# scipy stats.rv_continuous() | Python

`scipy.stats.rv_continuous() ` is a continuous random variable class which is meant for sub-classing. It is a base class for constructing specific distribution from continuous random variables. This class can’t directly be used as a distribution.

Parameters :
moment : [int] moment calculation to use: 0 for pdf, 1 for ppf. Default = 1
a : [float] Lower bound for distribution. Default is -ve infinity.
b : [float] Upper bound for distribution. Default is +ve infinity.
xtol : [float] tolerance for fixed point calculation for ppf
name : [str] Name of the instance. Used to construct the default e.g. for distributions
badvalue : [object] Default is np.nan. Value in a result arrays that indicates a value that for which some argument restriction is violated.
logname : [str] Used as part of theFirst line of the docstring.
extradoc : [str] Used as the last part of the docstring
shapes : [str] Shape of the distribution.

Return : Continuous Random Variable Distribution.

Code #1 : Using “rv_continuous class”.

 `def` `sample(``self``, size ``=` `1``, random_state ``=` `None``): ` `     `  `        ``""" ` `        ``Return a sample from PDF - Probability Distribution Function. ` `        ``calling - rv_continuous class. ` ` `  `        ``"""` `         `  `        ``return` `self``._rv.rvs(size ``=` `size, random_state ``=` `random_state)  `

Code #2 : Creating Gaussian Distribution from rv_continuous.

 `from` `scipy.stats ``import` `rv_continuous ` `import` `numpy as np ` ` `  `class` `gaussian_gen(rv_continuous): ` `    ``'''Gaussian distribution'''` `    ``def` `_pdf(``self``, x): ` `        ``return` `np.exp(``-``x``*``*``2` `/` `2.``) ``/` `np.sqrt(``2.0` `*` `np.pi) ` `     `  `gaussian ``=` `gaussian_gen(name ``=` `'gaussian'``) ` ` `  `x ``=` `2.0` `gaussian._pdf(x) `

Output :

```0.05399096651318806
```

My Personal Notes arrow_drop_up

Check out this Author's contributed articles.

If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.

Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.

Article Tags :

Be the First to upvote.

Please write to us at contribute@geeksforgeeks.org to report any issue with the above content.