print np.shape(Nud[0]),np.shape(Nud[-1])
inpath = 'comment/nagi_comment (*).xml'
Nep = 26
Nwd,Nw,Nd,user_name = parseNwd(inpath,Nep)
print Nw,Nd,sum(Nw)
print np.shape(Nwd[0]),np.shape(Nwd[-1])
save_evi('nagi_evi')
load_evi('nagi_evi')
iteration = 200
Nz = 20
Nep =26
alpha = [10 for _ in range(Nep)]
beta = [1 for _ in range(Nep)]
Pz_d,Pu_z,Pw_z,Pd,Pz_u = plsa_multi([Nd,Nu,Nw,Nud,Nwd,Nep],[alpha,beta],Nz,iteration)
save_inf('nagi_inf')
load_inf('nagi_inf')
from pylab import *
print np.shape(Pu_z)
ax = plot(np.sum(Pu_z,2).T)
legend(ax,actor_name)
show()
Nz = 5 Nep =26 redo = 3 sigma = 6 weight = 1 mean1 = 6#6 mean2 = 20#20 love1 = np.zeros([7,7]) love2 = np.zeros([7,7]) for i in range(redo): alpha1 = [weight*mlab.normpdf(j,mean1,sigma) for j in range(Nep)] beta1 = [ mlab.normpdf(j,mean1,sigma) for j in range(Nep)] Pz_d,Pu_z,Pw_z,Pd,Pz_u = plsa_multi([Nd,Nu,Nw,Nud,Nwd,Nep],[alpha1,beta1],Nz,iteration) Puz = np.sum(Pz_u,2) love1 += Puz.dot(Puz.T) for i in range(redo): alpha2 = [weight*mlab.normpdf(j,mean2,sigma) for j in range(Nep)] beta2 = [ mlab.normpdf(j,mean2,sigma) for j in range(Nep)] Pz_d,Pu_z,Pw_z,Pd,Pz_u = plsa_multi([Nd,Nu,Nw,Nud,Nwd,Nep],[alpha2,beta2],Nz,iteration) Puz = np.sum(Pz_u,2) love2 += Puz.dot(Puz.T) plt.figure(1) plt.subplot(131) plt.pcolor(love1/redo)
