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FIXED updated unit tests; integer data is no longer a requirement for…
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… transition solvers 🎉
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@dmnapolitano
dmnapolitano committed Mar 28, 2024
1 parent 4edb1fd commit 9beef48
Showing 1 changed file with 108 additions and 67 deletions.
175 changes: 108 additions & 67 deletions tests/test_transition_matrix_solver.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,7 @@
ATOL = 1e-04


def test_matrix_fit_predict():
def test_matrix_fit_predict_with_integers():
X = np.array(
[
[1, 2],
Expand All @@ -30,15 +30,56 @@ def test_matrix_fit_predict():
]
)

expected_betas = np.array([[9.99831808e-01, 1.68191521e-04], [1.49085896e-04, 9.99850914e-01]])
expected_yhat = np.array(
[
[1.00012998, 1.99987002],
[3.00009177, 3.99990823],
[5.00005356, 5.99994644],
[7.00001535, 7.99998465],
[8.99997714, 10.00002286],
[10.99993892, 12.00006108],
]
)

tms = TransitionMatrixSolver().fit(X, Y)
current_yhat = tms.predict(X)
np.testing.assert_allclose(expected_betas, tms.coefficients, rtol=RTOL, atol=ATOL)
np.testing.assert_allclose(expected_yhat, current_yhat, rtol=RTOL, atol=ATOL)


def test_matrix_fit_predict():
X = np.array(
[
[0.33333333, 0.66666667],
[0.42857143, 0.57142857],
[0.45454545, 0.54545455],
[0.46666667, 0.53333333],
[0.47368421, 0.52631579],
[0.47826087, 0.52173913],
]
)

Y = np.array(
[
[0.4, 0.6],
[0.44444444, 0.55555556],
[0.46153846, 0.53846154],
[0.47058824, 0.52941176],
[0.47619048, 0.52380952],
[0.48, 0.52],
]
)

expected_betas = np.array([[0.760428, 0.239572], [0.216642, 0.783358]])
expected_yhat = np.array(
[
[1.19371187, 1.80628813],
[3.14785177, 3.85214823],
[5.10199167, 5.89800833],
[7.05613156, 7.94386844],
[9.01027146, 9.98972854],
[10.96441136, 12.03558864],
[0.39790396, 0.60209604],
[0.44969311, 0.55030689],
[0.46381742, 0.53618258],
[0.47040877, 0.52959123],
[0.47422481, 0.52577519],
[0.47671354, 0.52328646],
]
)

Expand All @@ -51,23 +92,23 @@ def test_matrix_fit_predict():
def test_matrix_fit_predict_with_weights():
X = np.array(
[
[1, 2],
[3, 4],
[5, 6],
[7, 8],
[9, 10],
[11, 12],
[0.33333333, 0.66666667],
[0.42857143, 0.57142857],
[0.45454545, 0.54545455],
[0.46666667, 0.53333333],
[0.47368421, 0.52631579],
[0.47826087, 0.52173913],
]
)

Y = np.array(
[
[2, 3],
[4, 5],
[6, 7],
[8, 9],
[10, 11],
[12, 13],
[0.4, 0.6],
[0.44444444, 0.55555556],
[0.46153846, 0.53846154],
[0.47058824, 0.52941176],
[0.47619048, 0.52380952],
[0.48, 0.52],
]
)

Expand All @@ -82,23 +123,23 @@ def test_matrix_fit_predict_with_weights():
def test_matrix_fit_predict_not_strict():
X = np.array(
[
[1, 2],
[3, 4],
[5, 6],
[7, 8],
[9, 10],
[11, 12],
[0.33333333, 0.66666667],
[0.42857143, 0.57142857],
[0.45454545, 0.54545455],
[0.46666667, 0.53333333],
[0.47368421, 0.52631579],
[0.47826087, 0.52173913],
]
)

Y = np.array(
[
[2, 3],
[4, 5],
[6, 7],
[8, 9],
[10, 11],
[12, 13],
[0.4, 0.6],
[0.44444444, 0.55555556],
[0.46153846, 0.53846154],
[0.47058824, 0.52941176],
[0.47619048, 0.52380952],
[0.48, 0.52],
]
)

Expand All @@ -111,23 +152,23 @@ def test_matrix_fit_predict_not_strict():
def test_ridge_matrix_fit_predict():
X = np.array(
[
[1, 2],
[3, 4],
[5, 6],
[7, 8],
[9, 10],
[11, 12],
[0.33333333, 0.66666667],
[0.42857143, 0.57142857],
[0.45454545, 0.54545455],
[0.46666667, 0.53333333],
[0.47368421, 0.52631579],
[0.47826087, 0.52173913],
]
)

Y = np.array(
[
[2, 3],
[4, 5],
[6, 7],
[8, 9],
[10, 11],
[12, 13],
[0.4, 0.6],
[0.44444444, 0.55555556],
[0.46153846, 0.53846154],
[0.47058824, 0.52941176],
[0.47619048, 0.52380952],
[0.48, 0.52],
]
)

Expand Down Expand Up @@ -162,12 +203,12 @@ def test_matrix_fit_predict_pivoted():

expected_betas = np.array(
[
[0.68274443, 0.18437159, 0.06760119, 0.03363495, 0.0197597, 0.01188814],
[0.13541428, 0.48122828, 0.22128163, 0.0960816, 0.04540571, 0.02058852],
[0.04545795, 0.16052607, 0.38881747, 0.27665629, 0.12758087, 0.00096135],
[0.02289342, 0.06401812, 0.17970185, 0.28708764, 0.28820718, 0.15809178],
[0.01424566, 0.03468587, 0.08136858, 0.21299756, 0.26935036, 0.38735196],
[0.00995853, 0.02159863, 0.04337214, 0.1113991, 0.30326763, 0.51040397],
[9.99706e-01, 1.85000e-04, 5.00000e-05, 2.80000e-05, 1.90000e-05, 1.30000e-05],
[4.80000e-05, 9.99464e-01, 3.43000e-04, 8.10000e-05, 4.00000e-05, 2.40000e-05],
[1.70000e-05, 1.56000e-04, 9.99188e-01, 4.86000e-04, 1.06000e-04, 4.70000e-05],
[1.00000e-05, 4.60000e-05, 2.76000e-04, 9.98960e-01, 5.93000e-04, 1.14000e-04],
[7.00000e-06, 2.40000e-05, 7.40000e-05, 3.88000e-04, 9.98887e-01, 6.20000e-04],
[5.00000e-06, 1.50000e-05, 3.60000e-05, 9.70000e-05, 4.66000e-04, 9.99382e-01],
]
)

Expand All @@ -178,12 +219,12 @@ def test_matrix_fit_predict_pivoted():
def test_matrix_fit_predict_bad_dimensions():
X = np.array(
[
[1, 2],
[3, 4],
[5, 6],
[7, 8],
[9, 10],
[11, 12],
[0.33333333, 0.66666667],
[0.42857143, 0.57142857],
[0.45454545, 0.54545455],
[0.46666667, 0.53333333],
[0.47368421, 0.52631579],
[0.47826087, 0.52173913],
]
)

Expand All @@ -207,24 +248,24 @@ def test_matrix_fit_predict_pandas():

X = pandas.DataFrame(
[
[1, 2],
[3, 4],
[5, 6],
[7, 8],
[9, 10],
[11, 12],
[0.33333333, 0.66666667],
[0.42857143, 0.57142857],
[0.45454545, 0.54545455],
[0.46666667, 0.53333333],
[0.47368421, 0.52631579],
[0.47826087, 0.52173913],
],
columns=["x1", "x2"],
)

Y = pandas.DataFrame(
[
[2, 3],
[4, 5],
[6, 7],
[8, 9],
[10, 11],
[12, 13],
[0.4, 0.6],
[0.44444444, 0.55555556],
[0.46153846, 0.53846154],
[0.47058824, 0.52941176],
[0.47619048, 0.52380952],
[0.48, 0.52],
],
columns=["y1", "y2"],
)
Expand Down

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