Question

是否可以删除xarray数据集中包含的DataArrays值，以便xr_dataset在下面的示例代码中转换为xr_flat？

import xarray as xr
import numpy as np
n = np.nan

a = np.array([[n,n,1],
              [1,2,2],
              [2,n,n]], dtype='float32')
b = np.random.rand(3,3)
xr_dataset = xr.Dataset({'a': xr.DataArray(a, dims=['x', 'y']),
                         'b': xr.DataArray(b, dims=['x', 'y'])})

a_flat = a[np.isfinite(a)]
b_flat = b[np.isfinite(a)]

xr_flat = xr.Dataset({'a': xr.DataArray(a_flat),
                      'b': xr.DataArray(b_flat)})

Answer 1

您可以使用xarray的stack和where方法执行此操作。为了与你的例子保持一致，我也删除了x / y坐标，但这并不是严格要求的。关键部分是：

使用堆叠将x / y变暗展平为dim_0
使用where与drop=True一起屏蔽并仅选择有限元素

这是一个例子，从你离开的地方开始......

In [2]: ds_stack = xr_dataset.stack(dim_0=('x', 'y'))

In [3]: ds_stack = ds_stack.reset_index('dim_0').drop(['x', 'y'])

In [4]: ds_stack.where(np.isfinite(ds_stack['a']), drop=True)
Out[4]:
<xarray.Dataset>
Dimensions:  (dim_0: 5)
Dimensions without coordinates: dim_0
Data variables:
    a        (dim_0) float32 1.0 1.0 2.0 2.0 2.0
    b        (dim_0) float64 0.8642 0.05446 0.3728 0.7797 0.9501

In [5]: xr_flat
Out[5]:
<xarray.Dataset>
Dimensions:  (dim_0: 5)
Dimensions without coordinates: dim_0
Data variables:
    a        (dim_0) float32 1.0 1.0 2.0 2.0 2.0
    b        (dim_0) float64 0.8642 0.05446 0.3728 0.7797 0.9501

删除值并展平xarray Dataset的DataArrays

1 个答案: