Make progress bar labels consistent

src/python/miplearn/components/branching.py

@@ -104,7 +104,7 @@ class BranchPriorityComponent(Component):
         # Run strong branching on pending instances
         subcomponents = Parallel(n_jobs=n_jobs)(
             delayed(_process)(instance)
-            for instance in tqdm(self.pending_instances, desc="Branch priority")
+            for instance in tqdm(self.pending_instances, desc="Fit (branch)")
         )
         self.merge(subcomponents)
         self.pending_instances.clear()

src/python/miplearn/components/primal.py

@@ -50,7 +50,7 @@ class PrimalSolutionComponent(Component):
         features = VariableFeaturesExtractor().extract(training_instances)
         solutions = SolutionExtractor().extract(training_instances)
 
-        for category in tqdm(features.keys(), desc="Fit (Primal)"):
+        for category in tqdm(features.keys(), desc="Fit (primal)"):
             x_train = features[category]
             y_train = solutions[category]
             for label in [0, 1]:
@@ -116,7 +116,8 @@ class PrimalSolutionComponent(Component):
     def evaluate(self, instances):
         ev = {"Fix zero": {},
               "Fix one": {}}
-        for instance_idx in tqdm(range(len(instances))):
+        for instance_idx in tqdm(range(len(instances)),
+                                 desc="Evaluate (primal)"):
             instance = instances[instance_idx]
             solution_actual = instance.solution
             solution_pred = self.predict(instance)

src/python/miplearn/extractors.py

@@ -35,7 +35,7 @@ class VariableFeaturesExtractor(Extractor):
     def extract(self, instances):
         result = {}
         for instance in tqdm(instances,
-                             desc="Extract var features",
+                             desc="Extract (vars)",
                              disable=len(instances) < 5):
             instance_features = instance.get_instance_features()
             var_split = self.split_variables(instance)
@@ -60,7 +60,7 @@ class SolutionExtractor(Extractor):
     def extract(self, instances):
         result = {}
         for instance in tqdm(instances,
-                             desc="Extract solution",
+                             desc="Extract (solution)",
                              disable=len(instances) < 5):
             var_split = self.split_variables(instance)
             for (category, var_index_pairs) in var_split.items():