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))
