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NumPy | logical_and method

schedule Aug 10, 2023

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Python●NumPy

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Parameters Return value Examples Basic usage

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Numpy's logical_and(~) compares the input arrays element-wise, and for each comparison, returns True if both values evaluates to True.

Parameters

1. x1 | array_like

The first input array.

2. x2 | array-like

The second input array.

3. out | Numpy array | optional

Instead of creating a new array, you can place the computed result into the array specified by out.

4. where | array of boolean | optional

Values that are flagged as False will be ignored, that is, their original value will be uninitialized. If you specified the out parameter, the behavior is slightly different - the original value will be kept intact.

Return value

If x1 and x2 are scalars, then a single boolean is returned. Otherwise, a Numpy array of booleans is returned.

Examples

Basic usage


        
        
            
                
                
                    np.logical_and(False, True)
                
            
            False


        
        
            
                
                
                    np.logical_and([False, True], [True, True])
                
            
            array([False,  True])

On a more practical note, suppose we wanted to find an even number larger than 3 from an array:


        
        
            
                
                
                    a = np.array([1,2,3,4,5])
mask = np.logical_and(a%2==0, a>3)
mask
                
            
            array([False, False, False,  True, False])

To fetch the values that fit our criteria (i.e. the one flagged as True):

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Published by Isshin Inada

Edited by 0 others

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