[英]How to flatten an xarray dataset into a 1D numpy array?
Is there a simple way of flattening an xarray dataset into a single 1D numpy array? 有没有一种简单的方法可以将xarray数据集展平为单个1D numpy数组?
For example, flattening the following test dataset: 例如,展平以下测试数据集:
xr.Dataset({
'a' : xr.DataArray(
data=[10,11,12,13,14],
coords={'x':[0,1,2,3,4]},
dims={'x':5}
),
'b' : xr.DataArray(data=1,coords={'y':0}),
'c' : xr.DataArray(data=2,coords={'y':0}),
'd' : xr.DataArray(data=3,coords={'y':0})
})
to 至
[10,11,12,13,14,1,2,3]
? ?
If you're OK with repeated values, you can use .to_array()
and then flatten the values in NumPy, eg, 如果您对重复值没有问题,可以使用
.to_array()
然后在NumPy中展平值,例如,
>>> ds.to_array().values.ravel()
array([10, 11, 12, 13, 14, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3,
3, 3, 3])
If you don't want repeated values, then you'll need to write something yourself, eg, 如果你不想重复值,那么你需要自己写一些东西,例如,
>>> np.concatenate([v.values.ravel() for v in ds.data_vars.values()])
array([10, 11, 12, 13, 14, 1, 2, 3])
More generally, this sounds somewhat similar to a proposed interface for "stacking" data variables in 2D for machine learning applications: https://github.com/pydata/xarray/issues/1317 更一般地说,这听起来有点类似于为机器学习应用程序在2D中“堆叠”数据变量的建议接口: https : //github.com/pydata/xarray/issues/1317
Get Dataset from question: 从问题中获取数据集:
ds = xr.Dataset({
'a' : xr.DataArray(
data=[10,11,12,13,14],
coords={'x':[0,1,2,3,4]},
dims={'x':5}
),
'b' : xr.DataArray(data=1,coords={'y':0}),
'c' : xr.DataArray(data=2,coords={'y':0}),
'd' : xr.DataArray(data=3,coords={'y':0})
})
Get the list of data variables: 获取数据变量列表:
variables = ds.data_vars
Use the np.flatten()
method to reduce arrays to 1D: 使用
np.flatten()
方法将数组减少到1D:
arrays = [ ds[i].values.flatten() for i in variables ]
Then expand list of 1D arrays (as detailed in this answer ): 然后展开1D数组列表( 详见本答复 ):
arrays = [i for j in arrays for i in j ]
Now convert this to an array as requested in Q (as currently a list): 现在将其转换为Q中请求的数组(目前是列表):
array = np.array(arrays)
截至2019年7月,xarray现在具有执行此功能的to_stacked_array和to_unstacked_dataset函数。
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