【python】numpy库np.clip详解
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2022-06-01 12:56:59
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将将数组中的元素限制在a_min, a_max之间,大于a_max的就使得它等于 a_max,小于a_min,的就使得它等于a_min.
a = np.array([[1,2,3,4,5,6,7,8],[1,2,3,4,5,6,7,8]])
np.clip(a,2,6)
#输出:array([[2, 2, 3, 4, 5, 6, 6, 6],
[2, 2, 3, 4, 5, 6, 6, 6]])
官方文档:
Parameters:
a : np数组
a_min : scalar or array_like or None#可以为空
Minimum value. If None, clipping is not performed on lower interval edge. Not more than one of a_min and a_max may be None.
a_max : scalar or array_like or None#可以为空
Maximum value. If None, clipping is not performed on upper interval edge. Not more than one of a_min and a_max may be None. If a_min or a_max are array_like, then the three arrays will be broadcasted to match their shapes.
out : ndarray, optional
The results will be placed in this array. It may be the input array for in-place clipping. out must be of the right shape to hold the output. Its type is preserved.
>>> a = np.arange(10)
>>> np.clip(a, 1, 8)
array([1, 1, 2, 3, 4, 5, 6, 7, 8, 8])
>>> a
array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
>>> np.clip(a, 3, 6, out=a)
array([3, 3, 3, 3, 4, 5, 6, 6, 6, 6])
>>> a = np.arange(10)
>>> a
array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
>>> np.clip(a, [3, 4, 1, 1, 1, 4, 4, 4, 4, 4], 8)
array([3, 4, 2, 3, 4, 5, 6, 7, 8, 8])
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