wedap 0.0.2

weighted ensemble data analysis and plotting

wedap

weighted ensemble data analysis and plotting (wedap)

This is used to plot H5 files produced from running WESTPA.

This repository is currently under development.

Requirements

• Numpy
• Matplotlib
• H5py
• Moviepy
• Scipy
• tqdm
• Gooey (optional for GUI)

GUI

wedap has a GUI built using Gooey which can be launched by running wedap or python wedap if you're in the main wedap directory of this repository. If you're using MacOSX, you'll need to run pythonw wedap in the main directory since conda prevents wxPython from accessing the display on Mac. If you pip install (instead of conda installing) wxPython and Gooey on Mac you may be able to just run wedap. If you wish to use the command line interface instead include any amount of arguments and include -h or --help to see the available options.

For MacOSX, you can set up an alias in your .bash_profile by running the following:

echo "alias wedap=pythonw /Path/to/wedap/git/repo/wedap/wedap" >> ~/.bash_profile

Then simply type wedap on the terminal to run the wedap GUI.

Installation

Install into a new conda env:

conda env create --name wedap python=3.7+
conda activate wedap
conda install -c conda-forge gooey
pip install wedap

Or update an existing environmnent:

conda activate ENV_NAME
conda install -c conda-forge gooey
pip install wedap

Or, if you have the repository cloned, go into the main wedap directory (may have more up to date features):

conda install -c conda-forge gooey
pip install .

If you don't need the GUI, then installing gooey is not required

Note that gooey is kindof troublesome to pip install in some systems, which is also why it's not included in the requirements (although it is required for the GUI). I am trying to fix this but for now I reccomend conda installing gooey.

Examples

After installation, to run the CLI version and view available options:

wedap --help

Or:

wedap -h

To start the GUI simply input:

wedap

To start the GUI on MacOSX:

pythonw /Path/to/wedap/git/repo/wedap/wedap

To visualize the evolution of the pcoord for the example p53.h5 file via CLI:

wedap -h5 wedap/data/p53.h5

To do the same with the API:

import wedap
import matplotlib.pyplot as plt

wedap.H5_Plot(h5="wedap/data/p53.h5", data_type="evolution").plot()
plt.show()

The resulting p53.h5 file evolution plot will look like this:

See the examples directory for more realistic applications using the Python API.

Contributing

Features should be developed on branches. To create and switch to a branch, use the command:

git checkout -b new_branch_name

To switch to an existing branch, use:

git checkout branch_name

To submit your feature to be incorporated into the main branch, you should submit a Pull Request. The repository maintainers will review your pull request before accepting your changes.

Copyright

Copyright (c) 2021, Darian Yang