.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/115_simplify_network.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        Click :ref:`here <sphx_glr_download_auto_examples_115_simplify_network.py>`
        to download the full example code

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

.. _sphx_glr_auto_examples_115_simplify_network.py:


Simplify a Network
==================

There are times when a simplified view of a complex network is required, to provide a summary of the overall
mass-balance. This can be achieved by collapsing the network into a single node, which represents the system
internals. This is useful for high-level reporting and visualisation.

In this example, we will demonstrate how to simplify a network using the `to_simple` method.

.. GENERATED FROM PYTHON SOURCE LINES 12-24

.. code-block:: default


    import plotly
    import pandas as pd
    from functools import partial

    from elphick.mass_composition.flowsheet import Flowsheet
    from elphick.mass_composition.utils.partition import perfect, napier_munn
    from elphick.mass_composition.datasets.sample_data import size_by_assay
    from elphick.mass_composition import MassComposition

    # sphinx_gallery_thumbnail_number = -1








.. GENERATED FROM PYTHON SOURCE LINES 25-29

Create a network
----------------

We create the same network as in the [Compare Partition Separations](#compare-partition-separations) example.

.. GENERATED FROM PYTHON SOURCE LINES 30-49

.. code-block:: default


    mc_size: MassComposition = MassComposition(size_by_assay(), name='size sample')
    mc_ideal_feed, mc_sim_feed = mc_size.split(0.5, 'ideal feed', 'sim feed')
    part_ideal = partial(perfect, d50=0.150, dim='size')
    part_sim = partial(napier_munn, d50=0.150, ep=0.1, dim='size')
    # Separate the object using the defined partitions
    mc_ideal_coarse, mc_ideal_fine = mc_ideal_feed.split_by_partition(partition_definition=part_ideal,
                                                                      name_1='ideal_coarse', name_2='ideal_fine')
    mc_sim_coarse, mc_sim_fine = mc_sim_feed.split_by_partition(partition_definition=part_sim, name_1='sim_coarse',
                                                                name_2='sim_fine')

    fs: Flowsheet = Flowsheet().from_streams([mc_size, mc_ideal_feed, mc_sim_feed,
                                              mc_ideal_coarse, mc_ideal_fine,
                                              mc_sim_coarse, mc_sim_fine])

    fig = fs.table_plot(table_pos='left',
                        sankey_color_var='Fe', sankey_edge_colormap='copper_r', sankey_vmin=50, sankey_vmax=70)
    fig






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.. GENERATED FROM PYTHON SOURCE LINES 50-52

Simplify the Network
--------------------

.. GENERATED FROM PYTHON SOURCE LINES 52-59

.. code-block:: default


    fs_simple = fs.to_simple(node_name='system')

    fig = fs_simple.table_plot(table_pos='left',
                               sankey_color_var='Fe', sankey_edge_colormap='copper_r', sankey_vmin=50, sankey_vmax=70)
    # noinspection PyTypeChecker
    plotly.io.show(fig)  # this call to show will set the thumbnail for use in the gallery



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    :file: images/sphx_glr_115_simplify_network_001.html






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

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