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python: run black on all files

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This commit is contained in:
Mizux Seiha
2024-04-11 10:56:30 +02:00
committed by Corentin Le Molgat
parent 8c51109f2d
commit be220948a3
17 changed files with 574 additions and 523 deletions
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114
examples/python/arc_flow_cutting_stock_sat.py
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@@ -1,3 +1,4 @@
#!/usr/bin/env python3
# Copyright 2010-2024 Google LLC
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
@@ -10,15 +11,16 @@
# 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.
"""Cutting stock problem with the objective to minimize wasted space."""
"""Cutting stock problem with the objective to minimize wasted space."""
import collections
import time
import numpy as np
from absl import app
from absl import flags
import numpy as np
from google.protobuf import text_format
from ortools.linear_solver.python import model_builder as mb
from ortools.sat.python import cp_model
@@ -26,13 +28,14 @@ from ortools.sat.python import cp_model
FLAGS = flags.FLAGS
_OUTPUT_PROTO = flags.DEFINE_string(
'output_proto', '', 'Output file to write the cp_model proto to.')
"output_proto", "", "Output file to write the cp_model proto to."
)
_PARAMS = flags.DEFINE_string(
'params',
'num_search_workers:8,log_search_progress:true,max_time_in_seconds:10',
'Sat solver parameters.')
_SOLVER = flags.DEFINE_string(
'solver', 'sat', 'Method used to solve: sat, mip.')
"params",
"num_search_workers:8,log_search_progress:true,max_time_in_seconds:10",
"Sat solver parameters.",
)
_SOLVER = flags.DEFINE_string("solver", "sat", "Method used to solve: sat, mip.")
DESIRED_LENGTHS = [
@@ -104,9 +107,9 @@ def create_state_graph(items, max_capacity):
states.append(new_state)
state_to_index[new_state] = new_state_index
# Add the transition
transitions.append([
current_state_index, new_state_index, item_index, card + 1
])
transitions.append(
[current_state_index, new_state_index, item_index, card + 1]
)
return states, transitions
@@ -114,14 +117,19 @@ def create_state_graph(items, max_capacity):
def solve_cutting_stock_with_arc_flow_and_sat(output_proto_file: str, params: str):
"""Solve the cutting stock with arc-flow and the CP-SAT solver."""
items = regroup_and_count(DESIRED_LENGTHS)
print('Items:', items)
print("Items:", items)
num_items = len(DESIRED_LENGTHS)
max_capacity = max(POSSIBLE_CAPACITIES)
states, transitions = create_state_graph(items, max_capacity)
print('Dynamic programming has generated', len(states), 'states and',
len(transitions), 'transitions')
print(
"Dynamic programming has generated",
len(states),
"states and",
len(transitions),
"transitions",
)
incoming_vars = collections.defaultdict(list)
outgoing_vars = collections.defaultdict(list)
@@ -139,8 +147,8 @@ def solve_cutting_stock_with_arc_flow_and_sat(output_proto_file: str, params: st
count = items[item_index][1]
max_count = count // card
count_var = model.NewIntVar(
0, max_count,
'i%i_f%i_t%i_C%s' % (item_index, incoming, outgoing, card))
0, max_count, "i%i_f%i_t%i_C%s" % (item_index, incoming, outgoing, card)
)
incoming_vars[incoming].append(count_var)
outgoing_vars[outgoing].append(count_var)
item_vars[item_index].append(count_var)
@@ -150,7 +158,7 @@ def solve_cutting_stock_with_arc_flow_and_sat(output_proto_file: str, params: st
for state_index, state in enumerate(states):
if state_index == 0:
continue
exit_var = model.NewIntVar(0, num_items, 'e%i' % state_index)
exit_var = model.NewIntVar(0, num_items, "e%i" % state_index)
outgoing_vars[state_index].append(exit_var)
incoming_sink_vars.append(exit_var)
price = price_usage(state, POSSIBLE_CAPACITIES)
@@ -159,8 +167,7 @@ def solve_cutting_stock_with_arc_flow_and_sat(output_proto_file: str, params: st
# Flow conservation
for state_index in range(1, len(states)):
model.Add(
sum(incoming_vars[state_index]) == sum(outgoing_vars[state_index]))
model.Add(sum(incoming_vars[state_index]) == sum(outgoing_vars[state_index]))
# Flow going out of the source must go in the sink
model.Add(sum(outgoing_vars[0]) == sum(incoming_sink_vars))
@@ -169,13 +176,17 @@ def solve_cutting_stock_with_arc_flow_and_sat(output_proto_file: str, params: st
for item_index, size_and_count in enumerate(items):
num_arcs = len(item_vars[item_index])
model.Add(
sum(item_vars[item_index][i] * item_coeffs[item_index][i]
for i in range(num_arcs)) == size_and_count[1])
sum(
item_vars[item_index][i] * item_coeffs[item_index][i]
for i in range(num_arcs)
)
== size_and_count[1]
)
# Objective is the sum of waste
model.Minimize(
sum(objective_vars[i] * objective_coeffs[i]
for i in range(len(objective_vars))))
sum(objective_vars[i] * objective_coeffs[i] for i in range(len(objective_vars)))
)
# Output model proto to file.
if output_proto_file:
@@ -192,13 +203,18 @@ def solve_cutting_stock_with_arc_flow_and_sat(output_proto_file: str, params: st
def solve_cutting_stock_with_arc_flow_and_mip():
"""Solve the cutting stock with arc-flow and a MIP solver."""
items = regroup_and_count(DESIRED_LENGTHS)
print('Items:', items)
print("Items:", items)
num_items = len(DESIRED_LENGTHS)
max_capacity = max(POSSIBLE_CAPACITIES)
states, transitions = create_state_graph(items, max_capacity)
print('Dynamic programming has generated', len(states), 'states and',
len(transitions), 'transitions')
print(
"Dynamic programming has generated",
len(states),
"states and",
len(transitions),
"transitions",
)
incoming_vars = collections.defaultdict(list)
outgoing_vars = collections.defaultdict(list)
@@ -216,8 +232,10 @@ def solve_cutting_stock_with_arc_flow_and_mip():
for outgoing, incoming, item_index, card in transitions:
count = items[item_index][1]
count_var = model.new_int_var(
0, count, 'a%i_i%i_f%i_t%i_c%i' % (var_index, item_index, incoming,
outgoing, card))
0,
count,
"a%i_i%i_f%i_t%i_c%i" % (var_index, item_index, incoming, outgoing, card),
)
var_index += 1
incoming_vars[incoming].append(count_var)
outgoing_vars[outgoing].append(count_var)
@@ -227,7 +245,7 @@ def solve_cutting_stock_with_arc_flow_and_mip():
for state_index, state in enumerate(states):
if state_index == 0:
continue
exit_var = model.new_int_var(0, num_items, 'e%i' % state_index)
exit_var = model.new_int_var(0, num_items, "e%i" % state_index)
outgoing_vars[state_index].append(exit_var)
incoming_sink_vars.append(exit_var)
price = price_usage(state, POSSIBLE_CAPACITIES)
@@ -237,44 +255,52 @@ def solve_cutting_stock_with_arc_flow_and_mip():
# Flow conservation
for state_index in range(1, len(states)):
model.add(
mb.LinearExpr.sum(incoming_vars[state_index]) == mb.LinearExpr.sum(
outgoing_vars[state_index]))
mb.LinearExpr.sum(incoming_vars[state_index])
== mb.LinearExpr.sum(outgoing_vars[state_index])
)
# Flow going out of the source must go in the sink
model.add(
mb.LinearExpr.sum(outgoing_vars[0]) == mb.LinearExpr.sum(
incoming_sink_vars))
mb.LinearExpr.sum(outgoing_vars[0]) == mb.LinearExpr.sum(incoming_sink_vars)
)
# Items must be placed
for item_index, size_and_count in enumerate(items):
num_arcs = len(item_vars[item_index])
model.add(
mb.LinearExpr.sum([item_vars[item_index][i] * item_coeffs[item_index][i]
for i in range(num_arcs)]) == size_and_count[1])
mb.LinearExpr.sum(
[
item_vars[item_index][i] * item_coeffs[item_index][i]
for i in range(num_arcs)
]
)
== size_and_count[1]
)
# Objective is the sum of waste
model.minimize(np.dot(objective_vars, objective_coeffs))
solver = mb.ModelSolver('scip')
solver = mb.ModelSolver("scip")
solver.enable_output(True)
status = solver.solve(model)
### Output the solution.
if status == mb.SolveStatus.OPTIMAL or status == mb.SolveStatus.FEASIBLE:
print('Objective value = %f found in %.2f s' %
(solver.objective_value, time.time() - start_time))
print(
"Objective value = %f found in %.2f s"
% (solver.objective_value, time.time() - start_time)
)
else:
print('No solution')
print("No solution")
def main(_):
"""Main function"""
if _SOLVER.value == 'sat':
solve_cutting_stock_with_arc_flow_and_sat(_OUTPUT_PROTO.value,
_PARAMS.value)
"""Main function."""
if _SOLVER.value == "sat":
solve_cutting_stock_with_arc_flow_and_sat(_OUTPUT_PROTO.value, _PARAMS.value)
else: # 'mip'
solve_cutting_stock_with_arc_flow_and_mip()
if __name__ == '__main__':
if __name__ == "__main__":
app.run(main)

1
examples/python/testdata/BUILD.bazel vendored
View File

@@ -18,4 +18,3 @@ exports_files(
"salbp_20_1.alb",
],
)