numpy.geomspace() in Python
numpy.geomspace() is used to return numbers spaced evenly on a log scale (a geometric progression).
This is similar to numpy.logspace() but with endpoints specified directly. Each output sample is a constant multiple of the previous.
Syntax : numpy.geomspace(start, stop, num=50, endpoint=True, dtype=None)
Parameters :
start : [scalar] The starting value of the sequence.
stop : [scalar] 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.
Return :
samples : [ndarray] num samples, equally spaced on a log scale.
Code #1 : Working
# Python3 Program demonstrate
# numpy.geomspace() function
import numpy as geek
print("B\n", geek.geomspace(2.0, 3.0, num = 5), "\n")
# To evaluate sin() in long range
point = geek.geomspace(1, 2, 10)
print("A\n", geek.sin(point))
Output :
B [ 2. 2.21336384 2.44948974 2.71080601 3. ] A [ 0.84147098 0.88198596 0.91939085 0.95206619 0.9780296 0.9948976 0.99986214 0.98969411 0.96079161 0.90929743]
Code #2 : Graphical Representation of numpy.geomspace()
# Graphical Representation of numpy.geomspace()
import numpy as geek
import pylab as p
% matplotlib inline
# Start = 1
# End = 3
# Samples to generate = 10
x1 = geek.geomspace(1, 3, 10, endpoint = False)
y1 = geek.ones(10)
p.plot(x1, y1, '+')
Output :
