transition-sampling | MD Engine Agnostic Implementation of Aimless-Shooting

by UWPRG Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | transition-sampling Summary

transition-sampling is a Python library. transition-sampling has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

MD Engine Agnostic Implementation of Aimless-Shooting Likelihood Maximization [Peters and Trout doi:10.1063/1.2234477]. See the main documentation at

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Support

transition-sampling has a low active ecosystem.

It has 2 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

There are 3 open issues and 4 have been closed. On average issues are closed in 4 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of transition-sampling is current.

Quality

transition-sampling has no bugs reported.

Security

transition-sampling has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

transition-sampling is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

transition-sampling releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Top functions reviewed by kandi - BETA

kandi has reviewed transition-sampling and discovered the below as its top functions. This is intended to give you an instant insight into transition-sampling implemented functionality, and help decide if they suit your requirements.

Optimizes the objective function .
Perform a minimization of the problem .
Estimate the initial starting position .
Calculate the p - value for the posterior distribution .
Parse aimless arguments .
Split the COMMITOR section .
Calculate the Jacobian .
Validate a likelihood file .
Validate colvar inputs .
Create a subprocess and wait for it to finish .

Get all kandi verified functions for this library.

transition-sampling Key Features

No Key Features are available at this moment for transition-sampling.

transition-sampling Examples and Code Snippets

No Code Snippets are available at this moment for transition-sampling.

Community Discussions

No Community Discussions are available at this moment for transition-sampling.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install transition-sampling

You can download it from GitHub.
You can use transition-sampling like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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