hopsy.Mixture.log_gradient#

Mixture.log_gradient(self, x)#

Computes the gradient of the logarithm of the weighted sum of the probability density functions of the model components

$$\mathrm{\nabla }\log f(x)=\mathrm{\nabla }\log \sum _{i=1}^n{w}_i{f}_i(x).$$

Parameters:

x (numpy.ndarray[n, 1]) – Input vector

Returns:

The gradient of the (unnormalized) log_density

Return type:

numpy.ndarray[n, 1]