NumPy clip()
The numpy.clip() function limits the values in an array to a specified range. Any values lower than the minimum threshold are set to the minimum, and any values higher than the maximum threshold are set to the maximum.
Syntax
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numpy.clip(a, a_min, a_max, out=None, *, min=None, max=None)Parameters
| Parameter | Type | Description |
|---|---|---|
a | array_like | Input array containing elements to clip. |
a_min | array_like or None | Minimum value. Elements below this value are clipped to a_min. If None, no lower bound is applied. |
a_max | array_like or None | Maximum value. Elements above this value are clipped to a_max. If None, no upper bound is applied. |
out | ndarray, optional | Optional output array where the result is stored. It must have the same shape as the input array. |
min | array_like or None | Alternative for a_min, introduced in NumPy 2.1.0. |
max | array_like or None | Alternative for a_max, introduced in NumPy 2.1.0. |
Return Value
Returns an array where values lower than a_min are replaced with a_min, and values higher than a_max are replaced with a_max. The shape and type of the input array are preserved.
Examples
1. Clipping Values in a NumPy Array
In this example, we clip an array so that values are limited between 2 and 8.
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import numpy as np
# Define an array with values outside the clipping range
arr = np.array([1, 3, 5, 7, 9, 11])
# Clip values below 2 to 2, and above 8 to 8
clipped_arr = np.clip(arr, 2, 8)
# Print the result
print("Original array:", arr)
print("Clipped array:", clipped_arr)Output:
Original array: [ 1 3 5 7 9 11]
Clipped array: [2 3 5 7 8 8]