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"""test sparse matrix construction functions"""
from numpy.testing import *
from scipy.sparse import csr_matrix
import numpy as np
from scipy.sparse.extract import *
class TestExtract(TestCase):
def setUp(self):
cases = []
cases.append( csr_matrix( [[1,2]] ) )
cases.append( csr_matrix( [[1,0]] ) )
cases.append( csr_matrix( [[0,0]] ) )
cases.append( csr_matrix( [[1],[2]] ) )
cases.append( csr_matrix( [[1],[0]] ) )
cases.append( csr_matrix( [[0],[0]] ) )
cases.append( csr_matrix( [[1,2],[3,4]] ) )
cases.append( csr_matrix( [[0,1],[0,0]] ) )
cases.append( csr_matrix( [[0,0],[1,0]] ) )
cases.append( csr_matrix( [[0,0],[0,0]] ) )
cases.append( csr_matrix( [[1,2,0,0,3],[4,5,0,6,7],[0,0,8,9,0]] ) )
cases.append( csr_matrix( [[1,2,0,0,3],[4,5,0,6,7],[0,0,8,9,0]] ).T )
self.cases = cases
def find(self):
for A in self.cases:
I,J,V = find(A)
assert_equal( A.toarray(), csr_matrix(((I,J),V), shape=A.shape) )
def test_tril(self):
for A in self.cases:
B = A.toarray()
for k in [-3,-2,-1,0,1,2,3]:
assert_equal( tril(A,k=k).toarray(), np.tril(B,k=k))
def test_triu(self):
for A in self.cases:
B = A.toarray()
for k in [-3,-2,-1,0,1,2,3]:
assert_equal( triu(A,k=k).toarray(), np.triu(B,k=k))
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