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NumPy | logspace method

schedule Aug 11, 2023

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Parameters Return value Examples Basic Usage Excluding the endpoint Explicit typing

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Numpy's logspace(~) method creates a Numpy array with values that are evenly spaced in a log-scale.

Parameters

1. start | number

The starting value of the Numpy array.

2. stop | number

The ending value of the Numpy array. This is inclusive.

3. num | int | optional

The number of samples you want to generate. By default, num=50.

4. endpoint | boolean | optional

If set to True, then stop will be the last value of the Numpy array. By default, endpoint=False.

5. base | float | optional

The base of the logarithm to use. By default, base=10.

6. dtype | string or type | optional

The desired data type for the Numpy array. This overrides the default behaviour of using the same data-type as the source array.

Return value

A Numpy array with values that are evenly spaced in a log-scale.

Examples

Basic Usage


        
        
            
                
                
                    np.logspace(2, 5, 4)
                
            
            array([   100.,   1000.,  10000., 100000.])

Here, the numbers in the array are generated like so:


        
        
            
                
                
                    [0] 10^2 = 100
[1] 10^3 = 1000
[2] 10^4 = 10000
[3] 10^5 = 100000

Excluding the endpoint

We set endpoint=False, like follows:


        
        
            
                
                
                    np.logspace(2,5,4, endpoint=False)
                
            
            array([  100.        ,   562.34132519,  3162.27766017, 17782.79410039])

Explicit typing

We set dtype=float to obtain a Numpy array of type float.


        
        
            
                
                
                    np.logspace(2,5,4, dtype=float)
                
            
            array([   100.,   1000.,  10000., 100000.])

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Published by Isshin Inada

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