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70999b4fa0
* Add linear decay funciton to dynamic value challenges * Add the ability to choose between decay functions for dynamic value challenges * Closes #2224 * Closes #865
76 lines
1.9 KiB
Python
76 lines
1.9 KiB
Python
from __future__ import division # Use floating point for math calculations
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import math
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from CTFd.models import Solves
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from CTFd.utils.modes import get_model
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def get_solve_count(challenge):
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Model = get_model()
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solve_count = (
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Solves.query.join(Model, Solves.account_id == Model.id)
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.filter(
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Solves.challenge_id == challenge.id,
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Model.hidden == False,
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Model.banned == False,
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)
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.count()
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)
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return solve_count
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def linear(challenge):
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solve_count = get_solve_count(challenge)
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# If the solve count is 0 we shouldn't manipulate the solve count to
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# let the math update back to normal
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if solve_count != 0:
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# We subtract -1 to allow the first solver to get max point value
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solve_count -= 1
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value = challenge.initial - (challenge.decay * solve_count)
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value = math.ceil(value)
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if value < challenge.minimum:
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value = challenge.minimum
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return value
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def logarithmic(challenge):
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solve_count = get_solve_count(challenge)
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# If the solve count is 0 we shouldn't manipulate the solve count to
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# let the math update back to normal
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if solve_count != 0:
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# We subtract -1 to allow the first solver to get max point value
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solve_count -= 1
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# Handle situations where admins have entered a 0 decay
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# This is invalid as it can cause a division by zero
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if challenge.decay == 0:
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challenge.decay = 1
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# It is important that this calculation takes into account floats.
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# Hence this file uses from __future__ import division
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value = (
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((challenge.minimum - challenge.initial) / (challenge.decay ** 2))
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* (solve_count ** 2)
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) + challenge.initial
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value = math.ceil(value)
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if value < challenge.minimum:
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value = challenge.minimum
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return value
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DECAY_FUNCTIONS = {
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"linear": linear,
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"logarithmic": logarithmic,
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}
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