Python 创建玩具3D阵列包含每小时频率、温度和纬度、经度坐标

我想创建一个三维数据数组，它存储具有相应纬度和长度的温度数据，以及具有每小时频率的时间。所以我做了如下的编码

np.random.seed(123)

temperature_3d = 15 + 10 * np.random.randn(24,4,4)    # 3-dimensional
lat = np.random.uniform(low=-90, high=90, size=(1,4))
lon = np.random.uniform(low=-180, high=180, size=(1,4))

# round to two digits after decimal point
temperature_3d = np.around(temperature_3d, decimals=2)
lat , lon = np.around([lat, lon], decimals=2)
date_rng = pd.date_range(start='1/1/2018T01:00', end='1/2/2018', freq='H')

我得到了这个错误

ValueError: conflicting sizes for dimension 'x': length 24 on the data but length 1 on coordinate 'lat'

维度上是错误的，我可以在不包含时间的情况下修复它，我的目标是创建一个具有720x40x40维度（timexlat，lonxtime）的数据数组

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我也是这类图书馆的新手。因此，我将非常感谢您的建议。

看起来形状需要正确匹配

首先，由于您的温度数据是形状（24,4,4）

您需要在DIM中首先输入日期：

da = xr.DataArray(data=temperature_3d,
              coords={"lat": (["x","y"], lat),
                      "lon": (["x","y"], lon), 
                      "day": date_rng},
              dims=["day","x","y"])

其次，你的lat和lon坐标有一个符合[“x”，“y”]的形状，因此在本例中，你需要一个4x4网格来表示每个点的lat，另一个4x4网格用于表示每个点的lon。为此，我们可以使用np.meshgrid：

latgrid, longrid = np.meshgrid(lat,lon)

因此，全文如下：

import numpy as np
import xarray as xa

np.random.seed(123)

temperature_3d = 15 + 10 * np.random.randn(24,4,4)    # 3-dimensional
lat = np.random.uniform(low=-90, high=90, size=(4))
lon = np.random.uniform(low=-180, high=180, size=(4))

# round to two digits after decimal point
temperature_3d = np.around(temperature_3d, decimals=2)
lat , lon = np.around([lat, lon], decimals=2)
latgrid, longrid = np.meshgrid(lat,lon)
date_rng = pd.date_range(start='1/1/2018T01:00', end='1/2/2018', freq='H')

da = xa.DataArray(data=temperature_3d,
              coords={"lat": (["x","y"], latgrid),
                      "lon": (["x","y"], longrid), 
                      "day": date_rng},
              dims=["day","x","y"])
da

latgrid, longrid = np.meshgrid(lat,lon)

import numpy as np
import xarray as xa

np.random.seed(123)

temperature_3d = 15 + 10 * np.random.randn(24,4,4)    # 3-dimensional
lat = np.random.uniform(low=-90, high=90, size=(4))
lon = np.random.uniform(low=-180, high=180, size=(4))

# round to two digits after decimal point
temperature_3d = np.around(temperature_3d, decimals=2)
lat , lon = np.around([lat, lon], decimals=2)
latgrid, longrid = np.meshgrid(lat,lon)
date_rng = pd.date_range(start='1/1/2018T01:00', end='1/2/2018', freq='H')

da = xa.DataArray(data=temperature_3d,
              coords={"lat": (["x","y"], latgrid),
                      "lon": (["x","y"], longrid), 
                      "day": date_rng},
              dims=["day","x","y"])
da