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.
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.
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))
[ 10. 12.91549665 16.68100537 21.5443469 27.82559402
35.93813664 46.41588834 59.94842503 77.42636827 100. ]
[ 4. 5.0396842 6.34960421 8. 10.0793684
12.69920842 16. 20.1587368 25.39841683 32. ]