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This commit is contained in:
Laurent Perron
2023-06-27 14:21:34 +02:00
parent be9d0e6041
commit a743431365
15 changed files with 1636 additions and 1371 deletions
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22
examples/python/rcpsp_sat.py
View File

@@ -27,18 +27,18 @@ from absl import app
from absl import flags
from google.protobuf import text_format
from ortools.sat.python import cp_model
from ortools.scheduling import pywraprcpsp
from ortools.scheduling import rcpsp_pb2
FLAGS = flags.FLAGS
from ortools.scheduling import pywraprcpsp
_INPUT = flags.DEFINE_string('input', '', 'Input file to parse and solve.')
_OUTPUT_PROTO = flags.DEFINE_string(
'output_proto', '', 'Output file to write the cp_model proto to.')
_PARAMS = flags.DEFINE_string('params', '', 'Sat solver parameters.')
_USE_INTERVAL_MAKESPAN = flags.DEFINE_bool(
'use_interval_makespan', True,
'Whether we encode the makespan using an interval or not.')
'use_interval_makespan',
False,
'Whether we encode the makespan using an interval or not.',
)
_HORIZON = flags.DEFINE_integer('horizon', -1, 'Force horizon.')
_ADD_REDUNDANT_ENERGETIC_CONSTRAINTS = flags.DEFINE_bool(
'add_redundant_energetic_constraints', False,
@@ -213,7 +213,7 @@ def SolveRcpsp(problem,
lower_bound: A valid lower bound of the makespan objective.
Returns:
(lower_bound of the objective, best solution found, asssignment)
(lower_bound of the objective, best solution found, assignment)
"""
# Create the model.
model = cp_model.CpModel()
@@ -350,8 +350,7 @@ def SolveRcpsp(problem,
task = problem.tasks[task_id]
num_modes = len(task.recipes)
for successor_index in range(len(task.successors)):
next_id = task.successors[successor_index]
for successor_index, next_id in enumerate(task.successors):
delay_matrix = task.successor_delays[successor_index]
num_next_modes = len(problem.tasks[next_id].recipes)
for m1 in range(num_modes):
@@ -510,6 +509,9 @@ def SolveRcpsp(problem,
# Solve model.
solver = cp_model.CpSolver()
if not _USE_INTERVAL_MAKESPAN.value:
solver.parameters.exploit_all_precedences = True
solver.parameters.use_hard_precedences_in_cumulative = True
if params:
text_format.Parse(params, solver.parameters)
if in_main_solve:
@@ -517,7 +519,7 @@ def SolveRcpsp(problem,
status = solver.Solve(model)
if status == cp_model.OPTIMAL or status == cp_model.FEASIBLE:
assignment = rcpsp_pb2.RcpspAssignment()
for t in range(len(problem.tasks)):
for t, _ in enumerate(problem.tasks):
if t in task_starts:
assignment.start_of_task.append(solver.Value(task_starts[t]))
for r in range(len(task_to_presence_literals[t])):
@@ -666,7 +668,7 @@ def ComputePreemptiveLowerBound(problem, after, lower_bound):
min_duration = max_duration
for t in c:
min_duration = min(min_duration, duration_map[t])
count = model.NewIntVar(0, min_duration, f'count_{t}')
count = model.NewIntVar(0, min_duration, f'count_{c}')
all_vars.append(count)
for t in c:
vars_per_task[t].append(count)

129
ortools/algorithms/samples/knapsack.py
View File

@@ -11,6 +11,7 @@
# 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.
"""A simple knapsack problem."""
# [START program]
# [START import]
@@ -22,22 +23,118 @@ def main():
# Create the solver.
# [START solver]
solver = pywrapknapsack_solver.KnapsackSolver(
pywrapknapsack_solver.KnapsackSolver.
KNAPSACK_MULTIDIMENSION_BRANCH_AND_BOUND_SOLVER, 'KnapsackExample')
pywrapknapsack_solver.KnapsackSolver.KNAPSACK_MULTIDIMENSION_BRANCH_AND_BOUND_SOLVER,
"KnapsackExample",
)
# [END solver]
# [START data]
values = [
360, 83, 59, 130, 431, 67, 230, 52, 93, 125, 670, 892, 600, 38, 48, 147,
78, 256, 63, 17, 120, 164, 432, 35, 92, 110, 22, 42, 50, 323, 514, 28,
87, 73, 78, 15, 26, 78, 210, 36, 85, 189, 274, 43, 33, 10, 19, 389, 276,
312
360,
83,
59,
130,
431,
67,
230,
52,
93,
125,
670,
892,
600,
38,
48,
147,
78,
256,
63,
17,
120,
164,
432,
35,
92,
110,
22,
42,
50,
323,
514,
28,
87,
73,
78,
15,
26,
78,
210,
36,
85,
189,
274,
43,
33,
10,
19,
389,
276,
312,
]
weights = [
[
7,
0,
30,
22,
80,
94,
11,
81,
70,
64,
59,
18,
0,
36,
3,
8,
15,
42,
9,
0,
42,
47,
52,
32,
26,
48,
55,
6,
29,
84,
2,
4,
18,
56,
7,
29,
93,
44,
71,
3,
86,
66,
31,
65,
0,
79,
20,
65,
52,
13,
]
]
weights = [[
7, 0, 30, 22, 80, 94, 11, 81, 70, 64, 59, 18, 0, 36, 3, 8, 15, 42, 9, 0,
42, 47, 52, 32, 26, 48, 55, 6, 29, 84, 2, 4, 18, 56, 7, 29, 93, 44, 71,
3, 86, 66, 31, 65, 0, 79, 20, 65, 52, 13
]]
capacities = [850]
# [END data]
@@ -50,18 +147,18 @@ def main():
packed_items = []
packed_weights = []
total_weight = 0
print('Total value =', computed_value)
print("Total value =", computed_value)
for i in range(len(values)):
if solver.BestSolutionContains(i):
packed_items.append(i)
packed_weights.append(weights[0][i])
total_weight += weights[0][i]
print('Total weight:', total_weight)
print('Packed items:', packed_items)
print('Packed_weights:', packed_weights)
print("Total weight:", total_weight)
print("Packed items:", packed_items)
print("Packed_weights:", packed_weights)
# [END print_solution]
if __name__ == '__main__':
if __name__ == "__main__":
main()
# [END program]

30
ortools/algorithms/samples/simple_knapsack_program.py
View File

@@ -23,15 +23,33 @@ def main():
# Create the solver.
# [START solver]
solver = pywrapknapsack_solver.KnapsackSolver(
pywrapknapsack_solver.KnapsackSolver.
KNAPSACK_DYNAMIC_PROGRAMMING_SOLVER, "test")
pywrapknapsack_solver.KnapsackSolver.KNAPSACK_DYNAMIC_PROGRAMMING_SOLVER, "test"
)
# [END solver]
# [START data]
weights = [[
565, 406, 194, 130, 435, 367, 230, 315, 393, 125, 670, 892, 600, 293,
712, 147, 421, 255
]]
weights = [
[
565,
406,
194,
130,
435,
367,
230,
315,
393,
125,
670,
892,
600,
293,
712,
147,
421,
255,
]
]
capacities = [850]
values = weights[0]
# [END data]

32
ortools/graph/samples/assignment_linear_sum_assignment.py
View File

@@ -28,17 +28,20 @@ def main():
# [END solver]
# [START data]
costs = np.array([
[90, 76, 75, 70],
[35, 85, 55, 65],
[125, 95, 90, 105],
[45, 110, 95, 115],
])
costs = np.array(
[
[90, 76, 75, 70],
[35, 85, 55, 65],
[125, 95, 90, 105],
[45, 110, 95, 115],
]
)
# Let's transform this into 3 parallel vectors (start_nodes, end_nodes,
# arc_costs)
end_nodes_unraveled, start_nodes_unraveled = np.meshgrid(
np.arange(costs.shape[1]), np.arange(costs.shape[0]))
np.arange(costs.shape[1]), np.arange(costs.shape[0])
)
start_nodes = start_nodes_unraveled.ravel()
end_nodes = end_nodes_unraveled.ravel()
arc_costs = costs.ravel()
@@ -54,18 +57,19 @@ def main():
# [START print_solution]
if status == assignment.OPTIMAL:
print(f'Total cost = {assignment.optimal_cost()}\n')
print(f"Total cost = {assignment.optimal_cost()}\n")
for i in range(0, assignment.num_nodes()):
print(f'Worker {i} assigned to task {assignment.right_mate(i)}.' +
f' Cost = {assignment.assignment_cost(i)}')
print(
f"Worker {i} assigned to task {assignment.right_mate(i)}."
+ f" Cost = {assignment.assignment_cost(i)}"
)
elif status == assignment.INFEASIBLE:
print('No assignment is possible.')
print("No assignment is possible.")
elif status == assignment.POSSIBLE_OVERFLOW:
print(
'Some input costs are too large and may cause an integer overflow.')
print("Some input costs are too large and may cause an integer overflow.")
# [END print_solution]
if __name__ == '__main__':
if __name__ == "__main__":
main()
# [END Program]

44
ortools/graph/samples/assignment_min_flow.py
View File

@@ -28,18 +28,20 @@ def main():
# [START data]
# Define the directed graph for the flow.
start_nodes = [0, 0, 0, 0] + [
1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4
] + [5, 6, 7, 8]
end_nodes = [1, 2, 3, 4] + [5, 6, 7, 8, 5, 6, 7, 8, 5, 6, 7, 8, 5, 6, 7, 8
] + [9, 9, 9, 9]
capacities = [1, 1, 1, 1] + [
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1
] + [1, 1, 1, 1]
start_nodes = (
[0, 0, 0, 0] + [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4] + [5, 6, 7, 8]
)
end_nodes = (
[1, 2, 3, 4] + [5, 6, 7, 8, 5, 6, 7, 8, 5, 6, 7, 8, 5, 6, 7, 8] + [9, 9, 9, 9]
)
capacities = (
[1, 1, 1, 1] + [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] + [1, 1, 1, 1]
)
costs = (
[0, 0, 0, 0] +
[90, 76, 75, 70, 35, 85, 55, 65, 125, 95, 90, 105, 45, 110, 95, 115] +
[0, 0, 0, 0])
[0, 0, 0, 0]
+ [90, 76, 75, 70, 35, 85, 55, 65, 125, 95, 90, 105, 45, 110, 95, 115]
+ [0, 0, 0, 0]
)
source = 0
sink = 9
@@ -50,8 +52,9 @@ def main():
# [START constraints]
# Add each arc.
for i in range(len(start_nodes)):
smcf.add_arc_with_capacity_and_unit_cost(start_nodes[i], end_nodes[i],
capacities[i], costs[i])
smcf.add_arc_with_capacity_and_unit_cost(
start_nodes[i], end_nodes[i], capacities[i], costs[i]
)
# Add node supplies.
for i in range(len(supplies)):
smcf.set_node_supply(i, supplies[i])
@@ -64,23 +67,24 @@ def main():
# [START print_solution]
if status == smcf.OPTIMAL:
print('Total cost = ', smcf.optimal_cost())
print("Total cost = ", smcf.optimal_cost())
print()
for arc in range(smcf.num_arcs()):
# Can ignore arcs leading out of source or into sink.
if smcf.tail(arc) != source and smcf.head(arc) != sink:
# Arcs in the solution have a flow value of 1. Their start and end nodes
# give an assignment of worker to task.
if smcf.flow(arc) > 0:
print('Worker %d assigned to task %d. Cost = %d' %
(smcf.tail(arc), smcf.head(arc), smcf.unit_cost(arc)))
print(
"Worker %d assigned to task %d. Cost = %d"
% (smcf.tail(arc), smcf.head(arc), smcf.unit_cost(arc))
)
else:
print('There was an issue with the min cost flow input.')
print(f'Status: {status}')
print("There was an issue with the min cost flow input.")
print(f"Status: {status}")
# [END print_solution]
if __name__ == '__main__':
if __name__ == "__main__":
main()
# [END program]

95
ortools/graph/samples/balance_min_flow.py
View File

@@ -30,20 +30,59 @@ def main():
team_a = [1, 3, 5]
team_b = [2, 4, 6]
start_nodes = ([0, 0] + [11, 11, 11] + [12, 12, 12] + [
1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6
] + [7, 8, 9, 10])
end_nodes = ([11, 12] + team_a + team_b + [
7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8,
9, 10
] + [13, 13, 13, 13])
capacities = ([2, 2] + [1, 1, 1] + [1, 1, 1] + [
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1
] + [1, 1, 1, 1])
costs = ([0, 0] + [0, 0, 0] + [0, 0, 0] + [
90, 76, 75, 70, 35, 85, 55, 65, 125, 95, 90, 105, 45, 110, 95, 115, 60,
105, 80, 75, 45, 65, 110, 95
] + [0, 0, 0, 0])
start_nodes = (
[0, 0]
+ [11, 11, 11]
+ [12, 12, 12]
+ [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6]
+ [7, 8, 9, 10]
)
end_nodes = (
[11, 12]
+ team_a
+ team_b
+ [7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10]
+ [13, 13, 13, 13]
)
capacities = (
[2, 2]
+ [1, 1, 1]
+ [1, 1, 1]
+ [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
+ [1, 1, 1, 1]
)
costs = (
[0, 0]
+ [0, 0, 0]
+ [0, 0, 0]
+ [
90,
76,
75,
70,
35,
85,
55,
65,
125,
95,
90,
105,
45,
110,
95,
115,
60,
105,
80,
75,
45,
65,
110,
95,
]
+ [0, 0, 0, 0]
)
source = 0
sink = 13
@@ -55,8 +94,9 @@ def main():
# [START constraints]
# Add each arc.
for i in range(0, len(start_nodes)):
smcf.add_arc_with_capacity_and_unit_cost(start_nodes[i], end_nodes[i],
capacities[i], costs[i])
smcf.add_arc_with_capacity_and_unit_cost(
start_nodes[i], end_nodes[i], capacities[i], costs[i]
)
# Add node supplies.
for i in range(0, len(supplies)):
@@ -70,24 +110,29 @@ def main():
# [START print_solution]
if status == smcf.OPTIMAL:
print('Total cost = ', smcf.optimal_cost())
print("Total cost = ", smcf.optimal_cost())
print()
for arc in range(smcf.num_arcs()):
# Can ignore arcs leading out of source or intermediate, or into sink.
if (smcf.tail(arc) != source and smcf.tail(arc) != 11 and
smcf.tail(arc) != 12 and smcf.head(arc) != sink):
if (
smcf.tail(arc) != source
and smcf.tail(arc) != 11
and smcf.tail(arc) != 12
and smcf.head(arc) != sink
):
# Arcs in the solution will have a flow value of 1.
# There start and end nodes give an assignment of worker to task.
if smcf.flow(arc) > 0:
print('Worker %d assigned to task %d. Cost = %d' %
(smcf.tail(arc), smcf.head(arc), smcf.unit_cost(arc)))
print(
"Worker %d assigned to task %d. Cost = %d"
% (smcf.tail(arc), smcf.head(arc), smcf.unit_cost(arc))
)
else:
print('There was an issue with the min cost flow input.')
print(f'Status: {status}')
print("There was an issue with the min cost flow input.")
print(f"Status: {status}")
# [END print_solution]
if __name__ == '__main__':
if __name__ == "__main__":
main()
# [END program]

18
ortools/graph/samples/simple_max_flow_program.py
View File

@@ -50,20 +50,20 @@ def main():
# [START print_solution]
if status != smf.OPTIMAL:
print('There was an issue with the max flow input.')
print(f'Status: {status}')
print("There was an issue with the max flow input.")
print(f"Status: {status}")
exit(1)
print('Max flow:', smf.optimal_flow())
print('')
print(' Arc Flow / Capacity')
print("Max flow:", smf.optimal_flow())
print("")
print(" Arc Flow / Capacity")
solution_flows = smf.flows(all_arcs)
for arc, flow, capacity in zip(all_arcs, solution_flows, capacities):
print(f'{smf.tail(arc)} / {smf.head(arc)} {flow:3} / {capacity:3}')
print('Source side min-cut:', smf.get_source_side_min_cut())
print('Sink side min-cut:', smf.get_sink_side_min_cut())
print(f"{smf.tail(arc)} / {smf.head(arc)} {flow:3} / {capacity:3}")
print("Source side min-cut:", smf.get_source_side_min_cut())
print("Sink side min-cut:", smf.get_sink_side_min_cut())
# [END print_solution]
if __name__ == '__main__':
if __name__ == "__main__":
main()
# [END program]

17
ortools/graph/samples/simple_min_cost_flow_program.py
View File

@@ -44,7 +44,8 @@ def main():
# [START constraints]
# Add arcs, capacities and costs in bulk using numpy.
all_arcs = smcf.add_arcs_with_capacity_and_unit_cost(
start_nodes, end_nodes, capacities, unit_costs)
start_nodes, end_nodes, capacities, unit_costs
)
# Add supply for each nodes.
smcf.set_nodes_supplies(np.arange(0, len(supplies)), supplies)
@@ -57,21 +58,21 @@ def main():
# [START print_solution]
if status != smcf.OPTIMAL:
print('There was an issue with the min cost flow input.')
print(f'Status: {status}')
print("There was an issue with the min cost flow input.")
print(f"Status: {status}")
exit(1)
print(f'Minimum cost: {smcf.optimal_cost()}')
print('')
print(' Arc Flow / Capacity Cost')
print(f"Minimum cost: {smcf.optimal_cost()}")
print("")
print(" Arc Flow / Capacity Cost")
solution_flows = smcf.flows(all_arcs)
costs = solution_flows * unit_costs
for arc, flow, cost in zip(all_arcs, solution_flows, costs):
print(
f'{smcf.tail(arc):1} -> {smcf.head(arc)} {flow:3} / {smcf.capacity(arc):3} {cost}'
f"{smcf.tail(arc):1} -> {smcf.head(arc)} {flow:3} / {smcf.capacity(arc):3} {cost}"
)
# [END print_solution]
if __name__ == '__main__':
if __name__ == "__main__":
main()
# [END program]

26
ortools/init/python/pywrapinit_test.py
View File

@@ -11,6 +11,7 @@
# 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.
"""Simple unit tests for python/init.i. Not exhaustive."""
import unittest
@@ -18,26 +19,25 @@ from ortools.init import pywrapinit
class PyWrapInit(unittest.TestCase):
def test_logging(self):
print('test_logging')
pywrapinit.CppBridge.InitLogging('pywrapinit_test.py')
print("test_logging")
pywrapinit.CppBridge.InitLogging("pywrapinit_test.py")
pywrapinit.CppBridge.ShutdownLogging()
def test_flags(self):
print('test_cpp_flags')
print("test_cpp_flags")
cpp_flags = pywrapinit.CppFlags()
# print(f'{dir(cpp_flags)}')
assert hasattr(cpp_flags, 'stderrthreshold')
assert hasattr(cpp_flags, 'log_prefix')
assert hasattr(cpp_flags, 'cp_model_dump_prefix')
assert hasattr(cpp_flags, 'cp_model_dump_models')
assert hasattr(cpp_flags, 'cp_model_dump_lns')
assert hasattr(cpp_flags, 'cp_model_dump_response')
assert hasattr(cpp_flags, "stderrthreshold")
assert hasattr(cpp_flags, "log_prefix")
assert hasattr(cpp_flags, "cp_model_dump_prefix")
assert hasattr(cpp_flags, "cp_model_dump_models")
assert hasattr(cpp_flags, "cp_model_dump_lns")
assert hasattr(cpp_flags, "cp_model_dump_response")
pywrapinit.CppBridge.SetFlags(cpp_flags)
def test_version(self):
print('test_version')
print("test_version")
major = pywrapinit.OrToolsVersion.MajorNumber()
self.assertIsInstance(major, int)
minor = pywrapinit.OrToolsVersion.MinorNumber()
@@ -46,9 +46,9 @@ class PyWrapInit(unittest.TestCase):
self.assertIsInstance(patch, int)
version = pywrapinit.OrToolsVersion.VersionString()
self.assertIsInstance(version, str)
string = f'{major}.{minor}.{patch}'
string = f"{major}.{minor}.{patch}"
self.assertEqual(version, string)
if __name__ == '__main__':
if __name__ == "__main__":
unittest.main()

1520
ortools/sat/python/cp_model.py
View File

File diff suppressed because it is too large Load Diff

32
ortools/sat/python/cp_model_helper.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.
"""helpers methods for the cp_model module."""
import numbers
@@ -28,56 +29,56 @@ def is_integral(x):
def is_a_number(x):
"""Checks if x has either a number.Number or a np.double type."""
return isinstance(x, numbers.Number) or isinstance(
x, np.double) or isinstance(x, np.integer)
return (
isinstance(x, numbers.Number)
or isinstance(x, np.double)
or isinstance(x, np.integer)
)
def is_zero(x):
"""Checks if the x is 0 or 0.0."""
return (is_integral(x) and int(x) == 0) or (is_a_number(x) and
float(x) == 0.0)
return (is_integral(x) and int(x) == 0) or (is_a_number(x) and float(x) == 0.0)
def is_one(x):
"""Checks if x is 1 or 1.0."""
return (is_integral(x) and int(x) == 1) or (is_a_number(x) and
float(x) == 1.0)
return (is_integral(x) and int(x) == 1) or (is_a_number(x) and float(x) == 1.0)
def is_minus_one(x):
"""Checks if x is -1 or -1.0."""
return (is_integral(x) and int(x) == -1) or (is_a_number(x) and
float(x) == -1.0)
return (is_integral(x) and int(x) == -1) or (is_a_number(x) and float(x) == -1.0)
def assert_is_int64(x):
"""Asserts that x is integer and x is in [min_int_64, max_int_64]."""
if not is_integral(x):
raise TypeError('Not an integer: %s' % x)
raise TypeError("Not an integer: %s" % x)
if x < INT_MIN or x > INT_MAX:
raise OverflowError('Does not fit in an int64_t: %s' % x)
raise OverflowError("Does not fit in an int64_t: %s" % x)
return int(x)
def assert_is_int32(x):
"""Asserts that x is integer and x is in [min_int_32, max_int_32]."""
if not is_integral(x):
raise TypeError('Not an integer: %s' % x)
raise TypeError("Not an integer: %s" % x)
if x < INT32_MIN or x > INT32_MAX:
raise OverflowError('Does not fit in an int32_t: %s' % x)
raise OverflowError("Does not fit in an int32_t: %s" % x)
return int(x)
def assert_is_boolean(x):
"""Asserts that x is 0 or 1."""
if not is_integral(x) or x < 0 or x > 1:
raise TypeError('Not a boolean: %s' % x)
raise TypeError("Not a boolean: %s" % x)
def assert_is_a_number(x):
"""Asserts that x is a number and returns it."""
if not is_a_number(x):
raise TypeError('Not a number: %s' % x)
raise TypeError("Not a number: %s" % x)
elif is_integral(x):
return int(x)
else:
@@ -101,8 +102,7 @@ def capped_subtraction(x, y):
return x
if x == y:
if x == INT_MAX or x == INT_MIN:
raise OverflowError(
'Integer NaN: subtracting INT_MAX or INT_MIN to itself')
raise OverflowError("Integer NaN: subtracting INT_MAX or INT_MIN to itself")
return 0
if x == INT_MAX or x == INT_MIN:
return x

71
ortools/sat/python/cp_model_helper_test.py
View File

@@ -11,6 +11,7 @@
# 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.
"""Tests for ortools.sat.python.cp_model_helper."""
from absl.testing import absltest
@@ -18,64 +19,80 @@ from ortools.sat.python import cp_model_helper
class CpModelHelperTest(absltest.TestCase):
def testassert_is_int64(self):
print('testassert_is_int64')
self.assertRaises(TypeError, cp_model_helper.assert_is_int64, 'Hello')
print("testassert_is_int64")
self.assertRaises(TypeError, cp_model_helper.assert_is_int64, "Hello")
self.assertRaises(TypeError, cp_model_helper.assert_is_int64, 1.2)
self.assertRaises(OverflowError, cp_model_helper.assert_is_int64, 2**63)
self.assertRaises(OverflowError, cp_model_helper.assert_is_int64,
-2**63 - 1)
self.assertRaises(
OverflowError, cp_model_helper.assert_is_int64, -(2**63) - 1
)
cp_model_helper.assert_is_int64(123)
cp_model_helper.assert_is_int64(2**63 - 1)
cp_model_helper.assert_is_int64(-2**63)
cp_model_helper.assert_is_int64(-(2**63))
def testto_capped_int64(self):
print('testto_capped_int64')
print("testto_capped_int64")
self.assertEqual(
cp_model_helper.to_capped_int64(cp_model_helper.INT_MAX),
cp_model_helper.INT_MAX)
cp_model_helper.INT_MAX,
)
self.assertEqual(
cp_model_helper.to_capped_int64(cp_model_helper.INT_MAX + 1),
cp_model_helper.INT_MAX)
cp_model_helper.INT_MAX,
)
self.assertEqual(
cp_model_helper.to_capped_int64(cp_model_helper.INT_MIN),
cp_model_helper.INT_MIN)
cp_model_helper.INT_MIN,
)
self.assertEqual(
cp_model_helper.to_capped_int64(cp_model_helper.INT_MIN - 1),
cp_model_helper.INT_MIN)
cp_model_helper.INT_MIN,
)
self.assertEqual(cp_model_helper.to_capped_int64(15), 15)
def testcapped_subtraction(self):
print('testcapped_subtraction')
print("testcapped_subtraction")
self.assertEqual(cp_model_helper.capped_subtraction(10, 5), 5)
self.assertEqual(
cp_model_helper.capped_subtraction(cp_model_helper.INT_MIN, 5),
cp_model_helper.INT_MIN)
cp_model_helper.INT_MIN,
)
self.assertEqual(
cp_model_helper.capped_subtraction(cp_model_helper.INT_MIN, -5),
cp_model_helper.INT_MIN)
cp_model_helper.INT_MIN,
)
self.assertEqual(
cp_model_helper.capped_subtraction(cp_model_helper.INT_MAX, 5),
cp_model_helper.INT_MAX)
cp_model_helper.INT_MAX,
)
self.assertEqual(
cp_model_helper.capped_subtraction(cp_model_helper.INT_MAX, -5),
cp_model_helper.INT_MAX)
cp_model_helper.INT_MAX,
)
self.assertEqual(
cp_model_helper.capped_subtraction(2, cp_model_helper.INT_MIN),
cp_model_helper.INT_MAX)
cp_model_helper.INT_MAX,
)
self.assertEqual(
cp_model_helper.capped_subtraction(2, cp_model_helper.INT_MAX),
cp_model_helper.INT_MIN)
self.assertRaises(OverflowError, cp_model_helper.capped_subtraction,
cp_model_helper.INT_MAX, cp_model_helper.INT_MAX)
self.assertRaises(OverflowError, cp_model_helper.capped_subtraction,
cp_model_helper.INT_MIN, cp_model_helper.INT_MIN)
self.assertRaises(TypeError, cp_model_helper.capped_subtraction, 5,
'dummy')
self.assertRaises(TypeError, cp_model_helper.capped_subtraction,
'dummy', 5)
cp_model_helper.INT_MIN,
)
self.assertRaises(
OverflowError,
cp_model_helper.capped_subtraction,
cp_model_helper.INT_MAX,
cp_model_helper.INT_MAX,
)
self.assertRaises(
OverflowError,
cp_model_helper.capped_subtraction,
cp_model_helper.INT_MIN,
cp_model_helper.INT_MIN,
)
self.assertRaises(TypeError, cp_model_helper.capped_subtraction, 5, "dummy")
self.assertRaises(TypeError, cp_model_helper.capped_subtraction, "dummy", 5)
if __name__ == '__main__':
if __name__ == "__main__":
absltest.main()

916
ortools/sat/python/cp_model_test.py
View File

File diff suppressed because it is too large Load Diff

46
ortools/sat/python/swig_helper_test.py
View File

@@ -11,6 +11,7 @@
# 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.
"""Tests for ortools.sat.python.swig_helper."""
from absl.testing import absltest
@@ -21,13 +22,12 @@ from ortools.sat.python import swig_helper
class Callback(swig_helper.SolutionCallback):
def __init__(self):
swig_helper.SolutionCallback.__init__(self)
self.__solution_count = 0
def OnSolutionCallback(self):
print('New Solution')
print("New Solution")
self.__solution_count += 1
def SolutionCount(self):
@@ -35,7 +35,6 @@ class Callback(swig_helper.SolutionCallback):
class SwigHelperTest(absltest.TestCase):
def testVariableDomain(self):
model_string = """
variables { domain: [ -10, 10 ] }
@@ -45,9 +44,11 @@ class SwigHelperTest(absltest.TestCase):
self.assertTrue(text_format.Parse(model_string, model))
d0 = swig_helper.CpSatHelper.SerializedVariableDomain(
model.variables[0].SerializeToString())
model.variables[0].SerializeToString()
)
d1 = swig_helper.CpSatHelper.SerializedVariableDomain(
model.variables[1].SerializeToString())
model.variables[1].SerializeToString()
)
self.assertEqual(d0.FlattenedIntervals(), [-10, 10])
self.assertEqual(d1.FlattenedIntervals(), [-5, -5, 3, 6])
@@ -89,8 +90,10 @@ class SwigHelperTest(absltest.TestCase):
solve_wrapper = swig_helper.SolveWrapper()
solution = cp_model_pb2.CpSolverResponse.FromString(
swig_helper.SolveWrapper.SerializedSolve(model.SerializeToString(),
solve_wrapper))
swig_helper.SolveWrapper.SerializedSolve(
model.SerializeToString(), solve_wrapper
)
)
self.assertEqual(cp_model_pb2.OPTIMAL, solution.status)
self.assertEqual(30.0, solution.objective_value)
@@ -135,10 +138,13 @@ class SwigHelperTest(absltest.TestCase):
solve_wrapper = swig_helper.SolveWrapper()
swig_helper.SolveWrapper.SetSerializedParameters(
parameters.SerializeToString(), solve_wrapper)
parameters.SerializeToString(), solve_wrapper
)
solution = cp_model_pb2.CpSolverResponse.FromString(
swig_helper.SolveWrapper.SerializedSolve(model.SerializeToString(),
solve_wrapper))
swig_helper.SolveWrapper.SerializedSolve(
model.SerializeToString(), solve_wrapper
)
)
self.assertEqual(cp_model_pb2.OPTIMAL, solution.status)
self.assertEqual(30.0, solution.objective_value)
@@ -161,8 +167,10 @@ class SwigHelperTest(absltest.TestCase):
solve_wrapper = swig_helper.SolveWrapper()
solution = cp_model_pb2.CpSolverResponse.FromString(
swig_helper.SolveWrapper.SerializedSolve(model.SerializeToString(),
solve_wrapper))
swig_helper.SolveWrapper.SerializedSolve(
model.SerializeToString(), solve_wrapper
)
)
self.assertEqual(cp_model_pb2.OPTIMAL, solution.status)
self.assertEqual(30.0, solution.objective_value)
@@ -184,10 +192,13 @@ class SwigHelperTest(absltest.TestCase):
params = sat_parameters_pb2.SatParameters()
params.enumerate_all_solutions = True
swig_helper.SolveWrapper.SetSerializedParameters(
params.SerializeToString(), solve_wrapper)
params.SerializeToString(), solve_wrapper
)
solution = cp_model_pb2.CpSolverResponse.FromString(
swig_helper.SolveWrapper.SerializedSolve(model.SerializeToString(),
solve_wrapper))
swig_helper.SolveWrapper.SerializedSolve(
model.SerializeToString(), solve_wrapper
)
)
self.assertEqual(5, callback.SolutionCount())
self.assertEqual(cp_model_pb2.OPTIMAL, solution.status)
@@ -228,10 +239,9 @@ class SwigHelperTest(absltest.TestCase):
"""
model = cp_model_pb2.CpModelProto()
self.assertTrue(text_format.Parse(model_string, model))
stats = swig_helper.CpSatHelper.SerializedModelStats(
model.SerializeToString())
stats = swig_helper.CpSatHelper.SerializedModelStats(model.SerializeToString())
self.assertTrue(stats)
if __name__ == '__main__':
if __name__ == "__main__":
absltest.main()

9
ortools/util/python/sorted_interval_list_test.py
View File

@@ -11,6 +11,7 @@
# 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.
"""Tests for ortools.util.python.sorted_interval_list."""
import unittest
@@ -18,22 +19,20 @@ from ortools.util.python import sorted_interval_list
class SortedIntervalListTest(unittest.TestCase):
def testCtorAndGetter(self):
bool_domain = sorted_interval_list.Domain(0, 1)
self.assertEqual(2, bool_domain.Size())
self.assertEqual(0, bool_domain.Min())
self.assertEqual(1, bool_domain.Max())
self.assertFalse(bool_domain.IsEmpty())
self.assertEqual(str(bool_domain), '[0,1]')
self.assertEqual(str(bool_domain), "[0,1]")
def testFromValues(self):
domain = sorted_interval_list.Domain.FromValues([1, 3, -5, 5])
self.assertEqual(4, domain.Size())
self.assertEqual(-5, domain.Min())
self.assertEqual(5, domain.Max())
self.assertEqual([-5, -5, 1, 1, 3, 3, 5, 5],
domain.FlattenedIntervals())
self.assertEqual([-5, -5, 1, 1, 3, 3, 5, 5], domain.FlattenedIntervals())
self.assertTrue(domain.Contains(1))
self.assertFalse(domain.Contains(0))
@@ -86,5 +85,5 @@ class SortedIntervalListTest(unittest.TestCase):
self.assertEqual([6, 9223372036854775807], d2.FlattenedIntervals())
if __name__ == '__main__':
if __name__ == "__main__":
unittest.main()