Search Results for "setup-subversion"

A JavaScript display engine for mathematics that works in all browsers. No more setup for readers. It just works. MathJax provides tools to transform your content from traditional print sources into modern, accessible web content and ePubs. The MathJax team is available to train your staff in using our resources for preparing online teaching material and creating accessible STEM content. MathJax is highly flexible and can be tailored to the needs of your institution by creating customized configurations and specialized software workflows. ...

...These packages come with their own CPU and GPU kernel implementations based on C++/CUDA extensions. We do not recommend installation as root user on your system python. Please setup an Anaconda/Miniconda environment or create a Docker image. We provide pip wheels for all major OS/PyTorch/CUDA combinations.

MCPower-GUI is a desktop application that provides a graphical interface for the MCPower Monte Carlo power analysis library. It guides users through the full workflow across three tabs: Model setup (formula input with live parsing, CSV data upload with auto-detected variable types, effect size sliders, and correlation editing), Analysis configuration (find power for a given sample size or find the minimum sample size for a target power, with multiple testing correction and scenario analysis), and Results (interactive charts, exportable tables, and auto-generated Python replication scripts). ...

GLSLmath provides C++ math operations as defined by GLSL. For example, it provides methods to easily setup viewing transformations and perspective projections. GLSLmath has been inspired by the glm and slmath libraries, which aim to mimic GLSL, but in contrast to those GLSLmath does not focus on a complete conforming implementation of GLSL. It rather aims to provide a convenient single header file that implements the most commonly used subset of GLSL so that it is easy to use for rapid prototyping and GLSL teaching purposes. ...

...ZIP also include 16 MB file with 16,7 mil numbers of PI Benchmark(Single-Thread): Hardware & Environment Apple Silicon: Apple M2 (Mac mini/MacBook) x86_64 Platform: Intel Core Ultra 5 225F (Arrow Lake, 10 Cores) OS 1: Fedora 43 (GNOME) OS 2: Windows 11 Pro (23H2/24H2) Software: Python 3.14.3 + Numba JIT (latest) Results (Lower is better) Platform / OS CPU Time (Seconds) macOS (Native) Apple M2 52.151311 s (in default setup) Fedora Linux Intel Core Ultra 5 225F 58.536457 s (in default Power Management: Balanced) Windows 11 Intel Core Ultra 5 225F 59.681427 s (important! Power Management set as High Performance .. in Balanced is slow)

If you have Windows or a MAC , you can setup and run Statistics Tables with very little effort. You can use jdistabs in place of paper Probability Tables to get electronic probabilities. You can also download the Java code used to create this APP. There are 2 zips. One is for a working windows APP, and the other with complete code and file structure. I used Eclipse to develop the APP.

...It is supposed to be a fast and easy to use/modify library for anyone interested in assessing interval arithmetic merits or using it on a regular basis. WARNING: starting October 2016, the new location for GAOL is http://frederic.goualard.net/#research-software. Sourceforge and the Sourceforge Subversion repository will no longer be used.

...Especially need to catch exceptions and give reasonable error messages. (In the moment, the standard error handler is invoked. Simply click "resume" on any error.) For newest binary builds, look in the "/bin" directory of the Subversion distribution (code section). Make sure to also download the 2008 version of math.dotnet.iridium. The corresponding dll file is in the files section.

Crispy Plotter is a function graph plotter for mathematical functions, featuring high drawing speed and an intuitive interface that is fun to use.

Hier wird die Versionsverwaltung (SVN) für die LaTeX-Mitschrift der Vorlesung "Analysis für Informatiker und Statistiker" gehostet. Diese findet im WS 2009/2010 an der LMU München statt.

Structlab is a machine learning C++ framework for structured domains, which provides a toolbox of learning methods and tools for preprocessing and visualization. It also provides a GUI to setup elaborate experiments in a visual and intuitive way.