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

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

.. _sphx_glr_auto_examples_flim_plot_pixel_masks.py:


=================
Using Pixel masks
=================

.. GENERATED FROM PYTHON SOURCE LINES 9-30

.. code-block:: Python

    import pylab as plt
    from matplotlib.pyplot import imread
    import tttrlib
    import numpy as np

    tttr_data = tttrlib.TTTR('../../tttr-data/imaging/pq/ht3/pq_ht3_clsm.ht3', 'HT3')
    channels = (0, 1)
    reading_parameter = {
        "tttr_data": tttr_data,
        "marker_frame_start": [4],
        "marker_line_start": 1,
        "marker_line_stop": 2,
        "marker_event_type": 1,
        "n_pixel_per_line": 256, # if zero n_pixel_per_line = n_lines
        "reading_routine": 'default',
        "fill": True,
        "channels": channels,
        "skip_before_first_frame_marker": True
    }
    clsm_image = tttrlib.CLSMImage(**reading_parameter)








.. GENERATED FROM PYTHON SOURCE LINES 31-70

.. code-block:: Python

    n_frames, n_lines, n_pixel = clsm_image.shape
    mask_template = imread("../../tttr-data/imaging/misc/clsm_mask.png").astype(np.uint8).T
    mask = np.empty((n_frames, n_lines, n_pixel), dtype=np.uint8)
    for i in range(n_frames):
        mask[i] = mask_template
    kw = {
        "tttr_data": tttr_data,
        "mask": mask,
        "tac_coarsening": 16,
        "stack_frames": False
    }
    decay = clsm_image.get_decay_of_pixels(**kw)
    intensity = clsm_image.intensity
    intensity_stacked = intensity.sum(axis=0)

    # mask small intensities to have transparency
    masked_intensity_stacked = np.ma.masked_where(
        intensity_stacked < 0.9,
        intensity_stacked
    )
    masked_intensity = np.ma.masked_where(
        intensity < 0.9,
        intensity
    )
    mask = np.ma.masked_where(mask < 0.9, mask)

    fig, ax = plt.subplots(nrows=1, ncols=3)
    im = ax[0].imshow(intensity_stacked)
    ax[0].set_title('Stacked frames')
    im = ax[0].imshow(mask[0], vmin=0.1)
    ax[1].set_title('Pixel selection mask')
    im = ax[2].semilogy(decay.sum(axis=0), label='Mask: Stacked frames')

    im = ax[1].imshow(masked_intensity[0], vmin=0.1)
    ax[1].set_title('First frame')
    im = ax[1].imshow(mask[0], vmin=0.1)
    im = ax[2].semilogy(decay[0], label='Mask: First frame')
    ax[2].legend()
    plt.show()



.. image-sg:: /auto_examples/flim/images/sphx_glr_plot_pixel_masks_001.png
   :alt: Stacked frames, First frame
   :srcset: /auto_examples/flim/images/sphx_glr_plot_pixel_masks_001.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 1.757 seconds)


.. _sphx_glr_download_auto_examples_flim_plot_pixel_masks.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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