Search Results for "statistics algebra"

SymPy is an open source Python library for symbolic mathematics. Its goal is to become a full-featured computer algebra system (CAS) while maintaining the simplicity of its code. Written entirely in Python, SymPy is easy to use, comprehensible and easily extensible. It’s also very lightweight as it solely depends on mpmath, a pure Python library for arbitrary floating point arithmetic. SymPy has participated in every Google Summer of Code since 2007 and because of this has continuously...

This is the main repository for the SciPy library, one of the core packages that make up the SciPy stack. SciPy is an open source software used in the fields of mathematics, science, and engineering, with modules for statistics, optimization, integration, linear algebra, signal and image processing, and many more. The SciPy library contains many of the user-friendly and efficient numerical routines, including those for numerical integration, interpolation, and optimization. SciPy is built to work with NumPy, a software that provides convenient and fast N-dimensional array manipulation. ...

***** THIS PROJECT HAS MOVED TO https://gitlab.in2p3.fr/sirocco/sdap/sdap-dev ***** ***** THIS PROJECT HAS MOVED TO https://gitlab.in2p3.fr/sirocco/sdap/sdap-dev ***** ***** THIS PROJECT HAS MOVED TO https://gitlab.in2p3.fr/sirocco/sdap/sdap-dev ***** Within the SIROCCO suite of numerical tools, the purpose of SDAP is to provide a flexible platform to carry out multivariate assimilation of geophysical data in a numerical model. The program is multi-grid (finite differences or finite...

PyArmadillo - streamlined linear algebra library for Python, with emphasis on ease of use. Alternative to NumPy / SciPy. * Main page: https://pyarma.sourceforge.io * Documentation: https://pyarma.sourceforge.io/docs.html * Bug reports: https://pyarma.sourceforge.io/faq.html * Git repo: https://gitlab.com/jason-rumengan/pyarma

This repository is a curated roadmap for learning the core mathematics used in computer science, machine learning, and data science without getting lost in unnecessary detours. It organizes topics like algebra, calculus, linear algebra, probability, and statistics into a pragmatic sequence that favors intuition and problem-solving over purely formal proofs. The materials emphasize short, high-leverage resources—video lectures, concise notes, and hands-on exercises—that help you build momentum quickly. It also suggests checkpoints and practice ideas so you can test comprehension and move forward with confidence. ...

...This sourceforge project contains only old historical versions of the software. SciPy is package of tools for science and engineering for Python. It includes modules for statistics, optimization, integration, linear algebra, Fourier transforms, signal and image processing, ODE solvers, and more.

SCaVis is an environment for scientific computation, data analysis and data visualization for scientists, engineers and students. The program is fully multiplatform (100% Java) and integrated with Java and a number of scripting languages: Jython (Python), Groovy, JRuby, BeanShell. SCaVis can be used to plot functions and data in 2D and 3D, perform statistical tests, data mining, numeric computations, function minimization, linear algebra, solving systems of linear and differential...

A lightweight C++ and Python library for finance, statistics and linear algebra. Finance features include compound rate present/future value, annuity, various present/future value coefficients ... Statistics features include mean, median, variance, standard deviation, covariance, correlation, linear regression, probabilities and random variates of various distributions ... Linear algebra features include matrix arithmetic, inverse, determinant, rank, linear system solution, lu/qr decomposition, svd, eigen values/vectors ... ...

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.