Scaling factor calculation

[dshean]

In https://github.com/uw-cryo/DeepDEM/blob/main/notebooks/0d_Calculating_Scale_Factor.ipynb

    std_values = sum(map(return_sample_std, sampler), [])
            
    lower_percentile, upper_percentile = np.percentile(std_values,  5), np.percentile(std_values,  95)
    std_values = np.ma.masked_where((std_values < lower_percentile) & (std_values > upper_percentile), std_values)

The & logic doesn't make sense to me. I'm not sure this is actually doing anything. This should be or or should be specified for range between lower_percentile and upper_percentile.

            with rasterio.open(dsm_file) as ds:
                img = ds.read(1, window=rasterio.windows.from_bounds(minx, miny, maxx, maxy, transform=ds.transform)).flatten()
                img = np.ma.masked_where(img == ds.nodata, img)
                std_values.append(np.std(img))

See previously issue about opening directly as masked array using rasterio, rather than a separate step.
I haven't tested, but if img is a masked array, then you should be able to directly do img.std() here to computed std of unmasked values. I don't know if np.std will honor the masked array values, or if you need to explicitly use np.ma.std - and behavior may be different for numpy 1.X vs 2.X. I noticed environment.yml has numpy pinned at 1.26.4 (https://github.com/uw-cryo/DeepDEM/blob/main/environment.yml#L11), not entirely sure why.