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Bone-Market-Solver
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Update quadratic buyers to reflect balance changes 

The Investment-Minded Ambassador yields 80% of their former secondary
revenue, while the Tentacled Entrepreneur and Teller of Terrors yield
400% of theirs.
This commit is contained in:
Jeremy Saklad 2021-09-11 15:11:01 -05:00
parent 8cc1ddc0b5 32531d2b58
commit 3ff1b2fd46
Signed by: Jeremy Saklad
GPG Key ID: 9CA2149583EDBF84
1 changed files with 28 additions and 12 deletions
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bonemarketsolver/solve.py
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@ -721,14 +721,24 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.AN_INVESTMENT_MINDED_AMBASSADOR]) model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.AN_INVESTMENT_MINDED_AMBASSADOR])
model.Add(antiquity > 0).OnlyEnforceIf(actions[Buyer.AN_INVESTMENT_MINDED_AMBASSADOR]) model.Add(antiquity > 0).OnlyEnforceIf(actions[Buyer.AN_INVESTMENT_MINDED_AMBASSADOR])
antiquity_squared = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name, 'antiquity squared')) antiquity_squared_times_four_fifths = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name, 'antiquity squared times four-fifths'))
model.AddMultiplicationEquality(antiquity_squared, [antiquity, antiquity]) antiquity_squared_times_four = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name, 'antiquity squared times four'))
model.AddGeneralMultiplicationEquality(antiquity_squared_times_four, antiquity, antiquity, 4)
model.AddDivisionEquality(antiquity_squared_times_four_fifths, antiquity_squared_times_four, 5)
del antiquity_squared_times_four
tailfeathers = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name, 'tailfeathers')) tailfeathers = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name, 'tailfeathers'))
if bone_market_fluctuations == Fluctuation.ANTIQUITY: if bone_market_fluctuations == Fluctuation.ANTIQUITY:
model.AddApproximateExponentiationEquality(tailfeathers, antiquity, 2.1, MAXIMUM_ATTRIBUTE) boosted_antiquity = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name, 'boosted antiquity'))
model.AddApproximateExponentiationEquality(boosted_antiquity, antiquity, 2.1, MAXIMUM_ATTRIBUTE)
boosted_antiquity_times_four = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name, 'boosted antiquity times four'))
model.AddMultiplicationEquality(boosted_antiquity_times_four, [boosted_antiquity, 4])
boosted_antiquity_times_four_fifths = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name, 'boosted antiquity times four-fifths'))
model.AddDivisionEquality(boosted_antiquity_times_four_fifths, boosted_antiquity_times_four, 5)
model.Add(tailfeathers == boosted_antiquity_times_four_fifths).OnlyEnforceIf(actions[Buyer.AN_INVESTMENT_MINDED_AMBASSADOR])
del boosted_antiquity, boosted_antiquity_times_four, boosted_antiquity_times_four_fifths
else: else:
model.Add(tailfeathers == antiquity_squared).OnlyEnforceIf(actions[Buyer.AN_INVESTMENT_MINDED_AMBASSADOR]) model.Add(tailfeathers == antiquity_squared_times_four_fifths).OnlyEnforceIf(actions[Buyer.AN_INVESTMENT_MINDED_AMBASSADOR])
total_value = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name, 'total value')) total_value = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name, 'total value'))
model.Add(total_value == value + zoological_mania_bonus) model.Add(total_value == value + zoological_mania_bonus)
@ -744,10 +754,10 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
# The indirection is necessary for applying an enforcement literal # The indirection is necessary for applying an enforcement literal
derived_exhaustion = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name, 'derived exhaustion')) derived_exhaustion = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name, 'derived exhaustion'))
model.AddDivisionEquality(derived_exhaustion, antiquity_squared, 20) model.AddDivisionEquality(derived_exhaustion, antiquity_squared_times_four_fifths, 20)
model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.AN_INVESTMENT_MINDED_AMBASSADOR]) model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.AN_INVESTMENT_MINDED_AMBASSADOR])
del antiquity_squared, tailfeathers, total_value, total_value_remainder, extra_value, derived_exhaustion del antiquity_squared_times_four_fifths, tailfeathers, total_value, total_value_remainder, extra_value, derived_exhaustion
# A Teller of Terrors # A Teller of Terrors
@ -759,9 +769,12 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
feathers = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_TELLER_OF_TERRORS.name, 'feathers')) feathers = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_TELLER_OF_TERRORS.name, 'feathers'))
if bone_market_fluctuations == Fluctuation.MENACE: if bone_market_fluctuations == Fluctuation.MENACE:
model.AddApproximateExponentiationEquality(feathers, menace, 2.1, MAXIMUM_ATTRIBUTE) boosted_menace = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_TELLER_OF_TERRORS.name, 'boosted menace'))
model.AddApproximateExponentiationEquality(boosted_menace, menace, 2.1, MAXIMUM_ATTRIBUTE)
model.Add(feathers == 4*boosted_menace).OnlyEnforceIf(actions[Buyer.A_TELLER_OF_TERRORS])
del boosted_menace
else: else:
model.Add(feathers == menace_squared).OnlyEnforceIf(actions[Buyer.A_TELLER_OF_TERRORS]) model.Add(feathers == 4*menace_squared).OnlyEnforceIf(actions[Buyer.A_TELLER_OF_TERRORS])
total_value = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_TELLER_OF_TERRORS.name, 'total value')) total_value = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_TELLER_OF_TERRORS.name, 'total value'))
model.Add(total_value == value + zoological_mania_bonus) model.Add(total_value == value + zoological_mania_bonus)
@ -776,7 +789,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
# The indirection is necessary for applying an enforcement literal # The indirection is necessary for applying an enforcement literal
derived_exhaustion = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_TELLER_OF_TERRORS.name, 'derived exhaustion')) derived_exhaustion = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_TELLER_OF_TERRORS.name, 'derived exhaustion'))
model.AddDivisionEquality(derived_exhaustion, menace_squared, 100) model.AddDivisionEquality(derived_exhaustion, menace_squared, 25)
model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.A_TELLER_OF_TERRORS]) model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.A_TELLER_OF_TERRORS])
del menace_squared, feathers, total_value, total_value_remainder, derived_exhaustion del menace_squared, feathers, total_value, total_value_remainder, derived_exhaustion
@ -791,9 +804,12 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
final_breaths = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_TENTACLED_ENTREPRENEUR.name, 'final breaths')) final_breaths = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_TENTACLED_ENTREPRENEUR.name, 'final breaths'))
if bone_market_fluctuations == Fluctuation.AMALGAMY: if bone_market_fluctuations == Fluctuation.AMALGAMY:
model.AddApproximateExponentiationEquality(final_breaths, amalgamy, 2.1, MAXIMUM_ATTRIBUTE) boosted_amalgamy = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_TENTACLED_ENTREPRENEUR.name, 'boosted amalgamy'))
model.AddApproximateExponentiationEquality(boosted_amalgamy, amalgamy, 2.1, MAXIMUM_ATTRIBUTE)
model.Add(final_breaths == 4*boosted_amalgamy).OnlyEnforceIf(actions[Buyer.A_TENTACLED_ENTREPRENEUR])
del boosted_amalgamy
else: else:
model.Add(final_breaths == amalgamy_squared).OnlyEnforceIf(actions[Buyer.A_TENTACLED_ENTREPRENEUR]) model.Add(final_breaths == 4*amalgamy_squared).OnlyEnforceIf(actions[Buyer.A_TENTACLED_ENTREPRENEUR])
total_value = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_TENTACLED_ENTREPRENEUR.name, 'total value')) total_value = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_TENTACLED_ENTREPRENEUR.name, 'total value'))
model.Add(total_value == value + zoological_mania_bonus) model.Add(total_value == value + zoological_mania_bonus)
@ -808,7 +824,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
# The indirection is necessary for applying an enforcement literal # The indirection is necessary for applying an enforcement literal
derived_exhaustion = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_TENTACLED_ENTREPRENEUR.name, 'derived exhaustion')) derived_exhaustion = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_TENTACLED_ENTREPRENEUR.name, 'derived exhaustion'))
model.AddDivisionEquality(derived_exhaustion, amalgamy_squared, 100) model.AddDivisionEquality(derived_exhaustion, amalgamy_squared, 25)
model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.A_TENTACLED_ENTREPRENEUR]) model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.A_TENTACLED_ENTREPRENEUR])
del amalgamy_squared, final_breaths, total_value, total_value_remainder, derived_exhaustion del amalgamy_squared, final_breaths, total_value, total_value_remainder, derived_exhaustion