Add ability to specify multiple buyers at once
Users can now specify multiple buyers, allowing the solver to figure out the best skeleton that could be sold to any of them. This could be useful for buyers that share a payout.
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@ -1158,7 +1158,7 @@ class OccasionalBuyer(enum.Enum):
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]
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def Solve(bone_market_fluctuations, zoological_mania, occasional_buyer = None, desired_buyer = None, maximum_cost = cp_model.INT32_MAX, maximum_exhaustion = cp_model.INT32_MAX, time_limit = float('inf'), stdscr = None):
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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'), stdscr = None):
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model = cp_model.CpModel()
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actions = {}
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@ -1203,9 +1203,13 @@ def Solve(bone_market_fluctuations, zoological_mania, occasional_buyer = None, d
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model.AddAssumptions([
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actions[buyer].Not()
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for unavailable_buyer in OccasionalBuyer if unavailable_buyer != occasional_buyer
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for buyer in unavailable_buyer.value if buyer != desired_buyer
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for buyer in unavailable_buyer.value if buyer not in desired_buyers
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])
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# Restrict to desired buyers
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if desired_buyers:
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model.Add(cp_model.LinearExpr.Sum([actions[desired_buyer] for desired_buyer in desired_buyers]) == 1)
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# One torso
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model.Add(cp_model.LinearExpr.Sum([value for (key, value) in actions.items() if isinstance(key, Torso)]) == 1)
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@ -1216,9 +1220,6 @@ def Solve(bone_market_fluctuations, zoological_mania, occasional_buyer = None, d
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# One buyer
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model.Add(cp_model.LinearExpr.Sum([value for (key, value) in actions.items() if isinstance(key, Buyer)]) == 1)
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# Set buyer
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if desired_buyer is not None:
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model.AddAssumption(actions[desired_buyer])
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# Value calculation
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original_value = model.NewIntVar(0, cp_model.INT32_MAX, 'original value')
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@ -2137,19 +2138,28 @@ def Solve(bone_market_fluctuations, zoological_mania, occasional_buyer = None, d
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class EnumAction(argparse.Action):
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def __init__(self, **kwargs):
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# Pop off the type value
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enum = kwargs.pop("type", None)
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enum = kwargs.pop('type', None)
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nargs = kwargs.pop('nargs', None)
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# Generate choices from the Enum
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kwargs.setdefault("choices", tuple(e.name.lower() for e in enum))
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kwargs.setdefault('choices', tuple(member.name.lower() for member in enum))
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super(EnumAction, self).__init__(**kwargs)
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self._enum = enum
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self._nargs = nargs
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def __call__(self, parser, namespace, values, option_string=None):
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# Convert value back into an Enum
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enum = self._enum[values.upper()]
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setattr(namespace, self.dest, enum)
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if self._nargs is None or self._nargs == '?':
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setattr(namespace, self.dest, enum)
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else:
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items = getattr(namespace, self.dest, list())
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items.append(enum)
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setattr(namespace, self.dest, items)
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def main():
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@ -2184,9 +2194,11 @@ def main():
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buyer.add_argument(
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'-b','--buyer', '--desired-buyer',
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action=EnumAction,
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nargs='+',
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default=[],
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type=Buyer,
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help='specific buyer that skeleton should be designed for',
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dest='desired_buyer'
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help='specific buyer that skeleton should be designed for (if declared repeatedly, will choose from among those provided)',
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dest='desired_buyers'
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)
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parser.add_argument(
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@ -2222,7 +2234,7 @@ 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_buyer, args.maximum_cost, args.maximum_exhaustion, args.time_limit)
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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)
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if not args.verbose:
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def WrappedSolve(stdscr, arguments):
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