【Numpy】clip（）

clip(a, a_min, a_max, out=None) -> None
Clip (limit) the values in an array.

Given an interval, values outside the interval are clipped to the interval edges. For example, if an interval of [0, 1] is specified, values smaller than 0 become 0, and values larger than 1 become 1.
规定一个间隔，值在间隔外的数据将被修剪。例如：对于间隔[0,1],值小于0的数将被设置为0，大于1的数被设置为1

Parameters

a : array_like Array containing elements to clip.
a:数组形状的数据

a_min : scalar or array_like or None 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_min:标量或array_like或无最小值。 如果为“无”，则不会在较低间隔的边缘执行剪切。 a_min和a_max中最多一个可以为None。

a_max : scalar or array_like or None 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.
a_max:同a_min相似

If a_min or a_max are array_like, then the three arrays will be broadcasted to match their shapes.
如果a_min或a_max是array_like，则将广播这三个数组以匹配其形状。

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.

Returns

clipped_array : ndarray An array with the elements of a, but where values < a_min are replaced with a_min, and those > a_max with a_max.
返回被修剪之后的数组，大小与原数组相同

See Also
numpy.doc.ufuncs : Section “Output arguments”

Examples

>>> 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])
对于a_min,如果a中的值小于a_min数组中的值，则修剪为a_min中的值。换另一种说法，两者之间取其大者
0<3,1<4,2 >1,3>1,4>1,5>4,6>4,7>4,8>4
3 ,4 ,2 ,3 ,4…