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  • kmuehlbauer · 5 ✖

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  • Y-axis flipped when reading data with Xarray · 5 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1469467986 https://github.com/pydata/xarray/issues/7621#issuecomment-1469467986 https://api.github.com/repos/pydata/xarray/issues/7621 IC_kwDOAMm_X85Xlk1S kmuehlbauer 5821660 2023-03-15T07:15:47Z 2023-03-15T07:15:47Z MEMBER

@RY4GIT Glad you can use the code. And good there's a way to use the data as is without tampering.

Regarding the different rasterio-approaches, just to be on the same page. The code I provided above (with the fn_NASA_Earthdata_download file) works for you too, but with fn_NSIDC_output it does not? Out of the box, the second also doesn't work for me. Didn't check this.

I've no immediate idea, what's going on in that case. The only thing I can think of is, that in the conversion process something has gone wrong with the georeferencing and/or the image origin. I hope you can figure that out, eventually.

Here for reference my package versions:

INSTALLED VERSIONS ------------------ commit: None python: 3.10.5 | packaged by conda-forge | (main, Jun 14 2022, 07:06:46) [GCC 10.3.0] python-bits: 64 OS: Linux OS-release: 5.14.21-150400.24.46-default machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: de_DE.UTF-8 LOCALE: ('de_DE', 'UTF-8') libhdf5: 1.12.2 libnetcdf: 4.9.1 xarray: 2023.2.1.dev22+g49ae0f8d.d20230310 pandas: 1.4.2 numpy: 1.23.5 scipy: 1.9.1 netCDF4: 1.6.2 pydap: None h5netcdf: 1.1.0 h5py: 3.8.0 Nio: None zarr: 2.12.0 cftime: 1.5.1.1 nc_time_axis: 1.4.1 PseudoNetCDF: None rasterio: 1.3.6 cfgrib: None iris: 3.2.1 bottleneck: 1.3.5 dask: 2022.10.0 distributed: 2022.10.0 matplotlib: 3.6.3 cartopy: 0.21.1 seaborn: None numbagg: None fsspec: 2023.1.0 cupy: None pint: 0.17 sparse: None flox: None numpy_groupies: None setuptools: 59.2.0 pip: 21.3.1 conda: None pytest: 7.1.2 mypy: None IPython: 8.2.0 sphinx: None rioxarray: 0.13.3 gdal: 3.6.2 pyproj: 3.4.1 PROJ: 9.1.1
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  Y-axis flipped when reading data with Xarray 1622197017
1468375177 https://github.com/pydata/xarray/issues/7621#issuecomment-1468375177 https://api.github.com/repos/pydata/xarray/issues/7621 IC_kwDOAMm_X85XhaCJ kmuehlbauer 5821660 2023-03-14T15:58:20Z 2023-03-14T15:58:20Z MEMBER

@RY4GIT I forgot to add my package versions. I'll add them the next day. But I'm pretty sure to have the most recent one's installed in a Python 3.10 conda-forge environment.

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  Y-axis flipped when reading data with Xarray 1622197017
1467552710 https://github.com/pydata/xarray/issues/7621#issuecomment-1467552710 https://api.github.com/repos/pydata/xarray/issues/7621 IC_kwDOAMm_X85XeRPG kmuehlbauer 5821660 2023-03-14T07:40:28Z 2023-03-14T07:41:24Z MEMBER

For the rasterio-approach:

python ds_NASA_download_rasterio = xr.open_dataset(os.path.join(input_path, fn_NASA_Earthdata_download), engine='rasterio') ds_NASA_download_rasterio = ds_NASA_download_rasterio.set_coords(["cell_lat", "cell_lon"]) ds_NASA_download_rasterio.Geophysical_Data_precipitation_total_surface_flux[0].plot(y="cell_lat", x="cell_lon")

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  Y-axis flipped when reading data with Xarray 1622197017
1467520091 https://github.com/pydata/xarray/issues/7621#issuecomment-1467520091 https://api.github.com/repos/pydata/xarray/issues/7621 IC_kwDOAMm_X85XeJRb kmuehlbauer 5821660 2023-03-14T07:21:30Z 2023-03-14T07:35:37Z MEMBER

First, I've found this on SO: https://gis.stackexchange.com/questions/454543/fixing-the-flipped-inverted-y-axis-in-the-xarray-with-rasterio

For your data reading method 1, it works for me like this:

```python

load root group with coordinates

ds_NSIDC_root = xr.open_dataset(os.path.join(input_path, fn_NSIDC_output), group="/", engine='netcdf4')

load data from Geophysical_Data group

ds_NSIDC_precip = xr.open_dataset(os.path.join(input_path, fn_NSIDC_output), group="Geophysical_Data", engine='netcdf4')

merge groups

ds_NSIDC = xr.merge([ds_NSIDC_root, ds_NSIDC_precip])

plot

ds_NSIDC.precipitation_total_surface_flux.plot()

the above is essentially the same as

ds_NSIDC.precipitation_total_surface_flux.plot(x="x", y="y")

```

This can be expanded to use the cell_lon/cell_lat:

```

set lat/lon as coords

ds_NSIDC = ds_NSIDC.set_coords(["cell_lon", "cell_lat"]) ds_NSIDC.precipitation_total_surface_flux.plot(x="cell_lon", y="cell_lat") ```

Update: This should also work like above when directly using NASA Earth Data.

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  Y-axis flipped when reading data with Xarray 1622197017
1466920659 https://github.com/pydata/xarray/issues/7621#issuecomment-1466920659 https://api.github.com/repos/pydata/xarray/issues/7621 IC_kwDOAMm_X85Xb27T kmuehlbauer 5821660 2023-03-13T20:36:54Z 2023-03-13T20:36:54Z MEMBER

@RY4GIT You would need to assign cell_lat/cell_lon as coordinates of the dataset and then use x="cell_lon" and y="cell_lat" in the call to .plot().

Plotting without that, will use the dimension coordinates (x,y) and there might be a difference in origin (upper vs. lower).

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  Y-axis flipped when reading data with Xarray 1622197017

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