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if the plot is a warped gp, then it plots Y before warping
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@ -10,6 +10,7 @@ import numpy as np
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from base_plots import gpplot, x_frame1D, x_frame2D
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from ...models.gp_coregionalized_regression import GPCoregionalizedRegression
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from ...models.sparse_gp_coregionalized_regression import SparseGPCoregionalizedRegression
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from ...models.warped_gp import WarpedGP
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from scipy import sparse
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from ...core.parameterization.variational import VariationalPosterior
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@ -73,6 +74,10 @@ def plot_fit(model, plot_limits=None, which_data_rows='all',
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else:
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X = model.X
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Y = model.Y
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if isinstance(model, WarpedGP):
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Y = model.Y_untransformed
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if sparse.issparse(Y): Y = Y.todense().view(np.ndarray)
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if hasattr(model, 'Z'): Z = model.Z
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