-
>>>
import numpy
as np
-
>>> a = np.random.randint(
-5,
5, (
5,
5))
-
>>> a
-
array([[
-4,
-4,
-5,
2,
1],
-
[
-1,
-2,
-1,
3,
3],
-
[
-1,
-2,
3,
-5,
3],
-
[
0,
-3,
-5,
1,
-4],
-
[
0,
3,
1,
3,
-4]])
-
# 方式一
-
>>> np.maximum(a,
0)
-
array([[
0,
0,
0,
2,
1],
-
[
0,
0,
0,
3,
3],
-
[
0,
0,
3,
0,
3],
-
[
0,
0,
0,
1,
0],
-
[
0,
3,
1,
3,
0]])
-
# 方式二
-
>>> (a + abs(a)) /
2
-
array([[
0,
0,
0,
2,
1],
-
[
0,
0,
0,
3,
3],
-
[
0,
0,
3,
0,
3],
-
[
0,
0,
0,
1,
0],
-
[
0,
3,
1,
3,
0]])
-
# 方式三
-
>>> b = a.copy()
-
>>> b[b <
0] =
0
-
>>> b
-
array([[
0,
0,
0,
2,
1],
-
[
0,
0,
0,
3,
3],
-
[
0,
0,
3,
0,
3],
-
[
0,
0,
0,
1,
0],
-
[
0,
3,
1,
3,
0]])
-
# 方式四
-
>>> np.where(a >
0, a,
0)
-
array([[
0,
0,
0,
2,
1],
-
[
0,
0,
0,
3,
3],
-
[
0,
0,
3,
0,
3],
-
[
0,
0,
0,
1,
0],
-
[
0,
3,
1,
3,
0]])
python numpy矩阵中令小于0的元素改为0
最新推荐文章于 2024-06-09 13:25:20 发布