def run_freq(self, Vf, Wf=None, Zf=None, Hf=None, niter=5):
self.freq_analyzer.V = Vf
if Wf is None or Zf is None or Hf is None:
initW, initZ, initH = self.freq_analyzer.initialize()
if Wf is None: Wf = initW
if Zf is None: Zf = initZ
if Hf is None: Hf = initH
for iter in xrange(niter):
logprob, WZH = self.freq_analyzer.do_estep(Wf, Zf, Hf)
logger.info('Iteration f%d: logprob = %f', iter, logprob)
Wf, Zf, Hf = self.freq_analyzer.do_mstep(iter)
plt.clf()
plt.plot(Wf[...,0])
plt.draw()
# Hf : (rank, F, rank*T)
# Hf_sum : (rank, F, T)
meta_Hf = self.sum_pieces(Hf)
meta_logprob, meta_WZH = self.meta_freq_analyzer.do_estep(
Wf, Zf, meta_Hf)
logger.info('Meta f%d: logprob = %f', iter, logprob)
meta_Wf, meta_Zf, meta_Hf = self.meta_freq_analyzer.do_mstep(0)
return Wf, Zf, Hf, meta_Hf
def run_time(self, Vt, Wt=None, Zt=None, Ht=None, niter=5):
self.time_analyzer.V = Vt
if Wt is None or Zt is None or Ht is None:
initW, initZ, initH = self.time_analyzer.initialize()
if Wt is None: Wt = initW
if Zt is None: Zt = initZ
if Ht is None: Ht = initH
for iter in xrange(niter):
logprob, WZH = self.time_analyzer.do_estep(Wt, Zt, Ht)
logger.info('Iteration t%d: logprob = %f', iter, logprob)
Wt, Zt, Ht = self.time_analyzer.do_mstep(iter)
assert Wt.ndim == 3
assert Zt.ndim == 1
assert Ht.ndim == 2
# Ht : (rank, rank*F*T)
# Ht_sum : (rank, F*T)
meta_Ht = self.sum_pieces(Ht)
Htt = meta_Ht.reshape(self.rank, self.f_steps, self.t_steps)
Hmax = np.max(Htt)
plt.clf()
plt.imshow(np.rollaxis(Htt[0:3]/Hmax*2, 0, 3), origin='lower', aspect='auto', interpolation='nearest')
plt.draw()
meta_logprob, meta_WZH = self.meta_time_analyzer.do_estep(Wt, Zt, meta_Ht)
logger.info('Meta t%d: logprob = %f', iter, logprob)
meta_Wt, meta_Zt, meta_Ht = self.meta_time_analyzer.do_mstep(0)
return Wt, Zt, Ht, meta_Ht
def plot(self, V, Wf, Wt, Z, H, curriter=-1):
rank = len(Z)
nrows = rank + 2
WZH = self.reconstruct(Wf, Wt, Z, H, circular=self.circular)
W = Basilica.w_product(Wf, Wt)
plottools.plotall([V, WZH] + [SIPLCA2.reconstruct(W[:,z,:], Z[z], H[z,:],
circular=self.circular)
for z in xrange(len(Z))],
title=['V (Iteration %d)' % curriter,
'Reconstruction'] +
['Basis %d reconstruction' % x
for x in xrange(len(Z))],
colorbar=False, grid=False, cmap=plt.cm.hot,
subplot=(nrows, 2), order='c', align='xy')
plottools.plotall([None] + [Z], subplot=(nrows, 2), clf=False,
plotfun=lambda x: plt.bar(np.arange(len(x)) - 0.4, x),
xticks=[[], range(rank)], grid=False,
colorbar=False, title='Z')
plots = [None] * (3*nrows + 2)
titles = plots + ['W%d' % x for x in range(rank)]
wxticks = [[]] * (3*nrows + rank + 1) + [range(0, W.shape[2], 10)]
plots.extend(W.transpose((1, 0, 2)))
plottools.plotall(plots, subplot=(nrows, 6), clf=False, order='c',
align='xy', cmap=plt.cm.hot, colorbar=False,
ylabel=r'$\parallel$', grid=False,
title=titles, yticks=[[]], xticks=wxticks)
plots = [None] * (2*nrows + 2)
titles=plots + ['H%d' % x for x in range(rank)]
if np.squeeze(H).ndim < 4:
plotH = np.squeeze(H)
else:
plotH = H.sum(2)
if rank == 1:
plotH = [plotH]
plots.extend(plotH)
plottools.plotall(plots, subplot=(nrows, 3), order='c', align='xy',
grid=False, clf=False, title=titles, yticks=[[]],
colorbar=False, cmap=plt.cm.hot, ylabel=r'$*$',
xticks=[[]]*(3*nrows-1) + [range(0, V.shape[1], 100)])
plt.draw()
