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 Represenation 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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