scib_metrics.utils.compute_simpson_index#
- scib_metrics.utils.compute_simpson_index(knn_dists, knn_idx, row_idx, labels, n_labels, perplexity=30, tol=1e-05)[source]#
Compute the Simpson index for each cell.
- Parameters:
- knn_dists
ndarray|Array KNN distances of size (n_cells, n_neighbors).
- knn_idx
ndarray|Array KNN indices of size (n_cells, n_neighbors) corresponding to distances.
- row_idx
ndarray|Array Idx of each row (n_cells, 1).
- labels
ndarray|Array Cell labels of size (n_cells,).
- n_labels
int Number of labels.
- perplexity
float(default:30) Measure of the effective number of neighbors.
- tol
float(default:1e-05) Tolerance for binary search.
- knn_dists
- Return type:
- Returns:
simpson_index Simpson index of size (n_cells,).