csc_diagonal(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
+ unsigned short Yx)
+ csc_diagonal(int n_row, int n_col, int Ap, int Aj, int Ax, int Yx)
+ csc_diagonal(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
+ unsigned int Yx)
+ csc_diagonal(int n_row, int n_col, int Ap, int Aj, long long Ax,
+ long long Yx)
+ csc_diagonal(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
+ unsigned long long Yx)
+ csc_diagonal(int n_row, int n_col, int Ap, int Aj, float Ax, float Yx)
+ csc_diagonal(int n_row, int n_col, int Ap, int Aj, double Ax, double Yx)
+ csc_diagonal(int n_row, int n_col, int Ap, int Aj, long double Ax,
+ long double Yx)
+ csc_diagonal(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
+ npy_cfloat_wrapper Yx)
+ csc_diagonal(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
+ npy_cdouble_wrapper Yx)
+ csc_diagonal(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
+ npy_clongdouble_wrapper Yx)
+ """
+ return _csc.csc_diagonal(*args)
def csc_tocsr(*args):
- """
- csc_tocsr(int n_row, int n_col, int Ap, int Ai, signed char Ax,
- int Bp, int Bj, signed char Bx)
- csc_tocsr(int n_row, int n_col, int Ap, int Ai, unsigned char Ax,
- int Bp, int Bj, unsigned char Bx)
- csc_tocsr(int n_row, int n_col, int Ap, int Ai, short Ax, int Bp,
- int Bj, short Bx)
- csc_tocsr(int n_row, int n_col, int Ap, int Ai, unsigned short Ax,
- int Bp, int Bj, unsigned short Bx)
- csc_tocsr(int n_row, int n_col, int Ap, int Ai, int Ax, int Bp,
- int Bj, int Bx)
- csc_tocsr(int n_row, int n_col, int Ap, int Ai, unsigned int Ax,
- int Bp, int Bj, unsigned int Bx)
- csc_tocsr(int n_row, int n_col, int Ap, int Ai, long long Ax,
- int Bp, int Bj, long long Bx)
- csc_tocsr(int n_row, int n_col, int Ap, int Ai, unsigned long long Ax,
- int Bp, int Bj, unsigned long long Bx)
- csc_tocsr(int n_row, int n_col, int Ap, int Ai, float Ax, int Bp,
- int Bj, float Bx)
- csc_tocsr(int n_row, int n_col, int Ap, int Ai, double Ax, int Bp,
- int Bj, double Bx)
- csc_tocsr(int n_row, int n_col, int Ap, int Ai, long double Ax,
- int Bp, int Bj, long double Bx)
- csc_tocsr(int n_row, int n_col, int Ap, int Ai, npy_cfloat_wrapper Ax,
- int Bp, int Bj, npy_cfloat_wrapper Bx)
- csc_tocsr(int n_row, int n_col, int Ap, int Ai, npy_cdouble_wrapper Ax,
- int Bp, int Bj, npy_cdouble_wrapper Bx)
- csc_tocsr(int n_row, int n_col, int Ap, int Ai, npy_clongdouble_wrapper Ax,
- int Bp, int Bj, npy_clongdouble_wrapper Bx)
"""
- return _csc.csc_tocsr(*args)
+ csc_tocsr(int n_row, int n_col, int Ap, int Ai, signed char Ax,
+ int Bp, int Bj, signed char Bx)
+ csc_tocsr(int n_row, int n_col, int Ap, int Ai, unsigned char Ax,
+ int Bp, int Bj, unsigned char Bx)
+ csc_tocsr(int n_row, int n_col, int Ap, int Ai, short Ax, int Bp,
+ int Bj, short Bx)
+ csc_tocsr(int n_row, int n_col, int Ap, int Ai, unsigned short Ax,
+ int Bp, int Bj, unsigned short Bx)
+ csc_tocsr(int n_row, int n_col, int Ap, int Ai, int Ax, int Bp,
+ int Bj, int Bx)
+ csc_tocsr(int n_row, int n_col, int Ap, int Ai, unsigned int Ax,
+ int Bp, int Bj, unsigned int Bx)
+ csc_tocsr(int n_row, int n_col, int Ap, int Ai, long long Ax,
+ int Bp, int Bj, long long Bx)
+ csc_tocsr(int n_row, int n_col, int Ap, int Ai, unsigned long long Ax,
+ int Bp, int Bj, unsigned long long Bx)
+ csc_tocsr(int n_row, int n_col, int Ap, int Ai, float Ax, int Bp,
+ int Bj, float Bx)
+ csc_tocsr(int n_row, int n_col, int Ap, int Ai, double Ax, int Bp,
+ int Bj, double Bx)
+ csc_tocsr(int n_row, int n_col, int Ap, int Ai, long double Ax,
+ int Bp, int Bj, long double Bx)
+ csc_tocsr(int n_row, int n_col, int Ap, int Ai, npy_cfloat_wrapper Ax,
+ int Bp, int Bj, npy_cfloat_wrapper Bx)
+ csc_tocsr(int n_row, int n_col, int Ap, int Ai, npy_cdouble_wrapper Ax,
+ int Bp, int Bj, npy_cdouble_wrapper Bx)
+ csc_tocsr(int n_row, int n_col, int Ap, int Ai, npy_clongdouble_wrapper Ax,
+ int Bp, int Bj, npy_clongdouble_wrapper Bx)
+ """
+ return _csc.csc_tocsr(*args)
def csc_matmat_pass2(*args):
- """
- csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, signed char Ax,
- int Bp, int Bi, signed char Bx, int Cp, int Ci,
- signed char Cx)
- csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, unsigned char Ax,
- int Bp, int Bi, unsigned char Bx, int Cp,
- int Ci, unsigned char Cx)
- csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, short Ax, int Bp,
- int Bi, short Bx, int Cp, int Ci, short Cx)
- csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, unsigned short Ax,
- int Bp, int Bi, unsigned short Bx, int Cp,
- int Ci, unsigned short Cx)
- csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, int Ax, int Bp,
- int Bi, int Bx, int Cp, int Ci, int Cx)
- csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, unsigned int Ax,
- int Bp, int Bi, unsigned int Bx, int Cp,
- int Ci, unsigned int Cx)
- csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, long long Ax,
- int Bp, int Bi, long long Bx, int Cp, int Ci,
- long long Cx)
- csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, unsigned long long Ax,
- int Bp, int Bi, unsigned long long Bx,
- int Cp, int Ci, unsigned long long Cx)
- csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, float Ax, int Bp,
- int Bi, float Bx, int Cp, int Ci, float Cx)
- csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, double Ax, int Bp,
- int Bi, double Bx, int Cp, int Ci, double Cx)
- csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, long double Ax,
- int Bp, int Bi, long double Bx, int Cp, int Ci,
- long double Cx)
- csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, npy_cfloat_wrapper Ax,
- int Bp, int Bi, npy_cfloat_wrapper Bx,
- int Cp, int Ci, npy_cfloat_wrapper Cx)
- csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, npy_cdouble_wrapper Ax,
- int Bp, int Bi, npy_cdouble_wrapper Bx,
- int Cp, int Ci, npy_cdouble_wrapper Cx)
- csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, npy_clongdouble_wrapper Ax,
- int Bp, int Bi, npy_clongdouble_wrapper Bx,
- int Cp, int Ci, npy_clongdouble_wrapper Cx)
"""
- return _csc.csc_matmat_pass2(*args)
+ csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, signed char Ax,
+ int Bp, int Bi, signed char Bx, int Cp, int Ci,
+ signed char Cx)
+ csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, unsigned char Ax,
+ int Bp, int Bi, unsigned char Bx, int Cp,
+ int Ci, unsigned char Cx)
+ csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, short Ax, int Bp,
+ int Bi, short Bx, int Cp, int Ci, short Cx)
+ csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, unsigned short Ax,
+ int Bp, int Bi, unsigned short Bx, int Cp,
+ int Ci, unsigned short Cx)
+ csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, int Ax, int Bp,
+ int Bi, int Bx, int Cp, int Ci, int Cx)
+ csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, unsigned int Ax,
+ int Bp, int Bi, unsigned int Bx, int Cp,
+ int Ci, unsigned int Cx)
+ csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, long long Ax,
+ int Bp, int Bi, long long Bx, int Cp, int Ci,
+ long long Cx)
+ csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, unsigned long long Ax,
+ int Bp, int Bi, unsigned long long Bx,
+ int Cp, int Ci, unsigned long long Cx)
+ csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, float Ax, int Bp,
+ int Bi, float Bx, int Cp, int Ci, float Cx)
+ csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, double Ax, int Bp,
+ int Bi, double Bx, int Cp, int Ci, double Cx)
+ csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, long double Ax,
+ int Bp, int Bi, long double Bx, int Cp, int Ci,
+ long double Cx)
+ csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, npy_cfloat_wrapper Ax,
+ int Bp, int Bi, npy_cfloat_wrapper Bx,
+ int Cp, int Ci, npy_cfloat_wrapper Cx)
+ csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, npy_cdouble_wrapper Ax,
+ int Bp, int Bi, npy_cdouble_wrapper Bx,
+ int Cp, int Ci, npy_cdouble_wrapper Cx)
+ csc_matmat_pass2(int n_row, int n_col, int Ap, int Ai, npy_clongdouble_wrapper Ax,
+ int Bp, int Bi, npy_clongdouble_wrapper Bx,
+ int Cp, int Ci, npy_clongdouble_wrapper Cx)
+ """
+ return _csc.csc_matmat_pass2(*args)
def csc_matvec(*args):
- """
- csc_matvec(int n_row, int n_col, int Ap, int Ai, signed char Ax,
- signed char Xx, signed char Yx)
- csc_matvec(int n_row, int n_col, int Ap, int Ai, unsigned char Ax,
- unsigned char Xx, unsigned char Yx)
- csc_matvec(int n_row, int n_col, int Ap, int Ai, short Ax, short Xx,
- short Yx)
- csc_matvec(int n_row, int n_col, int Ap, int Ai, unsigned short Ax,
- unsigned short Xx, unsigned short Yx)
- csc_matvec(int n_row, int n_col, int Ap, int Ai, int Ax, int Xx,
- int Yx)
- csc_matvec(int n_row, int n_col, int Ap, int Ai, unsigned int Ax,
- unsigned int Xx, unsigned int Yx)
- csc_matvec(int n_row, int n_col, int Ap, int Ai, long long Ax,
- long long Xx, long long Yx)
- csc_matvec(int n_row, int n_col, int Ap, int Ai, unsigned long long Ax,
- unsigned long long Xx, unsigned long long Yx)
- csc_matvec(int n_row, int n_col, int Ap, int Ai, float Ax, float Xx,
- float Yx)
- csc_matvec(int n_row, int n_col, int Ap, int Ai, double Ax, double Xx,
- double Yx)
- csc_matvec(int n_row, int n_col, int Ap, int Ai, long double Ax,
- long double Xx, long double Yx)
- csc_matvec(int n_row, int n_col, int Ap, int Ai, npy_cfloat_wrapper Ax,
- npy_cfloat_wrapper Xx, npy_cfloat_wrapper Yx)
- csc_matvec(int n_row, int n_col, int Ap, int Ai, npy_cdouble_wrapper Ax,
- npy_cdouble_wrapper Xx, npy_cdouble_wrapper Yx)
- csc_matvec(int n_row, int n_col, int Ap, int Ai, npy_clongdouble_wrapper Ax,
- npy_clongdouble_wrapper Xx, npy_clongdouble_wrapper Yx)
"""
- return _csc.csc_matvec(*args)
+ csc_matvec(int n_row, int n_col, int Ap, int Ai, signed char Ax,
+ signed char Xx, signed char Yx)
+ csc_matvec(int n_row, int n_col, int Ap, int Ai, unsigned char Ax,
+ unsigned char Xx, unsigned char Yx)
+ csc_matvec(int n_row, int n_col, int Ap, int Ai, short Ax, short Xx,
+ short Yx)
+ csc_matvec(int n_row, int n_col, int Ap, int Ai, unsigned short Ax,
+ unsigned short Xx, unsigned short Yx)
+ csc_matvec(int n_row, int n_col, int Ap, int Ai, int Ax, int Xx,
+ int Yx)
+ csc_matvec(int n_row, int n_col, int Ap, int Ai, unsigned int Ax,
+ unsigned int Xx, unsigned int Yx)
+ csc_matvec(int n_row, int n_col, int Ap, int Ai, long long Ax,
+ long long Xx, long long Yx)
+ csc_matvec(int n_row, int n_col, int Ap, int Ai, unsigned long long Ax,
+ unsigned long long Xx, unsigned long long Yx)
+ csc_matvec(int n_row, int n_col, int Ap, int Ai, float Ax, float Xx,
+ float Yx)
+ csc_matvec(int n_row, int n_col, int Ap, int Ai, double Ax, double Xx,
+ double Yx)
+ csc_matvec(int n_row, int n_col, int Ap, int Ai, long double Ax,
+ long double Xx, long double Yx)
+ csc_matvec(int n_row, int n_col, int Ap, int Ai, npy_cfloat_wrapper Ax,
+ npy_cfloat_wrapper Xx, npy_cfloat_wrapper Yx)
+ csc_matvec(int n_row, int n_col, int Ap, int Ai, npy_cdouble_wrapper Ax,
+ npy_cdouble_wrapper Xx, npy_cdouble_wrapper Yx)
+ csc_matvec(int n_row, int n_col, int Ap, int Ai, npy_clongdouble_wrapper Ax,
+ npy_clongdouble_wrapper Xx, npy_clongdouble_wrapper Yx)
+ """
+ return _csc.csc_matvec(*args)
def csc_matvecs(*args):
- """
- csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, signed char Ax,
- signed char Xx, signed char Yx)
- csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, unsigned char Ax,
- unsigned char Xx, unsigned char Yx)
- csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, short Ax,
- short Xx, short Yx)
- csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, unsigned short Ax,
- unsigned short Xx, unsigned short Yx)
- csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, int Ax,
- int Xx, int Yx)
- csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, unsigned int Ax,
- unsigned int Xx, unsigned int Yx)
- csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, long long Ax,
- long long Xx, long long Yx)
- csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, unsigned long long Ax,
- unsigned long long Xx,
- unsigned long long Yx)
- csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, float Ax,
- float Xx, float Yx)
- csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, double Ax,
- double Xx, double Yx)
- csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, long double Ax,
- long double Xx, long double Yx)
- csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, npy_cfloat_wrapper Ax,
- npy_cfloat_wrapper Xx,
- npy_cfloat_wrapper Yx)
- csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, npy_cdouble_wrapper Ax,
- npy_cdouble_wrapper Xx,
- npy_cdouble_wrapper Yx)
- csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, npy_clongdouble_wrapper Ax,
- npy_clongdouble_wrapper Xx,
- npy_clongdouble_wrapper Yx)
"""
- return _csc.csc_matvecs(*args)
+ csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, signed char Ax,
+ signed char Xx, signed char Yx)
+ csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, unsigned char Ax,
+ unsigned char Xx, unsigned char Yx)
+ csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, short Ax,
+ short Xx, short Yx)
+ csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, unsigned short Ax,
+ unsigned short Xx, unsigned short Yx)
+ csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, int Ax,
+ int Xx, int Yx)
+ csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, unsigned int Ax,
+ unsigned int Xx, unsigned int Yx)
+ csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, long long Ax,
+ long long Xx, long long Yx)
+ csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, unsigned long long Ax,
+ unsigned long long Xx,
+ unsigned long long Yx)
+ csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, float Ax,
+ float Xx, float Yx)
+ csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, double Ax,
+ double Xx, double Yx)
+ csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, long double Ax,
+ long double Xx, long double Yx)
+ csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, npy_cfloat_wrapper Ax,
+ npy_cfloat_wrapper Xx,
+ npy_cfloat_wrapper Yx)
+ csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, npy_cdouble_wrapper Ax,
+ npy_cdouble_wrapper Xx,
+ npy_cdouble_wrapper Yx)
+ csc_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Ai, npy_clongdouble_wrapper Ax,
+ npy_clongdouble_wrapper Xx,
+ npy_clongdouble_wrapper Yx)
+ """
+ return _csc.csc_matvecs(*args)
def csc_elmul_csc(*args):
- """
- csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, signed char Ax,
- int Bp, int Bi, signed char Bx, int Cp, int Ci,
- signed char Cx)
- csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, unsigned char Ax,
- int Bp, int Bi, unsigned char Bx, int Cp,
- int Ci, unsigned char Cx)
- csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, short Ax, int Bp,
- int Bi, short Bx, int Cp, int Ci, short Cx)
- csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, unsigned short Ax,
- int Bp, int Bi, unsigned short Bx, int Cp,
- int Ci, unsigned short Cx)
- csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, int Ax, int Bp,
- int Bi, int Bx, int Cp, int Ci, int Cx)
- csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, unsigned int Ax,
- int Bp, int Bi, unsigned int Bx, int Cp,
- int Ci, unsigned int Cx)
- csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, long long Ax,
- int Bp, int Bi, long long Bx, int Cp, int Ci,
- long long Cx)
- csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, unsigned long long Ax,
- int Bp, int Bi, unsigned long long Bx,
- int Cp, int Ci, unsigned long long Cx)
- csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, float Ax, int Bp,
- int Bi, float Bx, int Cp, int Ci, float Cx)
- csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, double Ax, int Bp,
- int Bi, double Bx, int Cp, int Ci, double Cx)
- csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, long double Ax,
- int Bp, int Bi, long double Bx, int Cp, int Ci,
- long double Cx)
- csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, npy_cfloat_wrapper Ax,
- int Bp, int Bi, npy_cfloat_wrapper Bx,
- int Cp, int Ci, npy_cfloat_wrapper Cx)
- csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, npy_cdouble_wrapper Ax,
- int Bp, int Bi, npy_cdouble_wrapper Bx,
- int Cp, int Ci, npy_cdouble_wrapper Cx)
- csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, npy_clongdouble_wrapper Ax,
- int Bp, int Bi, npy_clongdouble_wrapper Bx,
- int Cp, int Ci, npy_clongdouble_wrapper Cx)
"""
- return _csc.csc_elmul_csc(*args)
+ csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, signed char Ax,
+ int Bp, int Bi, signed char Bx, int Cp, int Ci,
+ signed char Cx)
+ csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, unsigned char Ax,
+ int Bp, int Bi, unsigned char Bx, int Cp,
+ int Ci, unsigned char Cx)
+ csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, short Ax, int Bp,
+ int Bi, short Bx, int Cp, int Ci, short Cx)
+ csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, unsigned short Ax,
+ int Bp, int Bi, unsigned short Bx, int Cp,
+ int Ci, unsigned short Cx)
+ csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, int Ax, int Bp,
+ int Bi, int Bx, int Cp, int Ci, int Cx)
+ csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, unsigned int Ax,
+ int Bp, int Bi, unsigned int Bx, int Cp,
+ int Ci, unsigned int Cx)
+ csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, long long Ax,
+ int Bp, int Bi, long long Bx, int Cp, int Ci,
+ long long Cx)
+ csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, unsigned long long Ax,
+ int Bp, int Bi, unsigned long long Bx,
+ int Cp, int Ci, unsigned long long Cx)
+ csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, float Ax, int Bp,
+ int Bi, float Bx, int Cp, int Ci, float Cx)
+ csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, double Ax, int Bp,
+ int Bi, double Bx, int Cp, int Ci, double Cx)
+ csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, long double Ax,
+ int Bp, int Bi, long double Bx, int Cp, int Ci,
+ long double Cx)
+ csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, npy_cfloat_wrapper Ax,
+ int Bp, int Bi, npy_cfloat_wrapper Bx,
+ int Cp, int Ci, npy_cfloat_wrapper Cx)
+ csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, npy_cdouble_wrapper Ax,
+ int Bp, int Bi, npy_cdouble_wrapper Bx,
+ int Cp, int Ci, npy_cdouble_wrapper Cx)
+ csc_elmul_csc(int n_row, int n_col, int Ap, int Ai, npy_clongdouble_wrapper Ax,
+ int Bp, int Bi, npy_clongdouble_wrapper Bx,
+ int Cp, int Ci, npy_clongdouble_wrapper Cx)
+ """
+ return _csc.csc_elmul_csc(*args)
def csc_eldiv_csc(*args):
- """
- csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, signed char Ax,
- int Bp, int Bi, signed char Bx, int Cp, int Ci,
- signed char Cx)
- csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, unsigned char Ax,
- int Bp, int Bi, unsigned char Bx, int Cp,
- int Ci, unsigned char Cx)
- csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, short Ax, int Bp,
- int Bi, short Bx, int Cp, int Ci, short Cx)
- csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, unsigned short Ax,
- int Bp, int Bi, unsigned short Bx, int Cp,
- int Ci, unsigned short Cx)
- csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, int Ax, int Bp,
- int Bi, int Bx, int Cp, int Ci, int Cx)
- csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, unsigned int Ax,
- int Bp, int Bi, unsigned int Bx, int Cp,
- int Ci, unsigned int Cx)
- csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, long long Ax,
- int Bp, int Bi, long long Bx, int Cp, int Ci,
- long long Cx)
- csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, unsigned long long Ax,
- int Bp, int Bi, unsigned long long Bx,
- int Cp, int Ci, unsigned long long Cx)
- csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, float Ax, int Bp,
- int Bi, float Bx, int Cp, int Ci, float Cx)
- csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, double Ax, int Bp,
- int Bi, double Bx, int Cp, int Ci, double Cx)
- csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, long double Ax,
- int Bp, int Bi, long double Bx, int Cp, int Ci,
- long double Cx)
- csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, npy_cfloat_wrapper Ax,
- int Bp, int Bi, npy_cfloat_wrapper Bx,
- int Cp, int Ci, npy_cfloat_wrapper Cx)
- csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, npy_cdouble_wrapper Ax,
- int Bp, int Bi, npy_cdouble_wrapper Bx,
- int Cp, int Ci, npy_cdouble_wrapper Cx)
- csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, npy_clongdouble_wrapper Ax,
- int Bp, int Bi, npy_clongdouble_wrapper Bx,
- int Cp, int Ci, npy_clongdouble_wrapper Cx)
"""
- return _csc.csc_eldiv_csc(*args)
+ csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, signed char Ax,
+ int Bp, int Bi, signed char Bx, int Cp, int Ci,
+ signed char Cx)
+ csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, unsigned char Ax,
+ int Bp, int Bi, unsigned char Bx, int Cp,
+ int Ci, unsigned char Cx)
+ csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, short Ax, int Bp,
+ int Bi, short Bx, int Cp, int Ci, short Cx)
+ csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, unsigned short Ax,
+ int Bp, int Bi, unsigned short Bx, int Cp,
+ int Ci, unsigned short Cx)
+ csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, int Ax, int Bp,
+ int Bi, int Bx, int Cp, int Ci, int Cx)
+ csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, unsigned int Ax,
+ int Bp, int Bi, unsigned int Bx, int Cp,
+ int Ci, unsigned int Cx)
+ csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, long long Ax,
+ int Bp, int Bi, long long Bx, int Cp, int Ci,
+ long long Cx)
+ csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, unsigned long long Ax,
+ int Bp, int Bi, unsigned long long Bx,
+ int Cp, int Ci, unsigned long long Cx)
+ csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, float Ax, int Bp,
+ int Bi, float Bx, int Cp, int Ci, float Cx)
+ csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, double Ax, int Bp,
+ int Bi, double Bx, int Cp, int Ci, double Cx)
+ csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, long double Ax,
+ int Bp, int Bi, long double Bx, int Cp, int Ci,
+ long double Cx)
+ csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, npy_cfloat_wrapper Ax,
+ int Bp, int Bi, npy_cfloat_wrapper Bx,
+ int Cp, int Ci, npy_cfloat_wrapper Cx)
+ csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, npy_cdouble_wrapper Ax,
+ int Bp, int Bi, npy_cdouble_wrapper Bx,
+ int Cp, int Ci, npy_cdouble_wrapper Cx)
+ csc_eldiv_csc(int n_row, int n_col, int Ap, int Ai, npy_clongdouble_wrapper Ax,
+ int Bp, int Bi, npy_clongdouble_wrapper Bx,
+ int Cp, int Ci, npy_clongdouble_wrapper Cx)
+ """
+ return _csc.csc_eldiv_csc(*args)
def csc_plus_csc(*args):
- """
- csc_plus_csc(int n_row, int n_col, int Ap, int Ai, signed char Ax,
- int Bp, int Bi, signed char Bx, int Cp, int Ci,
- signed char Cx)
- csc_plus_csc(int n_row, int n_col, int Ap, int Ai, unsigned char Ax,
- int Bp, int Bi, unsigned char Bx, int Cp,
- int Ci, unsigned char Cx)
- csc_plus_csc(int n_row, int n_col, int Ap, int Ai, short Ax, int Bp,
- int Bi, short Bx, int Cp, int Ci, short Cx)
- csc_plus_csc(int n_row, int n_col, int Ap, int Ai, unsigned short Ax,
- int Bp, int Bi, unsigned short Bx, int Cp,
- int Ci, unsigned short Cx)
- csc_plus_csc(int n_row, int n_col, int Ap, int Ai, int Ax, int Bp,
- int Bi, int Bx, int Cp, int Ci, int Cx)
- csc_plus_csc(int n_row, int n_col, int Ap, int Ai, unsigned int Ax,
- int Bp, int Bi, unsigned int Bx, int Cp,
- int Ci, unsigned int Cx)
- csc_plus_csc(int n_row, int n_col, int Ap, int Ai, long long Ax,
- int Bp, int Bi, long long Bx, int Cp, int Ci,
- long long Cx)
- csc_plus_csc(int n_row, int n_col, int Ap, int Ai, unsigned long long Ax,
- int Bp, int Bi, unsigned long long Bx,
- int Cp, int Ci, unsigned long long Cx)
- csc_plus_csc(int n_row, int n_col, int Ap, int Ai, float Ax, int Bp,
- int Bi, float Bx, int Cp, int Ci, float Cx)
- csc_plus_csc(int n_row, int n_col, int Ap, int Ai, double Ax, int Bp,
- int Bi, double Bx, int Cp, int Ci, double Cx)
- csc_plus_csc(int n_row, int n_col, int Ap, int Ai, long double Ax,
- int Bp, int Bi, long double Bx, int Cp, int Ci,
- long double Cx)
- csc_plus_csc(int n_row, int n_col, int Ap, int Ai, npy_cfloat_wrapper Ax,
- int Bp, int Bi, npy_cfloat_wrapper Bx,
- int Cp, int Ci, npy_cfloat_wrapper Cx)
- csc_plus_csc(int n_row, int n_col, int Ap, int Ai, npy_cdouble_wrapper Ax,
- int Bp, int Bi, npy_cdouble_wrapper Bx,
- int Cp, int Ci, npy_cdouble_wrapper Cx)
- csc_plus_csc(int n_row, int n_col, int Ap, int Ai, npy_clongdouble_wrapper Ax,
- int Bp, int Bi, npy_clongdouble_wrapper Bx,
- int Cp, int Ci, npy_clongdouble_wrapper Cx)
"""
- return _csc.csc_plus_csc(*args)
+ csc_plus_csc(int n_row, int n_col, int Ap, int Ai, signed char Ax,
+ int Bp, int Bi, signed char Bx, int Cp, int Ci,
+ signed char Cx)
+ csc_plus_csc(int n_row, int n_col, int Ap, int Ai, unsigned char Ax,
+ int Bp, int Bi, unsigned char Bx, int Cp,
+ int Ci, unsigned char Cx)
+ csc_plus_csc(int n_row, int n_col, int Ap, int Ai, short Ax, int Bp,
+ int Bi, short Bx, int Cp, int Ci, short Cx)
+ csc_plus_csc(int n_row, int n_col, int Ap, int Ai, unsigned short Ax,
+ int Bp, int Bi, unsigned short Bx, int Cp,
+ int Ci, unsigned short Cx)
+ csc_plus_csc(int n_row, int n_col, int Ap, int Ai, int Ax, int Bp,
+ int Bi, int Bx, int Cp, int Ci, int Cx)
+ csc_plus_csc(int n_row, int n_col, int Ap, int Ai, unsigned int Ax,
+ int Bp, int Bi, unsigned int Bx, int Cp,
+ int Ci, unsigned int Cx)
+ csc_plus_csc(int n_row, int n_col, int Ap, int Ai, long long Ax,
+ int Bp, int Bi, long long Bx, int Cp, int Ci,
+ long long Cx)
+ csc_plus_csc(int n_row, int n_col, int Ap, int Ai, unsigned long long Ax,
+ int Bp, int Bi, unsigned long long Bx,
+ int Cp, int Ci, unsigned long long Cx)
+ csc_plus_csc(int n_row, int n_col, int Ap, int Ai, float Ax, int Bp,
+ int Bi, float Bx, int Cp, int Ci, float Cx)
+ csc_plus_csc(int n_row, int n_col, int Ap, int Ai, double Ax, int Bp,
+ int Bi, double Bx, int Cp, int Ci, double Cx)
+ csc_plus_csc(int n_row, int n_col, int Ap, int Ai, long double Ax,
+ int Bp, int Bi, long double Bx, int Cp, int Ci,
+ long double Cx)
+ csc_plus_csc(int n_row, int n_col, int Ap, int Ai, npy_cfloat_wrapper Ax,
+ int Bp, int Bi, npy_cfloat_wrapper Bx,
+ int Cp, int Ci, npy_cfloat_wrapper Cx)
+ csc_plus_csc(int n_row, int n_col, int Ap, int Ai, npy_cdouble_wrapper Ax,
+ int Bp, int Bi, npy_cdouble_wrapper Bx,
+ int Cp, int Ci, npy_cdouble_wrapper Cx)
+ csc_plus_csc(int n_row, int n_col, int Ap, int Ai, npy_clongdouble_wrapper Ax,
+ int Bp, int Bi, npy_clongdouble_wrapper Bx,
+ int Cp, int Ci, npy_clongdouble_wrapper Cx)
+ """
+ return _csc.csc_plus_csc(*args)
def csc_minus_csc(*args):
- """
- csc_minus_csc(int n_row, int n_col, int Ap, int Ai, signed char Ax,
- int Bp, int Bi, signed char Bx, int Cp, int Ci,
- signed char Cx)
- csc_minus_csc(int n_row, int n_col, int Ap, int Ai, unsigned char Ax,
- int Bp, int Bi, unsigned char Bx, int Cp,
- int Ci, unsigned char Cx)
- csc_minus_csc(int n_row, int n_col, int Ap, int Ai, short Ax, int Bp,
- int Bi, short Bx, int Cp, int Ci, short Cx)
- csc_minus_csc(int n_row, int n_col, int Ap, int Ai, unsigned short Ax,
- int Bp, int Bi, unsigned short Bx, int Cp,
- int Ci, unsigned short Cx)
- csc_minus_csc(int n_row, int n_col, int Ap, int Ai, int Ax, int Bp,
- int Bi, int Bx, int Cp, int Ci, int Cx)
- csc_minus_csc(int n_row, int n_col, int Ap, int Ai, unsigned int Ax,
- int Bp, int Bi, unsigned int Bx, int Cp,
- int Ci, unsigned int Cx)
- csc_minus_csc(int n_row, int n_col, int Ap, int Ai, long long Ax,
- int Bp, int Bi, long long Bx, int Cp, int Ci,
- long long Cx)
- csc_minus_csc(int n_row, int n_col, int Ap, int Ai, unsigned long long Ax,
- int Bp, int Bi, unsigned long long Bx,
- int Cp, int Ci, unsigned long long Cx)
- csc_minus_csc(int n_row, int n_col, int Ap, int Ai, float Ax, int Bp,
- int Bi, float Bx, int Cp, int Ci, float Cx)
- csc_minus_csc(int n_row, int n_col, int Ap, int Ai, double Ax, int Bp,
- int Bi, double Bx, int Cp, int Ci, double Cx)
- csc_minus_csc(int n_row, int n_col, int Ap, int Ai, long double Ax,
- int Bp, int Bi, long double Bx, int Cp, int Ci,
- long double Cx)
- csc_minus_csc(int n_row, int n_col, int Ap, int Ai, npy_cfloat_wrapper Ax,
- int Bp, int Bi, npy_cfloat_wrapper Bx,
- int Cp, int Ci, npy_cfloat_wrapper Cx)
- csc_minus_csc(int n_row, int n_col, int Ap, int Ai, npy_cdouble_wrapper Ax,
- int Bp, int Bi, npy_cdouble_wrapper Bx,
- int Cp, int Ci, npy_cdouble_wrapper Cx)
- csc_minus_csc(int n_row, int n_col, int Ap, int Ai, npy_clongdouble_wrapper Ax,
- int Bp, int Bi, npy_clongdouble_wrapper Bx,
- int Cp, int Ci, npy_clongdouble_wrapper Cx)
"""
- return _csc.csc_minus_csc(*args)
-
+ csc_minus_csc(int n_row, int n_col, int Ap, int Ai, signed char Ax,
+ int Bp, int Bi, signed char Bx, int Cp, int Ci,
+ signed char Cx)
+ csc_minus_csc(int n_row, int n_col, int Ap, int Ai, unsigned char Ax,
+ int Bp, int Bi, unsigned char Bx, int Cp,
+ int Ci, unsigned char Cx)
+ csc_minus_csc(int n_row, int n_col, int Ap, int Ai, short Ax, int Bp,
+ int Bi, short Bx, int Cp, int Ci, short Cx)
+ csc_minus_csc(int n_row, int n_col, int Ap, int Ai, unsigned short Ax,
+ int Bp, int Bi, unsigned short Bx, int Cp,
+ int Ci, unsigned short Cx)
+ csc_minus_csc(int n_row, int n_col, int Ap, int Ai, int Ax, int Bp,
+ int Bi, int Bx, int Cp, int Ci, int Cx)
+ csc_minus_csc(int n_row, int n_col, int Ap, int Ai, unsigned int Ax,
+ int Bp, int Bi, unsigned int Bx, int Cp,
+ int Ci, unsigned int Cx)
+ csc_minus_csc(int n_row, int n_col, int Ap, int Ai, long long Ax,
+ int Bp, int Bi, long long Bx, int Cp, int Ci,
+ long long Cx)
+ csc_minus_csc(int n_row, int n_col, int Ap, int Ai, unsigned long long Ax,
+ int Bp, int Bi, unsigned long long Bx,
+ int Cp, int Ci, unsigned long long Cx)
+ csc_minus_csc(int n_row, int n_col, int Ap, int Ai, float Ax, int Bp,
+ int Bi, float Bx, int Cp, int Ci, float Cx)
+ csc_minus_csc(int n_row, int n_col, int Ap, int Ai, double Ax, int Bp,
+ int Bi, double Bx, int Cp, int Ci, double Cx)
+ csc_minus_csc(int n_row, int n_col, int Ap, int Ai, long double Ax,
+ int Bp, int Bi, long double Bx, int Cp, int Ci,
+ long double Cx)
+ csc_minus_csc(int n_row, int n_col, int Ap, int Ai, npy_cfloat_wrapper Ax,
+ int Bp, int Bi, npy_cfloat_wrapper Bx,
+ int Cp, int Ci, npy_cfloat_wrapper Cx)
+ csc_minus_csc(int n_row, int n_col, int Ap, int Ai, npy_cdouble_wrapper Ax,
+ int Bp, int Bi, npy_cdouble_wrapper Bx,
+ int Cp, int Ci, npy_cdouble_wrapper Cx)
+ csc_minus_csc(int n_row, int n_col, int Ap, int Ai, npy_clongdouble_wrapper Ax,
+ int Bp, int Bi, npy_clongdouble_wrapper Bx,
+ int Cp, int Ci, npy_clongdouble_wrapper Cx)
+ """
+ return _csc.csc_minus_csc(*args)
Modified: branches/refactor_fft/scipy/sparse/sparsetools/csr.py
===================================================================
--- branches/refactor_fft/scipy/sparse/sparsetools/csr.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/sparse/sparsetools/csr.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -50,569 +50,568 @@
def expandptr(*args):
- """expandptr(int n_row, int Ap, int Bi)"""
- return _csr.expandptr(*args)
+ """expandptr(int n_row, int Ap, int Bi)"""
+ return _csr.expandptr(*args)
def csr_matmat_pass1(*args):
- """
- csr_matmat_pass1(int n_row, int n_col, int Ap, int Aj, int Bp, int Bj,
- int Cp)
"""
- return _csr.csr_matmat_pass1(*args)
+ csr_matmat_pass1(int n_row, int n_col, int Ap, int Aj, int Bp, int Bj,
+ int Cp)
+ """
+ return _csr.csr_matmat_pass1(*args)
def csr_count_blocks(*args):
- """csr_count_blocks(int n_row, int n_col, int R, int C, int Ap, int Aj) -> int"""
- return _csr.csr_count_blocks(*args)
+ """csr_count_blocks(int n_row, int n_col, int R, int C, int Ap, int Aj) -> int"""
+ return _csr.csr_count_blocks(*args)
def csr_has_sorted_indices(*args):
- """csr_has_sorted_indices(int n_row, int Ap, int Aj) -> bool"""
- return _csr.csr_has_sorted_indices(*args)
+ """csr_has_sorted_indices(int n_row, int Ap, int Aj) -> bool"""
+ return _csr.csr_has_sorted_indices(*args)
def csr_diagonal(*args):
- """
- csr_diagonal(int n_row, int n_col, int Ap, int Aj, signed char Ax,
- signed char Yx)
- csr_diagonal(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
- unsigned char Yx)
- csr_diagonal(int n_row, int n_col, int Ap, int Aj, short Ax, short Yx)
- csr_diagonal(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
- unsigned short Yx)
- csr_diagonal(int n_row, int n_col, int Ap, int Aj, int Ax, int Yx)
- csr_diagonal(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
- unsigned int Yx)
- csr_diagonal(int n_row, int n_col, int Ap, int Aj, long long Ax,
- long long Yx)
- csr_diagonal(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
- unsigned long long Yx)
- csr_diagonal(int n_row, int n_col, int Ap, int Aj, float Ax, float Yx)
- csr_diagonal(int n_row, int n_col, int Ap, int Aj, double Ax, double Yx)
- csr_diagonal(int n_row, int n_col, int Ap, int Aj, long double Ax,
- long double Yx)
- csr_diagonal(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
- npy_cfloat_wrapper Yx)
- csr_diagonal(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
- npy_cdouble_wrapper Yx)
- csr_diagonal(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
- npy_clongdouble_wrapper Yx)
"""
- return _csr.csr_diagonal(*args)
+ csr_diagonal(int n_row, int n_col, int Ap, int Aj, signed char Ax,
+ signed char Yx)
+ csr_diagonal(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
+ unsigned char Yx)
+ csr_diagonal(int n_row, int n_col, int Ap, int Aj, short Ax, short Yx)
+ csr_diagonal(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
+ unsigned short Yx)
+ csr_diagonal(int n_row, int n_col, int Ap, int Aj, int Ax, int Yx)
+ csr_diagonal(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
+ unsigned int Yx)
+ csr_diagonal(int n_row, int n_col, int Ap, int Aj, long long Ax,
+ long long Yx)
+ csr_diagonal(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
+ unsigned long long Yx)
+ csr_diagonal(int n_row, int n_col, int Ap, int Aj, float Ax, float Yx)
+ csr_diagonal(int n_row, int n_col, int Ap, int Aj, double Ax, double Yx)
+ csr_diagonal(int n_row, int n_col, int Ap, int Aj, long double Ax,
+ long double Yx)
+ csr_diagonal(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
+ npy_cfloat_wrapper Yx)
+ csr_diagonal(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
+ npy_cdouble_wrapper Yx)
+ csr_diagonal(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
+ npy_clongdouble_wrapper Yx)
+ """
+ return _csr.csr_diagonal(*args)
def csr_scale_rows(*args):
- """
- csr_scale_rows(int n_row, int n_col, int Ap, int Aj, signed char Ax,
- signed char Xx)
- csr_scale_rows(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
- unsigned char Xx)
- csr_scale_rows(int n_row, int n_col, int Ap, int Aj, short Ax, short Xx)
- csr_scale_rows(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
- unsigned short Xx)
- csr_scale_rows(int n_row, int n_col, int Ap, int Aj, int Ax, int Xx)
- csr_scale_rows(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
- unsigned int Xx)
- csr_scale_rows(int n_row, int n_col, int Ap, int Aj, long long Ax,
- long long Xx)
- csr_scale_rows(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
- unsigned long long Xx)
- csr_scale_rows(int n_row, int n_col, int Ap, int Aj, float Ax, float Xx)
- csr_scale_rows(int n_row, int n_col, int Ap, int Aj, double Ax, double Xx)
- csr_scale_rows(int n_row, int n_col, int Ap, int Aj, long double Ax,
- long double Xx)
- csr_scale_rows(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
- npy_cfloat_wrapper Xx)
- csr_scale_rows(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
- npy_cdouble_wrapper Xx)
- csr_scale_rows(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
- npy_clongdouble_wrapper Xx)
"""
- return _csr.csr_scale_rows(*args)
+ csr_scale_rows(int n_row, int n_col, int Ap, int Aj, signed char Ax,
+ signed char Xx)
+ csr_scale_rows(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
+ unsigned char Xx)
+ csr_scale_rows(int n_row, int n_col, int Ap, int Aj, short Ax, short Xx)
+ csr_scale_rows(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
+ unsigned short Xx)
+ csr_scale_rows(int n_row, int n_col, int Ap, int Aj, int Ax, int Xx)
+ csr_scale_rows(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
+ unsigned int Xx)
+ csr_scale_rows(int n_row, int n_col, int Ap, int Aj, long long Ax,
+ long long Xx)
+ csr_scale_rows(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
+ unsigned long long Xx)
+ csr_scale_rows(int n_row, int n_col, int Ap, int Aj, float Ax, float Xx)
+ csr_scale_rows(int n_row, int n_col, int Ap, int Aj, double Ax, double Xx)
+ csr_scale_rows(int n_row, int n_col, int Ap, int Aj, long double Ax,
+ long double Xx)
+ csr_scale_rows(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
+ npy_cfloat_wrapper Xx)
+ csr_scale_rows(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
+ npy_cdouble_wrapper Xx)
+ csr_scale_rows(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
+ npy_clongdouble_wrapper Xx)
+ """
+ return _csr.csr_scale_rows(*args)
def csr_scale_columns(*args):
- """
- csr_scale_columns(int n_row, int n_col, int Ap, int Aj, signed char Ax,
- signed char Xx)
- csr_scale_columns(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
- unsigned char Xx)
- csr_scale_columns(int n_row, int n_col, int Ap, int Aj, short Ax, short Xx)
- csr_scale_columns(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
- unsigned short Xx)
- csr_scale_columns(int n_row, int n_col, int Ap, int Aj, int Ax, int Xx)
- csr_scale_columns(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
- unsigned int Xx)
- csr_scale_columns(int n_row, int n_col, int Ap, int Aj, long long Ax,
- long long Xx)
- csr_scale_columns(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
- unsigned long long Xx)
- csr_scale_columns(int n_row, int n_col, int Ap, int Aj, float Ax, float Xx)
- csr_scale_columns(int n_row, int n_col, int Ap, int Aj, double Ax, double Xx)
- csr_scale_columns(int n_row, int n_col, int Ap, int Aj, long double Ax,
- long double Xx)
- csr_scale_columns(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
- npy_cfloat_wrapper Xx)
- csr_scale_columns(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
- npy_cdouble_wrapper Xx)
- csr_scale_columns(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
- npy_clongdouble_wrapper Xx)
"""
- return _csr.csr_scale_columns(*args)
+ csr_scale_columns(int n_row, int n_col, int Ap, int Aj, signed char Ax,
+ signed char Xx)
+ csr_scale_columns(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
+ unsigned char Xx)
+ csr_scale_columns(int n_row, int n_col, int Ap, int Aj, short Ax, short Xx)
+ csr_scale_columns(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
+ unsigned short Xx)
+ csr_scale_columns(int n_row, int n_col, int Ap, int Aj, int Ax, int Xx)
+ csr_scale_columns(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
+ unsigned int Xx)
+ csr_scale_columns(int n_row, int n_col, int Ap, int Aj, long long Ax,
+ long long Xx)
+ csr_scale_columns(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
+ unsigned long long Xx)
+ csr_scale_columns(int n_row, int n_col, int Ap, int Aj, float Ax, float Xx)
+ csr_scale_columns(int n_row, int n_col, int Ap, int Aj, double Ax, double Xx)
+ csr_scale_columns(int n_row, int n_col, int Ap, int Aj, long double Ax,
+ long double Xx)
+ csr_scale_columns(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
+ npy_cfloat_wrapper Xx)
+ csr_scale_columns(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
+ npy_cdouble_wrapper Xx)
+ csr_scale_columns(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
+ npy_clongdouble_wrapper Xx)
+ """
+ return _csr.csr_scale_columns(*args)
def csr_tocsc(*args):
- """
- csr_tocsc(int n_row, int n_col, int Ap, int Aj, signed char Ax,
- int Bp, int Bi, signed char Bx)
- csr_tocsc(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
- int Bp, int Bi, unsigned char Bx)
- csr_tocsc(int n_row, int n_col, int Ap, int Aj, short Ax, int Bp,
- int Bi, short Bx)
- csr_tocsc(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
- int Bp, int Bi, unsigned short Bx)
- csr_tocsc(int n_row, int n_col, int Ap, int Aj, int Ax, int Bp,
- int Bi, int Bx)
- csr_tocsc(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
- int Bp, int Bi, unsigned int Bx)
- csr_tocsc(int n_row, int n_col, int Ap, int Aj, long long Ax,
- int Bp, int Bi, long long Bx)
- csr_tocsc(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
- int Bp, int Bi, unsigned long long Bx)
- csr_tocsc(int n_row, int n_col, int Ap, int Aj, float Ax, int Bp,
- int Bi, float Bx)
- csr_tocsc(int n_row, int n_col, int Ap, int Aj, double Ax, int Bp,
- int Bi, double Bx)
- csr_tocsc(int n_row, int n_col, int Ap, int Aj, long double Ax,
- int Bp, int Bi, long double Bx)
- csr_tocsc(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
- int Bp, int Bi, npy_cfloat_wrapper Bx)
- csr_tocsc(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
- int Bp, int Bi, npy_cdouble_wrapper Bx)
- csr_tocsc(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
- int Bp, int Bi, npy_clongdouble_wrapper Bx)
"""
- return _csr.csr_tocsc(*args)
+ csr_tocsc(int n_row, int n_col, int Ap, int Aj, signed char Ax,
+ int Bp, int Bi, signed char Bx)
+ csr_tocsc(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
+ int Bp, int Bi, unsigned char Bx)
+ csr_tocsc(int n_row, int n_col, int Ap, int Aj, short Ax, int Bp,
+ int Bi, short Bx)
+ csr_tocsc(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
+ int Bp, int Bi, unsigned short Bx)
+ csr_tocsc(int n_row, int n_col, int Ap, int Aj, int Ax, int Bp,
+ int Bi, int Bx)
+ csr_tocsc(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
+ int Bp, int Bi, unsigned int Bx)
+ csr_tocsc(int n_row, int n_col, int Ap, int Aj, long long Ax,
+ int Bp, int Bi, long long Bx)
+ csr_tocsc(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
+ int Bp, int Bi, unsigned long long Bx)
+ csr_tocsc(int n_row, int n_col, int Ap, int Aj, float Ax, int Bp,
+ int Bi, float Bx)
+ csr_tocsc(int n_row, int n_col, int Ap, int Aj, double Ax, int Bp,
+ int Bi, double Bx)
+ csr_tocsc(int n_row, int n_col, int Ap, int Aj, long double Ax,
+ int Bp, int Bi, long double Bx)
+ csr_tocsc(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
+ int Bp, int Bi, npy_cfloat_wrapper Bx)
+ csr_tocsc(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
+ int Bp, int Bi, npy_cdouble_wrapper Bx)
+ csr_tocsc(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
+ int Bp, int Bi, npy_clongdouble_wrapper Bx)
+ """
+ return _csr.csr_tocsc(*args)
def csr_tobsr(*args):
- """
- csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- signed char Ax, int Bp, int Bj, signed char Bx)
- csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- unsigned char Ax, int Bp, int Bj, unsigned char Bx)
- csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- short Ax, int Bp, int Bj, short Bx)
- csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- unsigned short Ax, int Bp, int Bj, unsigned short Bx)
- csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- int Ax, int Bp, int Bj, int Bx)
- csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- unsigned int Ax, int Bp, int Bj, unsigned int Bx)
- csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- long long Ax, int Bp, int Bj, long long Bx)
- csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- unsigned long long Ax, int Bp, int Bj, unsigned long long Bx)
- csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- float Ax, int Bp, int Bj, float Bx)
- csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- double Ax, int Bp, int Bj, double Bx)
- csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- long double Ax, int Bp, int Bj, long double Bx)
- csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- npy_cfloat_wrapper Ax, int Bp, int Bj, npy_cfloat_wrapper Bx)
- csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- npy_cdouble_wrapper Ax, int Bp, int Bj, npy_cdouble_wrapper Bx)
- csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
- npy_clongdouble_wrapper Ax, int Bp, int Bj,
- npy_clongdouble_wrapper Bx)
"""
- return _csr.csr_tobsr(*args)
+ csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ signed char Ax, int Bp, int Bj, signed char Bx)
+ csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ unsigned char Ax, int Bp, int Bj, unsigned char Bx)
+ csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ short Ax, int Bp, int Bj, short Bx)
+ csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ unsigned short Ax, int Bp, int Bj, unsigned short Bx)
+ csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ int Ax, int Bp, int Bj, int Bx)
+ csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ unsigned int Ax, int Bp, int Bj, unsigned int Bx)
+ csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ long long Ax, int Bp, int Bj, long long Bx)
+ csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ unsigned long long Ax, int Bp, int Bj, unsigned long long Bx)
+ csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ float Ax, int Bp, int Bj, float Bx)
+ csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ double Ax, int Bp, int Bj, double Bx)
+ csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ long double Ax, int Bp, int Bj, long double Bx)
+ csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ npy_cfloat_wrapper Ax, int Bp, int Bj, npy_cfloat_wrapper Bx)
+ csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ npy_cdouble_wrapper Ax, int Bp, int Bj, npy_cdouble_wrapper Bx)
+ csr_tobsr(int n_row, int n_col, int R, int C, int Ap, int Aj,
+ npy_clongdouble_wrapper Ax, int Bp, int Bj,
+ npy_clongdouble_wrapper Bx)
+ """
+ return _csr.csr_tobsr(*args)
def csr_matmat_pass2(*args):
- """
- csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, signed char Ax,
- int Bp, int Bj, signed char Bx, int Cp, int Cj,
- signed char Cx)
- csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
- int Bp, int Bj, unsigned char Bx, int Cp,
- int Cj, unsigned char Cx)
- csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, short Ax, int Bp,
- int Bj, short Bx, int Cp, int Cj, short Cx)
- csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
- int Bp, int Bj, unsigned short Bx, int Cp,
- int Cj, unsigned short Cx)
- csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, int Ax, int Bp,
- int Bj, int Bx, int Cp, int Cj, int Cx)
- csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
- int Bp, int Bj, unsigned int Bx, int Cp,
- int Cj, unsigned int Cx)
- csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, long long Ax,
- int Bp, int Bj, long long Bx, int Cp, int Cj,
- long long Cx)
- csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
- int Bp, int Bj, unsigned long long Bx,
- int Cp, int Cj, unsigned long long Cx)
- csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, float Ax, int Bp,
- int Bj, float Bx, int Cp, int Cj, float Cx)
- csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, double Ax, int Bp,
- int Bj, double Bx, int Cp, int Cj, double Cx)
- csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, long double Ax,
- int Bp, int Bj, long double Bx, int Cp, int Cj,
- long double Cx)
- csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
- int Bp, int Bj, npy_cfloat_wrapper Bx,
- int Cp, int Cj, npy_cfloat_wrapper Cx)
- csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
- int Bp, int Bj, npy_cdouble_wrapper Bx,
- int Cp, int Cj, npy_cdouble_wrapper Cx)
- csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
- int Bp, int Bj, npy_clongdouble_wrapper Bx,
- int Cp, int Cj, npy_clongdouble_wrapper Cx)
"""
- return _csr.csr_matmat_pass2(*args)
+ csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, signed char Ax,
+ int Bp, int Bj, signed char Bx, int Cp, int Cj,
+ signed char Cx)
+ csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
+ int Bp, int Bj, unsigned char Bx, int Cp,
+ int Cj, unsigned char Cx)
+ csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, short Ax, int Bp,
+ int Bj, short Bx, int Cp, int Cj, short Cx)
+ csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
+ int Bp, int Bj, unsigned short Bx, int Cp,
+ int Cj, unsigned short Cx)
+ csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, int Ax, int Bp,
+ int Bj, int Bx, int Cp, int Cj, int Cx)
+ csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
+ int Bp, int Bj, unsigned int Bx, int Cp,
+ int Cj, unsigned int Cx)
+ csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, long long Ax,
+ int Bp, int Bj, long long Bx, int Cp, int Cj,
+ long long Cx)
+ csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
+ int Bp, int Bj, unsigned long long Bx,
+ int Cp, int Cj, unsigned long long Cx)
+ csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, float Ax, int Bp,
+ int Bj, float Bx, int Cp, int Cj, float Cx)
+ csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, double Ax, int Bp,
+ int Bj, double Bx, int Cp, int Cj, double Cx)
+ csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, long double Ax,
+ int Bp, int Bj, long double Bx, int Cp, int Cj,
+ long double Cx)
+ csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
+ int Bp, int Bj, npy_cfloat_wrapper Bx,
+ int Cp, int Cj, npy_cfloat_wrapper Cx)
+ csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
+ int Bp, int Bj, npy_cdouble_wrapper Bx,
+ int Cp, int Cj, npy_cdouble_wrapper Cx)
+ csr_matmat_pass2(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
+ int Bp, int Bj, npy_clongdouble_wrapper Bx,
+ int Cp, int Cj, npy_clongdouble_wrapper Cx)
+ """
+ return _csr.csr_matmat_pass2(*args)
def csr_matvec(*args):
- """
- csr_matvec(int n_row, int n_col, int Ap, int Aj, signed char Ax,
- signed char Xx, signed char Yx)
- csr_matvec(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
- unsigned char Xx, unsigned char Yx)
- csr_matvec(int n_row, int n_col, int Ap, int Aj, short Ax, short Xx,
- short Yx)
- csr_matvec(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
- unsigned short Xx, unsigned short Yx)
- csr_matvec(int n_row, int n_col, int Ap, int Aj, int Ax, int Xx,
- int Yx)
- csr_matvec(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
- unsigned int Xx, unsigned int Yx)
- csr_matvec(int n_row, int n_col, int Ap, int Aj, long long Ax,
- long long Xx, long long Yx)
- csr_matvec(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
- unsigned long long Xx, unsigned long long Yx)
- csr_matvec(int n_row, int n_col, int Ap, int Aj, float Ax, float Xx,
- float Yx)
- csr_matvec(int n_row, int n_col, int Ap, int Aj, double Ax, double Xx,
- double Yx)
- csr_matvec(int n_row, int n_col, int Ap, int Aj, long double Ax,
- long double Xx, long double Yx)
- csr_matvec(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
- npy_cfloat_wrapper Xx, npy_cfloat_wrapper Yx)
- csr_matvec(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
- npy_cdouble_wrapper Xx, npy_cdouble_wrapper Yx)
- csr_matvec(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
- npy_clongdouble_wrapper Xx, npy_clongdouble_wrapper Yx)
"""
- return _csr.csr_matvec(*args)
+ csr_matvec(int n_row, int n_col, int Ap, int Aj, signed char Ax,
+ signed char Xx, signed char Yx)
+ csr_matvec(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
+ unsigned char Xx, unsigned char Yx)
+ csr_matvec(int n_row, int n_col, int Ap, int Aj, short Ax, short Xx,
+ short Yx)
+ csr_matvec(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
+ unsigned short Xx, unsigned short Yx)
+ csr_matvec(int n_row, int n_col, int Ap, int Aj, int Ax, int Xx,
+ int Yx)
+ csr_matvec(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
+ unsigned int Xx, unsigned int Yx)
+ csr_matvec(int n_row, int n_col, int Ap, int Aj, long long Ax,
+ long long Xx, long long Yx)
+ csr_matvec(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
+ unsigned long long Xx, unsigned long long Yx)
+ csr_matvec(int n_row, int n_col, int Ap, int Aj, float Ax, float Xx,
+ float Yx)
+ csr_matvec(int n_row, int n_col, int Ap, int Aj, double Ax, double Xx,
+ double Yx)
+ csr_matvec(int n_row, int n_col, int Ap, int Aj, long double Ax,
+ long double Xx, long double Yx)
+ csr_matvec(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
+ npy_cfloat_wrapper Xx, npy_cfloat_wrapper Yx)
+ csr_matvec(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
+ npy_cdouble_wrapper Xx, npy_cdouble_wrapper Yx)
+ csr_matvec(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
+ npy_clongdouble_wrapper Xx, npy_clongdouble_wrapper Yx)
+ """
+ return _csr.csr_matvec(*args)
def csr_matvecs(*args):
- """
- csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, signed char Ax,
- signed char Xx, signed char Yx)
- csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, unsigned char Ax,
- unsigned char Xx, unsigned char Yx)
- csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, short Ax,
- short Xx, short Yx)
- csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, unsigned short Ax,
- unsigned short Xx, unsigned short Yx)
- csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, int Ax,
- int Xx, int Yx)
- csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, unsigned int Ax,
- unsigned int Xx, unsigned int Yx)
- csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, long long Ax,
- long long Xx, long long Yx)
- csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, unsigned long long Ax,
- unsigned long long Xx,
- unsigned long long Yx)
- csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, float Ax,
- float Xx, float Yx)
- csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, double Ax,
- double Xx, double Yx)
- csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, long double Ax,
- long double Xx, long double Yx)
- csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, npy_cfloat_wrapper Ax,
- npy_cfloat_wrapper Xx,
- npy_cfloat_wrapper Yx)
- csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, npy_cdouble_wrapper Ax,
- npy_cdouble_wrapper Xx,
- npy_cdouble_wrapper Yx)
- csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, npy_clongdouble_wrapper Ax,
- npy_clongdouble_wrapper Xx,
- npy_clongdouble_wrapper Yx)
"""
- return _csr.csr_matvecs(*args)
+ csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, signed char Ax,
+ signed char Xx, signed char Yx)
+ csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, unsigned char Ax,
+ unsigned char Xx, unsigned char Yx)
+ csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, short Ax,
+ short Xx, short Yx)
+ csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, unsigned short Ax,
+ unsigned short Xx, unsigned short Yx)
+ csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, int Ax,
+ int Xx, int Yx)
+ csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, unsigned int Ax,
+ unsigned int Xx, unsigned int Yx)
+ csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, long long Ax,
+ long long Xx, long long Yx)
+ csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, unsigned long long Ax,
+ unsigned long long Xx,
+ unsigned long long Yx)
+ csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, float Ax,
+ float Xx, float Yx)
+ csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, double Ax,
+ double Xx, double Yx)
+ csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, long double Ax,
+ long double Xx, long double Yx)
+ csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, npy_cfloat_wrapper Ax,
+ npy_cfloat_wrapper Xx,
+ npy_cfloat_wrapper Yx)
+ csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, npy_cdouble_wrapper Ax,
+ npy_cdouble_wrapper Xx,
+ npy_cdouble_wrapper Yx)
+ csr_matvecs(int n_row, int n_col, int n_vecs, int Ap, int Aj, npy_clongdouble_wrapper Ax,
+ npy_clongdouble_wrapper Xx,
+ npy_clongdouble_wrapper Yx)
+ """
+ return _csr.csr_matvecs(*args)
def csr_elmul_csr(*args):
- """
- csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, signed char Ax,
- int Bp, int Bj, signed char Bx, int Cp, int Cj,
- signed char Cx)
- csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
- int Bp, int Bj, unsigned char Bx, int Cp,
- int Cj, unsigned char Cx)
- csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, short Ax, int Bp,
- int Bj, short Bx, int Cp, int Cj, short Cx)
- csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
- int Bp, int Bj, unsigned short Bx, int Cp,
- int Cj, unsigned short Cx)
- csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, int Ax, int Bp,
- int Bj, int Bx, int Cp, int Cj, int Cx)
- csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
- int Bp, int Bj, unsigned int Bx, int Cp,
- int Cj, unsigned int Cx)
- csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, long long Ax,
- int Bp, int Bj, long long Bx, int Cp, int Cj,
- long long Cx)
- csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
- int Bp, int Bj, unsigned long long Bx,
- int Cp, int Cj, unsigned long long Cx)
- csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, float Ax, int Bp,
- int Bj, float Bx, int Cp, int Cj, float Cx)
- csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, double Ax, int Bp,
- int Bj, double Bx, int Cp, int Cj, double Cx)
- csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, long double Ax,
- int Bp, int Bj, long double Bx, int Cp, int Cj,
- long double Cx)
- csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
- int Bp, int Bj, npy_cfloat_wrapper Bx,
- int Cp, int Cj, npy_cfloat_wrapper Cx)
- csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
- int Bp, int Bj, npy_cdouble_wrapper Bx,
- int Cp, int Cj, npy_cdouble_wrapper Cx)
- csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
- int Bp, int Bj, npy_clongdouble_wrapper Bx,
- int Cp, int Cj, npy_clongdouble_wrapper Cx)
"""
- return _csr.csr_elmul_csr(*args)
+ csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, signed char Ax,
+ int Bp, int Bj, signed char Bx, int Cp, int Cj,
+ signed char Cx)
+ csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
+ int Bp, int Bj, unsigned char Bx, int Cp,
+ int Cj, unsigned char Cx)
+ csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, short Ax, int Bp,
+ int Bj, short Bx, int Cp, int Cj, short Cx)
+ csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
+ int Bp, int Bj, unsigned short Bx, int Cp,
+ int Cj, unsigned short Cx)
+ csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, int Ax, int Bp,
+ int Bj, int Bx, int Cp, int Cj, int Cx)
+ csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
+ int Bp, int Bj, unsigned int Bx, int Cp,
+ int Cj, unsigned int Cx)
+ csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, long long Ax,
+ int Bp, int Bj, long long Bx, int Cp, int Cj,
+ long long Cx)
+ csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
+ int Bp, int Bj, unsigned long long Bx,
+ int Cp, int Cj, unsigned long long Cx)
+ csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, float Ax, int Bp,
+ int Bj, float Bx, int Cp, int Cj, float Cx)
+ csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, double Ax, int Bp,
+ int Bj, double Bx, int Cp, int Cj, double Cx)
+ csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, long double Ax,
+ int Bp, int Bj, long double Bx, int Cp, int Cj,
+ long double Cx)
+ csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
+ int Bp, int Bj, npy_cfloat_wrapper Bx,
+ int Cp, int Cj, npy_cfloat_wrapper Cx)
+ csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
+ int Bp, int Bj, npy_cdouble_wrapper Bx,
+ int Cp, int Cj, npy_cdouble_wrapper Cx)
+ csr_elmul_csr(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
+ int Bp, int Bj, npy_clongdouble_wrapper Bx,
+ int Cp, int Cj, npy_clongdouble_wrapper Cx)
+ """
+ return _csr.csr_elmul_csr(*args)
def csr_eldiv_csr(*args):
- """
- csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, signed char Ax,
- int Bp, int Bj, signed char Bx, int Cp, int Cj,
- signed char Cx)
- csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
- int Bp, int Bj, unsigned char Bx, int Cp,
- int Cj, unsigned char Cx)
- csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, short Ax, int Bp,
- int Bj, short Bx, int Cp, int Cj, short Cx)
- csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
- int Bp, int Bj, unsigned short Bx, int Cp,
- int Cj, unsigned short Cx)
- csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, int Ax, int Bp,
- int Bj, int Bx, int Cp, int Cj, int Cx)
- csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
- int Bp, int Bj, unsigned int Bx, int Cp,
- int Cj, unsigned int Cx)
- csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, long long Ax,
- int Bp, int Bj, long long Bx, int Cp, int Cj,
- long long Cx)
- csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
- int Bp, int Bj, unsigned long long Bx,
- int Cp, int Cj, unsigned long long Cx)
- csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, float Ax, int Bp,
- int Bj, float Bx, int Cp, int Cj, float Cx)
- csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, double Ax, int Bp,
- int Bj, double Bx, int Cp, int Cj, double Cx)
- csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, long double Ax,
- int Bp, int Bj, long double Bx, int Cp, int Cj,
- long double Cx)
- csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
- int Bp, int Bj, npy_cfloat_wrapper Bx,
- int Cp, int Cj, npy_cfloat_wrapper Cx)
- csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
- int Bp, int Bj, npy_cdouble_wrapper Bx,
- int Cp, int Cj, npy_cdouble_wrapper Cx)
- csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
- int Bp, int Bj, npy_clongdouble_wrapper Bx,
- int Cp, int Cj, npy_clongdouble_wrapper Cx)
"""
- return _csr.csr_eldiv_csr(*args)
+ csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, signed char Ax,
+ int Bp, int Bj, signed char Bx, int Cp, int Cj,
+ signed char Cx)
+ csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
+ int Bp, int Bj, unsigned char Bx, int Cp,
+ int Cj, unsigned char Cx)
+ csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, short Ax, int Bp,
+ int Bj, short Bx, int Cp, int Cj, short Cx)
+ csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
+ int Bp, int Bj, unsigned short Bx, int Cp,
+ int Cj, unsigned short Cx)
+ csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, int Ax, int Bp,
+ int Bj, int Bx, int Cp, int Cj, int Cx)
+ csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
+ int Bp, int Bj, unsigned int Bx, int Cp,
+ int Cj, unsigned int Cx)
+ csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, long long Ax,
+ int Bp, int Bj, long long Bx, int Cp, int Cj,
+ long long Cx)
+ csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
+ int Bp, int Bj, unsigned long long Bx,
+ int Cp, int Cj, unsigned long long Cx)
+ csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, float Ax, int Bp,
+ int Bj, float Bx, int Cp, int Cj, float Cx)
+ csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, double Ax, int Bp,
+ int Bj, double Bx, int Cp, int Cj, double Cx)
+ csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, long double Ax,
+ int Bp, int Bj, long double Bx, int Cp, int Cj,
+ long double Cx)
+ csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
+ int Bp, int Bj, npy_cfloat_wrapper Bx,
+ int Cp, int Cj, npy_cfloat_wrapper Cx)
+ csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
+ int Bp, int Bj, npy_cdouble_wrapper Bx,
+ int Cp, int Cj, npy_cdouble_wrapper Cx)
+ csr_eldiv_csr(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
+ int Bp, int Bj, npy_clongdouble_wrapper Bx,
+ int Cp, int Cj, npy_clongdouble_wrapper Cx)
+ """
+ return _csr.csr_eldiv_csr(*args)
def csr_plus_csr(*args):
- """
- csr_plus_csr(int n_row, int n_col, int Ap, int Aj, signed char Ax,
- int Bp, int Bj, signed char Bx, int Cp, int Cj,
- signed char Cx)
- csr_plus_csr(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
- int Bp, int Bj, unsigned char Bx, int Cp,
- int Cj, unsigned char Cx)
- csr_plus_csr(int n_row, int n_col, int Ap, int Aj, short Ax, int Bp,
- int Bj, short Bx, int Cp, int Cj, short Cx)
- csr_plus_csr(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
- int Bp, int Bj, unsigned short Bx, int Cp,
- int Cj, unsigned short Cx)
- csr_plus_csr(int n_row, int n_col, int Ap, int Aj, int Ax, int Bp,
- int Bj, int Bx, int Cp, int Cj, int Cx)
- csr_plus_csr(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
- int Bp, int Bj, unsigned int Bx, int Cp,
- int Cj, unsigned int Cx)
- csr_plus_csr(int n_row, int n_col, int Ap, int Aj, long long Ax,
- int Bp, int Bj, long long Bx, int Cp, int Cj,
- long long Cx)
- csr_plus_csr(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
- int Bp, int Bj, unsigned long long Bx,
- int Cp, int Cj, unsigned long long Cx)
- csr_plus_csr(int n_row, int n_col, int Ap, int Aj, float Ax, int Bp,
- int Bj, float Bx, int Cp, int Cj, float Cx)
- csr_plus_csr(int n_row, int n_col, int Ap, int Aj, double Ax, int Bp,
- int Bj, double Bx, int Cp, int Cj, double Cx)
- csr_plus_csr(int n_row, int n_col, int Ap, int Aj, long double Ax,
- int Bp, int Bj, long double Bx, int Cp, int Cj,
- long double Cx)
- csr_plus_csr(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
- int Bp, int Bj, npy_cfloat_wrapper Bx,
- int Cp, int Cj, npy_cfloat_wrapper Cx)
- csr_plus_csr(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
- int Bp, int Bj, npy_cdouble_wrapper Bx,
- int Cp, int Cj, npy_cdouble_wrapper Cx)
- csr_plus_csr(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
- int Bp, int Bj, npy_clongdouble_wrapper Bx,
- int Cp, int Cj, npy_clongdouble_wrapper Cx)
"""
- return _csr.csr_plus_csr(*args)
+ csr_plus_csr(int n_row, int n_col, int Ap, int Aj, signed char Ax,
+ int Bp, int Bj, signed char Bx, int Cp, int Cj,
+ signed char Cx)
+ csr_plus_csr(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
+ int Bp, int Bj, unsigned char Bx, int Cp,
+ int Cj, unsigned char Cx)
+ csr_plus_csr(int n_row, int n_col, int Ap, int Aj, short Ax, int Bp,
+ int Bj, short Bx, int Cp, int Cj, short Cx)
+ csr_plus_csr(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
+ int Bp, int Bj, unsigned short Bx, int Cp,
+ int Cj, unsigned short Cx)
+ csr_plus_csr(int n_row, int n_col, int Ap, int Aj, int Ax, int Bp,
+ int Bj, int Bx, int Cp, int Cj, int Cx)
+ csr_plus_csr(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
+ int Bp, int Bj, unsigned int Bx, int Cp,
+ int Cj, unsigned int Cx)
+ csr_plus_csr(int n_row, int n_col, int Ap, int Aj, long long Ax,
+ int Bp, int Bj, long long Bx, int Cp, int Cj,
+ long long Cx)
+ csr_plus_csr(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
+ int Bp, int Bj, unsigned long long Bx,
+ int Cp, int Cj, unsigned long long Cx)
+ csr_plus_csr(int n_row, int n_col, int Ap, int Aj, float Ax, int Bp,
+ int Bj, float Bx, int Cp, int Cj, float Cx)
+ csr_plus_csr(int n_row, int n_col, int Ap, int Aj, double Ax, int Bp,
+ int Bj, double Bx, int Cp, int Cj, double Cx)
+ csr_plus_csr(int n_row, int n_col, int Ap, int Aj, long double Ax,
+ int Bp, int Bj, long double Bx, int Cp, int Cj,
+ long double Cx)
+ csr_plus_csr(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
+ int Bp, int Bj, npy_cfloat_wrapper Bx,
+ int Cp, int Cj, npy_cfloat_wrapper Cx)
+ csr_plus_csr(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
+ int Bp, int Bj, npy_cdouble_wrapper Bx,
+ int Cp, int Cj, npy_cdouble_wrapper Cx)
+ csr_plus_csr(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
+ int Bp, int Bj, npy_clongdouble_wrapper Bx,
+ int Cp, int Cj, npy_clongdouble_wrapper Cx)
+ """
+ return _csr.csr_plus_csr(*args)
def csr_minus_csr(*args):
- """
- csr_minus_csr(int n_row, int n_col, int Ap, int Aj, signed char Ax,
- int Bp, int Bj, signed char Bx, int Cp, int Cj,
- signed char Cx)
- csr_minus_csr(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
- int Bp, int Bj, unsigned char Bx, int Cp,
- int Cj, unsigned char Cx)
- csr_minus_csr(int n_row, int n_col, int Ap, int Aj, short Ax, int Bp,
- int Bj, short Bx, int Cp, int Cj, short Cx)
- csr_minus_csr(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
- int Bp, int Bj, unsigned short Bx, int Cp,
- int Cj, unsigned short Cx)
- csr_minus_csr(int n_row, int n_col, int Ap, int Aj, int Ax, int Bp,
- int Bj, int Bx, int Cp, int Cj, int Cx)
- csr_minus_csr(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
- int Bp, int Bj, unsigned int Bx, int Cp,
- int Cj, unsigned int Cx)
- csr_minus_csr(int n_row, int n_col, int Ap, int Aj, long long Ax,
- int Bp, int Bj, long long Bx, int Cp, int Cj,
- long long Cx)
- csr_minus_csr(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
- int Bp, int Bj, unsigned long long Bx,
- int Cp, int Cj, unsigned long long Cx)
- csr_minus_csr(int n_row, int n_col, int Ap, int Aj, float Ax, int Bp,
- int Bj, float Bx, int Cp, int Cj, float Cx)
- csr_minus_csr(int n_row, int n_col, int Ap, int Aj, double Ax, int Bp,
- int Bj, double Bx, int Cp, int Cj, double Cx)
- csr_minus_csr(int n_row, int n_col, int Ap, int Aj, long double Ax,
- int Bp, int Bj, long double Bx, int Cp, int Cj,
- long double Cx)
- csr_minus_csr(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
- int Bp, int Bj, npy_cfloat_wrapper Bx,
- int Cp, int Cj, npy_cfloat_wrapper Cx)
- csr_minus_csr(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
- int Bp, int Bj, npy_cdouble_wrapper Bx,
- int Cp, int Cj, npy_cdouble_wrapper Cx)
- csr_minus_csr(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
- int Bp, int Bj, npy_clongdouble_wrapper Bx,
- int Cp, int Cj, npy_clongdouble_wrapper Cx)
"""
- return _csr.csr_minus_csr(*args)
+ csr_minus_csr(int n_row, int n_col, int Ap, int Aj, signed char Ax,
+ int Bp, int Bj, signed char Bx, int Cp, int Cj,
+ signed char Cx)
+ csr_minus_csr(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
+ int Bp, int Bj, unsigned char Bx, int Cp,
+ int Cj, unsigned char Cx)
+ csr_minus_csr(int n_row, int n_col, int Ap, int Aj, short Ax, int Bp,
+ int Bj, short Bx, int Cp, int Cj, short Cx)
+ csr_minus_csr(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
+ int Bp, int Bj, unsigned short Bx, int Cp,
+ int Cj, unsigned short Cx)
+ csr_minus_csr(int n_row, int n_col, int Ap, int Aj, int Ax, int Bp,
+ int Bj, int Bx, int Cp, int Cj, int Cx)
+ csr_minus_csr(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
+ int Bp, int Bj, unsigned int Bx, int Cp,
+ int Cj, unsigned int Cx)
+ csr_minus_csr(int n_row, int n_col, int Ap, int Aj, long long Ax,
+ int Bp, int Bj, long long Bx, int Cp, int Cj,
+ long long Cx)
+ csr_minus_csr(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
+ int Bp, int Bj, unsigned long long Bx,
+ int Cp, int Cj, unsigned long long Cx)
+ csr_minus_csr(int n_row, int n_col, int Ap, int Aj, float Ax, int Bp,
+ int Bj, float Bx, int Cp, int Cj, float Cx)
+ csr_minus_csr(int n_row, int n_col, int Ap, int Aj, double Ax, int Bp,
+ int Bj, double Bx, int Cp, int Cj, double Cx)
+ csr_minus_csr(int n_row, int n_col, int Ap, int Aj, long double Ax,
+ int Bp, int Bj, long double Bx, int Cp, int Cj,
+ long double Cx)
+ csr_minus_csr(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
+ int Bp, int Bj, npy_cfloat_wrapper Bx,
+ int Cp, int Cj, npy_cfloat_wrapper Cx)
+ csr_minus_csr(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
+ int Bp, int Bj, npy_cdouble_wrapper Bx,
+ int Cp, int Cj, npy_cdouble_wrapper Cx)
+ csr_minus_csr(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
+ int Bp, int Bj, npy_clongdouble_wrapper Bx,
+ int Cp, int Cj, npy_clongdouble_wrapper Cx)
+ """
+ return _csr.csr_minus_csr(*args)
def csr_sort_indices(*args):
- """
- csr_sort_indices(int n_row, int Ap, int Aj, signed char Ax)
- csr_sort_indices(int n_row, int Ap, int Aj, unsigned char Ax)
- csr_sort_indices(int n_row, int Ap, int Aj, short Ax)
- csr_sort_indices(int n_row, int Ap, int Aj, unsigned short Ax)
- csr_sort_indices(int n_row, int Ap, int Aj, int Ax)
- csr_sort_indices(int n_row, int Ap, int Aj, unsigned int Ax)
- csr_sort_indices(int n_row, int Ap, int Aj, long long Ax)
- csr_sort_indices(int n_row, int Ap, int Aj, unsigned long long Ax)
- csr_sort_indices(int n_row, int Ap, int Aj, float Ax)
- csr_sort_indices(int n_row, int Ap, int Aj, double Ax)
- csr_sort_indices(int n_row, int Ap, int Aj, long double Ax)
- csr_sort_indices(int n_row, int Ap, int Aj, npy_cfloat_wrapper Ax)
- csr_sort_indices(int n_row, int Ap, int Aj, npy_cdouble_wrapper Ax)
- csr_sort_indices(int n_row, int Ap, int Aj, npy_clongdouble_wrapper Ax)
"""
- return _csr.csr_sort_indices(*args)
+ csr_sort_indices(int n_row, int Ap, int Aj, signed char Ax)
+ csr_sort_indices(int n_row, int Ap, int Aj, unsigned char Ax)
+ csr_sort_indices(int n_row, int Ap, int Aj, short Ax)
+ csr_sort_indices(int n_row, int Ap, int Aj, unsigned short Ax)
+ csr_sort_indices(int n_row, int Ap, int Aj, int Ax)
+ csr_sort_indices(int n_row, int Ap, int Aj, unsigned int Ax)
+ csr_sort_indices(int n_row, int Ap, int Aj, long long Ax)
+ csr_sort_indices(int n_row, int Ap, int Aj, unsigned long long Ax)
+ csr_sort_indices(int n_row, int Ap, int Aj, float Ax)
+ csr_sort_indices(int n_row, int Ap, int Aj, double Ax)
+ csr_sort_indices(int n_row, int Ap, int Aj, long double Ax)
+ csr_sort_indices(int n_row, int Ap, int Aj, npy_cfloat_wrapper Ax)
+ csr_sort_indices(int n_row, int Ap, int Aj, npy_cdouble_wrapper Ax)
+ csr_sort_indices(int n_row, int Ap, int Aj, npy_clongdouble_wrapper Ax)
+ """
+ return _csr.csr_sort_indices(*args)
def csr_eliminate_zeros(*args):
- """
- csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, signed char Ax)
- csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, unsigned char Ax)
- csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, short Ax)
- csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, unsigned short Ax)
- csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, int Ax)
- csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, unsigned int Ax)
- csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, long long Ax)
- csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax)
- csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, float Ax)
- csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, double Ax)
- csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, long double Ax)
- csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax)
- csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax)
- csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax)
"""
- return _csr.csr_eliminate_zeros(*args)
+ csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, signed char Ax)
+ csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, unsigned char Ax)
+ csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, short Ax)
+ csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, unsigned short Ax)
+ csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, int Ax)
+ csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, unsigned int Ax)
+ csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, long long Ax)
+ csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax)
+ csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, float Ax)
+ csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, double Ax)
+ csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, long double Ax)
+ csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax)
+ csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax)
+ csr_eliminate_zeros(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax)
+ """
+ return _csr.csr_eliminate_zeros(*args)
def csr_sum_duplicates(*args):
- """
- csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, signed char Ax)
- csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, unsigned char Ax)
- csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, short Ax)
- csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, unsigned short Ax)
- csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, int Ax)
- csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, unsigned int Ax)
- csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, long long Ax)
- csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax)
- csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, float Ax)
- csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, double Ax)
- csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, long double Ax)
- csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax)
- csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax)
- csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax)
"""
- return _csr.csr_sum_duplicates(*args)
+ csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, signed char Ax)
+ csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, unsigned char Ax)
+ csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, short Ax)
+ csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, unsigned short Ax)
+ csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, int Ax)
+ csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, unsigned int Ax)
+ csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, long long Ax)
+ csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax)
+ csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, float Ax)
+ csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, double Ax)
+ csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, long double Ax)
+ csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax)
+ csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax)
+ csr_sum_duplicates(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax)
+ """
+ return _csr.csr_sum_duplicates(*args)
def get_csr_submatrix(*args):
- """
- get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, signed char Ax,
- int ir0, int ir1, int ic0, int ic1, std::vector<(int)> Bp,
- std::vector<(int)> Bj, std::vector<(signed char)> Bx)
- get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
- int ir0, int ir1, int ic0, int ic1, std::vector<(int)> Bp,
- std::vector<(int)> Bj, std::vector<(unsigned char)> Bx)
- get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, short Ax, int ir0,
- int ir1, int ic0, int ic1, std::vector<(int)> Bp,
- std::vector<(int)> Bj, std::vector<(short)> Bx)
- get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
- int ir0, int ir1, int ic0, int ic1, std::vector<(int)> Bp,
- std::vector<(int)> Bj, std::vector<(unsigned short)> Bx)
- get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, int Ax, int ir0,
- int ir1, int ic0, int ic1, std::vector<(int)> Bp,
- std::vector<(int)> Bj, std::vector<(int)> Bx)
- get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
- int ir0, int ir1, int ic0, int ic1, std::vector<(int)> Bp,
- std::vector<(int)> Bj, std::vector<(unsigned int)> Bx)
- get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, long long Ax,
- int ir0, int ir1, int ic0, int ic1, std::vector<(int)> Bp,
- std::vector<(int)> Bj, std::vector<(long long)> Bx)
- get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
- int ir0, int ir1, int ic0, int ic1,
- std::vector<(int)> Bp, std::vector<(int)> Bj,
- std::vector<(unsigned long long)> Bx)
- get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, float Ax, int ir0,
- int ir1, int ic0, int ic1, std::vector<(int)> Bp,
- std::vector<(int)> Bj, std::vector<(float)> Bx)
- get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, double Ax, int ir0,
- int ir1, int ic0, int ic1, std::vector<(int)> Bp,
- std::vector<(int)> Bj, std::vector<(double)> Bx)
- get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, long double Ax,
- int ir0, int ir1, int ic0, int ic1, std::vector<(int)> Bp,
- std::vector<(int)> Bj, std::vector<(long double)> Bx)
- get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
- int ir0, int ir1, int ic0, int ic1,
- std::vector<(int)> Bp, std::vector<(int)> Bj,
- std::vector<(npy_cfloat_wrapper)> Bx)
- get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
- int ir0, int ir1, int ic0, int ic1,
- std::vector<(int)> Bp, std::vector<(int)> Bj,
- std::vector<(npy_cdouble_wrapper)> Bx)
- get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
- int ir0, int ir1, int ic0, int ic1,
- std::vector<(int)> Bp, std::vector<(int)> Bj,
- std::vector<(npy_clongdouble_wrapper)> Bx)
"""
- return _csr.get_csr_submatrix(*args)
-
+ get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, signed char Ax,
+ int ir0, int ir1, int ic0, int ic1, std::vector<(int)> Bp,
+ std::vector<(int)> Bj, std::vector<(signed char)> Bx)
+ get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, unsigned char Ax,
+ int ir0, int ir1, int ic0, int ic1, std::vector<(int)> Bp,
+ std::vector<(int)> Bj, std::vector<(unsigned char)> Bx)
+ get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, short Ax, int ir0,
+ int ir1, int ic0, int ic1, std::vector<(int)> Bp,
+ std::vector<(int)> Bj, std::vector<(short)> Bx)
+ get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, unsigned short Ax,
+ int ir0, int ir1, int ic0, int ic1, std::vector<(int)> Bp,
+ std::vector<(int)> Bj, std::vector<(unsigned short)> Bx)
+ get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, int Ax, int ir0,
+ int ir1, int ic0, int ic1, std::vector<(int)> Bp,
+ std::vector<(int)> Bj, std::vector<(int)> Bx)
+ get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, unsigned int Ax,
+ int ir0, int ir1, int ic0, int ic1, std::vector<(int)> Bp,
+ std::vector<(int)> Bj, std::vector<(unsigned int)> Bx)
+ get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, long long Ax,
+ int ir0, int ir1, int ic0, int ic1, std::vector<(int)> Bp,
+ std::vector<(int)> Bj, std::vector<(long long)> Bx)
+ get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, unsigned long long Ax,
+ int ir0, int ir1, int ic0, int ic1,
+ std::vector<(int)> Bp, std::vector<(int)> Bj,
+ std::vector<(unsigned long long)> Bx)
+ get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, float Ax, int ir0,
+ int ir1, int ic0, int ic1, std::vector<(int)> Bp,
+ std::vector<(int)> Bj, std::vector<(float)> Bx)
+ get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, double Ax, int ir0,
+ int ir1, int ic0, int ic1, std::vector<(int)> Bp,
+ std::vector<(int)> Bj, std::vector<(double)> Bx)
+ get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, long double Ax,
+ int ir0, int ir1, int ic0, int ic1, std::vector<(int)> Bp,
+ std::vector<(int)> Bj, std::vector<(long double)> Bx)
+ get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, npy_cfloat_wrapper Ax,
+ int ir0, int ir1, int ic0, int ic1,
+ std::vector<(int)> Bp, std::vector<(int)> Bj,
+ std::vector<(npy_cfloat_wrapper)> Bx)
+ get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, npy_cdouble_wrapper Ax,
+ int ir0, int ir1, int ic0, int ic1,
+ std::vector<(int)> Bp, std::vector<(int)> Bj,
+ std::vector<(npy_cdouble_wrapper)> Bx)
+ get_csr_submatrix(int n_row, int n_col, int Ap, int Aj, npy_clongdouble_wrapper Ax,
+ int ir0, int ir1, int ic0, int ic1,
+ std::vector<(int)> Bp, std::vector<(int)> Bj,
+ std::vector<(npy_clongdouble_wrapper)> Bx)
+ """
+ return _csr.get_csr_submatrix(*args)
Modified: branches/refactor_fft/scipy/sparse/sparsetools/dia.py
===================================================================
--- branches/refactor_fft/scipy/sparse/sparsetools/dia.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/sparse/sparsetools/dia.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -51,40 +51,39 @@
def dia_matvec(*args):
- """
- dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
- signed char diags, signed char Xx, signed char Yx)
- dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
- unsigned char diags, unsigned char Xx, unsigned char Yx)
- dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
- short diags, short Xx, short Yx)
- dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
- unsigned short diags, unsigned short Xx,
- unsigned short Yx)
- dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
- int diags, int Xx, int Yx)
- dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
- unsigned int diags, unsigned int Xx, unsigned int Yx)
- dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
- long long diags, long long Xx, long long Yx)
- dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
- unsigned long long diags, unsigned long long Xx,
- unsigned long long Yx)
- dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
- float diags, float Xx, float Yx)
- dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
- double diags, double Xx, double Yx)
- dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
- long double diags, long double Xx, long double Yx)
- dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
- npy_cfloat_wrapper diags, npy_cfloat_wrapper Xx,
- npy_cfloat_wrapper Yx)
- dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
- npy_cdouble_wrapper diags, npy_cdouble_wrapper Xx,
- npy_cdouble_wrapper Yx)
- dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
- npy_clongdouble_wrapper diags, npy_clongdouble_wrapper Xx,
- npy_clongdouble_wrapper Yx)
"""
- return _dia.dia_matvec(*args)
-
+ dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
+ signed char diags, signed char Xx, signed char Yx)
+ dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
+ unsigned char diags, unsigned char Xx, unsigned char Yx)
+ dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
+ short diags, short Xx, short Yx)
+ dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
+ unsigned short diags, unsigned short Xx,
+ unsigned short Yx)
+ dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
+ int diags, int Xx, int Yx)
+ dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
+ unsigned int diags, unsigned int Xx, unsigned int Yx)
+ dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
+ long long diags, long long Xx, long long Yx)
+ dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
+ unsigned long long diags, unsigned long long Xx,
+ unsigned long long Yx)
+ dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
+ float diags, float Xx, float Yx)
+ dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
+ double diags, double Xx, double Yx)
+ dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
+ long double diags, long double Xx, long double Yx)
+ dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
+ npy_cfloat_wrapper diags, npy_cfloat_wrapper Xx,
+ npy_cfloat_wrapper Yx)
+ dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
+ npy_cdouble_wrapper diags, npy_cdouble_wrapper Xx,
+ npy_cdouble_wrapper Yx)
+ dia_matvec(int n_row, int n_col, int n_diags, int L, int offsets,
+ npy_clongdouble_wrapper diags, npy_clongdouble_wrapper Xx,
+ npy_clongdouble_wrapper Yx)
+ """
+ return _dia.dia_matvec(*args)
Modified: branches/refactor_fft/scipy/sparse/sputils.py
===================================================================
--- branches/refactor_fft/scipy/sparse/sputils.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/sparse/sputils.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -100,7 +100,7 @@
# Assume it's a tuple of matrix dimensions (M, N)
(M, N) = x
assert isintlike(M) and isintlike(N) # raises TypeError unless integers
- assert M > 0 and N > 0
+ #assert M > 0 and N > 0
except (ValueError, TypeError, AssertionError):
return False
else:
Modified: branches/refactor_fft/scipy/sparse/tests/test_base.py
===================================================================
--- branches/refactor_fft/scipy/sparse/tests/test_base.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/sparse/tests/test_base.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -34,7 +34,6 @@
warnings.simplefilter('ignore',SparseEfficiencyWarning)
-#TODO check that invalid shape in constructor raises exception
#TODO check that spmatrix( ... , copy=X ) is respected
#TODO test prune
#TODO test has_sorted_indices
@@ -45,13 +44,24 @@
self.dat = matrix([[1,0,0,2],[3,0,1,0],[0,2,0,0]],'d')
self.datsp = self.spmatrix(self.dat)
+ def test_empty(self):
+ """create empty matrices"""
+
+ assert_equal(self.spmatrix((3,3)).todense(), np.zeros((3,3)))
+ assert_equal(self.spmatrix((3,3)).nnz, 0)
+
+ def test_invalid_shapes(self):
+ assert_raises(ValueError, self.spmatrix, (-1,3) )
+ assert_raises(ValueError, self.spmatrix, (3,-1) )
+ assert_raises(ValueError, self.spmatrix, (-1,-1) )
+
def test_repr(self):
repr(self.datsp)
def test_str(self):
str(self.datsp)
- def test_empty(self):
+ def test_empty_arithmetic(self):
"""Test manipulating empty matrices. Fails in SciPy SVN <= r1768
"""
shape = (5, 5)
@@ -304,17 +314,11 @@
assert(isinstance( M * array([1,2,3]), ndarray))
assert(isinstance( M * matrix([1,2,3]).T, matrix))
-
#ensure exception is raised for improper dimensions
bad_vecs = [array([1,2]), array([1,2,3,4]), array([[1],[2]]),
matrix([1,2,3]), matrix([[1],[2]])]
- caught = 0
for x in bad_vecs:
- try:
- y = M * x
- except ValueError:
- caught += 1
- assert_equal(caught,len(bad_vecs))
+ assert_raises(ValueError, M.__mul__, x)
# Should this be supported or not?!
#flat = array([1,2,3])
@@ -351,21 +355,18 @@
csp = bsp.tocsc()
c = b
assert_array_almost_equal((asp*csp).todense(), a*c)
- assert_array_almost_equal((asp.matmat(csp)).todense(), a*c)
assert_array_almost_equal( asp*c, a*c)
assert_array_almost_equal( a*csp, a*c)
assert_array_almost_equal( a2*csp, a*c)
csp = bsp.tocsr()
assert_array_almost_equal((asp*csp).todense(), a*c)
- assert_array_almost_equal((asp.matmat(csp)).todense(), a*c)
assert_array_almost_equal( asp*c, a*c)
assert_array_almost_equal( a*csp, a*c)
assert_array_almost_equal( a2*csp, a*c)
csp = bsp.tocoo()
assert_array_almost_equal((asp*csp).todense(), a*c)
- assert_array_almost_equal((asp.matmat(csp)).todense(), a*c)
assert_array_almost_equal( asp*c, a*c)
assert_array_almost_equal( a*csp, a*c)
@@ -522,47 +523,6 @@
assert_array_equal(self.dat/17.3,a.todense())
-class _TestMatvecOutput:
- """test using the matvec() output parameter"""
- def test_matvec_output(self):
- pass #Currently disabled
-
-# #flat array
-# x = array([1.25, -6.5, 0.125, -3.75],dtype='d')
-# y = zeros(3,dtype='d')
-#
-# self.datsp.matvec(x,y)
-# assert_array_equal(self.datsp*x,y)
-#
-# #column vector
-# x = array([1.25, -6.5, 0.125, -3.75],dtype='d')
-# x = x.reshape(4,1)
-# y = zeros((3,1),dtype='d')
-#
-# self.datsp.matvec(x,y)
-# assert_array_equal(self.datsp*x,y)
-#
-# # improper output type
-# x = array([1.25, -6.5, 0.125, -3.75],dtype='d')
-# y = zeros(3,dtype='i')
-#
-# self.assertRaises( ValueError, self.datsp.matvec, x, y )
-#
-# # improper output shape
-# x = array([1.25, -6.5, 0.125, -3.75],dtype='d')
-# y = zeros(2,dtype='d')
-#
-# self.assertRaises( ValueError, self.datsp.matvec, x, y )
-#
-# # proper upcast output type
-# x = array([1.25, -6.5, 0.125, -3.75],dtype='complex64')
-# x.imag = [1,2,3,4]
-# y = zeros(3,dtype='complex128')
-#
-# self.datsp.matvec(x,y)
-# assert_array_equal(self.datsp*x,y)
-# assert_equal((self.datsp*x).dtype,y.dtype)
-
class _TestGetSet:
def test_setelement(self):
a = self.spmatrix((3,4))
@@ -889,7 +849,7 @@
class TestCSR(_TestCommon, _TestGetSet, _TestSolve,
- _TestInplaceArithmetic, _TestArithmetic, _TestMatvecOutput,
+ _TestInplaceArithmetic, _TestArithmetic,
_TestHorizSlicing, _TestVertSlicing, _TestBothSlicing,
_TestFancyIndexing, TestCase):
spmatrix = csr_matrix
@@ -986,7 +946,7 @@
class TestCSC(_TestCommon, _TestGetSet, _TestSolve,
- _TestInplaceArithmetic, _TestArithmetic, _TestMatvecOutput,
+ _TestInplaceArithmetic, _TestArithmetic,
_TestHorizSlicing, _TestVertSlicing, _TestBothSlicing,
_TestFancyIndexing, TestCase):
spmatrix = csc_matrix
@@ -1304,10 +1264,10 @@
assert_array_equal(C.A, D.A)
def test_fancy_indexing(self):
- M = arange(25).reshape(5,5)
+ M = arange(25).reshape(5,5)
A = lil_matrix( M )
- assert_equal(A[array([1,2,3]),2:3].todense(), M[array([1,2,3]),2:3])
+ assert_equal(A[array([1,2,3]),2:3].todense(), M[array([1,2,3]),2:3])
def test_point_wise_multiply(self):
l = lil_matrix((4,3))
@@ -1371,8 +1331,8 @@
def test_constructor4(self):
"""from dense matrix"""
mat = array([[0,1,0,0],
- [7,0,3,0],
- [0,4,0,0]])
+ [7,0,3,0],
+ [0,4,0,0]])
coo = coo_matrix(mat)
assert_array_equal(coo.todense(),mat)
@@ -1386,12 +1346,17 @@
spmatrix = dia_matrix
def test_constructor1(self):
- pass
- #TODO add test
+ D = matrix([[1, 0, 3, 0],
+ [1, 2, 0, 4],
+ [0, 2, 3, 0],
+ [0, 0, 3, 4]])
+ data = np.array([[1,2,3,4]]).repeat(3,axis=0)
+ offsets = np.array([0,-1,2])
+ assert_equal(dia_matrix( (data,offsets), shape=(4,4)).todense(), D)
-class TestBSR(_TestCommon, _TestArithmetic, _TestInplaceArithmetic,
- _TestMatvecOutput, TestCase):
+
+class TestBSR(_TestCommon, _TestArithmetic, _TestInplaceArithmetic, TestCase):
spmatrix = bsr_matrix
def test_constructor1(self):
Modified: branches/refactor_fft/scipy/sparse/tests/test_sputils.py
===================================================================
--- branches/refactor_fft/scipy/sparse/tests/test_sputils.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/sparse/tests/test_sputils.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -47,10 +47,9 @@
assert_equal(isshape( (1,2) ),True)
assert_equal(isshape( (5,2) ),True)
- assert_equal(isshape( (-1,4) ),False)
assert_equal(isshape( (1.5,2) ),False)
- assert_equal(isshape( (0,4) ),False)
assert_equal(isshape( (2,2,2) ),False)
+ assert_equal(isshape( ([2],2) ),False)
def test_issequence(self):
assert_equal(issequence( (1,) ),True)
Modified: branches/refactor_fft/scipy/stats/distributions.py
===================================================================
--- branches/refactor_fft/scipy/stats/distributions.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/stats/distributions.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -542,7 +542,7 @@
goodargs = argsreduce(cond, *((x,)+args))
place(output,cond,self._sf(*goodargs))
if output.ndim == 0:
- return output[()]
+ return output[()]
return output
def ppf(self,q,*args,**kwds):
@@ -573,7 +573,7 @@
scale, loc, goodargs = goodargs[-2], goodargs[-1], goodargs[:-2]
place(output,cond,self._ppf(*goodargs)*scale + loc)
if output.ndim == 0:
- return output[()]
+ return output[()]
return output
def isf(self,q,*args,**kwds):
@@ -3517,7 +3517,7 @@
goodargs = argsreduce(cond, *((k,)+args))
place(output,cond,self._pmf(*goodargs))
if output.ndim == 0:
- return output[()]
+ return output[()]
return output
def cdf(self, k, *args, **kwds):
@@ -3547,7 +3547,7 @@
goodargs = argsreduce(cond, *((k,)+args))
place(output,cond,self._cdf(*goodargs))
if output.ndim == 0:
- return output[()]
+ return output[()]
return output
def sf(self,k,*args,**kwds):
@@ -3577,7 +3577,7 @@
goodargs = argsreduce(cond, *((k,)+args))
place(output,cond,self._sf(*goodargs))
if output.ndim == 0:
- return output[()]
+ return output[()]
return output
def ppf(self,q,*args,**kwds):
@@ -3607,7 +3607,7 @@
loc, goodargs = goodargs[-1], goodargs[:-1]
place(output,cond,self._ppf(*goodargs) + loc)
if output.ndim == 0:
- return output[()]
+ return output[()]
return output
def isf(self,q,*args,**kwds):
@@ -3638,7 +3638,7 @@
loc, goodargs = goodargs[-1], goodargs[:-1]
place(output,cond,self._ppf(*goodargs) + loc)
if output.ndim == 0:
- return output[()]
+ return output[()]
return output
def stats(self, *args, **kwds):
Modified: branches/refactor_fft/scipy/stats/stats.py
===================================================================
--- branches/refactor_fft/scipy/stats/stats.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/stats/stats.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -489,10 +489,7 @@
- numpy.median has a ddof argument to replace bias in a more general manner.
scipy.stats.median(a, bias=True) can be replaced by numpy.median(x,
axis=0, ddof=1).""", DeprecationWarning)
- a, axis = _chk_asarray(a, axis)
- if axis != 0:
- a = np.rollaxis(a, axis, 0)
- return np.median(a)
+ return np.median(a, axis)
def mode(a, axis=0):
"""Returns an array of the modal (most common) value in the passed array.
Modified: branches/refactor_fft/scipy/stats/tests/test_stats.py
===================================================================
--- branches/refactor_fft/scipy/stats/tests/test_stats.py 2008-10-26 09:20:24 UTC (rev 4845)
+++ branches/refactor_fft/scipy/stats/tests/test_stats.py 2008-10-26 11:02:22 UTC (rev 4846)
@@ -625,15 +625,6 @@
A += val
assert_almost_equal(stats.mean(a,axis=None),A/(5*3.0*5))
-class TestMedian(TestCase):
- def test_basic(self):
- a1 = [3,4,5,10,-3,-5,6]
- a2 = [3,-6,-2,8,7,4,2,1]
- a3 = [3.,4,5,10,-3,-5,-6,7.0]
- assert_equal(stats.median(a1),4)
- assert_equal(stats.median(a2),2.5)
- assert_equal(stats.median(a3),3.5)
-
class TestPercentile(TestCase):
def setUp(self):
self.a1 = [3,4,5,10,-3,-5,6]
@@ -694,6 +685,20 @@
assert_almost_equal(stats.median(data1),2.5)
assert_almost_equal(stats.median(data2),5)
+ def test_basic2(self):
+ a1 = [3,4,5,10,-3,-5,6]
+ a2 = [3,-6,-2,8,7,4,2,1]
+ a3 = [3.,4,5,10,-3,-5,-6,7.0]
+ assert_equal(stats.median(a1),4)
+ assert_equal(stats.median(a2),2.5)
+ assert_equal(stats.median(a3),3.5)
+
+ def test_axis(self):
+ """Regression test for #760."""
+ a1 = np.array([[3,4,5], [10,-3,-5]])
+ assert_equal(stats.median(a1), np.array([6.5, 0.5, 0.]))
+ assert_equal(stats.median(a1, axis=-1), np.array([4., -3]))
+
class TestMode(TestCase):
def test_basic(self):
data1 = [3,5,1,10,23,3,2,6,8,6,10,6]
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