mirror of
https://github.com/ANL-CEEESA/MIPLearn.git
synced 2025-12-08 02:18:51 -06:00
Move tests to separate folder
This commit is contained in:
24
tests/problems/test_knapsack.py
Normal file
24
tests/problems/test_knapsack.py
Normal file
@@ -0,0 +1,24 @@
|
||||
# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
|
||||
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
|
||||
# Released under the modified BSD license. See COPYING.md for more details.
|
||||
|
||||
import numpy as np
|
||||
from scipy.stats import uniform, randint
|
||||
|
||||
from miplearn.problems.knapsack import MultiKnapsackGenerator
|
||||
|
||||
|
||||
def test_knapsack_generator():
|
||||
gen = MultiKnapsackGenerator(
|
||||
n=randint(low=100, high=101),
|
||||
m=randint(low=30, high=31),
|
||||
w=randint(low=0, high=1000),
|
||||
K=randint(low=500, high=501),
|
||||
u=uniform(loc=1.0, scale=1.0),
|
||||
alpha=uniform(loc=0.50, scale=0.0),
|
||||
)
|
||||
instances = gen.generate(100)
|
||||
w_sum = sum(instance.weights for instance in instances) / len(instances)
|
||||
b_sum = sum(instance.capacities for instance in instances) / len(instances)
|
||||
assert round(np.mean(w_sum), -1) == 500.0
|
||||
assert round(np.mean(b_sum), -3) == 25000.0
|
||||
Reference in New Issue
Block a user