Python:NumPy .clip()

Numpy’s .clip() method limits the values in an array to a specified range by replacing values below a minimum or above a maximum with those boundary values.

Syntax

ndarray.clip(min=None, max=None, out=None)

Parameters:

• min: The minimum value to clip array elements to. All values below this will be set to min.
• max: The maximum value to clip array elements to. All values above this will be set to max.
• out: Output array for storing the result. Must have the same shape as the input array.

Return value:

Returns an array in which all values are clipped to the specified range. If out is provided, the result is stored in it and a reference to out is returned.

Example 1: Clipping an Array Using .clip()

In this example, .clip() is used without the out parameter to restrict all values of an array to a given range:

import numpy as np

# Create an array
np_array = np.array([0, 1, 1, 2, 3, 5, 8, 13, 21])

# Clip values between 3 and 9
clipped_array = np_array.clip(min=3, max=9)

# Print clipped array
print("Clipped Array: ", clipped_array)

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The output of this code is:

Clipped Array:  [3 3 3 3 3 5 8 9 9]

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Example 2: Element-Wise Clipping Using .clip()

This example demonstrates using arrays for min and max to clip values element-wise:

import numpy as np

np_array = np.array([[[20, -1, 12], [2, -3, 50]]])
output_array = np.empty_like(np_array)

min_vals = np.array([[[-1, 4, 7], [10, -13, 16]]])
max_vals = np.array([[[2, 5, 11], [13, 17, 19]]])

np_array.clip(min_vals, max_vals, out=output_array)

print("Clipped Array:\n", output_array)

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The output of this code is:

Clipped Array:
 [[[ 2  4 11]
  [10 -3 19]]]

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Codebyte Example

In this example, .clip() is provided with an integer for min and an array for max:

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