MDAnalysis example data
Project description
# MDAnalysisData
[![Build Status](https://travis-ci.com/MDAnalysis/MDAnalysisData.svg?branch=master)](https://travis-ci.com/MDAnalysis/MDAnalysisData)
[![codecov](https://codecov.io/gh/MDAnalysis/MDAnalysisData/branch/master/graph/badge.svg)](https://codecov.io/gh/MDAnalysis/MDAnalysisData)
[![docs](https://img.shields.io/badge/docs-latest-brightgreen.svg)](https://www.mdanalysis.org/MDAnalysisData/)
[![PRs welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](http://makeapullrequest.com)
[![DOI](https://zenodo.org/badge/147885122.svg)](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
```
## 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()
```
## 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.
[![Build Status](https://travis-ci.com/MDAnalysis/MDAnalysisData.svg?branch=master)](https://travis-ci.com/MDAnalysis/MDAnalysisData)
[![codecov](https://codecov.io/gh/MDAnalysis/MDAnalysisData/branch/master/graph/badge.svg)](https://codecov.io/gh/MDAnalysis/MDAnalysisData)
[![docs](https://img.shields.io/badge/docs-latest-brightgreen.svg)](https://www.mdanalysis.org/MDAnalysisData/)
[![PRs welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](http://makeapullrequest.com)
[![DOI](https://zenodo.org/badge/147885122.svg)](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
```
## 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()
```
## 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.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
MDAnalysisData-0.3.0.tar.gz
(53.4 kB
view hashes)
Built Distribution
Close
Hashes for MDAnalysisData-0.3.0-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | e4ba66196905ddda9c756e7982ffe20457ddb9cd56df8310e0463d61476229a3 |
|
MD5 | f76e607e40ccbe91b57ddb19a07a98a9 |
|
BLAKE2b-256 | fe7e65d14b2e5eb1c0dc32be90668896cf99074352b608b073a2f44650d89d28 |