Skip to main content

MDAnalysis example data

Project description

MDAnalysisData

Build Status codecov docs PRs welcome Anaconda-Server Badge DOI

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:

  1. 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
  2. deposit data in an archive under an Open Data compatible license (CC0 or CC-BY preferred)
  3. 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.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

MDAnalysisData-0.9.0.tar.gz (43.3 kB view details)

Uploaded Source

Built Distribution

MDAnalysisData-0.9.0-py2.py3-none-any.whl (37.5 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file MDAnalysisData-0.9.0.tar.gz.

File metadata

  • Download URL: MDAnalysisData-0.9.0.tar.gz
  • Upload date:
  • Size: 43.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/4.0.2 CPython/3.11.6

File hashes

Hashes for MDAnalysisData-0.9.0.tar.gz
Algorithm Hash digest
SHA256 11cbd4a7ebd1df5176fa3e5d18894a5049594471bd80297cc157aaace3c9970c
MD5 d65e152814e75e04f43ce65df7ea12b9
BLAKE2b-256 3204df5494e9266b903476f370800ee950a6528b427cb3f77300f19445428278

See more details on using hashes here.

File details

Details for the file MDAnalysisData-0.9.0-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for MDAnalysisData-0.9.0-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 782e58bc8bd44337ec464e925bfa5c6fee3eea2f77dba059da143a500c553b2f
MD5 58d1f264ebe546fc90e1a29e3ae77958
BLAKE2b-256 b48f577ebc409a9e57e3caad8ef3e118dacf40920b4ddfa2e64094db98d13031

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page