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use black on examples/python

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Laurent Perron
2023-07-01 06:06:53 +02:00
parent d65333dab0
commit 84ec414e61
41 changed files with 18801 additions and 4140 deletions
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202
examples/python/knapsack_2d_sat.py Executable file → Normal file
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@@ -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.
"""Solver a 2D rectangle knapsack problem.
This code is adapted from
@@ -29,14 +30,16 @@ from google.protobuf import text_format
from ortools.sat.python import cp_model
_OUTPUT_PROTO = flags.DEFINE_string(
'output_proto', '', 'Output file to write the cp_model proto to.')
_PARAMS = flags.DEFINE_string(
'params',
'num_search_workers:16,log_search_progress:true,max_time_in_seconds:45',
'Sat solver parameters.',
"output_proto", "", "Output file to write the cp_model proto to."
)
_PARAMS = flags.DEFINE_string(
"params",
"num_search_workers:16,log_search_progress:true,max_time_in_seconds:45",
"Sat solver parameters.",
)
_MODEL = flags.DEFINE_string(
"model", "rotation", "'duplicate' or 'rotation' or 'optional'"
)
_MODEL = flags.DEFINE_string('model', 'rotation',
'\'duplicate\' or \'rotation\' or \'optional\'')
def build_data():
@@ -55,25 +58,25 @@ def build_data():
k10 9 11 5 369.560 cyan
"""
data = pd.read_table(io.StringIO(data), sep=r'\s+')
print('Input data')
data = pd.read_table(io.StringIO(data), sep=r"\s+")
print("Input data")
print(data)
max_height = 20
max_width = 30
print(f'Container max_width:{max_width} max_height:{max_height}')
print(f'#Items: {len(data.index)}')
print(f"Container max_width:{max_width} max_height:{max_height}")
print(f"#Items: {len(data.index)}")
return (data, max_height, max_width)
def solve_with_duplicate_items(data, max_height, max_width):
"""Solve the problem by building 2 items (rotated or not) for each item."""
# Derived data (expanded to individual items).
data_widths = data['width'].to_numpy()
data_heights = data['height'].to_numpy()
data_availability = data['available'].to_numpy()
data_values = data['value'].to_numpy()
data_widths = data["width"].to_numpy()
data_heights = data["height"].to_numpy()
data_availability = data["available"].to_numpy()
data_values = data["value"].to_numpy()
# Non duplicated items data.
base_item_widths = np.repeat(data_widths, data_availability)
@@ -102,21 +105,25 @@ def solve_with_duplicate_items(data, max_height, max_width):
for i in range(num_items):
## Is the item used?
is_used.append(model.NewBoolVar(f'is_used{i}'))
is_used.append(model.NewBoolVar(f"is_used{i}"))
## Item coordinates.
x_starts.append(model.NewIntVar(0, max_width, f'x_start{i}'))
x_ends.append(model.NewIntVar(0, max_width, f'x_end{i}'))
y_starts.append(model.NewIntVar(0, max_height, f'y_start{i}'))
y_ends.append(model.NewIntVar(0, max_height, f'y_end{i}'))
x_starts.append(model.NewIntVar(0, max_width, f"x_start{i}"))
x_ends.append(model.NewIntVar(0, max_width, f"x_end{i}"))
y_starts.append(model.NewIntVar(0, max_height, f"y_start{i}"))
y_ends.append(model.NewIntVar(0, max_height, f"y_end{i}"))
## Interval variables.
x_intervals.append(
model.NewIntervalVar(x_starts[i], item_widths[i] * is_used[i],
x_ends[i], f'x_interval{i}'))
model.NewIntervalVar(
x_starts[i], item_widths[i] * is_used[i], x_ends[i], f"x_interval{i}"
)
)
y_intervals.append(
model.NewIntervalVar(y_starts[i], item_heights[i] * is_used[i],
y_ends[i], f'y_interval{i}'))
model.NewIntervalVar(
y_starts[i], item_heights[i] * is_used[i], y_ends[i], f"y_interval{i}"
)
)
# Unused boxes are fixed at (0.0).
model.Add(x_starts[i] == 0).OnlyEnforceIf(is_used[i].Not())
@@ -136,8 +143,8 @@ def solve_with_duplicate_items(data, max_height, max_width):
# Output proto to file.
if _OUTPUT_PROTO.value:
print(f'Writing proto to {_OUTPUT_PROTO.value}')
with open(_OUTPUT_PROTO.value, 'w') as text_file:
print(f"Writing proto to {_OUTPUT_PROTO.value}")
with open(_OUTPUT_PROTO.value, "w") as text_file:
text_file.write(str(model))
# Solve model.
@@ -150,25 +157,27 @@ def solve_with_duplicate_items(data, max_height, max_width):
# Report solution.
if status == cp_model.OPTIMAL or status == cp_model.FEASIBLE:
used = {i for i in range(num_items) if solver.BooleanValue(is_used[i])}
data = pd.DataFrame({
'x_start': [solver.Value(x_starts[i]) for i in used],
'y_start': [solver.Value(y_starts[i]) for i in used],
'item_width': [item_widths[i] for i in used],
'item_height': [item_heights[i] for i in used],
'x_end': [solver.Value(x_ends[i]) for i in used],
'y_end': [solver.Value(y_ends[i]) for i in used],
'item_value': [item_values[i] for i in used]
})
data = pd.DataFrame(
{
"x_start": [solver.Value(x_starts[i]) for i in used],
"y_start": [solver.Value(y_starts[i]) for i in used],
"item_width": [item_widths[i] for i in used],
"item_height": [item_heights[i] for i in used],
"x_end": [solver.Value(x_ends[i]) for i in used],
"y_end": [solver.Value(y_ends[i]) for i in used],
"item_value": [item_values[i] for i in used],
}
)
print(data)
def solve_with_duplicate_optional_items(data, max_height, max_width):
"""Solve the problem by building 2 optional items (rotated or not) for each item."""
# Derived data (expanded to individual items).
data_widths = data['width'].to_numpy()
data_heights = data['height'].to_numpy()
data_availability = data['available'].to_numpy()
data_values = data['value'].to_numpy()
data_widths = data["width"].to_numpy()
data_heights = data["height"].to_numpy()
data_availability = data["available"].to_numpy()
data_values = data["value"].to_numpy()
# Non duplicated items data.
base_item_widths = np.repeat(data_widths, data_availability)
@@ -195,22 +204,27 @@ def solve_with_duplicate_optional_items(data, max_height, max_width):
for i in range(num_items):
## Is the item used?
is_used.append(model.NewBoolVar(f'is_used{i}'))
is_used.append(model.NewBoolVar(f"is_used{i}"))
## Item coordinates.
x_starts.append(
model.NewIntVar(0, max_width - int(item_widths[i]), f'x_start{i}'))
model.NewIntVar(0, max_width - int(item_widths[i]), f"x_start{i}")
)
y_starts.append(
model.NewIntVar(0, max_height - int(item_heights[i]),
f'y_start{i}'))
model.NewIntVar(0, max_height - int(item_heights[i]), f"y_start{i}")
)
## Interval variables.
x_intervals.append(
model.NewOptionalFixedSizeIntervalVar(x_starts[i], item_widths[i],
is_used[i], f'x_interval{i}'))
model.NewOptionalFixedSizeIntervalVar(
x_starts[i], item_widths[i], is_used[i], f"x_interval{i}"
)
)
y_intervals.append(
model.NewOptionalFixedSizeIntervalVar(y_starts[i], item_heights[i],
is_used[i], f'y_interval{i}'))
model.NewOptionalFixedSizeIntervalVar(
y_starts[i], item_heights[i], is_used[i], f"y_interval{i}"
)
)
# Unused boxes are fixed at (0.0).
model.Add(x_starts[i] == 0).OnlyEnforceIf(is_used[i].Not())
model.Add(y_starts[i] == 0).OnlyEnforceIf(is_used[i].Not())
@@ -229,8 +243,8 @@ def solve_with_duplicate_optional_items(data, max_height, max_width):
# Output proto to file.
if _OUTPUT_PROTO.value:
print(f'Writing proto to {_OUTPUT_PROTO.value}')
with open(_OUTPUT_PROTO.value, 'w') as text_file:
print(f"Writing proto to {_OUTPUT_PROTO.value}")
with open(_OUTPUT_PROTO.value, "w") as text_file:
text_file.write(str(model))
# Solve model.
@@ -243,27 +257,27 @@ def solve_with_duplicate_optional_items(data, max_height, max_width):
# Report solution.
if status == cp_model.OPTIMAL or status == cp_model.FEASIBLE:
used = {i for i in range(num_items) if solver.BooleanValue(is_used[i])}
data = pd.DataFrame({
'x_start': [solver.Value(x_starts[i]) for i in used],
'y_start': [solver.Value(y_starts[i]) for i in used],
'item_width': [item_widths[i] for i in used],
'item_height': [item_heights[i] for i in used],
'x_end': [solver.Value(x_starts[i]) + item_widths[i] for i in used],
'y_end': [
solver.Value(y_starts[i]) + item_heights[i] for i in used
],
'item_value': [item_values[i] for i in used]
})
data = pd.DataFrame(
{
"x_start": [solver.Value(x_starts[i]) for i in used],
"y_start": [solver.Value(y_starts[i]) for i in used],
"item_width": [item_widths[i] for i in used],
"item_height": [item_heights[i] for i in used],
"x_end": [solver.Value(x_starts[i]) + item_widths[i] for i in used],
"y_end": [solver.Value(y_starts[i]) + item_heights[i] for i in used],
"item_value": [item_values[i] for i in used],
}
)
print(data)
def solve_with_rotations(data, max_height, max_width):
"""Solve the problem by rotating items."""
# Derived data (expanded to individual items).
data_widths = data['width'].to_numpy()
data_heights = data['height'].to_numpy()
data_availability = data['available'].to_numpy()
data_values = data['value'].to_numpy()
data_widths = data["width"].to_numpy()
data_heights = data["height"].to_numpy()
data_availability = data["available"].to_numpy()
data_values = data["value"].to_numpy()
item_widths = np.repeat(data_widths, data_availability)
item_heights = np.repeat(data_heights, data_availability)
@@ -287,26 +301,26 @@ def solve_with_rotations(data, max_height, max_width):
for i in range(num_items):
sizes = [0, int(item_widths[i]), int(item_heights[i])]
# X coordinates.
x_starts.append(model.NewIntVar(0, max_width, f'x_start{i}'))
x_starts.append(model.NewIntVar(0, max_width, f"x_start{i}"))
x_sizes.append(
model.NewIntVarFromDomain(cp_model.Domain.FromValues(sizes),
f'x_size{i}'))
x_ends.append(model.NewIntVar(0, max_width, f'x_end{i}'))
model.NewIntVarFromDomain(cp_model.Domain.FromValues(sizes), f"x_size{i}")
)
x_ends.append(model.NewIntVar(0, max_width, f"x_end{i}"))
# Y coordinates.
y_starts.append(model.NewIntVar(0, max_height, f'y_start{i}'))
y_starts.append(model.NewIntVar(0, max_height, f"y_start{i}"))
y_sizes.append(
model.NewIntVarFromDomain(cp_model.Domain.FromValues(sizes),
f'y_size{i}'))
y_ends.append(model.NewIntVar(0, max_height, f'y_end{i}'))
model.NewIntVarFromDomain(cp_model.Domain.FromValues(sizes), f"y_size{i}")
)
y_ends.append(model.NewIntVar(0, max_height, f"y_end{i}"))
## Interval variables
x_intervals.append(
model.NewIntervalVar(x_starts[i], x_sizes[i], x_ends[i],
f'x_interval{i}'))
model.NewIntervalVar(x_starts[i], x_sizes[i], x_ends[i], f"x_interval{i}")
)
y_intervals.append(
model.NewIntervalVar(y_starts[i], y_sizes[i], y_ends[i],
f'y_interval{i}'))
model.NewIntervalVar(y_starts[i], y_sizes[i], y_ends[i], f"y_interval{i}")
)
# is_used[i] == True if and only if item i is selected.
is_used = []
@@ -315,9 +329,9 @@ def solve_with_rotations(data, max_height, max_width):
## for each item, decide is unselected, no_rotation, rotated.
for i in range(num_items):
not_selected = model.NewBoolVar(f'not_selected_{i}')
no_rotation = model.NewBoolVar(f'no_rotation_{i}')
rotated = model.NewBoolVar(f'rotated_{i}')
not_selected = model.NewBoolVar(f"not_selected_{i}")
no_rotation = model.NewBoolVar(f"no_rotation_{i}")
rotated = model.NewBoolVar(f"rotated_{i}")
### Exactly one state must be chosen.
model.AddExactlyOne(not_selected, no_rotation, rotated)
@@ -346,8 +360,8 @@ def solve_with_rotations(data, max_height, max_width):
# Output proto to file.
if _OUTPUT_PROTO.value:
print(f'Writing proto to {_OUTPUT_PROTO.value}')
with open(_OUTPUT_PROTO.value, 'w') as text_file:
print(f"Writing proto to {_OUTPUT_PROTO.value}")
with open(_OUTPUT_PROTO.value, "w") as text_file:
text_file.write(str(model))
# Solve model.
@@ -360,28 +374,30 @@ def solve_with_rotations(data, max_height, max_width):
# Report solution.
if status == cp_model.OPTIMAL or status == cp_model.FEASIBLE:
used = {i for i in range(num_items) if solver.BooleanValue(is_used[i])}
data = pd.DataFrame({
'x_start': [solver.Value(x_starts[i]) for i in used],
'y_start': [solver.Value(y_starts[i]) for i in used],
'item_width': [solver.Value(x_sizes[i]) for i in used],
'item_height': [solver.Value(y_sizes[i]) for i in used],
'x_end': [solver.Value(x_ends[i]) for i in used],
'y_end': [solver.Value(y_ends[i]) for i in used],
'item_value': [item_values[i] for i in used]
})
data = pd.DataFrame(
{
"x_start": [solver.Value(x_starts[i]) for i in used],
"y_start": [solver.Value(y_starts[i]) for i in used],
"item_width": [solver.Value(x_sizes[i]) for i in used],
"item_height": [solver.Value(y_sizes[i]) for i in used],
"x_end": [solver.Value(x_ends[i]) for i in used],
"y_end": [solver.Value(y_ends[i]) for i in used],
"item_value": [item_values[i] for i in used],
}
)
print(data)
def main(_):
"""Solve the problem with all models."""
data, max_height, max_width = build_data()
if _MODEL.value == 'duplicate':
if _MODEL.value == "duplicate":
solve_with_duplicate_items(data, max_height, max_width)
elif _MODEL.value == 'optional':
elif _MODEL.value == "optional":
solve_with_duplicate_optional_items(data, max_height, max_width)
else:
solve_with_rotations(data, max_height, max_width)
if __name__ == '__main__':
if __name__ == "__main__":
app.run(main)