[Scipy-svn] r4619 - in trunk/scipy: sparse/linalg/dsolve sparse/linalg/dsolve/umfpack sparse/linalg/dsolve/umfpack/tests sparse/linalg/eigen/arpack/tests stats
scipy-svn at scipy.org
scipy-svn at scipy.org
Fri Aug 8 03:11:33 EDT 2008
Author: jarrod.millman
Date: 2008-08-08 02:11:28 -0500 (Fri, 08 Aug 2008)
New Revision: 4619
Modified:
trunk/scipy/sparse/linalg/dsolve/linsolve.py
trunk/scipy/sparse/linalg/dsolve/umfpack/info.py
trunk/scipy/sparse/linalg/dsolve/umfpack/tests/try_umfpack.py
trunk/scipy/sparse/linalg/eigen/arpack/tests/test_speigs.py
trunk/scipy/stats/morestats.py
Log:
cleanup
Modified: trunk/scipy/sparse/linalg/dsolve/linsolve.py
===================================================================
--- trunk/scipy/sparse/linalg/dsolve/linsolve.py 2008-08-08 06:17:26 UTC (rev 4618)
+++ trunk/scipy/sparse/linalg/dsolve/linsolve.py 2008-08-08 07:11:28 UTC (rev 4619)
@@ -107,9 +107,9 @@
A linear solver, for a sparse, square matrix A, using LU decomposition where
L is a lower triangular matrix and U is an upper triagular matrix.
- Returns a factored_lu object. (scipy.linsolve._superlu.SciPyLUType)
+ Returns a factored_lu object. (scipy.sparse.linalg.dsolve._superlu.SciPyLUType)
- See scipy.linsolve._superlu.dgstrf for more info.
+ See scipy.sparse.linalg.dsolve._superlu.dgstrf for more info.
"""
if not isspmatrix_csc(A):
Modified: trunk/scipy/sparse/linalg/dsolve/umfpack/info.py
===================================================================
--- trunk/scipy/sparse/linalg/dsolve/umfpack/info.py 2008-08-08 06:17:26 UTC (rev 4618)
+++ trunk/scipy/sparse/linalg/dsolve/umfpack/info.py 2008-08-08 07:11:28 UTC (rev 4619)
@@ -50,7 +50,7 @@
:Examples:
----------
-Assuming this module imported as um (import scipy.linsolve.umfpack as um)
+Assuming this module imported as um (import scipy.sparse.linalg.dsolve.umfpack as um)
Sparse matrix in CSR or CSC format: mtx
Righthand-side: rhs
Modified: trunk/scipy/sparse/linalg/dsolve/umfpack/tests/try_umfpack.py
===================================================================
--- trunk/scipy/sparse/linalg/dsolve/umfpack/tests/try_umfpack.py 2008-08-08 06:17:26 UTC (rev 4618)
+++ trunk/scipy/sparse/linalg/dsolve/umfpack/tests/try_umfpack.py 2008-08-08 07:11:28 UTC (rev 4619)
@@ -4,16 +4,16 @@
"""Benchamrks for umfpack module"""
from optparse import OptionParser
-import scipy.linsolve.umfpack as um
-import numpy as nm
-#import scipy.io as io
-import scipy.sparse as sp
-import scipy.linalg as nla
-#import pylab
import time
import urllib
import gzip
+import numpy as np
+
+import scipy.sparse as sp
+import scipy.sparse.linalg.dsolve.umfpack as um
+import scipy.linalg as nla
+
defaultURL = 'http://www.cise.ufl.edu/research/sparse/HBformat/'
usage = """%%prog [options] <matrix file name> [<matrix file name>, ...]
@@ -35,8 +35,8 @@
nRow, nCol = map( int, fd.readline().split() )
nItem = int( fd.readline() )
- ij = nm.zeros( (nItem,2), nm.int32 )
- val = nm.zeros( (nItem,), nm.float64 )
+ ij = np.zeros( (nItem,2), np.int32 )
+ val = np.zeros( (nItem,), np.float64 )
for ii, row in enumerate( fd.readlines() ):
aux = row.split()
ij[ii] = int( aux[0] ), int( aux[1] )
@@ -54,7 +54,7 @@
ij, val = io.read_array( fd,
columns = [(0,1), (2,)],
- atype = (nm.int32, nm.float64),
+ atype = (np.int32, np.float64),
rowsize = nItem )
mtx = sp.csc_matrix( (val, ij), dims = (nRow, nCol), nzmax = nItem )
@@ -137,14 +137,14 @@
sizes.append( mtx.shape )
nnzs.append( mtx.nnz )
- tts = nm.zeros( (2,), dtype = nm.double )
+ tts = np.zeros( (2,), dtype = np.double )
times.append( tts )
- err = nm.zeros( (2,2), dtype = nm.double )
+ err = np.zeros( (2,2), dtype = np.double )
errors.append( err )
print 'size : %s (%d nnz)' % (mtx.shape, mtx.nnz)
- sol0 = nm.ones( (mtx.shape[0],), dtype = nm.double )
+ sol0 = np.ones( (mtx.shape[0],), dtype = np.double )
rhs = mtx * sol0
umfpack = um.UmfpackContext()
@@ -181,7 +181,7 @@
import pylab
except ImportError:
raise ImportError, "could not import pylab"
- times = nm.array( times )
+ times = np.array( times )
print times
pylab.plot( times[:,0], 'b-o' )
if options.compare:
@@ -196,17 +196,17 @@
xrng = range( len( nnzs ) )
for ii in xrng:
yy = y2 + 0.4 * (ax[3] - ax[2])\
- * nm.sin( ii * 2 * nm.pi / (len( xrng ) - 1) )
+ * np.sin( ii * 2 * np.pi / (len( xrng ) - 1) )
if options.compare:
pylab.text( ii+0.02, yy,
'%s\n%.2e err_umf\n%.2e err_sp'
- % (sizes[ii], nm.sum( errors[ii][0,:] ),
- nm.sum( errors[ii][1,:] )) )
+ % (sizes[ii], np.sum( errors[ii][0,:] ),
+ np.sum( errors[ii][1,:] )) )
else:
pylab.text( ii+0.02, yy,
'%s\n%.2e err_umf'
- % (sizes[ii], nm.sum( errors[ii][0,:] )) )
+ % (sizes[ii], np.sum( errors[ii][0,:] )) )
pylab.plot( [ii, ii], [ax[2], ax[3]], 'k:' )
pylab.xticks( xrng, ['%d' % (nnzs[ii] ) for ii in xrng] )
Modified: trunk/scipy/sparse/linalg/eigen/arpack/tests/test_speigs.py
===================================================================
--- trunk/scipy/sparse/linalg/eigen/arpack/tests/test_speigs.py 2008-08-08 06:17:26 UTC (rev 4618)
+++ trunk/scipy/sparse/linalg/eigen/arpack/tests/test_speigs.py 2008-08-08 07:11:28 UTC (rev 4619)
@@ -39,10 +39,10 @@
# class TestGeneigs(TestCase):
# def test(self):
# import pickle
-# import scipy.linsolve
+# from scipy.sparse.linalg import dsolve
# A,B = pickle.load(file('mats.pickle'))
# sigma = 27.
-# sigma_solve = scipy.linsolve.splu(A - sigma*B).solve
+# sigma_solve = dsolve.splu(A - sigma*B).solve
# w = ARPACK_gen_eigs(B.matvec, sigma_solve, B.shape[0], sigma, 10)[0]
# assert_array_almost_equal(w,
# [27.346442255386375, 49.100299170945405, 56.508474856551544, 56.835800191692492,
Modified: trunk/scipy/stats/morestats.py
===================================================================
--- trunk/scipy/stats/morestats.py 2008-08-08 06:17:26 UTC (rev 4618)
+++ trunk/scipy/stats/morestats.py 2008-08-08 07:11:28 UTC (rev 4619)
@@ -16,7 +16,6 @@
import scipy.optimize as optimize
import scipy.special as special
import futil
-import numpy as sb
from numpy.testing.decorators import setastest
import warnings
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