import pickle

from earm.lopez_embedded import model

import pylab as plt

import numpy as np

import scipy.interpolate

cm = plt.cm.get_cmap('RdBu')

traces = pickle.load(open('test_traces2.p'))

params = [ i for i in traces['params']]

params = np.asarray(params)

params = params.reshape(np.shape(params)[0]*np.shape(params)[1],np.shape(params)[2])

#params = params[:100,:]

k_names = [p.name for p in model.parameters_rules()]

#fig = plt.figure(figsize=(10,10))

#for i in range(25):

# ax =fig.add_subplot(5,5,i)

# weights = np.ones_like(params[:,i])/float(len(params[:,i]))

# ax.hist(params[:,i],100,weights=weights)

#plt.title(k_names[i])

# ax.set_xticklabels([])

# ax.set_yticklabels([])

#fig.tight_layout()

#plt.show()

mat = np.zeros((len(model.parameters_rules()),len(model.parameters_rules())))

for i in range(105):

for j in range(i+1,105):

plt.plot(params[:,i],params[:,j],'.')

plt.savefig('p%s_vs_p%s.png'%(i,j))

plt.close()

cov = np.corrcoef(np.vstack((params[:,i],params[:,j])))

mat[i,j] = cov[0,1]

plt.imshow(mat+mat.T,interpolation='nearest',cmap=cm,

vmin=-1,vmax=1)

plt.colorbar()

plt.show()