UMAP and t-SNE are dimensionality reduction algorithms that allow for visualizing high dimensional data. One of the differences between them is that UMAP attempts to preserve the global structure of data by displaying meaningful between-cluster distances. Therefore, in this piece, the UMAP landscape captures the trajectory of bud to flower in the cluster layout whereas the t-SNE landscape does not.