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

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

.. _sphx_glr_auto_examples_matrix_plot_matrix_of_perturbation_plots.py:


Matrix of Perturbation Correlation Plots
========================================
This example demonstrates how to generate a matrix plot of perturbation plots for a suite of applications and experiments. This method
is detailed in the :ref:`technical manual <sec-consistent-random-variables>`, and requires randomly sampling nuclear data libraries to
generate a scatter plot. It is recommended that the user refers to :ref:`sphx_glr_auto_examples_correlation_plot_perturbation_correlation_plot.py`
for more information on the perturbation correlation plots that compose the matrix plots shown herein before continuing with this
example.

.. GENERATED FROM PYTHON SOURCE LINES 12-23

Interactive Matrix Plots
------------------------
Interactive matrix plots wrap several Plotly plots in an html grid that's served by a Dash app that allows users to interact
with each of the individual plots. This is useful for comparing multiple applications and experiments in a single figure.
Specifically, it is useful for viewing all combinations of a given set of SDF files in a single figure

**Note** that by default the the correlation plots in the off-diagonal cells are 
:class:`tsunami_ip_utils.viz.scatter_plot.InteractiveScatterLegend` plots, which are fully interactive, and dynamically update
the calculated summary statistics and regression when points are excluded with the legend. However, this interactivity requires
clientiside python to run, and so is not represented in the documentation. The off-diagonal plot types can be changed, and doing so
is documented in :ref:`sphx_glr_auto_examples_matrix_plot_changing_plot_defaults.py`.

.. GENERATED FROM PYTHON SOURCE LINES 23-29

.. code-block:: Python


    from paths import EXAMPLES

    application_files = [ EXAMPLES / 'data' / 'example_sdfs' / 'u235-dummy' / f'sphere_model_{i}.sdf' for i in range(1,4) ]
    experiment_files = application_files








.. GENERATED FROM PYTHON SOURCE LINES 30-33

Generate the Points Array
-------------------------
First, an array of points must be generated for each application-experiment pair (these are used to construct the perturbation plots).

.. GENERATED FROM PYTHON SOURCE LINES 33-43

.. code-block:: Python


    from tsunami_ip_utils.perturbations import generate_points
    from pathlib import Path

    base_library = EXAMPLES / 'data' / 'dummy_56_v7.1'
    perturbation_factors = Path("~/codes/SCALE-6.3.1/data/perturb/56n.v7.1")
    num_perturbations = 100

    points = generate_points(application_files, experiment_files, base_library, perturbation_factors, num_perturbations)





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

 .. code-block:: none


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.. GENERATED FROM PYTHON SOURCE LINES 44-50

Generate the Plot Objects
-------------------------
Now, the :func:`tsunami_ip_utils.viz.viz.matrix_plot` function needs a numpy array of plot objects to generate the matrix plot.
We can generate this array using the :func:`tsunami_ip_utils.viz.plot_utils.generate_plot_objects_array_from_perturbations` function.
This function takes a dictionary of contributions and the name of the integral index, and returns a numpy array of plot objects
that can be passed to the :func:`tsunami_ip_utils.viz.viz.matrix_plot` function.

.. GENERATED FROM PYTHON SOURCE LINES 50-55

.. code-block:: Python


    from tsunami_ip_utils.viz.plot_utils import generate_plot_objects_array_from_perturbations

    plot_objects = generate_plot_objects_array_from_perturbations(points)








.. GENERATED FROM PYTHON SOURCE LINES 56-60

Create the Matrix Plot
----------------------
Finally, we can create the matrix plot using the :func:`tsunami_ip_utils.viz.viz.matrix_plot` function. This function takes the
numpy array of plot objects generated in the previous step, and generates a matrix plot of perturbation correlation plots.

.. GENERATED FROM PYTHON SOURCE LINES 60-70

.. code-block:: Python


    from tsunami_ip_utils.viz.viz import matrix_plot

    labels = {
        'applications': [ file.name for file in application_files ],
        'experiments': [ file.name for file in experiment_files ]
    }
    fig = matrix_plot(plot_objects, plot_type='interactive', labels=labels)
    fig.show()




.. raw:: html

    <div class="zoomControls">
        <button type="button" onclick="zoom(1, this)">- Zoom Out</button>
        <button type="button" onclick="zoom(-1, this)">+ Zoom In</button>
    </div>
    <div class="iframe_container">
        <iframe src="../../_static/plot_fdeebc4f-877e-4003-8c8d-e7be95dac242.html" width="100%" height="100%" frameborder="0" class="myiframe"></iframe>
    </div>
    <script>
        function zoom(direction, element) {
            // Find the closest parent container that includes both the buttons and the iframe
            const zoomContainer = element.closest('.zoomControls');
            const iframeContainer = zoomContainer.nextElementSibling;
            const iframe = iframeContainer.querySelector('.myiframe');

            // Initialize or retrieve the current scale
            let currentScale = parseFloat($(iframe).data('scale')) || 0.5;
            let originalWidth = parseFloat($(iframe).data('originalWidth')) || $(iframe).width();
            let originalHeight = parseFloat($(iframe).data('originalHeight')) || $(iframe).height();

            if (direction === 1) {
                currentScale /= 1.1;
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            let scaledWidth = originalWidth / currentScale;
            let scaledHeight = originalHeight / currentScale;

            // Store the updated scale
            $(iframe).data('scale', currentScale);

            // Apply the new scale as a CSS transform
            $(iframe).css('transform', `scale(${currentScale})`);
            $(iframe).css('width', `${scaledWidth}px`);
            $(iframe).css('height', `${scaledHeight}px`);
        }

        function applyInitialScale() {
            document.querySelectorAll('.myiframe').forEach(iframe => {
                let initialScale = 0.5;
                let originalWidth = $(iframe).width();
                let originalHeight = $(iframe).height();

                $(iframe).data('scale', initialScale);
                $(iframe).data('originalWidth', originalWidth);
                $(iframe).data('originalHeight', originalHeight);

                let scaledWidth = originalWidth / initialScale;
                let scaledHeight = originalHeight / initialScale;

                iframe.style.width = `${scaledWidth}px`;
                iframe.style.height = `${scaledHeight}px`;
                iframe.style.transform = 'scale(0.5)'; // Apply a neutral scale since size is already adjusted
                iframe.style.transformOrigin = '0 0'; // Transform from top left corner
            });
        }

        window.onload = function() {
            // Apply initial scale to all iframes when the page loads
            applyInitialScale();
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    </script>
            




.. GENERATED FROM PYTHON SOURCE LINES 71-72

The plot can be saved to an image by using the :meth:`tsunami_ip_utils.viz.matrix_plot.InteractiveMatrixPlot.to_image` method

.. GENERATED FROM PYTHON SOURCE LINES 72-76

.. code-block:: Python


    fig = matrix_plot(plot_objects, plot_type='interactive', labels=labels)
    fig.to_image( EXAMPLES / '_static' / 'perturbation_matrix.png' )

    # sphinx_gallery_thumbnail_path = '../../examples/_static/perturbation_matrix.png'


.. raw:: html

    <div class="zoomControls">
        <button type="button" onclick="zoom(1, this)">- Zoom Out</button>
        <button type="button" onclick="zoom(-1, this)">+ Zoom In</button>
    </div>
    <div class="iframe_container">
        <iframe src="../../_static/plot_62901cde-96af-47dd-b46c-34eff0368916.html" width="100%" height="100%" frameborder="0" class="myiframe"></iframe>
    </div>
    <script>
        function zoom(direction, element) {
            // Find the closest parent container that includes both the buttons and the iframe
            const zoomContainer = element.closest('.zoomControls');
            const iframeContainer = zoomContainer.nextElementSibling;
            const iframe = iframeContainer.querySelector('.myiframe');

            // Initialize or retrieve the current scale
            let currentScale = parseFloat($(iframe).data('scale')) || 0.5;
            let originalWidth = parseFloat($(iframe).data('originalWidth')) || $(iframe).width();
            let originalHeight = parseFloat($(iframe).data('originalHeight')) || $(iframe).height();

            if (direction === 1) {
                currentScale /= 1.1;
            } else {
                currentScale *= 1.1;
            }

            let scaledWidth = originalWidth / currentScale;
            let scaledHeight = originalHeight / currentScale;

            // Store the updated scale
            $(iframe).data('scale', currentScale);

            // Apply the new scale as a CSS transform
            $(iframe).css('transform', `scale(${currentScale})`);
            $(iframe).css('width', `${scaledWidth}px`);
            $(iframe).css('height', `${scaledHeight}px`);
        }

        function applyInitialScale() {
            document.querySelectorAll('.myiframe').forEach(iframe => {
                let initialScale = 0.5;
                let originalWidth = $(iframe).width();
                let originalHeight = $(iframe).height();

                $(iframe).data('scale', initialScale);
                $(iframe).data('originalWidth', originalWidth);
                $(iframe).data('originalHeight', originalHeight);

                let scaledWidth = originalWidth / initialScale;
                let scaledHeight = originalHeight / initialScale;

                iframe.style.width = `${scaledWidth}px`;
                iframe.style.height = `${scaledHeight}px`;
                iframe.style.transform = 'scale(0.5)'; // Apply a neutral scale since size is already adjusted
                iframe.style.transformOrigin = '0 0'; // Transform from top left corner
            });
        }

        window.onload = function() {
            // Apply initial scale to all iframes when the page loads
            applyInitialScale();
        };
    </script>
            





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

   **Total running time of the script:** (0 minutes 26.175 seconds)


.. _sphx_glr_download_auto_examples_matrix_plot_matrix_of_perturbation_plots.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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