luk036/n-sphere

import matplotlib.pyplot as plt
import matplotlib.tri as mtri
import numpy as np
# Luk ???
# from mpl_toolkits.mplot3d import Axes3D
from scipy.spatial import ConvexHull

from n_sphere.discrep_2 import discrep_2
from n_sphere.sphere import sphere


def average_g(triples):
    return np.mean([triple[2] for triple in triples])


def sample_spherical(npoints, ndim=3):
    vec = np.random.randn(ndim, npoints)
    vec /= np.linalg.norm(vec, axis=0)
    return vec.transpose()


def my_plot(Triples, ax):
    hull = ConvexHull(Triples)
    triangles = hull.simplices
    measure = discrep_2(triangles, Triples)
    print(measure)

    colors = np.array([
        average_g([Triples[idx] for idx in triangle]) for triangle in triangles
    ])

    X = Triples[:, 0]
    Y = Triples[:, 1]
    Z = Triples[:, 2]

    collec = ax.plot_trisurf(mtri.Triangulation(X, Y, triangles),
                             Z,
                             shade=False,
                             cmap=plt.get_cmap('RdYlBu'),
                             array=colors)
    collec.autoscale()


# Triples = np.array(list(zip(X, Y, Z)))
npoints = 600

fig = plt.figure()
ax1 = fig.add_subplot(121, projection='3d')
ax2 = fig.add_subplot(122, projection='3d')

Triples = np.array([p for p in sphere(npoints, [2, 3, 5])])
my_plot(Triples, ax1)
Triples = sample_spherical(npoints)
my_plot(Triples, ax2)
plt.show()

# plt.plot(points[:,0], points[:,1], 'o')
# plt.plot(points[hull.vertices,0], points[hull.vertices,1], 'r--', lw=2)
# plt.show()