numpy.logspace() function with example in python

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numpy.logspace(): This  function return numbers spaced evenly on a log scale.

Syntax: numpy.logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None, axis=0)

In linear space, the sequence starts at base ** start (base to the power of start) and ends with base ** stop (see endpoint below).

Changed in version 1.16.0: Non-scalar start and stop are now supported.

Parameters:
start : array_like
base ** start is the starting value of the sequence.

stop : array_like
base ** stop is the final value of the sequence, unless endpoint is False. In that case, num + 1 values are spaced over the interval in log-space, of which all but the last (a sequence of length num) are returned.

num : integer, optional
Number of samples to generate. Default is 50.

endpoint : boolean, optional
If true, stop is the last sample. Otherwise, it is not included. Default is True.

base : float, optional
The base of the log space. The step size between the elements in ln(samples) / ln(base) (or log_base(samples)) is uniform. Default is 10.0.

dtype : dtype
The type of the output array. If dtype is not given, infer the data type from the other input arguments.

axis : int, optional
The axis in the result to store the samples. Relevant only if start or stop are array-like. By default (0), the samples will be along a new axis inserted at the beginning. Use -1 to get an axis at the end.

New in version 1.16.0.

Returns:
samples : ndarray
num samples, equally spaced on a log scale.

# numpy.logspace() example program in python

import numpy as np print(np.logspace(1,2, num=10)) print(np.logspace(2,5,num=10, base=2.0))

 

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