Source code for MDAnalysisData.vesicles

# -*- coding: utf-8 -*-

"""Large vesicles library (coarse grained).

from os.path import dirname, exists, join
from os import makedirs, remove
import tarfile

import logging

from .base import get_data_home
from .base import _fetch_remote, _read_description
from .base import RemoteFileMetadata
from .base import Bunch

    'vesicle_lib': {
        'NAME': "vesicle_library",
        'DESCRIPTION': "vesicle_lib.rst",
        'ARCHIVE': {
            'tarfile': RemoteFileMetadata(
        'CONTENTS': {
            'structures': ["vesicles/1_75M/system.gro",
            'labels': ["1_75M", "3_5M", "10M"],
            'N_structures': 3,

logger = logging.getLogger(__name__)

[docs] def fetch_vesicle_lib(data_home=None, download_if_missing=True): """Load the vesicle library dataset Parameters ---------- data_home : optional, default: None Specify another download and cache folder for the datasets. By default all MDAnalysisData data is stored in '~/MDAnalysis_data' subfolders. This dataset is stored in ``<data_home>/vesicle_library``. download_if_missing : optional, default=True If ``False``, raise a :exc:`IOError` if the data is not locally available instead of trying to download the data from the source site. Returns ------- dataset : dict-like object with the following attributes: dataset.structures : list list with filenames of the different vesicle systems (in GRO format) dataset.N_structures : int number of structures dataset.labels : list descriptors of the files in `dataset.structures` (same order), giving their approximate sizes in number of particles dataset.DESCR : string Description of the ensemble See :ref:`vesicle-library-dataset` for description. """ metadata = METADATA['vesicle_lib'] name = metadata['NAME'] data_location = join(get_data_home(data_home=data_home), name) if not exists(data_location): makedirs(data_location) records = Bunch() meta = metadata['ARCHIVE']['tarfile'] local_path = join(data_location, meta.filename) if not exists(local_path): if not download_if_missing: raise IOError("Data {0}={1} not found and `download_if_missing` is " "False".format(file_type, local_path))"Downloading {0}: {1} -> {2}...".format( "tarfile", meta.url, local_path)) archive_path = _fetch_remote(meta, dirname=data_location)"Unpacking {}...".format(archive_path)) with, 'r') as tar: tar.extractall(path=data_location) records.structures = [join(data_location, path) for path in metadata['CONTENTS']['structures'] if exists(join(data_location, path))] records.N_structures = metadata['CONTENTS']['N_structures'] records.labels = metadata['CONTENTS']['labels'] if len(records.structures) != records.N_structures: # should not happen... raise RuntimeError("structure files in {0} are incomplete: only {1} " "but should be {2}.".format( metadata['CONTENTS']['structures'], len(records.structures), records.N_structures)) records.DESCR = _read_description(metadata['DESCRIPTION']) return records