cleanest way to modify a netcdf entry in xarray using nearest location and given time stamp
Question:
I want to modify the value of a netcdf array at a given index which is the nearest array entry to my chosen lat/lon coordinate and for a given date. I came up with the following solution using xarray‘s sel and loc but the loc command seems very longwinded with all the "values", using the online xarray manual and also this answer
ds=xr.open_dataset("test1.nc")
idx=ds.sel(lon=0,lat=20,time="1951-03-15",method="nearest")
ds["sit"].loc[dict(lon=idx.coords["lon"].values,lat=idx.coords["lat"].values,time=idx.coords["time"].values)]=100
ds.to_netcdf("test2.nc")
Is there is a shorter, neater way to do this task?
Answers:
You can pass DataArrays for the dictionary values to xr.DataArray.loc:
ds["sit"].loc[dict(lon=idx.lon,lat=idx.lat,time=idx.time)] = 100
I want to modify the value of a netcdf array at a given index which is the nearest array entry to my chosen lat/lon coordinate and for a given date. I came up with the following solution using xarray‘s sel and loc but the loc command seems very longwinded with all the "values", using the online xarray manual and also this answer
ds=xr.open_dataset("test1.nc")
idx=ds.sel(lon=0,lat=20,time="1951-03-15",method="nearest")
ds["sit"].loc[dict(lon=idx.coords["lon"].values,lat=idx.coords["lat"].values,time=idx.coords["time"].values)]=100
ds.to_netcdf("test2.nc")
Is there is a shorter, neater way to do this task?
You can pass DataArrays for the dictionary values to xr.DataArray.loc:
ds["sit"].loc[dict(lon=idx.lon,lat=idx.lat,time=idx.time)] = 100