numpy.geomspace () in Python

NumPy | Python Methods and Functions

numpy.geomspace() is used to return numbers evenly spaced on a logarithmic scale (geometric progression). 
This looks like logspace-python/ rel=noopener target=_blank> numpy.logspace () but with endpoints specified directly. Each output pattern is a constant multiple of the previous one.

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: Work

# Python3 program demonstrates
# numpy.geomspace () function

 

import numpy as geek

  

 

print ( " B " , geek.geomspace ( 2.0 , 3.0 , num  = 5 ), "" )

 
# To evaluate sin () at great distance

point = geek.geomspace ( 1 , 2 , 10 )

print ( "A" , 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 (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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