# Scipy Python

- SciPy (pronounced / ˈsaɪpaɪ / 'sigh pie') is a free and open-source Python library used for scientific computing and technical computing. SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.
- The SciPy library of Python is built to work with NumPy arrays and provides many user-friendly and efficient numerical practices such as routines for numerical integration and optimization. Together, they run on all popular operating systems, are quick to install and are free of charge.

A Poisson discrete random variable.

SciPy 2021, the 20th annual Scientific Computing with Python conference, will be a virtual conference held July 12-18, 2021. The annual SciPy Conference brings together attendees from industry, academia, and government to showcase their latest projects, learn from skilled users and developers, and collaborate on code development.

As an instance of the `rv_discrete`

class, `poisson`

object inherits from ita collection of generic methods (see below for the full list),and completes them with details specific for this particular distribution.

Notes

The probability mass function for `poisson`

is:

for (k ge 0).

`poisson`

takes (mu) as shape parameter.When mu = 0 then at quantile k = 0, `pmf`

methodreturns *1.0*.

The probability mass function above is defined in the “standardized” form.To shift distribution use the `loc`

parameter.Specifically, `poisson.pmf(k,mu,loc)`

is identicallyequivalent to `poisson.pmf(k-loc,mu)`

.

Examples

Calculate a few first moments:

Display the probability mass function (`pmf`

):

Alternatively, the distribution object can be called (as a function)to fix the shape and location. This returns a “frozen” RV object holdingthe given parameters fixed.

Freeze the distribution and display the frozen `pmf`

:

### Scipy Python Tutorial

Check accuracy of `cdf`

and `ppf`

:

Generate random numbers:

Methods

| Random variates. |

| Probability mass function. |

| Log of the probability mass function. |

| Cumulative distribution function. |

| Log of the cumulative distribution function. |

| Survival function (also defined as |

| Log of the survival function. |

| Percent point function (inverse of |

| Inverse survival function (inverse of |

| Mean(‘m’), variance(‘v’), skew(‘s’), and/or kurtosis(‘k’). |

| (Differential) entropy of the RV. |

| Expected value of a function (of one argument) with respect to the distribution. |

| Median of the distribution. |

| Mean of the distribution. |

| Variance of the distribution. |

| Standard deviation of the distribution. |

| Endpoints of the range that contains alpha percent of the distribution |

### Scipy Python Pip

### Commonly used with `scipy`

### Scipy Python

Based on how often these packages appear together in public `requirements.txt`

files on GitHub.

### Scipy Python Install

A set of python modules for machine learning and data mining |

A set of python modules for machine learning and data mining |

A domain-specific language for modeling convex optimization problems in Python. |

Access a multitude of neuroimaging data formats |

A library for manipulating C3D binary files |

Python wrapper for Google's RE2 using Cython |

Use Vamp plugins for audio feature analysis. |

A banded matrix library for python. |

Python module for audio and music processing |

Efficiently computes derivatives of numpy code. |

Easily read and write to different storage platforms in Python. |

A utility module for handling app settings. |

A framework for elegantly configuring complex applications |

Publications (and donations) tracer |

A garden of scikit-learn compatible trees Css target safari. |

Access modules for the MultiNest and Cuba integration libraries |

Constrained multivariate least-squares optimizer |

algorithms for image registration |

Python DTW Module |