Search Results for "algorithms" - Page 2
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Showing 136 open source projects for "algorithms"
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Neural Networks Collection
Neural Networks Collection
...The project can run in two modes: command line tool and Python 7.2 extension. Currently, Python version appears more functional, as it allows easy interaction with algorithms developed by other people. -
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iHome by ionware
iHome Smart Home System Platform
iHome is a fully tested Smart Home Automation system using the Raspberry Pi Zero WiFi SBC and Linux OS and has all the functional features of NEST or ECOBEE smart thermostats with the added benefit of full privacy and security at less than half the price! It incorporates MBLogic with algorithms and Modbus coms for HVAC home control via the ionware modbus compatible ionC1 input/output controller board. The iHome software system comes fully configured as a SD Card image file for Raspberry Pi Zero wifi Plug and Play capability complete with MBLogic, Node-RED and MQTT already fully installed and ready to go. See wiki instructions to burn the SD Card image file, insert into your RPi Zero and Plug and Play. ... -
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PBTK Optimizer
Application for optimization of parameters in PBTK models
...When it is impractical to use these methods to estimate a parameter, techniques can be used to optimize parameters so that model results best fit validation data. This tool was designed to optimize a user-specified list of parameters to a user-specified PBTK model. The user also controls validation data and optimization algorithms. In addition to optimized parameters, the tool outputs statistical information about the fit of the optimized model. -
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DEBay
Deconvolutes qPCR data to estimate cell-type-specific gene expression
DEBay: Deconvolution of Ensemble through Bayes-approach DEBay estimates cell type-specific gene expression by deconvolution of quantitative PCR data of a mixed population. It will be useful in experiments where the segregation of different cell types in a sample is arduous, but the proportion of different cell types in the sample can be measured. DEBay uses the population distribution data and the qPCR data to calculate the relative expression of the target gene in different cell types in... -
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RoboSchool
Open source software for robot simulation, integrated with OpenAI Gym
...The library is built on the Bullet Physics engine, making it accessible without the licensing requirements of Mujoco. Roboschool includes training scripts and examples for applying reinforcement learning algorithms to its environments. While the project has since been deprecated in favor of more modern frameworks, it remains historically significant as a bridge between early reinforcement learning research and scalable, open-access environments. Its goal was to make reproducible robot learning experiments available to a wider audience without restrictive dependencies . -
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An open source framework for LC-MS based proteomics and metabolomics. OpenMS offers data structures and algorithms for the processing of mass spectrometry data. The library is written in C++. Our source code and wiki lives on GitHub (https://github.com/OpenMS/OpenMS).
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PyRobot
An Open Source Robotics Research Platform
...The library exposes canonical abstractions (base, arm, gripper, camera, sensors) with calibration and kinematics helpers so beginners can get meaningful results quickly. It also plugs into simulation backends, letting you prototype perception and control algorithms before deploying on physical robots. By standardizing common operations and providing examples, PyRobot reduces boilerplate and encourages best practices in perception-control loops, data collection, and benchmarking. -
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plot.py
direct data plotting and evaluation
The Plot.py project tries to supply a measurement data visualization and treatment framework being easy to use while keeping the freedom for advanced users to execute additional data treatment algorithms. Plotting is done via gnuplot and the script used to produce the graphs can be exported for later use/changes. Many raw experimental data types (mostly of x-ray and neutron scattering experiments) are supported with more to be added on user request. The data treatment includes non-linear fitting, integration and differentiation, peak-finder and more. ... -
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Presage
the intelligent predictive text entry platform
...Presage generates predictions by modelling natural language as a combination of redundant information sources. Presage computes probabilities for words which are most likely to be entered next by merging predictions generated by the different predictive algorithms. Presage's modular and extensible architecture allows its language model to be extended and customized to utilize statistical, syntactic, and semantic predictive algorithms. Presage's predictive capabilities are implemented by predictive plugins. Predictive plugins use services provided by the platform to implement multiple prediction techniques. -
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PySptools
Hyperspectral algorithms for Python
A lightweight hyperspectral imaging library that provides developers with spectral algorithms for the Python programming language. New for v0.14.x: a scikit-learn bridge (alpha and partial). The functions and classes are organized by topics: * abundance maps: FCLS, NNLS, UCLS * classification: AbundanceClassification, NormXCorr, KMeans SAM, SID, SVC * detection: ACE, CEM, GLRT, MatchedFilter, OSP * distance: chebychev, NormXCorr, SAM, SID * endmembers extraction: ATGP, FIPPI, NFINDR, PPI * material count: HfcVd, HySime * noise: Savitzky Golay, MNF, whiten * sigproc: bilateral * sklearn: HyperEstimatorCrossVal, HyperSVC and others * spectro: convex hull quotient, features extraction (tetracorder style), USGS06 lib interface * util: load_ENVI_file, load_ENVI_spec_lib, corr, cov and others The library do an extensive use of the numpy numeric library and can achieve good speed. ... -
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Charting tools, backtesting tools, and data visualization tools for the most popular cryptocurrencies.
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darc
Durham Adaptive-optics Real-time Controller
darc, the Durham Adaptive optics Real-time Controller. For documentation or darctalk client only, select "View all files". For the latest bleeding-edge version, please use: git clone git://git.code.sf.net/p/darc2/code darc (no password required) (this changed May 2013 due to a sourceforge update). If you use darc, please cite with: Basden, A and Myers, R, MNRAS Vol 242, page 1483, 2012 -
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TEACUP
TCP Experiment Automation Controlled Using Python
TEACUP automates many aspects of running TCP performance experiments in a specially-constructed physical testbed. TEACUP enables repeatable testing of different TCP algorithms over a range of emulated network path conditions, bottleneck rate limits and bottleneck queuing disciplines. TEACUP utilises a text-based configuration file to define experiments as combinations of parameters specifying desired network path and end host conditions. When multiple values are provided (e.g. for TCP congestion control algorithm), an experiment is made up of multiple tests. ... -
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FastVersion
FastVersion is a Qgis plugin for data versioning in a Postgis database
...It allows to create, changes and eliminate versions, and within each version , to insert, modify and eliminate elements. It is possible carry out the processes of “post” from one version to another, with conflict resolution functionality. The system uses algorithms and data structures so that information is not duplicated each time a version is created. We recommend downloading it from the Qgis app. Plugins->Manage and Install Plugins->Settings->Show also experimental plugins Plugins->Manage and Install Plugins->Search FastVersion If downloaded from sourceforge, it must be unzipped in \.qgis2\python\plugins -
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Phaistos is a framework for all-atom Monte Carlo simulations of proteins. It incorporates several advanced probabilistic models of protein structure for conformational sampling, efficient move-algorithms and the OPLS and PROFASI forcefields.
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Simple Python Fixed-Point Module
Pure-python binary fixed-point arithmetic library
This Python module provides basic facilities for mathematics on fixed-point numbers. The number of fractional binary digits is tunable, allowing near-arbitrary precision arithmetic. Arithmetic & functions such as sqrt, exp, log, sin & cos are available. For the latest releases please visit https://github.com/rwpenney/spfpm -
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Distant Speech Recognition
Beamforming and Speech Recognition Toolkit
BTK contains C++ and Python libraries that implement speech processing and microphone array techniques such as speech feature extraction, speech enhancement, speaker tracking, beamforming, dereverberation and echo cancellation algorithms. The Millennium ASR provides C++ and python libraries for automatic speech recognition. The Millennium ASR implements a weighted finite state transducer (WFST) decoder, training and adaptation methods. These toolkits are meant for facilitating research and development of automatic distant speech recognition. -
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RDKit
Open-Source Cheminformatics and Machine Learning
A collection of cheminformatics and machine-learning software written in C++ and Python. NOTE: the RDKit source code and downloads are now in github: https://github.com/rdkit/rdkit The core algorithms and data structures are written in C++. Wrappers are provided to use the toolkit from either Python or Java. Additionally, the RDKit distribution includes a PostgreSQL-based cartridge that allows molecules to be stored in relational database and retrieved via substructure and similarity searches. -
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The Modular toolkit for Data Processing (MDP) is a Python data processing framework. From the user's perspective, MDP is a collection of supervised and unsupervised learning algorithms and other data processing units that can be combined into data processing sequences and more complex feed-forward network architectures. From the scientific developer's perspective, MDP is a modular framework, which can easily be expanded. The implementation of new algorithms is easy and intuitive. The new implemented units are then automatically integrated with the rest of the library. ...
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This project, developed at UCL London, provides code for tomographic reconstruction. NiftyRec is written in C and has Python and Matlab extensions. Computationally intensive functions have a GPU accelerated version based on CUDA.
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SteppedStateMachine
Creates and operates a stepped state machine
Implements a stepped state machine, i.e. a state machine which executes a single state transition at a time. Because of this, no data, e.g. state data, can be stored between executions. Instead, any such data must be stored in persistent storage between executions. This permits operation of the state machine as a CGI program in a web server. A WSGI or fastCGI or other such web server is not required. Received symbols may be received from sources outside the state machine, or may be... -
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ExSTraCS
Extended Supervised Tracking and Classifying System
This advanced machine learning algorithm is a Michigan-style learning classifier system (LCS) developed to specialize in classification, prediction, data mining, and knowledge discovery tasks. Michigan-style LCS algorithms constitute a unique class of algorithms that distribute learned patterns over a collaborative population of of individually interpretable IF:THEN rules, allowing them to flexibly and effectively describe complex and diverse problem spaces. ExSTraCS was primarily developed to address problems in epidemiological data mining to identify complex patterns relating predictive attributes in noisy datasets to disease phenotypes of interest. ... -
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ChIP-RNA-seqPRO
ChIP-RNA-sequencing-processing (ChIP-RNA-seqPRO)
ChIP-RNA-seqPRO: A strategy for identifying regions of epigenetic deregulation associated with aberrant transcript splicing and RNA-editing sites. Runnable python scripts packaged together with customized annotation libraries, demo data input and README guide. 9/26 : v1.1 Updated MAIN_IV to debug error thrown by python pandas no longer supporting 'subset'. This code will no longer be actively maintained/updated here. A cloud-based resource for comparative analysis of epigenetic,... -
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The General Hidden Markov Model Library (GHMM) is a C library with additional Python bindings implementing a wide range of types of Hidden Markov Models and algorithms: discrete, continous emissions, basic training, HMM clustering, HMM mixtures.
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StochPy - Stochastistic modeling in Python - is an easy-to-use package, which provides several stochastic simulation algorithms and unique analysis techniques, which can be used for stochastic simulations of biochemical systems.
