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import torch
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from autoemulate .experimental .emulators import GaussianProcessExact
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from autoemulate .experimental .transforms import (
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+ DiscreteFourierTransform ,
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PCATransform ,
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StandardizeTransform ,
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VAETransform ,
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(PCATransform (n_components = 2 ), (20 , 2 )),
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(VAETransform (latent_dim = 2 ), (20 , 2 )),
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(StandardizeTransform (), (20 , 5 )),
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+ (DiscreteFourierTransform (n_components = 2 ), (20 , 2 )),
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],
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)
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def test_transform_shapes (sample_data_y2d , transform , expected_shape ):
@@ -30,7 +32,12 @@ def test_transform_shapes(sample_data_y2d, transform, expected_shape):
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@pytest .mark .parametrize (
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("transform" ),
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- [PCATransform (n_components = 2 ), VAETransform (latent_dim = 2 ), StandardizeTransform ()],
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+ [
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+ DiscreteFourierTransform (n_components = 2 ),
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+ PCATransform (n_components = 2 ),
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+ VAETransform (latent_dim = 2 ),
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+ StandardizeTransform (),
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+ ],
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)
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def test_transform_inverse_for_gaussians (sample_data_y2d , transform ):
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x , y = sample_data_y2d
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