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

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

.. _sphx_glr_auto_examples_troubleshooter_demo.py:

Τroubleshooter demo
=====================
This script demonstrates how to use the troubleshooter to diagnose
problems in a wavefront shaping experiment.
In this example, `alg` is the wavefront shaping algorithm object,
`roi_background` is a `SingleRoi` object that computes the average speckle intensity,
`cam` is a `Camera` object and `shutter` is an object to control the shutter.
The `report()` method prints a report of the analysis and test results to the console.

.. GENERATED FROM PYTHON SOURCE LINES 10-61

.. code-block:: Python


    import astropy.units as u
    import numpy as np

    from openwfs.algorithms import StepwiseSequential, troubleshoot
    from openwfs.processors import SingleRoi
    from openwfs.simulation import SLM, Microscope, Shutter, Camera
    from openwfs.utilities import set_pixel_size

    # === Define virtual devices for a WFS simulation ===
    # Note: these virtual-device classes may be replaced
    # with real-device classes to run a real WFS experiment

    # Define aberration as a pattern of random phases at the pupil plane
    aberrations = np.random.uniform(size=(40, 40)) * 2 * np.pi

    # Define specimen as an image with several bright pixels
    specimen = np.zeros((120, 120))
    specimen[60, 60] = 1e4
    specimen = set_pixel_size(specimen, pixel_size=200 * u.nm)

    # Simulate an SLM with incorrect phase response
    # Also simulate a shutter that can turn off the light
    # The SLM is conjugated to the back pupil plane
    slm = SLM(shape=(100, 100), phase_response=(np.arange(256) / 128 * np.pi) * 1.2)
    shutter = Shutter(slm.field)

    # Simulate a WFS microscope looking at the specimen
    sim = Microscope(
        source=specimen,
        incident_field=shutter,
        aberrations=aberrations,
        wavelength=800 * u.nm,
    )

    # Simulate a camera device with gaussian noise and shot noise
    cam = Camera(sim, analog_max=1e4, shot_noise=True, gaussian_noise_std=4.0)

    # Define feedback as circular region of interest in the center of the frame
    roi_detector = SingleRoi(cam, radius=0.1)

    # === Run wavefront shaping experiment ===
    # Use the stepwise sequential (SSA) WFS algorithm
    alg = StepwiseSequential(feedback=roi_detector, slm=slm, n_x=10, n_y=10, phase_steps=16)

    # Define a region of interest to determine background intensity
    roi_background = SingleRoi(cam, radius=10)

    # Run WFS troubleshooter and output a report to the console
    trouble = troubleshoot(algorithm=alg, background_feedback=roi_background, frame_source=cam, shutter=shutter)
    trouble.report()


.. _sphx_glr_download_auto_examples_troubleshooter_demo.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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