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我想将前面的n行作为列添加到NumPy数组中.
例如,如果n = 2,则下面的数组……
[[ 1, 2]
[ 3, 4]
[ 5, 6]
[ 7, 8]
[ 9, 10]
[11, 12]]
……应该变成以下一个:
[[ 1, 2, 0, 0, 0, 0]
[ 3, 4, 1, 2, 0, 0]
[ 5, 6, 3, 4, 1, 2]
[ 7, 8, 5, 6, 3, 4]
[ 9, 10, 7, 8, 5, 6]
[11, 12, 9, 10, 7, 8]]
任何想法我怎么能做到这一点,而不是在for循环中遍历整个数组?
最佳答案
这是一个矢量化的方法 –
def vectorized_app(a,n):
M,N = a.shape
idx = np.arange(a.shape[0])[:,None] - np.arange(n+1)
out = a[idx.ravel(),:].reshape(-1,N*(n+1))
out[N*(np.arange(1,M+1))[:,None] <= np.arange(N*(n+1))] = 0
return out
样品运行 –
In [255]: a
Out[255]:
array([[ 1, 2, 3],
[ 4, 5, 6],
[ 7, 8, 9],
[10, 11, 12],
[13, 14, 15],
[16, 17, 18]])
In [256]: vectorized_app(a,3)
Out[256]:
array([[ 1, 2, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[ 4, 5, 6, 1, 2, 3, 0, 0, 0, 0, 0, 0],
[ 7, 8, 9, 4, 5, 6, 1, 2, 3, 0, 0, 0],
[10, 11, 12, 7, 8, 9, 4, 5, 6, 1, 2, 3],
[13, 14, 15, 10, 11, 12, 7, 8, 9, 4, 5, 6],
[16, 17, 18, 13, 14, 15, 10, 11, 12, 7, 8, 9]])
运行时测试 –
我正在计时@Psidom's loop-comprehension based method和本文中列出的矢量化方法,在问题中发布的样本的100x放大版本(就大小而言):
In [246]: a = np.random.randint(0,9,(600,200))
In [247]: n = 200
In [248]: %timeit np.column_stack(mypad(a, i) for i in range(n + 1))
1 loops, best of 3: 748 ms per loop
In [249]: %timeit vectorized_app(a,n)
1 loops, best of 3: 224 ms per loop
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