Search Results for "stochastic"
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Showing 40 open source projects for "stochastic"
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LINE Solver
Queueing Theory Algorithms
LINE is an open-source software package to analyze queueing models via analytical methods and simulation. The solver is available for Java/Kotlin, MATLAB, and Python. LINE features algorithms for the solution of open queueing systems (e.g., M/M/1, M/M/k, M/G/1, ...), open and closed queueing networks, and layered queueing networks. Additional details are available on the project website: http://line-solver.sf.net. -
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XMDS
Fast integrator of stochastic partial differential equations
XMDS is a code generator that integrates equations. You write them down in human readable form in a XML file, and it goes away and writes and compiles a C++ program that integrates those equations as fast as it can possibly be done in your architecture. -
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Nemo
Individual-based forward-time genetics simulation software
Nemo is an individual-based, forward-time, genetically explicit, and stochastic simulation software designed for the study of the evolution of life history and quantitative traits, and genetic markers under various types of selection, in a spatially explicit, metapopulation framework. -
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Java Modelling Tools is a suite of scientific tools for performance analysis and modelling using queueing theory and colored stochastic Petri nets. Models are solved either with analytical, asymptotic or simulation methods; workload characterization tools are also included in the suite. See the project website for more details: http://jmt.sf.net
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QSMM
An adaptive state model development framework.
QSMM, a recursive acronym for "QSMM State Machine Model", is a framework for learning finite automatons that perform goal-directed interaction with entities which exhibit deterministic or stochastic behavior. The learning process can be carried out in real time together with the interaction process. A basic building block for supporting state models of finite automatons is adaptive probabilistic mapping, which for an argument from its domain returns more often results that maximize or minimize values of one or more objective functions. ... -
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LabRPS
Random phenomena generator
...Code and release files are primarily hosted on https://github.com/LabRPS/LabRPS and mirrored here LabRPS aims to be a tool for the numerical simulation of random phenomena such as stochastic wind velocity, seismic ground motion, sea surface ... etc. It can be in a wide range of uses around engineering, such as random vibration or vibration fatigue in mechanical engineering, buffeting analysis in bridge engineering.... LabRPS is mainly to assist reseachers in related fields to quickly implement new simulation methods programmatically in their new research work based on the existing works, help engineers to numerically generate random phenomena in a more realistic way, helps students and new comers to this field to learn quickly. ... -
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...Zgoubi simulates beam dynamics and polarization in a variety of accelerators (storage ring, synchrotron, cyclotron, betatron, microtron, FFAG, multi-pass ERL, etc) and optical systems (beam lines, magnetic and electrostatic optical components, time-of-flight and mass spectrometers, etc). The code includes built-in fitting procedures with a wide variety of constraints; stochastic SR energy loss; the tracking of synchrotron radiation (SR) Poynting vector; space charge models; various Monte Carlo procedures, etc. Contact: francoisgmeot@gmail.com Documentation (History of accelerators that zgoubi deals with, theory, tutorials): https://link.springer.com/book/10.1007/978-3-031-59979-8 https://link.springer.com/book/10.1007/978-3-031-16715-7, Chap. 14.
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StochSD
CSS package for contin., discrete and combined modelling & simulation
...In particular, StochSD includes features for stochastic modelling and post analysis of multiple simulations followed by presentation of the results in statistical form. Tools for Sensitivity Analysis, Optimization and Statistical Analysis are parts of StochSD. -
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PCRaster
PCRaster environmental modeling software
...A Python framework supports Monte Carlo simulations and data assimilation (Ensemble Kalman Filter and Particle Filter). The Aguila tool allows for the interactive visualisation of stochastic spatio-temporal data. -
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Zarja
Agent-based simulation toolkit
It is an open source scientific library that is focused on multi-agent simulations on graphs. It prepares basic toolkit for agents, models, timers, graphs, nodes and edges. It is also accompanied with tools for data processing. -
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MED-FOES
An Agent-Based Simulation of Invasive Pest Insects
MED-FOES is an implementation of a stochastic Agent-Based Simulation (ABS) system for analyzing demographic changes in a single population of Medfly (Ceratitis capitata) over time. The simulation currently takes population extinction as a given because it aims to give us better estimates of necessary quarantine lengths in areas where Medfly is not currently established but does repeatedly invade. -
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Stochastic simulator for signaling pathways occuring in biological cells. Handles reaction-diffusion processes in 3D tetrahedral meshes. Please check our new repository: https://github.com/CNS-OIST/STEPS
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Cambridge Rocketry Simulator
Simulate high power rocket flights with splash down plots
...Running in Monte Carlo mode allows generates multiple possible flight paths and splash down plots, indicating the probability of landing in an area. Peer-reviewed publication in the Journal of Open Research Software (JORS) http://doi.org/10.5334/jors.137 "Cambridge Rocketry Simulator – A Stochastic Six-Degrees-of-Freedom Rocket Flight Simulator" -
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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.
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RSSA
Rejection-based stochastic simulation algorithm (RSSA)
Rejection-based stochastic simulation algorithm (RSSA) is an efficient exact algorithm for doing stochastic simulation of biochemical reaction systems. RSSA improves over state of the art of stochastic simulations by avoiding and collapsing as much the number of propensity updates. -
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fesslix
Stochastic Analysis
A brief summary of the main features of Fesslix: - Perform non-intrusive reliability analysis or Bayesian updating either --- by running commands on the command line or --- by means of an Octave interface or --- by means of a Python interface - Flexible input language for writing Fesslix parameter files --- Control flow statements (e.g. if, for, while) --- Most parameters can be defined as functions - Working with response surfaces - Linear finite element analysis using truss, beam and plane stress/strain elements - Spectral Stochastic Finite Elements - Bayesian networks This is the download page for Windows executables of Fesslix. -
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Hy3S uses advanced MPI parallelized hybrid stochastic simulation methods to quickly compute the dynamics of biochemical networks with thousands of species/reactions. Many features included (see Home Page). An easy-to-use GUI (Matlab req) is included.
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abc-sde
approximate Bayesian computation for stochastic differential equations
A MATLAB toolbox for approximate Bayesian computation (ABC) in stochastic differential equation models. It performs approximate Bayesian computation for stochastic models having latent dynamics defined by stochastic differential equations (SDEs) and not limited to the "state-space" modelling framework. Both one- and multi-dimensional SDE systems are supported and partially observed systems are easily accommodated. -
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NAADSM
A framework for simulating the spread and control of animal diseases
NAADSM is a framework for creating stochastic, spatial, state-transition simulation models of the spread and control of highly contagious diseases of animals. User-established parameters define model behavior in terms of disease progression; disease spread by animal-to-animal contact, contact with contaminated personnel or equipment, and airborne dissemination; and the implementation of control measures such as vaccination and depopulation. -
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SPiM2Eclipse
Eclipse plugin for Stochastic Pi Machine
Stochastic Pi Machine (SPiM), created by Microsoft, is a programming language for modeling biological processes. Two tools are available from Microsoft for simulation. A web application Visual SPiM, and a destkop application SPiM Player. Both simulation tools require to be run on a Windows platform. Fortunately Microsoft has also released a command line version for Linux and Mac OS based on OCAML however this version will only output a CSV file for the simulation results. ... -
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simbTUM
Simulation of stochastic processes and ODE models in biology.
SIMulation of Biological systems (developed at the TU Munich) This program allows to define ODE-models or stochastic compartemental models of biological processes, to simulate, to fit data and to do some statistics (fitting and statistics for deterministic models only). -
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SPSens
Stochastic parameter sensitivity analysis for chemical networks
SPSens is a complete software package written in C that estimates parameter sensitivities for stochastic models of chemical and biochemical reaction networks using Monte Carlo (MC) stochastic simulations. It is possible to estimate sensitivities with respect to system parameters using the following algorithms: finite difference methods (crude monte carlo, common reaction path, coupled finite differences); likelihood ratio methods; and regularized pathwise derivatives. ... -
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A high-performance simulation package for sampling the chemical and reaction-diffusion master equations. Primarily intended for running stochastic simulations of microbial cells.
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OpenBioGeoSim it's a open source software that simulates the stochastic origin and spread of species geographic ranges in a heterogeneous landscape. It's a free alternative based on Gary Entsminger's BioGeoSim.
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NetBuilder' is a tool for building, visualizing, and simulating multi-layered biological networks, structured as hierarchical Petri-nets. It has a built-in stochastic simulator, but also provides easy access to other simulation and analysis.