Krige: Adapting to PyKrige

[MuellerSeb]

This PR updates the PyKrige interface example and replaces the pseudo_inv_type options (1, 2, 3) in all Kriging routines with more descriptive ones to be in line with the settings in PyKrige:

pseudo_inv_type : :class:`str` or :any:`callable`, optional
    Here you can select the algorithm to compute the pseudo-inverse matrix:

        * `"pinv"`: use `pinv` from `scipy` which uses `lstsq`
        * `"pinv2"`: use `pinv2` from `scipy` which uses `SVD`
        * `"pinvh"`: use `pinvh` from `scipy` which uses eigen-values

    If you want to use another routine to invert the kriging matrix,
    you can pass a callable which takes a matrix and returns the inverse.
    Default: `"pinv"`

See:

• Interface with GSTools PyKrige#124
• GSTools covariance model as variogram_model input PyKrige#125
• Use pseudo inverse to prevent singular matrices PyKrige#151
• Use pseudo inverse to prevent singular matrices PyKrige#151 (comment)

[MuellerSeb]

@LSchueler this is ready for review.

[LSchueler]

Apart from being consistent with PyKrige, this is much nicer than before! I even have the feeling, that we already discussed this once. 👍