pcaTransform
====================

Purpose
----------------------
Reduces the dimension of a matrix using principal component vectors previously returned by :func:`pcaFit`.

Format
----------------------
.. function:: X_transform  = pcaTransform(X, mdl)

    :param X: The matrix to transform. This matrix must have the same number of columns as the matrix passed to :func:`pcaFit`.
    :type X: NxP matrix
    
    :param mdl: This must have been previously been filled in by a call to :func:`pcaFit`.
    :type mdl:  `pcaModel` structure

    :return X_transform:   The input matrix projected on the component vectors returned by a previous call to :func:`pcaFit`.
    :rtype X_transform: Nxn_components matrix

Examples
-------------

::

    new;
    library gml;

    /*
    ** Load and prepare data
    */
    // Get file name with full path
    fname = getGAUSSHome("pkgs/gml/examples/winequality.csv");

    // Load data
    X = loadd(fname, ". -quality");

    // Split data
    X_train = X[1:1000,.];
    X_test = X[1001:rows(X), .];

    /*
    ** Fit model using
    ** training data
    */
    // Number of components
    n_components = 3;

    struct pcaModel mdl;
    mdl = pcaFit(X_train, n_components);

    /*
    ** Transform test data
    */
    X_transform = pcaTransform(X_test, mdl);

After the above code, the first 5 rows of *X_transform* will be:

::

        PC1              PC2              PC3
  37.441282        1.2145282       -1.5416867
 -2.0454164       -15.738950        1.0084994
  21.315231       -2.4328631       0.15655108
  41.776957        2.2901582       -2.2804431
 0.73984770       -12.260074      -0.68265628


.. seealso:: :func:`pcaFit`, :func:`pcaTransformInv`