在python中将平面列表读入多维数组/矩阵
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Read flat list into multidimensional array/matrix in python
提问by Chris
I have a list of numbers that represent the flattened output of a matrix or array produced by another program, I know the dimensions of the original array and want to read the numbers back into either a list of lists or a NumPy matrix. There could be more than 2 dimensions in the original array.
我有一个数字列表，表示由另一个程序生成的矩阵或数组的展平输出，我知道原始数组的维度，并希望将数字读回列表列表或 NumPy 矩阵。原始数组中可能有 2 个以上的维度。
e.g.
例如
data = [0, 2, 7, 6, 3, 1, 4, 5]
shape = (2,4)
print some_func(data, shape)
Would produce:
会产生：
[[0,2,7,6], [3,1,4,5]]
[[0,2,7,6], [3,1,4,5]]
Cheers in advance
提前干杯
采纳答案by Katriel
Use numpy.reshape:
>>> import numpy as np
>>> data = np.array( [0, 2, 7, 6, 3, 1, 4, 5] )
>>> shape = ( 2, 4 )
>>> data.reshape( shape )
array([[0, 2, 7, 6],
[3, 1, 4, 5]])
You can also assign directly to the shapeattribute of dataif you want to avoid copying it in memory:
如果你想避免在内存中复制它，你也可以直接分配给shape属性data：
>>> data.shape = shape
回答by Vajk Hermecz
If you dont want to use numpy, there is a simple oneliner for the 2d case:
如果您不想使用 numpy，则对于 2d 情况有一个简单的 oneliner：
group = lambda flat, size: [flat[i:i+size] for i in range(0,len(flat), size)]
And can be generalized for multidimensions by adding recursion:
并且可以通过添加递归来推广多维：
import operator
def shape(flat, dims):
subdims = dims[1:]
subsize = reduce(operator.mul, subdims, 1)
if dims[0]*subsize!=len(flat):
raise ValueError("Size does not match or invalid")
if not subdims:
return flat
return [shape(flat[i:i+subsize], subdims) for i in range(0,len(flat), subsize)]
回答by B.Mr.W.
For those one liners out there:
对于那里的那些班轮：
>>> data = [0, 2, 7, 6, 3, 1, 4, 5]
>>> col = 4 # just grab the number of columns here
>>> [data[i:i+col] for i in range(0, len(data), col)]
[[0, 2, 7, 6],[3, 1, 4, 5]]
>>> # for pretty print, use either np.array or np.asmatrix
>>> np.array([data[i:i+col] for i in range(0, len(data), col)])
array([[0, 2, 7, 6],
[3, 1, 4, 5]])
