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Gale Shapley Algorithm #2100

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44 changes: 44 additions & 0 deletions graphs/gale_shapley_bigraph.py
Original file line number Diff line number Diff line change
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from typing import List


def stable_matching(donor_pref: List[int], recipient_pref: List[int]) -> List[int]:
"""
Finds the stable match in any bipartite graph, i.e a pairing where no 2 objects
prefer each other over their partner. The function accepts the preferences of
oegan donors and recipients (where both are assigned numbers from 0 to n-1) and
returns a list where the index position corresponds to the donor and value at the
index is the organ recipient.

To better understand the algorithm, see also:
https://github.com/akashvshroff/Gale_Shapley_Stable_Matching (README).
https://www.youtube.com/watch?v=Qcv1IqHWAzg&t=13s (Numberphile YouTube).

>>> donor_pref = [[0, 1, 3, 2], [0, 2, 3, 1], [1, 0, 2, 3], [0, 3, 1, 2]]
>>> recipient_pref = [[3, 1, 2, 0], [3, 1, 0, 2], [0, 3, 1, 2], [1, 0, 3, 2]]
>>> print(stable_matching(donor_pref, recipient_pref))
[1, 2, 3, 0]
"""
assert len(donor_pref) == len(recipient_pref)
n = len(donor_pref)
unmatched_donors = list(range(n))
donor_record = [-1] * n # who the donor has donated to
rec_record = [-1] * n # who the recipient has received from
num_donations = [0] * n
while unmatched_donors:
donor = unmatched_donors[0]
donor_preference = donor_pref[donor]
recipient = donor_preference[num_donations[donor]]
num_donations[donor] += 1
rec_preference = recipient_pref[recipient]
prev_donor = rec_record[recipient]
if prev_donor != -1:
if rec_preference.index(prev_donor) > rec_preference.index(donor):
rec_record[recipient] = donor
donor_record[donor] = recipient
unmatched_donors.append(prev_donor)
unmatched_donors.remove(donor)
else:
rec_record[recipient] = donor
donor_record[donor] = recipient
unmatched_donors.remove(donor)
return donor_record