Ecco un'implementazione in Python basata sul suggerimento molto utile di izomorpio sopra. Questo si basa su this implementation del crescente problema di sottosuccessione. Funziona, come dice izomorphius, tenendo traccia di "i migliori V trovati finora" e delle "sequenze sempre migliori trovate finora". Si noti che estendere una V, una volta identificata, non è diversa dall'estensione di una sequenza decrescente. Inoltre deve esserci una regola per "generare" nuovi candidati V da sottosezioni crescenti precedentemente rilevate.
from bisect import bisect_left
def Vsequence(seq):
"""Returns the longest (non-contiguous) subsequence of seq that
first increases, then decreases (i.e. a "V sequence").
"""
# head[j] = index in 'seq' of the final member of the best increasing
# subsequence of length 'j + 1' yet found
head = [0]
# head_v[j] = index in 'seq' of the final member of the best
# V-subsequence yet found
head_v = []
# predecessor[j] = linked list of indices of best increasing subsequence
# ending at seq[j], in reverse order
predecessor = [-1] * len(seq)
# similarly, for the best V-subsequence
predecessor_v = [-1] * len(seq)
for i in xrange(1, len(seq)):
## First: extend existing V's via decreasing sequence algorithm.
## Note heads of candidate V's are stored in head_v and that
## seq[head_v[]] is a non-increasing sequence
j = -1 ## "length of best new V formed by modification, -1"
if len(head_v) > 0:
j = bisect_left([-seq[head_v[idx]] for idx in xrange(len(head_v))], -seq[i])
if j == len(head_v):
head_v.append(i)
if seq[i] > seq[head_v[j]]:
head_v[j] = i
## Second: detect "new V's" if the next point is lower than the head of the
## current best increasing sequence.
k = -1 ## "length of best new V formed by spawning, -1"
if len(head) > 1 and seq[i] < seq[head[-1]]:
k = len(head)
extend_with(head_v, i, k + 1)
for idx in range(k,-1,-1):
if seq[head_v[idx]] > seq[i]: break
head_v[idx] = i
## trace new predecessor path, if found
if k > j:
## It's better to build from an increasing sequence
predecessor_v[i] = head[-1]
trace_idx = predecessor_v[i]
while trace_idx > -1:
predecessor_v[trace_idx] = predecessor[trace_idx]
trace_idx=predecessor_v[trace_idx]
elif j > 0:
## It's better to extend an existing V
predecessor_v[i] = head_v[j - 1]
## Find j such that: seq[head[j - 1]] < seq[i] <= seq[head[j]]
## seq[head[j]] is increasing, so use binary search.
j = bisect_left([seq[head[idx]] for idx in xrange(len(head))], seq[i])
if j == len(head):
head.append(i) ## no way to turn any increasing seq into a V!
if seq[i] < seq[head[j]]:
head[j] = i
if j > 0: predecessor[i] = head[j - 1]
## trace subsequence back to output
result = []
trace_idx = head_v[-1]
while (trace_idx >= 0):
result.append(seq[trace_idx])
trace_idx = predecessor_v[trace_idx]
return result[::-1]
Qualche esempio di uscita:
>>> l1
[26, 92, 36, 61, 91, 93, 98, 58, 75, 48, 8, 10, 58, 7, 95]
>>> Vsequence(l1)
[26, 36, 61, 91, 93, 98, 75, 48, 10, 7]
>>>
>>> l2
[20, 66, 53, 4, 52, 30, 21, 67, 16, 48, 99, 90, 30, 85, 34, 60, 15, 30, 61, 4]
>>> Vsequence(l2)
[4, 16, 48, 99, 90, 85, 60, 30, 4]
I numeri nella sottosequenza sono nello stesso ordine in cui sono nella sequenza originale, ma non devono essere contigui, giusto? – gcbenison
sì esatto. Significa che puoi eliminare elementi dalla sequenza originale ma non puoi aggiungere e il numero di cancellazioni dovrebbe essere minimo. –
Duplicato di http://stackoverflow.com/questions/9764512/longest-subsequence-that-first-increases-then-decreases/9764580#9764580 –