.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "gallery/validation/percus_yevick_vs_tsang_2001_monodisperse.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_gallery_validation_percus_yevick_vs_tsang_2001_monodisperse.py>`
        to download the full example code.

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

.. _sphx_glr_gallery_validation_percus_yevick_vs_tsang_2001_monodisperse.py:


PackLab monodisperse Percus--Yevick versus Tsang et al.
=======================================================

This example compares PackLab's monodisperse Percus--Yevick (PY) solution with
digitised PY curves from Figure 8.1.3 of Tsang, Kong, Ding, and Ao (2001).
The two reference cases use volume fractions :math:`f=0.2` and :math:`f=0.3`
and the reduced separation :math:`r/b`, where :math:`b` is the sphere diameter.

The digitised curves come from a printed figure, so they support a visual
comparison rather than a high-precision numerical error estimate.

.. GENERATED FROM PYTHON SOURCE LINES 13-24

.. code-block:: Python


    import os
    from pathlib import Path

    import matplotlib.pyplot as plt
    from matplotlib.lines import Line2D
    import numpy as np

    from PackLab import analytical, ureg









.. GENERATED FROM PYTHON SOURCE LINES 25-27

Load the digitised PY curves
----------------------------

.. GENERATED FROM PYTHON SOURCE LINES 27-42

.. code-block:: Python


    if "PACKLAB_DOCS_ROOT" in os.environ:
        docs_root = Path(os.environ["PACKLAB_DOCS_ROOT"])
    else:
        docs_root = Path(__file__).resolve().parents[2]
    data_path = (
        docs_root
        / "manuscript"
        / "softwareX"
        / "data"
        / "tsang_2001_figure_8_1_3_digitized.csv"
    )
    digitized = np.genfromtxt(data_path, delimiter=",", names=True, dtype=None, encoding="utf-8")









.. GENERATED FROM PYTHON SOURCE LINES 43-45

Evaluate the matching PackLab PY solutions
------------------------------------------

.. GENERATED FROM PYTHON SOURCE LINES 45-87

.. code-block:: Python


    radii = np.array([1.0]) * ureg.micrometer
    reduced_separation = np.linspace(0.0, 5.0, 500)
    cases = ((0.2, "C0", ":", "o"), (0.3, "C1", "-", "s"))

    figure, axis = plt.subplots(figsize=(7, 4.5))
    for volume_fraction, colour, line_style, marker in cases:
        domain = analytical.PercusYevickDomain(
            size=100_000 * ureg.micrometer,
            radii=radii,
            volume_fraction=volume_fraction,
            number_fractions=np.array([1.0]),
        )
        result = analytical.PercusYevickSolver(
            densities=domain.particle_densities_per_radius,
            radii=domain.radii,
            wavenumber="auto",
        ).compute(reduced_separation * 2.0 * radii[0])
        _ = axis.plot(reduced_separation, result.g[0, 0], color=colour, linestyle=line_style, linewidth=2)

        reference = digitized[np.isclose(digitized["volume_fraction"], volume_fraction)]
        _ = axis.plot(
            reference["reduced_separation"],
            reference["g_r"],
            linestyle="none", marker=marker, markersize=4.5,
            markerfacecolor="white", markeredgecolor="black", markeredgewidth=0.9,
        )

    _ = axis.axhline(1.0, color="0.65", linestyle=":", linewidth=1)
    _ = axis.set(
        xlim=(0.0, 5.0), ylim=(0.0, 3.5),
        xlabel=r"reduced separation $r/b$", ylabel=r"pair correlation $g(r)$",
        title="PackLab and digitised Tsang et al. PY reference",
    )
    axis.grid(alpha=0.2)
    _ = axis.legend(handles=[
        Line2D([], [], color=colour, linestyle=line_style, marker=marker,
               markerfacecolor="white", markeredgecolor="black", label=rf"$f={fraction:.1f}$")
        for fraction, colour, line_style, marker in cases
    ])
    figure.tight_layout()
    plt.show()



.. image-sg:: /gallery/validation/images/sphx_glr_percus_yevick_vs_tsang_2001_monodisperse_001.png
   :alt: PackLab and digitised Tsang et al. PY reference
   :srcset: /gallery/validation/images/sphx_glr_percus_yevick_vs_tsang_2001_monodisperse_001.png
   :class: sphx-glr-single-img






.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.148 seconds)


.. _sphx_glr_download_gallery_validation_percus_yevick_vs_tsang_2001_monodisperse.py:

.. only:: html

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

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

      :download:`Download Jupyter notebook: percus_yevick_vs_tsang_2001_monodisperse.ipynb <percus_yevick_vs_tsang_2001_monodisperse.ipynb>`

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

      :download:`Download Python source code: percus_yevick_vs_tsang_2001_monodisperse.py <percus_yevick_vs_tsang_2001_monodisperse.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: percus_yevick_vs_tsang_2001_monodisperse.zip <percus_yevick_vs_tsang_2001_monodisperse.zip>`


.. only:: html

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

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