ANL-CEEESA/MIPLearn
1
0
Fork 0
mirror of https://github.com/ANL-CEEESA/MIPLearn.git synced 2025-12-06 01:18:52 -06:00
Code Issues Packages Projects Releases Wiki Activity

Use np.ndarray for var_types, basis_status

Browse Source
This commit is contained in:
Alinson S. Xavier
2021-08-08 07:36:57 -05:00
parent 7d55d6f34c
commit 45667ac2e4
6 changed files with 31 additions and 23 deletions
Download Patch File Download Diff File Expand all files Collapse all files

9
tests/features/test_extractor.py
View File

@@ -41,7 +41,10 @@ def test_knapsack() -> None:
assert_equals(
sample.get_vector("static_var_obj_coeffs"), [505.0, 352.0, 458.0, 220.0, 0.0]
)
assert_equals(sample.get_vector("static_var_types"), ["B", "B", "B", "B", "C"])
assert_equals(
sample.get_array("static_var_types"),
np.array(["B", "B", "B", "B", "C"], dtype="S"),
)
assert_equals(
sample.get_vector("static_var_upper_bounds"), [1.0, 1.0, 1.0, 1.0, 67.0]
)
@@ -76,8 +79,8 @@ def test_knapsack() -> None:
solver.solve_lp()
extractor.extract_after_lp_features(solver, sample)
assert_equals(
sample.get_vector("lp_var_basis_status"),
["U", "B", "U", "L", "U"],
sample.get_array("lp_var_basis_status"),
np.array(["U", "B", "U", "L", "U"], dtype="S"),
)
assert_equals(
sample.get_vector("lp_var_reduced_costs"),