Saklad5
/
Bone-Market-Solver
2
0
Fork 0
Code Issues Pull Requests Activity

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.
This commit is contained in:
Jeremy Saklad 2021-06-19 07:32:19 -05:00
parent eb94bb3b44
commit b7f47da9d0
Signed by: Jeremy Saklad
GPG Key ID: 9CA2149583EDBF84
1 changed files with 11 additions and 5 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

16
Bone Market Solver.py
View File

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