Resolve "(LearnerND) add iso-surface plot feature"

Closes #112 (closed)

adaptive/learner/learnerND.py

@@ -600,7 +600,8 @@ class LearnerND(BaseLearner):
             db = abs(value_b - level)
             dab = da + db
 
-            new_pt = db / dab * np.array(vertex_a) + da / dab * np.array(vertex_b)
+            new_pt = (db / dab * np.array(vertex_a)
+                      + da / dab * np.array(vertex_b))
 
             new_index = len(vertices)
             vertices.append(new_pt)
@@ -633,22 +634,28 @@ class LearnerND(BaseLearner):
 
             raise ValueError(
                 f"Could not draw isosurface for level={level}, as"
-                " this value is not inside the function range. Please choose a level"
-                f" strictly inside interval ({r_min}, {r_max})"
+                " this value is not inside the function range. Please choose"
+                f" a level strictly inside interval ({r_min}, {r_max})"
             )
 
         return vertices, faces
 
     def plot_isosurface(self, level=0.0, hull_opacity=0.2):
-        """Plots the linearly interpolated iso-surface of the function, based on
-        the currently evaluated points. This is the 3d analog of an iso-line.
+        """Plots the linearly interpolated isosurface of the function,
+        based on the currently evaluated points. This is the 3D analog
+        of an isoline.
 
         Parameters
         ----------
-        level : float
-            the function value which you are interested in. Defaults to 0.0.
-        hull_opacity : float
-            the opacity of the hull of the domain. Defaults to 0.2
+        level : float, default 0.0
+            the function value which you are interested in.
+        hull_opacity : float, default 0.0
+            the opacity of the hull of the domain.
+
+        Returns
+        -------
+        plot : plotly.offline.iplot object
+            The plot object of the isosurface.
         """
         plotly = ensure_plotly()
 
@@ -656,7 +663,8 @@ class LearnerND(BaseLearner):
         x, y, z = zip(*vertices)
 
         fig = plotly.figure_factory.create_trisurf(
-            x=x, y=y, z=z, plot_edges=False, simplices=faces, title="Isosurface")
+            x=x, y=y, z=z, plot_edges=False,
+            simplices=faces, title="Isosurface")
 
         if hull_opacity < 1e-3:
             # Do not compute the hull_mesh.
@@ -669,8 +677,8 @@ class LearnerND(BaseLearner):
         plotly = ensure_plotly()
         hull = scipy.spatial.ConvexHull(self._bounds_points)
 
-        # Find the colors of each plane, giving triangles which are coplanar the
-        # same color, such that a square face has the same color.
+        # Find the colors of each plane, giving triangles which are coplanar
+        # the same color, such that a square face has the same color.
         color_dict = {}
 
         def _get_plane_color(simplex):
@@ -678,12 +686,14 @@ class LearnerND(BaseLearner):
             # If the volume of the two triangles combined is zero then they
             # belong to the same plane.
             for simplex_key, color in color_dict.items():
-                points = np.array([hull.points[i] for i in set(simplex_key + simplex)])
+                points = [hull.points[i] for i in set(simplex_key + simplex)]
+                points = np.array(points)
                 if np.linalg.matrix_rank(points[1:] - points[0]) < 3:
                     return color
                 if scipy.spatial.ConvexHull(points).volume < 1e-5:
                     return color
-            color_dict[simplex] = tuple(random.randint(0, 255) for _ in range(3))
+            color_dict[simplex] = tuple(random.randint(0, 255)
+                                        for _ in range(3))
             return color_dict[simplex]
 
         colors = [_get_plane_color(simplex) for simplex in hull.simplices]