Search Results for "performance"
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Showing 12 open source projects for "performance"
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Swift Numerics
Advanced mathematical types and functions for Swift
...The package includes RealModule utilities and a full Complex type with the expected arithmetic and transcendental functions, bridging a long-standing gap for numerics in Swift. API design follows Swift’s emphasis on value semantics and protocol-oriented programming, enabling compiler optimizations and predictable performance. The modules are factored to keep dependencies minimal and to allow adopters to pull in only what they need. As a result, Swift Numerics underpins higher-level libraries in simulation, signal processing, and machine learning written in pure Swift. -
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JAX
Composable transformations of Python+NumPy programs
...But JAX also lets you just-in-time compile your own Python functions into XLA-optimized kernels using a one-function API, jit. Compilation and automatic differentiation can be composed arbitrarily, so you can express sophisticated algorithms and get maximal performance without leaving Python. -
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Digraph3
A collection of python3 modules for Algorithmic Decision Theory
...Technical documentation and tutorials are available under the following link: https://digraph3.readthedocs.io/en/latest/ The tutorials introduce the main objects like digraphs, outranking digraphs and performance tableaux. There is also a tutorial provided on undirected graphs. Some tutorials are problem oriented and show how to compute the winner of an election, how to build a best choice recommendation, or how to linearly rank or rate with multiple incommensurable performance criteria. Other tutorials concern more specifically operational aspects of computing maximal independent sets (MISs) and kernels in graphs and digraphs. -
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NAVAL-SEM
Free offline SEM software with HTMT, bootstrapping & exports
NAVAL-SEM is a free, open-source, fully offline desktop application for Structural Equation Modeling (SEM), supporting both PLS-SEM and CB-SEM workflows. Designed for researchers, PhD scholars, professors, students, and analysts, it enables advanced quantitative research without subscriptions, cloud dependencies, or proprietary software restrictions. Key features include visual drag-and-drop model building, bootstrapping, mediation analysis, HTMT, AVE, Composite Reliability (CR),... -
Error to trace to log to deploy. One click. No SSH.AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
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PI-Based Image Encoder / Converter
Python code able to convert / compress image to PI (3.14, π) Indexes
...Power Management set as High Performance .. in Balanced is slow) -
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Uranie
Uranie is CEA's uncertainty analysis platform, based on ROOT
...It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. Is is available both for Unix and Windows platforms (a dedicated platform archive is available on request). Note : if you have downloaded version 3.12 before the 8th of february, a patch exists for a minor bug on TOutputFileKey file, don't hesitate to ask us. -
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...Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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PanelCheck is an easy-to-use software tool for visualization of sensory profiling data using different types of plots. The joint information from the implemented plots provide detailed insight into assessor and panel performance.
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wmtsa-python
Discrete wavelet methods for time series analysis using python
...This module started as translation of the wmtsa Matlab toolbox (http://www.atmos.washington.edu/~wmtsa/), so most naming conventions and most of the code structure follows their choices. The code uses a mix of python and cython for improved performance. The code reflects my needs and preferences, but contributions from others are welcome. The code has to some extent been tested, but bugs are to be expected. -
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The Toolkit for Advanced Discriminative Modeling (TADM) is a C++ implementation for estimating the parameters of discriminative models, such as maximum entropy models. It uses the PETSc and TAO toolkits to provide high performance and scalability.
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PyLife is an implementation of the game of life algorithm featuring parallel programming. It uses MPI and python to achieve a consistent software architecture and reliably performance.
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