html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/5336#issuecomment-1485992930,https://api.github.com/repos/pydata/xarray/issues/5336,1485992930,IC_kwDOAMm_X85YknPi,8699967,2023-03-27T23:26:59Z,2023-03-27T23:26:59Z,CONTRIBUTOR,"I am not certain about my availability at the moment. If I get free time, I would be happy to do so. However, if someone else gets started on it first, that would be great as well.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,894788930
https://github.com/pydata/xarray/issues/7645#issuecomment-1476324526,https://api.github.com/repos/pydata/xarray/issues/7645,1476324526,IC_kwDOAMm_X85X_uyu,8699967,2023-03-20T14:21:06Z,2023-03-20T14:21:06Z,CONTRIBUTOR,"Thanks @Illviljan :+1:
> mypy should have caught this a while ago
Type hints are likely incomplete/inexact in some places in rioxarray code.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1630746106
https://github.com/pydata/xarray/pull/7000#issuecomment-1244548660,https://api.github.com/repos/pydata/xarray/issues/7000,1244548660,IC_kwDOAMm_X85KLk40,8699967,2022-09-12T21:51:15Z,2022-09-12T21:51:15Z,CONTRIBUTOR,"> We have other plans to eventually make pandas an optional import too
That makes not using a data frame make a lot of sense.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1363829843
https://github.com/pydata/xarray/pull/7000#issuecomment-1244517611,https://api.github.com/repos/pydata/xarray/issues/7000,1244517611,IC_kwDOAMm_X85KLdTr,8699967,2022-09-12T21:33:30Z,2022-09-12T21:33:30Z,CONTRIBUTOR,I think `show_engines` provides a simple user friendly interface that is valuable for users in it's current state.,"{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1363829843
https://github.com/pydata/xarray/issues/6577#issuecomment-1234745070,https://api.github.com/repos/pydata/xarray/issues/6577,1234745070,IC_kwDOAMm_X85JmLbu,8699967,2022-09-01T20:26:37Z,2022-09-01T20:26:37Z,CONTRIBUTOR,"Looks like something already exists:
```python
from xarray.backends.plugins import list_engines
```
It would be nice to add the `description` & `documentation` properties to `xarray.backends.common.BackendEntrypoint` that can be implemented by external libraries (and internally) and a more official `list_engines` function with the above metadata could be added.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1227144046
https://github.com/pydata/xarray/issues/2288#issuecomment-1205808926,https://api.github.com/repos/pydata/xarray/issues/2288,1205808926,IC_kwDOAMm_X85H3y8e,8699967,2022-08-04T21:56:28Z,2022-08-04T21:56:28Z,CONTRIBUTOR,That's nice @dcherian :+1: ,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,341331807
https://github.com/pydata/xarray/issues/4995#issuecomment-1110101560,https://api.github.com/repos/pydata/xarray/issues/4995,1110101560,IC_kwDOAMm_X85CKs44,8699967,2022-04-26T18:09:18Z,2022-04-26T18:12:14Z,CONTRIBUTOR,"Example using `nearest` & `tolerance` with `reindex` & `sel` when dims don't match based on the example in `sel`:
```python
import numpy
import xarray
da = xarray.DataArray(
numpy.arange(25).reshape(5, 5),
coords={""x"": numpy.arange(5), ""y"": numpy.arange(5)},
dims=(""x"", ""y""),
)
tgt_x = numpy.linspace(0, 4, num=5) + 0.5
tgt_y = numpy.linspace(0, 4, num=5) + 0.5
da = da.reindex(
x=tgt_x, y=tgt_y, method=""nearest"", tolerance=0.2, fill_value=numpy.nan
).sel(
x=xarray.DataArray(tgt_x, dims=""points""),
y=xarray.DataArray(tgt_y, dims=""points""),
)
```
Output:
```
array([nan, nan, nan, nan, nan])
Coordinates:
x (points) float64 0.5 1.5 2.5 3.5 4.5
y (points) float64 0.5 1.5 2.5 3.5 4.5
Dimensions without coordinates: points
```
Side note: I don't think it makes sense to add `fill_value` to `sel` as it would require adding new coordinates that didn't exist previously. Calling `reindex` first makes that more clear in my opinion.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,822320976
https://github.com/pydata/xarray/issues/6448#issuecomment-1098400102,https://api.github.com/repos/pydata/xarray/issues/6448,1098400102,IC_kwDOAMm_X85BeEFm,8699967,2022-04-13T19:21:59Z,2022-04-13T19:21:59Z,CONTRIBUTOR,"> GDAL doesn't actually need the CRS stored with the _CRS convention as documented in their ZARR driver specification?
GDAL may need to update the ZARR driver. The NetCDF driver does support CF. It would be good for them to be consistent.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1194993450
https://github.com/pydata/xarray/issues/6448#issuecomment-1098342334,https://api.github.com/repos/pydata/xarray/issues/6448,1098342334,IC_kwDOAMm_X85Bd1--,8699967,2022-04-13T18:11:21Z,2022-04-13T18:11:21Z,CONTRIBUTOR,"Top reasons for using CF over a CRS attribute:
- Supported by geospatial & netCDF software (GDAL/Esri/Unidata)
- Attributes are easily lost [ref](https://corteva.github.io/rioxarray/stable/getting_started/manage_information_loss.html)
- Encourage more usage of standard mechanisms of CRS storage","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1194993450
https://github.com/pydata/xarray/issues/6448#issuecomment-1098333054,https://api.github.com/repos/pydata/xarray/issues/6448,1098333054,IC_kwDOAMm_X85Bdzt-,8699967,2022-04-13T18:00:12Z,2022-04-13T18:00:12Z,CONTRIBUTOR,This document is also a useful reference for storing CRS in xarray: https://corteva.github.io/rioxarray/stable/getting_started/crs_management.html,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1194993450
https://github.com/pydata/xarray/issues/6448#issuecomment-1098331427,https://api.github.com/repos/pydata/xarray/issues/6448,1098331427,IC_kwDOAMm_X85BdzUj,8699967,2022-04-13T17:58:19Z,2022-04-13T17:58:19Z,CONTRIBUTOR,"> Instead, it recommends to use CF conventions for encoding CRS. This is more compatible with NetCDF, but won't be parsed correctly by GDAL.
GDAL does support the CF conventions for storing the CRS.
https://gdal.org/drivers/raster/netcdf.html#georeference
""The driver first tries to follow the CF-1 Convention from UNIDATA looking for the Metadata named โgrid_mappingโ.""","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1194993450
https://github.com/pydata/xarray/issues/6288#issuecomment-1069088984,https://api.github.com/repos/pydata/xarray/issues/6288,1069088984,IC_kwDOAMm_X84_uQDY,8699967,2022-03-16T12:46:15Z,2022-03-16T12:46:15Z,CONTRIBUTOR,"https://corteva.github.io/rioxarray/stable/getting_started/getting_started.html#xarray
Are you able to use `decode_coords=""all""` when opening?","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1143489702
https://github.com/pydata/xarray/pull/6350#issuecomment-1068278154,https://api.github.com/repos/pydata/xarray/issues/6350,1068278154,IC_kwDOAMm_X84_rKGK,8699967,2022-03-15T17:49:51Z,2022-03-15T17:49:51Z,CONTRIBUTOR,https://github.com/jupyter/nbconvert/releases/tag/6.4.3,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1166353506
https://github.com/pydata/xarray/pull/6024#issuecomment-1030701879,https://api.github.com/repos/pydata/xarray/issues/6024,1030701879,IC_kwDOAMm_X849b0M3,8699967,2022-02-05T21:29:03Z,2022-02-05T21:29:03Z,CONTRIBUTOR,"No worries. I will try to address the conflicts when I get a free moment. Though, I wouldn't complain if someone else with a sooner free moment finished this one off before I do :-).","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1062681040
https://github.com/pydata/xarray/pull/4140#issuecomment-985706928,https://api.github.com/repos/pydata/xarray/issues/4140,985706928,IC_kwDOAMm_X846wLGw,8699967,2021-12-03T17:40:18Z,2021-12-03T17:40:18Z,CONTRIBUTOR,Sounds like that may need changes in rioxarray. Mind opening up an issue: https://github.com/corteva/rioxarray/issues ?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,636451398
https://github.com/pydata/xarray/pull/6024#issuecomment-978097496,https://api.github.com/repos/pydata/xarray/issues/6024,978097496,IC_kwDOAMm_X846TJVY,8699967,2021-11-24T17:47:21Z,2021-11-24T17:47:21Z,CONTRIBUTOR,"> can we make it?
I am not seeing an option to do that: https://pre-commit.ci/","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1062681040
https://github.com/pydata/xarray/pull/6024#issuecomment-978093218,https://api.github.com/repos/pydata/xarray/issues/6024,978093218,IC_kwDOAMm_X846TISi,8699967,2021-11-24T17:41:22Z,2021-11-24T17:41:22Z,CONTRIBUTOR,"> Is mypy being run in the CI now?
Yes, it runs on the CI","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1062681040
https://github.com/pydata/xarray/pull/6024#issuecomment-978088422,https://api.github.com/repos/pydata/xarray/issues/6024,978088422,IC_kwDOAMm_X846THHm,8699967,2021-11-24T17:34:12Z,2021-11-24T17:34:12Z,CONTRIBUTOR,"> I didn't know we could pass --all like that.
I think it is equivalent to `--all-files`","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1062681040
https://github.com/pydata/xarray/pull/5959#issuecomment-969177424,https://api.github.com/repos/pydata/xarray/issues/5959,969177424,IC_kwDOAMm_X845xHlQ,8699967,2021-11-15T18:06:04Z,2021-11-15T18:06:04Z,CONTRIBUTOR,This works for rioxarray. Thanks :+1: ,"{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 1, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1048309254
https://github.com/pydata/xarray/issues/5944#issuecomment-963583761,https://api.github.com/repos/pydata/xarray/issues/5944,963583761,IC_kwDOAMm_X845bx8R,8699967,2021-11-08T21:19:08Z,2021-11-08T21:21:02Z,CONTRIBUTOR,"I see the same issue reported here: https://github.com/pydata/xarray/issues/5944#issuecomment-962958896
See: https://github.com/corteva/rioxarray/runs/4140632105 (Note: updated CI build link)","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1046454702
https://github.com/pydata/xarray/issues/5944#issuecomment-963281576,https://api.github.com/repos/pydata/xarray/issues/5944,963281576,IC_kwDOAMm_X845aoKo,8699967,2021-11-08T15:38:55Z,2021-11-08T15:38:55Z,CONTRIBUTOR,"When a fix is added for this, feel free to ping me to test the fix on `rioxarray`.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1046454702
https://github.com/pydata/xarray/pull/5808#issuecomment-932820224,https://api.github.com/repos/pydata/xarray/issues/5808,932820224,IC_kwDOAMm_X843mbUA,8699967,2021-10-02T21:03:39Z,2021-10-02T21:03:39Z,CONTRIBUTOR,Thanks for the review ๐,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1003587347
https://github.com/pydata/xarray/pull/5808#issuecomment-926981465,https://api.github.com/repos/pydata/xarray/issues/5808,926981465,IC_kwDOAMm_X843QJ1Z,8699967,2021-09-25T00:31:30Z,2021-09-25T00:31:30Z,CONTRIBUTOR,Updated this so it is deprecated in 0.19.1 and added an entry to `whats-new.rst`.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1003587347
https://github.com/pydata/xarray/pull/5808#issuecomment-924512348,https://api.github.com/repos/pydata/xarray/issues/5808,924512348,IC_kwDOAMm_X843GvBc,8699967,2021-09-22T01:39:37Z,2021-09-22T01:39:37Z,CONTRIBUTOR,Fix for doc build issues in #5805,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1003587347
https://github.com/pydata/xarray/issues/5782#issuecomment-924395904,https://api.github.com/repos/pydata/xarray/issues/5782,924395904,IC_kwDOAMm_X843GSmA,8699967,2021-09-21T21:24:03Z,2021-09-21T21:24:12Z,CONTRIBUTOR,"> xr.open_rasterio() is being used earlier in the pipeline
What issues do you have if you change to use `rioxarray.open_rasterio`?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,991857313
https://github.com/pydata/xarray/issues/5782#issuecomment-924395141,https://api.github.com/repos/pydata/xarray/issues/5782,924395141,IC_kwDOAMm_X843GSaF,8699967,2021-09-21T21:23:01Z,2021-09-21T21:23:01Z,CONTRIBUTOR,"This appears to not be an `xarray` issue since the code uses `open_dataset` and the `rio.crs` accessor. The `rio.crs` accessor is from `rioxarray`. From what I can tell, the issue has to do with the data is stored in the netCDF file: https://corteva.github.io/rioxarray/stable/getting_started/crs_management.html
My guess is that there is an attribute named `crs` with the contents `+init=EPSG:XXXX`. If that is the case, I recommend using `rioxarray` to do:
```python
data.rio.write_crs(""ESPG:XXXX"", inplace=True)
```
Hopefully this is helpful.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,991857313
https://github.com/pydata/xarray/pull/5609#issuecomment-880914020,https://api.github.com/repos/pydata/xarray/issues/5609,880914020,MDEyOklzc3VlQ29tbWVudDg4MDkxNDAyMA==,8699967,2021-07-15T18:18:43Z,2021-07-15T18:18:43Z,CONTRIBUTOR,"For reference:
- https://corteva.github.io/rioxarray/stable/examples/COG.html
- https://github.com/corteva/rioxarray/pull/48","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,945434599
https://github.com/pydata/xarray/pull/5501#issuecomment-867787488,https://api.github.com/repos/pydata/xarray/issues/5501,867787488,MDEyOklzc3VlQ29tbWVudDg2Nzc4NzQ4OA==,8699967,2021-06-24T16:34:50Z,2021-06-24T16:34:50Z,CONTRIBUTOR,Also see: https://github.com/corteva/rioxarray/pull/359,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,925533850
https://github.com/pydata/xarray/issues/3497#issuecomment-844116976,https://api.github.com/repos/pydata/xarray/issues/3497,844116976,MDEyOklzc3VlQ29tbWVudDg0NDExNjk3Ng==,8699967,2021-05-19T13:40:16Z,2021-05-19T13:40:16Z,CONTRIBUTOR,"> Not sure what we want to do about these attributes in the long term.
I like the idea of using them the same way xarray does for metadata. The next step would be to get pandas to add `.encoding` and then they could do `mask_and_scale` on their `read_*` methods :).","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,520079199
https://github.com/pydata/xarray/issues/5075#issuecomment-832696002,https://api.github.com/repos/pydata/xarray/issues/5075,832696002,MDEyOklzc3VlQ29tbWVudDgzMjY5NjAwMg==,8699967,2021-05-05T13:40:07Z,2021-05-05T13:40:07Z,CONTRIBUTOR,"Yes, the alignment stuff in there should do the trick.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,841012076
https://github.com/pydata/xarray/issues/5075#issuecomment-832685060,https://api.github.com/repos/pydata/xarray/issues/5075,832685060,MDEyOklzc3VlQ29tbWVudDgzMjY4NTA2MA==,8699967,2021-05-05T13:25:23Z,2021-05-05T13:25:23Z,CONTRIBUTOR,"I think it would be nice for xarray to have a ""close enough"" option where a certain number of decimal places is enough to consider them equal. Is there an issue somewhere where this is under consideration or is there an option already in existence that I missed?","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,841012076
https://github.com/pydata/xarray/issues/5075#issuecomment-832684387,https://api.github.com/repos/pydata/xarray/issues/5075,832684387,MDEyOklzc3VlQ29tbWVudDgzMjY4NDM4Nw==,8699967,2021-05-05T13:24:34Z,2021-05-05T13:24:34Z,CONTRIBUTOR,Also related: https://github.com/corteva/rioxarray/discussions/332,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,841012076
https://github.com/pydata/xarray/issues/4697#issuecomment-822618516,https://api.github.com/repos/pydata/xarray/issues/4697,822618516,MDEyOklzc3VlQ29tbWVudDgyMjYxODUxNg==,8699967,2021-04-19T16:48:12Z,2021-04-19T16:48:20Z,CONTRIBUTOR,@alexamici added the entrypoint here; https://github.com/corteva/rioxarray/pull/281. It seems xarray 0.18+ is required for it to work. Any timeline for the `0.18` release?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,767941842
https://github.com/pydata/xarray/pull/3136#issuecomment-822617369,https://api.github.com/repos/pydata/xarray/issues/3136,822617369,MDEyOklzc3VlQ29tbWVudDgyMjYxNzM2OQ==,8699967,2021-04-19T16:46:27Z,2021-04-19T16:46:27Z,CONTRIBUTOR,Related: https://github.com/corteva/rioxarray/issues/191,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,468937654
https://github.com/pydata/xarray/issues/5075#issuecomment-820578700,https://api.github.com/repos/pydata/xarray/issues/5075,820578700,MDEyOklzc3VlQ29tbWVudDgyMDU3ODcwMA==,8699967,2021-04-15T16:49:34Z,2021-04-15T16:49:34Z,CONTRIBUTOR,"Similarly at https://github.com/corteva/rioxarray/issues/298#issuecomment-820557568
```python
np.abs(resampled.x.values - da2.x.values).max(), np.abs(resampled.y.values - da2.y.values).max()
```
```
(4.000014541816199e-09, 6.666663665555461e-09)
```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,841012076
https://github.com/pydata/xarray/issues/5075#issuecomment-820575552,https://api.github.com/repos/pydata/xarray/issues/5075,820575552,MDEyOklzc3VlQ29tbWVudDgyMDU3NTU1Mg==,8699967,2021-04-15T16:46:15Z,2021-04-15T16:48:51Z,CONTRIBUTOR,"For the original post for this issue [ref](https://github.com/pydata/xarray/issues/5075#issue-841012076):
```
np.abs(raster_in.x.values - out_grid.x.values).max(), np.abs(raster_in.y.values - out_grid.y.values).max()
```
```
(1.7763568394002505e-15, 7.105427357601002e-15)
```
Looks like there is a tiny difference in decimal precision.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,841012076
https://github.com/pydata/xarray/issues/5075#issuecomment-820560634,https://api.github.com/repos/pydata/xarray/issues/5075,820560634,MDEyOklzc3VlQ29tbWVudDgyMDU2MDYzNA==,8699967,2021-04-15T16:23:28Z,2021-04-15T16:23:28Z,CONTRIBUTOR,"Similar issue here: https://github.com/corteva/rioxarray/issues/298
Reproducible example in the issue ^^","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,841012076
https://github.com/pydata/xarray/issues/5005#issuecomment-796092118,https://api.github.com/repos/pydata/xarray/issues/5005,796092118,MDEyOklzc3VlQ29tbWVudDc5NjA5MjExOA==,8699967,2021-03-10T20:57:09Z,2021-03-10T20:57:09Z,CONTRIBUTOR,"Thanks for mentioning that. For rioxarray, the fix is:
```python
transform = da.rio.transform()
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,823418135
https://github.com/pydata/xarray/pull/4979#issuecomment-790936823,https://api.github.com/repos/pydata/xarray/issues/4979,790936823,MDEyOklzc3VlQ29tbWVudDc5MDkzNjgyMw==,8699967,2021-03-04T20:58:29Z,2021-03-04T20:58:29Z,CONTRIBUTOR,"For reference for how rioxarray does things: https://corteva.github.io/rioxarray/stable/getting_started/crs_management.html
```
>>> import xarray, rioxarray
>>> xda = xarray.DataArray(1)
>>> xda.rio.write_crs(4326, inplace=True)
array(1)
Coordinates:
spatial_ref int64 0
Attributes:
grid_mapping: spatial_ref
>>> xda.spatial_ref
array(0)
Coordinates:
spatial_ref int64 0
Attributes:
crs_wkt: GEOGCS[""WGS 84"",DATUM[""WGS_1984"",SPHEROID[""...
semi_major_axis: 6378137.0
semi_minor_axis: 6356752.314245179
inverse_flattening: 298.257223563
reference_ellipsoid_name: WGS 84
longitude_of_prime_meridian: 0.0
prime_meridian_name: Greenwich
geographic_crs_name: WGS 84
grid_mapping_name: latitude_longitude
spatial_ref: GEOGCS[""WGS 84"",DATUM[""WGS_1984"",SPHEROID[""...
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,819062172
https://github.com/pydata/xarray/issues/4697#issuecomment-746518824,https://api.github.com/repos/pydata/xarray/issues/4697,746518824,MDEyOklzc3VlQ29tbWVudDc0NjUxODgyNA==,8699967,2020-12-16T15:52:34Z,2020-12-16T15:52:34Z,CONTRIBUTOR,"Looks like entrypoint support was added in #4577. What is the timeline for the next release?
> and rioxarray agrees
Is `rioxarray` agreeing to allow the addition of entrypoint support? If so, :+1:
","{""total_count"": 2, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 1, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,767941842
https://github.com/pydata/xarray/issues/3776#issuecomment-739655170,https://api.github.com/repos/pydata/xarray/issues/3776,739655170,MDEyOklzc3VlQ29tbWVudDczOTY1NTE3MA==,8699967,2020-12-07T04:27:45Z,2020-12-07T04:27:45Z,CONTRIBUTOR,You may be interested in rioxarray: https://corteva.github.io/rioxarray/stable/getting_started/getting_started.html,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,566961374
https://github.com/pydata/xarray/issues/1970#issuecomment-653927498,https://api.github.com/repos/pydata/xarray/issues/1970,653927498,MDEyOklzc3VlQ29tbWVudDY1MzkyNzQ5OA==,8699967,2020-07-05T19:14:29Z,2020-07-05T19:14:29Z,CONTRIBUTOR,Reference for writing from xarray to GeoTIFF or any other GDAL supported format: https://corteva.github.io/rioxarray/stable/examples/convert_to_raster.html,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,302806158
https://github.com/pydata/xarray/issues/4142#issuecomment-642669071,https://api.github.com/repos/pydata/xarray/issues/4142,642669071,MDEyOklzc3VlQ29tbWVudDY0MjY2OTA3MQ==,8699967,2020-06-11T13:54:33Z,2020-06-11T14:05:49Z,CONTRIBUTOR,"In `rioxarray` we updated `open_rasterio` so it opens a `tif` file like a DataArray and netcdf-like files as a dataset. It also loads in the metadata/tags as well:
### NetCDF file as Dataset
```python
import rioxarray
xds = rioxarray.open_rasterio(""PLANET_SCOPE_3D.nc"")
```
```
Dimensions: (time: 2, x: 10, y: 10)
Coordinates:
* y (y) float64 8.085e+06 8.085e+06 ... 8.085e+06 8.085e+06
* x (x) float64 4.663e+05 4.663e+05 ... 4.663e+05 4.663e+05
* time (time) object 2016-12-19 10:27:29 2016-12-29 12:52:41.659696
spatial_ref int64 0
Data variables:
blue (time, y, x) float64 6.611 5.581 0.3996 ... 3.491 5.056 3.368
green (time, y, x) float64 7.921 66.15 30.1 ... 21.76 27.29 18.41
Attributes:
coordinates: spatial_ref
```
### GeoTiff as DataArray
```python
rds = rioxarray.open_rasterio(""test_albedo.tif"")
```
```
[697320 values with dtype=int8]
Coordinates:
* band (band) int64 1
* y (y) float64 4.225e+06 4.225e+06 ... 4.216e+06 4.216e+06
* x (x) float64 6.168e+05 6.168e+05 ... 6.242e+05 6.242e+05
spatial_ref int64 0
Attributes:
transform: (10.0, 0.0, 616800.0, 0.0, -10.0, 4225260.0)
_FillValue: -1.0
scale_factor: 1.0
add_offset: 0.0
long_name: Albedo dry - the estimated ratio of the incident short-wav...
grid_mapping: spatial_ref
```
So, it could be modified to use as an `engine` in its current state.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,636493109
https://github.com/pydata/xarray/pull/4104#issuecomment-642340685,https://api.github.com/repos/pydata/xarray/issues/4104,642340685,MDEyOklzc3VlQ29tbWVudDY0MjM0MDY4NQ==,8699967,2020-06-11T00:48:40Z,2020-06-11T00:48:40Z,CONTRIBUTOR,"> go for it!
Sounds good, will do. Thanks for the patch :+1:
> I don't know much about rioxarray
The [usage examples](https://corteva.github.io/rioxarray/stable/examples/examples.html) are a good place to go to learn more.
> Is the intent to someday merge that into xarray or will the geospatial features mean it will remain separate?
It hasn't really been discussed/decided upon.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,626240065
https://github.com/pydata/xarray/pull/3964#issuecomment-642239585,https://api.github.com/repos/pydata/xarray/issues/3964,642239585,MDEyOklzc3VlQ29tbWVudDY0MjIzOTU4NQ==,8699967,2020-06-10T20:27:34Z,2020-06-10T20:27:34Z,CONTRIBUTOR,"@cheginit, thanks for being willing. The part to modify is here: https://github.com/corteva/rioxarray/blob/6587726a019f46ec68ca94d6cea866abea956a2a/rioxarray/_io.py#L657","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,598121005
https://github.com/pydata/xarray/pull/3964#issuecomment-642185516,https://api.github.com/repos/pydata/xarray/issues/3964,642185516,MDEyOklzc3VlQ29tbWVudDY0MjE4NTUxNg==,8699967,2020-06-10T18:32:52Z,2020-06-10T18:32:52Z,CONTRIBUTOR,"Would you like to add this update to [rioxarray](https://github.com/corteva/rioxarray) as well? If not, mind if I port it over?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,598121005
https://github.com/pydata/xarray/pull/4104#issuecomment-642185267,https://api.github.com/repos/pydata/xarray/issues/4104,642185267,MDEyOklzc3VlQ29tbWVudDY0MjE4NTI2Nw==,8699967,2020-06-10T18:32:23Z,2020-06-10T18:32:23Z,CONTRIBUTOR,"Would you like to add this update to [rioxarray](https://github.com/corteva/rioxarray) as well? If not, mind if I port it over?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,626240065
https://github.com/pydata/xarray/pull/4140#issuecomment-642184783,https://api.github.com/repos/pydata/xarray/issues/4140,642184783,MDEyOklzc3VlQ29tbWVudDY0MjE4NDc4Mw==,8699967,2020-06-10T18:31:26Z,2020-06-10T18:31:26Z,CONTRIBUTOR,"Would you like to add this update to [rioxarray](https://github.com/corteva/rioxarray) as well? If not, mind if I port it over?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,636451398
https://github.com/pydata/xarray/pull/3757#issuecomment-595233073,https://api.github.com/repos/pydata/xarray/issues/3757,595233073,MDEyOklzc3VlQ29tbWVudDU5NTIzMzA3Mw==,8699967,2020-03-05T13:36:25Z,2020-03-05T13:36:25Z,CONTRIBUTOR,Thanks for the fixes ๐,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,561132832
https://github.com/pydata/xarray/pull/3757#issuecomment-590556932,https://api.github.com/repos/pydata/xarray/issues/3757,590556932,MDEyOklzc3VlQ29tbWVudDU5MDU1NjkzMg==,8699967,2020-02-24T21:27:01Z,2020-02-24T21:27:01Z,CONTRIBUTOR,"> We might want to think about adding rioxarray as documentation build dependency
That brings along with it the fun of GDAL as a dependency.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,561132832
https://github.com/pydata/xarray/issues/2723#issuecomment-582984655,https://api.github.com/repos/pydata/xarray/issues/2723,582984655,MDEyOklzc3VlQ29tbWVudDU4Mjk4NDY1NQ==,8699967,2020-02-06T16:20:54Z,2020-02-06T16:20:54Z,CONTRIBUTOR,"@dcherian Maybe a link to these examples in that section then?
https://corteva.github.io/rioxarray/stable/examples/examples.html","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,404088563
https://github.com/pydata/xarray/issues/2723#issuecomment-582965693,https://api.github.com/repos/pydata/xarray/issues/2723,582965693,MDEyOklzc3VlQ29tbWVudDU4Mjk2NTY5Mw==,8699967,2020-02-06T15:42:35Z,2020-02-06T15:42:35Z,CONTRIBUTOR,"> Adding an example on doing these manipulations would also be very welcome.
What types of manipulations are you thinking about? Reprojection? Export to geotiff? Clip? Reading in files?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,404088563
https://github.com/pydata/xarray/issues/2723#issuecomment-582944232,https://api.github.com/repos/pydata/xarray/issues/2723,582944232,MDEyOklzc3VlQ29tbWVudDU4Mjk0NDIzMg==,8699967,2020-02-06T14:58:07Z,2020-02-06T14:58:07Z,CONTRIBUTOR,"Going to close this as it is over a year old.
For reference, WKT support is in `rioxarray`.
https://corteva.github.io/rioxarray/stable/examples/crs_management.html","{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 1, ""rocket"": 0, ""eyes"": 0}",,404088563
https://github.com/pydata/xarray/issues/3620#issuecomment-565680014,https://api.github.com/repos/pydata/xarray/issues/3620,565680014,MDEyOklzc3VlQ29tbWVudDU2NTY4MDAxNA==,8699967,2019-12-14T04:03:24Z,2019-12-14T04:03:24Z,CONTRIBUTOR,"> I'm wondering if an xarray accessor could work around some of the current limitations you're seeing.
I think this sounds like a good idea. ","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,537772490
https://github.com/pydata/xarray/issues/3620#issuecomment-565673569,https://api.github.com/repos/pydata/xarray/issues/3620,565673569,MDEyOklzc3VlQ29tbWVudDU2NTY3MzU2OQ==,8699967,2019-12-14T02:38:32Z,2019-12-14T02:38:32Z,CONTRIBUTOR,"For reference, here is how CRS information is handled in rioxarray: [CRS management docs](https://corteva.github.io/rioxarray/stable/examples/crs_management.html).","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,537772490
https://github.com/pydata/xarray/pull/2618#issuecomment-550467547,https://api.github.com/repos/pydata/xarray/issues/2618,550467547,MDEyOklzc3VlQ29tbWVudDU1MDQ2NzU0Nw==,8699967,2019-11-06T19:37:19Z,2019-11-06T19:37:19Z,CONTRIBUTOR,"@jsignell, the `masked` kwarg is in `rioxarray` if you need it: https://corteva.github.io/rioxarray/html/examples/clip_geom.html","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,392361367
https://github.com/pydata/xarray/issues/3449#issuecomment-546407518,https://api.github.com/repos/pydata/xarray/issues/3449,546407518,MDEyOklzc3VlQ29tbWVudDU0NjQwNzUxOA==,8699967,2019-10-25T15:47:33Z,2019-10-25T15:47:33Z,CONTRIBUTOR,Nice!,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,512584839
https://github.com/pydata/xarray/pull/2255#issuecomment-514713407,https://api.github.com/repos/pydata/xarray/issues/2255,514713407,MDEyOklzc3VlQ29tbWVudDUxNDcxMzQwNw==,8699967,2019-07-24T16:53:50Z,2019-07-24T16:53:50Z,CONTRIBUTOR,"> Put another way: why don't we put all the logic in rioxarray and make rioxarray an optional dependency of xarray to open rio files?
That is an option. All of the logic has already been moved over.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,336371511
https://github.com/pydata/xarray/pull/2255#issuecomment-514688429,https://api.github.com/repos/pydata/xarray/issues/2255,514688429,MDEyOklzc3VlQ29tbWVudDUxNDY4ODQyOQ==,8699967,2019-07-24T15:46:36Z,2019-07-24T15:46:36Z,CONTRIBUTOR,"> I'm curious, are there features in rioxarray that could be pushed upstream?
Depends on what the xarray maintainers would like to add. I would definitely like to see the `open_rasterio` function in `rioxarray` absorbed back into `xarray`. Things have just been really slow moving with the other PRs/issues.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,336371511
https://github.com/pydata/xarray/pull/2255#issuecomment-514685330,https://api.github.com/repos/pydata/xarray/issues/2255,514685330,MDEyOklzc3VlQ29tbWVudDUxNDY4NTMzMA==,8699967,2019-07-24T15:38:53Z,2019-07-24T15:39:53Z,CONTRIBUTOR,"> I've abandoned this PR. If anyone has time to pick it up, that would be welcome.
I appreciate you staring this! Based on this PR, I added the feature into `rioxarray` here: https://github.com/corteva/rioxarray/pull/31 (released in version 0.0.9). (Example usage can be seen [here](https://corteva.github.io/rioxarray/html/examples/clip_geom.html).)","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,336371511
https://github.com/pydata/xarray/pull/2255#issuecomment-514628738,https://api.github.com/repos/pydata/xarray/issues/2255,514628738,MDEyOklzc3VlQ29tbWVudDUxNDYyODczOA==,8699967,2019-07-24T13:19:47Z,2019-07-24T13:55:35Z,CONTRIBUTOR,"> How to create tiled TIFF files in the tests
One thing I would like to note is that the automatic chunking would be useful if the raster is tiled or not. I tested out a raster that was not tiled, but it still had chunks. This is due to the raster being written in stripes. So, I would recommend removing the restriction to only tiled rasters.
Also, to create a tiled raster:
```python
import rasterio
import numpy
from affine import Affine
with rasterio.open(
""tiled.tif"",
""w"",
driver=""GTiff"",
count=2,
width=1024,
height=1024,
crs=""+init=epsg:4326"",
transform=Affine(0.0083333333, 0.0, -180.00416666665, 0.0, -0.0083333333, 75.00416666665),
dtype=rasterio.float32,
tiled=True,
blockxsize=512,
blockysize=512,
) as rds:
rds.write((numpy.random.rand(2, 1024, 1024)*10).astype(numpy.float32))
```
Looks like they have this option in the tests:
```python
open_kwargs=dict(
tiled=True,
blockxsize=512,
blockysize=512
)
with create_tmp_geotiff(nx=1024, ny=1024, nz=2, open_kwargs=open_kwargs) as (tmp_file, expected):
....
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,336371511
https://github.com/pydata/xarray/pull/2255#issuecomment-514626195,https://api.github.com/repos/pydata/xarray/issues/2255,514626195,MDEyOklzc3VlQ29tbWVudDUxNDYyNjE5NQ==,8699967,2019-07-24T13:12:47Z,2019-07-24T13:27:41Z,CONTRIBUTOR,"> The right way to merge different dtypes and block shapes in the tiff file. Currently I'm assuming that they're uniform
I have yet to run into a raster that varies dtypes and block shapes across bands. Most of the time, they are single band rasters. And if they are not, they have had the same dtype and block shape. So, I think your assumption is a good one for most use cases.
Also, only a single dtype is allowed currently:
https://github.com/pydata/xarray/blob/1d7bcbdc75b6d556c04e2c7d7a042e4379e15303/xarray/backends/rasterio_.py#L39-L40
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,336371511
https://github.com/pydata/xarray/issues/2042#issuecomment-510693104,https://api.github.com/repos/pydata/xarray/issues/2042,510693104,MDEyOklzc3VlQ29tbWVudDUxMDY5MzEwNA==,8699967,2019-07-11T23:46:38Z,2019-07-11T23:46:38Z,CONTRIBUTOR,"A new project called [rioxarray](http://github.com/corteva/rioxarray) has a `to_raster` method with the default driver of `GTiff`.
You can use it like so:
```
import rioxarray
import xarray
xds = xarray.open_rasterio(""myfile.tif"")
wgs84_xds = xds.rio.reproject(""EPSG:4326"")
wgs84_xds.rio.to_raster(""myfile_wgs84.tif"")
```
It currently only supports 2d/3d `DataArray`s. So, you would have to iterate over your variables to export each one to a raster if you have a `Dataset`.","{""total_count"": 8, ""+1"": 7, ""-1"": 0, ""laugh"": 1, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,312203596
https://github.com/pydata/xarray/issues/2723#issuecomment-506403269,https://api.github.com/repos/pydata/xarray/issues/2723,506403269,MDEyOklzc3VlQ29tbWVudDUwNjQwMzI2OQ==,8699967,2019-06-27T15:49:52Z,2019-06-27T15:49:52Z,CONTRIBUTOR,@fmaussion just a ping for what are your thoughts are for next steps on this?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,404088563
https://github.com/pydata/xarray/pull/2618#issuecomment-487059783,https://api.github.com/repos/pydata/xarray/issues/2618,487059783,MDEyOklzc3VlQ29tbWVudDQ4NzA1OTc4Mw==,8699967,2019-04-26T13:38:13Z,2019-04-26T13:38:13Z,CONTRIBUTOR,"Good question, I was thinking adding tests.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,392361367
https://github.com/pydata/xarray/pull/2618#issuecomment-487050467,https://api.github.com/repos/pydata/xarray/issues/2618,487050467,MDEyOklzc3VlQ29tbWVudDQ4NzA1MDQ2Nw==,8699967,2019-04-26T13:08:39Z,2019-04-26T13:08:39Z,CONTRIBUTOR,"I think it would be good to write the dataset to a netcdf, and read it back in with xarray.open_dataset to ensure everything encodes/decides properly.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,392361367
https://github.com/pydata/xarray/issues/2723#issuecomment-460428737,https://api.github.com/repos/pydata/xarray/issues/2723,460428737,MDEyOklzc3VlQ29tbWVudDQ2MDQyODczNw==,8699967,2019-02-04T21:55:16Z,2019-02-04T21:55:16Z,CONTRIBUTOR,"I definitely agree ๐ฏ with you on avoiding redundancy. I actually had the same thought. However, part of the reason for using `crs_wkt` is motivated by [CF 1.7 convention](http://cfconventions.org/Data/cf-conventions/cf-conventions-1.7/cf-conventions.html). I figured it was a small change that sacrifices redundancy for consistency across the community. The `crs_proj4` name was just an attempt to be consistent with your original comment and the `crs_wkt`. But, I think renaming it to `proj4` to remove redundancy is a good choice as well.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,404088563
https://github.com/pydata/xarray/issues/2723#issuecomment-458669281,https://api.github.com/repos/pydata/xarray/issues/2723,458669281,MDEyOklzc3VlQ29tbWVudDQ1ODY2OTI4MQ==,8699967,2019-01-29T19:14:49Z,2019-01-29T19:14:49Z,CONTRIBUTOR,Tag: @fmaussion @djhoese,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,404088563
https://github.com/pydata/xarray/issues/2722#issuecomment-458332803,https://api.github.com/repos/pydata/xarray/issues/2722,458332803,MDEyOklzc3VlQ29tbWVudDQ1ODMzMjgwMw==,8699967,2019-01-28T22:45:52Z,2019-01-28T22:45:52Z,CONTRIBUTOR,"Since the main discussion is resolved, I will close this issue to prevent spam. I will open another issue for implementation details later.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,403971686
https://github.com/pydata/xarray/issues/2722#issuecomment-458322962,https://api.github.com/repos/pydata/xarray/issues/2722,458322962,MDEyOklzc3VlQ29tbWVudDQ1ODMyMjk2Mg==,8699967,2019-01-28T22:13:26Z,2019-01-28T22:13:26Z,CONTRIBUTOR,"Sounds like a good path forward to me.
Since the `crs` attribute will be deprecated, thoughts on replacing it with a `crs` coordinate and the `PROJ.4` and `WKT` representations in the coordinate attributes?
Something like:
```
array(0)
Coordinates:
crs int64 0
Attributes:
crs_wkt: PROJCS[""UTM Zone 15, Northern Hemisphere"",GEOGCS[""WGS 84"",D...
crs_proj4: +proj=...
```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,403971686
https://github.com/pydata/xarray/pull/2618#issuecomment-448628008,https://api.github.com/repos/pydata/xarray/issues/2618,448628008,MDEyOklzc3VlQ29tbWVudDQ0ODYyODAwOA==,8699967,2018-12-19T15:08:34Z,2018-12-19T15:09:01Z,CONTRIBUTOR,"I think the solution would be to add a masked argument and property to the class RasterioArrayWrapper [here](https://github.com/pydata/xarray/blob/778ffc49135d6f97e17b37b48304995fca72f1e0/xarray/backends/rasterio_.py#L24).
And pass in the (masked=masked) argument [here](https://github.com/pydata/xarray/blob/778ffc49135d6f97e17b37b48304995fca72f1e0/xarray/backends/rasterio_.py#L291)
That would pass riods.read( ..., masked=self.masked) when reading data from rasterio [here](https://github.com/pydata/xarray/blob/778ffc49135d6f97e17b37b48304995fca72f1e0/xarray/backends/rasterio_.py#L115)","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,392361367
https://github.com/pydata/xarray/pull/2618#issuecomment-448402521,https://api.github.com/repos/pydata/xarray/issues/2618,448402521,MDEyOklzc3VlQ29tbWVudDQ0ODQwMjUyMQ==,8699967,2018-12-18T22:54:44Z,2018-12-18T22:54:44Z,CONTRIBUTOR,"@jsignell, this looks like it would work - I like the implementation. Some things I would recommend to add is checks for when the nodata value varies across bands (maybe skip the mask and raise a warning) and when the nodata value is already NaN. Also, you should probably set the nodatavals to NaN if masked to resemble the behavior of xarray elsewhere.
I think @fmaussion would be a good reviewer for this PR.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,392361367
https://github.com/pydata/xarray/issues/1736#issuecomment-447903844,https://api.github.com/repos/pydata/xarray/issues/1736,447903844,MDEyOklzc3VlQ29tbWVudDQ0NzkwMzg0NA==,8699967,2018-12-17T16:19:45Z,2018-12-17T16:19:45Z,CONTRIBUTOR,"It would definitely be a fantastic feature to have. Some discussion happened in #2308 to discuss standardizing methods for storing data that would definitely assist with this, however it did not seem like a priority at the time. Definitely feel free to share your opinion and use cases.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,276131376
https://github.com/pydata/xarray/issues/2308#issuecomment-428177967,https://api.github.com/repos/pydata/xarray/issues/2308,428177967,MDEyOklzc3VlQ29tbWVudDQyODE3Nzk2Nw==,8699967,2018-10-09T12:46:54Z,2018-10-09T12:46:54Z,CONTRIBUTOR,Feel free to re-open if this becomes something of interest. Thanks!,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,344058811
https://github.com/pydata/xarray/issues/2288#issuecomment-415849716,https://api.github.com/repos/pydata/xarray/issues/2288,415849716,MDEyOklzc3VlQ29tbWVudDQxNTg0OTcxNg==,8699967,2018-08-24T18:50:44Z,2018-08-24T18:50:44Z,CONTRIBUTOR,"I was thinking just a ""simple"" library with a CRS object with utilities to create the object from WKT, PROJ.4, CF projection parameters, etc... And could take the object and convert it to any of the other formats. I wouldn't add any transform/resampling code and instead be a codebase that can be used by libraries that do those things. This way it would be useful to many different projects (geoxarray, pyresample, cartopy, metpy, ...). Thoughts?
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,341331807
https://github.com/pydata/xarray/issues/2288#issuecomment-415842467,https://api.github.com/repos/pydata/xarray/issues/2288,415842467,MDEyOklzc3VlQ29tbWVudDQxNTg0MjQ2Nw==,8699967,2018-08-24T18:23:57Z,2018-08-24T18:23:57Z,CONTRIBUTOR,Sounds good ๐. I see the CRS code potentially being useful outside of geoxarray. What are your thoughts on moving the CRS specific code into its own package?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,341331807
https://github.com/pydata/xarray/issues/2288#issuecomment-409566229,https://api.github.com/repos/pydata/xarray/issues/2288,409566229,MDEyOklzc3VlQ29tbWVudDQwOTU2NjIyOQ==,8699967,2018-08-01T13:00:26Z,2018-08-01T13:00:26Z,CONTRIBUTOR,"Lots of good thoughts there.
I think a lot depends on who you plan on having for a user base. I like `rasterio.crs.CRS`, but it does require GDAL. I know GDAL is a heavy dependency (solves runtime problems and it a source of installation problems), but if your users are already using it, then it isn't too big of an ask. If not, you could look into something like [pycrs](https://github.com/karimbahgat/PyCRS). But, it looks like it hasn't been touched for a while (never a good sign). Or, there are other options, (requiring a more work & maintenance) such as re-creating the `rasterio.crs.CRS` object and using cython with a copy of only the spatial reference code from GDAL in the repo (might be better to create your own repo/package if you head in this direction). Or maybe someone could ask really nicely for the GDAL maintainers to consider making the spatial reference code a package on it's own (not likely, but would be really nice).
My preference to have the CRS object something created/retrieved by the accessor based on information in the file. If it is not, users will have to remove the CRS object when using `to_netcdf()` as the object will not be serializable and `to_netcdf()` will throw errors. I think allowing the user to set the CRS on the file (by adding the `crs` to `.coords` and `grid_mapping` to `data_vars`) by passing in a valid projection string (WKT, proj.4) `geo.set_crs()` would be a good idea. This way, when the user calls, `to_netcdf()` it will happily do what they want. In addition, the CRS will still be available later with the accessor when loading in with `xr.open_dataset`.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,341331807
https://github.com/pydata/xarray/issues/2308#issuecomment-407862762,https://api.github.com/repos/pydata/xarray/issues/2308,407862762,MDEyOklzc3VlQ29tbWVudDQwNzg2Mjc2Mg==,8699967,2018-07-25T19:07:27Z,2018-07-25T19:07:27Z,CONTRIBUTOR,"@fmaussion, I guess the main reason for the proposed change is to be able to read in the raster using `open_rasterio()` and be able to generate a netCDF using `to_netcdf()` that would be compatible with the rasterio model when using `rasterio.open()`.
Also, since: ""xarray.Dataset is an in-memory representation of a netCDF file"", to me it makes more sense to store the data in a standard netCDF location that is consistent regardless of the backend. In doing so, other parts of xarray and libraries build off of xarray won't be required to find the same data in multiple locations.
Thanks for taking the time to consider this idea. I have used it quite a bit and it has made the datasets compatible across the various GIS tools I use (rasterio, GDAL, QGIS). It has definitely made my life easier and so I wanted to share what I have learned. But, it is just an idea. I really appreciate the work of the xarray developers and whatever y'all decide is fine with me.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,344058811
https://github.com/pydata/xarray/issues/2288#issuecomment-407857617,https://api.github.com/repos/pydata/xarray/issues/2288,407857617,MDEyOklzc3VlQ29tbWVudDQwNzg1NzYxNw==,8699967,2018-07-25T18:49:57Z,2018-07-25T18:49:57Z,CONTRIBUTOR,"The example I gave was just demonstrating that the *dimension* is not required for the `crs` coordinate variable.
I agree with the functionality that would support standardizing the `crs` as a coordinate variable on load for the case you specified. That way, the read in file will always behave the same and writing to netCDF it would be output correctly.
This all sounds like it is heading in a good direction. ๐ ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,341331807
https://github.com/pydata/xarray/issues/2288#issuecomment-407748105,https://api.github.com/repos/pydata/xarray/issues/2288,407748105,MDEyOklzc3VlQ29tbWVudDQwNzc0ODEwNQ==,8699967,2018-07-25T13:08:25Z,2018-07-25T13:08:25Z,CONTRIBUTOR,"It is not in the dimension, it is the *coordinate* attribute in the variable. That is handled automatically by xarray when writing `to_netcdf` if you add the *crs* to the `coords`.
From the ncdump:
```
dimensions:
x = 65 ;
y = 31 ;
variables:
double x(x) ;
x:_FillValue = NaN ;
x:long_name = ""x coordinate of projection"" ;
x:standard_name = ""projection_x_coordinate"" ;
x:units = ""m"" ;
double y(y) ;
y:_FillValue = NaN ;
y:long_name = ""y coordinate of projection"" ;
y:standard_name = ""projection_y_coordinate"" ;
y:units = ""m"" ;
int64 time ;
time:units = ""seconds since 2015-04-03T17:55:19"" ;
time:calendar = ""proleptic_gregorian"" ;
int64 spatial_ref ;
spatial_ref:spatial_ref = ""PROJCS[\""UTM Zone 15, Northern Hemisphere\"",GEOGCS[\""WGS 84\"",DATUM[\""WGS_1984\"",SPHEROID[\""WGS 84\"",6378137,298.257223563,AUTHORITY[\""EPSG\"",\""7030\""]],AUTHORITY[\""EPSG\"",\""6326\""]],PRIMEM[\""Greenwich\"",0,AUTHORITY[\""EPSG\"",\""8901\""]],UNIT[\""degree\"",0.0174532925199433,AUTHORITY[\""EPSG\"",\""9122\""]],AUTHORITY[\""EPSG\"",\""4326\""]],PROJECTION[\""Transverse_Mercator\""],PARAMETER[\""latitude_of_origin\"",0],PARAMETER[\""central_meridian\"",-93],PARAMETER[\""scale_factor\"",0.9996],PARAMETER[\""false_easting\"",500000],PARAMETER[\""false_northing\"",0],UNIT[\""Meter\"",1]]"" ;
double ndvi(y, x) ;
ndvi:_FillValue = NaN ;
ndvi:grid_mapping = ""spatial_ref"" ;
ndvi:coordinates = ""spatial_ref time"" ;
// global attributes:
:creation_date = ""2018-04-11 13:14:55.401183"" ;
```
It would definitely be a good idea to ensure that the `crs` variable is a coordinate, so I agree that having support for that would be a good idea.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,341331807
https://github.com/pydata/xarray/issues/2288#issuecomment-407614809,https://api.github.com/repos/pydata/xarray/issues/2288,407614809,MDEyOklzc3VlQ29tbWVudDQwNzYxNDgwOQ==,8699967,2018-07-25T02:39:34Z,2018-07-25T02:39:34Z,CONTRIBUTOR,"That is interesting, I am definitely not an expert with non-uniform datasets. From the satellite datasets I have used, the 2D latitude and longitude coordinates are stored in the datasets and are not super useful. I usually have to use other ways to recreate the grid coordinates in the original projection (ex. SMAP uses the EASE Grid 2.0 but it stores the latitude/longitude of the points in the file) or reproject & flatten the coordinates. I have had to do this with weather data and made an xarray extension [pangaea](https://github.com/snowman2/pangaea) to handle it. So, that is what I was referring to when I misunderstood your question.
> For your example of adding a crs attribute, ...
The files I have created have the `crs` coordinate variable inside the netCDF file already and it is always there when I load it in with `xarray.open_dataset()`. The method `set_crs()` could be used to add the `crs` coordinate variable and `grid_mapping` attributes to the dataset in the proper way so that it would be there on `xarray.open_dataset()` after dumping it to the file with `to_netcdf()`.
The CF stuff is supported by rasterio, GDAL, QGIS and that is why I like it. If there is another way that is as well supported, I am not opposed to it.
> In your example of methods is to_projection a remapping/resampling operation? If not, how does it differ from set_crs?
The `to_projection()` method would be a reproject/resampling operation.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,341331807
https://github.com/pydata/xarray/issues/2308#issuecomment-407610465,https://api.github.com/repos/pydata/xarray/issues/2308,407610465,MDEyOklzc3VlQ29tbWVudDQwNzYxMDQ2NQ==,8699967,2018-07-25T02:12:16Z,2018-07-25T02:12:16Z,CONTRIBUTOR,That is strange. Was the variable put in `data_vars` and not in `coords`?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,344058811
https://github.com/pydata/xarray/issues/2288#issuecomment-407546587,https://api.github.com/repos/pydata/xarray/issues/2288,407546587,MDEyOklzc3VlQ29tbWVudDQwNzU0NjU4Nw==,8699967,2018-07-24T20:47:23Z,2018-07-24T20:48:17Z,CONTRIBUTOR,"> In your own projects and use of raster-like data, do you ever deal with non-uniform/non-projected data?
I have dealt with non-uniform data in the geographic projection. I have found it easiest to deal with it if you can determine the original projection and project the coordinates back to that projection so it is uniform. But, I am by no means an expert in this arena. Most if the time I work ""normal"" data.
> How do you prefer to handle/store individual lon/lat values for each pixel?
rasterio/GDAL/QGIS all seem to use the centroid.
> Also it looks like xarray would have to be updated to add the ""crs"" coordinate since currently it is not
considered a coordinate variable. So a new library may need to have custom to_netcdf/open_dataset methods, right?
Actually, it is not difficult to add as it stands:
```python
ds.coords['crs'] = 0
ds.coords['crs'].attrs = dict(spatial_ref=""PROJCS[""UTM Zone 15, Northern Hemisphere"",GEOGCS[""WGS 84"",D..."")
```
But, if a `crs` does not already exist on the dataset, I guess that a function that adds the `crs` properly would be useful so it can also add the grid_mapping to all of the variables.
Example:
```python
ds.geo.set_crs(""+init=epsg:4326"")
```
I think that minor modifications will be needed once the crs is set properly on the xarray dataset. Because after that, the `to_netcdf()` will automatically produce georeferenced datasets.
I could see the first pass of the extension/library simply performing:
1. `ds.geo.crs`
2. `ds.geo.set_crs()`
3. `ds.geo.to_projection()`","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,341331807
https://github.com/pydata/xarray/issues/2308#issuecomment-407541054,https://api.github.com/repos/pydata/xarray/issues/2308,407541054,MDEyOklzc3VlQ29tbWVudDQwNzU0MTA1NA==,8699967,2018-07-24T20:28:28Z,2018-07-24T20:28:28Z,CONTRIBUTOR,I don't think so. The `crs` should already exist on the dataset beforehand and I think it may be a bit too much to expect it to add it to the dataset in that function as there are some that don't have it and not all xarray datasets are geospatially located.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,344058811
https://github.com/pydata/xarray/issues/2288#issuecomment-407404131,https://api.github.com/repos/pydata/xarray/issues/2288,407404131,MDEyOklzc3VlQ29tbWVudDQwNzQwNDEzMQ==,8699967,2018-07-24T13:21:31Z,2018-07-24T13:32:42Z,CONTRIBUTOR,"Here is an example of how it would look on a dataset:
```
Dimensions: (x: 65, y: 31)
Coordinates:
* x (x) float64 ...
* y (y) float64 ...
time datetime64[ns] ...
crs int64 ...
Data variables:
ndvi (y, x) float64 ...
Attributes:
```
Here is how the `crs` or `spatial_ref` coodinate variable would look:
```
array(0)
Coordinates:
time datetime64[ns] ...
crs int64 0
Attributes:
spatial_ref: PROJCS[""UTM Zone 15, Northern Hemisphere"",GEOGCS[""WGS 84"",D...
```
And here is how it would look on the variables:
```
array([[ ...]])
Coordinates:
* x (x) float64 ...
* y (y) float64 ...
time datetime64[ns] ...
crs int64 0
Attributes:
grid_mapping: crs
```
@djhoese Whether or not we use the CF convention is not what I am concerned about. What I think would benefit the most people is with the file format to be able to do `to_netcdf()` with the file and be able to have it read in with standard GIS tools such as rasterio, GDAL, and QGIS. With this schema, this is possible.
Another benefit is that it keeps the `crs` or `spatial_ref` with it when you do your operations as it is a coordinate of the variable.
Also, as a side note if you use the center pixel coordinates, then GDAL, rasterio, and QGIS are able to read in the file and determine it's affine/transform without a problem.
For the new library, if you have a `crs` method attached to it, it isn't too difficult to convert it to whatever format you need it to be in. With the [rasterio.crs.CRS.from_string](https://github.com/mapbox/rasterio/blob/c96168b59167bc4f67e3e39700ac253064720718/rasterio/_crs.pyx#L154) you can ""Make a CRS from an EPSG, PROJ, or WKT string"" and you can also get back the EPSG, PROJ, or WKT string with a simple method call.
For example, using the recommended method to [extend xarray](http://xarray.pydata.org/en/stable/internals.html#extending-xarray), you could add a crs property:
```python
from rasterio.crs import CRS
........
@property
def crs(self):
"""""":obj:`rasterio.crs.CRS`:
Projection from `xarray.DataArray`
""""""
if self._crs is not None:
return self._crs
try:
# look in grid_mapping
self._crs = CRS.from_string(self._obj.coords[self._obj.grid_mapping].spatial_ref)
except AttributeError:
raise ValueError(""Spatial reference not found."")
return self._crs
```
And if you call your extension `geo`, all you would need to get the CRS would be:
```python
ds.geo.crs
```
To get proj.4 string:
```python
ds.geo.crs.to_string()
```
To get WKT string:
```python
ds.geo.crs.wkt
```
To get EPSG code:
```python
ds.geo.crs.to_epsg()
```
","{""total_count"": 4, ""+1"": 4, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,341331807
https://github.com/pydata/xarray/issues/2288#issuecomment-407249087,https://api.github.com/repos/pydata/xarray/issues/2288,407249087,MDEyOklzc3VlQ29tbWVudDQwNzI0OTA4Nw==,8699967,2018-07-24T01:19:26Z,2018-07-24T01:19:26Z,CONTRIBUTOR,"I am really excited about this discussion. I know of other libraries that have done the same thing and have written internal libraries myself.
If possible, I would hope that we could follow the CF convention on this as it makes the output netCDF file compatible with QGIS, GDAL, and rasterio when written using `to_netcdf()`
To do so, you add the `crs` coordinate to the dataset/dataarray.
```
int crs;
```
And then, you add the `spatial_ref` attribute to the crs which is a crs WKT string.
Next, you add the `grid_mapping` attribute to all associated variables that contains `crs` as the grid_mapping.
See an example [here](https://gis.stackexchange.com/questions/230093/set-projection-for-netcdf4-in-python).
After that, you could store all kinds of information inside the `crs` variable such as the proj4 string, the affine, etc.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,341331807
https://github.com/pydata/xarray/pull/1740#issuecomment-358807759,https://api.github.com/repos/pydata/xarray/issues/1740,358807759,MDEyOklzc3VlQ29tbWVudDM1ODgwNzc1OQ==,8699967,2018-01-18T22:49:23Z,2018-01-18T22:49:23Z,CONTRIBUTOR,"Indeed, it would be nice to refactor the tests to use pytest functions so we can use fixtures and the pytest.mark.parametrize to reduce duplication.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,276246800
https://github.com/pydata/xarray/issues/1754#issuecomment-351590950,https://api.github.com/repos/pydata/xarray/issues/1754,351590950,MDEyOklzc3VlQ29tbWVudDM1MTU5MDk1MA==,8699967,2017-12-14T02:37:19Z,2017-12-14T02:37:19Z,CONTRIBUTOR,"I second this request. I have had this same need before where I don't always know what variables I don't want, but I do know the variables that I do want.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,278389733
https://github.com/pydata/xarray/pull/1712#issuecomment-351247577,https://api.github.com/repos/pydata/xarray/issues/1712,351247577,MDEyOklzc3VlQ29tbWVudDM1MTI0NzU3Nw==,8699967,2017-12-13T01:06:14Z,2017-12-13T01:06:14Z,CONTRIBUTOR,"Would it be possible to put the coordinate generation into a separate function? It would be nice to pass in the affine, width, height, and is_2d as args and get back the spatial coordinates.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,273268690
https://github.com/pydata/xarray/issues/1736#issuecomment-346513920,https://api.github.com/repos/pydata/xarray/issues/1736,346513920,MDEyOklzc3VlQ29tbWVudDM0NjUxMzkyMA==,8699967,2017-11-23T01:23:54Z,2017-11-23T01:24:11Z,CONTRIBUTOR,"One thought I had was that there could be a similar parameter to [`mask_and_scale`](https://github.com/pydata/xarray/blob/master/xarray/backends/api.py#L154) added that could be just called `mask` so `open_rasterio` behaves similarly to the `open_dataset` api. The `mask` parameter can allow the user to decide if they want to convert to float to get a mask or leave it alone if they want to preserve the integer data.
I would vote for adding the _FillValue attribute as it conforms with the CF conventions and it will make the dataset work better with other software looking for this value if you write it out with `to_netcdf()`.
Also, on a similar vein, it would be nice to break out the bands into separate variables if it is a multi-band raster. This way, each band can store it's own nodata value and metadata separately in the dataset.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,276131376
https://github.com/pydata/xarray/issues/1474#issuecomment-314167150,https://api.github.com/repos/pydata/xarray/issues/1474,314167150,MDEyOklzc3VlQ29tbWVudDMxNDE2NzE1MA==,8699967,2017-07-10T16:53:25Z,2017-07-10T16:53:25Z,CONTRIBUTOR,"@fmaussion, thanks again for your time!","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,241714748
https://github.com/pydata/xarray/issues/1474#issuecomment-314162736,https://api.github.com/repos/pydata/xarray/issues/1474,314162736,MDEyOklzc3VlQ29tbWVudDMxNDE2MjczNg==,8699967,2017-07-10T16:38:39Z,2017-07-10T16:38:39Z,CONTRIBUTOR,Which is what I think you do in salem.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,241714748
https://github.com/pydata/xarray/issues/1474#issuecomment-314162500,https://api.github.com/repos/pydata/xarray/issues/1474,314162500,MDEyOklzc3VlQ29tbWVudDMxNDE2MjUwMA==,8699967,2017-07-10T16:37:56Z,2017-07-10T16:37:56Z,CONTRIBUTOR,"Oh, and to make the time slice work for WRF, I had to make the time variables consistent:
```python
xds.rename(
{
time_dim: 'time',
time_var: 'time',
},
inplace=True
)
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,241714748
https://github.com/pydata/xarray/issues/1474#issuecomment-314162219,https://api.github.com/repos/pydata/xarray/issues/1474,314162219,MDEyOklzc3VlQ29tbWVudDMxNDE2MjIxOQ==,8699967,2017-07-10T16:36:53Z,2017-07-10T16:36:53Z,CONTRIBUTOR,"OK. That is good to know.
In this case, I don't know the name if the dimension beforehand, so I thought it might be preferable to do:
```python
data = data.loc[{self.lsm_time_dim: [pd.to_datetime(time_step)]}]
```
instead of:
```python
data = data.sel(**{self.lsm_time_dim: [pd.to_datetime(time_step)]})
```
What are your thoughts?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,241714748
https://github.com/pydata/xarray/issues/1474#issuecomment-314159012,https://api.github.com/repos/pydata/xarray/issues/1474,314159012,MDEyOklzc3VlQ29tbWVudDMxNDE1OTAxMg==,8699967,2017-07-10T16:25:20Z,2017-07-10T16:25:20Z,CONTRIBUTOR,"OK. I feel silly now. I thought I should have been using loc[]
Thanks @fmaussion for that.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,241714748
https://github.com/pydata/xarray/issues/1474#issuecomment-314151625,https://api.github.com/repos/pydata/xarray/issues/1474,314151625,MDEyOklzc3VlQ29tbWVudDMxNDE1MTYyNQ==,8699967,2017-07-10T16:00:11Z,2017-07-10T16:02:35Z,CONTRIBUTOR,"I am having the same issue with a completely different grid:
```
dask.array
Coordinates:
* longitude (longitude) float32 248.0 248.25 248.5 248.75
* latitude (latitude) float32 40.75 40.5 40.25 40.0 39.75
* time (time) datetime64[ns] 2016-01-02 2016-01-02T01:00:00 ...
Attributes:
units: Pa
long_name: Surface pressure
standard_name: surface_air_pressure
```
Error:
```
self = DatetimeIndex(['2016-01-02 00:00:00', '2016-01-02 01:00:00',
'2016-01-02 02:00:00', '2016-01-02 03:00:0...:00:00',
'2016-01-04 22:00:00', '2016-01-04 23:00:00'],
dtype='datetime64[ns]', freq=None)
key = array(Timestamp('2016-01-02 00:00:00'), dtype=object)
def __getitem__(self, key):
""""""
This getitem defers to the underlying array, which by-definition can
only handle list-likes, slices, and integer scalars
""""""
is_int = is_integer(key)
if is_scalar(key) and not is_int:
raise ValueError
getitem = self._data.__getitem__
if is_int:
val = getitem(key)
return self._box_func(val)
else:
if com.is_bool_indexer(key):
key = np.asarray(key)
if key.all():
key = slice(0, None, None)
else:
key = lib.maybe_booleans_to_slice(key.view(np.uint8))
attribs = self._get_attributes_dict()
is_period = isinstance(self, ABCPeriodIndex)
if is_period:
freq = self.freq
else:
freq = None
if isinstance(key, slice):
if self.freq is not None and key.step is not None:
freq = key.step * self.freq
else:
freq = self.freq
attribs['freq'] = freq
> result = getitem(key)
E IndexError: arrays used as indices must be of integer (or boolean) type
../../../tethys/miniconda/envs/gssha/lib/python3.6/site-packages/pandas/core/indexes/datetimelike.py:296: IndexError
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,241714748
https://github.com/pydata/xarray/issues/1442#issuecomment-306657305,https://api.github.com/repos/pydata/xarray/issues/1442,306657305,MDEyOklzc3VlQ29tbWVudDMwNjY1NzMwNQ==,8699967,2017-06-07T01:11:21Z,2017-06-07T01:11:21Z,CONTRIBUTOR,I just did. Thanks!,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,233744905
https://github.com/pydata/xarray/issues/688#issuecomment-304077718,https://api.github.com/repos/pydata/xarray/issues/688,304077718,MDEyOklzc3VlQ29tbWVudDMwNDA3NzcxOA==,8699967,2017-05-25T17:55:15Z,2017-05-25T17:55:15Z,CONTRIBUTOR,Strange. But I can't seem to re-produce the issue. Maybe it was on a Windows machine or maybe it is fixed now.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,124154674
https://github.com/pydata/xarray/issues/688#issuecomment-304003816,https://api.github.com/repos/pydata/xarray/issues/688,304003816,MDEyOklzc3VlQ29tbWVudDMwNDAwMzgxNg==,8699967,2017-05-25T12:57:34Z,2017-05-25T12:57:34Z,CONTRIBUTOR,"@shoyer, thanks for looking into it. I am resampling from 3hr data to 1hr data.
```python
resampled_ds = ds.resample('1H', dim='time', keep_attrs=True)
```
I am using it here:
https://github.com/CI-WATER/gsshapy/blob/f4e5cb13c1d528021e1953859b712553a4162311/gsshapy/grid/grid_to_gssha.py#L789-L844
I ran into the issue there and had to add code to make sure the coordinates were copied.
Thanks!
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,124154674
https://github.com/pydata/xarray/issues/1395#issuecomment-298744168,https://api.github.com/repos/pydata/xarray/issues/1395,298744168,MDEyOklzc3VlQ29tbWVudDI5ODc0NDE2OA==,8699967,2017-05-02T19:59:32Z,2017-05-02T19:59:32Z,CONTRIBUTOR,"I did a
```
$ ncdump -v time file.nc
```
And I got:
```
...
float time(time) ;
time:units = ""minutes since 2011-03-05 03:00:00"" ;
time:long_name = ""time"" ;
time:time_increment = ""10800"" ;
time:begin_date = ""20110305"" ;
time:begin_time = ""030000"" ;
...
data:
time = _ ;
}
```
So, it looks like a bad file ...","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,225757620