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https://github.com/mdanalysis/mdanalysisdata
Access to data for workshops and extended tests of MDAnalysis.
https://github.com/mdanalysis/mdanalysisdata
dataset-manager mdanalysis molecular-dynamics python
Last synced: 6 days ago
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Access to data for workshops and extended tests of MDAnalysis.
- Host: GitHub
- URL: https://github.com/mdanalysis/mdanalysisdata
- Owner: MDAnalysis
- License: bsd-3-clause
- Created: 2018-09-07T23:53:05.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2024-09-25T23:30:45.000Z (about 2 months ago)
- Last Synced: 2024-11-02T17:26:23.209Z (10 days ago)
- Topics: dataset-manager, mdanalysis, molecular-dynamics, python
- Language: Python
- Homepage: https://www.mdanalysis.org/MDAnalysisData
- Size: 7.12 MB
- Stars: 14
- Watchers: 6
- Forks: 5
- Open Issues: 9
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: docs/contributing.rst
- License: LICENSE
- Authors: AUTHORS
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README
# MDAnalysisData
[](https://github.com/MDAnalysis/MDAnalysisData/actions/workflows/gh-ci.yml)
[](https://codecov.io/gh/MDAnalysis/MDAnalysisData)
[](https://www.mdanalysis.org/MDAnalysisData/)
[](http://makeapullrequest.com)
[](https://anaconda.org/conda-forge/mdanalysisdata)
[](https://zenodo.org/badge/latestdoi/147885122)
Access to data for workshops and extended tests of MDAnalysis.
Data sets are stored at external stable URLs (e.g., on
[figshare](https://figshare.com/), [zenodo](https://zenodo.org/), or
[DataDryad](https://www.datadryad.org/)) and this package provides a
simple interface to download, cache, and access data sets.
## Installation
To use, install the package
```bash
pip install --upgrade MDAnalysisData
```
or install with `conda`
```bash
conda install --channel conda-forge mdanalysisdata
```
## Accessing data sets
Import the datasets and access your data set of choice:
```python
from MDAnalysisData import datasets
adk = datasets.fetch_adk_equilibrium()
```
The returned object contains attributes with the paths to topology and
trajectory files so that you can use it directly with, for instance, [MDAnalysis](https://www.mdanalysis.org):
```python
import MDAnalysis as mda
u = mda.Universe(adk.topology, adk.trajectory)
```
The metadata object also contains a `DESCR` attribute with a
description of the data set, including relevant citations:
```python
print(adk.DESCR)
```
## Managing data
Data are locally stored in the **data directory** `~/MDAnalysis_data`
(i.e., in the user's home directory). This location can be changed by
setting the environment variable `MDANALYSIS_DATA`, for instance
```bash
export MDANALYSIS_DATA=/tmp/MDAnalysis_data
```
The location of the data directory can be obtained with
```python
MDAnalysisData.base.get_data_home()
```
If the data directory is removed then data are downloaded again. Data
file integrity is checked with a SHA256 checksum when the file is
downloaded.
The data directory can we wiped with the function
```python
MDAnalysisData.base.clear_data_home()
```
## Contributing new datasets
Please add new datasets to MDAnalysisData. See [Contributing new
datasets](https://www.mdanalysis.org/MDAnalysisData/contributing.html)
for details, but in short:
1. raise an issue in the [issue
tracker](https://github.com/MDAnalysis/MDAnalysisData/issues) describing
what you want to add; this issue will become the focal point for discussions
where the developers can easily give advice
2. deposit data in an archive under an [Open
Data](https://opendatacommons.org/) compatible license (CC0 or
CC-BY preferred)
3. write accessor code in MDAnalysisData
## Credits
This package is modelled after
[sklearn.datasets](http://scikit-learn.org/stable/modules/classes.html#module-sklearn.datasets). It
uses code from `sklearn.datasets` (under the [BSD 3-clause
license](https://github.com/scikit-learn/scikit-learn/blob/master/COPYING)).
No data are included; please see the `DESCR` attribute for each data
set for authorship, citation, and license information for the data.