.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples/gallery/structure/modeling/mmtf_trajectory.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_examples_gallery_structure_modeling_mmtf_trajectory.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_examples_gallery_structure_modeling_mmtf_trajectory.py:


BinaryCIF as trajectory format
==============================

This example demonstrates how the BinaryCIF format can be used as an
alternative to classical trajectory formats (TRR, XTC, etc.).

For this purpose a trajectory file obtained from a MD simulation
(Gromacs) of lysozyme (PDB: 1AKI) was loaded
(101 frames, 50949 atoms), and the coordinates along with the frame
number are put into a custom BinaryCIF category.
For the model run length encoding is used.
For the coordinates a combination of delta encoding and integer packing
is used.

The trajectory file can be downloaded
:download:`here </examples/download/lysozyme_md.xtc>`.

Using BinaryCIF for macromolecular trajectories takes advantage
of the precise and open specification of the format and the wide support
by a multitude of software.
This comes at cost of a higher file size compared to XTC.

.. GENERATED FROM PYTHON SOURCE LINES 24-94



.. image-sg:: /examples/gallery/structure/modeling/images/sphx_glr_mmtf_trajectory_001.png
   :alt: mmtf trajectory
   :srcset: /examples/gallery/structure/modeling/images/sphx_glr_mmtf_trajectory_001.png
   :class: sphx-glr-single-img





.. code-block:: Python


    # Code source: Patrick Kunzmann
    # License: BSD 3 clause

    import os.path
    from tempfile import NamedTemporaryFile
    import matplotlib.pyplot as plt
    import numpy as np
    import biotite
    import biotite.structure.io.pdbx as pdbx
    import biotite.structure.io.xtc as xtc

    # Put here the path of the downloaded trajectory file
    xtc_file_path = "../../../download/lysozyme_md.xtc"

    xtc_file = xtc.XTCFile.read(xtc_file_path)
    coord = xtc_file.get_coord()
    n_frames = coord.shape[0]
    n_atoms = coord.shape[1]
    # [1, 1, ..., 1, 1, 2, 2, ..., 2, 2, n, n, ..., n, n] for n frames
    frames = np.repeat(np.arange(1, n_atoms + 1), n_frames)

    columns = {}
    columns["frame"] = pdbx.BinaryCIFData(
        frames,
        encoding=[
            pdbx.RunLengthEncoding(src_type=np.int32),
            pdbx.ByteArrayEncoding(),
        ],
    )
    for i, dim in enumerate(("x", "y", "z")):
        columns[f"coord_{dim}"] = pdbx.BinaryCIFData(
            coord[:, :, i].flatten(),
            encoding=[
                pdbx.FixedPointEncoding(factor=100, src_type=np.float32),
                pdbx.DeltaEncoding(),
                # Encode the difference into two bytes
                pdbx.IntegerPackingEncoding(byte_count=2, is_unsigned=False),
                pdbx.ByteArrayEncoding(),
            ],
        )
    category = pdbx.BinaryCIFCategory(columns)
    bcif_file = pdbx.BinaryCIFFile(
        {"lyosozyme_md": pdbx.BinaryCIFBlock({"coord": category})}
    )
    file = NamedTemporaryFile("wb", suffix=".bcif")
    bcif_file.write(file)
    file.flush()

    xtc_size = os.path.getsize(xtc_file_path)
    bcif_size = os.path.getsize(file.name)
    file.close()

    figure = plt.figure()
    ax = figure.add_subplot(111)
    ax.bar(
        [1, 2],
        [xtc_size / 1e6, bcif_size / 1e6],
        width=0.3,
        color=[biotite.colors["dimgreen"], biotite.colors["dimorange"]],
        linewidth=0,
    )
    ax.set_xticks([1, 2])
    ax.set_xticklabels(["XTC", "BinaryCIF"])
    ax.set_xlim(0.5, 2.5)
    ax.set_ylim(0, 40)
    ax.yaxis.grid(True)
    ax.set_ylabel("File size (MB)")
    figure.tight_layout()
    plt.show()


.. _sphx_glr_download_examples_gallery_structure_modeling_mmtf_trajectory.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: mmtf_trajectory.ipynb <mmtf_trajectory.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: mmtf_trajectory.py <mmtf_trajectory.py>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_