Changes in version 1.2.1                        

  - Initial version.

  - manifold_sculpting() implements Manifold Sculpting (Gashler, Ventura
    and Martinez, 2008), following the reference implementation of the
    authors in the Waffles library. The neighbor search and the
    iterations are written in C++. All the dimensions of the data are
    kept during the iterations at the cost of the preserved ones only,
    and nstart runs the algorithm several times and keeps the embedding
    with the lowest error.

  - predict() embeds new samples from their nearest training samples.

  - step_manifold_sculpting() is a recipes step, with the tuning
    parameters num_comp, neighbors and squishing_rate().

  - sim_swiss_roll() and sim_s_curve() simulate the test manifolds of
    the paper.

  - New vignette("comparison") compares Manifold Sculpting with Isomap,
    LLE, t-SNE, UMAP, nonlinear PCA and kernel PCA. It is precomputed,
    from vignettes/comparison.Rmd.orig, by vignettes/precompute.R.

  - New vignette("spectroscopy") explores the NIR spectra of meat of the
    modeldata package with Manifold Sculpting, the tidyverse and
    tidymodels: a two-dimensional embedding shows that the arch of the
    PCA scores is a genuine curve of the spectra, a one-dimensional
    embedding unfolds it into a coordinate along the gradient of fat,
    and a short comparison with principal component regression shows
    that unfolding does not help to predict protein.