无法使用numpy.isin公司xarray DataArray中的函数

Question

我有一个名为da_temp的xarray数据数组。它有维度time、latitude和longitude。你知道吗

time维度是一个小时数据，其坐标范围为2009-01-01T00:00:00到2009-12-31T23:00:00。你知道吗

<xarray.DataArray 'T_SFC' (time: 8760, latitude: 106, longitude: 193)>
array([[[13.609406, 13.613037, ..., 16.048492, 16.065308],
        [13.634644, 13.638123, ..., 16.062683, 16.07788 ],
        ...,
        [21.507715, 21.5213  , ..., 20.858679, 21.26879 ],
        [21.344576, 21.364063, ..., 20.826727, 21.127975]],

       [[13.616699, 13.617249, ..., 16.098816, 16.11792 ],
        [13.639832, 13.63916 , ..., 16.12085 , 16.137512],
        ...,
        [23.225473, 23.222776, ..., 21.637125, 22.041592],
        [23.069414, 23.077639, ..., 21.623928, 21.91626 ]],

       ...,

       [[14.325562, 14.323853, ..., 19.051544, 19.004974],
        [14.305298, 14.306183, ..., 19.011719, 18.970123],
        ...,
        [24.70183 , 24.588383, ..., 18.064957, 18.364614],
        [25.497314, 24.317244, ..., 17.94168 , 18.119926]],

       [[14.595551, 14.583862, ..., 18.971344, 18.976532],
        [14.529541, 14.525635, ..., 18.963531, 18.966766],
        ...,
        [25.039097, 24.982517, ..., 19.516224, 19.818233],
        [25.338848, 25.875378, ..., 19.330383, 19.520332]]], dtype=float32)
Coordinates:
  * latitude   (latitude) float32 -39.2 -39.149525 ... -33.950478 -33.9
  * longitude  (longitude) float32 140.8 140.84792 140.89584 ... 149.95209 150.0
  * time       (time) datetime64[ns] 2009-01-01 ... 2009-12-31T23:00:00
Attributes:
    projectionType:  MERCATOR
    level:           SFC
    units:           C
    gridType:        SCALAR
    lonCentre:       145.4
    latIntersect:    0.0

我只想选择一年前6个月的数据，即1月、2月、3月、4月、5月和6月。我试图使用np.isin检查time坐标中的月份是否在[1、2、3、4、5、6]列表中，但收到了一个错误。你知道吗

import numpy as np
import xarray as xr
MTHS = [1, 2, 3, 4, 5, 6]
da_mask = xr.where(np.isin(da_temp.time.dt.month.values, MTHS), da_temp, 0)

---

ValueError                                Traceback (most recent call last)
<ipython-input-72-7fee7a634922> in <module>
----> 1 da_autumn = xr.where(np.isin(da_temp.time.dt.month.values, autumn_mth_list), da_temp, 0)
      2 da_autumn.values

~\anaconda3\envs\PlannedBurnWindow\lib\site-packages\xarray\core\computation.py in where(cond, x, y)
   1115                        join='exact',
   1116                        dataset_join='exact',
-> 1117                        dask='allowed')

~\anaconda3\envs\PlannedBurnWindow\lib\site-packages\xarray\core\computation.py in apply_ufunc(func, input_core_dims, output_core_dims, exclude_dims, vectorize, join, dataset_join, dataset_fill_value, keep_attrs, kwargs, dask, output_dtypes, output_sizes, *args)
    967                                      join=join,
    968                                      exclude_dims=exclude_dims,
--> 969                                      keep_attrs=keep_attrs)
    970     elif any(isinstance(a, Variable) for a in args):
    971         return variables_vfunc(*args)

~\anaconda3\envs\PlannedBurnWindow\lib\site-packages\xarray\core\computation.py in apply_dataarray_vfunc(func, signature, join, exclude_dims, keep_attrs, *args)
    216 
    217     data_vars = [getattr(a, 'variable', a) for a in args]
--> 218     result_var = func(*data_vars)
    219 
    220     if signature.num_outputs > 1:

~\anaconda3\envs\PlannedBurnWindow\lib\site-packages\xarray\core\computation.py in apply_variable_ufunc(func, signature, exclude_dims, dask, output_dtypes, output_sizes, keep_attrs, *args)
    563             raise ValueError('unknown setting for dask array handling in '
    564                              'apply_ufunc: {}'.format(dask))
--> 565     result_data = func(*input_data)
    566 
    567     if signature.num_outputs == 1:

~\anaconda3\envs\PlannedBurnWindow\lib\site-packages\xarray\core\duck_array_ops.py in where(condition, x, y)
    191 def where(condition, x, y):
    192     """Three argument where() with better dtype promotion rules."""
--> 193     return _where(condition, *as_shared_dtype([x, y]))
    194 
    195 

~\anaconda3\envs\PlannedBurnWindow\lib\site-packages\xarray\core\duck_array_ops.py in f(*args, **kwargs)
     42             else:
     43                 wrapped = getattr(eager_module, name)
---> 44             return wrapped(*args, **kwargs)
     45     else:
     46         def f(*args, **kwargs):

ValueError: operands could not be broadcast together with shapes (8760,) (8760,106,193) () 

Answer 1

如果你只想抽出时间的一小部分，这就可以了。你知道吗

airtemps = xr.tutorial.open_dataset('air_temperature')

airtemps['air'].sel(time=slice('2013-01-01','2013-06-30'))

Answer 2

问题是np.isin返回一个NumPy数组（即没有标记的维度），因此xarray无法自动找出如何在where中适当地广播它。你知道吗

我建议改用xarray的内置^{}方法，它可以处理（并返回）标记的数据数组：

da_mask = xr.where(da_temp.time.dt.month.isin(MTHS), da_temp, 0)