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Bone-Market-Solver
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Use f-strings and multiline strings 

Inline string expressions are far easier to read, particularly for
complicated strings like the skeleton printer's output.

Care has been taken to ensure that no behavior has been changed in the
process.
This commit is contained in:
Jeremy Saklad 2021-09-18 19:55:22 -05:00
parent 807c3d834c
commit 5ef972295b
Signed by: Jeremy Saklad
GPG Key ID: 9CA2149583EDBF84
2 changed files with 141 additions and 138 deletions
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6
bonemarketsolver/objects/listaction.py
View File

@ -39,9 +39,11 @@ class ListAction(argparse.Action):
@staticmethod @staticmethod
def printable_list(enum): def printable_list(enum):
def printable_item(member): def printable_item(member):
return f"\n\t{enum.__name__}.{member.name}:\n\t\t{member}" return f"""
{enum.__name__}.{member.name}:
{member}"""
return "{}:{}".format(enum.__name__, str().join([printable_item(member) for member in enum])) return f"{enum.__name__}:{str().join([printable_item(member) for member in enum])}"
def __call__(self, parser, namespace, values, option_string=None): def __call__(self, parser, namespace, values, option_string=None):
# Check whether this is a single value or a list of them # Check whether this is a single value or a list of them

273
bonemarketsolver/solve.py
View File

@ -61,7 +61,7 @@ def AddGeneralMultiplicationEquality(self, target, *variables):
def function(a, b): def function(a, b):
nonlocal term_index nonlocal term_index
intermediate = self.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{} term {}'.format(target.Name(), term_index)) intermediate = self.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{target.Name()} term {term_index}')
term_index += 1 term_index += 1
self.AddMultiplicationEquality(intermediate, [a, b]) self.AddMultiplicationEquality(intermediate, [a, b])
return intermediate return intermediate
@ -581,10 +581,10 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
# A Naive Collector # A Naive Collector
model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.A_NAIVE_COLLECTOR]) model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.A_NAIVE_COLLECTOR])
total_value = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_NAIVE_COLLECTOR.name, 'total value')) total_value = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.A_NAIVE_COLLECTOR.name}: total value')
model.Add(total_value == value + zoological_mania_bonus) model.Add(total_value == value + zoological_mania_bonus)
total_value_remainder = model.NewIntVar(0, 249, '{}: {}'.format(Buyer.A_NAIVE_COLLECTOR.name, 'total value remainder')) total_value_remainder = model.NewIntVar(0, 249, f'{Buyer.A_NAIVE_COLLECTOR.name}: total value remainder')
model.AddModuloEquality(total_value_remainder, total_value, 250) model.AddModuloEquality(total_value_remainder, total_value, 250)
model.Add(primary_revenue == total_value - total_value_remainder).OnlyEnforceIf(actions[Buyer.A_NAIVE_COLLECTOR]) model.Add(primary_revenue == total_value - total_value_remainder).OnlyEnforceIf(actions[Buyer.A_NAIVE_COLLECTOR])
@ -601,10 +601,10 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.A_FAMILIAR_BOHEMIAN_SCULPTRESS]) model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.A_FAMILIAR_BOHEMIAN_SCULPTRESS])
model.Add(antiquity <= 0).OnlyEnforceIf(actions[Buyer.A_FAMILIAR_BOHEMIAN_SCULPTRESS]) model.Add(antiquity <= 0).OnlyEnforceIf(actions[Buyer.A_FAMILIAR_BOHEMIAN_SCULPTRESS])
total_value = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_FAMILIAR_BOHEMIAN_SCULPTRESS.name, 'total value')) total_value = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.A_FAMILIAR_BOHEMIAN_SCULPTRESS.name}: total value')
model.Add(total_value == value + zoological_mania_bonus) model.Add(total_value == value + zoological_mania_bonus)
total_value_remainder = model.NewIntVar(0, 249, '{}: {}'.format(Buyer.A_FAMILIAR_BOHEMIAN_SCULPTRESS.name, 'total value remainder')) total_value_remainder = model.NewIntVar(0, 249, f'{Buyer.A_FAMILIAR_BOHEMIAN_SCULPTRESS.name}: total value remainder')
model.AddModuloEquality(total_value_remainder, total_value, 250) model.AddModuloEquality(total_value_remainder, total_value, 250)
model.Add(primary_revenue == total_value - total_value_remainder + 1000).OnlyEnforceIf(actions[Buyer.A_FAMILIAR_BOHEMIAN_SCULPTRESS]) model.Add(primary_revenue == total_value - total_value_remainder + 1000).OnlyEnforceIf(actions[Buyer.A_FAMILIAR_BOHEMIAN_SCULPTRESS])
@ -621,10 +621,10 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.A_PEDAGOGICALLY_INCLINED_GRANDMOTHER]) model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.A_PEDAGOGICALLY_INCLINED_GRANDMOTHER])
model.Add(menace <= 0).OnlyEnforceIf(actions[Buyer.A_PEDAGOGICALLY_INCLINED_GRANDMOTHER]) model.Add(menace <= 0).OnlyEnforceIf(actions[Buyer.A_PEDAGOGICALLY_INCLINED_GRANDMOTHER])
total_value = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_PEDAGOGICALLY_INCLINED_GRANDMOTHER.name, 'total value')) total_value = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.A_PEDAGOGICALLY_INCLINED_GRANDMOTHER.name}: total value')
model.Add(total_value == value + zoological_mania_bonus) model.Add(total_value == value + zoological_mania_bonus)
total_value_remainder = model.NewIntVar(0, 49, '{}: {}'.format(Buyer.A_PEDAGOGICALLY_INCLINED_GRANDMOTHER.name, 'total value remainder')) total_value_remainder = model.NewIntVar(0, 49, f'{Buyer.A_PEDAGOGICALLY_INCLINED_GRANDMOTHER.name}: total value remainder')
model.AddModuloEquality(total_value_remainder, total_value, 50) model.AddModuloEquality(total_value_remainder, total_value, 50)
model.Add(primary_revenue == total_value - total_value_remainder + 1000).OnlyEnforceIf(actions[Buyer.A_PEDAGOGICALLY_INCLINED_GRANDMOTHER]) model.Add(primary_revenue == total_value - total_value_remainder + 1000).OnlyEnforceIf(actions[Buyer.A_PEDAGOGICALLY_INCLINED_GRANDMOTHER])
@ -641,10 +641,10 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.A_THEOLOGIAN_OF_THE_OLD_SCHOOL]) model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.A_THEOLOGIAN_OF_THE_OLD_SCHOOL])
model.Add(amalgamy <= 0).OnlyEnforceIf(actions[Buyer.A_THEOLOGIAN_OF_THE_OLD_SCHOOL]) model.Add(amalgamy <= 0).OnlyEnforceIf(actions[Buyer.A_THEOLOGIAN_OF_THE_OLD_SCHOOL])
total_value = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_THEOLOGIAN_OF_THE_OLD_SCHOOL.name, 'total value')) total_value = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.A_THEOLOGIAN_OF_THE_OLD_SCHOOL.name}: total value')
model.Add(total_value == value + zoological_mania_bonus) model.Add(total_value == value + zoological_mania_bonus)
total_value_remainder = model.NewIntVar(0, 249, '{}: {}'.format(Buyer.A_THEOLOGIAN_OF_THE_OLD_SCHOOL.name, 'total value remainder')) total_value_remainder = model.NewIntVar(0, 249, f'{Buyer.A_THEOLOGIAN_OF_THE_OLD_SCHOOL.name}: total value remainder')
model.AddModuloEquality(total_value_remainder, total_value, 250) model.AddModuloEquality(total_value_remainder, total_value, 250)
model.Add(primary_revenue == total_value - total_value_remainder + 1000).OnlyEnforceIf(actions[Buyer.A_THEOLOGIAN_OF_THE_OLD_SCHOOL]) model.Add(primary_revenue == total_value - total_value_remainder + 1000).OnlyEnforceIf(actions[Buyer.A_THEOLOGIAN_OF_THE_OLD_SCHOOL])
@ -661,10 +661,10 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.AN_ENTHUSIAST_OF_THE_ANCIENT_WORLD]) model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.AN_ENTHUSIAST_OF_THE_ANCIENT_WORLD])
model.Add(antiquity > 0).OnlyEnforceIf(actions[Buyer.AN_ENTHUSIAST_OF_THE_ANCIENT_WORLD]) model.Add(antiquity > 0).OnlyEnforceIf(actions[Buyer.AN_ENTHUSIAST_OF_THE_ANCIENT_WORLD])
total_value = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_PEDAGOGICALLY_INCLINED_GRANDMOTHER.name, 'total value')) total_value = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.A_PEDAGOGICALLY_INCLINED_GRANDMOTHER.name}: total value')
model.Add(total_value == value + zoological_mania_bonus) model.Add(total_value == value + zoological_mania_bonus)
total_value_remainder = model.NewIntVar(0, 49, '{}: {}'.format(Buyer.AN_ENTHUSIAST_OF_THE_ANCIENT_WORLD.name, 'total value remainder')) total_value_remainder = model.NewIntVar(0, 49, f'{Buyer.AN_ENTHUSIAST_OF_THE_ANCIENT_WORLD.name}: total value remainder')
model.AddModuloEquality(total_value_remainder, total_value, 50) model.AddModuloEquality(total_value_remainder, total_value, 50)
model.Add(primary_revenue == total_value - total_value_remainder).OnlyEnforceIf(actions[Buyer.AN_ENTHUSIAST_OF_THE_ANCIENT_WORLD]) model.Add(primary_revenue == total_value - total_value_remainder).OnlyEnforceIf(actions[Buyer.AN_ENTHUSIAST_OF_THE_ANCIENT_WORLD])
@ -681,10 +681,10 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.MRS_PLENTY]) model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.MRS_PLENTY])
model.Add(menace > 0).OnlyEnforceIf(actions[Buyer.MRS_PLENTY]) model.Add(menace > 0).OnlyEnforceIf(actions[Buyer.MRS_PLENTY])
total_value = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.MRS_PLENTY.name, 'total value')) total_value = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.MRS_PLENTY.name}: total value')
model.Add(total_value == value + zoological_mania_bonus) model.Add(total_value == value + zoological_mania_bonus)
total_value_remainder = model.NewIntVar(0, 49, '{}: {}'.format(Buyer.MRS_PLENTY.name, 'total value remainder')) total_value_remainder = model.NewIntVar(0, 49, f'{Buyer.MRS_PLENTY.name}: total value remainder')
model.AddModuloEquality(total_value_remainder, total_value, 50) model.AddModuloEquality(total_value_remainder, total_value, 50)
model.Add(primary_revenue == total_value - total_value_remainder).OnlyEnforceIf(actions[Buyer.MRS_PLENTY]) model.Add(primary_revenue == total_value - total_value_remainder).OnlyEnforceIf(actions[Buyer.MRS_PLENTY])
@ -701,10 +701,10 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.A_TENTACLED_SERVANT]) model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.A_TENTACLED_SERVANT])
model.Add(amalgamy > 0).OnlyEnforceIf(actions[Buyer.A_TENTACLED_SERVANT]) model.Add(amalgamy > 0).OnlyEnforceIf(actions[Buyer.A_TENTACLED_SERVANT])
total_value = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_TENTACLED_SERVANT.name, 'total value')) total_value = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.A_TENTACLED_SERVANT.name}: total value')
model.Add(total_value == value + zoological_mania_bonus) model.Add(total_value == value + zoological_mania_bonus)
total_value_remainder = model.NewIntVar(0, 49, '{}: {}'.format(Buyer.A_TENTACLED_SERVANT.name, 'total value remainder')) total_value_remainder = model.NewIntVar(0, 49, f'{Buyer.A_TENTACLED_SERVANT.name}: total value remainder')
model.AddModuloEquality(total_value_remainder, total_value, 50) model.AddModuloEquality(total_value_remainder, total_value, 50)
model.Add(primary_revenue == total_value - total_value_remainder + 250).OnlyEnforceIf(actions[Buyer.A_TENTACLED_SERVANT]) model.Add(primary_revenue == total_value - total_value_remainder + 250).OnlyEnforceIf(actions[Buyer.A_TENTACLED_SERVANT])
@ -721,31 +721,31 @@ 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_times_four_fifths = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name, 'antiquity squared times four-fifths')) antiquity_squared_times_four_fifths = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name}: antiquity squared times four-fifths')
antiquity_squared_times_four = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name, 'antiquity squared times four')) antiquity_squared_times_four = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name}: antiquity squared times four')
model.AddGeneralMultiplicationEquality(antiquity_squared_times_four, antiquity, antiquity, 4) model.AddGeneralMultiplicationEquality(antiquity_squared_times_four, antiquity, antiquity, 4)
model.AddDivisionEquality(antiquity_squared_times_four_fifths, antiquity_squared_times_four, 5) model.AddDivisionEquality(antiquity_squared_times_four_fifths, antiquity_squared_times_four, 5)
del antiquity_squared_times_four 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, f'{Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name}: tailfeathers')
if bone_market_fluctuations == Fluctuation.ANTIQUITY: if bone_market_fluctuations == Fluctuation.ANTIQUITY:
boosted_antiquity = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name, 'boosted antiquity')) boosted_antiquity = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name}: boosted antiquity')
model.AddApproximateExponentiationEquality(boosted_antiquity, antiquity, 2.1, MAXIMUM_ATTRIBUTE) 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')) boosted_antiquity_times_four = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name}: boosted antiquity times four')
model.AddMultiplicationEquality(boosted_antiquity_times_four, [boosted_antiquity, 4]) 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')) boosted_antiquity_times_four_fifths = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name}: boosted antiquity times four-fifths')
model.AddDivisionEquality(boosted_antiquity_times_four_fifths, boosted_antiquity_times_four, 5) 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]) 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 del boosted_antiquity, boosted_antiquity_times_four, boosted_antiquity_times_four_fifths
else: else:
model.Add(tailfeathers == antiquity_squared_times_four_fifths).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, f'{Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name}: total value')
model.Add(total_value == value + zoological_mania_bonus) model.Add(total_value == value + zoological_mania_bonus)
total_value_remainder = model.NewIntVar(0, 49, '{}: {}'.format(Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name, 'total value remainder')) total_value_remainder = model.NewIntVar(0, 49, f'{Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name}: total value remainder')
model.AddModuloEquality(total_value_remainder, total_value, 50) model.AddModuloEquality(total_value_remainder, total_value, 50)
extra_value = model.NewIntermediateBoolVar('{}: {}'.format(Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name, 'extra value'), total_value_remainder, cp_model.Domain.FromFlatIntervals([0, cp_model.INT_MAX])) extra_value = model.NewIntermediateBoolVar(f'{Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name}: extra value', total_value_remainder, cp_model.Domain.FromFlatIntervals([0, cp_model.INT_MAX]))
model.Add(primary_revenue == total_value + 50*extra_value + 250).OnlyEnforceIf(actions[Buyer.AN_INVESTMENT_MINDED_AMBASSADOR]) model.Add(primary_revenue == total_value + 50*extra_value + 250).OnlyEnforceIf(actions[Buyer.AN_INVESTMENT_MINDED_AMBASSADOR])
model.Add(secondary_revenue == 250*tailfeathers).OnlyEnforceIf(actions[Buyer.AN_INVESTMENT_MINDED_AMBASSADOR]) model.Add(secondary_revenue == 250*tailfeathers).OnlyEnforceIf(actions[Buyer.AN_INVESTMENT_MINDED_AMBASSADOR])
@ -753,7 +753,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(difficulty_level == 75*implausibility).OnlyEnforceIf(actions[Buyer.AN_INVESTMENT_MINDED_AMBASSADOR]) model.Add(difficulty_level == 75*implausibility).OnlyEnforceIf(actions[Buyer.AN_INVESTMENT_MINDED_AMBASSADOR])
# 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, f'{Buyer.AN_INVESTMENT_MINDED_AMBASSADOR.name}: derived exhaustion')
model.AddDivisionEquality(derived_exhaustion, antiquity_squared_times_four_fifths, 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])
@ -764,22 +764,22 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.A_TELLER_OF_TERRORS]) model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.A_TELLER_OF_TERRORS])
model.Add(menace > 0).OnlyEnforceIf(actions[Buyer.A_TELLER_OF_TERRORS]) model.Add(menace > 0).OnlyEnforceIf(actions[Buyer.A_TELLER_OF_TERRORS])
menace_squared = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_TELLER_OF_TERRORS.name, 'menace squared')) menace_squared = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.A_TELLER_OF_TERRORS.name}: menace squared')
model.AddMultiplicationEquality(menace_squared, [menace, menace]) model.AddMultiplicationEquality(menace_squared, [menace, menace])
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, f'{Buyer.A_TELLER_OF_TERRORS.name}: feathers')
if bone_market_fluctuations == Fluctuation.MENACE: if bone_market_fluctuations == Fluctuation.MENACE:
boosted_menace = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_TELLER_OF_TERRORS.name, 'boosted menace')) boosted_menace = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.A_TELLER_OF_TERRORS.name}: boosted menace')
model.AddApproximateExponentiationEquality(boosted_menace, menace, 2.1, MAXIMUM_ATTRIBUTE) model.AddApproximateExponentiationEquality(boosted_menace, menace, 2.1, MAXIMUM_ATTRIBUTE)
model.Add(feathers == 4*boosted_menace).OnlyEnforceIf(actions[Buyer.A_TELLER_OF_TERRORS]) model.Add(feathers == 4*boosted_menace).OnlyEnforceIf(actions[Buyer.A_TELLER_OF_TERRORS])
del boosted_menace del boosted_menace
else: else:
model.Add(feathers == 4*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, f'{Buyer.A_TELLER_OF_TERRORS.name}: total value')
model.Add(total_value == value + zoological_mania_bonus) model.Add(total_value == value + zoological_mania_bonus)
total_value_remainder = model.NewIntVar(0, 9, '{}: {}'.format(Buyer.A_TELLER_OF_TERRORS.name, 'total value remainder')) total_value_remainder = model.NewIntVar(0, 9, f'{Buyer.A_TELLER_OF_TERRORS.name}: total value remainder')
model.AddModuloEquality(total_value_remainder, total_value, 10) model.AddModuloEquality(total_value_remainder, total_value, 10)
model.Add(primary_revenue == total_value - total_value_remainder + 50).OnlyEnforceIf(actions[Buyer.A_TELLER_OF_TERRORS]) model.Add(primary_revenue == total_value - total_value_remainder + 50).OnlyEnforceIf(actions[Buyer.A_TELLER_OF_TERRORS])
@ -788,7 +788,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(difficulty_level == 75*implausibility).OnlyEnforceIf(actions[Buyer.A_TELLER_OF_TERRORS]) model.Add(difficulty_level == 75*implausibility).OnlyEnforceIf(actions[Buyer.A_TELLER_OF_TERRORS])
# 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, f'{Buyer.A_TELLER_OF_TERRORS.name}: derived exhaustion')
model.AddDivisionEquality(derived_exhaustion, menace_squared, 25) 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])
@ -799,22 +799,22 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.A_TENTACLED_ENTREPRENEUR]) model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.A_TENTACLED_ENTREPRENEUR])
model.Add(amalgamy > 0).OnlyEnforceIf(actions[Buyer.A_TENTACLED_ENTREPRENEUR]) model.Add(amalgamy > 0).OnlyEnforceIf(actions[Buyer.A_TENTACLED_ENTREPRENEUR])
amalgamy_squared = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_TENTACLED_ENTREPRENEUR.name, 'amalgamy squared')) amalgamy_squared = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.A_TENTACLED_ENTREPRENEUR.name}: amalgamy squared')
model.AddMultiplicationEquality(amalgamy_squared, [amalgamy, amalgamy]) model.AddMultiplicationEquality(amalgamy_squared, [amalgamy, amalgamy])
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, f'{Buyer.A_TENTACLED_ENTREPRENEUR.name}: final breaths')
if bone_market_fluctuations == Fluctuation.AMALGAMY: if bone_market_fluctuations == Fluctuation.AMALGAMY:
boosted_amalgamy = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_TENTACLED_ENTREPRENEUR.name, 'boosted amalgamy')) boosted_amalgamy = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.A_TENTACLED_ENTREPRENEUR.name}: boosted amalgamy')
model.AddApproximateExponentiationEquality(boosted_amalgamy, amalgamy, 2.1, MAXIMUM_ATTRIBUTE) model.AddApproximateExponentiationEquality(boosted_amalgamy, amalgamy, 2.1, MAXIMUM_ATTRIBUTE)
model.Add(final_breaths == 4*boosted_amalgamy).OnlyEnforceIf(actions[Buyer.A_TENTACLED_ENTREPRENEUR]) model.Add(final_breaths == 4*boosted_amalgamy).OnlyEnforceIf(actions[Buyer.A_TENTACLED_ENTREPRENEUR])
del boosted_amalgamy del boosted_amalgamy
else: else:
model.Add(final_breaths == 4*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, f'{Buyer.A_TENTACLED_ENTREPRENEUR.name}: total value')
model.Add(total_value == value + zoological_mania_bonus) model.Add(total_value == value + zoological_mania_bonus)
total_value_remainder = model.NewIntVar(0, 49, '{}: {}'.format(Buyer.A_TENTACLED_ENTREPRENEUR.name, 'total value remainder')) total_value_remainder = model.NewIntVar(0, 49, f'{Buyer.A_TENTACLED_ENTREPRENEUR.name}: total value remainder')
model.AddModuloEquality(total_value_remainder, total_value, 50) model.AddModuloEquality(total_value_remainder, total_value, 50)
model.Add(primary_revenue == total_value - total_value_remainder + 250).OnlyEnforceIf(actions[Buyer.A_TENTACLED_ENTREPRENEUR]) model.Add(primary_revenue == total_value - total_value_remainder + 250).OnlyEnforceIf(actions[Buyer.A_TENTACLED_ENTREPRENEUR])
@ -823,7 +823,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(difficulty_level == 75*implausibility).OnlyEnforceIf(actions[Buyer.A_TENTACLED_ENTREPRENEUR]) model.Add(difficulty_level == 75*implausibility).OnlyEnforceIf(actions[Buyer.A_TENTACLED_ENTREPRENEUR])
# 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, f'{Buyer.A_TENTACLED_ENTREPRENEUR.name}: derived exhaustion')
model.AddDivisionEquality(derived_exhaustion, amalgamy_squared, 25) 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])
@ -835,19 +835,19 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(antiquity > 0).OnlyEnforceIf(actions[Buyer.AN_AUTHOR_OF_GOTHIC_TALES]) model.Add(antiquity > 0).OnlyEnforceIf(actions[Buyer.AN_AUTHOR_OF_GOTHIC_TALES])
model.Add(menace > 0).OnlyEnforceIf(actions[Buyer.AN_AUTHOR_OF_GOTHIC_TALES]) model.Add(menace > 0).OnlyEnforceIf(actions[Buyer.AN_AUTHOR_OF_GOTHIC_TALES])
antiquity_times_menace = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_AUTHOR_OF_GOTHIC_TALES.name, 'antiquity times menace')) antiquity_times_menace = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.AN_AUTHOR_OF_GOTHIC_TALES.name}: antiquity times menace')
model.AddMultiplicationEquality(antiquity_times_menace, [antiquity, menace]) model.AddMultiplicationEquality(antiquity_times_menace, [antiquity, menace])
antiquity_fluctuation_bonus = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_AUTHOR_OF_GOTHIC_TALES.name, 'antiquity fluctuation bonus')) antiquity_fluctuation_bonus = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.AN_AUTHOR_OF_GOTHIC_TALES.name}: antiquity fluctuation bonus')
model.AddDivisionEquality(antiquity_fluctuation_bonus, antiquity, 2) model.AddDivisionEquality(antiquity_fluctuation_bonus, antiquity, 2)
menace_fluctuation_bonus = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_AUTHOR_OF_GOTHIC_TALES.name, 'menace fluctuation bonus')) menace_fluctuation_bonus = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.AN_AUTHOR_OF_GOTHIC_TALES.name}: menace fluctuation bonus')
model.AddDivisionEquality(menace_fluctuation_bonus, menace, 2) model.AddDivisionEquality(menace_fluctuation_bonus, menace, 2)
total_value = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_AUTHOR_OF_GOTHIC_TALES.name, 'total value')) total_value = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.AN_AUTHOR_OF_GOTHIC_TALES.name}: total value')
model.Add(total_value == value + zoological_mania_bonus) model.Add(total_value == value + zoological_mania_bonus)
total_value_remainder = model.NewIntVar(0, 49, '{}: {}'.format(Buyer.AN_AUTHOR_OF_GOTHIC_TALES.name, 'total value remainder')) total_value_remainder = model.NewIntVar(0, 49, f'{Buyer.AN_AUTHOR_OF_GOTHIC_TALES.name}: total value remainder')
model.AddModuloEquality(total_value_remainder, total_value, 50) model.AddModuloEquality(total_value_remainder, total_value, 50)
model.Add(primary_revenue == total_value - total_value_remainder + 250).OnlyEnforceIf(actions[Buyer.AN_AUTHOR_OF_GOTHIC_TALES]) model.Add(primary_revenue == total_value - total_value_remainder + 250).OnlyEnforceIf(actions[Buyer.AN_AUTHOR_OF_GOTHIC_TALES])
@ -856,7 +856,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(difficulty_level == 75*implausibility).OnlyEnforceIf(actions[Buyer.AN_AUTHOR_OF_GOTHIC_TALES]) model.Add(difficulty_level == 75*implausibility).OnlyEnforceIf(actions[Buyer.AN_AUTHOR_OF_GOTHIC_TALES])
# The indirection is necessary for applying an enforcement literal # The indirection is necessary for applying an enforcement literal
derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_AUTHOR_OF_GOTHIC_TALES.name, 'derived exhaustion')) derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.AN_AUTHOR_OF_GOTHIC_TALES.name}: derived exhaustion')
model.AddDivisionEquality(derived_exhaustion, antiquity_times_menace, 20) model.AddDivisionEquality(derived_exhaustion, antiquity_times_menace, 20)
model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.AN_AUTHOR_OF_GOTHIC_TALES]) model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.AN_AUTHOR_OF_GOTHIC_TALES])
@ -868,19 +868,19 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(antiquity > 0).OnlyEnforceIf(actions[Buyer.A_ZAILOR_WITH_PARTICULAR_INTERESTS]) model.Add(antiquity > 0).OnlyEnforceIf(actions[Buyer.A_ZAILOR_WITH_PARTICULAR_INTERESTS])
model.Add(amalgamy > 0).OnlyEnforceIf(actions[Buyer.A_ZAILOR_WITH_PARTICULAR_INTERESTS]) model.Add(amalgamy > 0).OnlyEnforceIf(actions[Buyer.A_ZAILOR_WITH_PARTICULAR_INTERESTS])
amalgamy_times_antiquity = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_ZAILOR_WITH_PARTICULAR_INTERESTS.name, 'amalgamy times antiquity')) amalgamy_times_antiquity = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.A_ZAILOR_WITH_PARTICULAR_INTERESTS.name}: amalgamy times antiquity')
model.AddMultiplicationEquality(amalgamy_times_antiquity, [amalgamy, antiquity]) model.AddMultiplicationEquality(amalgamy_times_antiquity, [amalgamy, antiquity])
amalgamy_fluctuation_bonus = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_ZAILOR_WITH_PARTICULAR_INTERESTS.name, 'amalgamy fluctuation bonus')) amalgamy_fluctuation_bonus = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.A_ZAILOR_WITH_PARTICULAR_INTERESTS.name}: amalgamy fluctuation bonus')
model.AddDivisionEquality(amalgamy_fluctuation_bonus, amalgamy, 2) model.AddDivisionEquality(amalgamy_fluctuation_bonus, amalgamy, 2)
antiquity_fluctuation_bonus = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_ZAILOR_WITH_PARTICULAR_INTERESTS.name, 'antiquity fluctuation bonus')) antiquity_fluctuation_bonus = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.A_ZAILOR_WITH_PARTICULAR_INTERESTS.name}: antiquity fluctuation bonus')
model.AddDivisionEquality(antiquity_fluctuation_bonus, antiquity, 2) model.AddDivisionEquality(antiquity_fluctuation_bonus, antiquity, 2)
total_value = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_ZAILOR_WITH_PARTICULAR_INTERESTS.name, 'total value')) total_value = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.A_ZAILOR_WITH_PARTICULAR_INTERESTS.name}: total value')
model.Add(total_value == value + zoological_mania_bonus) model.Add(total_value == value + zoological_mania_bonus)
total_value_remainder = model.NewIntVar(0, 9, '{}: {}'.format(Buyer.A_ZAILOR_WITH_PARTICULAR_INTERESTS.name, 'total value remainder')) total_value_remainder = model.NewIntVar(0, 9, f'{Buyer.A_ZAILOR_WITH_PARTICULAR_INTERESTS.name}: total value remainder')
model.AddModuloEquality(total_value_remainder, total_value, 10) model.AddModuloEquality(total_value_remainder, total_value, 10)
model.Add(primary_revenue == total_value - total_value_remainder + 250).OnlyEnforceIf(actions[Buyer.A_ZAILOR_WITH_PARTICULAR_INTERESTS]) model.Add(primary_revenue == total_value - total_value_remainder + 250).OnlyEnforceIf(actions[Buyer.A_ZAILOR_WITH_PARTICULAR_INTERESTS])
@ -889,7 +889,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(difficulty_level == 75*implausibility).OnlyEnforceIf(actions[Buyer.A_ZAILOR_WITH_PARTICULAR_INTERESTS]) model.Add(difficulty_level == 75*implausibility).OnlyEnforceIf(actions[Buyer.A_ZAILOR_WITH_PARTICULAR_INTERESTS])
# The indirection is necessary for applying an enforcement literal # The indirection is necessary for applying an enforcement literal
derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_ZAILOR_WITH_PARTICULAR_INTERESTS.name, 'derived exhaustion')) derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.A_ZAILOR_WITH_PARTICULAR_INTERESTS.name}: derived exhaustion')
model.AddDivisionEquality(derived_exhaustion, amalgamy_times_antiquity, 20) model.AddDivisionEquality(derived_exhaustion, amalgamy_times_antiquity, 20)
model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.A_ZAILOR_WITH_PARTICULAR_INTERESTS]) model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.A_ZAILOR_WITH_PARTICULAR_INTERESTS])
@ -901,19 +901,19 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(amalgamy > 0).OnlyEnforceIf(actions[Buyer.A_RUBBERY_COLLECTOR]) model.Add(amalgamy > 0).OnlyEnforceIf(actions[Buyer.A_RUBBERY_COLLECTOR])
model.Add(menace > 0).OnlyEnforceIf(actions[Buyer.A_RUBBERY_COLLECTOR]) model.Add(menace > 0).OnlyEnforceIf(actions[Buyer.A_RUBBERY_COLLECTOR])
amalgamy_times_menace = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_RUBBERY_COLLECTOR.name, 'amalgamy times menace')) amalgamy_times_menace = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.A_RUBBERY_COLLECTOR.name}: amalgamy times menace')
model.AddMultiplicationEquality(amalgamy_times_menace, [amalgamy, menace]) model.AddMultiplicationEquality(amalgamy_times_menace, [amalgamy, menace])
amalgamy_fluctuation_bonus = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_RUBBERY_COLLECTOR.name, 'amalgamy fluctuation bonus')) amalgamy_fluctuation_bonus = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.A_RUBBERY_COLLECTOR.name}: amalgamy fluctuation bonus')
model.AddDivisionEquality(amalgamy_fluctuation_bonus, amalgamy, 2) model.AddDivisionEquality(amalgamy_fluctuation_bonus, amalgamy, 2)
menace_fluctuation_bonus = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_RUBBERY_COLLECTOR.name, 'menace fluctuation bonus')) menace_fluctuation_bonus = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.A_RUBBERY_COLLECTOR.name}: menace fluctuation bonus')
model.AddDivisionEquality(menace_fluctuation_bonus, menace, 2) model.AddDivisionEquality(menace_fluctuation_bonus, menace, 2)
total_value = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_RUBBERY_COLLECTOR.name, 'total value')) total_value = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.A_RUBBERY_COLLECTOR.name}: total value')
model.Add(total_value == value + zoological_mania_bonus) model.Add(total_value == value + zoological_mania_bonus)
total_value_remainder = model.NewIntVar(0, 49, '{}: {}'.format(Buyer.A_RUBBERY_COLLECTOR.name, 'total value remainder')) total_value_remainder = model.NewIntVar(0, 49, f'{Buyer.A_RUBBERY_COLLECTOR.name}: total value remainder')
model.AddModuloEquality(total_value_remainder, total_value, 50) model.AddModuloEquality(total_value_remainder, total_value, 50)
model.Add(primary_revenue == total_value - total_value_remainder + 250).OnlyEnforceIf(actions[Buyer.A_RUBBERY_COLLECTOR]) model.Add(primary_revenue == total_value - total_value_remainder + 250).OnlyEnforceIf(actions[Buyer.A_RUBBERY_COLLECTOR])
@ -922,7 +922,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(difficulty_level == 75*implausibility).OnlyEnforceIf(actions[Buyer.A_RUBBERY_COLLECTOR]) model.Add(difficulty_level == 75*implausibility).OnlyEnforceIf(actions[Buyer.A_RUBBERY_COLLECTOR])
# The indirection is necessary for applying an enforcement literal # The indirection is necessary for applying an enforcement literal
derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_RUBBERY_COLLECTOR.name, 'derived exhaustion')) derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.A_RUBBERY_COLLECTOR.name}: derived exhaustion')
model.AddDivisionEquality(derived_exhaustion, amalgamy_times_menace, 20) model.AddDivisionEquality(derived_exhaustion, amalgamy_times_menace, 20)
model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.A_RUBBERY_COLLECTOR]) model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.A_RUBBERY_COLLECTOR])
@ -932,7 +932,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
# A Constable # A Constable
model.AddLinearExpressionInDomain(skeleton_in_progress, cp_model.Domain.FromFlatIntervals([110, 119])).OnlyEnforceIf(actions[Buyer.A_CONSTABLE]) model.AddLinearExpressionInDomain(skeleton_in_progress, cp_model.Domain.FromFlatIntervals([110, 119])).OnlyEnforceIf(actions[Buyer.A_CONSTABLE])
value_remainder = model.NewIntVar(0, 49, '{}: {}'.format(Buyer.A_CONSTABLE.name, 'value remainder')) value_remainder = model.NewIntVar(0, 49, f'{Buyer.A_CONSTABLE.name}: value remainder')
model.AddModuloEquality(value_remainder, value, 50) model.AddModuloEquality(value_remainder, value, 50)
model.Add(primary_revenue == value - value_remainder + 1000).OnlyEnforceIf(actions[Buyer.A_CONSTABLE]) model.Add(primary_revenue == value - value_remainder + 1000).OnlyEnforceIf(actions[Buyer.A_CONSTABLE])
@ -949,9 +949,9 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.AN_ENTHUSIAST_IN_SKULLS]) model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.AN_ENTHUSIAST_IN_SKULLS])
model.Add(skulls >= 2).OnlyEnforceIf(actions[Buyer.AN_ENTHUSIAST_IN_SKULLS]) model.Add(skulls >= 2).OnlyEnforceIf(actions[Buyer.AN_ENTHUSIAST_IN_SKULLS])
extra_skulls = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_ENTHUSIAST_IN_SKULLS.name, 'extra skulls')) extra_skulls = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.AN_ENTHUSIAST_IN_SKULLS.name}: extra skulls')
model.Add(extra_skulls == skulls - 1).OnlyEnforceIf(actions[Buyer.AN_ENTHUSIAST_IN_SKULLS]) model.Add(extra_skulls == skulls - 1).OnlyEnforceIf(actions[Buyer.AN_ENTHUSIAST_IN_SKULLS])
vital_intelligence = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_ENTHUSIAST_IN_SKULLS.name, 'vital intelligence')) vital_intelligence = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.AN_ENTHUSIAST_IN_SKULLS.name}: vital intelligence')
model.AddApproximateExponentiationEquality(vital_intelligence, extra_skulls, 1.8, MAXIMUM_ATTRIBUTE) model.AddApproximateExponentiationEquality(vital_intelligence, extra_skulls, 1.8, MAXIMUM_ATTRIBUTE)
model.Add(primary_revenue == value + zoological_mania_bonus).OnlyEnforceIf(actions[Buyer.AN_ENTHUSIAST_IN_SKULLS]) model.Add(primary_revenue == value + zoological_mania_bonus).OnlyEnforceIf(actions[Buyer.AN_ENTHUSIAST_IN_SKULLS])
@ -960,7 +960,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(difficulty_level == 60*implausibility).OnlyEnforceIf(actions[Buyer.AN_ENTHUSIAST_IN_SKULLS]) model.Add(difficulty_level == 60*implausibility).OnlyEnforceIf(actions[Buyer.AN_ENTHUSIAST_IN_SKULLS])
# 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_ENTHUSIAST_IN_SKULLS.name, 'derived exhaustion')) derived_exhaustion = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.AN_ENTHUSIAST_IN_SKULLS.name}: derived exhaustion')
model.AddDivisionEquality(derived_exhaustion, vital_intelligence, 4) model.AddDivisionEquality(derived_exhaustion, vital_intelligence, 4)
model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.AN_ENTHUSIAST_IN_SKULLS]) model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.AN_ENTHUSIAST_IN_SKULLS])
@ -972,10 +972,10 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(amalgamy <= 0).OnlyEnforceIf(actions[Buyer.A_DREARY_MIDNIGHTER]) model.Add(amalgamy <= 0).OnlyEnforceIf(actions[Buyer.A_DREARY_MIDNIGHTER])
model.Add(counter_church <= 0).OnlyEnforceIf(actions[Buyer.A_DREARY_MIDNIGHTER]) model.Add(counter_church <= 0).OnlyEnforceIf(actions[Buyer.A_DREARY_MIDNIGHTER])
total_value = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_DREARY_MIDNIGHTER.name, 'total value')) total_value = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.A_DREARY_MIDNIGHTER.name}: total value')
model.Add(total_value == value + zoological_mania_bonus) model.Add(total_value == value + zoological_mania_bonus)
total_value_remainder = model.NewIntVar(0, 2, '{}: {}'.format(Buyer.A_DREARY_MIDNIGHTER.name, 'total value remainder')) total_value_remainder = model.NewIntVar(0, 2, f'{Buyer.A_DREARY_MIDNIGHTER.name}: total value remainder')
model.AddModuloEquality(total_value_remainder, total_value, 3) model.AddModuloEquality(total_value_remainder, total_value, 3)
model.Add(primary_revenue == total_value - total_value_remainder + 300).OnlyEnforceIf(actions[Buyer.A_DREARY_MIDNIGHTER]) model.Add(primary_revenue == total_value - total_value_remainder + 300).OnlyEnforceIf(actions[Buyer.A_DREARY_MIDNIGHTER])
@ -993,16 +993,16 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(implausibility >= 2).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_BAZAARINE]) model.Add(implausibility >= 2).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_BAZAARINE])
model.Add(amalgamy >= 4).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_BAZAARINE]) model.Add(amalgamy >= 4).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_BAZAARINE])
amalgamy_times_implausibility = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_COLOURFUL_PHANTASIST_BAZAARINE.name, 'amalgamy times implausibility')) amalgamy_times_implausibility = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.A_COLOURFUL_PHANTASIST_BAZAARINE.name}: amalgamy times implausibility')
model.AddMultiplicationEquality(amalgamy_times_implausibility, [amalgamy, implausibility]) model.AddMultiplicationEquality(amalgamy_times_implausibility, [amalgamy, implausibility])
bazaarine_poetry = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_COLOURFUL_PHANTASIST_BAZAARINE.name, 'bazaarine poetry')) bazaarine_poetry = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.A_COLOURFUL_PHANTASIST_BAZAARINE.name}: bazaarine poetry')
model.Add(bazaarine_poetry == amalgamy_times_implausibility + 1) model.Add(bazaarine_poetry == amalgamy_times_implausibility + 1)
total_value = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_COLOURFUL_PHANTASIST_BAZAARINE.name, 'total value')) total_value = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.A_COLOURFUL_PHANTASIST_BAZAARINE.name}: total value')
model.Add(total_value == value + zoological_mania_bonus) model.Add(total_value == value + zoological_mania_bonus)
total_value_remainder = model.NewIntVar(0, 49, '{}: {}'.format(Buyer.A_COLOURFUL_PHANTASIST_BAZAARINE.name, 'total value remainder')) total_value_remainder = model.NewIntVar(0, 49, f'{Buyer.A_COLOURFUL_PHANTASIST_BAZAARINE.name}: total value remainder')
model.AddModuloEquality(total_value_remainder, total_value, 50) model.AddModuloEquality(total_value_remainder, total_value, 50)
model.Add(primary_revenue == total_value - total_value_remainder + 100).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_BAZAARINE]) model.Add(primary_revenue == total_value - total_value_remainder + 100).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_BAZAARINE])
@ -1011,7 +1011,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(difficulty_level == 0).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_BAZAARINE]) model.Add(difficulty_level == 0).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_BAZAARINE])
# The indirection is necessary for applying an enforcement literal # The indirection is necessary for applying an enforcement literal
derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_COLOURFUL_PHANTASIST_BAZAARINE.name, 'derived exhaustion')) derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.A_COLOURFUL_PHANTASIST_BAZAARINE.name}: derived exhaustion')
model.AddDivisionEquality(derived_exhaustion, bazaarine_poetry, 20) model.AddDivisionEquality(derived_exhaustion, bazaarine_poetry, 20)
model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_BAZAARINE]) model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_BAZAARINE])
@ -1023,16 +1023,16 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(implausibility >= 2).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_NOCTURNAL]) model.Add(implausibility >= 2).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_NOCTURNAL])
model.Add(menace >= 4).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_NOCTURNAL]) model.Add(menace >= 4).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_NOCTURNAL])
menace_times_implausibility = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_COLOURFUL_PHANTASIST_NOCTURNAL.name, 'menace times implausibility')) menace_times_implausibility = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.A_COLOURFUL_PHANTASIST_NOCTURNAL.name}: menace times implausibility')
model.AddMultiplicationEquality(menace_times_implausibility, [menace, implausibility]) model.AddMultiplicationEquality(menace_times_implausibility, [menace, implausibility])
stygian_ivory = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_COLOURFUL_PHANTASIST_NOCTURNAL.name, 'stygian ivory')) stygian_ivory = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.A_COLOURFUL_PHANTASIST_NOCTURNAL.name}: stygian ivory')
model.Add(stygian_ivory == menace_times_implausibility + 1) model.Add(stygian_ivory == menace_times_implausibility + 1)
total_value = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_COLOURFUL_PHANTASIST_NOCTURNAL.name, 'total value')) total_value = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.A_COLOURFUL_PHANTASIST_NOCTURNAL.name}: total value')
model.Add(total_value == value + zoological_mania_bonus) model.Add(total_value == value + zoological_mania_bonus)
total_value_remainder = model.NewIntVar(0, 49, '{}: {}'.format(Buyer.A_COLOURFUL_PHANTASIST_NOCTURNAL.name, 'total value remainder')) total_value_remainder = model.NewIntVar(0, 49, f'{Buyer.A_COLOURFUL_PHANTASIST_NOCTURNAL.name}: total value remainder')
model.AddModuloEquality(total_value_remainder, total_value, 50) model.AddModuloEquality(total_value_remainder, total_value, 50)
model.Add(primary_revenue == total_value - total_value_remainder + 100).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_NOCTURNAL]) model.Add(primary_revenue == total_value - total_value_remainder + 100).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_NOCTURNAL])
@ -1041,7 +1041,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(difficulty_level == 0).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_NOCTURNAL]) model.Add(difficulty_level == 0).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_NOCTURNAL])
# The indirection is necessary for applying an enforcement literal # The indirection is necessary for applying an enforcement literal
derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_COLOURFUL_PHANTASIST_NOCTURNAL.name, 'derived exhaustion')) derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.A_COLOURFUL_PHANTASIST_NOCTURNAL.name}: derived exhaustion')
model.AddDivisionEquality(derived_exhaustion, stygian_ivory, 20) model.AddDivisionEquality(derived_exhaustion, stygian_ivory, 20)
model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_NOCTURNAL]) model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_NOCTURNAL])
@ -1053,16 +1053,16 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(implausibility >= 2).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_CELESTIAL]) model.Add(implausibility >= 2).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_CELESTIAL])
model.Add(antiquity >= 4).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_CELESTIAL]) model.Add(antiquity >= 4).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_CELESTIAL])
antiquity_times_implausibility = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_COLOURFUL_PHANTASIST_CELESTIAL.name, 'antiquity times implausibility')) antiquity_times_implausibility = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.A_COLOURFUL_PHANTASIST_CELESTIAL.name}: antiquity times implausibility')
model.AddMultiplicationEquality(antiquity_times_implausibility, [antiquity, implausibility]) model.AddMultiplicationEquality(antiquity_times_implausibility, [antiquity, implausibility])
knob_of_scintillack = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_COLOURFUL_PHANTASIST_CELESTIAL.name, 'knob of scintillack')) knob_of_scintillack = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.A_COLOURFUL_PHANTASIST_CELESTIAL.name}: knob of scintillack')
model.Add(knob_of_scintillack == antiquity_times_implausibility + 1) model.Add(knob_of_scintillack == antiquity_times_implausibility + 1)
total_value = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_COLOURFUL_PHANTASIST_CELESTIAL.name, 'total value')) total_value = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.A_COLOURFUL_PHANTASIST_CELESTIAL.name}: total value')
model.Add(total_value == value + zoological_mania_bonus) model.Add(total_value == value + zoological_mania_bonus)
total_value_remainder = model.NewIntVar(0, 49, '{}: {}'.format(Buyer.A_COLOURFUL_PHANTASIST_CELESTIAL.name, 'total value remainder')) total_value_remainder = model.NewIntVar(0, 49, f'{Buyer.A_COLOURFUL_PHANTASIST_CELESTIAL.name}: total value remainder')
model.AddModuloEquality(total_value_remainder, total_value, 50) model.AddModuloEquality(total_value_remainder, total_value, 50)
model.Add(primary_revenue == total_value - total_value_remainder + 100).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_CELESTIAL]) model.Add(primary_revenue == total_value - total_value_remainder + 100).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_CELESTIAL])
@ -1071,7 +1071,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(difficulty_level == 0).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_CELESTIAL]) model.Add(difficulty_level == 0).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_CELESTIAL])
# The indirection is necessary for applying an enforcement literal # The indirection is necessary for applying an enforcement literal
derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.A_COLOURFUL_PHANTASIST_CELESTIAL.name, 'derived exhaustion')) derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.A_COLOURFUL_PHANTASIST_CELESTIAL.name}: derived exhaustion')
model.AddDivisionEquality(derived_exhaustion, knob_of_scintillack, 20) model.AddDivisionEquality(derived_exhaustion, knob_of_scintillack, 20)
model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_CELESTIAL]) model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.A_COLOURFUL_PHANTASIST_CELESTIAL])
@ -1082,13 +1082,13 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(tentacles >= 4).OnlyEnforceIf(actions[Buyer.AN_INGENUOUS_MALACOLOGIST]) model.Add(tentacles >= 4).OnlyEnforceIf(actions[Buyer.AN_INGENUOUS_MALACOLOGIST])
model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.AN_INGENUOUS_MALACOLOGIST]) model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.AN_INGENUOUS_MALACOLOGIST])
exponentiated_tentacles = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_INGENUOUS_MALACOLOGIST.name, 'exponentiated tentacles')) exponentiated_tentacles = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.AN_INGENUOUS_MALACOLOGIST.name}: exponentiated tentacles')
model.AddApproximateExponentiationEquality(exponentiated_tentacles, tentacles, 2.2, MAXIMUM_ATTRIBUTE) model.AddApproximateExponentiationEquality(exponentiated_tentacles, tentacles, 2.2, MAXIMUM_ATTRIBUTE)
collated_research = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_INGENUOUS_MALACOLOGIST.name, 'collated research')) collated_research = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.AN_INGENUOUS_MALACOLOGIST.name}: collated research')
model.AddDivisionEquality(collated_research, exponentiated_tentacles, 5) model.AddDivisionEquality(collated_research, exponentiated_tentacles, 5)
value_remainder = model.NewIntVar(0, 249, '{}: {}'.format(Buyer.AN_INGENUOUS_MALACOLOGIST.name, 'value remainder')) value_remainder = model.NewIntVar(0, 249, f'{Buyer.AN_INGENUOUS_MALACOLOGIST.name}: value remainder')
model.AddModuloEquality(value_remainder, value, 250) model.AddModuloEquality(value_remainder, value, 250)
model.Add(primary_revenue == value - value_remainder + 250).OnlyEnforceIf(actions[Buyer.AN_INGENUOUS_MALACOLOGIST]) model.Add(primary_revenue == value - value_remainder + 250).OnlyEnforceIf(actions[Buyer.AN_INGENUOUS_MALACOLOGIST])
@ -1097,7 +1097,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(difficulty_level == 60*implausibility).OnlyEnforceIf(actions[Buyer.AN_INGENUOUS_MALACOLOGIST]) model.Add(difficulty_level == 60*implausibility).OnlyEnforceIf(actions[Buyer.AN_INGENUOUS_MALACOLOGIST])
# The indirection is necessary for applying an enforcement literal # The indirection is necessary for applying an enforcement literal
derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_INGENUOUS_MALACOLOGIST.name, 'derived exhaustion')) derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.AN_INGENUOUS_MALACOLOGIST.name}: derived exhaustion')
model.AddDivisionEquality(derived_exhaustion, exponentiated_tentacles, 100) model.AddDivisionEquality(derived_exhaustion, exponentiated_tentacles, 100)
model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.AN_INGENUOUS_MALACOLOGIST]) model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.AN_INGENUOUS_MALACOLOGIST])
@ -1110,13 +1110,13 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.AN_ENTERPRISING_BOOT_SALESMAN]) model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.AN_ENTERPRISING_BOOT_SALESMAN])
model.Add(legs >= 4).OnlyEnforceIf(actions[Buyer.AN_ENTERPRISING_BOOT_SALESMAN]) model.Add(legs >= 4).OnlyEnforceIf(actions[Buyer.AN_ENTERPRISING_BOOT_SALESMAN])
diamonds = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_ENTERPRISING_BOOT_SALESMAN.name, 'diamonds')) diamonds = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.AN_ENTERPRISING_BOOT_SALESMAN.name}: diamonds')
model.AddApproximateExponentiationEquality(diamonds, legs, 2.2, MAXIMUM_ATTRIBUTE) model.AddApproximateExponentiationEquality(diamonds, legs, 2.2, MAXIMUM_ATTRIBUTE)
total_value = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_ENTERPRISING_BOOT_SALESMAN.name, 'total value')) total_value = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.AN_ENTERPRISING_BOOT_SALESMAN.name}: total value')
model.Add(total_value == value + zoological_mania_bonus) model.Add(total_value == value + zoological_mania_bonus)
total_value_remainder = model.NewIntVar(0, 49, '{}: {}'.format(Buyer.AN_ENTERPRISING_BOOT_SALESMAN.name, 'total value remainder')) total_value_remainder = model.NewIntVar(0, 49, f'{Buyer.AN_ENTERPRISING_BOOT_SALESMAN.name}: total value remainder')
model.AddModuloEquality(total_value_remainder, total_value, 50) model.AddModuloEquality(total_value_remainder, total_value, 50)
model.Add(primary_revenue == total_value - total_value_remainder).OnlyEnforceIf(actions[Buyer.AN_ENTERPRISING_BOOT_SALESMAN]) model.Add(primary_revenue == total_value - total_value_remainder).OnlyEnforceIf(actions[Buyer.AN_ENTERPRISING_BOOT_SALESMAN])
@ -1125,7 +1125,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(difficulty_level == 0).OnlyEnforceIf(actions[Buyer.AN_ENTERPRISING_BOOT_SALESMAN]) model.Add(difficulty_level == 0).OnlyEnforceIf(actions[Buyer.AN_ENTERPRISING_BOOT_SALESMAN])
# The indirection is necessary for applying an enforcement literal # The indirection is necessary for applying an enforcement literal
derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.AN_ENTERPRISING_BOOT_SALESMAN.name, 'derived exhaustion')) derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.AN_ENTERPRISING_BOOT_SALESMAN.name}: derived exhaustion')
model.AddDivisionEquality(derived_exhaustion, diamonds, 100) model.AddDivisionEquality(derived_exhaustion, diamonds, 100)
model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.AN_ENTERPRISING_BOOT_SALESMAN]) model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.AN_ENTERPRISING_BOOT_SALESMAN])
@ -1136,7 +1136,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.AddLinearExpressionInDomain(skeleton_in_progress, cp_model.Domain.FromFlatIntervals([180, 189])).OnlyEnforceIf(actions[Buyer.THE_DUMBWAITER_OF_BALMORAL]) model.AddLinearExpressionInDomain(skeleton_in_progress, cp_model.Domain.FromFlatIntervals([180, 189])).OnlyEnforceIf(actions[Buyer.THE_DUMBWAITER_OF_BALMORAL])
model.Add(value >= 250).OnlyEnforceIf(actions[Buyer.THE_DUMBWAITER_OF_BALMORAL]) model.Add(value >= 250).OnlyEnforceIf(actions[Buyer.THE_DUMBWAITER_OF_BALMORAL])
value_remainder = model.NewIntVar(0, 249, '{}: {}'.format(Buyer.THE_DUMBWAITER_OF_BALMORAL.name, 'value remainder')) value_remainder = model.NewIntVar(0, 249, f'{Buyer.THE_DUMBWAITER_OF_BALMORAL.name}: value remainder')
model.AddModuloEquality(value_remainder, value, 250) model.AddModuloEquality(value_remainder, value, 250)
model.Add(primary_revenue == value - value_remainder).OnlyEnforceIf(actions[Buyer.THE_DUMBWAITER_OF_BALMORAL]) model.Add(primary_revenue == value - value_remainder).OnlyEnforceIf(actions[Buyer.THE_DUMBWAITER_OF_BALMORAL])
@ -1165,10 +1165,10 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_AMALGAMY]) model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_AMALGAMY])
model.Add(amalgamy >= 5).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_AMALGAMY]) model.Add(amalgamy >= 5).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_AMALGAMY])
amalgamy_squared = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_AMALGAMY.name, 'amalgamy squared')) amalgamy_squared = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_AMALGAMY.name}: amalgamy squared')
model.AddMultiplicationEquality(amalgamy_squared, [amalgamy, amalgamy]) model.AddMultiplicationEquality(amalgamy_squared, [amalgamy, amalgamy])
value_remainder = model.NewIntVar(0, 49, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_AMALGAMY.name, 'value remainder')) value_remainder = model.NewIntVar(0, 49, f'{Buyer.THE_TRIFLING_DIPLOMAT_AMALGAMY.name}: value remainder')
model.AddModuloEquality(value_remainder, value, 50) model.AddModuloEquality(value_remainder, value, 50)
model.Add(primary_revenue == value - value_remainder + 50).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_AMALGAMY]) model.Add(primary_revenue == value - value_remainder + 50).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_AMALGAMY])
@ -1177,7 +1177,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(difficulty_level == 0).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_AMALGAMY]) model.Add(difficulty_level == 0).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_AMALGAMY])
# The indirection is necessary for applying an enforcement literal # The indirection is necessary for applying an enforcement literal
derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_AMALGAMY.name, 'derived exhaustion')) derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_AMALGAMY.name}: derived exhaustion')
model.AddDivisionEquality(derived_exhaustion, amalgamy_squared, 100) model.AddDivisionEquality(derived_exhaustion, amalgamy_squared, 100)
model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_AMALGAMY]) model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_AMALGAMY])
@ -1188,10 +1188,10 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_ANTIQUITY]) model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_ANTIQUITY])
model.Add(antiquity >= 5).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_ANTIQUITY]) model.Add(antiquity >= 5).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_ANTIQUITY])
antiquity_squared = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_ANTIQUITY.name, 'antiquity squared')) antiquity_squared = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_ANTIQUITY.name}: antiquity squared')
model.AddMultiplicationEquality(antiquity_squared, [antiquity, antiquity]) model.AddMultiplicationEquality(antiquity_squared, [antiquity, antiquity])
value_remainder = model.NewIntVar(0, 49, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_ANTIQUITY.name, 'value remainder')) value_remainder = model.NewIntVar(0, 49, f'{Buyer.THE_TRIFLING_DIPLOMAT_ANTIQUITY.name}: value remainder')
model.AddModuloEquality(value_remainder, value, 50) model.AddModuloEquality(value_remainder, value, 50)
model.Add(primary_revenue == value - value_remainder + 50).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_ANTIQUITY]) model.Add(primary_revenue == value - value_remainder + 50).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_ANTIQUITY])
@ -1200,7 +1200,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(difficulty_level == 0).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_ANTIQUITY]) model.Add(difficulty_level == 0).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_ANTIQUITY])
# The indirection is necessary for applying an enforcement literal # The indirection is necessary for applying an enforcement literal
derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_ANTIQUITY.name, 'derived exhaustion')) derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_ANTIQUITY.name}: derived exhaustion')
model.AddDivisionEquality(derived_exhaustion, antiquity_squared, 100) model.AddDivisionEquality(derived_exhaustion, antiquity_squared, 100)
model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_ANTIQUITY]) model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_ANTIQUITY])
@ -1210,19 +1210,19 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
# The Trifling Diplomat - Bird # The Trifling Diplomat - Bird
model.AddLinearExpressionInDomain(skeleton_in_progress, cp_model.Domain.FromFlatIntervals([180, 189])).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_BIRD]) model.AddLinearExpressionInDomain(skeleton_in_progress, cp_model.Domain.FromFlatIntervals([180, 189])).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_BIRD])
non_negative_amalgamy = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_BIRD.name, 'non-negative amalgamy')) non_negative_amalgamy = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_BIRD.name}: non-negative amalgamy')
model.AddMaxEquality(non_negative_amalgamy, [amalgamy, 0]) model.AddMaxEquality(non_negative_amalgamy, [amalgamy, 0])
non_negative_menace = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_BIRD.name, 'non-negative menace')) non_negative_menace = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_BIRD.name}: non-negative menace')
model.AddMaxEquality(non_negative_menace, [menace, 0]) model.AddMaxEquality(non_negative_menace, [menace, 0])
non_negative_antiquity = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_BIRD.name, 'non-negative antiquity')) non_negative_antiquity = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_BIRD.name}: non-negative antiquity')
model.AddMaxEquality(non_negative_antiquity, [antiquity, 0]) model.AddMaxEquality(non_negative_antiquity, [antiquity, 0])
compromising_documents = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_BIRD.name, 'compromising documents')) compromising_documents = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_BIRD.name}: compromising documents')
model.AddGeneralMultiplicationEquality(compromising_documents, non_negative_amalgamy, non_negative_menace, non_negative_antiquity) model.AddGeneralMultiplicationEquality(compromising_documents, non_negative_amalgamy, non_negative_menace, non_negative_antiquity)
value_remainder = model.NewIntVar(0, 49, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_BIRD.name, 'value remainder')) value_remainder = model.NewIntVar(0, 49, f'{Buyer.THE_TRIFLING_DIPLOMAT_BIRD.name}: value remainder')
model.AddModuloEquality(value_remainder, value, 50) model.AddModuloEquality(value_remainder, value, 50)
model.Add(primary_revenue == value - value_remainder + 50).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_BIRD]) model.Add(primary_revenue == value - value_remainder + 50).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_BIRD])
@ -1231,7 +1231,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(difficulty_level == 0).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_BIRD]) model.Add(difficulty_level == 0).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_BIRD])
# The indirection is necessary for applying an enforcement literal # The indirection is necessary for applying an enforcement literal
derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_BIRD.name, 'derived exhaustion')) derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_BIRD.name}: derived exhaustion')
model.AddDivisionEquality(derived_exhaustion, compromising_documents, 100) model.AddDivisionEquality(derived_exhaustion, compromising_documents, 100)
model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_BIRD]) model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_BIRD])
@ -1241,19 +1241,19 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
# The Trifling Diplomat - Fish # The Trifling Diplomat - Fish
model.AddLinearExpressionInDomain(skeleton_in_progress, cp_model.Domain.FromFlatIntervals([190, 199])).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_FISH]) model.AddLinearExpressionInDomain(skeleton_in_progress, cp_model.Domain.FromFlatIntervals([190, 199])).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_FISH])
non_negative_amalgamy = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_FISH.name, 'non-negative amalgamy')) non_negative_amalgamy = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_FISH.name}: non-negative amalgamy')
model.AddMaxEquality(non_negative_amalgamy, [amalgamy, 0]) model.AddMaxEquality(non_negative_amalgamy, [amalgamy, 0])
non_negative_menace = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_FISH.name, 'non-negative menace')) non_negative_menace = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_FISH.name}: non-negative menace')
model.AddMaxEquality(non_negative_menace, [menace, 0]) model.AddMaxEquality(non_negative_menace, [menace, 0])
non_negative_antiquity = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_FISH.name, 'non-negative antiquity')) non_negative_antiquity = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_FISH.name}: non-negative antiquity')
model.AddMaxEquality(non_negative_antiquity, [antiquity, 0]) model.AddMaxEquality(non_negative_antiquity, [antiquity, 0])
compromising_documents = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_FISH.name, 'compromising documents')) compromising_documents = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_FISH.name}: compromising documents')
model.AddGeneralMultiplicationEquality(compromising_documents, non_negative_amalgamy, non_negative_menace, non_negative_antiquity) model.AddGeneralMultiplicationEquality(compromising_documents, non_negative_amalgamy, non_negative_menace, non_negative_antiquity)
value_remainder = model.NewIntVar(0, 49, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_FISH.name, 'value remainder')) value_remainder = model.NewIntVar(0, 49, f'{Buyer.THE_TRIFLING_DIPLOMAT_FISH.name}: value remainder')
model.AddModuloEquality(value_remainder, value, 50) model.AddModuloEquality(value_remainder, value, 50)
model.Add(primary_revenue == value - value_remainder + 50).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_FISH]) model.Add(primary_revenue == value - value_remainder + 50).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_FISH])
@ -1262,7 +1262,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(difficulty_level == 0).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_FISH]) model.Add(difficulty_level == 0).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_FISH])
# The indirection is necessary for applying an enforcement literal # The indirection is necessary for applying an enforcement literal
derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_FISH.name, 'derived exhaustion')) derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_FISH.name}: derived exhaustion')
model.AddDivisionEquality(derived_exhaustion, compromising_documents, 100) model.AddDivisionEquality(derived_exhaustion, compromising_documents, 100)
model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_FISH]) model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_FISH])
@ -1272,19 +1272,19 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
# The Trifling Diplomat - Insect # The Trifling Diplomat - Insect
model.AddLinearExpressionInDomain(skeleton_in_progress, cp_model.Domain.FromFlatIntervals([210, 219])).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_INSECT]) model.AddLinearExpressionInDomain(skeleton_in_progress, cp_model.Domain.FromFlatIntervals([210, 219])).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_INSECT])
non_negative_amalgamy = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_INSECT.name, 'non-negative amalgamy')) non_negative_amalgamy = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_INSECT.name}: non-negative amalgamy')
model.AddMaxEquality(non_negative_amalgamy, [amalgamy, 0]) model.AddMaxEquality(non_negative_amalgamy, [amalgamy, 0])
non_negative_menace = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_INSECT.name, 'non-negative menace')) non_negative_menace = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_INSECT.name}: non-negative menace')
model.AddMaxEquality(non_negative_menace, [menace, 0]) model.AddMaxEquality(non_negative_menace, [menace, 0])
non_negative_antiquity = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_INSECT.name, 'non-negative antiquity')) non_negative_antiquity = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_INSECT.name}: non-negative antiquity')
model.AddMaxEquality(non_negative_antiquity, [antiquity, 0]) model.AddMaxEquality(non_negative_antiquity, [antiquity, 0])
compromising_documents = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_INSECT.name, 'compromising documents')) compromising_documents = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_INSECT.name}: compromising documents')
model.AddGeneralMultiplicationEquality(compromising_documents, non_negative_amalgamy, non_negative_menace, non_negative_antiquity) model.AddGeneralMultiplicationEquality(compromising_documents, non_negative_amalgamy, non_negative_menace, non_negative_antiquity)
value_remainder = model.NewIntVar(0, 49, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_INSECT.name, 'value remainder')) value_remainder = model.NewIntVar(0, 49, f'{Buyer.THE_TRIFLING_DIPLOMAT_INSECT.name}: value remainder')
model.AddModuloEquality(value_remainder, value, 50) model.AddModuloEquality(value_remainder, value, 50)
model.Add(primary_revenue == value - value_remainder + 50).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_INSECT]) model.Add(primary_revenue == value - value_remainder + 50).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_INSECT])
@ -1293,7 +1293,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(difficulty_level == 0).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_INSECT]) model.Add(difficulty_level == 0).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_INSECT])
# The indirection is necessary for applying an enforcement literal # The indirection is necessary for applying an enforcement literal
derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_INSECT.name, 'derived exhaustion')) derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_INSECT.name}: derived exhaustion')
model.AddDivisionEquality(derived_exhaustion, compromising_documents, 100) model.AddDivisionEquality(derived_exhaustion, compromising_documents, 100)
model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_INSECT]) model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_INSECT])
@ -1303,19 +1303,19 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
# The Trifling Diplomat - Reptile # The Trifling Diplomat - Reptile
model.AddLinearExpressionInDomain(skeleton_in_progress, cp_model.Domain.FromFlatIntervals([160, 169])).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_REPTILE]) model.AddLinearExpressionInDomain(skeleton_in_progress, cp_model.Domain.FromFlatIntervals([160, 169])).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_REPTILE])
non_negative_amalgamy = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_REPTILE.name, 'non-negative amalgamy')) non_negative_amalgamy = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_REPTILE.name}: non-negative amalgamy')
model.AddMaxEquality(non_negative_amalgamy, [amalgamy, 0]) model.AddMaxEquality(non_negative_amalgamy, [amalgamy, 0])
non_negative_menace = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_REPTILE.name, 'non-negative menace')) non_negative_menace = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_REPTILE.name}: non-negative menace')
model.AddMaxEquality(non_negative_menace, [menace, 0]) model.AddMaxEquality(non_negative_menace, [menace, 0])
non_negative_antiquity = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_REPTILE.name, 'non-negative antiquity')) non_negative_antiquity = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_REPTILE.name}: non-negative antiquity')
model.AddMaxEquality(non_negative_antiquity, [antiquity, 0]) model.AddMaxEquality(non_negative_antiquity, [antiquity, 0])
compromising_documents = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_REPTILE.name, 'compromising documents')) compromising_documents = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_REPTILE.name}: compromising documents')
model.AddGeneralMultiplicationEquality(compromising_documents, non_negative_amalgamy, non_negative_menace, non_negative_antiquity) model.AddGeneralMultiplicationEquality(compromising_documents, non_negative_amalgamy, non_negative_menace, non_negative_antiquity)
value_remainder = model.NewIntVar(0, 49, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_REPTILE.name, 'value remainder')) value_remainder = model.NewIntVar(0, 49, f'{Buyer.THE_TRIFLING_DIPLOMAT_REPTILE.name}: value remainder')
model.AddModuloEquality(value_remainder, value, 50) model.AddModuloEquality(value_remainder, value, 50)
model.Add(primary_revenue == value - value_remainder + 50).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_REPTILE]) model.Add(primary_revenue == value - value_remainder + 50).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_REPTILE])
@ -1324,7 +1324,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(difficulty_level == 0).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_REPTILE]) model.Add(difficulty_level == 0).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_REPTILE])
# The indirection is necessary for applying an enforcement literal # The indirection is necessary for applying an enforcement literal
derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_REPTILE.name, 'derived exhaustion')) derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_REPTILE.name}: derived exhaustion')
model.AddDivisionEquality(derived_exhaustion, compromising_documents, 100) model.AddDivisionEquality(derived_exhaustion, compromising_documents, 100)
model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_REPTILE]) model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_REPTILE])
@ -1335,19 +1335,19 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_SKULLS]) model.Add(skeleton_in_progress >= 100).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_SKULLS])
model.Add(skulls >= 5).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_SKULLS]) model.Add(skulls >= 5).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_SKULLS])
non_negative_amalgamy = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_SKULLS.name, 'non-negative amalgamy')) non_negative_amalgamy = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_SKULLS.name}: non-negative amalgamy')
model.AddMaxEquality(non_negative_amalgamy, [amalgamy, 0]) model.AddMaxEquality(non_negative_amalgamy, [amalgamy, 0])
non_negative_menace = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_SKULLS.name, 'non-negative menace')) non_negative_menace = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_SKULLS.name}: non-negative menace')
model.AddMaxEquality(non_negative_menace, [menace, 0]) model.AddMaxEquality(non_negative_menace, [menace, 0])
non_negative_antiquity = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_SKULLS.name, 'non-negative antiquity')) non_negative_antiquity = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_SKULLS.name}: non-negative antiquity')
model.AddMaxEquality(non_negative_antiquity, [antiquity, 0]) model.AddMaxEquality(non_negative_antiquity, [antiquity, 0])
compromising_documents = model.NewIntVar(0, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_SKULLS.name, 'compromising documents')) compromising_documents = model.NewIntVar(0, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_SKULLS.name}: compromising documents')
model.AddGeneralMultiplicationEquality(compromising_documents, non_negative_amalgamy, non_negative_menace, non_negative_antiquity) model.AddGeneralMultiplicationEquality(compromising_documents, non_negative_amalgamy, non_negative_menace, non_negative_antiquity)
value_remainder = model.NewIntVar(0, 49, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_SKULLS.name, 'value remainder')) value_remainder = model.NewIntVar(0, 49, f'{Buyer.THE_TRIFLING_DIPLOMAT_SKULLS.name}: value remainder')
model.AddModuloEquality(value_remainder, value, 50) model.AddModuloEquality(value_remainder, value, 50)
model.Add(primary_revenue == value - value_remainder + 50).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_SKULLS]) model.Add(primary_revenue == value - value_remainder + 50).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_SKULLS])
@ -1356,7 +1356,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
model.Add(difficulty_level == 0).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_SKULLS]) model.Add(difficulty_level == 0).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_SKULLS])
# The indirection is necessary for applying an enforcement literal # The indirection is necessary for applying an enforcement literal
derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, '{}: {}'.format(Buyer.THE_TRIFLING_DIPLOMAT_SKULLS.name, 'derived exhaustion')) derived_exhaustion = model.NewIntVar(cp_model.INT32_MIN, cp_model.INT32_MAX, f'{Buyer.THE_TRIFLING_DIPLOMAT_SKULLS.name}: derived exhaustion')
model.AddDivisionEquality(derived_exhaustion, compromising_documents, 100) model.AddDivisionEquality(derived_exhaustion, compromising_documents, 100)
model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_SKULLS]) model.Add(added_exhaustion == derived_exhaustion).OnlyEnforceIf(actions[Buyer.THE_TRIFLING_DIPLOMAT_SKULLS])
@ -1411,23 +1411,24 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
for _ in range(int(solver.Value(actions[action]))): for _ in range(int(solver.Value(actions[action]))):
output += str(action) + "\n" output += str(action) + "\n"
output += "\nProfit: £{:,.2f}\n".format(solver.Value(net_profit)/100) output += f"""
output += "Profit Margin: {:+,.2%}\n".format(solver.Value(profit_margin)/PROFIT_MARGIN_MULTIPLIER) Profit: £{solver.Value(net_profit)/100:,.2f}
Profit Margin: {solver.Value(profit_margin)/PROFIT_MARGIN_MULTIPLIER:+,.2%}
output += "\nTotal Revenue: £{:,.2f}\n".format(solver.Value(total_revenue)/100) Total Revenue: £{solver.Value(total_revenue)/100:,.2f}
output += "Primary Revenue: £{:,.2f}\n".format(solver.Value(primary_revenue)/100) Primary Revenue: £{solver.Value(primary_revenue)/100:,.2f}
output += "Secondary Revenue: £{:,.2f}\n".format(solver.Value(secondary_revenue)/100) Secondary Revenue: £{solver.Value(secondary_revenue)/100:,.2f}
output += "\nCost: £{:,.2f}\n".format(solver.Value(cost)/100) Cost: £{solver.Value(cost)/100:,.2f}
output += "\nValue: £{:,.2f}\n".format(solver.Value(value)/100) Value: £{solver.Value(value)/100:,.2f}
output += "Amalgamy: {:n}\n".format(solver.Value(amalgamy)) Amalgamy: {solver.Value(amalgamy):n}
output += "Antiquity: {:n}\n".format(solver.Value(antiquity)) Antiquity: {solver.Value(antiquity):n}
output += "Menace: {:n}\n".format(solver.Value(menace)) Menace: {solver.Value(menace):n}
output += "Counter-Church: {:n}\n".format(solver.Value(counter_church)) Counter-Church: {solver.Value(counter_church):n}
output += "Implausibility: {:n}\n".format(solver.Value(implausibility)) Implausibility: {solver.Value(implausibility):n}
output += "\nExhaustion: {:n}".format(solver.Value(exhaustion)) Exhaustion: {solver.Value(exhaustion):n}"""
return output return output
@ -1439,7 +1440,7 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
stdscr.clear() stdscr.clear()
stdscr.addstr(self.PrintableSolution()) stdscr.addstr(self.PrintableSolution())
stdscr.addstr(stdscr.getmaxyx()[0] - 1, 0, "Skeleton #{:n}".format(self.__solution_count)) stdscr.addstr(stdscr.getmaxyx()[0] - 1, 0, f"Skeleton #{self.__solution_count:n}")
stdscr.refresh() stdscr.refresh()
@ -1468,6 +1469,6 @@ def Solve(shadowy_level, bone_market_fluctuations = None, zoological_mania = Non
elif status == 'FEASIBLE': elif status == 'FEASIBLE':
print("WARNING: skeleton may be suboptimal.") print("WARNING: skeleton may be suboptimal.")
elif status != 'OPTIMAL': elif status != 'OPTIMAL':
raise RuntimeError("Unknown status returned: {}.".format(status)) raise RuntimeError(f"Unknown status returned: {status}.")
return printer.PrintableSolution(solver) return printer.PrintableSolution(solver)