import pylab
import matplotlib
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
#from isomapReduction import *
from diffusemapReduction import *
import pickle
plt.close('all')
folder = ''
graph_dist = np.genfromtxt('Hausdoff_dist_rot.txt')
y, result = diffusemapReduction(graph_dist, 2.5)
time = range(len(y[:, 0]))
fig = plt.figure(6)
plt.plot(result['eigenvalues'])
plt.xlabel('n')
plt.ylabel('lambda')
plt.figure(1)
plt.scatter(-y[:, 0], -y[:, 1], c=range(len(y[:, 0])))
plt.xlabel('x1')
plt.ylabel('x2')
plt.colorbar()
fig = plt.figure(2)
ax = fig.add_subplot(111, projection='3d')
def diffusemapAnalyzer(data, random_seq, orderdata):
psi6 = orderdata[random_seq - 1, 4]
rg = orderdata[random_seq - 1, 3]
y, result = diffusemapReduction(data, 0.5)
fig = plt.figure(1)
ax = fig.add_subplot(111, projection='3d')
ax.scatter(y[:, 0],
y[:, 1],
np.ones(y[:, 0].shape),
c=rg,
cmap=plt.cm.Spectral)
ax.set_xlabel('x1')
ax.set_ylabel('x2')
ax.set_zlabel('x3')
fig = plt.figure(2)
ax = fig.add_subplot(111)
ax.scatter(y[:, 0], y[:, 1], c=rg, cmap=plt.cm.Spectral)
ax.set_xlabel('x1')
ax.set_ylabel('x2')
fig = plt.figure(3)
ax = fig.add_subplot(111)
ax.scatter(y[:, 0], rg)
ax.set_xlabel('x1')
ax.set_ylabel('rg')
fig = plt.figure(4)
ax = fig.add_subplot(111)
ax.scatter(y[:, 0], psi6)
ax.set_xlabel('x1')
ax.set_ylabel('psi6')
fig = plt.figure(6)
plt.plot(result['eigenvalues'])
plt.xlabel('n')
plt.ylabel('lambda')
fig = plt.figure(7)
ax = fig.add_subplot(111)
ax.scatter(y[:, 1], rg)
ax.set_xlabel('x2')
ax.set_ylabel('rg')
fig = plt.figure(8)
ax = fig.add_subplot(111)
ax.scatter(y[:, 1] + y[:, 0], psi6)
ax.set_xlabel('x2')
ax.set_ylabel('psi6')
fig = plt.figure(9)
ax = fig.add_subplot(111)
ax.scatter(y[:, 0], y[:, 1], c=psi6, cmap=plt.cm.Spectral)
ax.set_xlabel('x1')
ax.set_ylabel('x2')
fig = plt.figure(11)
ax = fig.add_subplot(111, projection='3d')
ax.scatter(y[:, 0], y[:, 1], y[:, 2], c=rg, cmap=plt.cm.Spectral)
ax.set_xlabel('x1')
ax.set_ylabel('x2')
ax.set_zlabel('x3')
fig = plt.figure(12)
ax = fig.add_subplot(111, projection='3d')
ax.scatter(y[:, 0], y[:, 1], y[:, 2], c=psi6, cmap=plt.cm.Spectral)
ax.set_xlabel('x1')
ax.set_ylabel('x2')
ax.set_zlabel('x3')
# plt.colorbar()
np.savetxt('rg_sample.txt', rg)
np.savetxt('psi6_sample.txt', psi6)
np.savetxt('embedding.txt', y)
np.savetxt('lambda.txt', result['eigenvalues'])
return result