# -*- coding: utf-8 -*-
"""Coarse-grained molecular dynamics of an amphiphilic fiber.
https://figshare.com/articles/126chains_dcd/7259915
"""
from os.path import dirname, exists, join
from os import makedirs, remove
import logging
from .base import get_data_home
from .base import _fetch_remote, _read_description
from .base import RemoteFileMetadata
from .base import Bunch
NAME = "CG_fiber"
DESCRIPTION = "CG_fiber.rst"
# The original data can be found at the figshare URL.
# The SHA256 checksum of the zip file changes with every download so we
# cannot check its checksum. Instead we download individual files.
# separately. The keys of this dict are also going to be the keys in the
# Bunch that is returned.
ARCHIVE = {
'topology': RemoteFileMetadata(
filename='126chains.psf',
url='https://ndownloader.figshare.com/files/13374146',
checksum='3ddb654b68549ac2ad5107a4282899f41fad233d09ea572446031711af4e57da',
),
'trajectory': RemoteFileMetadata(
filename='126chains.dcd',
url='https://ndownloader.figshare.com/files/13375838',
checksum='e0b47d422f31ec209ea810edcf6cf3830da04bb2e1540f520477c27f4433d849',
),
}
logger = logging.getLogger(__name__)
[docs]
def fetch_CG_fiber(data_home=None, download_if_missing=True):
"""Load the CG fiber self-assembly trajectory
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>/CG_fiber``.
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.topology : filename
Filename of the topology file
dataset.trajectory : filename
Filename of the trajectory file
dataset.DESCR : string
Description of the trajectory.
See :ref:`CG_fiber-dataset` for description.
"""
name = NAME
data_location = join(get_data_home(data_home=data_home),
name)
if not exists(data_location):
makedirs(data_location)
records = Bunch()
for file_type, meta in ARCHIVE.items():
local_path = join(data_location, meta.filename)
records[file_type] = local_path
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))
logger.info("Downloading {0}: {1} -> {2}...".format(
file_type, meta.url, local_path))
archive_path = _fetch_remote(meta, dirname=data_location)
records.DESCR = _read_description(DESCRIPTION)
return records