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 : 
 

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• Python-numpy
• Python numpy-arrayCreation

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• python