Python param_to_array示例

示例#1

 def gamma_log_prob(self):
     loggamma = param_to_array(self.gamma).copy()
     loggamma[loggamma > -40] = -np.log1p(np.exp(-loggamma[loggamma > -40]))
     loggamma1 = -param_to_array(self.gamma).copy()
     loggamma1[loggamma1 > -40] = -np.log1p(
         np.exp(-loggamma1[loggamma1 > -40]))
     return loggamma, loggamma1

示例#2

 def gamma_probabilities(self):
     prob = np.zeros_like(param_to_array(self.gamma))
     prob[self.gamma > -710] = 1. / (1. +
                                     np.exp(-self.gamma[self.gamma > -710]))
     prob1 = -np.zeros_like(param_to_array(self.gamma))
     prob1[self.gamma < 710] = 1. / (1. +
                                     np.exp(self.gamma[self.gamma < 710]))
     return prob, prob1

示例#3

文件： variational.py 项目： Arthurkorn/GPy

 def gamma_log_prob(self):
     loggamma = param_to_array(self.gamma).copy()
     loggamma[loggamma>-40] = -np.log1p(np.exp(-loggamma[loggamma>-40]))
     loggamma1 = -param_to_array(self.gamma).copy()
     loggamma1[loggamma1>-40] = -np.log1p(np.exp(-loggamma1[loggamma1>-40]))
     return loggamma,loggamma1

示例#4

文件： variational.py 项目： Arthurkorn/GPy

 def gamma_probabilities(self):
     prob = np.zeros_like(param_to_array(self.gamma))
     prob[self.gamma>-710] = 1./(1.+np.exp(-self.gamma[self.gamma>-710]))
     prob1 = -np.zeros_like(param_to_array(self.gamma))
     prob1[self.gamma<710] = 1./(1.+np.exp(self.gamma[self.gamma<710]))
     return prob, prob1