如何通过 xarray 中的坐标组合二维平铺数据集

Question

我正在开展一个项目，我需要在 Xarray 中将不同的地理图像图块组合成一个大图块。我运行遇到了问题。我在下面做了一个简化的例子。

square1 = xr.DataArray(name="box1", data=np.random.randint(5, size=(3, 2)), coords=[("x", [0,1,2]),('y',[0,1])])
square2 = xr.DataArray(name="box2", data=np.random.randint(5, size=(3, 2)), coords=[("x", [3,4,5]),('y',[0,1])])
square3 = xr.DataArray(name="box3", data=np.random.randint(5, size=(3, 2)), coords=[("x", [0,1,2]),('y',[2,3])])
square4 = xr.DataArray(name="box4", data=np.random.randint(5, size=(3, 2)), coords=[("x", [3,4,5]),('y',[2,3])])

combineddata = xr.combine_by_coords([square1,square2,square3,square4])

我以为这就是您需要做的全部，但我收到了这个错误

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-57-fc5add80d55a> in <module>
----> 1 xr.combine_by_coords([square1,square2,square3,square4])

~/my-conda-envs/dem/lib/python3.8/site-packages/xarray/core/combine.py in combine_by_coords(datasets, compat, data_vars, coords, fill_value, join, combine_attrs)
    713 
    714     # Group by data vars
--> 715     sorted_datasets = sorted(datasets, key=vars_as_keys)
    716     grouped_by_vars = itertools.groupby(sorted_datasets, key=vars_as_keys)
    717 

~/my-conda-envs/dem/lib/python3.8/site-packages/xarray/core/combine.py in vars_as_keys(ds)
    502 
    503 def vars_as_keys(ds):
--> 504     return tuple(sorted(ds))
    505 
    506 

~/my-conda-envs/dem/lib/python3.8/site-packages/xarray/core/common.py in __bool__(self)
    118 
    119     def __bool__(self: Any) -> bool:
--> 120         return bool(self.values)
    121 
    122     def __float__(self: Any) -> float:

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

我做错了什么？

Answer 1

Xarray combine_by_coords 目前仅适用于 xarray Dataset 对象，不适用于 DataArray 对象。看到这个问题：https://github.com/pydata/xarray/issues/3248。 @dcherian 提供的解决方法是将 DataArray 转换为数据集，合并，然后再转换回 DataArray。

所以这有效：

import numpy as np
import xarray as xr

square1 = xr.DataArray(name="box", data=np.random.randint(5, size=(3, 2)), coords=[("x", [0,1,2]),('y',[0,1])]) 
square2 = xr.DataArray(name="box", data=np.random.randint(5, size=(3, 2)), coords=[("x", [3,4,5]),('y',[0,1])]) 
square3 = xr.DataArray(name="box", data=np.random.randint(5, size=(3, 2)), coords=[("x", [0,1,2]),('y',[2,3])]) 
square4 = xr.DataArray(name="box", data=np.random.randint(5, size=(3, 2)), coords=[("x", [3,4,5]),('y',[2,3])]) 

combineddata = xr.combine_by_coords(sq.to_dataset() for sq in [square1,square2,square3,square4]).to_array()

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