# -*- coding: iso-8859-1 -*-
-# Copyright (C) 2007-2013 CEA/DEN, EDF R&D
+# Copyright (C) 2007-2014 CEA/DEN, EDF R&D
#
# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License as published by the Free Software Foundation; either
-# version 2.1 of the License.
+# version 2.1 of the License, or (at your option) any later version.
#
# This library is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
def testGetCrudeCSRMatrix1(self):
""" testing CSR matrix output using numpy/scipy.
"""
- from scipy.sparse import diags
+ from scipy.sparse import spdiags #diags
import scipy
from numpy import array
arr=DataArrayDouble(3) ; arr.iota()
self.assertEqual(diff.getnnz(),0)
# IntegralGlobConstraint (division by sum of cols)
colSum=m.sum(axis=0)
- m_0=m*diags(array(1/colSum),[0])
+ # version 0.12.0 # m_0=m*diags(array(1/colSum),[0])
+ m_0=m*spdiags(array(1/colSum),[0],colSum.shape[1],colSum.shape[1])
del colSum
self.assertAlmostEqual(m_0[0,0],0.625,12)
self.assertAlmostEqual(m_0[1,0],0.25,12)
self.assertEqual(m_0.getnnz(),7)
# ConservativeVolumic (division by sum of rows)
rowSum=m.sum(axis=1)
- m_1=diags(array(1/rowSum.transpose()),[0])*m
+ # version 0.12.0 # m_1=diags(array(1/rowSum.transpose()),[0])*m
+ m_1=spdiags(array(1/rowSum.transpose()),[0],rowSum.shape[0],rowSum.shape[0])*m
del rowSum
self.assertAlmostEqual(m_1[0,0],1.,12)
self.assertAlmostEqual(m_1[1,0],0.4,12)