<reponame>clazaro/sfepy
from __future__ import absolute_import
from sfepy.base.testing import TestCommon

class Test(TestCommon):

    @staticmethod
    def from_conf(conf, options):
        return Test(conf=conf, options=options)

    def test_compose_sparse(self):
        import numpy as nm
        import scipy.sparse as sps
        from sfepy.linalg import compose_sparse

        ok = True

        # basic
        ma = sps.csr_matrix([[1, 0], [0, 1]])
        mb = sps.coo_matrix([[1, 1]])
        mk = compose_sparse([[ma, mb.T], [mb, 0]])
        expected = nm.array([[1, 0, 1],
                             [0, 1, 1],
                             [1, 1, 0]])

        _ok = nm.alltrue(mk.toarray() == expected)
        self.report('basic: %s' % _ok)
        ok = ok and _ok

        # sizes and slices
        ma = sps.csr_matrix([[2, 3]])
        mb = sps.coo_matrix([[4, 5, 6]])

        mk = compose_sparse([[ma, mb]], col_sizes=[2, 3])
        expected = nm.array([[2, 3, 4, 5, 6]])

        _ok = nm.alltrue(mk.toarray() == expected)
        self.report('sizes: %s' % _ok)
        ok = ok and _ok

        i1 = slice(1, 3)
        i2 = slice(8, 11)
        mk = compose_sparse([[ma, mb]], col_sizes=[i1, i2])
        expected = nm.array([[0, 2, 3, 0, 0, 0, 0, 0, 4, 5, 6]])

        _ok = nm.alltrue(mk.toarray() == expected)
        self.report('slices: %s' % _ok)
        ok = ok and _ok

        # zero block sizes and slices
        mk = compose_sparse([[0, ma, 0, mb, 0]], col_sizes=[1, 2, 5, 3, 1])
        expected = nm.array([[0, 2, 3, 0, 0, 0, 0, 0, 4, 5, 6, 0]])

        _ok = nm.alltrue(mk.toarray() == expected)
        self.report('zero block sizes: %s' % _ok)
        ok = ok and _ok

        expected = nm.array([[0, 2, 3, 0, 4, 5, 6, 0, 0, 0, 0],
                             [0, 0, 0, 0, 0, 0, 0, 0, 4, 5, 6]])

        i0 = slice(0, 1)
        i1 = slice(1, 3)
        i2 = slice(4, 7)
        i3 = slice(8, 11)
        mk = compose_sparse([[0, ma, mb, 0],
                             [0, 0, 0, mb]], col_sizes=[i0, i1, i2, i3])

        _ok = nm.alltrue(mk.toarray() == expected)
        self.report('zero block slices: %s' % _ok)
        ok = ok and _ok

        return ok


from __future__ import absolute_import
from sfepy.base.testing import TestCommon

class Test(TestCommon):

    @staticmethod
    def from_conf(conf, options):
        return Test(conf=conf, options=options)

    def test_compose_sparse(self):
        import numpy as nm
        import scipy.sparse as sps
        from sfepy.linalg import compose_sparse

        ok = True

        # basic
        ma = sps.csr_matrix([[1, 0], [0, 1]])
        mb = sps.coo_matrix([[1, 1]])
        mk = compose_sparse([[ma, mb.T], [mb, 0]])
        expected = nm.array([[1, 0, 1],
                             [0, 1, 1],
                             [1, 1, 0]])

        _ok = nm.alltrue(mk.toarray() == expected)
        self.report('basic: %s' % _ok)
        ok = ok and _ok

        # sizes and slices
        ma = sps.csr_matrix([[2, 3]])
        mb = sps.coo_matrix([[4, 5, 6]])

        mk = compose_sparse([[ma, mb]], col_sizes=[2, 3])
        expected = nm.array([[2, 3, 4, 5, 6]])

        _ok = nm.alltrue(mk.toarray() == expected)
        self.report('sizes: %s' % _ok)
        ok = ok and _ok

        i1 = slice(1, 3)
        i2 = slice(8, 11)
        mk = compose_sparse([[ma, mb]], col_sizes=[i1, i2])
        expected = nm.array([[0, 2, 3, 0, 0, 0, 0, 0, 4, 5, 6]])

        _ok = nm.alltrue(mk.toarray() == expected)
        self.report('slices: %s' % _ok)
        ok = ok and _ok

        # zero block sizes and slices
        mk = compose_sparse([[0, ma, 0, mb, 0]], col_sizes=[1, 2, 5, 3, 1])
        expected = nm.array([[0, 2, 3, 0, 0, 0, 0, 0, 4, 5, 6, 0]])

        _ok = nm.alltrue(mk.toarray() == expected)
        self.report('zero block sizes: %s' % _ok)
        ok = ok and _ok

        expected = nm.array([[0, 2, 3, 0, 4, 5, 6, 0, 0, 0, 0],
                             [0, 0, 0, 0, 0, 0, 0, 0, 4, 5, 6]])

        i0 = slice(0, 1)
        i1 = slice(1, 3)
        i2 = slice(4, 7)
        i3 = slice(8, 11)
        mk = compose_sparse([[0, ma, mb, 0],
                             [0, 0, 0, mb]], col_sizes=[i0, i1, i2, i3])

        _ok = nm.alltrue(mk.toarray() == expected)
        self.report('zero block slices: %s' % _ok)
        ok = ok and _ok

        return ok
# basic # sizes and slices # zero block sizes and slices