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Probably a resampled scene with fill values, considering that those are dummy files and they don't cover germany.
Actual results
[DEBUG: 2021-06-30 16:55:20 : satpy.readers.yaml_reader] Reading ('/home/gholl/checkouts/satpy/satpy/etc/readers/abi_l1b.yaml', '/media/nas/o16091/00_MITARBEITER/HOLL/Arbeit/checkouts-perforce/dev_Accso_EBP/config/readers/abi_l1b.yaml')
[DEBUG: 2021-06-30 16:55:20 : satpy.readers.yaml_reader] Assigning to abi_l1b: ['/media/nas/x21308/scratch/prob-glm-abi/OR_ABI-L1b-RadF-M6C14_G16_s19000010000000_e19000010005000_c20403662359590.nc']
[DEBUG: 2021-06-30 16:55:21 : satpy.readers.yaml_reader] Reading ('/home/gholl/checkouts/satpy/satpy/etc/readers/glm_l2.yaml',)
[DEBUG: 2021-06-30 16:55:21 : satpy.readers.yaml_reader] Assigning to glm_l2: ['/media/nas/x21308/scratch/prob-glm-abi/OR_GLM-L2-GLMF-M3_G16_s19000010001000_e19000010002000_c20403662359590.nc', '/media/nas/x21308/scratch/prob-glm-abi/OR_GLM-L2-GLMF-M3_G16_s19000010000000_e19000010001000_c20403662359590.nc', '/media/nas/x21308/scratch/prob-glm-abi/OR_GLM-L2-GLMF-M3_G16_s19000010003000_e19000010004000_c20403662359590.nc', '/media/nas/x21308/scratch/prob-glm-abi/OR_GLM-L2-GLMF-M3_G16_s19000010002000_e19000010003000_c20403662359590.nc', '/media/nas/x21308/scratch/prob-glm-abi/OR_GLM-L2-GLMF-M3_G16_s19000010004000_e19000010005000_c20403662359590.nc']
[DEBUG: 2021-06-30 16:55:21 : satpy.composites.config_loader] Looking for composites config file glm.yaml
[DEBUG: 2021-06-30 16:55:21 : satpy.composites.config_loader] Looking for composites config file visir.yaml
[DEBUG: 2021-06-30 16:55:21 : satpy.composites.config_loader] Looking for composites config file abi.yaml
[DEBUG: 2021-06-30 16:55:21 : satpy.readers.glm_l2] Reading in get_dataset flash_extent_density.
[DEBUG: 2021-06-30 16:55:21 : satpy.readers.glm_l2] Reading in get_dataset flash_extent_density.
[DEBUG: 2021-06-30 16:55:21 : satpy.readers.glm_l2] Reading in get_dataset flash_extent_density.
[DEBUG: 2021-06-30 16:55:21 : satpy.readers.glm_l2] Reading in get_dataset flash_extent_density.
[DEBUG: 2021-06-30 16:55:21 : satpy.readers.glm_l2] Reading in get_dataset flash_extent_density.
/data/gholl/miniconda3/envs/py39/lib/python3.9/site-packages/pyproj/crs/crs.py:1216: UserWarning: You will likely lose important projection information when converting to a PROJ string from another format. See: https://proj.org/faq.html#what-is-the-best-format-for-describing-coordinate-reference-systems
return self._crs.to_proj4(version=version)
[DEBUG: 2021-06-30 16:55:21 : satpy.scene] Resampling DataID(name='flash_extent_density', resolution=2000, modifiers=())
[INFO: 2021-06-30 16:55:21 : satpy.scene] Not reducing data before resampling.
[DEBUG: 2021-06-30 16:55:21 : satpy.resample] Initializing bucket resampler.
/data/gholl/miniconda3/envs/py39/lib/python3.9/site-packages/pyproj/crs/crs.py:1216: UserWarning: You will likely lose important projection information when converting to a PROJ string from another format. See: https://proj.org/faq.html#what-is-the-best-format-for-describing-coordinate-reference-systems
return self._crs.to_proj4(version=version)
[INFO: 2021-06-30 16:55:21 : pyresample.bucket] Determine bucket resampling indices
/home/gholl/checkouts/pyresample/pyresample/bucket/__init__.py:129: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
x_idxs = da.floor((proj_x - adef.area_extent[0]) / x_res).astype(np.int)
/home/gholl/checkouts/pyresample/pyresample/bucket/__init__.py:130: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
y_idxs = da.floor((adef.area_extent[3] - proj_y) / y_res).astype(np.int)
[DEBUG: 2021-06-30 16:55:21 : satpy.resample] Resampling DataID(name='flash_extent_density', resolution=2000, modifiers=())
Traceback (most recent call last):
File "/home/gholl/checkouts/protocode/mwe/bucket-sum-failure.py", line 12, in <module>
ls = sc.resample("germ", resampler="bucket_sum")
File "/home/gholl/checkouts/satpy/satpy/scene.py", line 812, in resample
self._resampled_scene(new_scn, destination, resampler=resampler,
File "/home/gholl/checkouts/satpy/satpy/scene.py", line 773, in _resampled_scene
res = resample_dataset(dataset, destination_area, **kwargs)
File "/home/gholl/checkouts/satpy/satpy/resample.py", line 1390, in resample_dataset
new_data = resample(source_area, dataset, destination_area, fill_value=fill_value, **kwargs)
File "/home/gholl/checkouts/satpy/satpy/resample.py", line 1353, in resample
res = resampler_instance.resample(data, **kwargs)
File "/home/gholl/checkouts/satpy/satpy/resample.py", line 1129, in resample
result = self.compute(data_arr, **kwargs)
File "/home/gholl/checkouts/satpy/satpy/resample.py", line 1238, in compute
res = self.resampler.get_sum(data, **kwargs)
TypeError: get_sum() got an unexpected keyword argument 'fill_value'
Environment Info:
Satpy Version: v0.29.0-58-gca8b6d9d
PyResample Version: v1.20.0
Additional context
Maybe I shouldn't be using the bucket resampler at all. I haven't tried this on real data yet as I'm still working on my unit tests. Maybe it's triggered by something strange in my data, but other resamplers work and it doesn't sound like an exception that should be happening.
The text was updated successfully, but these errors were encountered:
Describe the bug
The
bucket_sum
resampler fails with aTypeError
.To Reproduce
Expected behavior
Probably a resampled scene with fill values, considering that those are dummy files and they don't cover germany.
Actual results
Environment Info:
Additional context
Maybe I shouldn't be using the bucket resampler at all. I haven't tried this on real data yet as I'm still working on my unit tests. Maybe it's triggered by something strange in my data, but other resamplers work and it doesn't sound like an exception that should be happening.
The text was updated successfully, but these errors were encountered: