SortMergeTopDown
- class corsort.SortMergeTopDown(compute_history=False)[source]
Merge sort, top-down version (DFS, i.e. “natural” recursive version).
Examples
>>> merge_sort = SortMergeTopDown(compute_history=True) >>> my_xs = np.array([4, 1, 7, 6, 0, 8, 2, 3, 5]) >>> merge_sort(my_xs).n_comparisons_ 19 >>> merge_sort.history_comparisons_ [(1, 0), (3, 2), (1, 3), (0, 3), (4, 5), (7, 8), (6, 7), (4, 6), (6, 5), (7, 5), (8, 5), (4, 1), (1, 6), (6, 0), (7, 0), (0, 8), (8, 3), (3, 5), (2, 5)] >>> merge_sort.history_distances_ [30, 30, 30, 30, 30, 30, 30, 30, 30, 28, 26, 24, 16, 16, 10, 4, 4, 0, 0, 0] >>> merge_sort.sorted_list_ array([0, 1, 2, 3, 4, 5, 6, 7, 8])
- distance_to_sorted_array()[source]
Distance to sorted array.
- Returns:
Distance between the current estimation and the sorted array.
- Return type:
- property history_comparisons_values_
History of the pairwise comparisons, in terms of compared values. Tuple (x, y) means that items of values x and y were compared, and that x < y.
- test_i_lt_j(i, j)
Test whether perm[i] < perm[j].
- Parameters:
- Returns:
True if item of index i is lower than item of index j.
- Return type:
Notes
The history of distance is computed just before the comparison. Hence it should be computed a last time at the end of the algorithm.