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
\[\nabla \log f(x) = \nabla \log \sum_{i=1}^n w_i f_i(x).\]- Parameters:
x (numpy.ndarray[n, 1]) – Input vector
- Returns:
The gradient of the (unnormalized) log_density
- Return type:
numpy.ndarray[n, 1]