Open Source Python Statistics Software - Page 2
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Python Statistics Software
View 2707 business solutionsBrowse free open source Python Statistics Software and projects below. Use the toggles on the left to filter open source Python Statistics Software by OS, license, language, programming language, and project status.
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ExoPlanet
GUI based toolkit for running common Machine Learning algorithms.
ExoPlanet provides a graphical interface for the construction, evaluation and application of a Machine Learning model in predictive analysis. With the back-end built using the numpy and scikit-learn libraries, as a toolkit, ExoPlanet couples fast and well tested algorithms, a UI designed over the Qt4 framework, and graphs rendered using Matplotlib to provide the user with a rich interface, rapid analytics and interactive visuals. ExoPlanet is designed to have a minimal learning curve, allowing researchers to focus on the applicative aspect of Machine Learning rather than their implementation details. It provides algorithms for unsupervised and supervised learning, which may be done with continuous or discrete labels. Post analysis, the toolkit further automates building the visual representations for the trained model. -
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This project hosts tools used for analysis of Gaussian Mixture Distributions (GMDs) which are used for statistical signal processing. The tools are libraries for implementing GMD operations and programs used to analyze properties of GMDs.
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A small simulator for Mendelian genetics, genetic drift, natural selection and random mutations, built on matplotlib and wxpython. A graph will be generated that traces the distribution of genotypes at successive generations.
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This project examines techniques to model three-dimensional rigid body motion using the geometric algebra of Dual Quaternions and how such models compare to more traditional models when used in underconstrained filtering applications.
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HMMLab
A Hidden Markov Model editor with support to HTK
HMMLab is a Hidden Markov Model editor oriented on HMMs for speach recognition. It can create, edit, train and visualize HMMs. HMMLab supports loading/saving HMMs from/to HTK files. -
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This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.
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1. Create an object-oriented python script that can represent mathematical concepts and their properties. 2. Represent all numeric values exactly. 3. Provide a variety of formats to export or embed representations of the mathematical concepts.
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MRA
A general recommender system with basic models and MRA
Multi-categorization Recommendation Adjusting (MRA) is to optimize the results of recommendation based on traditional(basic) recommendation models, through introducing objective category information and taking use of the feature that users always get the habits of preferring certain categories. Besides this, there are two advantages of this improved model: 1) it can be easily applied to any kind of existing recommendation models. And 2) a controller is set in this improved model to provide controllable adjustment range, which thereby makes it possible to provide optional modes of recommendation aiming different kinds of users. -
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Noisy Channel Simulator
Demonstrate errors in transmission of a file over a noisy channel.
This program was written to dimonstrate errors in transmission for a presentation on Claude Shannon's Noisy Channel Coding Theorem. It takes an input file, the probability of a bit being flipped, and, if specified, the size of the header of the file. The program was intended to take monochrome bitmap files as input, so that each bit refers to a pixel in the image and thus, it would be easy to see errors in the output file, as some of the pixels would be flipped; however, it will work on any input file. -
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ProbAbilistic CALculator - a package for computing with probability distributions
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PGAF provides a framework tuned, user-specific genetic algorithms by handling I/O, UI, and parallelism. It is designed for optimizing functions that take a "very long time" to evaluate.
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PyMC
Bayesian Modeling and Probabilistic Programming in Python
PyMC is a Python library for probabilistic programming focused on Bayesian statistical modeling and machine learning. Built on top of computational tools like Aesara and NumPy, PyMC allows users to define models using intuitive syntax and perform inference using MCMC, variational inference, and other advanced algorithms. It’s widely used in scientific research, data science, and decision modeling. -
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Software for speech research. It includes programs and libraries for signal processing, along with general purpose scientific libraries. Most of the code is in Python, with C/C++ supporting code. Also, contains code releases corresponding to publishe
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That project aims at studying and comparing typical airline IT methods, for instance RM-related algorithms. It works from a Unix/Linux/Mac command-line, and exposes basic APIs. It is being developed in C++, with Python wrappers for some components.
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VAERity
Uncovering truth in data
VAERity is a free, open source tool to graphically explore the VAERS data set. It aims to eventually expand in scope to allow fast querying of arbitrary large datasets. It utilizes vaex and pandas as required to provide a balance of speed and query flexibility. -
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allink
Software for data analysis, image processing, simulations, solver.
Collection of utilities based on two basics classes: Matematica and VarData. Matematica) performs math operations on vectors and matrices for smoothing, interpolation, convolution, image processing... VarData) manipulate a structure of points connected by links. Addraw) openGL engine. ElPoly) analyze mechanical properties of polymer and membrane like structures. Addyn) perform molecular dynamics and Monte Carlo simulations and has a solver for 4th oder PDE. Avvis) perform all the operation of Matematica on different sets of data visualized on a Qt graphical interface. DrImage) image manipulation on the Matematica filters. The program is intended to use as less as possible external libs (optional: openGL, gsl, fftw, cgal, png, tiff, boost, MPI, Qt...). -
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dAnalytics
dAnalytics is a software made for education in discriminant analysis.
dAnalytics is a software made for educational purposes to work with discriminant analysis. It's a very simple calculator over bi-dimensional populations. You input a file with two columns (one for each variable) and tryout different separations of populations (blue and red) and analyze it's efficiency by observing the eigen value result for the attempted separation. It also gives many information about the statistics both of the input and the separated populations. There's a documentation folder in the software which brings a quick start guide for this software. -
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Python module to track the overall median of a stream of values "on-line" in reasonably efficient fashion.
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portas
Pequeno script em Python para provar o problema de Monty Hall
O jogo consiste no seguinte: Monty Hall (o apresentador) apresentava 3 portas aos concorrentes, sabendo que atrás de uma delas está um carro (prémio bom) e que as outras têm prêmios de pouco valor. Na 1ª etapa o concorrente escolhe uma porta (que ainda não é aberta); De seguida Monty abre uma das outras duas portas que o concorrente não escolheu, sabendo à partida que o carro não se encontra aí; Agora com duas portas apenas para escolher — pois uma delas já se viu, na 2ª etapa, que não tinha o prêmio — e sabendo que o carro está atrás de uma delas, o concorrente tem que se decidir se permanece com a porta que escolheu no início do jogo e abre-a ou se muda para a outra porta que ainda está fechada para então a abrir. Qual é a estratégia mais lógica? Ficar com a porta escolhida inicialmente ou mudar de porta? Com qual das duas portas ainda fechadas o concorrente tem mais probabilidades de ganhar? Por quê? -
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PYthon RELiabilitY A python package implementing state-of-the-art numerical methods arising in the field of uncertainty quantification : from statistical inference to uncertainty propagation for various purposes.
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Implementation in Python of some of the statistical methods provided by "asurv", the survival analysis software.
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slycat
Web-based data science analysis and visualization platform.
This is Slycat - a web-based data science analysis and visualization platform, created at Sandia National Laboratories. The goal of the Slycat project is to develop processes, tools and techniques to support data science, particularly analysis of large, high-dimensional data. -
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snlanalytic is a small Python script that takes a stem-and-leaf plot as input and returns basic statistics (sum, mean, median, mode) to the user.
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statspy
Python module for statistics built on top of NumPy/SciPy
