numpy.logspace() in Python
The numpy.logspace() function returns number spaces evenly w.r.t interval on a log scale.
Syntax :
numpy.logspace(start,
stop,
num = 50,
endpoint = True,
base = 10.0,
dtype = None)
Parameters :
-> start : [float] start(base ** start) of interval range.
-> stop : [float] end(base ** stop) of interval range
-> endpoint : [boolean, optional]If True, stop is the last sample. By default, True
-> num : [int, optional] No. of samples to generate
-> base : [float, optional] Base of log scale. By default, equals 10.0
-> dtype : type of output array
Return :
-> ndarray
Code 1 : Explaining the use of logspace()
Python
import numpy as geek
print ( "B\n" , geek.logspace( 2.0 , 3.0 , num = 5 , base = 11 ))
print ( "B\n" , geek.logspace( 2.0 , 3.0 , num = 5 ))
print ( "B\n" , geek.logspace( 2.0 , 3.0 , num = 5 , dtype = int ))
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Output :
B
[ 121. 220.36039471 401.31159963 730.8527479 1331. ]
B
[ 100. 177.827941 316.22776602 562.34132519 1000. ]
B
[ 100 177 316 562 1000]
Code 2 : Graphical Representation of numpy.logspace() using matplotlib module – pylab
Python
import numpy as geek
import pylab as p
x1 = geek.logspace( 0 , 1 , 10 )
y1 = geek.zeros( 10 )
x2 = geek.logspace( 0.1 , 1.5 , 12 )
y2 = geek.zeros( 12 )
p.plot(x1, y1 + 0.05 , 'o' )
p.xlim( - 0.2 , 18 )
p.ylim( - 0.5 , 1 )
p.plot(x2, y2, 'x' )
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Output :
Note :
These NumPy-Python programs won’t run on online IDE’s, so run them on your systems to explore them
Similar methods :
Last Updated :
05 Apr, 2022
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