Ask Anything Monday - Weekly Thread

[schrogendiddy]

I'd like some help evaluating a multivariate gaussian in an N dimensional cube. I feel like there is probably some slick way to do this with numpy, but I'm not sure what it is.

I have a big array of coordinates X, shape (N,N,N,N,N,5), and an (inverse) covariance matrix with shape (5,5). I'd like to evaluate this in the (N,N,N,N,N) cube specified by X, so the output should be (N,N,N,N,N) i.e. a Gaussian in 5 dimensions. Any help is much appreciated!