.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/110_network_layouts.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        Click :ref:`here <sphx_glr_download_auto_examples_110_network_layouts.py>`
        to download the full example code

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

.. _sphx_glr_auto_examples_110_network_layouts.py:


Network Layouts
===============

Related MassComposition objects can be represented in network using the Flowsheet object.

This example demonstrates layouts of such networks.

.. GENERATED FROM PYTHON SOURCE LINES 10-20

.. code-block:: default


    import plotly
    import pandas as pd

    from elphick.mass_composition.flowsheet import Flowsheet
    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 21-25

Create a mass-composition object
--------------------------------

We get some demo data in the form of a pandas DataFrame

.. GENERATED FROM PYTHON SOURCE LINES 26-30

.. code-block:: default


    df_data: pd.DataFrame = size_by_assay()









.. GENERATED FROM PYTHON SOURCE LINES 31-32

Create the object

.. GENERATED FROM PYTHON SOURCE LINES 32-36

.. code-block:: default


    mc_feed: MassComposition = MassComposition(df_data, name='feed')









.. GENERATED FROM PYTHON SOURCE LINES 37-39

Split the Sample
----------------

.. GENERATED FROM PYTHON SOURCE LINES 39-45

.. code-block:: default


    mc_1, mc_2 = mc_feed.split(0.5, 'split 1', 'split 2')
    mc_3, mc_4 = mc_1.split(0.5, 'split 3', 'split 4')
    mc_5, mc_6 = mc_2.split(0.5, 'split 5', 'split 6')









.. GENERATED FROM PYTHON SOURCE LINES 46-47

Create a network and plot with both orientations

.. GENERATED FROM PYTHON SOURCE LINES 48-56

.. code-block:: default


    fs: Flowsheet = Flowsheet().from_streams([mc_feed,
                                               mc_1, mc_2,
                                               mc_3, mc_4, mc_5, mc_6])

    fig = fs.plot_network(orientation='horizontal')
    fig






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.. GENERATED FROM PYTHON SOURCE LINES 57-60

.. code-block:: default

    fig = fs.plot_network(orientation='vertical')
    fig






.. raw:: html

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.. GENERATED FROM PYTHON SOURCE LINES 61-62

The table plot also supports orientation with the network_orientation argument.

.. GENERATED FROM PYTHON SOURCE LINES 63-67

.. code-block:: default


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.. _sphx_glr_download_auto_examples_110_network_layouts.py:

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