def calc_divergence(self, n, word_count, params):
if params['divergence'] == 'l2':
d = Util.l2dist_fast(self.regular_sum, self.model.weights_, n, word_count)
return d
elif params['divergence'] == 'kl':
d = Util.kl_div_fast(self.model.weights_, n, word_count)
return d
elif params['divergence'] == 'dispersion':
points = [self.model.means_[int(k)] for k,v in word_count.items() for i in range(0, v)]
d = Util.calc_dispersion(points)
return d
else:
print 'invalid divergence'
exit()
def calc_dispersion(self, word_count, params):
points = [self.str_to_tuple(k) for k,v in word_count.items() for i in range(0, v)]
d = Util.calc_dispersion(points)
return d
