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

.. only:: html

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

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

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

.. _sphx_glr_gallery_benchmarks_reproducible_parameter_sweep.py:


Reproducible parameter-sweep benchmark
======================================

Benchmark a fixed PyMieSim parameter grid while recording environment metadata.
The script is deterministic; runtime values are machine-dependent and should
be compared only under the same environment.

.. GENERATED FROM PYTHON SOURCE LINES 9-50




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

 .. code-block:: none

    Python: 3.11.16
    Platform: Linux-6.17.0-1022-azure-x86_64-with-glibc2.39
    PyMieSim grid: [1, 1, 1, 1, 100, 1, 1]
    Results: 100
    Median runtime: 0.001444 s
    All timings: [0.001465, 0.001444, 0.001452, 0.001435, 0.001442]






|

.. code-block:: Python


    import platform
    import statistics
    import time

    import numpy as np

    from PyMieSim import Experiment, GaussianSet, PolarizationSet, SphereSet, ureg


    def build_experiment(size: int = 100) -> Experiment:
        source = GaussianSet(
            wavelength=[600] * ureg.nanometer,
            polarization=PolarizationSet(angles=[0] * ureg.degree),
            optical_power=[1e-3] * ureg.watt,
            numerical_aperture=[0.2],
        )
        scatterer = SphereSet(
            diameter=np.linspace(100, 1000, size) * ureg.nanometer,
            material=[1.5],
            medium=[1.0],
        )
        return Experiment(scatterer_set=scatterer, source_set=source)


    experiment = build_experiment()
    for _ in range(2):
        experiment.get("Qsca").as_numpy()

    timings = []
    for _ in range(5):
        start = time.perf_counter()
        values = experiment.get("Qsca").as_numpy()
        timings.append(time.perf_counter() - start)

    print(f"Python: {platform.python_version()}")
    print(f"Platform: {platform.platform()}")
    print(f"PyMieSim grid: {experiment.array_shape}")
    print(f"Results: {np.asarray(values).size}")
    print(f"Median runtime: {statistics.median(timings):.6f} s")
    print(f"All timings: {[round(value, 6) for value in timings]}")


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

   **Total running time of the script:** (0 minutes 0.022 seconds)


.. _sphx_glr_download_gallery_benchmarks_reproducible_parameter_sweep.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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