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2024年4月22日发(作者：微信公众号开发小程序)

numpy 数组的仿射变换

English Answer:

Affine transformation is a linear transformation

followed by a translation. It is characterized by a 2x3

transformation matrix that contains the scaling, rotation,

and translation parameters. Affine transformation preserves

the straight lines and parallelism, but it can change the

shape and size of the objects.

In NumPy, there are several ways to perform affine

transformation on arrays. One way is to use the

`_transform` function. This function

takes the input array, the transformation matrix, and the

output shape as input, and returns the transformed array.

Another way to perform affine transformation is to use

the `Transform` class. This class

provides a convenient way to create and apply affine

transformations.

Here is an example of how to use the

`_transform` function to perform affine

transformation on a 2D array:

import numpy as np.

from e import affine_transform.

# Define the input array.

input_array = ([[1, 2, 3], [4, 5, 6], [7, 8,

9]])。

# Define the transformation matrix.

transformation_matrix = ([[1, 0, 0], [0, 1, 0],

[0, 0, 1]])。

# Perform affine transformation.

transformed_array = affine_transform(input_array,


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