# numpy.ma.clip#

ma.clip = <numpy.ma.core._convert2ma object>#

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.

Equivalent to but faster than `np.minimum(a_max, np.maximum(a, a_min))`.

No check is performed to ensure `a_min < a_max`.

Parameters:
aarray_like

Array containing elements to clip.

a_min, a_maxarray_like or None

Minimum and maximum value. If `None`, clipping is not performed on the corresponding edge. If both `a_min` and `a_max` are `None`, the elements of the returned array stay the same. Both are broadcasted against `a`.

outndarray, 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.

min, maxarray_like or None

Array API compatible alternatives for `a_min` and `a_max` arguments. Either `a_min` and `a_max` or `min` and `max` can be passed at the same time. Default: `None`.

New in version 2.1.0.

**kwargs

For other keyword-only arguments, see the ufunc docs.

New in version 1.17.0.

Returns:

An array with the elements of a, but where values < a_min are replaced with a_min, and those > a_max with a_max.

Notes

When a_min is greater than a_max, `clip` returns an array in which all values are equal to a_max, as shown in the second example.

Examples

```>>> import numpy as np
>>> a = np.arange(10)
>>> a
array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
>>> np.clip(a, 1, 8)
array([1, 1, 2, 3, 4, 5, 6, 7, 8, 8])
>>> np.clip(a, 8, 1)
array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1])
>>> np.clip(a, 3, 6, out=a)
array([3, 3, 3, 3, 4, 5, 6, 6, 6, 6])
>>> 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])
```