Show current best skeleton while calculating
So long as verbose mode is not active, the script will now display the current skeleton as it tries to search for more solutions. This feature uses the curses module to create an alternate screen, so intermediate solutions are not sent to standard output.
This commit is contained in:
parent
b75d412cb7
commit
3b13e9c25f
|
@ -2,6 +2,7 @@ import functools
|
||||||
import enum
|
import enum
|
||||||
import os
|
import os
|
||||||
import argparse
|
import argparse
|
||||||
|
import curses
|
||||||
|
|
||||||
from enum import auto
|
from enum import auto
|
||||||
from ortools.sat.python import cp_model
|
from ortools.sat.python import cp_model
|
||||||
|
@ -1145,7 +1146,7 @@ class Fluctuation(enum.Enum):
|
||||||
AMALGAMY = 2
|
AMALGAMY = 2
|
||||||
|
|
||||||
|
|
||||||
def Solve(bone_market_fluctuations, zoological_mania, desired_buyer = None, maximum_cost = cp_model.INT32_MAX, maximum_exhaustion = cp_model.INT32_MAX, verbose = False):
|
def Solve(bone_market_fluctuations, zoological_mania, desired_buyer = None, maximum_cost = cp_model.INT32_MAX, maximum_exhaustion = cp_model.INT32_MAX, stdscr = None):
|
||||||
model = cp_model.CpModel()
|
model = cp_model.CpModel()
|
||||||
|
|
||||||
actions = {}
|
actions = {}
|
||||||
|
@ -2060,9 +2061,15 @@ def Solve(bone_market_fluctuations, zoological_mania, desired_buyer = None, maxi
|
||||||
|
|
||||||
def OnSolutionCallback(self):
|
def OnSolutionCallback(self):
|
||||||
self.__solution_count += 1
|
self.__solution_count += 1
|
||||||
print()
|
|
||||||
print(self.PrintableSolution())
|
# Prints current solution to window
|
||||||
print()
|
stdscr.clear()
|
||||||
|
stdscr.addstr(self.PrintableSolution())
|
||||||
|
|
||||||
|
stdscr.addstr(stdscr.getmaxyx()[0] - 1, 0, "Skeleton #{:n}".format(self.__solution_count))
|
||||||
|
|
||||||
|
stdscr.refresh()
|
||||||
|
|
||||||
|
|
||||||
def SolutionCount(self):
|
def SolutionCount(self):
|
||||||
return self.__solution_count
|
return self.__solution_count
|
||||||
|
@ -2072,9 +2079,16 @@ def Solve(bone_market_fluctuations, zoological_mania, desired_buyer = None, maxi
|
||||||
|
|
||||||
solver = cp_model.CpSolver()
|
solver = cp_model.CpSolver()
|
||||||
solver.parameters.num_search_workers = os.cpu_count()
|
solver.parameters.num_search_workers = os.cpu_count()
|
||||||
solver.parameters.log_search_progress = verbose
|
|
||||||
|
|
||||||
status = solver.StatusName(solver.Solve(model))
|
# There's no window in verbose mode
|
||||||
|
if stdscr is None:
|
||||||
|
solver.parameters.log_search_progress = True
|
||||||
|
solver.Solve(model)
|
||||||
|
else:
|
||||||
|
solver.SolveWithSolutionCallback(model, printer)
|
||||||
|
|
||||||
|
status = solver.StatusName()
|
||||||
|
|
||||||
if status == "INFEASIBLE":
|
if status == "INFEASIBLE":
|
||||||
raise RuntimeError("There is no satisfactory skeleton.")
|
raise RuntimeError("There is no satisfactory skeleton.")
|
||||||
elif status == "FEASIBLE":
|
elif status == "FEASIBLE":
|
||||||
|
@ -2082,8 +2096,7 @@ def Solve(bone_market_fluctuations, zoological_mania, desired_buyer = None, maxi
|
||||||
elif status != "OPTIMAL":
|
elif status != "OPTIMAL":
|
||||||
raise RuntimeError("Unknown status returned: {}.".format(status))
|
raise RuntimeError("Unknown status returned: {}.".format(status))
|
||||||
|
|
||||||
print()
|
return printer.PrintableSolution(solver)
|
||||||
print(printer.PrintableSolution(solver))
|
|
||||||
|
|
||||||
|
|
||||||
class EnumAction(argparse.Action):
|
class EnumAction(argparse.Action):
|
||||||
|
@ -2149,13 +2162,21 @@ def main():
|
||||||
const='True',
|
const='True',
|
||||||
default=False,
|
default=False,
|
||||||
type=bool,
|
type=bool,
|
||||||
help='whether the solver should output progress',
|
help='whether the solver should output search progress rather than showing intermediate solutions',
|
||||||
dest='verbose'
|
dest='verbose'
|
||||||
)
|
)
|
||||||
|
|
||||||
args = parser.parse_args()
|
args = parser.parse_args()
|
||||||
|
|
||||||
Solve(args.bone_market_fluctuations, args.zoological_mania, args.desired_buyer, args.maximum_cost, args.maximum_exhaustion, args.verbose)
|
arguments = (args.bone_market_fluctuations, args.zoological_mania, args.desired_buyer, args.maximum_cost, args.maximum_exhaustion)
|
||||||
|
|
||||||
|
if not args.verbose:
|
||||||
|
def WrappedSolve(stdscr, arguments):
|
||||||
|
# Move stdscr to last position
|
||||||
|
return Solve(*arguments, stdscr)
|
||||||
|
print(curses.wrapper(WrappedSolve, arguments))
|
||||||
|
else:
|
||||||
|
print(Solve(*arguments))
|
||||||
|
|
||||||
|
|
||||||
main()
|
main()
|
||||||
|
|
Loading…
Reference in New Issue