minor bug spatial_skill default binning

[Hendrik1987]

https://github.com/DHI/fmskill/blob/686b146b776ec948dd44398ee736ca8df2aaa1a5/fmskill/compare.py#L611
Better: np.mean([np.min(x),np.max(x)])?

[jsmariegaard]

Could you explain what the problem is?

[Hendrik1987]

Currently, the default spatial bins will be with respect to the mean x and y of the available track data ('center of gravity'). For the global data for example, this results in default bins, which are not centered near x=0, but shifted to the west (less data for longitudes from 0 to 180 degrees than from -180 to 0 degrees). In the global example this is not visible as the bins are specifically defined.

As suggested above, I think it would be nice to instead use the mean of the extend of the data (center of bounding box of data).

Even nicer would be to use the center of the bounding box of the domain. However, the domain is not always available.