Apply priors on 1 and 2d histograms about corner.py HOT 3 OPEN

Can you explain what you think weights does differently? That's exactly what it was for!

from corner.py.

Indeed weights parameter of np.histogram or plt.hist is the way to apply a prior to the histogram. However from reading your code, the same weight/prior is applied to each parameter the same way.
e.g. for a 3 parameters triangle plot, the input data will be shape(N, 3). If I have different weights/priors for each parameter, I would like to have my weight data to be shape(N, 3). But for now the weights parameter must be shape(N).
Or maybe I just missed something too obvious!

from corner.py.

I'm trying to catch up on old issues here:

Each weight corresponds to a specific sample with different parameter values in each case. In your case, I think what you would want is for the weight to be the product of priors evaluated at the parameter values of that sample.

from corner.py.