March gen: add some testing and viz capabilities

This allows to visualize easily a generated configuration, thus allowing
testing

tools/test_marching_cubes_generator.py

@@ -0,0 +1,52 @@
+import gen_marching_cubes_conf as gen
+import matplotlib.pyplot as plt
+from mpl_toolkits.mplot3d import axes3d
+import random
+
+
+def split_pt_list(pts):
+    splitted = [[], [], []]
+    for point in pts:
+        for i in range(3):
+            splitted[i].append(point[i])
+    return splitted
+
+
+def pt_of_edge(edge):
+    def avg(val0, val1):
+        return (val0 + val1) / 2
+
+    vert0 = edge.vert[0]
+    vert1 = edge.vert[1]
+
+    return (avg(vert0[0], vert1[0]),
+            avg(vert0[1], vert1[1]),
+            avg(vert0[2], vert1[2]))
+
+
+def tri_repr(tri, subplt):
+    pts = [pt_of_edge(tri[i]) for i in range(3)]
+
+    x_val, y_val, z_val = split_pt_list(pts)
+    x_val = [val + random.random() / 10**5 for val in x_val]
+    y_val = [val + random.random() / 10**5 for val in y_val]
+
+    subplt.plot_trisurf(x_val, y_val, z_val)
+
+
+def display_case(tri_cube):
+    figure = plt.figure()
+    subplt = figure.add_subplot(111, projection='3d')
+
+    actives = split_pt_list(list(tri_cube.activated))
+    inactives = split_pt_list(list(tri_cube.non_activated))
+
+    subplt.scatter3D(actives[0], actives[1], actives[2],
+                     c='r', marker='o')
+    subplt.scatter3D(inactives[0], inactives[1], inactives[2],
+                     c='b', marker='.')
+
+    for triangle in tri_cube.triangles:
+        tri_repr(triangle, subplt)
+
+    plt.show()