沿 xarray 中的单个维度对多个坐标进行分组

Question

I have an xarray with multiple coordinates along a single dimension. In the example below, coords a and b are defined along dimension dim1 . How would I groupby using two coordinates that are defined along the same dimension(s)? Unlike this question , I am not trying to group along different dimensions, but a single one.

import xarray as xr

d = xr.DataArray([[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]],
    coords={
        'a': ('dim1',['A', 'A', 'B', 'B']),
        'b': ('dim1',['1', '2', '1', '2']),
        'c': ('dim2',['x', 'y', 'z'])
    },
    dims=['dim1', 'dim2'])
d.groupby(['a','b']) # this gives: TypeError: `group` must be an xarray.DataArray or the name of an xarray variable or dimension

Answer 1

This is my current workaround:

import numpy as np
import xarray as xr

def groupby_multicoords(da, fields):
    common_dim = da.coords[fields[0]].dims[0]
    tups_arr = np.empty(len(da[common_dim]), dtype=object)
    tups_arr[:] = list(zip(*(da[f].values for f in fields)))
    return da.assign_coords(grouping_zip=xr.DataArray(tups_arr, dims=common_dim)).groupby('grouping_zip')

and then, groupby_multicoords(da=d, fields=['a', 'b'])

However, after grouping I am still left with the 'grouping_zip' coord. I would be grateful to replace it with d.groupby(['a','b']) ..

Answer 2

您可以使用.stack(new=[“dim1”,”dim2”)它们堆叠到单个 MultiIndex 中，然后按该维度.stack(new=[“dim1”,”dim2”) 。