.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/108_sankey_plots.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        Click :ref:`here <sphx_glr_download_auto_examples_108_sankey_plots.py>`
        to download the full example code

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

.. _sphx_glr_auto_examples_108_sankey_plots.py:


Sankey Plots
============

Related MassComposition objects are managed as a network.

.. GENERATED FROM PYTHON SOURCE LINES 8-21

.. code-block:: default


    import pandas as pd
    import matplotlib.pyplot as plt
    import plotly
    from matplotlib import pyplot as plt
    from plotly.graph_objs import Figure

    from elphick.mass_composition import MassComposition
    from elphick.mass_composition.flowsheet import Flowsheet
    from elphick.mass_composition.datasets.sample_data import sample_data

    # sphinx_gallery_thumbnail_number = -1








.. GENERATED FROM PYTHON SOURCE LINES 22-26

Create some MassComposition objects
-----------------------------------

Create an object, and split it to create two more objects.

.. GENERATED FROM PYTHON SOURCE LINES 27-32

.. code-block:: default


    df_data: pd.DataFrame = sample_data()
    obj_mc: MassComposition = MassComposition(df_data, name='Feed')
    obj_mc_1, obj_mc_2 = obj_mc.split(0.4)








.. GENERATED FROM PYTHON SOURCE LINES 33-37

Create a Flowsheet object
-------------------------

This requires passing an Iterable of MassComposition objects

.. GENERATED FROM PYTHON SOURCE LINES 38-44

.. code-block:: default


    fs: Flowsheet = Flowsheet().from_streams([obj_mc, obj_mc_1, obj_mc_2])

    hf = fs.plot_network()
    plt.show()








.. GENERATED FROM PYTHON SOURCE LINES 45-51

Sankey Plot
-----------

A sankey represents the network with the width of each edge representing its mass.
The optional color of the edge represents the value of the selected composition analyte.
In this example, grades are the same, so will not add any value.

.. GENERATED FROM PYTHON SOURCE LINES 52-57

.. code-block:: default


    fig: Figure = fs.plot_sankey()
    # noinspection PyTypeChecker
    plotly.io.show(fig)  # this call to show will set the thumbnail for use in the gallery




.. raw:: html
    :file: images/sphx_glr_108_sankey_plots_001.html





.. GENERATED FROM PYTHON SOURCE LINES 58-65

Filtered Data
-------------

It is convenient to filter the underlying data before plotting.

To verify the filtering, we'll plot the sankey as part of the table_plot, which will tabulate the
aggregated mass-composition for each edge/stream in the network.

.. GENERATED FROM PYTHON SOURCE LINES 66-70

.. code-block:: default


    fig: Figure = fs.table_plot(plot_type='sankey', table_pos='left')
    fig






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.. GENERATED FROM PYTHON SOURCE LINES 71-72

Now filter and plot again

.. GENERATED FROM PYTHON SOURCE LINES 73-77

.. code-block:: default


    fig: Figure = fs.query(mc_name='Feed', queries={'index': 'Fe>58'}).table_plot(plot_type='sankey', table_pos='left')
    fig






.. raw:: html

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