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)