def testPseudoInverse(self): expectedPseudoInverse = np.array( [ [ 0.21264822, 0.20869565, 0.19683794, 0.1770751, 0.14940711, 0.11383399, 0.07035573, 0.01897233, -0.04031621, -0.10750988, ], [ -0.00395257, -0.00381388, -0.00339782, -0.00270439, -0.00173358, -0.0004854, 0.00104015, 0.00284308, 0.00492338, 0.00728105, ], ] ) linearModel = LinearModel(self.regressorList, self.regressorNames) self.assertTrue(np.allclose(linearModel.pseudoInverse(), expectedPseudoInverse, rtol=1.0e-6, atol=1.0e-08))
def testPseudoInverse(self): expectedPseudoInverse = np.array([[ 0.21264822, 0.20869565, 0.19683794, 0.1770751, 0.14940711, 0.11383399, 0.07035573, 0.01897233, -0.04031621, -0.10750988], [-0.00395257, -0.00381388, -0.00339782, -0.00270439, -0.00173358, -0.0004854, 0.00104015, 0.00284308, 0.00492338, 0.00728105]]) linearModel = LinearModel(self.regressorList, self.regressorNames) self.assertTrue(np.allclose(linearModel.pseudoInverse(), expectedPseudoInverse, rtol=1.0e-6, atol=1.e-08))