Displaying 1 to 20 from 21 results

gophernotes - The Go kernel for Jupyter notebooks and nteract.

  •    Go

Acknowledgements - This project utilizes a Go interpreter called gomacro under the hood to evaluate Go code interactively. The gophernotes logo was designed by the brilliant Marcus Olsson and was inspired by Renee French's original Go Gopher design. Important Note - gomacro relies on the plugin package when importing third party libraries. This package works reliably on Mac OS X only with Go 1.10.2+ as long as you never execute the command strip gophernotes. If you can only compile gophernotes with Go <= 1.10.1 on Mac, consider using the Docker install and run gophernotes/Jupyter in Docker.

tf-quant-finance - High-performance TensorFlow library for quantitative finance.

  •    Jupyter

This library provides high-performance components leveraging the hardware acceleration support and automatic differentiation of TensorFlow. The library will provide TensorFlow support for foundational mathematical methods, mid-level methods, and specific pricing models. The coverage is being rapidly expanded over the next few months. Foundational methods. Core mathematical methods - optimisation, interpolation, root finders, linear algebra, random and quasi-random number generation, etc.

Field Modeler 2012


Field Modeler 2012 was designed to allow introductory and advanced undergraduate students to get a ‘feel’ for the nature of the electromagnetic field.

herbie - Synthesis for floating-point expressions

  •    Racket

Herbie synthesizes floating-point programs from real-number programs, automatically handling simple numerical instabilities. Visit our website for tutorials, documentation, and an online demo.Herbie can improve the accuracy of many real-world programs, and is used by scientists in many disciplines. It has lead to two patches (for complex square roots and trigonometric functions), in math.js an open-source mathematics library. Herbie has semi-regular releases twice a year, maintains backwards compatibility, and uses standardized formats.

mpmath - Python library for arbitrary-precision floating-point arithmetic

  •    Python

A Python library for arbitrary-precision floating-point arithmetic. Numerous other people have contributed by reporting bugs, requesting new features, or suggesting improvements to the documentation.

riemann_book - Book in progress to illustrate Riemann solvers in Jupyter notebooks.

  •    HTML

This repository contains work on a book in progress to illustrate Riemann solvers in Jupyter notebooks. Contributors: @ketch, @rjleveque, and @maojrs.

mlinterp - Fast arbitrary dimension linear interpolation in C++

  •    C++

mlinterp is a fast C++ routine for linear interpolation in arbitrary dimensions (i.e., multilinear interpolation). mlinterp is written by Parsiad Azimzadeh and released under a permissive MIT License. The latest release can be downloaded here.

QuantPDE - :octocat: A high-performance, open-source, C++ library for pricing derivatives.

  •    C++

A high-performance, open-source, C++ library for pricing derivatives. Read the Getting Started section of the wiki to learn how to use QuantPDE.

RcppNumerical - Rcpp Integration for Numerical Computing Libraries

  •    C++

Rcpp is a powerful tool to write fast C++ code to speed up R programs. However, it is not easy, or at least not straightforward, to compute numerical integration or do optimization using pure C++ code inside Rcpp. RcppNumerical integrates a number of open source numerical computing libraries into Rcpp, so that users can call convenient functions to accomplish such tasks.

freeCappuccino - A three-dimensional unstructured finite volume code for fluid flow simulations.

  •    Fortran

The freeCappuccino is a three-dimensional fully unstructured finite volume code for Computational Fluid Dynamics which comes in serial and parallel version. Moreover, freeCappuccino is a fortran library for manipulation of discrete tensor fields, defined over polyhedral meshes.

descent - First-order optimization tools

  •    Python

Descent is a package for performing first-order optimization in python. Documentation (work in progress) is available at descent.readthedocs.org.

NumDiff - Modern Fortran Numerical Differentiation Library

  •    Fortran

NumDiff provides a modern Fortran interface for computing the Jacobian (derivative) matrix of m nonlinear functions which depend on n variables. The Jacobian matrix is required for various applications, including numerical optimization. The library also provides for computing the sparsity of this matrix, and returning the Jacobian in sparse or dense form. This is currently an experimental work in progress and is not production ready. The goal is a comprehensive library that contains a full suite of computationally efficient implementations of algorithms for sparsity determination and numerical differentiation.

double_pendulum - Animations of random double pendulums

  •    Python

The code behind @pendulum_bot Twitter bot which posts animations of a double pendulum released from a random position to swing for 30 seconds. The animation is saved as .mp4 video in animations subdirectory.

poisson-image-blending - :art: Web-based implementation of the poisson image blending in HTML5 Canvas / JavaScript

  •    Javascript

:art: Web-based implementation of the poisson image blending in HTML5 Canvas / JavaScript

sparse-linear-algebra - Numerical computation in native Haskell

  •    Haskell

This library provides common numerical analysis functionality, without requiring any external bindings. It aims to serve as an experimental platform for scientific computation in a purely functional setting. Mar 14, 2018: Mostly functional, but there are still a few (documented) bugs. Complex number support is still incomplete, so the users are advised to not rely on that for the time being. The issues related to Complex number handling are tracked in #51, #12, #30.

stats - A C++ header-only library of statistical distribution functions.

  •    C++

StatsLib is a templated C++ library of statistical distribution functions, featuring unique compile-time computing capabilities and seamless integration with several popular linear algebra libraries. The following options should be declared before including the StatsLib header files.