sampler.py 文件源码

def multiply_C(self, factor):
        """multiply ``self.C`` with ``factor`` updating internal states.

        ``factor`` can be a scalar, a vector or a matrix. The vector
        is used as outer product and multiplied element-wise, i.e.,
        ``multiply_C(diag(C)**-0.5)`` generates a correlation matrix.

        Details:
        """
        self._updateC()
        if np.isscalar(factor):
            self.C *= factor
            self.D *= factor**0.5
            try:
                self.inverse_root_C /= factor**0.5
            except AttributeError:
                pass
        elif len(np.asarray(factor).shape) == 1:
            self.C *= np.outer(factor, factor)
            self._decompose_C()
        elif len(factor.shape) == 2:
            self.C *= factor
            self._decompose_C()
        else:
            raise ValueError(str(factor))
        # raise NotImplementedError('never tested')