hello !
I am working with grid maps, representing an environment in terms of 2D or 3D cells that store values and can be plotted to create a map of the area.

I have datasets containing grid maps of an area, with three 3D arrays (x, y, and z) of size 501x624x94 that store the coordinates. Additionally, I have a variable prob of the same size, which holds a value associated with each grid cell.

I am dealing with three different datasets, where the prob variable represents different types of values across the datasets. I would like to compare these datasets in terms of both visual and statistical analysis. Specifically, I am interested in:

Visual comparisons: For example, surface plots, heatmaps, or 3D plots to compare the prob values across the datasets.
Statistical comparisons: I’m considering metrics like variance, correlation, or mutual information to quantify differences. Are there other methods or graphs that could highlight the differences between these datasets?
What tools or techniques would you recommend for both visualizing and analyzing grid map data?