从不同长度的数组创建ndarray [英] Create an ndarray from arrays of different lengths

问题描述

如何用不同长度的(1D-)数组优雅地创建NumPy ndarray，并填充其余部分?

How do you elegantly create a NumPy ndarray from (1D-)arrays of different lengths, padding the remainder?

数组始终是一维的，它们具有不同的长度(最大长度在20到100之间变化).

The arrays are always 1D, they have different lengths (maximum length varied between 20 and 100).

说有

a = range(40)
b = range(30)

结果ndarray应该是

X = [[0,1,2,3,...,39,40],
     [0,1,2,...29,30,0,0,...,0]]

棘手的解决方案

创建中介

Hacky solution

Creating an intermediary

I = [a,b]

并通过

I[1].extend([0] * (maximum - len(I[1])))

然后可以通过

X = np.array(I)

可以工作，但是没有内置的东西/可以通过PyPI使用/更多的pythonic吗?

works but is there nothing built-in / available via PyPI / more pythonic?

推荐答案

您可以创建零数组(np.zeros)，然后用a和b替换行.不确定是否比您的方式更好

You could create an array of zeros (np.zeros), then replace the rows with your a and b. Not sure that's any better than your way though

In [27]: a=range(40)

In [28]: b=range(30)

In [29]: x=np.zeros((2,max(len(a),len(b))))

In [30]: for i,j in enumerate([a,b]): x[i][:len(j)]=j

In [31]: x
Out[31]: 
array([[  0.,   1.,   2.,   3.,   4.,   5.,   6.,   7.,   8.,   9.,  10.,
         11.,  12.,  13.,  14.,  15.,  16.,  17.,  18.,  19.,  20.,  21.,
         22.,  23.,  24.,  25.,  26.,  27.,  28.,  29.,  30.,  31.,  32.,
         33.,  34.,  35.,  36.,  37.,  38.,  39.],
       [  0.,   1.,   2.,   3.,   4.,   5.,   6.,   7.,   8.,   9.,  10.,
         11.,  12.,  13.,  14.,  15.,  16.,  17.,  18.,  19.,  20.,  21.,
         22.,  23.,  24.,  25.,  26.,  27.,  28.,  29.,   0.,   0.,   0.,
          0.,   0.,   0.,   0.,   0.,   0.,   0.]])

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