def initialize(self, M, K, R):
self.M = M
self.K = K
self.R = R
for m in range(1, self.M + 1):
self.y_list.append(samplable.IntV(0))
self.y_combination.extend(utils.get_full_combination(self.M, self.K))
for i in range(1, len(self.y_combination)):
self.y_prob_list.append(samplable.RealV(0.0))
self.z = samplable.IntV(0)
for r in range(1, self.R + 1):
self.z_prob_list.append(samplable.RealV(0.0))
def initialize(self, M, K):
self.M = M
self.K = K
for m in range(1, self.M + 1):
self.y_list.append(samplable.IntV(0))
probs = numpy.ndarray(shape=(self.K + 1), dtype=samplable.RealV, order='C')
for i in range(1, self.K + 1):
probs[i] = samplable.RealV(1.0 / self.K)
self.y_prob_list.append(probs)
self.likelihood_list.append(samplable.RealV(0.0))
def initialize(self, M, K):
self.M = M
self.K = K
for m in range(1, self.M + 1):
self.y_list.append(samplable.IntV(0))
probs = numpy.ndarray(shape=(self.K + 1),
dtype=samplable.RealV,
order='C')
r = [numpy.random.random() for i in range(0, self.K)]
s = sum(r)
r = [i / s for i in r]
for i in range(1, self.K + 1):
probs[i] = samplable.RealV(r[i - 1])
self.y_prob_list.append(probs)