gpflux.experiment_support.plotting#

Module Contents#

plot_layer(X: gpflow.base.TensorType, layer_input: gpflow.base.TensorType, mean: List[gpflow.base.TensorType], cov: List[gpflow.base.TensorType], sample: List[gpflow.base.TensorType], idx: int | None, axes: Sequence[matplotlib.pyplot.Axes] | None = None) → None[source]#
Parameters:

  • X – original inputs to the DGP, shape [N, 1]

  • layer_input – inputs to this layer, shape [N, 1]

  • mean – mean of this layer’s output, shape [N, 1]

  • cov – covariance of this layer’s output, shape [1, N, N]

  • sample – samples from this layer’s output, shape [S, N, 1]

  • idx – the index of this layer (for labels)

  • axes – the sequence of 3 axes on which to plot