MDAnalysisData
Access to data for workshops and extended tests of MDAnalysis.
Data sets are stored at external stable URLs (e.g., on figshare, zenodo, or DataDryad) and this package provides a simple interface to download, cache, and access data sets.
Installation
To use, install the package
pip install --upgrade MDAnalysisData
or install with conda
conda install --channel conda-forge mdanalysisdata
Accessing data sets
Import the datasets and access your data set of choice:
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:
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:
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
export MDANALYSIS_DATA=/tmp/MDAnalysis_data
The location of the data directory can be obtained with
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
MDAnalysisData.base.clear_data_home()
Contributing new datasets
Please add new datasets to MDAnalysisData. See Contributing new datasets for details, but in short:
- raise an issue in the issue tracker describing what you want to add; this issue will become the focal point for discussions where the developers can easily give advice
- deposit data in an archive under an Open Data compatible license (CC0 or CC-BY preferred)
- write accessor code in MDAnalysisData
Credits
This package is modelled after
sklearn.datasets. It
uses code from sklearn.datasets (under the BSD 3-clause
license).
No data are included; please see the DESCR attribute for each data
set for authorship, citation, and license information for the data.
Metadata
Release files for MDAnalysisData 0.9.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| MDAnalysisData-0.9.0.tar.gz | 43.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| MDAnalysisData-0.9.0-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Total release size: 80.7 kB
Release files / MDAnalysisData-0.9.0.tar.gz
| Download URL | MDAnalysisData-0.9.0.tar.gz |
|---|---|
| Size | 43.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Yes |
| Uploaded via |
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Release files / MDAnalysisData-0.9.0-py2.py3-none-any.whl
| Download URL | MDAnalysisData-0.9.0-py2.py3-none-any.whl |
|---|---|
| Size | 37.5 kB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/4.0.2 CPython/3.11.6
|