Added switch_dim parameter to ChangePoints kernel

This parameter allows to define the ChangePoint on one particular dimension of
the input space. All other dimensions are still available to the kernels being
switched, and can be selected via active_dims.

gpflow/kernels/changepoints.py

@@ -54,13 +54,16 @@ def __init__(
         kernels: List[Kernel],
         locations: List[float],
         steepness: Union[float, List[float]] = 1.0,
+        switch_dim: int = 0,
         name: Optional[str] = None,
     ):
         """
         :param kernels: list of kernels defining the different regimes
         :param locations: list of change-point locations in the 1d input space
         :param steepness: the steepness parameter(s) of the sigmoids, this can be
             common between them or decoupled
+        :param switch_dim: the (one) dimension of the input space along which
+            the change-points are defined
         """
         if len(kernels) != len(locations) + 1:
             raise ValueError(
@@ -76,6 +79,7 @@ def __init__(
 
         super().__init__(kernels, name=name)
 
+        self.switch_dim = switch_dim
         self.locations = Parameter(locations)
         self.steepness = Parameter(steepness, transform=positive())
 
@@ -119,4 +123,5 @@ def _sigmoids(self, X: tf.Tensor) -> tf.Tensor:
         locations = tf.sort(self.locations)  # ensure locations are ordered
         locations = tf.reshape(locations, (1, 1, -1))
         steepness = tf.reshape(self.steepness, (1, 1, -1))
-        return tf.sigmoid(steepness * (X[:, :, None] - locations))
+        Xslice = tf.reshape(X[:, self.switch_dim], (-1, 1, 1))
+        return tf.sigmoid(steepness * (Xslice - locations))