Reorganize imports; start moving data to instance.training_data

miplearn/problems/knapsack.py

@@ -2,13 +2,13 @@
 #  Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 #  Released under the modified BSD license. See COPYING.md for more details.
 
-import miplearn
-from miplearn import Instance
 import numpy as np
 import pyomo.environ as pe
-from scipy.stats import uniform, randint, bernoulli
+from scipy.stats import uniform, randint
 from scipy.stats.distributions import rv_frozen
 
+from miplearn.instance import Instance
+
 
 class ChallengeA:
     """
@@ -56,6 +56,7 @@ class MultiKnapsackInstance(Instance):
     """
 
     def __init__(self, prices, capacities, weights):
+        super().__init__()
         assert isinstance(prices, np.ndarray)
         assert isinstance(capacities, np.ndarray)
         assert isinstance(weights, np.ndarray)
@@ -241,6 +242,7 @@ class KnapsackInstance(Instance):
     """
 
     def __init__(self, weights, prices, capacity):
+        super().__init__()
         self.weights = weights
         self.prices = prices
         self.capacity = capacity

miplearn/problems/stab.py

@@ -8,7 +8,7 @@ import pyomo.environ as pe
 from scipy.stats import uniform, randint
 from scipy.stats.distributions import rv_frozen
 
-from miplearn import Instance
+from miplearn.instance import Instance
 
 
 class ChallengeA:
@@ -101,6 +101,7 @@ class MaxWeightStableSetInstance(Instance):
     """
 
     def __init__(self, graph, weights):
+        super().__init__()
         self.graph = graph
         self.weights = weights
 

miplearn/problems/tests/test_knapsack.py

@@ -2,10 +2,10 @@
 #  Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 #  Released under the modified BSD license. See COPYING.md for more details.
 
-from miplearn import LearningSolver
-from miplearn.problems.knapsack import MultiKnapsackGenerator, MultiKnapsackInstance
-from scipy.stats import uniform, randint
 import numpy as np
+from scipy.stats import uniform, randint
+
+from miplearn.problems.knapsack import MultiKnapsackGenerator
 
 
 def test_knapsack_generator():

miplearn/problems/tests/test_stab.py

@@ -4,10 +4,11 @@
 
 import networkx as nx
 import numpy as np
-from miplearn import LearningSolver
-from miplearn.problems.stab import MaxWeightStableSetInstance
 from scipy.stats import uniform, randint
 
+from miplearn.problems.stab import MaxWeightStableSetInstance
+from miplearn.solvers.learning import LearningSolver
+
 
 def test_stab():
     graph = nx.cycle_graph(5)

miplearn/problems/tests/test_tsp.py

@@ -2,13 +2,14 @@
 #  Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 #  Released under the modified BSD license. See COPYING.md for more details.
 
-from miplearn import LearningSolver
-from miplearn.problems.tsp import TravelingSalesmanGenerator, TravelingSalesmanInstance
 import numpy as np
 from numpy.linalg import norm
 from scipy.spatial.distance import pdist, squareform
 from scipy.stats import uniform, randint
 
+from miplearn.problems.tsp import TravelingSalesmanGenerator, TravelingSalesmanInstance
+from miplearn.solvers.learning import LearningSolver
+
 
 def test_generator():
     instances = TravelingSalesmanGenerator(

miplearn/problems/tsp.py

@@ -2,14 +2,14 @@
 #  Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 #  Released under the modified BSD license. See COPYING.md for more details.
 
+import networkx as nx
 import numpy as np
 import pyomo.environ as pe
-from miplearn import Instance
-from scipy.stats import uniform, randint
 from scipy.spatial.distance import pdist, squareform
+from scipy.stats import uniform, randint
 from scipy.stats.distributions import rv_frozen
-import networkx as nx
-import random
+
+from miplearn.instance import Instance
 
 
 class ChallengeA: