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Add JMA HRIT readers for MTSAT-1R/2 #524

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merged 12 commits into from
Dec 7, 2018
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@sfinkens sfinkens commented Nov 29, 2018

  • Add method to compute geostationary earth mask

  • Add JMA HRIT readers for MTSAT-1R/2

    • Add YAML definitions for MTSAT-1R/2
    • Update YAML definition for Himawari-8
      • Rename hrit_jma.yaml -> hrit_ahi.yaml
      • Remove radiance datasets because it is not supported
      • Add counts datasets
    • Modify existing JMA HRIT reader:
      • Add support for half disk scans
      • Extract platform name from the file (needs to be improved for
        Himawari-9)
      • Mask space pixels
  • Tests added

  • Tests passed

  • Passes git diff origin/master -- "*py" | flake8 --diff

  • Fully documented

  • Add example notebook

@sfinkens sfinkens changed the title Feature mtsat Add JMA HRIT readers for MTSAT-1R/2 Nov 29, 2018
satpy/readers/hrit_jma.py Outdated Show resolved Hide resolved
satpy/readers/utils.py Outdated Show resolved Hide resolved
satpy/readers/utils.py Outdated Show resolved Hide resolved
satpy/tests/reader_tests/test_hrit_jma.py Outdated Show resolved Hide resolved
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coveralls commented Nov 30, 2018

Coverage Status

Coverage increased (+0.2%) to 74.813% when pulling 19a304c on sfinkens:feature-mtsat into ed9bd67 on pytroll:master.

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codecov bot commented Nov 30, 2018

Codecov Report

Merging #524 into master will increase coverage by 0.19%.
The diff coverage is 99.37%.

Impacted file tree graph

@@            Coverage Diff             @@
##           master     #524      +/-   ##
==========================================
+ Coverage   74.62%   74.81%   +0.19%     
==========================================
  Files         136      136              
  Lines       18342    18482     +140     
==========================================
+ Hits        13687    13827     +140     
  Misses       4655     4655
Impacted Files Coverage Δ
satpy/tests/reader_tests/test_hrit_jma.py 96.58% <100%> (+6.1%) ⬆️
satpy/readers/utils.py 71.11% <100%> (+2.43%) ⬆️
satpy/tests/reader_tests/test_utils.py 75.89% <100%> (+4.01%) ⬆️
satpy/readers/hrit_jma.py 98.43% <97.95%> (+0.76%) ⬆️

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@sfinkens
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sfinkens commented Dec 3, 2018

@djhoese Ready to merge as far as I'm concerned. Do you know what's wrong with the AppVeyor build?

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sfinkens commented Dec 3, 2018

Ah no, we wanted to wait for JMA's feedback regarding Himawari-9

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LGTM

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djhoese commented Dec 3, 2018

@sfinkens Yes, I do. I actually spent my weekend trying to figure out what to do with the appveyor tests. You can see the results in this issue and the ones linked to it: conda-forge/gdal-feedstock#241

Bottom line, we have to wait for a new build of gdal and possibly the geotiff library before things will start working. Hopefully if some of the core conda-forge folks have time today we'll see new builds today or tomorrow (USA/Brazil time zones).

Also keep in mind based on #527 that these reader names will likely change in before the SatPy 0.11 release. If this is a problem let's discuss it on slack and find a reasonable solution.

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mraspaud commented Dec 3, 2018

so it will become ahi_hrit and mtsat_imager_hrit, right ?

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djhoese commented Dec 3, 2018

I think mtsat2_imager_hrit and jami_hrit by the current sensor configuration I see in those files. See my most recent complications on the naming issue. Not sure how I feel about sensors that require separates or what to do when the sensor doesn't have a unique name like "imager" (old GOES also have "imager").

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sfinkens commented Dec 3, 2018

Since underscores separate the fields I would prefer mtsat-imager_hrit

- Add YAML definitions for MTSAT-1R/2
- Update YAML definition for Himawari-8
    - Rename hrit_jma.yaml -> hrit_ahi.yaml
    - Remove radiance datasets because it is not supported
    - Add counts datasets
- Modify existing JMA HRIT reader:
    - Add support for half disk scans
    - Extract platform name from the file (needs to be improved for
      Himawari-9)
    - Mask space pixels
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sfinkens commented Dec 7, 2018

Regarding the TODOs in the code: I will check that as soon as I have feedback from JMA and have the whole dataset.

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5 participants