numpy.geomspace(): This function return numbers spaced evenly on a log scale (a geometric progression).
Syntax: numpy.geomspace(start, stop, num=50, endpoint=True, dtype=None, axis=0)
This is similar to logspace, but with endpoints specified directly. Each output sample is a constant multiple of the previous.
Changed in version 1.16.0: Non-scalar start and stop are now supported.
start : array_like
The starting value of the sequence.
stop : array_like
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.
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.geomspace() example program
import numpy as np print(np.geomspace(1,5, num=5) print(np.geomspace(1,10, num=5)