def squash_embeddings(embeddings): spinner = Halo('squashing embeddings down to 2d and normalising').start() embeddings = UMAP(n_components=2).fit_transform(embeddings) normalised_embeddings = ((embeddings - embeddings.min(axis=0)) / (embeddings.max(axis=0) - embeddings.min(axis=0))) spinner.succeed() return normalised_embeddings