Issue/#159 - consistent names for loggers

smac/epm/random_epm.py

@@ -22,7 +22,7 @@ def __init__(self, rng):
         ----------
         rng : np.random.RandomState
         '''
-        self.logger = logging.getLogger("RandomEPM")
+        self.logger = logging.getLogger(self.__module__ + "." + self.__class__.__name__)
         self.rng = rng
 
     def train(self, X, Y, **kwargs):
@@ -83,4 +83,4 @@ def predict_marginalized_over_instances(self, X):
             Predictive variance
         """
 
-        return self.rng.rand(len(X), 1), self.rng.rand(len(X), 1)
+        return self.rng.rand(len(X), 1), self.rng.rand(len(X), 1)

smac/epm/rf_with_instances.py

@@ -87,7 +87,7 @@ def __init__(self, types,
                        min_samples_leaf, max_depth, eps_purity, seed]
         self.seed = seed
 
-        self.logger = logging.getLogger("RF")
+        self.logger = logging.getLogger(self.__module__ + "." + self.__class__.__name__)
 
         # Never use a lower variance than this
         self.var_threshold = 10 ** -5
@@ -137,7 +137,7 @@ def predict(self, X):
                              (self.types.shape[0], X.shape[1]))
 
         means, vars = self.rf.batch_predictions(X)
-        
+
         return means.reshape((-1, 1)), vars.reshape((-1, 1))
 
     def predict_marginalized_over_instances(self, X):

smac/epm/rfr_imputator.py

@@ -36,14 +36,14 @@ def __init__(self, rs, cutoff, threshold,
             highest possible values (e.g. cutoff * par)
         model:
             epm model (i.e. RandomForestWithInstances)
-        change_threshold : float 
+        change_threshold : float
             stop imputation if change is less than this
-        max_iter : maximum number of iteration            
+        max_iter : maximum number of iteration
         -------
         """
 
         super(RFRImputator, self).__init__()
-        self.logger = logging.getLogger("RFRImputor")
+        self.logger = logging.getLogger(self.__module__ + "." + self.__class__.__name__)
         self.max_iter = max_iter
         self.change_threshold = change_threshold
         self.cutoff = cutoff

smac/facade/func_facade.py

@@ -79,7 +79,7 @@ def fmin_smac(func: callable,
     scenario = Scenario(scenario_dict)
 
     smac = SMAC(scenario=scenario, tae_runner=ta, rng=rng)
-    smac.logger = logging.getLogger("fmin_smac")
+    smac.logger = logging.getLogger(smac.__module__ + "." + smac.__class__.__name__)
     incumbent = smac.optimize()
 
     config_id = smac.solver.runhistory.config_ids[incumbent]

smac/facade/roar_facade.py

@@ -50,14 +50,14 @@ def __init__(self,
         initial_design: InitialDesign
             initial sampling design
         initial_configurations: typing.List[Configuration]
-            list of initial configurations for initial design -- 
+            list of initial configurations for initial design --
             cannot be used together with initial_design
         stats: Stats
             optional stats object
         rng: np.random.RandomState
             Random number generator
         '''
-        self.logger = logging.getLogger("ROAR")
+        self.logger = logging.getLogger(self.__module__ + "." + self.__class__.__name__)
 
         # initial random number generator
         num_run, rng = self._get_rng(rng=rng)
@@ -74,7 +74,7 @@ def __init__(self,
             (scenario=scenario, num_params=num_params,
              success_states=[StatusType.SUCCESS, ],
              impute_censored_data=False, impute_state=None)
-                
+
         # use SMAC facade
         super().__init__(
                          scenario=scenario,

smac/facade/smac_facade.py

@@ -83,14 +83,14 @@ def __init__(self,
         initial_design: InitialDesign
             initial sampling design
         initial_configurations: typing.List[Configuration]
-            list of initial configurations for initial design -- 
+            list of initial configurations for initial design --
             cannot be used together with initial_design
         stats: Stats
             optional stats object
         rng: np.random.RandomState
             Random number generator
         '''
-        self.logger = logging.getLogger("SMAC")
+        self.logger = logging.getLogger(self.__module__ + "." + self.__class__.__name__)
 
         aggregate_func = average_cost
 
@@ -188,15 +188,15 @@ def __init__(self,
         if initial_design is not None and initial_configurations is not None:
             raise ValueError(
                 "Either use initial_design or initial_configurations; but not both")
-            
+
         if initial_configurations is not None:
             initial_design = MultiConfigInitialDesign(tae_runner=tae_runner,
                                                       scenario=scenario,
                                                       stats=self.stats,
                                                       traj_logger=traj_logger,
                                                       runhistory=runhistory,
                                                       rng=rng,
-                                                      configs=initial_configurations, 
+                                                      configs=initial_configurations,
                                                       intensifier=intensifier,
                                                       aggregate_func=aggregate_func)
         elif initial_design is None:
@@ -268,7 +268,7 @@ def __init__(self,
 
     def _get_rng(self, rng):
         '''
-            initial random number generator 
+            initial random number generator
 
             Arguments
             ---------

smac/initial_design/default_configuration_design.py

@@ -14,8 +14,8 @@
 
 
 class DefaultConfiguration(SingleConfigInitialDesign):
-    
-    def __init__(self, 
+
+    def __init__(self,
                  tae_runner: ExecuteTARun,
                  scenario: Scenario,
                  stats: Stats,
@@ -24,7 +24,7 @@ def __init__(self,
                  ):
         '''
         Constructor
-        
+
         Arguments
         ---------
         tae_runner: ExecuteTARun
@@ -39,7 +39,7 @@ def __init__(self,
         rng: np.random.RandomState
             random state
         '''
-        super().__init__(tae_runner=tae_runner, 
+        super().__init__(tae_runner=tae_runner,
                          scenario=scenario,
                          stats=stats,
                          traj_logger=traj_logger,

smac/initial_design/initial_design.py

@@ -14,8 +14,8 @@
 
 
 class InitialDesign(object):
-    
-    def __init__(self, 
+
+    def __init__(self,
                  tae_runner: ExecuteTARun,
                  scenario: Scenario,
                  stats: Stats,
@@ -24,7 +24,7 @@ def __init__(self,
                  ):
         '''
         Constructor
-        
+
         Arguments
         ---------
         tae_runner: ExecuteTARun
@@ -38,18 +38,18 @@ def __init__(self,
         rng: np.random.RandomState
             random state
         '''
-        
+
         self.tae_runner = tae_runner
         self.scenario = scenario
         self.stats = stats
         self.traj_logger = traj_logger
         self.rng = rng
-        self.logger = logging.getLogger("InitialDesign")
+        self.logger = logging.getLogger(self.__module__ + "." + self.__class__.__name__)
 
     def run(self):
         '''
             as an initial design: it simply runs the default configuration on random pair of instance and random seed
-            
+
             Returns
             -------
             incumbent: Configuration()

smac/initial_design/multi_config_initial_design.py

@@ -91,7 +91,7 @@ def run(self) -> Configuration:
         if len(set(configs)) > 1:
             # intensify will skip all challenger that are identical with the incumbent;
             # if <configs> has only identical configurations,
-            # intensifiy will not do any configuration runs 
+            # intensifiy will not do any configuration runs
             # (also not on the incumbent)
             # therefore, at least two different configurations have to be in <configs>
             inc, inc_perf = self.intensifier.intensify(challengers=set(configs[1:]),

smac/intensification/intensification.py

@@ -37,7 +37,7 @@ def __init__(self, tae_runner, stats, traj_logger, rng, instances,
         tae_runner : tae.executre_ta_run_*.ExecuteTARun* Object
             target algorithm run executor
         stats: Stats()
-            stats object            
+            stats object
         traj_logger: TrajLogger()
             TrajLogger object to log all new incumbents
         rng : np.random.RandomState
@@ -68,7 +68,7 @@ def __init__(self, tae_runner, stats, traj_logger, rng, instances,
             self.instance_specifics = {}
         else:
             self.instance_specifics = instance_specifics
-        self.logger = logging.getLogger("intensifier")
+        self.logger = logging.getLogger(self.__module__ + "." + self.__class__.__name__)
         self.run_limit = run_limit
         self.maxR = maxR
         self.minR = minR
@@ -118,7 +118,7 @@ def intensify(self, challengers: typing.List[Configuration],
             incumbent: Configuration()
                 current (maybe new) incumbent configuration
             inc_perf: float
-                empirical performance of incumbent configuration 
+                empirical performance of incumbent configuration
         '''
 
         self.start_time = time.time()
@@ -339,7 +339,7 @@ def _adapt_cutoff(self, challenger: Configuration,
                       run_history: RunHistory,
                       inc_sum_cost: float):
         '''
-            adaptive capping: 
+            adaptive capping:
             compute cutoff based on time so far used for incumbent
             and reduce cutoff for next run of challenger accordingly
 
@@ -380,19 +380,19 @@ def _adapt_cutoff(self, challenger: Configuration,
                      )
         return cutoff
 
-    def _compare_configs(self, incumbent: Configuration, 
-                         challenger: Configuration, 
+    def _compare_configs(self, incumbent: Configuration,
+                         challenger: Configuration,
                          run_history: RunHistory,
                          aggregate_func: typing.Callable):
         '''
-            compare two configuration wrt the runhistory 
+            compare two configuration wrt the runhistory
             and return the one which performs better (or None if the decision is not safe)
 
             Decision strategy to return x as being better than y:
                 1. x has at least as many runs as y
                 2. x performs better than y on the intersection of runs on x and y
 
-            Implicit assumption: 
+            Implicit assumption:
                 challenger was evaluated on the same instance-seed pairs as incumbent
 
             Parameters

smac/runhistory/runhistory.py

@@ -158,7 +158,7 @@ def compute_all_costs(self, instances: typing.List[str]=None):
 
     def incremental_update_cost(self, config: Configuration, cost: float):
         '''
-            incrementally updates the performance of a configuration by using a moving average; 
+            incrementally updates the performance of a configuration by using a moving average;
 
             Arguments
             --------
@@ -213,7 +213,7 @@ def empty(self):
 
         Returns
         ----------
-            bool: True if runs have been added to the RunHistory, 
+            bool: True if runs have been added to the RunHistory,
                   False otherwise
         """
         return len(self.data) == 0
@@ -309,7 +309,7 @@ def update(self, runhistory, external_data:bool=False):
         runhistory: RunHistory
             runhistory with additional data to be added to self
         external_data: bool
-            if True, run will not be added to self._configid_to_inst_seed 
+            if True, run will not be added to self._configid_to_inst_seed
             and not available through get_runs_for_config()
         """
 

smac/runhistory/runhistory2epm.py

@@ -61,7 +61,7 @@ def __init__(self, scenario, num_params,
         rs : numpy.random.RandomState
             only used for reshuffling data after imputation
         '''
-        self.logger = logging.getLogger("runhistory2epm")
+        self.logger = logging.getLogger(self.__module__ + "." + self.__class__.__name__)
 
         # General arguments
         self.scenario = scenario
@@ -95,7 +95,6 @@ def __init__(self, scenario, num_params,
         self.instance_features = scenario.feature_dict
         self.n_feats = scenario.n_features
 
-        self.logger = logging.getLogger("runhistory2epm")
         self.num_params = num_params
 
         # Sanity checks

smac/scenario/scenario.py

@@ -44,7 +44,7 @@ def __init__(self, scenario, cmd_args=None):
             command line arguments that were not processed by argparse
 
         """
-        self.logger = logging.getLogger("scenario")
+        self.logger = logging.getLogger(self.__module__ + "." + self.__class__.__name__)
         self.PCA_DIM = 7
 
         self.in_reader = InputReader()
@@ -72,7 +72,7 @@ def __init__(self, scenario, cmd_args=None):
             arg_name, arg_value = self._parse_argument(key, scenario, **value)
             parsed_arguments[arg_name] = arg_value
 
-        
+
         if len(scenario) != 0:
             raise ValueError('Could not parse the following arguments: %s' %
                              str(list(scenario.keys())))
@@ -183,7 +183,7 @@ def _parse_argument(self, name, scenario, help, callback=None, default=None,
             normalized_key = key.lower().replace('-', '').replace('_', '')
             if normalized_key == normalized_name:
                 value = scenario.pop(key)
-                
+
         if dest is None:
             dest = name.lower().replace('-', '_')
 
@@ -311,7 +311,7 @@ def extract_instance_specific(instance_list):
                 self.feature_array.append(self.feature_dict[inst_])
             self.feature_array = numpy.array(self.feature_array)
             self.n_features = self.feature_array.shape[1]
-            
+
             # reduce dimensionality of features of larger than PCA_DIM
             if self.feature_array.shape[1] > self.PCA_DIM:
                 X = self.feature_array
@@ -352,4 +352,4 @@ def __getstate__(self):
 
     def __setstate__(self, d):
         self.__dict__.update(d)
-        self.logger = logging.getLogger("scenario")
+        self.logger = logging.getLogger(self.__module__ + "." + self.__class__.__name__)