Add a YAMLReader to pad segmented geo data

[mraspaud]

This PR adds a class that knows how to pad segmented geo data

• Closes Pad all geostationary L1 data to full disk area #970
• Tests added and test suite added to parent suite
• Tests passed
• Passes flake8 satpy
• Fully documented

[coveralls]

Coverage increased (+0.1%) to 86.992% when pulling 0831cd2 on mraspaud:feature-geo-padding into 071e34b on pytroll:master.

[codecov]

Codecov Report

Merging #977 into master will decrease coverage by 0.11%.
The diff coverage is 97.78%.

@@            Coverage Diff             @@
##           master     #977      +/-   ##
==========================================
- Coverage    87.1%   86.99%   -0.12%     
==========================================
  Files         181      181              
  Lines       27635    27752     +117     
==========================================
+ Hits        24072    24143      +71     
- Misses       3563     3609      +46

Impacted Files	Coverage Δ
satpy/tests/test_yaml_reader.py	99.06% <100%> (+0.54%)	⬆️
satpy/readers/yaml_reader.py	94.17% <94.69%> (-0.07%)	⬇️
satpy/tests/reader_tests/test_utils.py	79.69% <0%> (-18.15%)	⬇️
satpy/readers/acspo.py	86.25% <0%> (-7.96%)	⬇️
satpy/readers/netcdf_utils.py	94.02% <0%> (-5.98%)	⬇️
satpy/readers/seviri_l1b_native.py	67.24% <0%> (-4.41%)	⬇️
satpy/readers/utils.py	75.23% <0%> (-4.33%)	⬇️
satpy/readers/li_l2.py	23.07% <0%> (-2.79%)	⬇️
satpy/tests/reader_tests/test_netcdf_utils.py	93.24% <0%> (-1.44%)	⬇️
satpy/readers/caliop_l2_cloud.py	31.57% <0%> (-1.18%)	⬇️
... and 27 more

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[pnuu]

I think everything else works, but when the first segment is missing there's a crash. With MSG/SEVIRI HRIT data:
ValueError: conflicting sizes for dimension 'y': length 3248 on 'y' and length 3712 on 'acq_time'

[pnuu]

And when the first segment is missing from Himawari-8/AHI HRIT:
ValueError: conflicting sizes for dimension 'y': length 5500 on <this-array> and length 4950 on 'y'.

[pnuu]

The tests are failing because something in packages that Conda installs has changed.

I've tested the padding and found it working for the following data:

• SEVIRI HRIT via seviri_l1b_hrit reader - 0 deg, RSS and IOCD services
• Himawari-8 HRIT via ahi_hrit reader
• GOES-13/15 HRIT via goes-imager_hrit reader

Both saving directly as full disk data and resampling the data works, as long as even one segment is available.

[djhoese]

Very cool. I have a couple concerns about the naming. "Collection" seems like a very generic name for this. In the future I'd like to add a "tiled" reader, but the StackedAreaDefinition doesn't support this idea. This "Collection" reader only supports stacking segments, right? What do you think about a "Segmented" reader name or "Stacked"?

Also, this means that people always get a full disk sized array right? Is there a way users can disable this? Like what if they only provide the segments for the top half of the full disk? Could a keyword argument be added to the Reader?

[pnuu]

Segmented does sound better. And yes, it supports stacking and padding only GEO segments together.

Yeah, the data are always returned as full disk representations. I'll have a look at adding the kwarg, and how it would actually be used when creating the Scene. Is it something like scn = Scene(..., reader_kwargs={'pad_data': False})?

[djhoese]

Yeah I think that should work.

[pnuu]

OK, disabling is now implemented. It needs to be done at load time:

scn.load([10.8], pad_data=False)

Unfortunately resampling when segments are missing is broken also in master branch (discussing this on slack). With padding to full disk (the default behaviour with this PR) the result is as expected.

[mraspaud]

Why not use super and make a extra function ?

[pnuu]

Because:

1. it didn't need to be a method
2. @staticmethod would've caused other problems
3. I couldn't get it to work with super()

In short, this was the easiest and fastest way to get it to work 😁