Add command-line parameter for Shadowy level
This argument determines how difficult selling to a buyer is, which influences how much Implausibility the solver produces.
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@ -20,8 +20,6 @@ MAXIMUM_ATTRIBUTE = 100
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# This is a constant used to calculate difficulty checks. You almost certainly do not need to change this.
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DIFFICULTY_SCALER = 0.6
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# This is the effective level of Shadowy used for attempting to sell.
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SHADOWY_LEVEL = 300
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class Cost(Enum):
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"""The number of pennies needed to produce a quality."""
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@ -1179,7 +1177,7 @@ class OccasionalBuyer(Enum):
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]
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def Solve(bone_market_fluctuations, zoological_mania, occasional_buyer = None, desired_buyers = [], maximum_cost = cp_model.INT32_MAX, maximum_exhaustion = cp_model.INT32_MAX, time_limit = float('inf'), workers = cpu_count(), stdscr = None):
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def Solve(shadowy_level, bone_market_fluctuations, zoological_mania, occasional_buyer = None, desired_buyers = [], maximum_cost = cp_model.INT32_MAX, maximum_exhaustion = cp_model.INT32_MAX, time_limit = float('inf'), workers = cpu_count(), stdscr = None):
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model = cp_model.CpModel()
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actions = {}
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@ -1343,7 +1341,7 @@ def Solve(bone_market_fluctuations, zoological_mania, occasional_buyer = None, d
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model.AddMaxEquality(non_zero_difficulty_level, [difficulty_level, 1])
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sale_actions_times_action_value = model.NewIntVar(0, cp_model.INT32_MAX, 'sale actions times action value')
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model.AddDivisionEquality(sale_actions_times_action_value, model.NewConstant(round(DIFFICULTY_SCALER*SHADOWY_LEVEL*Cost.ACTION.value)), non_zero_difficulty_level)
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model.AddDivisionEquality(sale_actions_times_action_value, model.NewConstant(round(DIFFICULTY_SCALER*shadowy_level*Cost.ACTION.value)), non_zero_difficulty_level)
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abstract_sale_cost = model.NewIntVar(0, cp_model.INT32_MAX, 'abstract sale cost')
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model.AddDivisionEquality(abstract_sale_cost, Cost.ACTION.value**2, sale_actions_times_action_value)
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sale_cost = model.NewIntVar(0, cp_model.INT32_MAX, 'sale cost')
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@ -2188,6 +2186,14 @@ class EnumAction(argparse.Action):
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def main():
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parser = argparse.ArgumentParser(prog='Bone Market Solver', description="Devise the optimal skeleton at the Bone Market in Fallen London.")
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parser.add_argument(
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"-s", "--shadowy",
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type=int,
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required=True,
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help="the effective level of Shadowy used for selling to buyers",
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dest='shadowy_level'
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)
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parser.add_argument(
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"-f", "--bone-market-fluctuations",
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action=EnumAction,
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@ -2264,7 +2270,7 @@ def main():
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args = parser.parse_args()
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arguments = (args.bone_market_fluctuations, args.zoological_mania, args.occasional_buyer, args.desired_buyers, args.maximum_cost, args.maximum_exhaustion, args.time_limit, args.workers)
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arguments = (args.shadowy_level, args.bone_market_fluctuations, args.zoological_mania, args.occasional_buyer, args.desired_buyers, args.maximum_cost, args.maximum_exhaustion, args.time_limit, args.workers)
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if not args.verbose:
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def WrappedSolve(stdscr, arguments):
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