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""" Test functions for linalg module using the matrix class."""
from __future__ import division, absolute_import, print_function
import numpy as np
from numpy.linalg.tests.test_linalg import (
LinalgCase, apply_tag, TestQR as _TestQR, LinalgTestCase,
_TestNorm2D, _TestNormDoubleBase, _TestNormSingleBase, _TestNormInt64Base,
SolveCases, InvCases, EigvalsCases, EigCases, SVDCases, CondCases,
PinvCases, DetCases, LstsqCases)
CASES = []
# square test cases
CASES += apply_tag('square', [
LinalgCase("0x0_matrix",
np.empty((0, 0), dtype=np.double).view(np.matrix),
np.empty((0, 1), dtype=np.double).view(np.matrix),
tags={'size-0'}),
LinalgCase("matrix_b_only",
np.array([[1., 2.], [3., 4.]]),
np.matrix([2., 1.]).T),
LinalgCase("matrix_a_and_b",
np.matrix([[1., 2.], [3., 4.]]),
np.matrix([2., 1.]).T),
])
# hermitian test-cases
CASES += apply_tag('hermitian', [
LinalgCase("hmatrix_a_and_b",
np.matrix([[1., 2.], [2., 1.]]),
None),
])
# No need to make generalized or strided cases for matrices.
class MatrixTestCase(LinalgTestCase):
TEST_CASES = CASES
class TestSolveMatrix(SolveCases, MatrixTestCase):
pass
class TestInvMatrix(InvCases, MatrixTestCase):
pass
class TestEigvalsMatrix(EigvalsCases, MatrixTestCase):
pass
class TestEigMatrix(EigCases, MatrixTestCase):
pass
class TestSVDMatrix(SVDCases, MatrixTestCase):
pass
class TestCondMatrix(CondCases, MatrixTestCase):
pass
class TestPinvMatrix(PinvCases, MatrixTestCase):
pass
class TestDetMatrix(DetCases, MatrixTestCase):
pass
class TestLstsqMatrix(LstsqCases, MatrixTestCase):
pass
class _TestNorm2DMatrix(_TestNorm2D):
array = np.matrix
class TestNormDoubleMatrix(_TestNorm2DMatrix, _TestNormDoubleBase):
pass
class TestNormSingleMatrix(_TestNorm2DMatrix, _TestNormSingleBase):
pass
class TestNormInt64Matrix(_TestNorm2DMatrix, _TestNormInt64Base):
pass
class TestQRMatrix(_TestQR):
array = np.matrix
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