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3 rows where state = "closed", type = "issue" and user = 2014301 sorted by updated_at descending
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| id | node_id | number | title | user | state | locked | assignee | milestone | comments | created_at | updated_at ▲ | closed_at | author_association | active_lock_reason | draft | pull_request | body | reactions | performed_via_github_app | state_reason | repo | type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 435535284 | MDU6SXNzdWU0MzU1MzUyODQ= | 2912 | Writing a netCDF file is unexpectedly slow | msaharia 2014301 | closed | 0 | 12 | 2019-04-21T18:31:36Z | 2023-09-12T15:58:18Z | 2023-09-12T15:58:18Z | NONE | ```python ncdat=xr.open_mfdataset(nclist, concat_dim='time') ncdat['lat']=ncdat['lat'].isel(time=0).drop('time') ncdat['lon']=ncdat['lon'].isel(time=0).drop('time') ncdat=ncdat.rename({'north_south':'lat', 'east_west':'lon'}) lat_coords=ncdat.lat[:,0] #Extract latitudes lon_coords=ncdat.lon[0,:] #Extract longitudes ncdat=ncdat.drop(['lat','lon']) reformatted_ncdat=ncdat.assign_coords(lat=lat_coords,lon=lon_coords, time=ncdat.coords['time']) ncdat = reformatted_ncdat.sortby('time') ncdat.to_netcdf('testing.nc') ``` Problem descriptionAfter some processing, I am left with this xarray dataset
How can I expedite this process? Is there anything wrong with the structure of Expected OutputA netCDF file Output of
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completed | xarray 13221727 | issue | ||||||
| 455200681 | MDU6SXNzdWU0NTUyMDA2ODE= | 3017 | Why am I running into a IndexVariable error message while assigning dims? | msaharia 2014301 | closed | 0 | 1 | 2019-06-12T13:01:44Z | 2020-04-06T22:43:53Z | 2020-04-06T22:43:53Z | NONE | Code Sample, a copy-pastable example if possibleI am trying to remove the (north_south, east_west) from ```python ncdat = xr.open_mfdataset(files_lis) ncdat['lat']=ncdat['lat'].isel(time=0).drop('time') ncdat['lon']=ncdat['lon'].isel(time=0).drop('time') ncdat=ncdat.rename({'north_south':'lat', 'east_west':'lon'}) lat_coords = ncdat['lat'].values[:,-1] #Extract latitudes lon_coords = ncdat['lon'].values[-1,:] #Extract longitudes reformatted_ncdat=ncdat.assign_coords(lat=lat_coords, lon=lon_coords, time=ncdat.coords['time']) ``` Problem descriptionThis is Error
Expected OutputPlease ignore values. Just an illustration.
Output of
|
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completed | xarray 13221727 | issue | ||||||
| 392816513 | MDU6SXNzdWUzOTI4MTY1MTM= | 2623 | Why is my export to netcdf command leading to a __truediv__ error? | msaharia 2014301 | closed | 0 | 7 | 2018-12-19T23:16:14Z | 2018-12-24T15:58:03Z | 2018-12-24T15:58:03Z | NONE | Code Sample, a copy-pastable example if possible```python import numpy as np import xarray as xr import glob, os NCDIR = './output/out/' finalfile = 'summaout.nc' outfilelist = glob.glob((NCDIR+'/{}.nc').format('basin_*timestep')) ds=xr.open_mfdataset(outfilelist, concat_dim='hru') replace = ds['pptrate'] runoff = ds['averageInstantRunoff'].values runoff = np.squeeze(runoffdata, axis=2) runoff = runoff.transpose() replace.values = runoff ncconvert = ds.drop('averageInstantRunoff') runoffarray = xr.DataArray(runoff, dims=['time','hru']) ds['averageInstantRunoff'] = runoffarray ds.to_netcdf('test.nc') ``` Problem descriptionThis is
Expected OutputnetCDF Output of
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completed | xarray 13221727 | issue |
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