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Parameters Return value Examples Basic usage Squeezing only a subset of axis

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NumPy | squeeze method

schedule Aug 11, 2023

Last updated

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Python●NumPy

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Parameters Return value Examples Basic usage Squeezing only a subset of axis

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Numpy's squeeze(~) method returns a Numpy array with redundant axes removed. Check the examples below for clarification.

Parameters

1. a | array-like

The input array.

2. axislink | int | optional

The axis you want to remove if redundant. By default, all redundant axises are removed.

Return value

A new Numpy array with redundant axises removed.

Examples

Basic usage

Suppose we have the following 2D array:


        
        
            
                
                
                    a = np.array([[4],[5],[6]])
a
                
            
            array([[4],
       [5],
       [6]])

Can you see how a can be expressed simply as an 1D array [4,5,6] in this case? The squeeze(~) method allows us to do this:


        
        
            
                
                
                    a.squeeze()
                
            
            array([4, 5, 6])

The same principle applies for the following case:


        
        
            
                
                
                    a = np.array([[[1,2],[3,4]]])
a
                
            
            array([[[1, 2],
        [3, 4]]])

Here, we have a 3D array, yet it's clear that this can be reduced to a 2D array, like so:


        
        
            
                
                
                    a.squeeze()
                
            
            array([[1, 2],
       [3, 4]])

Squeezing only a subset of axis

Suppose we have the following 3D array:


        
        
            
                
                
                    a = np.array([[[4],[5],[6]]])
a
                
            
            array([[[4],
        [5],
        [6]]])

It's clear that this can be reduced to either a 2D array or even more compactly to a 1D array. We can specify which dimension to reduce to using the axis parameter.

Reducing to a 2D array:


        
        
            
                
                
                    np.squeeze(a, axis=0)
                
            
            array([[4],
       [5],
       [6]])

Note that, by default, all redundant axises are removed:


        
        
            
                
                
                    np.squeeze(a)
                
            
            array([4, 5, 6])

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Published by Isshin Inada

Edited by 0 others

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