Deep cartograph is a package to analyze and enhance MD simulations.
This software has been developed for the European BioExcel, funded by the European Commission (EU Horizon Europe 101093290).
Deep cartograph can be used to train different collective variables from simulation data. Either to analyze existing trajectories or to use them to enhance the sampling in subsequent simulations. It leverages PLUMED to compute the features and the mlcolvar library to train the different collective variables 1.
Starting from a trajectory and topology files, Deep cartograph can be used to:
- Featurize the trajectory.
- Filter the features.
- Compute and train different collective variables (CVs).
- Project and cluster the trajectory in the CV space.
- Produce a PLUMED input file to enhance the sampling.
- deep_cartograph: contains all the tools and modules that form part of the deep_cartograph package.
- examples: contains examples of how to use the package.
Full documentation, including one page per tool, is at https://nbdsoftware.github.io/deep_cartograph/.
git clone https://github.com/NBDsoftware/deep_cartograph.git
cd deep_cartograph
conda env create -f environment_detailed.yml
conda activate deep_cartograph
pip install .
See the installation guide for GPU support and development installs.
Run the full workflow with deep_carto:
deep_carto -conf config.yml -traj_data trajectories/ -top_data topologies/ -out output/
An example YAML configuration file is in deep_cartograph/default_config.yml. Each step is also available as a standalone tool (compute_features, train_colvars, ...); see the tools list and the documentation for all options.
Common problems are covered in the FAQ.
If you use Deep Cartograph, please cite it using the metadata in CITATION.cff, or GitHub's "Cite this repository" button. Changes between versions are listed in the CHANGELOG.
This project is offered under a dual-license model, intended to make the software freely available for academic and non-commercial use while preventing its use for profit.
For academic, research, and other non-commercial purposes, this software is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).
Under this license, you are free to:
- Share — copy and redistribute the material in any medium or format.
- Adapt — remix, transform, and build upon the material.
As long as you follow the license terms:
- Attribution — You must give appropriate credit.
- Non-Commercial — You may not use the material for commercial purposes.
- Share-Alike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
A full copy of the license is available in the LICENSE file in this repository.
Use of this software for commercial purposes is not permitted under the CC BY-NC-SA 4.0 license.
If you wish to use this software in a commercial product, for-profit service, or any other commercial context, you must obtain a separate commercial license.
Please contact it@nostrumbiodiscovery.com to inquire about purchasing a commercial license.
