.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/004_plot_demo.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        Click :ref:`here <sphx_glr_download_auto_examples_004_plot_demo.py>`
        to download the full example code

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

.. _sphx_glr_auto_examples_004_plot_demo.py:


Plot Demo
=========

Demonstrating the mass-composition plot methods.

.. GENERATED FROM PYTHON SOURCE LINES 7-14

.. code-block:: default


    import pandas as pd
    import plotly
    from plotly.graph_objs import Figure
    from elphick.mass_composition.datasets.sample_data import sample_data
    from elphick.mass_composition import MassComposition








.. GENERATED FROM PYTHON SOURCE LINES 15-19

Create a MassComposition object
-------------------------------

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

.. GENERATED FROM PYTHON SOURCE LINES 20-24

.. code-block:: default


    df_data: pd.DataFrame = sample_data()
    print(df_data.head())





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

 .. code-block:: none

           wet_mass  mass_dry    FE  SIO2  al2o3  LOI  group
    index                                                   
    0         100.0      90.0  57.0   5.2    3.0  5.0  grp_1
    1          90.0      80.0  59.0   3.1    1.7  4.0  grp_1
    2         110.0      90.0  61.0   2.2    0.9  3.0  grp_2




.. GENERATED FROM PYTHON SOURCE LINES 25-26

Construct a MassComposition object and standardise the chemistry variables

.. GENERATED FROM PYTHON SOURCE LINES 27-31

.. code-block:: default


    obj_mc: MassComposition = MassComposition(df_data)
    print(obj_mc)





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

 .. code-block:: none


    unnamed
    <xarray.Dataset> Size: 216B
    Dimensions:   (index: 3)
    Coordinates:
      * index     (index) int64 24B 0 1 2
    Data variables:
        mass_wet  (index) float64 24B 100.0 90.0 110.0
        mass_dry  (index) float64 24B 90.0 80.0 90.0
        H2O       (index) float64 24B 10.0 11.11 18.18
        Fe        (index) float64 24B 57.0 59.0 61.0
        SiO2      (index) float64 24B 5.2 3.1 2.2
        Al2O3     (index) float64 24B 3.0 1.7 0.9
        LOI       (index) float64 24B 5.0 4.0 3.0
        group     (index) object 24B 'grp_1' 'grp_1' 'grp_2'
    Attributes:
        mc_name:            unnamed
        mc_vars_mass:       ['mass_wet', 'mass_dry']
        mc_vars_chem:       ['Fe', 'SiO2', 'Al2O3', 'LOI']
        mc_vars_attrs:      ['group']
        mc_interval_edges:  {}




.. GENERATED FROM PYTHON SOURCE LINES 32-33

Create an interactive parallel plot

.. GENERATED FROM PYTHON SOURCE LINES 34-38

.. code-block:: default


    fig: Figure = obj_mc.plot_parallel()
    fig






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>                        <script type="text/javascript">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>
            <script charset="utf-8" src="https://cdn.plot.ly/plotly-2.32.0.min.js"></script>                <div id="5d4ea9e9-eca0-41e8-9ffd-cb3a16a75cfd" class="plotly-graph-div" style="height:100%; width:100%;"></div>            <script type="text/javascript">                                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("5d4ea9e9-eca0-41e8-9ffd-cb3a16a75cfd")) {                    Plotly.newPlot(                        "5d4ea9e9-eca0-41e8-9ffd-cb3a16a75cfd",                        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    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 39-40

Create an interactive parallel plot with only the components

.. GENERATED FROM PYTHON SOURCE LINES 41-45

.. code-block:: default


    fig2 = obj_mc.plot_parallel(vars_include=['mass_wet', 'H2O', 'Fe'])
    fig2






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
    <div>                        <script type="text/javascript">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>
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                       {"responsive": true}                    )                };                            </script>        </div>
    </div>
    <br />
    <br />

.. GENERATED FROM PYTHON SOURCE LINES 46-47

Create a parallel plot with color

.. GENERATED FROM PYTHON SOURCE LINES 48-52

.. code-block:: default


    fig3 = obj_mc.plot_parallel(color='group')
    fig3






.. raw:: html

    <div class="output_subarea output_html rendered_html output_result">
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.. GENERATED FROM PYTHON SOURCE LINES 53-54

Create a ternary diagram for 3 composition variables

.. GENERATED FROM PYTHON SOURCE LINES 55-60

.. code-block:: default


    fig4 = obj_mc.plot_ternary(variables=['SiO2', 'Al2O3', 'LOI'], color='group')
    # noinspection PyTypeChecker
    plotly.io.show(fig4)  # this call to show will set the thumbnail for use in the gallery




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   **Total running time of the script:** ( 0 minutes  1.445 seconds)


.. _sphx_glr_download_auto_examples_004_plot_demo.py:

.. only:: html

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