plot_swissroll.txt

.. _sphx_glr_auto_examples_manifold_plot_swissroll.py:


===================================
Swiss Roll reduction with LLE
===================================

An illustration of Swiss Roll reduction
with locally linear embedding



.. image:: /auto_examples/manifold/images/sphx_glr_plot_swissroll_001.png
    :align: center


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

 Out::

      Computing LLE embedding
    Done. Reconstruction error: 9.45483e-08




|


.. code-block:: python


    # Author: Fabian Pedregosa -- <fabian.pedregosa@inria.fr>
    # License: BSD 3 clause (C) INRIA 2011

    print(__doc__)

    import matplotlib.pyplot as plt

    # This import is needed to modify the way figure behaves
    from mpl_toolkits.mplot3d import Axes3D
    Axes3D

    #----------------------------------------------------------------------
    # Locally linear embedding of the swiss roll

    from sklearn import manifold, datasets
    X, color = datasets.samples_generator.make_swiss_roll(n_samples=1500)

    print("Computing LLE embedding")
    X_r, err = manifold.locally_linear_embedding(X, n_neighbors=12,
                                                 n_components=2)
    print("Done. Reconstruction error: %g" % err)

    #----------------------------------------------------------------------
    # Plot result

    fig = plt.figure()
    try:
        # compatibility matplotlib < 1.0
        ax = fig.add_subplot(211, projection='3d')
        ax.scatter(X[:, 0], X[:, 1], X[:, 2], c=color, cmap=plt.cm.Spectral)
    except:
        ax = fig.add_subplot(211)
        ax.scatter(X[:, 0], X[:, 2], c=color, cmap=plt.cm.Spectral)

    ax.set_title("Original data")
    ax = fig.add_subplot(212)
    ax.scatter(X_r[:, 0], X_r[:, 1], c=color, cmap=plt.cm.Spectral)
    plt.axis('tight')
    plt.xticks([]), plt.yticks([])
    plt.title('Projected data')
    plt.show()

**Total running time of the script:**
(0 minutes 0.472 seconds)



.. container:: sphx-glr-download

    **Download Python source code:** :download:`plot_swissroll.py <plot_swissroll.py>`


.. container:: sphx-glr-download

    **Download IPython notebook:** :download:`plot_swissroll.ipynb <plot_swissroll.ipynb>`