# numpy.logspace() in Python

Last Updated : 05 Apr, 2022

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

 `# Python Programming illustrating` `# numpy.logspace method`   `import` `numpy as geek`   `# base = 11` `print``(``"B\n"``, geek.logspace(``2.0``, ``3.0``, num``=``5``, base ``=` `11``))`   `# base = 10` `print``(``"B\n"``, geek.logspace(``2.0``, ``3.0``, num``=``5``))`   `# base = 10, dtype = int` `print``(``"B\n"``, geek.logspace(``2.0``, ``3.0``, num``=``5``, dtype ``=` `int``))`

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

 `# Graphical Representation of numpy.logspace()` `import` `numpy as geek` `import` `pylab as p`   `# Start = 0` `# End = 2` `# Samples to generate = 10` `x1 ``=` `geek.logspace(``0``, ``1``, ``10``)` `y1 ``=` `geek.zeros(``10``)`   `# Start = 0.1` `# End = 1.5` `# Samples to generate = 12` `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'``)`

Output :

Note :
These NumPy-Python programs wonâ€™t run on online IDE’s, so run them on your systems to explore them
Similar methods :

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