  # 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: 