[英]Efficiently invert floats in a list based on a condition
I have one ndarray of floats ( a
) and one list of 0 or 1 ( b
). 我有一个浮点数ndarray(
a
)和一个0或1( b
)的列表。 a
and b
have the same length, typically 1000. I would like to apply a simple function (such as minus the inverse) to the elements of a
whose index correspond to 1 in b
. a
和b
具有相同的长度,通常为1000。我想对索引与b
1对应的a
的元素应用一个简单的函数(例如,减去逆数)。
The following method takes a bit less than 1 millisecond. 以下方法花费不到1毫秒的时间。 Would it be possible to make it faster?
是否有可能使其更快?
import numpy as np
# generate dummy data
n = 1000
a = np.random.uniform(low=0, high=10, size=n)
b = np.random.choice(2, 1000)
# map the function
start = time.time()
out = [a[i] if b[i] == 0 else -1/a[i] for i in range(n)]
print time.time() - start
Use b
as a mask, and set a
's cells accordingly: 使用
b
作为遮罩,并相应设置a
的单元格:
m = np.array(b).astype(bool)
a[m] = -1 / a[m]
Even better, initialise b
using np.random.choice
: 更好的是,使用
np.random.choice
初始化b
:
b = np.random.choice(2, 1000).astype(bool)
Now, you don't need the overhead of converting b
to an array, just use it directly to index a
: 现在,您无需将
b
转换为数组的开销,只需将其直接用于索引a
:
a[b] = -1 / a[b]
This runs in 这在
22.3 µs ± 501 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)
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