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mostly PascalCase -> sname_case

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Laurent Perron
2018-11-20 05:44:21 -08:00
parent 3fae2c719f
commit 44e52c1ef8
19 changed files with 208 additions and 205 deletions
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2
examples/python/appointments.py
View File

@@ -38,7 +38,7 @@ class AllSolutionCollector(cp_model.CpSolverSolutionCallback):
self.__variables = variables
self.__collect = []
def OnSolutionCallback(self):
def on_solution_callback(self):
"""Collect a new combination."""
combination = [self.Value(v) for v in self.__variables]
self.__collect.append(combination)

5
examples/python/balance_group_sat.py
View File

@@ -37,7 +37,7 @@ class SolutionPrinter(cp_model.CpSolverSolutionCallback):
self.__all_items = all_items
self.__item_in_group = item_in_group
def OnSolutionCallback(self):
def on_solution_callback(self):
print('Solution %i' % self.__solution_count)
self.__solution_count += 1
@@ -61,9 +61,6 @@ class SolutionPrinter(cp_model.CpSolverSolutionCallback):
print(' (%i, %i, %i)' % (item, value, color), end='')
print(']')
def SolutionCount(self):
return self.__solution_count
def main():
# Data.

242
examples/python/flexible_job_shop_sat.py
View File

@@ -10,6 +10,7 @@
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Solves a flexible jobshop problems with the CP-SAT solver."""
from __future__ import print_function
@@ -24,149 +25,156 @@ class SolutionPrinter(cp_model.CpSolverSolutionCallback):
cp_model.CpSolverSolutionCallback.__init__(self)
self.__solution_count = 0
def OnSolutionCallback(self):
def on_solution_callback(self):
"""Called at each new solution."""
print('Solution %i, time = %f s, objective = %i' %
(self.__solution_count, self.WallTime(), self.ObjectiveValue()))
self.__solution_count += 1
# Data part.
jobs = [[[(3, 0), (1, 1), (5, 2)], [(2, 0), (4, 1), (6, 2)],
[(2, 0), (3, 1), (1, 2)]],
[[(2, 0), (3, 1), (4, 2)], [(1, 0), (5, 1), (4, 2)],
[(2, 0), (1, 1), (4, 2)]],
[[(2, 0), (1, 1), (4, 2)], [(2, 0), (3, 1), (4, 2)],
[(3, 0), (1, 1), (5, 2)]]]
def flexible_jobshop():
"""Solve a small flexible jobshop problem."""
# Data part.
jobs = [[[(3, 0), (1, 1), (5, 2)], [(2, 0), (4, 1), (6, 2)],
[(2, 0), (3, 1), (1, 2)]],
[[(2, 0), (3, 1), (4, 2)], [(1, 0), (5, 1), (4, 2)],
[(2, 0), (1, 1), (4, 2)]],
[[(2, 0), (1, 1), (4, 2)], [(2, 0), (3, 1), (4, 2)],
[(3, 0), (1, 1), (5, 2)]]]
num_jobs = len(jobs)
all_jobs = range(num_jobs)
num_jobs = len(jobs)
all_jobs = range(num_jobs)
num_machines = 3
all_machines = range(num_machines)
num_machines = 3
all_machines = range(num_machines)
# Model the flexible jobshop problem.
model = cp_model.CpModel()
# Model the flexible jobshop problem.
model = cp_model.CpModel()
horizon = 0
for job in jobs:
for task in job:
max_task_duration = 0
for alternative in task:
max_task_duration = max(max_task_duration, alternative[0])
horizon += max_task_duration
horizon = 0
for job in jobs:
for task in job:
max_task_duration = 0
for alternative in task:
max_task_duration = max(max_task_duration, alternative[0])
horizon += max_task_duration
print('Horizon = %i' % horizon)
print('Horizon = %i' % horizon)
# Global storage of variables.
intervals_per_resources = defaultdict(list)
starts = {} # indexed by (job_id, task_id).
presences = {} # indexed by (job_id, task_id, alt_id).
job_ends = []
# Global storage of variables.
intervals_per_resources = defaultdict(list)
starts = {} # indexed by (job_id, task_id).
presences = {} # indexed by (job_id, task_id, alt_id).
job_ends = []
# Scan the jobs and create the relevant variables and intervals.
for job_id in all_jobs:
job = jobs[job_id]
num_tasks = len(job)
previous_end = None
for task_id in range(num_tasks):
task = job[task_id]
# Scan the jobs and create the relevant variables and intervals.
for job_id in all_jobs:
job = jobs[job_id]
num_tasks = len(job)
previous_end = None
for task_id in range(num_tasks):
task = job[task_id]
min_duration = task[0][0]
max_duration = task[0][0]
min_duration = task[0][0]
max_duration = task[0][0]
num_alternatives = len(task)
all_alternatives = range(num_alternatives)
num_alternatives = len(task)
all_alternatives = range(num_alternatives)
for alt_id in range(1, num_alternatives):
alt_duration = task[alt_id][0]
min_duration = min(min_duration, alt_duration)
max_duration = max(max_duration, alt_duration)
for alt_id in range(1, num_alternatives):
alt_duration = task[alt_id][0]
min_duration = min(min_duration, alt_duration)
max_duration = max(max_duration, alt_duration)
# Create main interval for the task.
suffix_name = '_j%i_t%i' % (job_id, task_id)
start = model.NewIntVar(0, horizon, 'start' + suffix_name)
duration = model.NewIntVar(min_duration, max_duration,
'duration' + suffix_name)
end = model.NewIntVar(0, horizon, 'end' + suffix_name)
interval = model.NewIntervalVar(start, duration, end,
'interval' + suffix_name)
# Create main interval for the task.
suffix_name = '_j%i_t%i' % (job_id, task_id)
start = model.NewIntVar(0, horizon, 'start' + suffix_name)
duration = model.NewIntVar(min_duration, max_duration,
'duration' + suffix_name)
end = model.NewIntVar(0, horizon, 'end' + suffix_name)
interval = model.NewIntervalVar(start, duration, end,
'interval' + suffix_name)
# Store the start for the solution.
starts[(job_id, task_id)] = start
# Store the start for the solution.
starts[(job_id, task_id)] = start
# Add precedence with previous task in the same job.
if previous_end:
model.Add(start >= previous_end)
previous_end = end
# Add precedence with previous task in the same job.
if previous_end:
model.Add(start >= previous_end)
previous_end = end
# Create alternative intervals.
if num_alternatives > 1:
l_presences = []
for alt_id in all_alternatives:
alt_suffix = '_j%i_t%i_a%i' % (job_id, task_id, alt_id)
l_presence = model.NewBoolVar('presence' + alt_suffix)
l_start = model.NewIntVar(0, horizon, 'start' + alt_suffix)
l_duration = task[alt_id][0]
l_end = model.NewIntVar(0, horizon, 'end' + alt_suffix)
l_interval = model.NewOptionalIntervalVar(
l_start, l_duration, l_end, l_presence,
'interval' + alt_suffix)
l_presences.append(l_presence)
# Create alternative intervals.
if num_alternatives > 1:
l_presences = []
for alt_id in all_alternatives:
alt_suffix = '_j%i_t%i_a%i' % (job_id, task_id, alt_id)
l_presence = model.NewBoolVar('presence' + alt_suffix)
l_start = model.NewIntVar(0, horizon, 'start' + alt_suffix)
l_duration = task[alt_id][0]
l_end = model.NewIntVar(0, horizon, 'end' + alt_suffix)
l_interval = model.NewOptionalIntervalVar(
l_start, l_duration, l_end, l_presence,
'interval' + alt_suffix)
l_presences.append(l_presence)
# Link the master variables with the local ones.
model.Add(start == l_start).OnlyEnforceIf(l_presence)
model.Add(duration == l_duration).OnlyEnforceIf(l_presence)
model.Add(end == l_end).OnlyEnforceIf(l_presence)
# Link the master variables with the local ones.
model.Add(start == l_start).OnlyEnforceIf(l_presence)
model.Add(duration == l_duration).OnlyEnforceIf(l_presence)
model.Add(end == l_end).OnlyEnforceIf(l_presence)
# Add the local interval to the right machine.
intervals_per_resources[task[alt_id][1]].append(l_interval)
# Add the local interval to the right machine.
intervals_per_resources[task[alt_id][1]].append(l_interval)
# Store the presences for the solution.
presences[(job_id, task_id, alt_id)] = l_presence
# Store the presences for the solution.
presences[(job_id, task_id, alt_id)] = l_presence
# Select exactly one presence variable.
model.Add(sum(l_presences) == 1)
else:
intervals_per_resources[task[0][1]].append(interval)
presences[(job_id, task_id, 0)] = model.NewConstant(1)
# Select exactly one presence variable.
model.Add(sum(l_presences) == 1)
else:
intervals_per_resources[task[0][1]].append(interval)
presences[(job_id, task_id, 0)] = model.NewConstant(1)
job_ends.append(previous_end)
job_ends.append(previous_end)
# Create machines constraints.
for machine_id in all_machines:
intervals = intervals_per_resources[machine_id]
if len(intervals) > 1:
model.AddNoOverlap(intervals)
# Create machines constraints.
for machine_id in all_machines:
intervals = intervals_per_resources[machine_id]
if len(intervals) > 1:
model.AddNoOverlap(intervals)
# Makespan objective
makespan = model.NewIntVar(0, horizon, 'makespan')
model.AddMaxEquality(makespan, job_ends)
model.Minimize(makespan)
# Makespan objective
makespan = model.NewIntVar(0, horizon, 'makespan')
model.AddMaxEquality(makespan, job_ends)
model.Minimize(makespan)
# Solve model.
solver = cp_model.CpSolver()
solution_printer = SolutionPrinter()
status = solver.SolveWithSolutionCallback(model, solution_printer)
# Solve model.
solver = cp_model.CpSolver()
solution_printer = SolutionPrinter()
status = solver.SolveWithSolutionCallback(model, solution_printer)
# Print final solution.
for job_id in all_jobs:
print('Job %i:' % job_id)
for task_id in range(len(jobs[job_id])):
start_value = solver.Value(starts[(job_id, task_id)])
machine = -1
duration = -1
selected = -1
for alt_id in range(len(jobs[job_id][task_id])):
if solver.Value(presences[(job_id, task_id, alt_id)]):
duration = jobs[job_id][task_id][alt_id][0]
machine = jobs[job_id][task_id][alt_id][1]
selected = alt_id
print(' task_%i_%i starts at %i (alt %i, machine %i, duration %i)' %
(job_id, task_id, start_value, selected, machine, duration))
# Print final solution.
for job_id in all_jobs:
print('Job %i:' % job_id)
for task_id in range(len(jobs[job_id])):
start_value = solver.Value(starts[(job_id, task_id)])
machine = -1
duration = -1
selected = -1
for alt_id in range(len(jobs[job_id][task_id])):
if solver.Value(presences[(job_id, task_id, alt_id)]):
duration = jobs[job_id][task_id][alt_id][0]
machine = jobs[job_id][task_id][alt_id][1]
selected = alt_id
print(
' task_%i_%i starts at %i (alt %i, machine %i, duration %i)' %
(job_id, task_id, start_value, selected, machine, duration))
print('Solve status: %s' % solver.StatusName(status))
print('Optimal objective value: %i' % solver.ObjectiveValue())
print('Statistics')
print(' - conflicts : %i' % solver.NumConflicts())
print(' - branches : %i' % solver.NumBranches())
print(' - wall time : %f s' % solver.WallTime())
print('Solve status: %s' % solver.StatusName(status))
print('Optimal objective value: %i' % solver.ObjectiveValue())
print('Statistics')
print(' - conflicts : %i' % solver.NumConflicts())
print(' - branches : %i' % solver.NumBranches())
print(' - wall time : %f s' % solver.WallTime())
flexible_jobshop()

6
examples/python/nqueens_sat.py
View File

@@ -26,10 +26,10 @@ class NQueenSolutionPrinter(cp_model.CpSolverSolutionCallback):
self.__solution_count = 0
self.__start_time = time.time()
def SolutionCount(self):
def solution_count(self):
return self.__solution_count
def OnSolutionCallback(self):
def on_solution_callback(self):
current_time = time.time()
print('Solution %i, time = %f s' % (self.__solution_count,
current_time - self.__start_time))
@@ -87,7 +87,7 @@ def main(board_size):
print(' - conflicts : %i' % solver.NumConflicts())
print(' - branches : %i' % solver.NumBranches())
print(' - wall time : %f ms' % solver.WallTime())
print(' - solutions found : %i' % solution_printer.SolutionCount())
print(' - solutions found : %i' % solution_printer.solution_count())
# By default, solve the 8x8 problem.

6
examples/python/nurses_sat.py
View File

@@ -28,7 +28,7 @@ class NursesPartialSolutionPrinter(cp_model.CpSolverSolutionCallback):
self.__solutions = set(sols)
self.__solution_count = 0
def OnSolutionCallback(self):
def on_solution_callback(self):
self.__solution_count += 1
if self.__solution_count in self.__solutions:
print('Solution #%i' % self.__solution_count)
@@ -40,7 +40,7 @@ class NursesPartialSolutionPrinter(cp_model.CpSolverSolutionCallback):
print(' Nurse #%i is working shift #%i' % (n, s))
print()
def SolutionCount(self):
def solution_count(self):
return self.__solution_count
@@ -126,7 +126,7 @@ def main():
print(' - conflicts : %i' % solver.NumConflicts())
print(' - branches : %i' % solver.NumBranches())
print(' - wall time : %f ms' % solver.WallTime())
print(' - solutions found : %i' % solution_printer.SolutionCount())
print(' - solutions found : %i' % solution_printer.solution_count())
if __name__ == '__main__':

6
examples/python/qubo_sat.py
View File

@@ -650,7 +650,7 @@ class ObjectiveSolutionPrinter(cp_model.CpSolverSolutionCallback):
self.__solution_count = 0
self.__start_time = time.time()
def OnSolutionCallback(self):
def on_solution_callback(self):
"""Called at each new solution."""
current_time = time.time()
objective = self.ObjectiveValue()
@@ -659,7 +659,7 @@ class ObjectiveSolutionPrinter(cp_model.CpSolverSolutionCallback):
objective, self.BestObjectiveBound()))
self.__solution_count += 1
def SolutionCount(self):
def solution_count(self):
return self.__solution_count
def solve_qubo():
@@ -706,7 +706,7 @@ def solve_qubo():
print(' - conflicts : %i' % solver.NumConflicts())
print(' - branches : %i' % solver.NumBranches())
print(' - wall time : %f ms' % solver.WallTime())
print(' - solutions found : %i' % solution_printer.SolutionCount())
print(' - solutions found : %i' % solution_printer.solution_count())
if __name__ == '__main__':

16
examples/python/rcpsp_sat.py
View File

@@ -24,15 +24,15 @@ from google.protobuf import text_format
from ortools.data import pywraprcpsp
from ortools.sat.python import cp_model
Parser = argparse.ArgumentParser()
Parser.add_argument(
PARSER = argparse.ArgumentParser()
PARSER.add_argument(
'--input', default="", help='Input file to parse and solve.')
Parser.add_argument(
PARSER.add_argument(
'--output_proto',
default="",
help='Output file to write the cp_model'
'proto to.')
Parser.add_argument('--params', default="", help='Sat solver parameters.')
PARSER.add_argument('--params', default="", help='Sat solver parameters.')
class SolutionPrinter(cp_model.CpSolverSolutionCallback):
@@ -43,7 +43,7 @@ class SolutionPrinter(cp_model.CpSolverSolutionCallback):
self.__solution_count = 0
self.__start_time = time.time()
def OnSolutionCallback(self):
def on_solution_callback(self):
current_time = time.time()
objective = self.ObjectiveValue()
print('Solution %i, time = %f s, objective = %i' %
@@ -52,7 +52,7 @@ class SolutionPrinter(cp_model.CpSolverSolutionCallback):
self.__solution_count += 1
def SolveRcpsp(problem, proto_file, params):
def solve_rcpsp(problem, proto_file, params):
"""Parse and solve a given RCPSP problem in proto format."""
# Determine problem type.
@@ -286,8 +286,8 @@ def SolveRcpsp(problem, proto_file, params):
def main(args):
rcpsp_parser = pywraprcpsp.RcpspParser()
rcpsp_parser.ParseFile(args.input)
SolveRcpsp(rcpsp_parser.Problem(), args.output_proto, args.params)
solve_rcpsp(rcpsp_parser.Problem(), args.output_proto, args.params)
if __name__ == '__main__':
main(Parser.parse_args())
main(PARSER.parse_args())

14
examples/python/shift_scheduling_sat.py
View File

@@ -21,13 +21,13 @@ from google.protobuf import text_format
from ortools.sat.python import cp_model
Parser = argparse.ArgumentParser()
Parser.add_argument(
PARSER = argparse.ArgumentParser()
PARSER.add_argument(
'--output_proto',
default="",
help='Output file to write the cp_model'
'proto to.')
Parser.add_argument('--params', default="", help='Sat solver parameters.')
PARSER.add_argument('--params', default="", help='Sat solver parameters.')
class ObjectiveSolutionPrinter(cp_model.CpSolverSolutionCallback):
@@ -38,7 +38,7 @@ class ObjectiveSolutionPrinter(cp_model.CpSolverSolutionCallback):
self.__solution_count = 0
self.__start_time = time.time()
def OnSolutionCallback(self):
def on_solution_callback(self):
"""Called on each new solution."""
current_time = time.time()
objective = self.ObjectiveValue()
@@ -47,7 +47,7 @@ class ObjectiveSolutionPrinter(cp_model.CpSolverSolutionCallback):
objective, self.BestObjectiveBound()))
self.__solution_count += 1
def SolutionCount(self):
def solution_count(self):
"""Returns the number of solutions found."""
return self.__solution_count
@@ -453,7 +453,7 @@ def solve_shift_scheduling(params, output_proto):
print(' - conflicts : %i' % solver.NumConflicts())
print(' - branches : %i' % solver.NumBranches())
print(' - wall time : %f ms' % solver.WallTime())
print(' - solutions found : %i' % solution_printer.SolutionCount())
print(' - solutions found : %i' % solution_printer.solution_count())
def main(args):
@@ -462,4 +462,4 @@ def main(args):
if __name__ == '__main__':
main(Parser.parse_args())
main(PARSER.parse_args())

2
examples/python/single_machine_scheduling_with_setup_release_due_dates_sat.py
View File

@@ -45,7 +45,7 @@ class SolutionPrinter(cp_model.CpSolverSolutionCallback):
cp_model.CpSolverSolutionCallback.__init__(self)
self.__solution_count = 0
def OnSolutionCallback(self):
def on_solution_callback(self):
print('Solution %i, time = %f s, objective = %i' %
(self.__solution_count, self.WallTime(), self.ObjectiveValue()))
self.__solution_count += 1

54
examples/python/steel_mill_slab_sat.py
View File

@@ -36,7 +36,7 @@ PARSER.add_argument(
help='Output file to write the cp_model proto to.')
def BuildProblem(problem_id):
def build_problem(problem_id):
"""Build problem data."""
if problem_id == 0:
capacities = [
@@ -270,7 +270,7 @@ class SteelMillSlabSolutionPrinter(cp_model.CpSolverSolutionCallback):
self.__all_slabs = range(len(assign[0]))
self.__start_time = time.time()
def OnSolutionCallback(self):
def on_solution_callback(self):
current_time = time.time()
objective = sum(self.Value(l) for l in self.__loss)
print('Solution %i, time = %f s, objective = %i' %
@@ -299,7 +299,7 @@ class SolutionPrinterWithObjective(cp_model.CpSolverSolutionCallback):
self.__solution_count = 0
self.__start_time = time.time()
def OnSolutionCallback(self):
def on_solution_callback(self):
current_time = time.time()
print('Solution %i, time = %f s, objective = %i' %
(self.__solution_count, current_time - self.__start_time,
@@ -307,10 +307,10 @@ class SolutionPrinterWithObjective(cp_model.CpSolverSolutionCallback):
self.__solution_count += 1
def SteelMillSlab(problem, break_symmetries, output_proto):
def steel_mill_slab(problem, break_symmetries, output_proto):
"""Solves the Steel Mill Slab Problem."""
### Load problem.
(num_slabs, capacities, num_colors, orders) = BuildProblem(problem)
(num_slabs, capacities, num_colors, orders) = build_problem(problem)
num_orders = len(orders)
num_capacities = len(capacities)
@@ -458,15 +458,15 @@ class AllSolutionsCollector(cp_model.CpSolverSolutionCallback):
self.__solutions = []
self.__variables = variables
def OnSolutionCallback(self):
def on_solution_callback(self):
solution = [self.Value(v) for v in self.__variables]
self.__solutions.append(tuple(solution))
def AllSolutions(self):
def all_solutions(self):
return self.__solutions
def CollectValidSlabs(capacities, colors, widths, loss_array, all_colors):
def collect_valid_slabs(capacities, colors, widths, loss_array, all_colors):
"""Collect valid columns (assign, loss) for one slab."""
max_capacity = max(capacities)
all_orders = range(len(colors))
@@ -505,13 +505,13 @@ def CollectValidSlabs(capacities, colors, widths, loss_array, all_colors):
collector = AllSolutionsCollector(assign + [loss, load])
solver.SearchForAllSolutions(model, collector)
print('Collect Valid Slabs...DONE')
return collector.AllSolutions()
return collector.all_solutions()
def SteelMillSlabWithValidSlabs(problem, break_symmetries, output_proto):
def steel_mill_slab_with_valid_slabs(problem, break_symmetries, output_proto):
"""Solves the Steel Mill Slab Problem."""
### Load problem.
(num_slabs, capacities, num_colors, orders) = BuildProblem(problem)
(num_slabs, capacities, num_colors, orders) = build_problem(problem)
num_orders = len(orders)
num_capacities = len(capacities)
@@ -543,8 +543,8 @@ def SteelMillSlabWithValidSlabs(problem, break_symmetries, output_proto):
]
losses = [model.NewIntVar(0, max_loss, 'loss_%i' % s) for s in all_slabs]
unsorted_valid_slabs = CollectValidSlabs(capacities, colors, widths,
loss_array, all_colors)
unsorted_valid_slabs = collect_valid_slabs(capacities, colors, widths,
loss_array, all_colors)
# Sort slab by descending load/loss. Remove duplicates.
valid_slabs = sorted(
unsorted_valid_slabs, key=lambda c: 1000 * c[-1] + c[-2])
@@ -646,14 +646,13 @@ def SteelMillSlabWithValidSlabs(problem, break_symmetries, output_proto):
print('No solution')
def SteelMillSlabWithColumnGeneration(problem, output_proto):
def steel_mill_slab_with_column_generation(problem, output_proto):
"""Solves the Steel Mill Slab Problem."""
### Load problem.
(num_slabs, capacities, num_colors, orders) = BuildProblem(problem)
(num_slabs, capacities, num_colors, orders) = build_problem(problem)
num_orders = len(orders)
num_capacities = len(capacities)
all_slabs = range(num_slabs)
all_colors = range(num_colors)
all_orders = range(len(orders))
print('Solving steel mill with %i orders, %i slabs, and %i capacities' %
@@ -671,8 +670,8 @@ def SteelMillSlabWithColumnGeneration(problem, output_proto):
### Model problem.
# Generate all valid slabs (columns)
unsorted_valid_slabs = CollectValidSlabs(capacities, colors, widths,
loss_array, all_colors)
unsorted_valid_slabs = collect_valid_slabs(capacities, colors, widths,
loss_array, all_colors)
# Sort slab by descending load/loss. Remove duplicates.
valid_slabs = sorted(
unsorted_valid_slabs, key=lambda c: 1000 * c[-1] + c[-2])
@@ -722,14 +721,13 @@ def SteelMillSlabWithColumnGeneration(problem, output_proto):
print('No solution')
def SteelMillSlabWithMipColumnGeneration(problem):
def steel_mill_slab_with_mip_column_generation(problem):
"""Solves the Steel Mill Slab Problem."""
### Load problem.
(num_slabs, capacities, num_colors, orders) = BuildProblem(problem)
(num_slabs, capacities, num_colors, orders) = build_problem(problem)
num_orders = len(orders)
num_capacities = len(capacities)
all_slabs = range(num_slabs)
all_colors = range(num_colors)
all_orders = range(len(orders))
print('Solving steel mill with %i orders, %i slabs, and %i capacities' %
@@ -748,8 +746,8 @@ def SteelMillSlabWithMipColumnGeneration(problem):
# Generate all valid slabs (columns)
start = time.time()
unsorted_valid_slabs = CollectValidSlabs(capacities, colors, widths,
loss_array, all_colors)
unsorted_valid_slabs = collect_valid_slabs(capacities, colors, widths,
loss_array, all_colors)
# Sort slab by descending load/loss. Remove duplicates.
valid_slabs = sorted(
unsorted_valid_slabs, key=lambda c: 1000 * c[-1] + c[-2])
@@ -792,14 +790,14 @@ def SteelMillSlabWithMipColumnGeneration(problem):
def main(args):
'''Main function'''
if args.solver == 'sat':
SteelMillSlab(args.problem, args.break_symmetries, args.output_proto)
steel_mill_slab(args.problem, args.break_symmetries, args.output_proto)
elif args.solver == 'sat_table':
SteelMillSlabWithValidSlabs(args.problem, args.break_symmetries,
args.output_proto)
steel_mill_slab_with_valid_slabs(args.problem, args.break_symmetries,
args.output_proto)
elif args.solver == 'sat_column':
SteelMillSlabWithColumnGeneration(args.problem, args.output_proto)
steel_mill_slab_with_column_generation(args.problem, args.output_proto)
else: # 'mip_column'
SteelMillSlabWithMipColumnGeneration(args.problem)
steel_mill_slab_with_mip_column_generation(args.problem)
if __name__ == '__main__':

2
examples/python/tasks_and_workers_assignment_sat.py
View File

@@ -24,7 +24,7 @@ class ObjectivePrinter(cp_model.CpSolverSolutionCallback):
cp_model.CpSolverSolutionCallback.__init__(self)
self.__solution_count = 0
def OnSolutionCallback(self):
def on_solution_callback(self):
print('Solution %i, time = %f s, objective = %i' %
(self.__solution_count, self.WallTime(), self.ObjectiveValue()))
self.__solution_count += 1

8
examples/python/vendor_scheduling_sat.py
View File

@@ -33,7 +33,7 @@ class SolutionPrinter(cp_model.CpSolverSolutionCallback):
self.__hours_stat = hours_stat
self.__min_vendors = min_vendors
def OnSolutionCallback(self):
def on_solution_callback(self):
"""Called at each new solution."""
self.__solution_count += 1
print('Solution %i: ', self.__solution_count)
@@ -50,7 +50,7 @@ class SolutionPrinter(cp_model.CpSolverSolutionCallback):
print()
print()
def SolutionCount(self):
def solution_count(self):
"""Returns the number of solution found."""
return self.__solution_count
@@ -137,8 +137,8 @@ def main():
print(' - conflicts : %i' % solver.NumConflicts())
print(' - branches : %i' % solver.NumBranches())
print(' - wall time : %f s' % solver.WallTime())
print(
' - number of solutions found: %i' % solution_printer.SolutionCount())
print(' - number of solutions found: %i' %
solution_printer.solution_count())
if __name__ == '__main__':

15
examples/python/wedding_optimal_chart_sat.py
View File

@@ -53,7 +53,7 @@ class WeddingChartPrinter(cp_model.CpSolverSolutionCallback):
self.__num_tables = num_tables
self.__num_guests = num_guests
def OnSolutionCallback(self):
def on_solution_callback(self):
current_time = time.time()
objective = self.ObjectiveValue()
print("Solution %i, time = %f s, objective = %i" %
@@ -67,7 +67,7 @@ class WeddingChartPrinter(cp_model.CpSolverSolutionCallback):
if self.Value(self.__seats[(t, g)]):
print(" " + self.__names[g])
def NumSolutions(self):
def num_solutions(self):
return self.__solution_count
@@ -116,7 +116,7 @@ def BuildData():
return num_tables, table_capacity, min_known_neighbors, C, names
def SolveWithDiscreteModel():
def solve_with_discrete_model():
num_tables, table_capacity, min_known_neighbors, C, names = BuildData()
num_guests = len(C)
@@ -203,12 +203,7 @@ def SolveWithDiscreteModel():
print(" - conflicts : %i" % solver.NumConflicts())
print(" - branches : %i" % solver.NumBranches())
print(" - wall time : %f ms" % solver.WallTime())
print(" - num solutions: %i" % solution_printer.NumSolutions())
print(" - num solutions: %i" % solution_printer.num_solutions())
def main():
SolveWithDiscreteModel()
if __name__ == "__main__":
main()
solve_with_discrete_model()

5
ortools/sat/python/cp_model.py
View File

@@ -1374,6 +1374,11 @@ class CpSolverSolutionCallback(pywrapsat.SolutionCallback):
and Value() methods.
"""
def OnSolutionCallback(self):
"""Proxy to the same method with different naming convention."""
self.on_solution_callback()
def BooleanValue(self, lit):
"""Returns the boolean value of a boolean literal.

4
ortools/sat/samples/channeling_sample_sat.py
View File

@@ -27,13 +27,13 @@ class VarArraySolutionPrinter(cp_model.CpSolverSolutionCallback):
self.__variables = variables
self.__solution_count = 0
def OnSolutionCallback(self):
def on_solution_callback(self):
self.__solution_count += 1
for v in self.__variables:
print('%s=%i' % (v, self.Value(v)), end=' ')
print()
def SolutionCount(self):
def solution_count(self):
return self.__solution_count

6
ortools/sat/samples/cp_is_fun_sat.py
View File

@@ -34,13 +34,13 @@ class VarArraySolutionPrinter(cp_model.CpSolverSolutionCallback):
self.__variables = variables
self.__solution_count = 0
def OnSolutionCallback(self):
def on_solution_callback(self):
self.__solution_count += 1
for v in self.__variables:
print('%s=%i' % (v, self.Value(v)), end=' ')
print()
def SolutionCount(self):
def solution_count(self):
return self.__solution_count
# [END solution_printing]
@@ -93,7 +93,7 @@ def CPIsFunSat():
print(' - conflicts : %i' % solver.NumConflicts())
print(' - branches : %i' % solver.NumBranches())
print(' - wall time : %f ms' % solver.WallTime())
print(' - solutions found : %i' % solution_printer.SolutionCount())
print(' - solutions found : %i' % solution_printer.solution_count())
if __name__ == '__main__':

6
ortools/sat/samples/search_for_all_solutions_sample_sat.py
View File

@@ -29,13 +29,13 @@ class VarArraySolutionPrinter(cp_model.CpSolverSolutionCallback):
self.__variables = variables
self.__solution_count = 0
def OnSolutionCallback(self):
def on_solution_callback(self):
self.__solution_count += 1
for v in self.__variables:
print('%s=%i' % (v, self.Value(v)), end=' ')
print()
def SolutionCount(self):
def solution_count(self):
return self.__solution_count
# [END print_solution]
@@ -68,7 +68,7 @@ def SearchForAllSolutionsSampleSat():
# [END solve]
print('Status = %s' % solver.StatusName(status))
print('Number of solutions found: %i' % solution_printer.SolutionCount())
print('Number of solutions found: %i' % solution_printer.solution_count())
SearchForAllSolutionsSampleSat()

6
ortools/sat/samples/solve_and_print_intermediate_solutions_sample_sat.py
View File

@@ -30,7 +30,7 @@ class VarArrayAndObjectiveSolutionPrinter(cp_model.CpSolverSolutionCallback):
self.__variables = variables
self.__solution_count = 0
def OnSolutionCallback(self):
def on_solution_callback(self):
print('Solution %i' % self.__solution_count)
print(' objective value = %i' % self.ObjectiveValue())
for v in self.__variables:
@@ -38,7 +38,7 @@ class VarArrayAndObjectiveSolutionPrinter(cp_model.CpSolverSolutionCallback):
print()
self.__solution_count += 1
def SolutionCount(self):
def solution_count(self):
return self.__solution_count
# [END print_solution]
@@ -75,7 +75,7 @@ def SolveAndPrintIntermediateSolutionsSampleSat():
# [END solve]
print('Status = %s' % solver.StatusName(status))
print('Number of solutions found: %i' % solution_printer.SolutionCount())
print('Number of solutions found: %i' % solution_printer.solution_count())
SolveAndPrintIntermediateSolutionsSampleSat()

8
ortools/sat/samples/stop_after_n_solutions_sample_sat.py
View File

@@ -28,7 +28,7 @@ class VarArraySolutionPrinterWithLimit(cp_model.CpSolverSolutionCallback):
self.__solution_count = 0
self.__solution_limit = limit
def OnSolutionCallback(self):
def on_solution_callback(self):
self.__solution_count += 1
for v in self.__variables:
print('%s=%i' % (v, self.Value(v)), end=' ')
@@ -37,7 +37,7 @@ class VarArraySolutionPrinterWithLimit(cp_model.CpSolverSolutionCallback):
print('Stop search after %i solutions' % self.__solution_limit)
self.StopSearch()
def SolutionCount(self):
def solution_count(self):
return self.__solution_count
@@ -56,8 +56,8 @@ def StopAfterNSolutionsSampleSat():
solution_printer = VarArraySolutionPrinterWithLimit([x, y, z], 5)
status = solver.SearchForAllSolutions(model, solution_printer)
print('Status = %s' % solver.StatusName(status))
print('Number of solutions found: %i' % solution_printer.SolutionCount())
assert solution_printer.SolutionCount() == 5
print('Number of solutions found: %i' % solution_printer.solution_count())
assert solution_printer.solution_count() == 5
StopAfterNSolutionsSampleSat()