滚动意味着持续到明年（xarray）
Rolling mean continuing into next year (xarray)
我有一个维度为（年：5，纬度：90，经度：180，月：12）的 xarray。我现在可以使用 计算 3 个月的滚动平均值
my_xarray = my_xarray.rolling(month=3).mean()
问题是滚动功能不会在前一年的 12 月后继续到下一年（即每年的 1 月和 2 月的图是空白的，因为它重新开始滚动 window每年）。
我可以通过某种方式指定它在到达月份列的末尾时跳转到下一年（和月份）的列吗？
希望我想要实现的目标是可以理解的。
感谢您的帮助！
编辑：
如果有帮助，这些就是我使用
时的结果
打印(my_xarray.dims) <xarray.DataArray (year: 5, lat: 90, lon: 180, month: 12)>
print(my_xarray) 在取滚动平均值之前：
-9.87300873e-02, -2.58998200e-03, -1.67404532e-01],
[ 5.95971942e-04, -2.02189982e-01, -3.97106633e-03, ...,
-9.64657962e-02, -3.48943099e-03, -1.64729238e-01],
[ 3.09602171e-03, -2.09298491e-01, -1.11376867e-02, ...,
-9.64361429e-02, -3.36983800e-03, -1.62733972e-01],
...,
[-6.85611367e-03, -1.94556922e-01, 4.57027294e-02, ...,
-8.56379271e-02, -4.38956916e-03, -1.74577653e-01],
[-4.64860350e-03, -2.00546771e-01, 3.28682028e-02, ...,
-8.63482431e-02, -5.57301566e-03, -1.73252046e-01],
[-4.17149812e-03, -2.02498823e-01, 2.37097144e-02, ...,
-8.98122042e-02, -4.10436466e-03, -1.72041461e-01]],
[[-6.76314309e-02, -5.28460778e-02, 1.12987854e-01, ...,
-1.75108999e-01, 1.14214182e-01, -9.38383192e-02],
[-3.71367447e-02, -1.19695403e-02, 6.92197084e-02, ...,
-1.66514024e-01, 1.31363243e-01, -1.02556169e-01],
[-5.75000793e-03, -1.72003862e-02, 5.47835231e-02, ...,
-1.55288070e-01, 1.24138020e-01, -1.03031531e-01],
...
-2.58931130e-01, 8.03834945e-02, -1.80395544e-01],
[ 3.55556488e-01, -7.68683434e-01, 3.21449339e-03, ...,
-2.84671545e-01, 5.23177236e-02, -1.65052935e-01],
[ 3.99193943e-01, -7.59860992e-01, 5.04764691e-02, ...,
-2.98249483e-01, 3.26042697e-02, -1.58649802e-01]],
[[ 3.25531572e-01, -4.28714514e-01, -1.47960767e-01, ...,
-1.24289311e-01, -3.02775592e-01, -3.59893829e-01],
[ 3.32164109e-01, -4.26804453e-01, -1.53042451e-01, ...,
-1.20779485e-01, -3.07494372e-01, -3.57666224e-01],
[ 3.45293462e-01, -4.26565051e-01, -1.55301645e-01, ...,
-1.20180212e-01, -3.11209410e-01, -3.45913649e-01],
...,
[ 2.99354017e-01, -4.30373788e-01, -1.71406969e-01, ...,
-1.09746858e-01, -2.76240230e-01, -3.72962207e-01],
[ 3.06181461e-01, -4.35510933e-01, -1.72495663e-01, ...,
-1.13980271e-01, -2.79644579e-01, -3.66411239e-01],
[ 3.18018258e-01, -4.34309036e-01, -1.64760321e-01, ...,
-1.23182893e-01, -2.91709840e-01, -3.65398616e-01]]]],
dtype=float32)
Coordinates:
* lon (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0
* lat (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0
height float64 2.0
* month (month) int64 1 2 3 4 5 6 7 8 9 10 11 12
* year (year) int64 2020 2021 2022 2023 2024
('year', 'lat', 'lon', 'month')
- 并且在采用滚动平均值之后：
my_xarray = my_xarray.rolling(月=3).均值()
打印（my_xarray）
<xarray.DataArray (year: 5, lat: 90, lon: 180, month: 12)>
array([[[[ nan, nan, -6.64931387e-02, ...,
-9.65834657e-02, -4.84402974e-02, -8.95748734e-02],
[ nan, nan, -6.85216933e-02, ...,
-9.58202779e-02, -4.96433278e-02, -8.82281562e-02],
[ nan, nan, -7.24467238e-02, ...,
-9.80513891e-02, -5.37225107e-02, -8.75133177e-02],
...,
[ nan, nan, -5.19034366e-02, ...,
-9.29711560e-02, -3.84746144e-02, -8.82017215e-02],
[ nan, nan, -5.74423869e-02, ...,
-9.49127277e-02, -4.14346159e-02, -8.83911053e-02],
[ nan, nan, -6.09868666e-02, ...,
-9.67354774e-02, -4.46880311e-02, -8.86526704e-02]],
[[ nan, nan, -2.49655296e-03, ...,
-3.19432567e-02, -3.28139116e-02, -5.15777121e-02],
[ nan, nan, 6.70447449e-03, ...,
-2.96478843e-02, -2.62145599e-02, -4.59023168e-02],
[ nan, nan, 1.06110424e-02, ...,
-2.02979098e-02, -2.67094250e-02, -4.47271963e-02],
...
[ nan, nan, -1.55030757e-01, ...,
-9.92223521e-02, -8.67839058e-02, -1.19647721e-01],
[ nan, nan, -1.36637489e-01, ...,
-1.22766892e-01, -1.13554617e-01, -1.32468919e-01],
[ nan, nan, -1.03396863e-01, ...,
-1.32896582e-01, -1.27950917e-01, -1.41431669e-01]],
[[ nan, nan, -8.37145646e-02, ...,
-6.00561102e-02, -1.46990995e-01, -2.62319565e-01],
[ nan, nan, -8.25609316e-02, ...,
-5.84986111e-02, -1.46998684e-01, -2.61980017e-01],
[ nan, nan, -7.88577447e-02, ...,
-5.79771499e-02, -1.48239036e-01, -2.59101093e-01],
...,
[ nan, nan, -1.00808918e-01, ...,
-5.09810448e-02, -1.30277574e-01, -2.52983093e-01],
[ nan, nan, -1.00608379e-01, ...,
-5.37393292e-02, -1.33528948e-01, -2.53345370e-01],
[ nan, nan, -9.36836998e-02, ...,
-5.75257987e-02, -1.41069442e-01, -2.60097106e-01]]]])
Coordinates:
* lon (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0
* lat (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0
height float64 2.0
* month (month) int64 1 2 3 4 5 6 7 8 9 10 11 12
* year (year) int64 2020 2021 2022 2023 2024
好的，滚动函数“重新启动”，因为月份维度对应不同的行，每年一行。
执行您想要的操作的一种方法如下。我创建了一些类似于您的虚拟数据，如下所示：
import numpy as np
import pandas as pd
import xarray as xr
da = xr.DataArray(
np.random.random(size=(2,12)),
dims=("year","month"),
coords={"month":np.linspace(1, 12, num=12).astype(int),
"year":[2000,2001]
},
)
print(da)
然后我使用堆栈方法创建了一个结合了年和月的新维度，并在该维度上应用了滚动 window:
my_xarray = da.stack(z=("year", "month")).rolling(z=3).mean()
print(my_xarray)
好像给了你想要的：
xarray.DataArrayz: 24
array([ nan, nan, 0.60642737, 0.67814489, 0.44616648,
0.45587241, 0.36101104, 0.33491579, 0.39246105, 0.42972596,
0.54526778, 0.55617721, 0.46796958, 0.46491759, 0.44476617,
0.47922742, 0.58516182, 0.55660812, 0.4536117 , 0.33743334,
0.27727016, 0.3451959 , 0.49314071, 0.63349366])
Coordinates:
z
(z)
MultiIndex
(year, month)
array([(2000, 1), (2000, 2), (2000, 3), (2000, 4), (2000, 5), (2000, 6),
(2000, 7), (2000, 8), (2000, 9), (2000, 10), (2000, 11), (2000, 12),
(2001, 1), (2001, 2), (2001, 3), (2001, 4), (2001, 5), (2001, 6),
(2001, 7), (2001, 8), (2001, 9), (2001, 10), (2001, 11), (2001, 12)],
dtype=object)
year
(z)
int64
2000 2000 2000 ... 2001 2001 2001
array([2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000,
2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001])
month
(z)
int64
1 2 3 4 5 6 7 ... 6 7 8 9 10 11 12
array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6,
7, 8, 9, 10, 11, 12])
我有一个维度为（年：5，纬度：90，经度：180，月：12）的 xarray。我现在可以使用 计算 3 个月的滚动平均值
my_xarray = my_xarray.rolling(month=3).mean()
问题是滚动功能不会在前一年的 12 月后继续到下一年（即每年的 1 月和 2 月的图是空白的，因为它重新开始滚动 window每年）。
我可以通过某种方式指定它在到达月份列的末尾时跳转到下一年（和月份）的列吗？
希望我想要实现的目标是可以理解的。 感谢您的帮助！
编辑： 如果有帮助，这些就是我使用
时的结果打印(my_xarray.dims)
<xarray.DataArray (year: 5, lat: 90, lon: 180, month: 12)>print(my_xarray) 在取滚动平均值之前：
-9.87300873e-02, -2.58998200e-03, -1.67404532e-01],
[ 5.95971942e-04, -2.02189982e-01, -3.97106633e-03, ...,
-9.64657962e-02, -3.48943099e-03, -1.64729238e-01],
[ 3.09602171e-03, -2.09298491e-01, -1.11376867e-02, ...,
-9.64361429e-02, -3.36983800e-03, -1.62733972e-01],
...,
[-6.85611367e-03, -1.94556922e-01, 4.57027294e-02, ...,
-8.56379271e-02, -4.38956916e-03, -1.74577653e-01],
[-4.64860350e-03, -2.00546771e-01, 3.28682028e-02, ...,
-8.63482431e-02, -5.57301566e-03, -1.73252046e-01],
[-4.17149812e-03, -2.02498823e-01, 2.37097144e-02, ...,
-8.98122042e-02, -4.10436466e-03, -1.72041461e-01]],
[[-6.76314309e-02, -5.28460778e-02, 1.12987854e-01, ...,
-1.75108999e-01, 1.14214182e-01, -9.38383192e-02],
[-3.71367447e-02, -1.19695403e-02, 6.92197084e-02, ...,
-1.66514024e-01, 1.31363243e-01, -1.02556169e-01],
[-5.75000793e-03, -1.72003862e-02, 5.47835231e-02, ...,
-1.55288070e-01, 1.24138020e-01, -1.03031531e-01],
...
-2.58931130e-01, 8.03834945e-02, -1.80395544e-01],
[ 3.55556488e-01, -7.68683434e-01, 3.21449339e-03, ...,
-2.84671545e-01, 5.23177236e-02, -1.65052935e-01],
[ 3.99193943e-01, -7.59860992e-01, 5.04764691e-02, ...,
-2.98249483e-01, 3.26042697e-02, -1.58649802e-01]],
[[ 3.25531572e-01, -4.28714514e-01, -1.47960767e-01, ...,
-1.24289311e-01, -3.02775592e-01, -3.59893829e-01],
[ 3.32164109e-01, -4.26804453e-01, -1.53042451e-01, ...,
-1.20779485e-01, -3.07494372e-01, -3.57666224e-01],
[ 3.45293462e-01, -4.26565051e-01, -1.55301645e-01, ...,
-1.20180212e-01, -3.11209410e-01, -3.45913649e-01],
...,
[ 2.99354017e-01, -4.30373788e-01, -1.71406969e-01, ...,
-1.09746858e-01, -2.76240230e-01, -3.72962207e-01],
[ 3.06181461e-01, -4.35510933e-01, -1.72495663e-01, ...,
-1.13980271e-01, -2.79644579e-01, -3.66411239e-01],
[ 3.18018258e-01, -4.34309036e-01, -1.64760321e-01, ...,
-1.23182893e-01, -2.91709840e-01, -3.65398616e-01]]]],
dtype=float32)
Coordinates:
* lon (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0
* lat (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0
height float64 2.0
* month (month) int64 1 2 3 4 5 6 7 8 9 10 11 12
* year (year) int64 2020 2021 2022 2023 2024
('year', 'lat', 'lon', 'month')
- 并且在采用滚动平均值之后： my_xarray = my_xarray.rolling(月=3).均值() 打印（my_xarray）
<xarray.DataArray (year: 5, lat: 90, lon: 180, month: 12)>
array([[[[ nan, nan, -6.64931387e-02, ...,
-9.65834657e-02, -4.84402974e-02, -8.95748734e-02],
[ nan, nan, -6.85216933e-02, ...,
-9.58202779e-02, -4.96433278e-02, -8.82281562e-02],
[ nan, nan, -7.24467238e-02, ...,
-9.80513891e-02, -5.37225107e-02, -8.75133177e-02],
...,
[ nan, nan, -5.19034366e-02, ...,
-9.29711560e-02, -3.84746144e-02, -8.82017215e-02],
[ nan, nan, -5.74423869e-02, ...,
-9.49127277e-02, -4.14346159e-02, -8.83911053e-02],
[ nan, nan, -6.09868666e-02, ...,
-9.67354774e-02, -4.46880311e-02, -8.86526704e-02]],
[[ nan, nan, -2.49655296e-03, ...,
-3.19432567e-02, -3.28139116e-02, -5.15777121e-02],
[ nan, nan, 6.70447449e-03, ...,
-2.96478843e-02, -2.62145599e-02, -4.59023168e-02],
[ nan, nan, 1.06110424e-02, ...,
-2.02979098e-02, -2.67094250e-02, -4.47271963e-02],
...
[ nan, nan, -1.55030757e-01, ...,
-9.92223521e-02, -8.67839058e-02, -1.19647721e-01],
[ nan, nan, -1.36637489e-01, ...,
-1.22766892e-01, -1.13554617e-01, -1.32468919e-01],
[ nan, nan, -1.03396863e-01, ...,
-1.32896582e-01, -1.27950917e-01, -1.41431669e-01]],
[[ nan, nan, -8.37145646e-02, ...,
-6.00561102e-02, -1.46990995e-01, -2.62319565e-01],
[ nan, nan, -8.25609316e-02, ...,
-5.84986111e-02, -1.46998684e-01, -2.61980017e-01],
[ nan, nan, -7.88577447e-02, ...,
-5.79771499e-02, -1.48239036e-01, -2.59101093e-01],
...,
[ nan, nan, -1.00808918e-01, ...,
-5.09810448e-02, -1.30277574e-01, -2.52983093e-01],
[ nan, nan, -1.00608379e-01, ...,
-5.37393292e-02, -1.33528948e-01, -2.53345370e-01],
[ nan, nan, -9.36836998e-02, ...,
-5.75257987e-02, -1.41069442e-01, -2.60097106e-01]]]])
Coordinates:
* lon (lon) float64 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0
* lat (lat) float64 -89.0 -87.0 -85.0 -83.0 -81.0 ... 83.0 85.0 87.0 89.0
height float64 2.0
* month (month) int64 1 2 3 4 5 6 7 8 9 10 11 12
* year (year) int64 2020 2021 2022 2023 2024
好的，滚动函数“重新启动”，因为月份维度对应不同的行，每年一行。
执行您想要的操作的一种方法如下。我创建了一些类似于您的虚拟数据，如下所示：
import numpy as np
import pandas as pd
import xarray as xr
da = xr.DataArray(
np.random.random(size=(2,12)),
dims=("year","month"),
coords={"month":np.linspace(1, 12, num=12).astype(int),
"year":[2000,2001]
},
)
print(da)
然后我使用堆栈方法创建了一个结合了年和月的新维度，并在该维度上应用了滚动 window:
my_xarray = da.stack(z=("year", "month")).rolling(z=3).mean()
print(my_xarray)
好像给了你想要的：
xarray.DataArrayz: 24
array([ nan, nan, 0.60642737, 0.67814489, 0.44616648,
0.45587241, 0.36101104, 0.33491579, 0.39246105, 0.42972596,
0.54526778, 0.55617721, 0.46796958, 0.46491759, 0.44476617,
0.47922742, 0.58516182, 0.55660812, 0.4536117 , 0.33743334,
0.27727016, 0.3451959 , 0.49314071, 0.63349366])
Coordinates:
z
(z)
MultiIndex
(year, month)
array([(2000, 1), (2000, 2), (2000, 3), (2000, 4), (2000, 5), (2000, 6),
(2000, 7), (2000, 8), (2000, 9), (2000, 10), (2000, 11), (2000, 12),
(2001, 1), (2001, 2), (2001, 3), (2001, 4), (2001, 5), (2001, 6),
(2001, 7), (2001, 8), (2001, 9), (2001, 10), (2001, 11), (2001, 12)],
dtype=object)
year
(z)
int64
2000 2000 2000 ... 2001 2001 2001
array([2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000, 2000,
2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001])
month
(z)
int64
1 2 3 4 5 6 7 ... 6 7 8 9 10 11 12
array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6,
7, 8, 9, 10, 11, 12])