 # scipy stats.rv_continuous () | python

`scipy.stats.rv_continuous() ` — it is a class of continuous random variables intended for subclasses. It is a base class for constructing a specific distribution from continuous random variables. This class cannot be directly 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 eg 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 the “rv_continuous class”.

 ` def ` ` sample (` ` self ` `, size ` ` = ` ` 1 ` `, random_state ` ` = ` ` None ` `): `   ` ` `" "" ` ` Return sample from PDF - probability distribution function. ` ` call - rv_continuous class. `   ` "" "` ` `  ` ` ` return ` ` self ` ` ._ rv.rvs (size ` ` = ` ` size, random_state ` ` = ` ` random_state) `

Code # 2: Generating a Gaussian distribution from rv_continuous.

 < p> ` from ` ` scipy.stats ` ` import ` ` rv_continuous ` ` import ` ` numpy as np `   ` class ` ` gaussian_gen (rv_continuous): ` ` & # 39; & # 39; & # 39; Gaussian distribution & # 39; & # 39; & # 39; ` ` 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 `