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

    Click :ref:`here <sphx_glr_download_auto_examples_plot_5_example_Demultiplexer_Multiplexer.py>` to download the full example code
.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_plot_5_example_Demultiplexer_Multiplexer.py:


.. _example5:

Fifth Example: Demultiplexor - multiplexor
-----------------------------------------------

An imaginative layout using a classifier to predict the cluster labels and fitting a separate model for each cluster.

Steps of the **PipeGraph**:

- **scaler**: A :class:`MinMaxScaler` data preprocessor
- **classifier**: A :class:`GaussianMixture` classifier
- **demux**: A custom :class:`Demultiplexer` class in charge of splitting the input arrays accordingly to the selection input vector
- **lm_0**: A :class:`LinearRegression` model
- **lm_1**: A :class:`LinearRegression` model
- **lm_2**: A :class:`LinearRegression` model
- **mux**: A custom :class:`Multiplexer` class in charge of combining different input arrays into a single one accordingly to the selection input vector

.. figure:: https://raw.githubusercontent.com/mcasl/PipeGraph/master/examples/images/Diapositiva5.png

    Figure 1. PipeGraph diagram showing the steps and their connections



.. code-block:: python

    import numpy as np
    import pandas as pd
    from sklearn.preprocessing import MinMaxScaler
    from sklearn.linear_model import LinearRegression
    from sklearn.model_selection import GridSearchCV
    from pipegraph.base import PipeGraph, Demultiplexer, Multiplexer
    import matplotlib.pyplot as plt
    from sklearn.mixture import GaussianMixture

    X_first = pd.Series(np.random.rand(100,))
    y_first = pd.Series(4 * X_first + 0.5*np.random.randn(100,))
    X_second = pd.Series(np.random.rand(100,) + 3)
    y_second = pd.Series(-4 * X_second + 0.5*np.random.randn(100,))
    X_third = pd.Series(np.random.rand(100,) + 6)
    y_third = pd.Series(2 * X_third + 0.5*np.random.randn(100,))

    X = pd.concat([X_first, X_second, X_third], axis=0).to_frame()
    y = pd.concat([y_first, y_second, y_third], axis=0).to_frame()

    scaler = MinMaxScaler()
    gaussian_mixture = GaussianMixture(n_components=3)
    demux = Demultiplexer()
    lm_0 = LinearRegression()
    lm_1 = LinearRegression()
    lm_2 = LinearRegression()
    mux = Multiplexer()


    steps = [('scaler', scaler),
             ('classifier', gaussian_mixture),
             ('demux', demux),
             ('lm_0', lm_0),
             ('lm_1', lm_1),
             ('lm_2', lm_2),
             ('mux', mux), ]







Instead of using ``inject`` as in previous example, in this one we are going to pass a dictionary
describing the connections to PipeGraph constructor



.. code-block:: python


    connections = { 'scaler': {'X': 'X'},
                    'classifier': {'X': 'scaler'},
                    'demux': {'X': 'scaler',
                              'y': 'y',
                              'selection': 'classifier'},
                    'lm_0': {'X': ('demux', 'X_0'),
                             'y': ('demux', 'y_0')},
                    'lm_1': {'X': ('demux', 'X_1'),
                             'y': ('demux', 'y_1')},
                    'lm_2': {'X': ('demux', 'X_2'),
                             'y': ('demux', 'y_2')},
                    'mux': {'0': 'lm_0',
                            '1': 'lm_1',
                            '2': 'lm_2',
                            'selection': 'classifier'}}

    pgraph = PipeGraph(steps=steps, fit_connections=connections)
    pgraph.fit(X, y)
    #%%
    y_pred = pgraph.predict(X)
    plt.scatter(X, y)
    plt.scatter(X, y_pred)




.. image:: /auto_examples/images/sphx_glr_plot_5_example_Demultiplexer_Multiplexer_001.png
    :class: sphx-glr-single-img




**Total running time of the script:** ( 0 minutes  0.031 seconds)


.. _sphx_glr_download_auto_examples_plot_5_example_Demultiplexer_Multiplexer.py:


.. only :: html

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



  .. container:: sphx-glr-download

     :download:`Download Python source code: plot_5_example_Demultiplexer_Multiplexer.py <plot_5_example_Demultiplexer_Multiplexer.py>`



  .. container:: sphx-glr-download

     :download:`Download Jupyter notebook: plot_5_example_Demultiplexer_Multiplexer.ipynb <plot_5_example_Demultiplexer_Multiplexer.ipynb>`


.. only:: html

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

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