[Scipy-svn] r4737 - in trunk/scipy/sparse: . benchmarks linalg/dsolve/tests linalg/dsolve/umfpack linalg/dsolve/umfpack/tests linalg/eigen/arpack linalg/eigen/arpack/tests linalg/eigen/lobpcg linalg/eigen/lobpcg/tests linalg/isolve linalg/isolve/tests linalg/tests tests

scipy-svn@scip... scipy-svn@scip...
Thu Sep 18 16:20:23 CDT 2008


Author: alan.mcintyre
Date: 2008-09-18 16:20:05 -0500 (Thu, 18 Sep 2008)
New Revision: 4737

Modified:
   trunk/scipy/sparse/benchmarks/bench_sparse.py
   trunk/scipy/sparse/bsr.py
   trunk/scipy/sparse/compressed.py
   trunk/scipy/sparse/construct.py
   trunk/scipy/sparse/coo.py
   trunk/scipy/sparse/csc.py
   trunk/scipy/sparse/csr.py
   trunk/scipy/sparse/dia.py
   trunk/scipy/sparse/dok.py
   trunk/scipy/sparse/linalg/dsolve/tests/test_linsolve.py
   trunk/scipy/sparse/linalg/dsolve/umfpack/tests/test_umfpack.py
   trunk/scipy/sparse/linalg/dsolve/umfpack/umfpack.py
   trunk/scipy/sparse/linalg/eigen/arpack/speigs.py
   trunk/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py
   trunk/scipy/sparse/linalg/eigen/lobpcg/lobpcg.py
   trunk/scipy/sparse/linalg/eigen/lobpcg/tests/test_lobpcg.py
   trunk/scipy/sparse/linalg/isolve/iterative.py
   trunk/scipy/sparse/linalg/isolve/minres.py
   trunk/scipy/sparse/linalg/isolve/tests/test_iterative.py
   trunk/scipy/sparse/linalg/tests/test_interface.py
   trunk/scipy/sparse/spfuncs.py
   trunk/scipy/sparse/tests/test_base.py
   trunk/scipy/sparse/tests/test_extract.py
Log:
Removed unused imports.
Standardize NumPy import as "import numpy as np".


Modified: trunk/scipy/sparse/benchmarks/bench_sparse.py
===================================================================
--- trunk/scipy/sparse/benchmarks/bench_sparse.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/benchmarks/bench_sparse.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -8,8 +8,7 @@
 from numpy.testing import *
 
 from scipy import sparse
-from scipy.sparse import csc_matrix, csr_matrix, dok_matrix, \
-        coo_matrix, lil_matrix, dia_matrix, spdiags
+from scipy.sparse import csr_matrix, coo_matrix, dia_matrix
 
 
 def random_sparse(m,n,nnz_per_row):

Modified: trunk/scipy/sparse/bsr.py
===================================================================
--- trunk/scipy/sparse/bsr.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/bsr.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -7,16 +7,15 @@
 from warnings import warn
 
 from numpy import zeros, intc, array, asarray, arange, diff, tile, rank, \
-        prod, ravel, empty, matrix, asmatrix, empty_like, hstack
+                  ravel, empty, empty_like
 
 from data import _data_matrix
 from compressed import _cs_matrix
 from base import isspmatrix, _formats
-from sputils import isshape, getdtype, to_native, isscalarlike, isdense, \
-        upcast
+from sputils import isshape, getdtype, to_native, upcast
 import sparsetools
-from sparsetools import bsr_matvec, bsr_matvecs, csr_matmat_pass1, csr_matmat_pass2, \
-        bsr_matmat_pass2, bsr_transpose, bsr_sort_indices
+from sparsetools import bsr_matvec, bsr_matvecs, csr_matmat_pass1, \
+                        bsr_matmat_pass2, bsr_transpose, bsr_sort_indices
 
 class bsr_matrix(_cs_matrix):
     """Block Sparse Row matrix

Modified: trunk/scipy/sparse/compressed.py
===================================================================
--- trunk/scipy/sparse/compressed.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/compressed.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -5,10 +5,8 @@
 
 from warnings import warn
 
-import numpy
-from numpy import array, matrix, asarray, asmatrix, zeros, rank, intc, \
-        empty, hstack, isscalar, ndarray, shape, searchsorted, empty_like, \
-        where, concatenate, transpose, deprecate
+from numpy import array, asarray, zeros, rank, intc, empty, isscalar, \
+                  empty_like, where, concatenate, deprecate, diff, multiply
 
 from base import spmatrix, isspmatrix, SparseEfficiencyWarning
 from data import _data_matrix
@@ -166,7 +164,7 @@
                 if self.indices.min() < 0:
                     raise ValueError, "%s index values must be >= 0" % \
                             minor_name
-                if numpy.diff(self.indptr).min() < 0:
+                if diff(self.indptr).min() < 0:
                     raise ValueError,'index pointer values must form a " \
                                         "non-decreasing sequence'
 
@@ -260,7 +258,7 @@
             raise ValueError('inconsistent shapes')
 
         if isdense(other):
-            return numpy.multiply(self.todense(),other)
+            return multiply(self.todense(),other)
         else:
             other = self.__class__(other)
             return self._binopt(other,'_elmul_')
@@ -541,7 +539,7 @@
 
         index  = self.indices[indices] - start
         data   = self.data[indices]
-        indptr = numpy.array([0, len(indices)])
+        indptr = array([0, len(indices)])
         return self.__class__((data, index, indptr), shape=shape, \
                               dtype=self.dtype)
 

Modified: trunk/scipy/sparse/construct.py
===================================================================
--- trunk/scipy/sparse/construct.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/construct.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -15,16 +15,13 @@
 
 from sputils import upcast
 
-from csr import csr_matrix, isspmatrix_csr
-from csc import csc_matrix, isspmatrix_csc
+from csr import csr_matrix
+from csc import csc_matrix
 from bsr import bsr_matrix
 from coo import coo_matrix
-from dok import dok_matrix
 from lil import lil_matrix
 from dia import dia_matrix
-from base import isspmatrix
 
-
 def spdiags(data, diags, m, n, format=None):
     """Return a sparse matrix from diagonals.
 

Modified: trunk/scipy/sparse/coo.py
===================================================================
--- trunk/scipy/sparse/coo.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/coo.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -7,14 +7,13 @@
 from itertools import izip
 from warnings import warn
 
-from numpy import array, asarray, empty, intc, zeros, \
-        unique, searchsorted, atleast_2d, rank, deprecate, hstack
+from numpy import array, asarray, empty, intc, zeros, unique, searchsorted,\
+                  atleast_2d, rank, deprecate, hstack
 
-from sparsetools import coo_tocsr, coo_tocsc, coo_todense, coo_matvec
+from sparsetools import coo_tocsr, coo_todense, coo_matvec
 from base import isspmatrix
 from data import _data_matrix
 from sputils import upcast, to_native, isshape, getdtype
-from spfuncs import estimate_blocksize
 
 class coo_matrix(_data_matrix):
     """A sparse matrix in COOrdinate format.

Modified: trunk/scipy/sparse/csc.py
===================================================================
--- trunk/scipy/sparse/csc.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/csc.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -6,15 +6,9 @@
 
 from warnings import warn
 
-import numpy
-from numpy import array, matrix, asarray, asmatrix, zeros, rank, intc, \
-        empty, hstack, isscalar, ndarray, shape, searchsorted, where, \
-        concatenate, deprecate, transpose, ravel
-
-from base import spmatrix, isspmatrix
+from numpy import asarray, intc, empty, searchsorted, deprecate
 from sparsetools import csc_tocsr
-from sputils import upcast, to_native, isdense, isshape, getdtype, \
-        isscalarlike, isintlike
+from sputils import upcast, isintlike
 
 from compressed import _cs_matrix
 

Modified: trunk/scipy/sparse/csr.py
===================================================================
--- trunk/scipy/sparse/csr.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/csr.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -7,16 +7,12 @@
 
 from warnings import warn
 
-import numpy
-from numpy import array, matrix, asarray, asmatrix, zeros, rank, intc, \
-        empty, hstack, isscalar, ndarray, shape, searchsorted, where, \
-        concatenate, deprecate, arange, ones, ravel
+from numpy import asarray, asmatrix, zeros, intc, empty, isscalar, array, \
+                  searchsorted, where, deprecate, arange, ones, ravel
 
-from base import spmatrix, isspmatrix
 from sparsetools import csr_tocsc, csr_tobsr, csr_count_blocks, \
         get_csr_submatrix
-from sputils import upcast, to_native, isdense, isshape, getdtype, \
-        isscalarlike, isintlike
+from sputils import upcast, isintlike
 
 
 from compressed import _cs_matrix
@@ -319,7 +315,7 @@
 
         index  = self.indices[indices] - start
         data   = self.data[indices]
-        indptr = numpy.array([0, len(indices)])
+        indptr = array([0, len(indices)])
         return csr_matrix( (data, index, indptr), shape=(1, stop-start) )
 
     def _get_submatrix( self, row_slice, col_slice ):

Modified: trunk/scipy/sparse/dia.py
===================================================================
--- trunk/scipy/sparse/dia.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/dia.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -4,14 +4,12 @@
 
 __all__ = ['dia_matrix','isspmatrix_dia']
 
-from numpy import asarray, asmatrix, matrix, zeros, arange, array, \
-        empty_like, intc, atleast_1d, atleast_2d, add, multiply, \
-        unique, hstack
+from numpy import asarray, zeros, arange, array, intc, atleast_1d, \
+                  atleast_2d, unique, hstack
 
 from base import isspmatrix, _formats
 from data import _data_matrix
-from sputils import isscalarlike, isshape, upcast, getdtype, isdense
-
+from sputils import isshape, upcast, getdtype
 from sparsetools import dia_matvec
 
 class dia_matrix(_data_matrix):

Modified: trunk/scipy/sparse/dok.py
===================================================================
--- trunk/scipy/sparse/dok.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/dok.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -7,7 +7,7 @@
 import operator
 from itertools import izip
 
-from numpy import asarray, asmatrix, intc, isscalar, array, matrix
+from numpy import asarray, intc, isscalar
 
 from base import spmatrix,isspmatrix
 from sputils import isdense, getdtype, isshape, isintlike, isscalarlike

Modified: trunk/scipy/sparse/linalg/dsolve/tests/test_linsolve.py
===================================================================
--- trunk/scipy/sparse/linalg/dsolve/tests/test_linsolve.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/linalg/dsolve/tests/test_linsolve.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -4,7 +4,7 @@
 from numpy.testing import *
 
 from scipy.linalg import norm, inv
-from scipy.sparse import spdiags, csc_matrix, SparseEfficiencyWarning
+from scipy.sparse import spdiags, SparseEfficiencyWarning
 from scipy.sparse.linalg.dsolve import spsolve, use_solver
 
 warnings.simplefilter('ignore',SparseEfficiencyWarning)

Modified: trunk/scipy/sparse/linalg/dsolve/umfpack/tests/test_umfpack.py
===================================================================
--- trunk/scipy/sparse/linalg/dsolve/umfpack/tests/test_umfpack.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/linalg/dsolve/umfpack/tests/test_umfpack.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -6,14 +6,11 @@
 """
 
 import warnings
-
-from numpy import transpose, array, arange
-
 import random
 from numpy.testing import *
 
 from scipy import rand, matrix, diag, eye
-from scipy.sparse import csc_matrix, dok_matrix, spdiags, SparseEfficiencyWarning
+from scipy.sparse import csc_matrix, spdiags, SparseEfficiencyWarning
 from scipy.sparse.linalg import linsolve
 
 warnings.simplefilter('ignore',SparseEfficiencyWarning)
@@ -112,8 +109,8 @@
         self.a = spdiags([[1, 2, 3, 4, 5], [6, 5, 8, 9, 10]], [0, 1], 5, 5)
         #print "The sparse matrix (constructed from diagonals):"
         #print self.a
-        self.b = array([1, 2, 3, 4, 5])
-        self.b2 = array([5, 4, 3, 2, 1])
+        self.b = np.array([1, 2, 3, 4, 5])
+        self.b2 = np.array([5, 4, 3, 2, 1])
 
 
 

Modified: trunk/scipy/sparse/linalg/dsolve/umfpack/umfpack.py
===================================================================
--- trunk/scipy/sparse/linalg/dsolve/umfpack/umfpack.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/linalg/dsolve/umfpack/umfpack.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -9,7 +9,7 @@
 #from base import Struct, pause
 import numpy as np
 import scipy.sparse as sp
-import re, imp
+import re
 try: # Silence import error.
     import _umfpack as _um
 except:

Modified: trunk/scipy/sparse/linalg/eigen/arpack/speigs.py
===================================================================
--- trunk/scipy/sparse/linalg/eigen/arpack/speigs.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/linalg/eigen/arpack/speigs.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -1,6 +1,5 @@
 import numpy as np
 import _arpack
-import warnings
 
 __all___=['ArpackException','ARPACK_eigs', 'ARPACK_gen_eigs']
 

Modified: trunk/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py
===================================================================
--- trunk/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/linalg/eigen/arpack/tests/test_arpack.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -7,9 +7,8 @@
 
 from numpy.testing import *
 
-from numpy import array,real,imag,finfo,concatenate,\
-    column_stack,argsort,dot,round,conj,sort,random
-from scipy.sparse.linalg.eigen.arpack import eigen_symmetric,eigen
+from numpy import array, finfo, argsort, dot, round, conj, random
+from scipy.sparse.linalg.eigen.arpack import eigen_symmetric, eigen
 
 
 def assert_almost_equal_cc(actual,desired,decimal=7,err_msg='',verbose=True):

Modified: trunk/scipy/sparse/linalg/eigen/lobpcg/lobpcg.py
===================================================================
--- trunk/scipy/sparse/linalg/eigen/lobpcg/lobpcg.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/linalg/eigen/lobpcg/lobpcg.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -10,8 +10,6 @@
 Examples in tests directory contributed by Nils Wagner.
 """
 
-from warnings import warn
-
 import numpy as np
 import scipy as sp
 

Modified: trunk/scipy/sparse/linalg/eigen/lobpcg/tests/test_lobpcg.py
===================================================================
--- trunk/scipy/sparse/linalg/eigen/lobpcg/tests/test_lobpcg.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/linalg/eigen/lobpcg/tests/test_lobpcg.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -5,8 +5,7 @@
 import numpy
 from numpy.testing import *
 
-from scipy import array, arange, ones, sort, cos, pi, rand, \
-     set_printoptions, r_, diag, linalg
+from scipy import arange, ones, rand, set_printoptions, r_, diag, linalg
 from scipy.linalg import eig
 from scipy.sparse.linalg.eigen.lobpcg import lobpcg
 

Modified: trunk/scipy/sparse/linalg/isolve/iterative.py
===================================================================
--- trunk/scipy/sparse/linalg/isolve/iterative.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/linalg/isolve/iterative.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -13,7 +13,6 @@
 
 import _iterative
 import numpy as np
-import copy
 
 from scipy.sparse.linalg.interface import LinearOperator
 from utils import make_system

Modified: trunk/scipy/sparse/linalg/isolve/minres.py
===================================================================
--- trunk/scipy/sparse/linalg/isolve/minres.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/linalg/isolve/minres.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -1,4 +1,4 @@
-from numpy import ndarray, matrix, sqrt, inner, finfo, asarray, zeros
+from numpy import sqrt, inner, finfo, zeros
 from numpy.linalg import norm
 
 from utils import make_system
@@ -280,7 +280,6 @@
     from scipy import ones, arange
     from scipy.linalg import norm
     from scipy.sparse import spdiags
-    from scipy.sparse.linalg import cg
 
     n = 10
 

Modified: trunk/scipy/sparse/linalg/isolve/tests/test_iterative.py
===================================================================
--- trunk/scipy/sparse/linalg/isolve/tests/test_iterative.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/linalg/isolve/tests/test_iterative.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -4,8 +4,7 @@
 
 from numpy.testing import *
 
-from numpy import zeros, dot, diag, ones, arange, array, abs, max
-from numpy.random import rand
+from numpy import zeros, ones, arange, array, abs, max
 from scipy.linalg import norm
 from scipy.sparse import spdiags, csr_matrix
 

Modified: trunk/scipy/sparse/linalg/tests/test_interface.py
===================================================================
--- trunk/scipy/sparse/linalg/tests/test_interface.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/linalg/tests/test_interface.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -5,7 +5,7 @@
 from numpy.testing import *
 
 import numpy
-from numpy import array, matrix, ones, ravel
+from numpy import array, matrix, dtype
 from scipy.sparse import csr_matrix
 
 from scipy.sparse.linalg.interface import *
@@ -21,7 +21,7 @@
 
         class matlike:
             def __init__(self):
-                self.dtype = numpy.dtype('int')
+                self.dtype = dtype('int')
                 self.shape = (2,3)
             def matvec(self,x):
                 y = array([ 1*x[0] + 2*x[1] + 3*x[2],

Modified: trunk/scipy/sparse/spfuncs.py
===================================================================
--- trunk/scipy/sparse/spfuncs.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/spfuncs.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -3,15 +3,8 @@
 
 __all__ = ['count_blocks','estimate_blocksize']
 
-from numpy import empty, ravel
-
-from base import isspmatrix
 from csr import isspmatrix_csr, csr_matrix
 from csc import isspmatrix_csc
-from bsr import isspmatrix_bsr
-from sputils import upcast
-
-import sparsetools
 from sparsetools import csr_count_blocks
 
 def extract_diagonal(A):

Modified: trunk/scipy/sparse/tests/test_base.py
===================================================================
--- trunk/scipy/sparse/tests/test_base.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/tests/test_base.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -15,9 +15,10 @@
 
 import warnings
 
-import numpy
-from numpy import arange, zeros, array, dot, ones, matrix, asmatrix, \
-        asarray, vstack, ndarray, transpose, diag
+import numpy as np
+from numpy import arange, zeros, array, dot, matrix, asmatrix, asarray, \
+                  vstack, ndarray, transpose, diag, kron, inf, conjugate, \
+                  int8
 
 import random
 from numpy.testing import *
@@ -94,12 +95,12 @@
         mats.append( [[0,1],[0,2],[0,3]] )
         mats.append( [[0,0,1],[0,0,2],[0,3,0]] )
 
-        mats.append( numpy.kron(mats[0],[[1,2]]) )
-        mats.append( numpy.kron(mats[0],[[1],[2]]) )
-        mats.append( numpy.kron(mats[1],[[1,2],[3,4]]) )
-        mats.append( numpy.kron(mats[2],[[1,2],[3,4]]) )
-        mats.append( numpy.kron(mats[3],[[1,2],[3,4]]) )
-        mats.append( numpy.kron(mats[3],[[1,2,3,4]]) )
+        mats.append( kron(mats[0],[[1,2]]) )
+        mats.append( kron(mats[0],[[1],[2]]) )
+        mats.append( kron(mats[1],[[1,2],[3,4]]) )
+        mats.append( kron(mats[2],[[1,2],[3,4]]) )
+        mats.append( kron(mats[3],[[1,2],[3,4]]) )
+        mats.append( kron(mats[3],[[1,2,3,4]]) )
 
         for m in mats:
             assert_equal(self.spmatrix(m).diagonal(),diag(m))
@@ -257,7 +258,7 @@
         assert_array_equal((self.datsp / self.datsp).todense(),expected)
 
         denom = self.spmatrix(matrix([[1,0,0,4],[-1,0,0,0],[0,8,0,-5]],'d'))
-        res = matrix([[1,0,0,0.5],[-3,0,numpy.inf,0],[0,0.25,0,0]],'d')
+        res = matrix([[1,0,0,0.5],[-3,0,inf,0],[0,0.25,0,0]],'d')
         assert_array_equal((self.datsp / denom).todense(),res)
 
         # complex
@@ -421,7 +422,7 @@
     def test_tobsr(self):
         x = array([[1,0,2,0],[0,0,0,0],[0,0,4,5]])
         y = array([[0,1,2],[3,0,5]])
-        A = numpy.kron(x,y)
+        A = kron(x,y)
         Asp = self.spmatrix(A)
         for format in ['bsr']:
             fn = getattr(Asp, 'to' + format )
@@ -584,16 +585,16 @@
         Wagner for a 64-bit machine, 02 March 2005 (EJS)
         """
         n = 20
-        numpy.random.seed(0) #make tests repeatable
+        np.random.seed(0) #make tests repeatable
         A = zeros((n,n), dtype=complex)
-        x = numpy.random.rand(n)
-        y = numpy.random.rand(n-1)+1j*numpy.random.rand(n-1)
-        r = numpy.random.rand(n)
+        x = np.random.rand(n)
+        y = np.random.rand(n-1)+1j*np.random.rand(n-1)
+        r = np.random.rand(n)
         for i in range(len(x)):
             A[i,i] = x[i]
         for i in range(len(y)):
             A[i,i+1] = y[i]
-            A[i+1,i] = numpy.conjugate(y[i])
+            A[i+1,i] = conjugate(y[i])
         A = self.spmatrix(A)
         x = splu(A).solve(r)
         assert_almost_equal(A*x,r)
@@ -764,7 +765,7 @@
 
         # Check bug reported by Robert Cimrman:
         # http://thread.gmane.org/gmane.comp.python.scientific.devel/7986
-        s = slice(numpy.int8(2),numpy.int8(4),None)
+        s = slice(int8(2),int8(4),None)
         assert_equal(A[s,:].todense(), B[2:4,:])
         assert_equal(A[:,s].todense(), B[:,2:4])
 
@@ -920,9 +921,9 @@
 
     def test_constructor4(self):
         """using (data, ij) format"""
-        row  = numpy.array([2, 3, 1, 3, 0, 1, 3, 0, 2, 1, 2])
-        col  = numpy.array([0, 1, 0, 0, 1, 1, 2, 2, 2, 2, 1])
-        data = numpy.array([  6.,  10.,   3.,   9.,   1.,   4.,
+        row  = array([2, 3, 1, 3, 0, 1, 3, 0, 2, 1, 2])
+        col  = array([0, 1, 0, 0, 1, 1, 2, 2, 2, 2, 1])
+        data = array([  6.,  10.,   3.,   9.,   1.,   4.,
                               11.,   2.,   8.,   5.,   7.])
 
         ij = vstack((row,col))
@@ -994,9 +995,9 @@
 
     def test_constructor4(self):
         """using (data, ij) format"""
-        row  = numpy.array([2, 3, 1, 3, 0, 1, 3, 0, 2, 1, 2])
-        col  = numpy.array([0, 1, 0, 0, 1, 1, 2, 2, 2, 2, 1])
-        data = numpy.array([  6.,  10.,   3.,   9.,   1.,   4.,
+        row  = array([2, 3, 1, 3, 0, 1, 3, 0, 2, 1, 2])
+        col  = array([0, 1, 0, 0, 1, 1, 2, 2, 2, 2, 1])
+        data = array([  6.,  10.,   3.,   9.,   1.,   4.,
                               11.,   2.,   8.,   5.,   7.])
 
         ij = vstack((row,col))
@@ -1295,9 +1296,9 @@
     spmatrix = coo_matrix
     def test_constructor1(self):
         """unsorted triplet format"""
-        row  = numpy.array([2, 3, 1, 3, 0, 1, 3, 0, 2, 1, 2])
-        col  = numpy.array([0, 1, 0, 0, 1, 1, 2, 2, 2, 2, 1])
-        data = numpy.array([  6.,  10.,   3.,   9.,   1.,   4.,
+        row  = array([2, 3, 1, 3, 0, 1, 3, 0, 2, 1, 2])
+        col  = array([0, 1, 0, 0, 1, 1, 2, 2, 2, 2, 1])
+        data = array([  6.,  10.,   3.,   9.,   1.,   4.,
                               11.,   2.,   8.,   5.,   7.])
 
         coo = coo_matrix((data,(row,col)),(4,3))
@@ -1306,9 +1307,9 @@
 
     def test_constructor2(self):
         """unsorted triplet format with duplicates (which are summed)"""
-        row  = numpy.array([0,1,2,2,2,2,0,0,2,2])
-        col  = numpy.array([0,2,0,2,1,1,1,0,0,2])
-        data = numpy.array([2,9,-4,5,7,0,-1,2,1,-5])
+        row  = array([0,1,2,2,2,2,0,0,2,2])
+        col  = array([0,2,0,2,1,1,1,0,0,2])
+        data = array([2,9,-4,5,7,0,-1,2,1,-5])
         coo = coo_matrix((data,(row,col)),(3,3))
 
         mat = matrix([[4,-1,0],[0,0,9],[-3,7,0]])
@@ -1327,14 +1328,14 @@
 
     def test_constructor4(self):
         """from dense matrix"""
-        mat = numpy.array([[0,1,0,0],
+        mat = array([[0,1,0,0],
                            [7,0,3,0],
                            [0,4,0,0]])
         coo = coo_matrix(mat)
         assert_array_equal(coo.todense(),mat)
 
         #upgrade rank 1 arrays to row matrix
-        mat = numpy.array([0,1,0,0])
+        mat = array([0,1,0,0])
         coo = coo_matrix(mat)
         assert_array_equal(coo.todense(),mat.reshape(1,-1))
 
@@ -1366,7 +1367,7 @@
         data[3] = array([[ 0,  5, 10],
                          [15,  0, 25]])
 
-        A = numpy.kron( [[1,0,2,0],[0,0,0,0],[0,0,4,5]], [[0,1,2],[3,0,5]] )
+        A = kron( [[1,0,2,0],[0,0,0,0],[0,0,4,5]], [[0,1,2],[3,0,5]] )
         Asp = bsr_matrix((data,indices,indptr),shape=(6,12))
         assert_equal(Asp.todense(),A)
 
@@ -1385,7 +1386,7 @@
         assert_equal(bsr_matrix(A,blocksize=(2,2)).todense(),A)
         assert_equal(bsr_matrix(A,blocksize=(2,3)).todense(),A)
 
-        A = numpy.kron( [[1,0,2,0],[0,0,0,0],[0,0,4,5]], [[0,1,2],[3,0,5]] )
+        A = kron( [[1,0,2,0],[0,0,0,0],[0,0,4,5]], [[0,1,2],[3,0,5]] )
         assert_equal(bsr_matrix(A).todense(),A)
         assert_equal(bsr_matrix(A,shape=(6,12)).todense(),A)
         assert_equal(bsr_matrix(A,blocksize=(1,1)).todense(),A)
@@ -1395,11 +1396,11 @@
         assert_equal(bsr_matrix(A,blocksize=(3,12)).todense(),A)
         assert_equal(bsr_matrix(A,blocksize=(6,12)).todense(),A)
 
-        A = numpy.kron( [[1,0,2,0],[0,1,0,0],[0,0,0,0]], [[0,1,2],[3,0,5]] )
+        A = kron( [[1,0,2,0],[0,1,0,0],[0,0,0,0]], [[0,1,2],[3,0,5]] )
         assert_equal(bsr_matrix(A,blocksize=(2,3)).todense(),A)
 
     def test_eliminate_zeros(self):
-        data = numpy.kron([1, 0, 0, 0, 2, 0, 3, 0], [[1,1],[1,1]]).T
+        data = kron([1, 0, 0, 0, 2, 0, 3, 0], [[1,1],[1,1]]).T
         data = data.reshape(-1,2,2)
         indices = array( [1, 2, 3, 4, 5, 6, 7, 8] )
         indptr  = array( [0, 3, 8] )

Modified: trunk/scipy/sparse/tests/test_extract.py
===================================================================
--- trunk/scipy/sparse/tests/test_extract.py	2008-09-18 20:00:22 UTC (rev 4736)
+++ trunk/scipy/sparse/tests/test_extract.py	2008-09-18 21:20:05 UTC (rev 4737)
@@ -1,9 +1,6 @@
 """test sparse matrix construction functions"""
 
-import numpy
-from numpy import array, matrix
 from numpy.testing import *
-
 from scipy.sparse import csr_matrix
 
 import numpy as np



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