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.. "auto_examples/wfs_demonstration_experimental.py"
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.. only:: html

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

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

.. _sphx_glr_auto_examples_wfs_demonstration_experimental.py:


WFS demo experiment
=====================
This script demonstrates how to perform a wavefront shaping experiment using the openwfs library.
It performs wavefront shaping with a FourierDualReference algorithm, maximizing feedback from a
single region of interest (ROI) on a camera.
It assumes that you have a genicam-compatible camera and an SLM connected to the video output of your computer.

Adjustments to make for your specific setup:
* the path to the camera driver.
* The code assumes the SLM is connected as a secondary monitor. If not, adjust the monitor_id below.
* The gray value that corresponds to a 2pi phase shift on the SLM. This is used to set the lookup table of the SLM.

.. GENERATED FROM PYTHON SOURCE LINES 14-62

.. code-block:: Python


    import astropy.units as u
    import matplotlib.pyplot as plt
    import numpy as np

    from openwfs.algorithms import FourierDualReference
    from openwfs.devices import Camera, SLM
    from openwfs.processors import SingleRoi
    from openwfs.utilities import Transform

    # Adjust these parameters to your setup
    # The camera driver file path
    camera_driver_path = R"C:\Program Files\Basler\pylon 7\Runtime\x64\ProducerU3V.cti"
    monitor_id = 2
    # time to stabilize the SLM, in frames
    settle_time = 2
    # we are using a setup with an SLM that produces 2pi phase shift
    # at a gray value of 142. With proper calibration, this is usually 256.
    two_pi_gray_value = 142
    centering = Transform(source_origin=(0, 0), destination_origin=(0.0, 0.3))


    # This script shows how a wavefront shaping experiment can be performed from Python
    cam = Camera(camera_driver_path, PixelFormat="Mono10p")
    cam.exposure = 16.666 * u.ms
    roi_detector = SingleRoi(cam, radius=2)

    # constructs the actual slm for wavefront shaping, and a monitor window to display the current phase pattern
    slm = SLM(monitor_id=monitor_id, duration=settle_time, transform=centering)
    monitor = slm.clone(monitor_id=0, pos=(0, 0), shape=(slm.shape[0] // 3, slm.shape[1] // 3))

    slm.lookup_table = range(two_pi_gray_value)
    alg = FourierDualReference(feedback=roi_detector, slm=slm, slm_shape=[800, 800], k_radius=9)

    result = alg.execute()
    print(result)
    optimised_wf = -np.angle(result.t)
    before = roi_detector.read()
    slm.set_phases(optimised_wf)
    after = roi_detector.read()
    print(f"actual_optimized_intensity: {after}")
    print(f"improvement_ratio: {after / before}")

    while True:
        slm.set_phases(optimised_wf)
        plt.pause(1.0)
        slm.set_phases(0.0)
        plt.pause(1.0)


.. _sphx_glr_download_auto_examples_wfs_demonstration_experimental.py:

.. only:: html

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

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

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

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

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

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

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


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