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Update test_features.py
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Lines changed: 4 additions & 39 deletions

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deeptrack/tests/test_features.py

Lines changed: 4 additions & 39 deletions
Original file line numberDiff line numberDiff line change
@@ -2002,7 +2002,7 @@ def test_Slice_static_dynamic(self):
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self.assertTrue(np.array_equal(dinamic_output, expected_output))
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def test_Bind(self): # TODO
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def test_Bind(self):
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value = features.Value(
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value=lambda input_value: input_value,
@@ -2016,11 +2016,7 @@ def test_Bind(self): # TODO
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res = pipeline_with_small_input.update().resolve()
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self.assertEqual(res, 11)
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with self.assertWarns(DeprecationWarning):
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res = pipeline_with_small_input.update(input_value=10).resolve()
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self.assertEqual(res, 11)
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def test_Bind_gaussian_noise(self): # TODO
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def test_Bind_gaussian_noise(self):
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# Define the Gaussian noise feature and bind its properties
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gaussian_noise = Gaussian()
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bound_feature = features.Bind(gaussian_noise, mu=-5, sigma=2)
@@ -2035,43 +2031,12 @@ def test_Bind_gaussian_noise(self): # TODO
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output_mean = np.mean(output_image)
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output_std = np.std(output_image)
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# Assert that the mean and standard deviation are close to the bound values
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# Assert that the mean and standard deviation are close to the bound
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# values
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self.assertAlmostEqual(output_mean, -5, delta=0.2)
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self.assertAlmostEqual(output_std, 2, delta=0.2)
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def test_BindResolve(self): # TODO
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value = features.Value(
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value=lambda input_value: input_value,
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input_value=10,
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)
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value = features.Value(
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value=lambda input_value: input_value,
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input_value=10,
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)
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pipeline = (value + 10) / value
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pipeline_with_small_input = features.BindResolve(
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pipeline,
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input_value=1
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)
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pipeline_with_small_input = features.BindResolve(
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pipeline,
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input_value=1
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)
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res = pipeline.update().resolve()
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self.assertEqual(res, 2)
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res = pipeline_with_small_input.update().resolve()
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self.assertEqual(res, 11)
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with self.assertWarns(DeprecationWarning):
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res = pipeline_with_small_input.update(input_value=10).resolve()
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self.assertEqual(res, 11)
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def test_BindUpdate(self): # DEPRECATED
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value = features.Value(
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value=lambda input_value: input_value,

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