### Clone Repository and Install from Source

Source: https://www.mdanalysis.org/MDAnalysisData/_sources/install.rst.txt

Clone the MDAnalysisData repository from GitHub and install it using pip.

```bash
git clone https://github.com/MDAnalysis/MDAnalysisData.git
```

```bash
pip install MDAnalysisData/
```

--------------------------------

### Install MDAnalysisData with pip

Source: https://www.mdanalysis.org/MDAnalysisData/_sources/install.rst.txt

Use pip to install or upgrade the MDAnalysisData package from PyPi.

```bash
pip install --upgrade MDAnalysisData
```

--------------------------------

### Install MDAnalysisData from source with pip

Source: https://www.mdanalysis.org/MDAnalysisData/install.html

Install the MDAnalysisData package locally after cloning the repository, using pip.

```bash
pip install MDAnalysisData/

```

--------------------------------

### Install MDAnalysisData with conda

Source: https://www.mdanalysis.org/MDAnalysisData/_sources/install.rst.txt

Configure conda to use the conda-forge channel and then install the mdanalysisdata package.

```bash
conda config --add channels conda-forge
conda install mdanalysisdata
```

--------------------------------

### Install MDAnalysisData with conda

Source: https://www.mdanalysis.org/MDAnalysisData/install.html

Install MDAnalysisData using the conda package manager, ensuring the conda-forge channel is added.

```bash
conda config --add channels conda-forge
conda install mdanalysisdata

```

--------------------------------

### Get MDAnalysis Data Home Directory

Source: https://www.mdanalysis.org/MDAnalysisData/_modules/MDAnalysisData/base.html

Retrieves the path to the MDAnalysis data directory, creating it if it doesn't exist. The directory can be specified via an environment variable or programmatically.

```python
[docs]
def get_data_home(data_home=None):
    """Return the path of the MDAnalysisData data dir.

    This folder is used by some large dataset loaders to avoid
    downloading the data several times.  By default the data dir is
    set to a folder named 'MDAnalysis_data' in the user's home directory.

    Alternatively, it can be set by the :envvar:`MDANALYSIS_DATA` environment
    variable or programmatically by giving an explicit folder path. The '~'
    symbol is expanded to the user home folder.

    If the folder does not already exist, it is automatically created.

    Parameters
    ----------
    data_home : str | None
        The path to MDAnalysisData data dir.

    """
    if data_home is None:
        data_home = environ.get('MDANALYSIS_DATA',
                                DEFAULT_DATADIR)
    data_home = expanduser(data_home)
    if not exists(data_home):
        makedirs(data_home)
    return data_home

```

--------------------------------

### Load I-FABP Water Trajectory - Python

Source: https://www.mdanalysis.org/MDAnalysisData/ifabp_water.html

Use this function to load the I-FABP with water 0.5 ns equilibrium trajectory. Specify a custom data directory or disable downloading if the data is not locally available.

```python
MDAnalysisData.ifabp_water.fetch_ifabp_water(_data_home =None_, _download_if_missing =True_)
```

--------------------------------

### fetch_yiip_equilibrium_short

Source: https://www.mdanalysis.org/MDAnalysisData/_modules/MDAnalysisData/yiip_equilibrium.html

Loads the Yii P 9 ns equilibrium trajectory. Allows specifying a custom data home directory and controlling download behavior.

```APIDOC
## fetch_yiip_equilibrium_short

### Description
Loads the Yii P 9 ns equilibrium trajectory. This function allows users to specify an alternative directory for downloading and caching data, and to control whether the data should be downloaded if it's not found locally.

### 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>/yiip_equilibrium``.
- **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): An object with the following attributes:
  - **topology** (filename): Filename of the topology file.
  - **trajectory** (filename): Filename of the trajectory file.
  - **DESCR** (string): Description of the trajectory.

### See Also
See :ref:`yiip-equilibrium-dataset` for a more detailed description.
```

--------------------------------

### fetch_yiip_equilibrium_short

Source: https://www.mdanalysis.org/MDAnalysisData/_sources/yiip_equilibrium.rst.txt

Fetches the short (9-ns) equilibrium MD trajectory of the YiiP membrane-protein system.

```APIDOC
## fetch_yiip_equilibrium_short

### Description
Fetches the short (9-ns) equilibrium MD trajectory of the YiiP membrane-protein system.

### Method
This is a function call, not an HTTP request.

### Parameters
This function does not take any parameters.

### Returns
- A trajectory object representing the 9-ns MD simulation.
```

--------------------------------

### Get Data Home Directory

Source: https://www.mdanalysis.org/MDAnalysisData/helpers.html

Retrieves the path to the MDAnalysisData cache directory. This directory is used to store downloaded datasets. The path can be programmatically set or determined by the MDANALYSIS_DATA environment variable. If the directory does not exist, it will be created.

```python
MDAnalysisData.base.get_data_home()
```

--------------------------------

### fetch_adk_transitions_DIMS

Source: https://www.mdanalysis.org/MDAnalysisData/_modules/MDAnalysisData/adk_transitions.html

Loads the AdK DIMS transition dataset. This function downloads the dataset if it's not found locally and returns a dataset object containing topology, trajectories, and descriptive information.

```APIDOC
## fetch_adk_transitions_DIMS

### Description
Loads the AdK DIMS transititions dataset. This function downloads the dataset if it's not found locally and returns a dataset object containing topology, trajectories, and descriptive information.

### Parameters
#### Path Parameters
None

#### Query 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>/adk_transitions_DIMS``.
- **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) - An object with the following attributes:
  - **topology** (filename): Filename of the topology file.
  - **trajectories** (list): List with filenames of the trajectory ensemble.
  - **N_trajectories** (int): Number of trajectories in the ensemble.
  - **DESCR** (string): Description of the ensemble.

### See Also
See :ref:`adk-transitions-DIMS-dataset` for description.
```

--------------------------------

### fetch_adk_transitions_FRODA

Source: https://www.mdanalysis.org/MDAnalysisData/_modules/MDAnalysisData/adk_transitions.html

Loads the AdK FRODA transition dataset. This function downloads the dataset if it's not found locally and returns a dataset object containing topology, trajectories, and descriptive information.

```APIDOC
## fetch_adk_transitions_FRODA

### Description
Loads the AdK FRODA transititions dataset. This function downloads the dataset if it's not found locally and returns a dataset object containing topology, trajectories, and descriptive information.

### Parameters
#### Path Parameters
None

#### Query 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>/adk_transitions_FRODA``.
- **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) - An object with the following attributes:
  - **topology** (filename): Filename of the topology file.
  - **trajectories** (list): List with filenames of the trajectory ensemble.
  - **N_trajectories** (int): Number of trajectories in the ensemble.
  - **DESCR** (string): Description of the ensemble.

### See Also
See :ref:`adk-transitions-FRODA-dataset` for description.
```

--------------------------------

### Load AdK Equilibrium Trajectory - Python

Source: https://www.mdanalysis.org/MDAnalysisData/adk_equilibrium.html

Use this function to load the AdK 1us equilibrium trajectory without water. Specify a custom download directory or set download_if_missing to False to prevent automatic downloads.

```python
MDAnalysisData.adk_equilibrium.fetch_adk_equilibrium(_data_home =None_, _download_if_missing =True_)
```

--------------------------------

### _fetch_remote()

Source: https://www.mdanalysis.org/MDAnalysisData/helpers.html

Downloads a remote dataset, saves it locally, and verifies its integrity using a checksum.

```APIDOC
## MDAnalysisData.base._fetch_remote(_remote_ , _dirname =None_)

### Description
Helper function to download a remote dataset into path
Fetch a dataset pointed by remote’s url, save into path using remote’s filename and ensure its integrity based on the SHA256 Checksum of the downloaded file.

### Parameters
* **remote** (_RemoteFileMetadata_) – Named tuple containing remote dataset meta information: url, filename and checksum
* **dirname** (_string_) – Directory to save the file to.

### Returns
**file_path** – Full path of the created file.

### Return type
string
```

--------------------------------

### fetch_nhaa_equilibrium

Source: https://www.mdanalysis.org/MDAnalysisData/_sources/nhaa_equilibrium.rst.txt

Fetches the NhaA equilibrium dataset, which includes a 500-ns MD trajectory of a membrane-protein system with solvent removed.

```APIDOC
## fetch_nhaa_equilibrium

### Description
Fetches the NhaA equilibrium dataset, which contains a 500-ns MD trajectory of a membrane-protein system with all solvent removed. This dataset is useful for studying membrane-protein dynamics.

### Usage
```python
import MDAnalysisData.nhaa_equilibrium

# Fetch the dataset
data = MDAnalysisData.nhaa_equilibrium.fetch_nhaa_equilibrium()

# The 'data' object can now be used with MDAnalysis or other tools.
```

### Returns
- The NhaA equilibrium dataset, typically a file path or an object that can be loaded into a molecular dynamics analysis tool.
```

--------------------------------

### Fetch PEG_1chain Dataset

Source: https://www.mdanalysis.org/MDAnalysisData/_modules/MDAnalysisData/PEG_1chain.html

Use this function to load the PEG polymer trajectory. Specify `data_home` to set a custom download location or `download_if_missing=False` to prevent automatic downloads.

```python
from MDAnalysisData.datasets import PEG_1chain

# Load the dataset, downloading if necessary
dataset = PEG_1chain.fetch_PEG_1chain()

# Access the topology and trajectory files
topology_file = dataset.topology
trajectory_file = dataset.trajectory

# Access the description
description = dataset.DESCR

print(f"Topology file: {topology_file}")
print(f"Trajectory file: {trajectory_file}")
print(f"Description: {description}")
```

--------------------------------

### Fetch Vesicle Library Dataset

Source: https://www.mdanalysis.org/MDAnalysisData/_modules/MDAnalysisData/vesicles.html

Use this function to download and load the vesicle library dataset. Specify `data_home` to set a custom download location. `download_if_missing` controls whether to attempt download if data is not found locally.

```python
# -*- coding: utf-8 -*-

"""Large vesicles library (coarse grained).

https://figshare.com/articles/Large_System_Vesicle_Benchmark_Library/3406708
"""


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

METADATA = {
    'vesicle_lib': {
        'NAME': "vesicle_library",
        'DESCRIPTION': "vesicle_lib.rst",
        'ARCHIVE': {
            'tarfile': RemoteFileMetadata(
                filename='vesicles_1.0.tar.bz2',
                url='https://ndownloader.figshare.com/files/5320846',
                checksum='cba5a6221df664c79229a27d82faf779f63dee608f96a7b3b64ef209b93ec0d0',
            ),
        },
        'CONTENTS': {
            'structures': ["vesicles/1_75M/system.gro",
                           "vesicles/3_5M/system.gro",
                           "vesicles/10M/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))
        logger.info("Downloading {0}: {1} -> {2}...".format(
            "tarfile", meta.url, local_path))
        archive_path = _fetch_remote(meta, dirname=data_location)

        logger.info("Unpacking {}...".format(archive_path))
        with tarfile.open(archive_path, '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

```

--------------------------------

### Import Fetch Function in Datasets

Source: https://www.mdanalysis.org/MDAnalysisData/_sources/contributing.rst.txt

Import the fetch function for a new dataset into the main datasets module.

```python
from .{MODULE_NAME} import fetch_{NAME}
```

--------------------------------

### Load PEG Polymer Trajectory

Source: https://www.mdanalysis.org/MDAnalysisData/PEG_1chain.html

Use this function to load the PEG polymer trajectory. Specify an alternative download directory if needed. By default, data is stored in `~/MDAnalysis_data/CG_fiber`. If `download_if_missing` is `False`, an `IOError` will be raised if the data is not found locally.

```python
MDAnalysisData.PEG_1chain.fetch_PEG_1chain(_data_home =None_, _download_if_missing =True_)
```

--------------------------------

### Fetch AdK Equilibrium Dataset

Source: https://www.mdanalysis.org/MDAnalysisData/usage.html

Downloads and unpacks the AdK equilibrium dataset. The first call is slow as it downloads from figshare; subsequent calls use cached files.

```python
>>> from MDAnalysisData import datasets
>>> adk = datasets.fetch_adk_equilibrium()
```

--------------------------------

### fetch_adk_transitions_FRODA

Source: https://www.mdanalysis.org/MDAnalysisData/adk_transitions.html

Loads the AdK FRODA transitions dataset. This function allows specifying a custom data directory and controlling the download behavior if the data is not found locally.

```APIDOC
## fetch_adk_transitions_FRODA

### Description
Loads the AdK FRODA transititions dataset.

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Method
None (Python function)

### Endpoint
None (Python function)

### 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>/adk_transitions_FRODA`.
* **download_if_missing** (_optional_, default: True) - If `False`, raise a `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.trajectories** (_list_) – list with filenames of the trajectory ensemble
  * **dataset.N_trajectories** (_int_) – number of trajectories in the ensemble
  * **dataset.DESCR** (_string_) – Description of the ensemble

### Request Example
```python
import MDAnalysisData
trajectories = MDAnalysisData.adk_transitions.fetch_adk_transitions_FRODA()
```

### Response
#### Success Response
Returns a dataset object with topology, trajectories, number of trajectories, and description attributes.

#### Response Example
```json
{
  "topology": "path/to/adk_frodar.xtc",
  "trajectories": ["path/to/adk_frodar_001.xtc", "path/to/adk_frodar_002.xtc", ...],
  "N_trajectories": 200,
  "DESCR": "Description of the AdK FRODA transitions ensemble dataset."
}
```
```

--------------------------------

### Fetch I-FABP Water Data

Source: https://www.mdanalysis.org/MDAnalysisData/_modules/MDAnalysisData/ifabp_water.html

Loads the I-FABP with water 0.5 ns equilibrium trajectory. Handles downloading data if missing. Specify `data_home` to set a custom cache directory.

```python
# -*- coding: utf-8 -*-

"""MD simulation of I-FABP with water.

https://figshare.com/articles/Molecular_dynamics_trajectory_of_I-FABP_for_testing_and_benchmarking_solvent_dynamics_analysis/7058030
"""

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 = "ifabp_water"
DESCRIPTION = "ifabp_water.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='ifabp_water.psf',
        url='https://ndownloader.figshare.com/files/12980639',
        checksum='ba40714318aabec537015dc550fe5bd5ac1ac0b853f5abdd2f0ae63af9cfcafa',
    ),
    'structure': RemoteFileMetadata(
        filename='ifabp_water_0.pdb',
        url='https://ndownloader.figshare.com/files/12980636',
        checksum='8ccf5f75fd85385921c0cb77f00281a93b933fc1261c42fc9492f43983448a72',
    ),
    'trajectory':  RemoteFileMetadata(
        filename='rmsfit_ifabp_water_1.dcd',
        url='https://ndownloader.figshare.com/files/12980642',
        checksum='cebb48e58015abc8ff2f5bb7ba3eb7a289047f256351a8252bf1f29f9aaacf0e',
    ),
}



logger = logging.getLogger(__name__)




def fetch_ifabp_water(data_home=None, download_if_missing=True):
    """Load the I-FABP with water 0.5 ns equilibrium 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>/ifabp_water``.
    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.structure : filename
        Filename of a structure file in PDB format
    dataset.DESCR : string
        Description of the trajectory.


    See :ref:`ifabp-water-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

```

--------------------------------

### fetch_adk_transitions_DIMS

Source: https://www.mdanalysis.org/MDAnalysisData/_sources/adk_transitions.rst.txt

Fetches the DIMS dataset for adenylate kinase transitions.

```APIDOC
## fetch_adk_transitions_DIMS

### Description
Fetches the DIMS dataset for adenylate kinase transitions.

### Method
```python
fetch_adk_transitions_DIMS()
```

### Parameters
This function does not take any parameters.

### Response
Returns the DIMS dataset for adenylate kinase transitions.
```

--------------------------------

### Access Dataset Topology and Trajectory Files

Source: https://www.mdanalysis.org/MDAnalysisData/usage.html

Prints the file paths for the topology and trajectory files of the dataset.

```python
>>> print(adk.topology)
>>> print(adk.trajectory)
```

--------------------------------

### TqdmUpTo Callback for Progress Updates

Source: https://www.mdanalysis.org/MDAnalysisData/_modules/MDAnalysisData/base.html

A callback class that extends `tqdm` to provide an `update_to` method for tracking progress. Useful for download or processing tasks.

```python
class TqdmUpTo(tqdm):
    """Provides `update_to(n)` which uses `tqdm.update(delta_n)`.

    From https://pypi.org/project/tqdm/#hooks-and-callbacks
    """

    def update_to(self, b=1, bsize=1, tsize=None):
        """
        b  : int, optional
            Number of blocks transferred so so far [default: 1].
        bsize  : int, optional
            Size of each block (in tqdm units) [default: 1].
        tsize  : int, optional
            Total size (in tqdm units). If [default: None] remains unchanged.
        """
        if tsize is not None:
            self.total = tsize
        self.update(b * bsize - self.n)  # will also set self.n = b * bsize
```

--------------------------------

### Import MDAnalysisData yiip_equilibrium Module

Source: https://www.mdanalysis.org/MDAnalysisData/_modules/MDAnalysisData/yiip_equilibrium.html

Imports the necessary yiip_equilibrium module and its associated components. This is typically the first step when working with this module's functionalities.

```python
from os.path import dirname, exists, join
from os import makedirs, remove
import codecs

import logging

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

NAME = "yiip_equilibrium"
DESCRIPTION = "yiip_equilibrium.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
```

--------------------------------

### fetch_vesicle_lib

Source: https://www.mdanalysis.org/MDAnalysisData/_modules/MDAnalysisData/vesicles.html

Loads the vesicle library dataset. This function handles downloading the data if it's missing and provides access to vesicle structures, their labels, and a description of the dataset.

```APIDOC
## fetch_vesicle_lib

### Description
Loads the vesicle library dataset. This function handles downloading the data if it's missing and provides access to vesicle structures, their labels, and a description of the dataset.

### Parameters
#### Path Parameters
None

#### Query 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) - An object with the following attributes:
  - **structures** (list) - List with filenames of the different vesicle systems (in GRO format).
  - **N_structures** (int) - Number of structures.
  - **labels** (list) - Descriptors of the files in `dataset.structures` (same order), giving their approximate sizes in number of particles.
  - **DESCR** (string) - Description of the ensemble.

### See Also
:ref:`vesicle-library-dataset` for description.
```

--------------------------------

### fetch_adk_transitions_FRODA

Source: https://www.mdanalysis.org/MDAnalysisData/_sources/adk_transitions.rst.txt

Fetches the FRODA dataset for adenylate kinase transitions.

```APIDOC
## fetch_adk_transitions_FRODA

### Description
Fetches the FRODA dataset for adenylate kinase transitions.

### Method
```python
fetch_adk_transitions_FRODA()
```

### Parameters
This function does not take any parameters.

### Response
Returns the FRODA dataset for adenylate kinase transitions.
```

--------------------------------

### fetch_PEG_1chain

Source: https://www.mdanalysis.org/MDAnalysisData/_sources/PEG_1chain.rst.txt

Fetches the PEG polymer dataset, which contains a coarse-grained MD trajectory showing the self-assembly of an amphiphilic molecule.

```APIDOC
## fetch_PEG_1chain

### Description
Fetches the PEG polymer dataset. This dataset includes a coarse-grained MD trajectory illustrating the self-assembly of an amphiphilic molecule.

### Method
`fetch_PEG_1chain()`

### Parameters
This function does not take any parameters.

### Returns
- A dataset object containing the PEG polymer trajectory data.
```

--------------------------------

### get_data_home

Source: https://www.mdanalysis.org/MDAnalysisData/_sources/helpers.rst.txt

Returns the path to the data home directory.

```APIDOC
def get_data_home() -> str:
    """Returns the path to the data home directory."""
    pass
```

--------------------------------

### Compute SHA256 Checksum from Command Line

Source: https://www.mdanalysis.org/MDAnalysisData/_sources/contributing.rst.txt

An alternative method to compute the SHA256 checksum of a file directly from the command line. Replace FILENAME with the actual file path.

```bash
python -c 'import MDAnalysisData; print(MDAnalysisData.base._sha256("FILENAME"))'
```

--------------------------------

### Fetch Remote Dataset

Source: https://www.mdanalysis.org/MDAnalysisData/_modules/MDAnalysisData/base.html

Downloads a dataset from a given URL, saves it to a specified directory, and verifies its integrity using a SHA256 checksum. Displays download progress using a tqdm progress bar.

```python
[docs]
def _fetch_remote(remote, dirname=None):
    """Helper function to download a remote dataset into path

    Fetch a dataset pointed by remote's url, save into path using remote's
    filename and ensure its integrity based on the SHA256 Checksum of the
    downloaded file.

    Parameters
    -----------
    remote : RemoteFileMetadata
        Named tuple containing remote dataset meta information: url, filename
        and checksum
    dirname : string
        Directory to save the file to.

    Returns
    -------
    file_path: string
        Full path of the created file.
    """

    file_path = (remote.filename if dirname is None
                 else join(dirname, remote.filename))
    with TqdmUpTo(unit='B', unit_scale=True, miniters=1,
                  desc=remote.filename) as t:
        urlretrieve(remote.url, filename=file_path,
                    reporthook=t.update_to, data=None)
    checksum = _sha256(file_path)
    if remote.checksum != checksum:
        raise IOError("{} has an SHA256 checksum ({}) "

```

--------------------------------

### fetch_yiip_equilibrium_long

Source: https://www.mdanalysis.org/MDAnalysisData/_sources/yiip_equilibrium.rst.txt

Fetches the long (90-ns) equilibrium MD trajectory of the YiiP membrane-protein system.

```APIDOC
## fetch_yiip_equilibrium_long

### Description
Fetches the long (90-ns) equilibrium MD trajectory of the YiiP membrane-protein system.

### Method
This is a function call, not an HTTP request.

### Parameters
This function does not take any parameters.

### Returns
- A trajectory object representing the 90-ns MD simulation.
```

--------------------------------

### Fetch AdK FRODA transitions dataset

Source: https://www.mdanalysis.org/MDAnalysisData/adk_transitions.html

Loads the AdK FRODA transitions dataset. This dataset contains trajectories sampled using the Framework Rigidity Optimized Dynamics Algorithm (FRODA).

```APIDOC
## fetch_adk_transitions_FRODA

### Description
Loads the AdK FRODA transititions dataset.

### Method
`fetch_adk_transitions_FRODA(data_home=None, download_if_missing=True)`

### Parameters
#### Path Parameters
None

#### Query Parameters
- **data_home** (str) - Optional - 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>/adk_transitions_FRODA`.
- **download_if_missing** (bool) - Optional - If `False`, raise a `IOError` if the data is not locally available instead of trying to download the data from the source site. Default is `True`.

### Request Example
```python
import MDAnalysisData.adk_transitions

topology_file, trajectories = MDAnalysisData.adk_transitions.fetch_adk_transitions_FRODA()
```

### Response
#### Success Response (dataset)
- **dataset.topology** (filename) - Filename of the topology file
- **dataset.trajectories** (list) - list with filenames of the trajectory ensemble
- **dataset.N_trajectories** (int) - number of trajectories in the ensemble
- **dataset.DESCR** (string) - Description of the ensemble

#### Response Example
```json
{
  "topology": "path/to/1ake.pdb",
  "trajectories": ["path/to/froda_traj1.dcd", "path/to/froda_traj2.dcd", ...],
  "N_trajectories": 200,
  "DESCR": "FRODA AdK with geometric targeting on a rigid decomposition (FRODA server); closed (1AKE) to open (4AKE). Topology file: 1ake.pdb (without hydrogens)"
}
```
```

--------------------------------

### Load Dataset into MDAnalysis Universe

Source: https://www.mdanalysis.org/MDAnalysisData/_sources/usage.rst.txt

Loads the topology and trajectory files into an MDAnalysis Universe object for analysis.

```python
import MDAnalysis as mda
u = mda.Universe(adk.topology, adk.trajectory)
```

--------------------------------

### fetch_vesicle_lib

Source: https://www.mdanalysis.org/MDAnalysisData/_sources/vesicles.rst.txt

Fetches a vesicle library dataset. This function provides access to pre-constructed vesicle models.

```APIDOC
## fetch_vesicle_lib

### Description
Fetches a vesicle library dataset. This function provides access to pre-constructed vesicle models.

### Method
`fetch_vesicle_lib()`

### Parameters
This function does not take any parameters.

### Returns
- A dataset object representing a vesicle model.
```

--------------------------------

### _read_description()

Source: https://www.mdanalysis.org/MDAnalysisData/helpers.html

Reads dataset descriptions from restructured text files.

```APIDOC
## MDAnalysisData.base._read_description(_filename_ , _description_dir ='descr'_)

### Description
Read the description from restructured text file.

### Parameters
* **filename** (_str_) – name of the description file under the `descr` directory

### Note
All description files are supposed to be stored in the directory description_dir `="descr"` that lives in the same directory as the `MDAnalysisData.base` module file. All descriptions are assumed to be in restructured text format and in UTF-8 encoding.
```

--------------------------------

### Set Data Directory via Environment Variable

Source: https://www.mdanalysis.org/MDAnalysisData/_sources/usage.rst.txt

Configures the local data directory for MDAnalysisData by setting the MDANALYSIS_DATA environment variable. This affects where datasets are downloaded and cached.

```bash
export MDANALYSIS_DATA=/tmp/MDAnalysis_data
```

--------------------------------

### Read Description File

Source: https://www.mdanalysis.org/MDAnalysisData/helpers.html

Reads dataset descriptions from reStructuredText files located in the 'descr' directory. Assumes UTF-8 encoding for the description files.

```python
MDAnalysisData.base._read_description(_filename_ , _description_dir ='descr'_)
```

--------------------------------

### fetch_yiip_equilibrium_long

Source: https://www.mdanalysis.org/MDAnalysisData/_modules/MDAnalysisData/yiip_equilibrium.html

Loads the Yii P 90 ns equilibrium trajectory. Allows specifying a custom data home directory and controlling download behavior.

```APIDOC
## fetch_yiip_equilibrium_long

### Description
Loads the Yii P 90 ns equilibrium trajectory. This function allows users to specify an alternative directory for downloading and caching data, and to control whether the data should be downloaded if it's not found locally.

### 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>/yiip_equilibrium``.
- **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): An object with the following attributes:
  - **topology** (filename): Filename of the topology file.
  - **trajectory** (filename): Filename of the trajectory file.
  - **DESCR** (string): Description of the trajectory.

### See Also
See :ref:`yiip-equilibrium-dataset` for a more detailed description.
```

--------------------------------

### Download and Unpack Data Archive

Source: https://www.mdanalysis.org/MDAnalysisData/_modules/MDAnalysisData/adk_transitions.html

This function handles downloading a tar.gz archive if it's missing and then unpacks it to a specified directory. It ensures that the topology and trajectory files are correctly placed and accessible.

```python
import tarfile
import glob
from os.path import join, exists
from os import makedirs
import logging

from MDAnalysis.utils.download import _fetch_remote
from MDAnalysis.utils.misc import get_data_home, Bunch

logger = logging.getLogger(__name__)

def _read_description(metadata):
    # Placeholder for actual description reading logic
    return "Description not available."

def load_dataset(metadata, download_if_missing=True, data_home=None, file_type='tarfile'):
    """
    Loads a dataset from a local directory or downloads it if missing.

    Parameters
    ----------
    metadata : dict
        Metadata describing the dataset, including archive details and contents.
    download_if_missing : bool, optional
        If True, download the data if it is not found locally. Defaults to True.
    data_home : str, optional
        The base directory for storing downloaded data. Defaults to MDAnalysis's default data directory.
    file_type : str, optional
        The type of archive file. Currently supports 'tarfile'. Defaults to 'tarfile'.

    Returns
    -------
    dataset : dict-like object with the following attributes:
    dataset.topology : filename
        Filename of the topology file
    dataset.trajectories : list
        list with filenames of the trajectory ensemble
    dataset.DESCR : string
        Description of the ensemble

    Note
    ----
    Assumptions that are built in:
    - download a single tar.gz file
    - trajectories are given with a glob pattern

    """
    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))
        logger.info("Downloading {0}: {1} -> {2}...".format(
            "tarfile", meta.url, local_path))
        archive_path = _fetch_remote(meta, dirname=data_location)

        logger.info("Unpacking {}...".format(archive_path))
        with tarfile.open(archive_path, 'r') as tar:
            tar.extractall(path=data_location)

    records.topology = join(data_location, metadata['CONTENTS']['topology'])
    if not exists(records.topology):
        # should not happen...
        raise RuntimeError("topology file {} is missing".format(records.topology))

    trajectory_pattern = join(data_location, metadata['CONTENTS']['trajectories'])
    records.trajectories = glob.glob(trajectory_pattern)
    records.N_trajectories = metadata['CONTENTS']['N_trajectories']
    if len(records.trajectories) != records.N_trajectories:
        # should not happen...
        raise RuntimeError("trajectory files in {0} are incomplete: only {1} "
                           "but should be {2}.".format(
                               trajectory_pattern, len(records.trajectories),
                               records.N_trajectories))

    records.DESCR = _read_description(metadata['DESCRIPTION'])

    return records

```

--------------------------------

### Fetch AdK Equilibrium Trajectory Data

Source: https://www.mdanalysis.org/MDAnalysisData/_modules/MDAnalysisData/adk_equilibrium.html

Loads the AdK 1us equilibrium trajectory (without water). Specify `data_home` to set a custom cache folder. Set `download_if_missing` to `False` to prevent automatic downloads.

```python
# -*- coding: utf-8 -*-

"""AdK equilibrium trajectory without water.

https://figshare.com/articles/Molecular_dynamics_trajectory_for_benchmarking_MDAnalysis/5108170/1
"""

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 = "adk_equilibrium"
DESCRIPTION = "adk_equilibrium.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='adk4AKE.psf',
        url='https://ndownloader.figshare.com/files/8672230',
        checksum='1aa947d58fb41b6805dc1e7be4dbe65c6a8f4690f0bd7fc2ae03e7bd437085f4',
    ),
    'trajectory':  RemoteFileMetadata(
        filename='1ake_007-nowater-core-dt240ps.dcd',
        url='https://ndownloader.figshare.com/files/8672074',
        checksum='598fcbcfcc425f6eafbe9997238320fcacc6a4613ecce061e1521732bab734bf',
    ),
}

logger = logging.getLogger(__name__)




[docs]
def fetch_adk_equilibrium(data_home=None, download_if_missing=True):
    """Load the AdK 1us equilibrium trajectory (without water)

    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>/adk_equilibrium``.
    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:`adk-equilibrium-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

```

--------------------------------

### Read Description File

Source: https://www.mdanalysis.org/MDAnalysisData/_modules/MDAnalysisData/base.html

Reads a description from a restructured text file located in the 'descr' directory. Assumes UTF-8 encoding.

```python
def _read_description(filename, description_dir='descr'):
    """Read the description from restructured text file.

    Arguments
    ---------
    filename : str
        name of the description file under the ``descr`` directory

    Note
    ----
    All description files are supposed to be stored in the directory
    `description_dir` ``="descr"`` that lives in the same directory as
    the :mod:`MDAnalysisData.base` module file. All descriptions are
    assumed to be in restructured text format and in UTF-8 encoding.

    """
    # The descr directory should be in the same directory as this file base.py.
    # `resource_string` returns bytes, which we need to decode to UTF-8
    path = importlib.resources.files('MDAnalysisData') / description_dir / filename
    DESCR = path.read_bytes().decode("utf-8")
    return DESCR
```

--------------------------------

### Fetch membrane peptide dataset

Source: https://www.mdanalysis.org/MDAnalysisData/_modules/MDAnalysisData/membrane_peptide.html

Use this function to download and load the helical peptide in DMPC membrane equilibrium trajectory. Specify `data_home` to set a custom download location or `download_if_missing=False` to prevent automatic downloads.

```python
from MDAnalysisData.membrane_peptide import fetch_membrane_peptide

# Load the dataset, downloading if necessary
dataset = fetch_membrane_peptide()

# Access the topology and trajectory files
topology_file = dataset.topology
trajectory_file = dataset.trajectory

# Access the description
description = dataset.DESCR

print(f"Topology file: {topology_file}")
print(f"Trajectory file: {trajectory_file}")
print(f"Description: {description}")
```

--------------------------------

### Access Dataset Description

Source: https://www.mdanalysis.org/MDAnalysisData/usage.html

Prints the human-readable description of the fetched dataset, including its characteristics and origin.

```python
>>> print(adk.DESCR)
```