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NumPy | float_power method

schedule Aug 12, 2023

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Python●NumPy

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Parameters Return value Examples A common exponent Multiple exponents

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NumPy's float_power(~) method raises each value in the input array by the specified amount.

NOTE

There is a difference between NumPy's power(~) and float_power(~). NumPy's power(~) method uses the same data-type as the input array to perform the calculation; if your input array only contains integers, then the returned result will also be of type int. On the other hand, float_power(~) always uses float64 for maximum precision.

Parameters

1. x1 | array_like

The input array.

2. x2 | array_like

An array of exponents.

3. out | Numpy array | optional

Instead of creating a new array, you can place the computed mean 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 behaviour is slightly different - the original value will be kept intact.

Return value

A scalar is returned if x1 and x2 are scalars, otherwise a NumPy array is returned. Either way, the returned data-type is float64.

Examples

A common exponent


        
        
            
                
                
                    np.float_power([1,2,3], 2)
                
            
            array([1., 4., 9.])

Multiple exponents


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

Here, we are doing 1**3=1, 2**2=4 and 3**1=3.

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Published by Isshin Inada

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