WrapFullJit

class corsort.wrap_full_jit.JitCorsortBorda(compute_history=False, record_states=False)[source]

Corsort “Borda”. Cf. WrapFullJit.

Examples

>>> sort = JitCorsortBorda()

class corsort.wrap_full_jit.JitCorsortDeltaMaxDelta(compute_history=False, record_states=False)[source]

Corsort with delta core scorer, max-knowledge tie-break, and delta output scorer. Cf. WrapFullJit.

Examples

>>> sort = JitCorsortDeltaMaxDelta()

class corsort.wrap_full_jit.JitCorsortDeltaMaxRho(compute_history=False, record_states=False)[source]

Corsort with delta core scorer, max-knowledge tie-break, and rho output scorer. Cf. WrapFullJit.

Examples

>>> sort = JitCorsortDeltaMaxRho()

class corsort.wrap_full_jit.JitCorsortDeltaSumDelta(compute_history=False, record_states=False)[source]

Corsort with delta core scorer, sum-knowledge tie-break, and delta output scorer. Cf. WrapFullJit.

Examples

>>> sort = JitCorsortDeltaSumDelta()

class corsort.wrap_full_jit.JitCorsortDeltaSumRho(compute_history=False, record_states=False)[source]

Corsort with delta core scorer, sum-knowledge tie-break, and rho output scorer. Cf. WrapFullJit.

Examples

>>> sort = JitCorsortDeltaSumRho()

class corsort.wrap_full_jit.JitCorsortRhoMaxDelta(compute_history=False, record_states=False)[source]

Corsort with rho core scorer, max-knowledge tie-break, and delta output scorer. Cf. WrapFullJit.

Examples

>>> sort = JitCorsortRhoMaxDelta()

class corsort.wrap_full_jit.JitCorsortRhoMaxRho(compute_history=False, record_states=False)[source]

Corsort with rho core scorer, max-knowledge tie-break, and rho output scorer. Cf. WrapFullJit.

Examples

>>> sort = JitCorsortRhoMaxRho()

class corsort.wrap_full_jit.JitCorsortRhoSumDelta(compute_history=False, record_states=False)[source]

Corsort with rho core scorer, sum-knowledge tie-break, and delta output scorer. Cf. WrapFullJit.

Examples

>>> sort = JitCorsortRhoSumDelta()

class corsort.wrap_full_jit.JitCorsortRhoSumRho(compute_history=False, record_states=False)[source]

Corsort with rho core scorer, sum-knowledge tie-break, and rho output scorer. Cf. WrapFullJit.

Examples

>>> sort = JitCorsortRhoSumRho()

class corsort.wrap_full_jit.JitHeapsort(compute_history=False, record_states=False)[source]

Heapsort. Cf. WrapFullJit.

Examples

>>> sort = JitHeapsort()

class corsort.wrap_full_jit.WrapFullJit(jit_sort, compute_history=False, record_states=False)[source]

Delegate everything (sort and scores) to a jit function.

Parameters:

compute_history (bool) – If True, then compute the history of the distance to the sorted array.
record_states (bool) – If True, then record the states of the algorithm.

n_

Number of items in the list.

Type:: int:

perm_

Input permutation.

Type:: ndarray

n_comparisons_

Number of comparison performed.

Type:: int

history_distances_

History of the kendall-tau distance to the sorted list.

Type:: list of int

history_comparisons_

History of the pairwise comparisons. Tuple (i, j) means that items of indices i and j were compared, and that perm[i] < perm[j].

Type:: list of tuple

history_states_

History of the state of the list.

Type:: list of tuple

Examples

>>> corsort = WrapFullJit(jit_sort=jit_corsort_borda, compute_history=True, record_states=True)
>>> corsort.__name__
'corsort_borda'
>>> np.random.seed(22)
>>> n = 15
>>> p = np.random.permutation(n)
>>> corsort(p).n_comparisons_
43
>>> entropy_bound(n)  
40.24212...
>>> corsort.history_distances_  
[76, 64, 76, 74, 74, 72, 62, 62, 54, 48, 48, 48, 44, 46, 44, 44, 44, 36, 36, 26, 22, 18, 18, 16, 14, 18, 14, 12,
 10, 12, 8, 6, 6, 10, 8, 6, 8, 6, 6, 4, 4, 0, 2, 0]
>>> corsort.history_comparisons_  
[(0, 1), (3, 2), (3, 0), (0, 4), (4, 1), (2, 4), (2, 0), (0, 5), (7, 6), (7, 0),
(3, 7), (0, 8), (8, 5), (5, 1), (8, 6), (2, 7), (9, 10), (8, 10), (11, 8), (11, 7),
(13, 12), (8, 12), (12, 10), (6, 12), (4, 6), (12, 1), (10, 1), (13, 0), (2, 13),
(11, 2), (11, 3), (7, 13), (9, 0), (2, 9), (4, 8), (5, 12), (6, 5), (7, 9), (13, 9),
(14, 0), (2, 14), (13, 14), (14, 9)]
>>> corsort.history_comparisons_values_  
[(7, 14), (1, 2), (1, 7), (7, 8), (8, 14), (2, 8), (2, 7), (7, 11), (3, 10), (3, 7),
(1, 3), (7, 9), (9, 11), (11, 14), (9, 10), (2, 3), (6, 13), (9, 13), (0, 9), (0, 3),
(4, 12), (9, 12), (12, 13), (10, 12), (8, 10), (12, 14), (13, 14), (4, 7), (2, 4),
(0, 2), (0, 1), (3, 4), (6, 7), (2, 6), (8, 9), (11, 12), (10, 11), (3, 6), (4, 6),
(5, 7), (2, 5), (4, 5), (5, 6)]

>>> p = np.array([2, 1, 3, 0])
>>> corsort(p).history_states_
[[2, 1, 3, 0], [1, 3, 0, 2], [1, 0, 2, 3], [1, 0, 2, 3], [1, 0, 2, 3], [0, 1, 2, 3]]

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.

Type:: list of tuple