从多个 2D 阵列创建 3D 阵列答案

【问题标题】：Create 3D array from multiple 2D arrays从多个 2D 阵列创建 3D 阵列
【发布时间】：2017-05-26 12:22:54
【问题描述】：

我有两个月度网格数据集，我想稍后进行比较。两种数据的输入看起来都像这样，这也是我想要的输出。

In[4]: data1.shape
Out[4]: (444, 72, 144)

In[5]: gfz.shape
Out[5]: (155, 72, 144)

In[6]: data1
Out[6]: 
array([[[ 0.98412287,  0.96739882,  0.91172796, ...,  1.12651634,
          1.0682013 ,  1.07681048],
        [ 1.47803092,  1.44721365,  1.49585509, ...,  1.58934438,
          1.66956687,  1.57198083],
        [ 0.68730044,  0.76112831,  0.78218687, ...,  0.92582172,
          1.07873237,  0.87490368],
        ..., 
        [ 1.00752461,  1.00758123,  0.99440521, ...,  0.94128627,
          0.88981551,  0.93984401],
        [ 1.03467119,  1.02640462,  0.91580886, ...,  0.88302392,
          0.99204206,  0.96396238],
        [ 0.8280431 ,  0.82936555,  0.82637453, ...,  0.92009377,
          0.77890259,  0.81065702]],

       ..., 
       [[-0.12173297, -0.06624345, -0.02809682, ..., -0.04522502,
         -0.11502996, -0.22779272],
        [-0.61080372, -0.61958522, -0.52239478, ..., -0.6775983 ,
         -0.79460669, -0.70022893],
        [-0.12011283, -0.10849079,  0.096185  , ..., -0.45782232,
         -0.39763898, -0.31247514],
        ..., 
        [ 0.90601307,  0.88580155,  0.90268403, ...,  0.86414611,
          0.87041426,  0.86274058],
        [ 1.46445823,  1.31938004,  1.37585044, ...,  1.51378822,
          1.48515761,  1.49078977],
        [ 0.29749078,  0.22273554,  0.27161494, ...,  0.43205476,
          0.43777165,  0.36340511]],

       [[ 0.41008961,  0.44208974,  0.40928891, ...,  0.45899671,
          0.39472976,  0.36803097],
        [-0.13514084, -0.17332518, -0.11183424, ..., -0.22284794,
         -0.2532815 , -0.15402752],
        [ 0.28614867,  0.33750001,  0.48767376, ...,  0.01886483,
          0.07220326,  0.17406547],
        ..., 
        [ 1.0551219 ,  1.09540403,  1.19031584, ...,  1.09203815,
          1.07658005,  1.08363533],
        [ 1.54310501,  1.49531853,  1.56107259, ...,  1.57243073,
          1.5867976 ,  1.57728028],
        [ 1.1034857 ,  0.98658448,  1.14141166, ...,  0.97744882,
          1.13562942,  1.08589089]],

       [[ 1.02020931,  0.99780071,  0.87209344, ...,  1.11072564,
          1.01270151,  0.9222675 ],
        [ 0.93467152,  0.81068456,  0.68190312, ...,  0.95696563,
          0.84669352,  0.84596157],
        [ 0.97022212,  0.94228816,  0.97413743, ...,  1.06613588,
          1.08708596,  1.04224277],
        ..., 
        [ 1.21519053,  1.23492992,  1.2802881 , ...,  1.33915019,
          1.32537413,  1.27963519],
        [ 1.32051706,  1.28170252,  1.36266208, ...,  1.29100537,
          1.38395023,  1.34622073],
        [ 0.86108029,  0.86364979,  0.88489276, ...,  0.81707358,
          0.82471925,  0.83550251]]], dtype=float32)

因此两者具有相同的 144x72 空间分辨率，但时间长度不同。由于其中一个缺少一些月份，我确保只有选择的月份都有数据。所以我创建了一个二维数组，如果两个数据集都包含本月，则根据它们的经度和纬度值存储数据。最后我想要一个长度相同的data1和data2的三维数组。

3Darray_data1 =[]
3Darray_data2=[]
xy_data1=[[0 for i in range(len(lons_data1))] for j in range(len(lats_data1))]
xy_data2=[[0 for i in range(len(lons_data2))] for j in range(len(lats_data2))] 

# comparing the time steps 
for i in range(len(time_data1)):
    for j in range(len(time_data2)):
        if time_data1.year[i] == time_data2[j].year and time_data1[i].month==time_data2[j].month:

            # loop for data1 which writes the data into a 2D array
            for x in range(len(lats_data1)):
                for y in range(len(lons_data1)):
                    xy_data1[x][y]=data1[j,0,x,y]

            # append to get an array of arrays                   
            xy_data1 = np.squeeze(np.asarray(xy_data1))
            3Darray_data1 = np.append(3Darray_data1,[xy_data1])

            # loop for data2 which writes the data into a 2D array
            for x in range(len(lats_data2)):
                for y in range(len(lons_data2)):
                    xy_data2[x][y]=data2[i,x,y]

            # append to get an array of arrays                    
            xy_data2 = np.squeeze(np.asarray(xy_data2))
            3Darray_data2 = np.append(3Darray_data2,[xy_data2])

脚本运行没有错误，但是，我只得到一个很长的一维数组。

In[3]: 3Darray_data1
Out[3]: array([        nan,         nan,         nan, ...,  0.81707358,
        0.82471925,  0.83550251])

如何将它排列成一个三维数组？

【问题讨论】：

你在找这个吗？ stackoverflow.com/questions/18595488/…
你能提供一个输入和期望输出的例子吗？
是的，与此类似，但我想将它们沿第三个轴（时间）堆叠在一起，而不是将行和列混淆@kazemakase

标签： python arrays numpy datagrid

【解决方案1】：

对我来说，我让它与以下内容一起工作。我定义了一个经纬度固定，时间轴长度不定的三维数组。

temp_data1 = np.zeros((0,len(lats_data1),len(lons_data1)))

然后我沿时间轴附加了二维输出。

3Darray = np.append(3Darray,xy_data1[np.newaxis,:,:],axis=0)

【讨论】：