ANL-CEEESA/MIPLearn
1
0
Fork 0
mirror of https://github.com/ANL-CEEESA/MIPLearn.git synced 2025-12-06 17:38:51 -06:00
Code Issues Packages Projects Releases Wiki Activity

Convert TrainingSample to dataclass

Browse Source
This commit is contained in:
Alinson S. Xavier
2021-04-05 20:36:04 -05:00
parent aeed338837
commit b11779817a
15 changed files with 122 additions and 129 deletions
Download Patch File Download Diff File Expand all files Collapse all files

29
tests/solvers/test_learning_solver.py
View File

@@ -27,22 +27,21 @@ def test_learning_solver():
)
solver.solve(instance)
assert hasattr(instance, "features")
data = instance.training_data[0]
assert data["Solution"]["x"][0] == 1.0
assert data["Solution"]["x"][1] == 0.0
assert data["Solution"]["x"][2] == 1.0
assert data["Solution"]["x"][3] == 1.0
assert data["Lower bound"] == 1183.0
assert data["Upper bound"] == 1183.0
assert round(data["LP solution"]["x"][0], 3) == 1.000
assert round(data["LP solution"]["x"][1], 3) == 0.923
assert round(data["LP solution"]["x"][2], 3) == 1.000
assert round(data["LP solution"]["x"][3], 3) == 0.000
assert round(data["LP value"], 3) == 1287.923
assert len(data["MIP log"]) > 100
sample = instance.training_data[0]
assert sample.solution["x"][0] == 1.0
assert sample.solution["x"][1] == 0.0
assert sample.solution["x"][2] == 1.0
assert sample.solution["x"][3] == 1.0
assert sample.lower_bound == 1183.0
assert sample.upper_bound == 1183.0
assert round(sample.lp_solution["x"][0], 3) == 1.000
assert round(sample.lp_solution["x"][1], 3) == 0.923
assert round(sample.lp_solution["x"][2], 3) == 1.000
assert round(sample.lp_solution["x"][3], 3) == 0.000
assert round(sample.lp_value, 3) == 1287.923
assert len(sample.mip_log) > 100
solver.fit([instance])
solver.solve(instance)
@@ -73,7 +72,7 @@ def test_parallel_solve():
assert len(results) == 10
for instance in instances:
data = instance.training_data[0]
assert len(data["Solution"]["x"].keys()) == 4
assert len(data.solution["x"].keys()) == 4
def test_solve_fit_from_disk():