Merge pull request #327 from python-adaptive/LearnerND-example

take out a cut from the 3D sphere, LearnerND example

Author: basnijholt

adaptive/learner/learnerND.py

@@ -909,7 +909,7 @@ def plot_slice(self, cut_mapping, n=None):
         else:
             raise ValueError("Only 1 or 2-dimensional plots can be generated.")
 
-    def plot_3D(self, with_triangulation=False):
+    def plot_3D(self, with_triangulation=False, return_fig=False):
         """Plot the learner's data in 3D using plotly.
 
         Does *not* work with the
@@ -919,6 +919,9 @@ def plot_3D(self, with_triangulation=False):
         ----------
         with_triangulation : bool, default: False
             Add the verticices to the plot.
+        return_fig : bool, default: False
+            Return the `plotly.graph_objs.Figure` object instead of showing
+            the rendered plot (default).
 
         Returns
         -------
@@ -989,7 +992,7 @@ def plot_3D(self, with_triangulation=False):
 
         fig = plotly.graph_objs.Figure(data=plots, layout=layout)
 
-        return plotly.offline.iplot(fig)
+        return fig if return_fig else plotly.offline.iplot(fig)
 
     def _get_iso(self, level=0.0, which="surface"):
         if which == "surface":

docs/source/docs.rst

@@ -147,9 +147,22 @@ on the *Play* :fa:`play` button or move the sliders.
         return np.exp(-(x**2 + y**2 + z**2 - 0.75**2)**2/a**4)
 
     learner = adaptive.LearnerND(sphere, bounds=[(-1, 1), (-1, 1), (-1, 1)])
-    adaptive.runner.simple(learner, lambda l: l.npoints == 3000)
-
-    learner.plot_3D()
+    adaptive.runner.simple(learner, lambda l: l.npoints == 5000)
+
+    fig = learner.plot_3D(return_fig=True)
+
+    # Remove a slice from the plot to show the inside of the sphere
+    scatter = fig.data[0]
+    coords_col = [
+        (x, y, z, color)
+        for x, y, z, color in zip(
+            scatter["x"], scatter["y"], scatter["z"], scatter.marker["color"]
+        )
+        if not (x > 0 and y > 0)
+    ]
+    scatter["x"], scatter["y"], scatter["z"], scatter.marker["color"] = zip(*coords_col)
+
+    fig
 
 see more in the :ref:`Tutorial Adaptive`.