Add Mahalanobis similarity

[iiroseppa]

Mahalanobis distance

The idea:

• Mahalanobis "distance" or similarity is standard deviation extended to multiple variables
• Main idea of this script is to measure similarity of all locations in a given geotiff to a (small) group of known mineral occurences.
  • The similarity is measured compared to the averaged features of the mineral occurences, meaning that even the known mineral occurences do not get full similarity.

Inputs:

Geotiff with different geophysical measurements in each band

Known mineral occurences: current testing implementation takes csv that contains values sampled from the Geotiff. However this is just for alpha testing. Further revisions should just ask a shapefile, geopackage or similar that has the locations of the known mineral occurences. Then the geotiff values at these locations should be sampled. This reduces user work considerably

Outputs

printed: multivariate normality test results possible warnings 2 Geotiffs, that have the same geographical extent as the original geotiff

• Mahalanobis similarity in standard deviations. Because there are probably more than 2 variables, values over 2 are to be expected even for the known occurences.
• P-values. Users should be noted that p-values close to 1 mean high confidence in similarity, while values close to 0 mean dissimilarity. This can be confusing as usually low p-values are considered "good"

[iiroseppa]

A jupyter notebook prototype has been created for this, and I would like to create draft pull request for it. I'll probably need write permissions that I don't currently have. With those I could create a new branch where I could create a draft pull request . Please correct me if I have misunderstood something.

[nmaarnio]

I gave you write permissions now @iiroseppa , sorry for the delay.