.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/optical/plot_03_hager2021_fig5.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_optical_plot_03_hager2021_fig5.py>`
        to download the full example code.

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

.. _sphx_glr_auto_examples_optical_plot_03_hager2021_fig5.py:


Häger & Pfister 2021, Fig. 5: linear equalisation and back-propagation
======================================================================

Fig. 5 of C. Häger and H. D. Pfister, "Physics-based deep learning for fiber-optic
communication systems", *IEEE J. Sel. Areas Commun.* 39(1), 2021 (arXiv:2010.14258),
gives the effective SNR against the launch power of a single channel over 25 spans of
80 km of standard fibre at 10.7 GBd with Gaussian symbols, for linear equalisation
(dispersion compensation alone) and digital back-propagation (DBP) with one step per
span. The link is that of the paper: :math:`\beta_2 = -21.683` ps²/km at 194.6 THz,
:math:`\gamma = 1.3` /W/km, 0.2 dB/km, a noise figure of 5 dB, root-raised-cosine
pulses of roll-off 0.1, propagation at 6 samples per symbol and receivers at 2.

The published values were read from the vector paths of the figure (about 0.05 dB)
and are the ``expect`` entries of ``specs/validation/hager2021_fig5.yaml``, which CI
checks within 0.3 dB at the 25 launch powers of the figure; the agreement is within
0.20 dB (0.15 dB below 2 dBm). This script runs that
specification with two trials per point instead of four and draws the published
points on the simulated curves. The validation found that the coarse-step DBP applied
the nonlinear phase over the step length instead of the effective length (60 % of the
phase with one step per span), fixed since.

.. GENERATED FROM PYTHON SOURCE LINES 23-53

.. code-block:: Python


    import matplotlib.pyplot as plt
    import yaml
    from _gallery_utils import SPECS

    import comnum
    from comnum.plot import BACKGROUND

    text = (SPECS / "validation/hager2021_fig5.yaml").read_text(encoding="utf-8")
    spec = yaml.safe_load(text)
    results = comnum.run_spec(text.replace("stop: {max_trials: 4}", "stop: {max_trials: 2}"))

    fig, ax = plt.subplots()
    labels = {"linear": "linear equalisation", "dbp1": "DBP, 1 step per span"}
    for (receiver, label), marker in zip(labels.items(), ["o", "s"], strict=True):
        x, snr = results.series("power_dbm", "snr_eff_db", receiver=receiver)
        (line,) = ax.plot(x, snr, marker=marker, markeredgecolor=BACKGROUND, label=f"comnum, {label}")
        published = next(e for e in spec["expect"] if e["where"]["receiver"] == receiver)["curve"]
        ax.plot(published["x"], published["y"], "x", color=line.get_color(), markersize=7, mew=1.6,
                label=f"Häger & Pfister, Fig. 5, {label}")  # fmt: skip
    ax.set(
        xlim=(-12, 3),
        ylim=(10, 27),
        xlabel="launch power (dBm)",
        ylabel="effective SNR (dB)",
        title="25 × 80 km, 10.7 GBd (Häger & Pfister 2021, Fig. 5)",
    )
    ax.legend(loc="lower left")
    fig.tight_layout()




.. image-sg:: /auto_examples/optical/images/sphx_glr_plot_03_hager2021_fig5_001.png
   :alt: 25 × 80 km, 10.7 GBd (Häger & Pfister 2021, Fig. 5)
   :srcset: /auto_examples/optical/images/sphx_glr_plot_03_hager2021_fig5_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 54-55

The largest difference with the published points, over the powers common to both.

.. GENERATED FROM PYTHON SOURCE LINES 55-62

.. code-block:: Python

    for receiver, label in labels.items():
        rows = dict(zip(*results.series("power_dbm", "snr_eff_db", receiver=receiver), strict=True))
        published = next(e for e in spec["expect"] if e["where"]["receiver"] == receiver)["curve"]
        diffs = [
            abs(rows[x] - y) for x, y in zip(published["x"], published["y"], strict=True) if x in rows
        ]
        print(f"{label}: within {max(diffs):.2f} dB of the published points")




.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    linear equalisation: within 0.13 dB of the published points
    DBP, 1 step per span: within 0.54 dB of the published points





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

   **Total running time of the script:** (0 minutes 16.817 seconds)


.. _sphx_glr_download_auto_examples_optical_plot_03_hager2021_fig5.py:

.. only:: html

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

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

      :download:`Download Jupyter notebook: plot_03_hager2021_fig5.ipynb <plot_03_hager2021_fig5.ipynb>`

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

      :download:`Download Python source code: plot_03_hager2021_fig5.py <plot_03_hager2021_fig5.py>`

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

      :download:`Download zipped: plot_03_hager2021_fig5.zip <plot_03_hager2021_fig5.zip>`


.. only:: html

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

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