Displaying 1 to 8 from 8 results

glm-js - JavaScript adaptation of the OpenGL Mathematics (GLM) C++ library interfaces.

  •    Javascript

experimental JavaScript implementation of the OpenGL Mathematics (GLM) C++ Library

retro - A simple retro-pixelart 2D game engine (Hacker's Week 5 workshop)

  •    C++

retro++ is a simple retro-pixelart 2D game engine that aims to help to introduce anybody with knowledge of programming (specially with C++) into the world of game development without having to deal with the low-level APIs OpenGL or DirectX, or with newer APIs like Vulkan or Metal (both unsupported in this engine). The repo has submodules on it, so it will initialize them when cloning.

h2o4gpu - H2Oai GPU Edition

  •    Python

H2O4GPU is a collection of GPU solvers by H2Oai with APIs in Python and R. The Python API builds upon the easy-to-use scikit-learn API and its well-tested CPU-based algorithms. It can be used as a drop-in replacement for scikit-learn (i.e. import h2o4gpu as sklearn) with support for GPUs on selected (and ever-growing) algorithms. H2O4GPU inherits all the existing scikit-learn algorithms and falls back to CPU algorithms when the GPU algorithm does not support an important existing scikit-learn class option. The R package is a wrapper around the H2O4GPU Python package, and the interface follows standard R conventions for modeling. Daal library added for CPU, currently supported only x86_64 architecture.

glm - jvm glm

  •    Kotlin

This is the Kotlin port of OpenGL Mathematics (GLM), written by g-truc (repository), a header only C++ mathematics library for graphics software based on the OpenGL Shading Language (GLSL) specifications. GLM provides classes and functions designed and implemented with the same naming conventions and functionality than GLSL so that anyone who knows GLSL, can use GLM as well in Kotlin and Java.




margins - An R Port of Stata's 'margins' Command

  •    R

The margins and prediction packages are a combined effort to port the functionality of Stata's (closed source) margins command to (open source) R. The major functionality of margins - namely the estimation of marginal (or partial) effects - is provided through a single function, margins(). This is an S3 generic method for calculating the marginal effects of covariates included in model objects (like those of classes "lm" and "glm"). Users interested in generating predicted (fitted) values, such as the "predictive margins" generated by Stata's margins command, should consider using prediction() from the sibling project, prediction. Stata's margins command is incredibly robust. It works with nearly any kind of statistical model and estimation procedure, including OLS, generalized linear models, panel regression models, and so forth. It also represents a significant improvement over Stata's previous marginal effects command - mfx - which was subject to various well-known bugs. While other Stata modules have provided functionality for deriving quantities of interest from regression estimates (e.g., Clarify), none has done so with the simplicity and genearlity of margins.

GLM - Code for the General Lake Model

  •    C

The General Lake Model (GLM) is a water balance and one-dimensional vertical stratification hydrodynamic model. It accounts for the effect of inflows/outflows, mixing and surface heating and cooling, including the effect of ice cover. It is suited to longer-term investigations ranging from seasons to decades, and for coupling with biogeochemical models to explore the role that stratification and vertical mixing has on biogeochemical and ecological dynamics of lakes.







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