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

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

.. _sphx_glr_auto_examples_flim_plot_lifetime_moments.py:


====================
Mean lifetime images
====================
Compute the mean lifetime in a pixel using the method of moments
(Irvin Isenberg, 1973, Biophysical journal).

.. GENERATED FROM PYTHON SOURCE LINES 8-20

.. code-block:: Python

    import tttrlib
    import numpy as np
    import pylab as plt

    filename = '../../tttr-data/imaging/pq/ht3/crn_clv_img.ht3'
    filename_irf = '../../tttr-data/imaging/pq/ht3/crn_clv_mirror.ht3'
    channels_green = [0, 2]
    channels_red = [1, 3]

    data = tttrlib.TTTR(filename)
    irf = tttrlib.TTTR(filename_irf)








.. GENERATED FROM PYTHON SOURCE LINES 21-24

Create a new CLSM Image. This image will be used as a template for the green and red image.
This avoids passing through the TTTR screen multiple times. The frame line, and pixel locations
will be copied for the green and red image from this template.

.. GENERATED FROM PYTHON SOURCE LINES 24-68

.. code-block:: Python

    clsm_template = tttrlib.CLSMImage(data)
    clsm_green = tttrlib.CLSMImage(
        source=clsm_template,
        channels=channels_green
    )
    clsm_red = tttrlib.CLSMImage(
        source=clsm_template,
        channels=channels_red
    )

    mean_tau_green = clsm_green.get_mean_lifetime(
        tttr_irf=irf[irf.get_selection_by_channel(channels_green)],
        tttr_data=data,
        minimum_number_of_photons=20,
        stack_frames=True
    )

    green = clsm_green.intensity.sum(axis=0)
    red = clsm_red.intensity.sum(axis=0)

    mask = (green < 20) + (red < 20)
    masked_green = np.ma.masked_where(mask, green)
    masked_red = np.ma.masked_where(mask, red)
    masked_tau = np.ma.masked_where(mask, mean_tau_green.mean(axis=0))
    lg_sg_sr = np.log(masked_green / masked_red)

    fig, ax = plt.subplots(nrows=2, ncols=2)
    ax[0, 0].set_title('Green intensity')
    ax[0, 1].set_title('Red intensity')
    ax[1, 0].set_title('Mean green fl. lifetime')
    ax[1, 1].set_title('Pixel histogram')
    ax[1, 1].set_xlabel('tauG / ns')
    ax[1, 1].set_ylabel('log(Sg/Sr')
    ax[0, 0].imshow(green, cmap='cividis')
    ax[0, 1].imshow(red, cmap='inferno')
    ax[1, 0].imshow(mean_tau_green.mean(axis=0), cmap='Spectral')
    ax[1, 1].hist2d(
        x=masked_tau.flatten(),
        y=lg_sg_sr.flatten(),
        range=((0.001, 4), (-2, 0.9)),
        bins=41
    )
    plt.show()




.. image-sg:: /auto_examples/flim/images/sphx_glr_plot_lifetime_moments_001.png
   :alt: Green intensity, Red intensity, Mean green fl. lifetime, Pixel histogram
   :srcset: /auto_examples/flim/images/sphx_glr_plot_lifetime_moments_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none

    /builds/skf/tttrlib/examples/flim/plot_lifetime_moments.py:48: RuntimeWarning: divide by zero encountered in log
      lg_sg_sr = np.log(masked_green / masked_red)





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

   **Total running time of the script:** (0 minutes 17.986 seconds)


.. _sphx_glr_download_auto_examples_flim_plot_lifetime_moments.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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