def dt_comp(self,sampled_topics): """ Compute document-topic matrix from sampled_topics. """ samples = sampled_topics.shape[0] dt = np.zeros((self.D,self.K,samples)) for s in xrange(samples): dt[:,:,s] = samplers.dt_comp(self.docid, sampled_topics[s,:], self.N, self.K, self.D, self.alpha) return dt
def dt_comp(self, sampled_topics):
"""
Compute document-topic matrix from sampled_topics.
"""
samples = sampled_topics.shape[0]
dt = np.zeros((self.D, self.K, samples))
for s in xrange(samples):
dt[:, :, s] = samplers.dt_comp(self.docid, sampled_topics[s, :],
self.N, self.K, self.D, self.alpha)
return dt
def query(self,query_samples):
"""
Query docs with query_samples number of Gibbs sampling iterations.
"""
self.sampled_topics = np.zeros((self.samples,self.N), dtype = np.int)
for s in xrange(self.samples):
self.sampled_topics[s,:] = samplers.sampler_query(self.docid, self.tokens, self.topic_seed,
np.ascontiguousarray(self.tt[:,:,s], dtype=np.float),
self.N, self.K, self.D, self.alpha, query_samples)
print("Sample %d queried" % s)
self.dt = np.zeros((self.D,self.K,self.samples))
for s in xrange(self.samples):
self.dt[:,:,s] = samplers.dt_comp(self.docid,self.sampled_topics[s,:], self.N, self.K, self.D, self.alpha)
def query(self, query_samples):
"""
Query docs with query_samples number of Gibbs sampling iterations.
"""
self.sampled_topics = np.zeros((self.samples, self.N), dtype=np.int)
for s in xrange(self.samples):
self.sampled_topics[s, :] = samplers.sampler_query(
self.docid, self.tokens, self.topic_seed,
np.ascontiguousarray(self.tt[:, :, s], dtype=np.float), self.N,
self.K, self.D, self.alpha, query_samples)
print("Sample %d queried" % s)
self.dt = np.zeros((self.D, self.K, self.samples))
for s in xrange(self.samples):
self.dt[:, :,
s] = samplers.dt_comp(self.docid,
self.sampled_topics[s, :], self.N,
self.K, self.D, self.alpha)