Fix unnecessary Dask compute()s in NDVIHybridGreen compositor

[pnuu]

The NDVIHybridGreenCompositor was using da.where() on a DataArray to replace values outside limits causing unnecessary computations. This PR replaces these two calls with a DataArray.clip() and adds checks in the tests that there is only one computation and only when it is requested.

• Closes NDVI hybrid green correction triggers early dask computations #2619
• Tests adjusted

[codecov]

Codecov Report

Merging #2623 (dd2c879) into main (86c075a) will increase coverage by 0.00%.
The diff coverage is 100.00%.

@@           Coverage Diff           @@
##             main    #2623   +/-   ##
=======================================
  Coverage   95.18%   95.18%           
=======================================
  Files         354      354           
  Lines       51270    51280   +10     
=======================================
+ Hits        48803    48813   +10     
  Misses       2467     2467           

Flag	Coverage Δ
behaviourtests	4.24% <0.00%> (-0.01%)	⬇️
unittests	95.81% <100.00%> (+<0.01%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Files	Coverage Δ
satpy/composites/spectral.py	100.00% <100.00%> (ø)
satpy/tests/compositor_tests/test_spectral.py	100.00% <100.00%> (ø)

[strandgren]

Thanks @pnuu. Such a small change to make the code shorter, cleaner and much more efficient :D Nice addition to the tests as well!

[coveralls]

Pull Request Test Coverage Report for Build 6721469074

• 23 of 23 (100.0%) changed or added relevant lines in 2 files are covered.
• No unchanged relevant lines lost coverage.
• Overall coverage remained the same at 95.759%

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Totals
Change from base Build 6663415040:	0.0%
Covered Lines:	48933
Relevant Lines:	51100

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💛 - Coveralls

[djhoese]

This looks good to me. One other check you could add is seeing if the computed numpy array from .values or .data.compute() has the same dtype as the DataArray. You could force the input data to be 32-bit floats and make sure it is np.float32 in the output since we rarely want data to be upcast to 64-bit. If the DataArray and the numpy array have different dtypes that's usually a sign that a map_blocks is doing things against it's interface.

If that seems pointless here then feel free to merge.

[mraspaud]

Lgtm