滚动均值持续到明年 (xarray)

Posted 2023-03-12

【中文标题】滚动均值持续到明年 (xarray)

【英文标题】：Rolling mean continuing into next year (xarray)

【发布时间】：2021-12-18 12:47:34

【问题描述】：

我有一个尺寸为（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()

问题是滚动功能在上一年的 12 月之后不会继续到下一年（即每年 1 月和 2 月的图都是空白的，因为它每年都重新开始滚动窗口）。

我能否以某种方式指定它应该在到达月末列时跳转到下一年（和月份）列？

希望我想要实现的目标是可以理解的。 感谢您的帮助！

编辑： 如果它有帮助，那是我使用时的结果

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')

在取滚动平均值之后： my_xarray = my_xarray.rolling(月=3).mean() 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

【问题讨论】：

请提供您的数据和当前代码的示例或示例，以便我们可以使用一些东西

@KZiovas 您好，我的代码真的很长，并且使用了不同的 netcdf 文件，我会在我的问题中添加使用不同打印语句时得到的内容

可能是数据样本

@KZiovas 这对我添加到我的问题有帮助吗？否则我可以尝试创建一个与我的真实 xarray 结构相似的 xarray

@KZiovas 非常感谢！我自己找不到解决这个问题的方法

【参考方案1】：

好的，滚动函数“重新启动”，因为月份维度对应于不同的行，每年一行。

做你想做的事的一种方法可能是以下。我创建了一些与您类似的虚拟数据，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 stack 方法创建了一个新维度，其中年和月相结合，并在该维度上应用了滚动窗口：

my_xarray = da.stack(z=("year", "month")).rolling(z=3).mean()
print(my_xarray)

它似乎给了你想要的：

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])

【讨论】：

非常感谢！！这对我有用:)