{"repo":"pyrates-neuroscience/PyRates","free":true,"listed":false,"github":"https://github.com/pyrates-neuroscience/PyRates","clone":"git clone https://github.com/pyrates-neuroscience/PyRates.git","description":"Open-source, graph-based Python code generator and analysis toolbox for dynamical systems (pre-implemented and custom models). Most pre-implemented models belong to the family of neural population models.","language":"Python","stars":92,"topics":["simulations","neural-networks","dynamical-systems","parameter-search","code-generation","network-simulator","scientific-computing","scientific-research","python","fortran90"],"license":"GPL-3.0","category":"dev-tools","readme_excerpt":"PyRates ======= PyRates is a framework for dynamical systems modeling, developed by Richard Gast and Daniel Rose. It is an open-source project that everyone is welcome to contribute to. Basic features =============== Basic features: --------------- - Frontend: - implement models via a frontend of your choice: YAML or Python - create basic mathematical building blocks (i.e. differential equations and algebraic equations) and use them to define a networks of nodes connected by edges - create hierarchical networks by connecting networks via edges - Backend: - choose from a number of different backends - NumPy backend for dynamical systems modeling on CPUs via Python - Tensorflow and PyTorch backends for parameter optimization via gradient descent and dynamical systems modeling on GPUs - Julia backend for dynamical system modeling in Julia , via tools such as DifferentialEquations.jl - Fortran backend for dynamical systems modeling via Fortran 90 and interfacing the parameter continuation software Auto-07p - Matlab backend for differential equation solving via Matlab - Other features: - perform quick numerical simulations via a single function call - choose between different numerical solvers - perform parameter sweeps over multiple parameters at once - generate backend-specific run functions that evaluate the vector field of your dynamical system - Implement dynamic edge equations that include scalar delays or delay distributions (delay distributions are automatically translated","default_branch":null,"files":null,"tree":[],"storefront":"/r/pyrates-neuroscience","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/pyrates-neuroscience/PyRates/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}