e5a98adc53c682047bd6873c127c9c94588b28ab,Python/phate/mds.py,,embed_MDS,#,38

Before Change

    // initialize all by CMDS
    Y = cmdscale_fast(X_dist, ndim)
    if how in ["metric", "nonmetric"]:
        _logger.debug("Performing metric MDS on "
                             "{} of shape {}...".format(type(X_dist),
                                                        X_dist.shape))
        // Metric MDS from sklearn
        Y, _ = manifold.smacof(X_dist, n_components=ndim, metric=True, max_iter=3000,
                               eps=1e-6, random_state=seed, n_jobs=n_jobs,
                               n_init=1, init=Y, verbose=verbose)
    if how == "nonmetric":
        _logger.debug(
            "Performing non-metric MDS on "
            "{} of shape {}...".format(type(X_dist),

After Change

        return Y

    // metric is next fastest
    try:
        // use sgd2 if it is available
        Y = sgd(X_dist, n_components=ndim, random_state=seed, init=Y)
    except NotImplementedError:
        // sgd2 currently only supports n_components==2
        Y = smacof(X_dist, n_components=ndim, random_state=seed, init=Y, metric=True)
    if how == "metric":
        return Y
    // nonmetric is slowest
    Y = smacof(X_dist, n_components=ndim, random_state=seed, init=Y, metric=False)

Instances