{"id":19757141,"url":"https://github.com/dynamicslab/sindy-pi","last_synced_at":"2025-04-30T12:31:24.420Z","repository":{"id":45794105,"uuid":"252863148","full_name":"dynamicslab/SINDy-PI","owner":"dynamicslab","description":"SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics","archived":false,"fork":false,"pushed_at":"2021-08-03T02:24:02.000Z","size":72300,"stargazers_count":119,"open_issues_count":4,"forks_count":40,"subscribers_count":11,"default_branch":"master","last_synced_at":"2024-05-04T00:24:47.821Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"MATLAB","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/dynamicslab.png","metadata":{"files":{"readme":"ReadMe.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2020-04-03T23:15:58.000Z","updated_at":"2024-04-28T06:17:34.000Z","dependencies_parsed_at":"2022-07-17T00:46:21.353Z","dependency_job_id":null,"html_url":"https://github.com/dynamicslab/SINDy-PI","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dynamicslab%2FSINDy-PI","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dynamicslab%2FSINDy-PI/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dynamicslab%2FSINDy-PI/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dynamicslab%2FSINDy-PI/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/dynamicslab","download_url":"https://codeload.github.com/dynamicslab/SINDy-PI/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":224208111,"owners_count":17273714,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-12T03:18:13.385Z","updated_at":"2024-11-12T03:18:13.989Z","avatar_url":"https://github.com/dynamicslab.png","language":"MATLAB","funding_links":[],"categories":[],"sub_categories":[],"readme":"# SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics\n\nSINDy-PI is a robust algorithm for parallel implicit sparse identification of nonlinear dynamics algorithm. The SINDy-PI algorithm implicit dynamical systems in a robust and parallel optimization.  The details of the approach are in our [arXiv paper](https://arxiv.org/abs/2004.02322).\n\n![](Images/DL_SINDy.jpg)\n\n## Examples\n### Belousov–Zhabotinsky (BZ) Reaction\n\nThe Belousov–Zhabotinsky (BZ) reaction is a classical example of non-equilibrium thermodynamics, which can be described by a rational PDE. The strong coupling dynamics and implicit behavior make the data-driven discovery of the BZ reaction challenging when using implicit-SINDy and PDE-FIND. However, SINDy-PI correctly identifies the dynamics.\n\n### Modified Korteweg–de Vries (KdV) Equation\n\nThe Korteweg–de Vries (KdV) equation is a mathematical model of shallow water waves. We modify the KdV equation to include a rational gain term and use SINDy-PI to identify the model.   \n\n### Mounted Double Pendulum\n\nThe double pendulum is a classic example of chaotic dynamics. Correctly identifying the equations of motion of the double pendulum is a challenging task due to the rational terms in the dynamics. Moreover, the complexity of the double pendulum ODEs make it challenging to use implicit-SINDy. However, SINDy-PI is able to correctly identify the dynamics.\n\n### Single Pendulum on a Cart\n\nFor many robotic systems, there is actuation applied to the system. We consider a classic example of a single pendulum on a cart and use SINDy-PI to identify the underlying ODE of the system.\n\n### Yeast Glycolysis\n\nTo compare the data usage of implicit-SINDy and SINDy-PI, we use yeast glycolysis as an example.\n\n## Dependencies:\n\n* CVX optimization packages for Matlab.  CVX is used for the constrained formulation of the SINDy-PI.\n* [Simulation data](https://drive.google.com/file/d/13sGPmjup8IvJL-TdKJvJRUmFUQ84zevA/view?usp=sharing) of the Michaelis Menten kinetics under multiple initial conditions. This data set is used for the comparison of implicit-SINDy and SINDy-PI under different noise levels. Please unzip it in the \"Comparison\\NoiseSenstivity\\Michaelis-Menten kinetics\\Datas\" folder for use.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdynamicslab%2Fsindy-pi","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdynamicslab%2Fsindy-pi","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdynamicslab%2Fsindy-pi/lists"}