clustering

Functions

calc_perm_variance(pca, embeddings_df[, ...])	Calculates the variance explained for a PCA of the permuted data.
get_optimal_n_components(embeddings[, ...])	Calculates the optimal number of principal components to keep in a dimension reduction situation.
hdbscan_clustering(reduced[, ...])	Uses HDBSCAN to calculate clusters from the reduced data.
kmeans_clustering(reduced[, num_clusters, ...])	This function calculates clusters based on the reduced vectors.
reduce_dimensions_pca(embeddings[, dimensions])	Reduces the number of dimensions using PCA.
reduce_dimensions_umap(embeddings[, ...])	Uses UMAP to reduce the dimensionality of the embeddings.
shuffle(df)	Shuffles the data by each column or row for a pandas dataframe.
single_sample_t_test(sample[, population_stat])	Run a simple t test on a sample to see if it is significantly different from the population mean.