Nonlinearity correction + datacube spec1d extractions + datacube fluxing improvements

[rcooke-ast]

This PR contains multiple updates (mostly in the context of KCWI/KCRM reductions).

Non-linearity correction
Based on commissioning data, I have calculated the non-linearity of KCWI (KCRM data are not currently available). I've also prepared a short document to describe the correction. See the following non-linearity report (pdf) for further details.

Datacube spec1d extractions
Introduced a new script that performs point source extractions from datacubes: pypeit_extract_datacube. This script produces spec1d files including boxcar + optimal extractions that can then be used for flux calibration or science analysis (if observing point sources).

Flux calibration
The flux calibration of datacubes has been moved to outside of the datacube generation. This allows the datacube generation to make use of the pypeit_sensfunc script. Note, there is a "bug" with the current approach to generating sensitivity functions. PypeIt only uses only one spec1d file (of a standard star) to generate the sensitivity function. The datacube module allows you to combine multiple standard star spec2d files into a single datacube. However, the extinction correction is performed on the extracted datacube - this means that the extinction correction cannot be performed on individual standard star spec2d files.

extended a test for datacube and fluxing (+ docs)
I've redeveloped a test that tests the entire datacube creation process + added new docs. There is an associated
dev-suite PR as well.

Part of this PR addresses Issue #1701.

Tests pass:

[kbwestfall]

@rcooke-ast Please check my conflict resolution in the following:

CONFLICT (content): Merge conflict in pypeit/core/flux_calib.py
CONFLICT (content): Merge conflict in pypeit/par/pypeitpar.py
CONFLICT (content): Merge conflict in pypeit/sensfunc.py

[rcooke-ast]

Tests pass...