# numpy.logspace() in Python

numpy.logspace(start, stop, num = 50, endpoint = True, base = 10.0, dtype = None) : Returns number spaces evenly w.r.t interval on a log scale.
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 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

 `# Graphical Represenation 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 won’t run on onlineID, so run them on your systems to explore them

Similiar methods :

• arange
• linspace
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