https://github.com/markovmodel/molpx

IPython API to visualize MD-trajectories along projected trajectories inside a Jupyter notebook
https://github.com/markovmodel/molpx

free-energy ipython-notebook jupyter-notebook molecular-dynamics tica visualization widget

Last synced: 3 months ago
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IPython API to visualize MD-trajectories along projected trajectories inside a Jupyter notebook

Host: GitHub
URL: https://github.com/markovmodel/molpx
Owner: markovmodel
License: lgpl-3.0
Created: 2016-12-14T13:05:38.000Z (over 8 years ago)
Default Branch: master
Last Pushed: 2019-02-14T16:40:40.000Z (about 6 years ago)
Last Synced: 2025-02-01T10:23:45.031Z (3 months ago)
Topics: free-energy, ipython-notebook, jupyter-notebook, molecular-dynamics, tica, visualization, widget
Language: Python
Homepage:
Size: 27.5 MB
Stars: 39
Watchers: 11
Forks: 2
Open Issues: 12
Metadata Files:
- Readme: README.rst
- License: LICENSE.txt

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README

        ###################################################

Welcome to molPX: The Molecular Projection Explorer

###################################################

|DOI| |travis_build| |appveyor_build| |coverage| |docs_build|

The Molecular Projection Explorer, molPX, is a python module that provides **interactive visualization of

projected coordinates of molecular dynamics (MD) trajectories** inside a `Jupyter notebook `_.

molPX is based on the incredibly useful  `nglview IPython/Jupyter widget `_.

Other libraries heavily used are  `mdtraj `_ and `PyEMMA `_.

At the moment, there is also an `sklearn `_ dependency that might disappear in the future.

.. image:: ../images/output.gif

   :align: center

At the moment the API consists of two subpackages:

* :doc:`molpx.visualize `

* :doc:`molpx.generate  `

**TL;DR**: see molPX in action through the

* :doc:`Example Jupyter Notebooks `

Find more about the people behind molPX here:

* :doc:`About & YouTube Introduction `

Download and Install

=====================

If you can't wait to play around with molPX, and you have the `Anaconda scientifc python distribution

`_ (which we strongly recommend), the easiest way to get molPX is to issue

the `conda command `_:

   >>> conda install molpx -c conda-forge

and jump to the Quick Start section of this document. Otherwise, check out our more exhaustive

* :doc:`Installation Guide `

Quick Start

=============

Start an ``IPython`` console

    >>> ipython

Import ``molpx`` and let the example notebooks guide you

    >>> import molpx

    >>> molpx.example_notebooks()

Voilà: you should be looking at a list of jupyter notebooks explaining the basic functionality of molPX

Documentation

==============

You can find the latest documentation online `here `_

You can build a local copy of the html documentation by navigating to the molPX installation

directory and issuing:

    >>> cd doc

    >>> make html

This will generate `molPX/docs/build/html/index.html` with the html documentation. If you are missing some of

the requirements for the documentation , issue:

    >>> pip install -r ./source/doc_requirements.txt

If you don't know where molPX is installed, you can find out this way:

    >>> ipython

    >>> import molpx

    >>> molpx._molpxdir()

The output of the last command is one subdirectory of molPX's installation directory, so just copy it and issue:

    >>> cd the-output-of-the-molpx._molpxdir-command

    >>> cd ..

and you are there !

Warnings

=========

molPX is currently under heavy development and the API might change rapidly. Stay tuned.

Data Privacy Statement

======================

When you import this Python package, some of your metadata is sent to our servers. These are:

 * molPX version

 * Python version

 * Operating System

 * Hostname/ mac address of the accessing computer

 * Time of retrieval

How to disable this feature easily:

-----------------------------------

Even before you use molPX for the first time:

 1. Create a hidden folder `.molpx` in your home folder

 2. Create a file `conf_molpx.py` inside of `.molpx` with the following line:

    `report_status = False`

 3. Restart your ipython/jupyter sessions

Hints:

* This is most easily realized from terminal by issuing:

        >>> mkdir ~/.molpx

        >>> echo "report_status = False" >> ~/.molpx/conf_molpx.py

* You can check your report status anytime by typing this line in a (i)python terminal

        >>> import molpx

        >>> molpx._report_status()

* If you don't know where your home folder is (for whatever reason), you can find it out by typing in a (i)python terminal

        >>> import os

        >>> os.path.expanduser('~/.molpx')

.. |DOI| image::

   https://zenodo.org/badge/76460348.svg

   :target: https://zenodo.org/badge/latestdoi/76460348

   :height: 20

   :alt: DOI

.. |travis_build| image::

   https://travis-ci.org/markovmodel/molPX.svg?branch=master

   :height: 10

   :target: https://travis-ci.org/markovmodel/molPX

   :alt: Travis build status

.. |appveyor_build| image::

   https://ci.appveyor.com/api/projects/status/396ej39s3fewhwy9/branch/master?svg=true

   :height: 10

   :target: https://ci.appveyor.com/project/gph82/molpx

   :alt: Appveyor build status

.. |coverage| image::

   https://codecov.io/gh/markovmodel/molPX/branch/master/graph/badge.svg

   :height: 20

   :target: https://codecov.io/gh/markovmodel/molPX

   :alt: Codecov

.. |docs_build| image::

   https://readthedocs.org/projects/molpx/badge/?version=latest

   :alt: Documentation Status

   :height: 20

   :target: http://molpx.readthedocs.io/en/latest/?badge=latest

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https://github.com/markovmodel/molpx

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README