{"id":13458671,"url":"https://github.com/deepmodeling/ADMP","last_synced_at":"2025-03-24T15:31:51.077Z","repository":{"id":43682293,"uuid":"441833260","full_name":"deepmodeling/ADMP","owner":"deepmodeling","description":"Automatic Differentiation Multipole Moment Molecular Forcefield","archived":false,"fork":true,"pushed_at":"2024-04-11T02:15:25.000Z","size":1170,"stargazers_count":2,"open_issues_count":1,"forks_count":2,"subscribers_count":1,"default_branch":"master","last_synced_at":"2024-10-29T03:33:18.807Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"admp.vercel.app","language":"Python","has_issues":false,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":"Roy-Kid/ADMP","license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/deepmodeling.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2021-12-26T07:22:47.000Z","updated_at":"2024-08-20T05:37:49.000Z","dependencies_parsed_at":null,"dependency_job_id":null,"html_url":"https://github.com/deepmodeling/ADMP","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/deepmodeling%2FADMP","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deepmodeling%2FADMP/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deepmodeling%2FADMP/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/deepmodeling%2FADMP/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/deepmodeling","download_url":"https://codeload.github.com/deepmodeling/ADMP/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245298143,"owners_count":20592550,"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":"2024-07-31T09:00:55.040Z","updated_at":"2025-03-24T15:31:46.068Z","avatar_url":"https://github.com/deepmodeling.png","language":"Python","readme":"# ADMP\r\n\r\nAutomatic Differentiable Multipolar Polarizable (ADMP) force field calculator. \r\n\r\nThis module provides an auto-differentiable implementation of multipolar polarizable force fields, that resembles the behavior of [MPID](https://github.com/andysim/MPIDOpenMMPlugin) plugin of OpenMM. Supposedly, this module is developed for the following purposes:\r\n\r\n1. Achieving an easy calculation of force and virial of the multipolar polarizable forcefield. \r\n2. Allowing fluctuating (geometric-dependent) multipoles/polarizabilities in multipolar polarizable potentials.\r\n3. Allowing the calculation of derivatives of various force field parameters, thus achieving a more systematic and automatic parameter optimization scheme.\r\n\r\nThe module is based on [JAX](https://github.com/google/jax) and [JAX-MD](https://github.com/google/jax-md) projects. \r\n\r\n\r\n\r\n## Installation\r\n\r\n### Dependencies\r\n\r\nADMP module depends on the following packages, install them before using ADMP:\r\n\r\n1. Install [jax](https://github.com/google/jax) (pick the correct cuda version, see more details on their installation guide):\r\n\r\n   ```bash\r\n   pip install jax[cuda11_cudnn82] -f https://storage.googleapis.com/jax-releases/jax_releases.html\r\n   ```\r\n\r\n2. Install [jax-md](https://github.com/google/jax-md) :\r\n\r\n   ```bash\r\n   pip install jax-md --upgrade\r\n   ```\r\n\r\n   ADMP currently relies on the space and partition modules to provide neighbor list\r\n\r\n3. Install ADMP:\r\n\r\n   ADMP is a pure python module, just simply put it in your $PYTHONPATH.\r\n\r\n   ```bash\r\n   export PYTHONPATH=$PYTHONPATH:/path/to/admp\t\r\n   ```\r\n\r\n\r\n\r\n## Settings\r\n\r\nIn `admp/settings.py`, you can modify some global settings, including:\r\n\r\n**PRECISION**: single or double precision\r\n\r\n**DO_JIT**: whether do jit or not.\r\n\r\n\r\n\r\n## Example\r\n\r\nWe provide a MPID 1024 water box example. In water_1024 and water_pol_1024, we show both the nonpolarizable and the polarizable cases.\r\n\r\n```bash\r\ncd ./examples/water_1024\r\n./run_admp.py\r\n\r\ncd ./examples/water_pol_1024\r\n./run_admp.py\r\n```\r\n\r\nif `DO_JIT = True`, then the first run would be a bit slow, since it tries to do the jit compilation. Further executions of `get_forces` or `get_energy` should be much faster.\r\n\r\n","funding_links":[],"categories":["Others"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdeepmodeling%2FADMP","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdeepmodeling%2FADMP","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdeepmodeling%2FADMP/lists"}