Open Source Algorithms - Page 40
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PI-Based Image Encoder / Converter
Python code able to convert / compress image to PI (3.14, π) Indexes
Image processing tool that encodes pixel data as indices within the first 16.7 million digits of PI (π). Features high-performance Numba-accelerated search and a signature 'film-grain' aesthetic upon reconstruction. 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) -
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PMCGPU
Parallel simulators for Membrane Computing on the GPU
Membrane Computing is a new research area (within Natural Computing) that aims to provide computing devices abstracted from the functioning and structure of living cells. These devices are called P systems. The objective of this project (PMCGPU) is to bring together all the researchers working on the development of parallel simulators for P systems, specially those using the GPU (e.g. CUDA, OpenCL, etc). Other parallel platforms are also welcome (multicore and manycore, FPGAs, etc). This project has been initiated by the Research Group on Natural Computing (Department of Computer Science and Artificial Intelligence, University of Seville). PMCGPU was born inside the P-Lingua project, of the same research group. PMCGPU is a GNU project, so all the applications developed within it are released under the GPLv3 license. Just contact us if you want to participate. Please, visit the Wiki of the project for further information. -
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PPSeq: Parallel NGS Analysis
Parallel Processing for Next-Generation Sequencing (NGS) Analysis
High-throughput next generation sequencing (NGS) technology has quickly emerged as a powerful tool in many aspects of biomedical research. However, along with its rapid development, the data magnitude and analysis complexity for NGS far exceed the capacity and capability of traditional small-scale computing facilities, such as multithreading algorithms on standalone workstations. To address this issue, here we present a solution using the ever-increasing supply of processing power by massive parallel processing (MPP) systems. -
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PRML
PRML algorithms implemented in Python
PRML repository is a respected and well-maintained project that implements the foundational algorithms from the famous textbook Pattern Recognition and Machine Learning by Christopher M. Bishop, providing a practical and accessible Python reference for both students and professionals. Rather than just summarizing concepts, the repository includes working code that demonstrates linear regression and classification, kernel methods, neural networks, graphical models, mixture models with EM algorithms, approximate inference, and sequential data methods — all following the book’s structure and notation. Many of these algorithms are paired with Jupyter notebooks that let users interact with the code, visualize results, and experiment with parameters in a way that deeply strengthens theoretical understanding. -
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PRMLT
Matlab code of machine learning algorithms in book PRML
This Matlab package implements machine learning algorithms described in the great textbook: Pattern Recognition and Machine Learning by C. Bishop (PRML). It is written purely in Matlab language. It is self-contained. There is no external dependency. This package requires Matlab R2016b or latter, since it utilizes a new Matlab syntax called Implicit expansion (a.k.a. broadcasting). It also requires Statistics Toolbox (for some simple random number generator) and Image Processing Toolbox (for reading image data). The code is extremely compact. Minimizing code length is a major goal. As a result, the core of the algorithms can be easily spotted. Many tricks for speeding up Matlab code are applied (e.g. vectorization, matrix factorization, etc.). Usually, functions in this package are orders faster than Matlab builtin ones (e.g. kmeans). Many tricks for numerical stability are applied, such as computing probability in logrithm domain, square root matrix update to enforce matrix symmetry. -
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Coupling the notion that during the search for the minimum of a function we must pass through its solution with a PSO solution generator engine, is the approach for solving, in time domain, a non-linear algebric-differential system of equations.
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Generic toolbox of Particle Swarm Optimization developed in Scilab (PSOTS). It is developed for a variety of complex problems, including single and multi-objective optimization problems, continuous and discrete problems, and mixed integer problems.
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PadotusRNDT.js
This library allows you to generate a random number
This library allows you to generate a random number in the specified range from 0 to n, without using the built-in function Math.random (), and gets a random number from the processing time of polymorphic mathematical calculations, which depends on the current physical parameters of the CPU, RAM, and t .P. The resulting sequence corresponds to a discrete uniform distribution and is close to natural random sequences in terms of statistical randomness tests (LFSR, Approximate Entropy, DIEHARD Test). -
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Pambaf
Another encryption algorithm
Pambaf is a new encryption algorithm for users or developers with extremely high demands for security. -
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ParaBWT - parallel BWT construction
a parallel and space-efficient Burrows-Wheeler transfrom constructor
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Generic engine to filter information. We wish to show that the power of expression of a filter makes it possible to appreciably reduce the size of the code necessary to extract information and that it is possible in Python.
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On open source MPI implementation of parallel bucket sorting. This implementation is scalable and gives linear speedup on SGI(Altix). The program sorts at using the bits and hence is stronger than other sorters which make assumptions about keys.
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User friendly application with graphical interface, for creating and training a multi-layer feed-forward neural-networks. The application is intended for systems of GRID computation.
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Sequential and parallel implementation of string quicksorts(-select) . Articles: On the number of string lookups in BSTs (and related algorithms) with digital access/ Combining digital access and parallel partition for quicksort and quickselect.
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The Parameter Tuning Unity (PTU) aims to adapt the parameters of ever connected multi-agents system, or expert system with a plugged optimization heuristic likes the descent of gradient for instance.
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PartWriter
A project designed to write sheet music.
The project is composed of two layers. The first layer is an artificial intelligence engine, partwriter, that writes music based on some heuristic. The second layer is the layer that defines the heuristic. The definition of this heuristic defines the type of music that partwriter will create. Currently (December 2012), the deepest layer is more or less complete. The author is now writing second layers of interest, namely species counterpoint heuristics according to Fux's Gradus Ad Parnassum. -
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Path Finder Qt
finds the sortest path on the square board. GUI is implemented in Qt.
The program demonstrates the usage of the A* algorithm to find the shortest path. It searches the shortest path between source piece and target piece on the rectangular board. On the board the obstacles (wall) can be constructed. In addition to the algorithm, the GUI is provided. The GUI is written in Qt. Using the GUI, one can construct and move interactively the obstacles on the board. For every modification of the board, the shortest path is calculated automatically. Some statistics related to A* algorithm are presented as well. This project is related to my other projects located at sourceforge as well: https://sourceforge.net/projects/a-star/ https://sourceforge.net/projects/shortest-path-graph-a-star/ -
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Path Partitioner
Finds bad examples for the local search Path Partitioning algorithm
Path Partitioner constructs random graph partitions and solves the linear (or integer) programming problems that assign weights to the edges such that the performance ratio of the local search algorithm for the Path Partitioning problem is minimized. See http://www.tau.ac.il/~ohadschn/Thesis/Partitioning.pdf. Requirements: Microsoft Automatic Graph Layout http://research.microsoft.com/en-us/projects/msagl/ Gurobi Optimizer http://www.gurobi.com/ Permutations, Combinations, and Variations using C# Generics http://www.codeproject.com/Articles/26050/Permutations-Combinations-and-Variations-using-C-G -
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PdfPageCounter
C++ code to count the number pages in a given PDF file.
This C++ library contains the 'PdfPageCount' class that performs the single task of finding the number of pages in a given PDF document. While the PdfPageCount class is very simple to use, the contained code is complex because the page count can be hidden in any number of places, quite often within compressed data. -
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Functions for creating random (pronouncable) "names", such as are used in a rogue-like. Some of the better names: Kehizarich, Awzecharz, Vizoueurv, Rieri
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PetoronHash2
PH2 Permutation-based cryptographic post-quantum hash library with duplex construction (C++20)
PetoronHash2 (PH2) is a standalone ARX-based sponge construction that combines: A 4096-bit internal permutation core A sponge/duplex architecture with explicit capacity separation An extendable-output function (XOF) Memory-hard (HARD) and burn (BURN) modes A structured tagged absorb scheme A parameterized architecture suitable for hashing, KDF, and stress-oriented derivation PH2 is designed as a wide-state cryptographic primitive with explicit domain separation and configurable output length. https://github.com/01alekseev/PetoronHash2 Petoron | Ivan Alekseev | MIT license -
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PetriOpti
Petri network optimization with Martinez-Silva algorithm
A simply application in order to demonstrate Martinez-Silva optimization algorithm on Petri networks. -
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Library Of Randomized Algorithms: Randomization is a powerful idea has applications in science and engineering. Difficult optimization problems, protein folding and data mining are only a few of the problems that have been solved using randomization.
