  We present a new method GTSNE to visualize high-dimensional data points in
the two dimensional map. The technique is a variation of t-SNE that produces
better visualizations by capturing both the local neighborhood structure and
the macro structure in the data. This is particularly important for
high-dimensional data that lie on continuous low-dimensional manifolds. We
illustrate the performance of GTSNE on a wide variety of datasets and compare
it the state of art methods, including t-SNE and UMAP. The visualizations
produced by GTSNE are better than those produced by the other techniques on
almost all of the datasets on the macro structure preservation.
