utils.py 文件源码

def gradient_logpdf(self, x, stepsize=None):
        """Return the gradient of log density of the joint prior at x.

        Parameters
        ----------
        x : float or np.ndarray
        stepsize : float or list
            Stepsize or stepsizes for the dimensions

        """
        x = np.asanyarray(x)
        ndim = x.ndim
        x = x.reshape((-1, self.dim))

        grads = np.zeros_like(x)

        for i in range(len(grads)):
            xi = x[i]
            grads[i] = numgrad(self.logpdf, xi, h=stepsize)

        grads[np.isinf(grads)] = 0
        grads[np.isnan(grads)] = 0

        if ndim == 0 or (ndim == 1 and self.dim > 1):
            grads = grads[0]
        return grads