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

.. only:: html

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

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

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

.. _sphx_glr_auto_examples_props_plot_xi_kappa.py:


Plot κ(ξ) for various models
=================================

.. GENERATED FROM PYTHON SOURCE LINES 5-90



.. image-sg:: /auto_examples/props/images/sphx_glr_plot_xi_kappa_001.png
   :alt: plot xi kappa
   :srcset: /auto_examples/props/images/sphx_glr_plot_xi_kappa_001.png
   :class: sphx-glr-single-img





.. code-block:: Python


    import logging
    import time

    import matplotlib.pyplot as plt
    import numpy as np

    from examples import utils
    from pttools.logging import setup_logging
    from pttools.bubble.boundary import Phase
    from pttools.bubble.bubble import Bubble
    from pttools.models.const_cs import ConstCSModel
    from pttools.bubble.fluid_reference import ref
    from pttools.speedup.parallel import run_parallel

    logger = logging.getLogger(__name__)


    def alpha_thetabarn_to_alpha_n(model: ConstCSModel, alpha_thetabarn: float, wn: float):
        return alpha_thetabarn - 1/wn * (1 - 1/(3*model.csb2))*(model.p(wn, Phase.SYMMETRIC) - model.p(wn, Phase.BROKEN))


    def kappa_vec(params: np.ndarray, v_walls: np.ndarray) -> np.ndarray:
        model, alpha_n = params
        kappas = np.ones_like(v_walls) * np.nan
        v_wall: float
        for i, v_wall in enumerate(v_walls):
            try:
                bubble = Bubble(model, v_wall=v_wall, alpha_n=alpha_n)
                kappas[i] = bubble.kappa
            except (IndexError, ValueError, RuntimeError):
                continue
        return kappas


    def main():
        ref()
        t_start = time.perf_counter()
        alpha_ns = np.array([0.01, 0.03, 0.1, 0.3, 1, 3])
        colors = ["blue", "orange", "red", "green", "purple", "grey"]
        v_walls = np.linspace(0.2, 0.95, 10)
        lines = ["--", "-", "--", "-"]
        V_s = 1
        a_s = 1.1
        a_b = 1
        allow_invalid = True
        logger.debug("Loading models for plot_xi_kappa.")
        models = [
            ConstCSModel(a_s=a_s, a_b=a_b, css2=1/3, csb2=1/3, V_s=V_s, allow_invalid=allow_invalid),
            ConstCSModel(a_s=a_s, a_b=a_b, css2=1/3, csb2=1/4, V_s=V_s, allow_invalid=allow_invalid),
            ConstCSModel(a_s=a_s, a_b=a_b, css2=1/4, csb2=1/3, V_s=V_s, allow_invalid=allow_invalid),
            ConstCSModel(a_s=a_s, a_b=a_b, css2=1/4, csb2=1/4, V_s=V_s, allow_invalid=allow_invalid)
        ]
        logger.debug("Models loaded for plot_xi_kappa.")
        fig: plt.Figure = plt.figure()
        ax: plt.Axes = fig.add_subplot()
        params = np.zeros((len(models), alpha_ns.size, 2), dtype=np.object_)
        for i_model, model in enumerate(models):
            for i_alpha, alpha_n in enumerate(alpha_ns):
                params[i_model, i_alpha, :] = (model, alpha_n)
        kappas = run_parallel(
            func=kappa_vec, params=params, multiple_params=True, args=(v_walls, ),
            return_arr_shape=(v_walls.size, ), output_dtypes=(np.float64, )
        )
        for i_alpha, color in enumerate(colors):
            for i_model, (model, ls) in enumerate(zip(models, lines)):
                ax.plot(
                    v_walls, kappas[i_model, i_alpha, :], color=color, ls=ls,
                    label=f"{alpha_ns[i_alpha]}, css2={model.css2:.3f}, csb={model.csb2:.3f}"
                )

        ax.set_ylim(0.01, 10)
        ax.set_yscale("log")
        ax.set_xlabel(r"$\xi_w$")
        ax.set_ylabel(r"$\kappa$")
        ax.legend()

        logger.info(f"Elapsed time: {time.perf_counter() - t_start:.2f}")
        return fig


    if __name__ == "__main__":
        setup_logging()
        fig = main()
        utils.save_and_show(fig, "plot_xi_kappa.png")


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

   **Total running time of the script:** (0 minutes 10.697 seconds)

**Estimated memory usage:**  263 MB


.. _sphx_glr_download_auto_examples_props_plot_xi_kappa.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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