add 'LearnerND.plot_3D' and add an example to the docs

adaptive/learner/learnerND.py

@@ -10,7 +10,7 @@ import scipy.spatial
 
 from .base_learner import BaseLearner
 
-from ..notebook_integration import ensure_holoviews
+from ..notebook_integration import ensure_holoviews, ensure_plotly
 from .triangulation import (Triangulation, point_in_simplex,
                             circumsphere, simplex_volume_in_embedding)
 from ..utils import restore, cache_latest
@@ -585,6 +585,69 @@ class LearnerND(BaseLearner):
         else:
             raise ValueError("Only 1 or 2-dimensional plots can be generated.")
 
+    def plot_3D(self, with_triangulation=False):
+        """Plot the learner's data in 3D using plotly.
+
+        Parameters
+        ----------
+        with_triangulation : bool, default: False
+            Add the verticices to the plot.
+
+        Returns
+        -------
+        plot : plotly.offline.iplot object
+            The 3D plot of ``learner.data``.
+        """
+        plotly = ensure_plotly()
+
+        plots = []
+
+        vertices = self.tri.vertices
+        if with_triangulation:
+            Xe, Ye, Ze = [], [], []
+            for simplex in self.tri.simplices:
+                for s in itertools.combinations(simplex, 2):
+                    Xe += [vertices[i][0] for i in s] + [None]
+                    Ye += [vertices[i][1] for i in s] + [None]
+                    Ze += [vertices[i][2] for i in s] + [None]
+
+            plots.append(plotly.graph_objs.Scatter3d(
+                x=Xe, y=Ye, z=Ze, mode='lines',
+                line=dict(color='rgb(125,125,125)', width=1),
+                hoverinfo='none'
+            ))
+
+        Xn, Yn, Zn = zip(*vertices)
+        colors = [self.data[p] for p in self.tri.vertices]
+        marker = dict(symbol='circle', size=3, color=colors,
+            colorscale='Viridis',
+            line=dict(color='rgb(50,50,50)', width=0.5))
+
+        plots.append(plotly.graph_objs.Scatter3d(
+            x=Xn, y=Yn, z=Zn, mode='markers',
+            name='actors', marker=marker,
+            hoverinfo='text'
+        ))
+
+        axis = dict(
+            showbackground=False,
+            showline=False,
+            zeroline=False,
+            showgrid=False,
+            showticklabels=False,
+            title='',
+        )
+
+        layout = plotly.graph_objs.Layout(
+            showlegend=False,
+            scene=dict(xaxis=axis, yaxis=axis, zaxis=axis),
+            margin=dict(t=100),
+            hovermode='closest')
+
+        fig = plotly.graph_objs.Figure(data=plots, layout=layout)
+
+        return plotly.offline.iplot(fig)
+
     def _get_data(self):
         return self.data
 

docs/source/docs.rst

@@ -132,6 +132,23 @@ on the *Play* :fa:`play` button or move the sliders.
     plots = {n: plot(learner, n) for n in range(10, 10000, 200)}
     hv.HoloMap(plots, kdims=['npoints'])
 
+`adaptive.LearnerND`
+~~~~~~~~~~~~~~~~~~~~
+
+.. jupyter-execute::
+    :hide-code:
+
+    def sphere(xyz):
+        import numpy as np
+        x, y, z = xyz
+        a = 0.4
+        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()
+
 see more in the :ref:`Tutorial Adaptive`.
 
 .. include:: ../../README.rst