def test_3x3_matrix(self): mat = numpy.array([[1, 2, 0], [-2, 1, 2], [1, 3, 1]]) evector, evalue = principal_eigenvector( mat, maximum_iterations=None, max_error=1e-10 ) self.assertAlmostEqual(evalue, 3) assert_array_almost_equal(evector, numpy.dot(mat, evector) / evalue) assert_array_almost_equal(evector, _normalise(numpy.array([0.5, 0.5, 1])))
def test_4x4_matrix(self): mat = [[2, 0, 0, 0], [1, 2, 0, 0], [0, 1, 3, 0], [0, 0, 1, 3]] evector, evalue = principal_eigenvector( mat, maximum_iterations=None, max_error=1e-10 ) self.assertAlmostEqual(evalue, 3, places=3) assert_array_almost_equal(evector, numpy.dot(mat, evector) / evalue) assert_array_almost_equal(evector, _normalise([0, 0, 0, 1]), decimal=4)
def test_4x4_matrix(self): mat = numpy.array([[2, 0, 0, 0], [1, 2, 0, 0], [0, 1, 3, 0], [0, 0, 1, 3]]) evector, evalue = principal_eigenvector( mat, maximum_iterations=None, max_error=1e-10 ) self.assertAlmostEqual(evalue, 3, places=3) assert_array_almost_equal(evector, numpy.dot(mat, evector) / evalue) assert_array_almost_equal( evector, _normalise(numpy.array([0, 0, 0, 1])), decimal=4 )
def test_2x2_matrix(self): mat = numpy.array([[2, 1], [1, 2]]) evector, evalue = principal_eigenvector(mat) self.assertAlmostEqual(evalue, 3) assert_array_almost_equal(evector, numpy.dot(mat, evector) / evalue) assert_array_almost_equal(evector, _normalise(numpy.array([1, 1])))
def test_identity_matrices(self): for size in range(2, 6): mat = numpy.identity(size) evector, evalue = principal_eigenvector(mat) self.assertAlmostEqual(evalue, 1) assert_array_almost_equal(evector, _normalise(numpy.ones(size)))