I have sorted start indices (included) and end indices (excluded) of intervals (obtained by using seachsorted), for instance: import numpy as np # Both arrays are of same size, and sorted. # Size of arrays is number of intervals. # Intervals do not overlap. # interval indices: 0 1 2 3 4 5 interval_start_idxs = np.array([0, 3, 3, 3, 6, 7]) interval_end_excl_idxs = np.array([2, 4, 4, 4, 7, 9]) An empty interval is identified when interval_start_idxs[interval_idx] == interval_end_excl_idxs[interval_idx]-1 I would like to identify the starts and ends of each region where intervals are empty. A region is made with one or several intervals sharing the same start indices and end excluded indices. With previous data, expected result would then be: empty_interval_starts = [1, 4] # start is included empty_intervals_ends_excl = [4, 5] # end is excluded This result is to be understood as: intervals from index 1 to 3, these intervals are a same region of empty intervals and interval at index 4 is a separate region on its own Continue reading...
