从多个2D阵列创建3D阵列

Question

I have two monthly gridded data sets which I want to compare later. The input looks like this for both data and that is also how I want the output.

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)

So both have the same spatial resolution of 144x72 but different length of time. As one of them has some missing months, I made sure that only the months are selected were both have data. So I created a two dimensional array where the data is stored according to their longitude and latitude value if both data sets contain this month. In the end I want to have a three dimensional array for data1 and data2 of the same length.

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])

The script runs without an error, however, I only get a really long 1D array.

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

How can I arrange it to a three dimensional array?

Answer 1

For me I got it working with the following. I defined the three dimensional array with the fixed dimension of the longitude and latitude and an undefined length of the time axis.

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

And then I appended two dimensional outputs along the time axis.

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