copula.py 文件源码

def _logcdf(self, samples):
        if self.theta == 0:
            vals = np.sum(np.log(samples), axis=1)
        else:
            old_settings = np.seterr(divide='ignore')
            vals = np.log(-np.log1p(np.expm1(-self.theta * samples[:, 0])
                                    * np.expm1(-self.theta * samples[:, 1])
                                    / (np.expm1(-self.theta)))) \
                - np.log(self.theta)
            np.seterr(**old_settings)
        return vals