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

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

.. _sphx_glr_auto_examples_flim_plot_transform.py:


===============
Image transform
===============
TTTR CLSM images are constructed of photons that are grouped into pixels. For each photon the micro time, the macro
time and the registering detector is stored as additional information, w. A transformation is a function that maps one
set to another set after performing some operations. An image transform is a function that maps one image to another
image. Instead of operating on gray level intensity of and image at any point. Photons (including their additional
information) are mapped to a new image. Such a mapping can eg for non-affine and affine transforamtions (rotations,
streching, etc.). Below a very simple image transformation (scaling/streching) is illustrated.

Note: Transformations of CLSM images changes the temporal ordering of the photons. Hence, a transformed images 
cannot be used for advanced data analyis such as image correlation. Try to plan your experiment optimally 
and aquire the data as needed (pixel dwell times, laser power, etc.). 

.. GENERATED FROM PYTHON SOURCE LINES 18-23

.. code-block:: Python

    from __future__ import print_function
    import tttrlib
    import numpy as np
    import pylab as plt








.. GENERATED FROM PYTHON SOURCE LINES 24-25

Read data of the CLSM image

.. GENERATED FROM PYTHON SOURCE LINES 25-77

.. code-block:: Python

    data = tttrlib.TTTR('../../tttr-data/imaging/pq/ht3/crn_clv_img.ht3')

    # Read contents of file into new CLSMImage
    settings = {
        "channels": [0, 1],
        "fill": True,
    }
    image = tttrlib.CLSMImage(data, **settings)

    img_original = image.intensity.sum(axis=0)

    # Transform
    # do a 4x4 binning
    bin_line = 4
    bin_pixel = 4
    n_frames, n_lines, n_pixel = image.shape
    n_px = n_frames * n_lines * n_pixel

    # interleaved 1D array of origin and target indices.
    mapping = np.empty(n_px * 2, dtype=np.uint32)
    i = 0
    for f in range(0, n_frames):
        for l in range(0, n_lines):
            for p in range(0, n_pixel):
                source_idx = image.to1D(f, l, p)
                # In this example the lines and pixels are binned by a factor of 4
                target_idx = image.to1D(f, l // bin_line, p // bin_pixel)
                mapping[i + 0] = source_idx
                mapping[i + 1] = target_idx
                i += 2

    # Any other arbitrary mapping cloud be used
    plt.plot(mapping)
    plt.show()

    image.transform(mapping)
    img_transformed = image.intensity.sum(axis=0)

    # Plot the results
    fig, axs = plt.subplots(1, 2)
    axs[0].imshow(img_original)
    axs[1].imshow(img_transformed)
    plt.show()

    # After transforming the image can be cropped
    image.crop(0, n_frames, 0, n_lines // bin_line, 0, n_pixel // bin_pixel)
    img_transformed_cropped = image.intensity.sum(axis=0)
    # Plot the results
    fig, axs = plt.subplots(1, 2)
    axs[0].imshow(img_original)
    axs[1].imshow(img_transformed_cropped)
    plt.show()



.. rst-class:: sphx-glr-horizontal


    *

      .. image-sg:: /auto_examples/flim/images/sphx_glr_plot_transform_001.png
         :alt: plot transform
         :srcset: /auto_examples/flim/images/sphx_glr_plot_transform_001.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /auto_examples/flim/images/sphx_glr_plot_transform_002.png
         :alt: plot transform
         :srcset: /auto_examples/flim/images/sphx_glr_plot_transform_002.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /auto_examples/flim/images/sphx_glr_plot_transform_003.png
         :alt: plot transform
         :srcset: /auto_examples/flim/images/sphx_glr_plot_transform_003.png
         :class: sphx-glr-multi-img






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

   **Total running time of the script:** (0 minutes 7.045 seconds)


.. _sphx_glr_download_auto_examples_flim_plot_transform.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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