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MilesCranmer
commited on
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•
e274713
1
Parent(s):
ec8124e
Fix test for PySRRegressor
Browse files- pysr/sr.py +1 -1
- test/test.py +7 -16
pysr/sr.py
CHANGED
@@ -914,7 +914,7 @@ class PySRRegressor(BaseEstimator, RegressorMixin):
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y = np.stack(
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[
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_denoise(X, y[:, i], Xresampled=Xresampled)[1]
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-
for i in range(nout)
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],
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axis=1,
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)
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y = np.stack(
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[
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_denoise(X, y[:, i], Xresampled=Xresampled)[1]
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+
for i in range(self.nout)
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],
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axis=1,
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)
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test/test.py
CHANGED
@@ -91,7 +91,7 @@ class TestPipeline(unittest.TestCase):
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self.assertTrue("None" not in regressor.__repr__())
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self.assertTrue(">>>>" in regressor.__repr__())
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-
self.assertLessEqual(regressor.equations.iloc[-1]["
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np.testing.assert_almost_equal(regressor.predict(X), y, decimal=1)
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# Tweak model selection:
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@@ -181,18 +181,17 @@ class TestBest(unittest.TestCase):
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"equation_file.csv.bkup", sep="|"
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)
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self.
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"equation_file.csv",
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n_features=2,
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variables_names="x0 x1".split(" "),
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extra_sympy_mappings={},
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output_jax_format=False,
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multioutput=False,
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nout=1,
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)
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-
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self.model
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self.
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def test_best(self):
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self.assertEqual(self.model.sympy(), sympy.cos(sympy.Symbol("x0")) ** 2)
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@@ -232,12 +231,4 @@ class TestFeatureSelection(unittest.TestCase):
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self.assertEqual(set(selected_var_names), set("x2 x3".split(" ")))
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np.testing.assert_array_equal(
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np.sort(selected_X, axis=1), np.sort(X[:, [2, 3]], axis=1)
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-
)
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-
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-
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-
class TestHelperFunctions(unittest.TestCase):
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@patch("builtins.input", side_effect=["y", "n"])
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def test_yesno(self, mock_input):
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# Assert that the yes/no function correctly deals with y/n
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self.assertEqual(_yesno("Test"), True)
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self.assertEqual(_yesno("Test"), False)
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self.assertTrue("None" not in regressor.__repr__())
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self.assertTrue(">>>>" in regressor.__repr__())
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+
self.assertLessEqual(regressor.equations.iloc[-1]["loss"], 1e-4)
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np.testing.assert_almost_equal(regressor.predict(X), y, decimal=1)
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# Tweak model selection:
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"equation_file.csv.bkup", sep="|"
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)
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+
self.model = PySRRegressor(
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+
equation_file="equation_file.csv",
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variables_names="x0 x1".split(" "),
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extra_sympy_mappings={},
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output_jax_format=False,
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multioutput=False,
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nout=1,
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)
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+
self.model.n_features = 2
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self.model.refresh()
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self.equations = self.model.equations
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def test_best(self):
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self.assertEqual(self.model.sympy(), sympy.cos(sympy.Symbol("x0")) ** 2)
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self.assertEqual(set(selected_var_names), set("x2 x3".split(" ")))
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np.testing.assert_array_equal(
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np.sort(selected_X, axis=1), np.sort(X[:, [2, 3]], axis=1)
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+
)
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