Numpy 将大小未知的二维阵列组合成一个三维阵列

我有一个函数，比如peaksdetect（），它将生成一个未知行数的二维数组；我会叫它几次，比如说3，我想用这3个数组，一个3-D数组。这是我的开始，但它非常复杂，有很多if语句，因此我希望尽可能简化：

import numpy as np

dim3 = 3   # the number of times peaksdetect() will be called
           # it is named dim3 because this number will determine 
           # the size of the third dimension of the result 3-D array

for num in range(dim3):
    data = peaksdetect(dataset[num])            # generates a 2-D array of unknown number of rows
    if num == 0:
        3Darray = np.zeros([dim3, data.shape])  # in fact the new dimension is in position 0
                                                # so dimensions 0 and 1 of "data" will be 
                                                # 1 and 2 respectively
    else:
        if data.shape[0] > 3Darray.shape[1]:
            "adjust 3Darray.shape[1] so that it equals data[0] by filling with zeroes"
            3Darray[num] = data
        else:
            "adjust data[0] so that it equals 3Darray.shape[1] by filling with zeroes"
            3Darray[num] = data
...

---

如果您希望调整数组的大小，那么预分配它很可能不会带来太多好处。将数组存储在列表中可能会更简单，然后计算数组的大小以容纳所有数组，并将数据转储到其中：

data = []
for num in range(dim3):
    data.append(peaksdetect(dataset[num]))
shape = map(max, zip(*(j.shape for j in data)))
shape = (dim3,) + tuple(shape)
data_array = np.zeros(shape, dtype=data[0].dtype)
for j, d in enumerate(data):
    data_array[j, :d.shape[0], :d.shape[1]] = d

---

真是太棒了！事实上，我对Python的基础知识一无所知，例如什么是列表。