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Define shuffling

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danielSanchezQ 2025-07-10 05:00:58 +00:00
parent cd601fdac4
commit 189c4c8244
1 changed files with 11 additions and 2 deletions
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13
da/assignations/refill.py
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@ -54,6 +54,14 @@ def heappop_next_for_subnetwork(subnetwork: Subnetwork, participants: List[Parti
heappush(participants, poped) heappush(participants, poped)
return participant return participant
# sample using fisher yates shuffling, returning
def sample(elements: Sequence[Any], random: ChaCha20, k: int) -> List[Any]:
# list is sorted for reproducibility
elements = sorted(elements)
# pythons built-in is fisher yates shuffling
random.shuffle(elements)
return elements[:k]
def fill_subnetworks( def fill_subnetworks(
available_nodes: List[Participant], available_nodes: List[Participant],
@ -91,7 +99,7 @@ def balance_subnetworks_shrink(
min_subnetwork = min(subnetworks) min_subnetwork = min(subnetworks)
diff_count = (len(max_subnetwork.participants) - len(min_subnetwork.participants)) // 2 diff_count = (len(max_subnetwork.participants) - len(min_subnetwork.participants)) // 2
diff_participants = sorted(max_subnetwork.participants - min_subnetwork.participants) diff_participants = sorted(max_subnetwork.participants - min_subnetwork.participants)
for participant in random.sample(diff_participants, k=diff_count): for participant in sample(diff_participants, random, k=diff_count):
min_subnetwork.participants.add(participant) min_subnetwork.participants.add(participant)
max_subnetwork.participants.remove(participant) max_subnetwork.participants.remove(participant)
@ -103,8 +111,9 @@ def balance_subnetworks_grow(
random: ChaCha20, random: ChaCha20,
): ):
for participant in filter(lambda x: x.participation > average_participation, sorted(participants)): for participant in filter(lambda x: x.participation > average_participation, sorted(participants)):
for subnework in random.sample( for subnework in sample(
sorted(filter(lambda subnetwork: participant.declaration_id in subnetwork.participants, subnetworks)), sorted(filter(lambda subnetwork: participant.declaration_id in subnetwork.participants, subnetworks)),
random,
k=participant.participation - average_participation k=participant.participation - average_participation
): ):
subnework.participants.remove(participant.declaration_id) subnework.participants.remove(participant.declaration_id)