[Scipy-svn] r3188 - trunk/Lib/sparse
scipy-svn at scipy.org
scipy-svn at scipy.org
Wed Jul 25 01:46:23 EDT 2007
Author: wnbell
Date: 2007-07-25 00:46:18 -0500 (Wed, 25 Jul 2007)
New Revision: 3188
Modified:
trunk/Lib/sparse/sparse.py
Log:
added __all__ to sparse.py to avoid polluting namespace
Modified: trunk/Lib/sparse/sparse.py
===================================================================
--- trunk/Lib/sparse/sparse.py 2007-07-24 14:13:43 UTC (rev 3187)
+++ trunk/Lib/sparse/sparse.py 2007-07-25 05:46:18 UTC (rev 3188)
@@ -4,6 +4,13 @@
Modified and extended by Ed Schofield, Robert Cimrman, and Nathan Bell
"""
+
+__all__ = ['csc_matrix','csr_matrix','coo_matrix','lil_matrix','dok_matrix',
+ 'spdiags','speye','spidentity',
+ 'isspmatrix','issparse','isspmatrix_csc','isspmatrix_csr',
+ 'isspmatrix_lil','isspmatrix_dok' ]
+
+
import warnings
from numpy import zeros, isscalar, real, imag, asarray, asmatrix, matrix, \
@@ -2104,7 +2111,7 @@
indptr, rowind, data = cootocsc(self.shape[0], self.shape[1], \
self.size, self.row, self.col, \
self.data)
- return csc_matrix((data, rowind, indptr), self.shape)
+ return csc_matrix((data, rowind, indptr), self.shape, check=False)
def tocsr(self):
@@ -2114,7 +2121,7 @@
indptr, colind, data = cootocsr(self.shape[0], self.shape[1], \
self.size, self.row, self.col, \
self.data)
- return csr_matrix((data, colind, indptr), self.shape)
+ return csr_matrix((data, colind, indptr), self.shape, check=False)
def tocoo(self, copy=False):
return self.toself(copy)
@@ -2600,48 +2607,3 @@
return isinstance(t, (list, tuple))
-def _testme():
- a = csc_matrix((arange(1, 9), \
- transpose([[0, 1, 1, 2, 2, 3, 3, 4], [0, 1, 3, 0, 2, 3, 4, 4]])))
- print "Representation of a matrix:"
- print repr(a)
- print "How a matrix prints:"
- print a
- print "Adding two matrices:"
- b = a+a
- print b
- print "Subtracting two matrices:"
- c = b - a
- print c
- print "Multiplying a sparse matrix by a dense vector:"
- d = a*[1, 2, 3, 4, 5]
- print d
- print [1, 2, 3, 4, 5]*a
-
- print "Inverting a sparse linear system:"
- print "The sparse matrix (constructed from diagonals):"
- a = spdiags([[1, 2, 3, 4, 5], [6, 5, 8, 9, 10]], [0, 1], 5, 5)
- b = array([1, 2, 3, 4, 5])
-
- print "(Various small tests follow ...)\n"
- print "Dictionary of keys matrix:"
- a = dok_matrix(shape=(10, 10))
- a[1, 1] = 1.
- a[1, 5] = 1.
- print a
- print "Adding it to itself:"
- print a + a
-
- print "Multiplying by a scalar:"
- print a * 100
-
- print "Dense representation:"
- print a.todense()
-
- print "Converting to a CSR matrix:"
- c = a.tocsr()
- print c
-
-if __name__ == "__main__":
- _testme()
-
More information about the Scipy-svn
mailing list