copula.py 文件源码

def logpdf(self, samples):
        '''
        Calculates the log of the probability density function.

        Parameters
        ----------
        samples : array_like
            n-by-2 matrix of samples where n is the number of samples.

        Returns
        -------
        vals : ndarray
            Log of the probability density function evaluated at `samples`.
        '''
        samples = np.copy(np.asarray(samples))
        samples = self.__rotate_input(samples)
        inner = np.all(np.bitwise_and(samples > 0.0, samples < 1.0), axis=1)
        outer = np.invert(inner)
        vals = np.zeros(samples.shape[0])
        vals[inner] = self._logpdf(samples[inner, :])
        # Assign zero mass to border
        vals[outer] = -np.inf
        return vals