Search Results for "framework python" - Page 2
Sort By:
Showing 39 open source projects for "framework python"
View related business solutions-
$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
-
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
1
Emulica provides manufacturing control engineers and researchers with generic modeling components to build industry-scale virtual (emulated) shop floor systems, and thus test control approaches.
-
2
FAUNUS is an object oriented class library for molecular simulation, written in C++. It contains routines and utility programs for, Metropolis Monte Carlo sampling (NVT, NPT, NmuT ensembles), Macromolecules, Proton Titration, Widom Analysis etc.
-
3
Ouroborus is an artificial life framework for mobile agents on a background of cellular automata. It can be used to teach and research topics such as population genetics, ecology and evolution. The demo includes a curses view and live Csound audio.
-
4
-
Veeam Data Platform v13.1Try Veeam Data Platform today. Experience the unified platform that's secure by design, portable by default, and proven to recover clean, fast, and anywhere.
-
5
IFoam is an OpenFOAM derived framework. It uses Python programming language for definition of its API. Itegrates visual components for limited post-processing. Provides access to some GUI components for more efficient set up the simulation cases.
-
6
The Location Containment Object Model(LCOM) is a simulation framework written in Python. LCOM provides a rule-based solution to handling partial object containment, object migration, message passing, and simulation observation.
-
7
Spyse is a software framework for building multi-agent systems. It allows Python developers to build distributed intelligent systems of multiple cooperative agents based on FIPA, OWL, SOA and many others. Spyse is designed for ease-of-use and fun.
-
8
Use SASSIE to generate and manipulate large numbers of molecular structures and then calculate the SAXS, SANS, and neutron reflectivity profiles from atomistic structures. Use for intrinsically disordered proteins. We need alpha-testers and developers.
-
9
PGAF provides a framework tuned, user-specific genetic algorithms by handling I/O, UI, and parallelism. It is designed for optimizing functions that take a "very long time" to evaluate.
-
Save Up to 91% on Cloud Compute With Spot VMsRun batch jobs at 60-91% off with Spot VMs. Long-running workloads get automatic discounts with sustained use.
-
10
The Automatic Model Optimization Reference Implementation, AMORI, is a framework that integrates the modelling and the optimization processes by providing a plug-in interface for both. A genetic algorithm and Markov simulations are currently implemented.
-
11
TAROT is a easy-to-use framework for Monte Carlo simulations in python. Calculations between different kinds of randomly distributed numbers are made as easy as basic arithmetics. Tarot provides an interactive graphical interface for interpretation.
-
12
edef - A small simulation framework for logic circuits, autoregressive processes, digital controller circuits and many more. Also there is a GUI application, that integrates a simple development environment and a circuit editor.
-
13
Poor Man's HPC is a framework that allows distributing and running code on a server farm. pmHPC is a scaled down and simplified version of distributed computing projects such as SETI, so is a perfect fit for enthusiasts and universities.
-
14
CoSimA+
The Co-Simulation Adaptation Platform
The co-simulation adapation platform serves as programming framework and middleware to enable coupling of distributed, heterogeneous numerical models. The framework facilitates the adaptation and integration of new sub-models into a common simulation platform.
