Merge pull request #101 from BlueBrain/weighted-opt

Enable weighted optimisation

bluepyemodel/efeatures_extraction/efeatures_extraction.py

@@ -219,6 +219,24 @@ def extract_save_features_protocols(access_point, mapper=map):
         targets_configuration.protocols_mapping,
     )
 
+    # correct for any weight present in features
+    for target in targets_configuration.targets:
+        if target.weight != 1.0:
+            try:
+                feat = next(
+                    feat
+                    for feat in fitness_calculator_config.efeatures
+                    if feat.efel_feature_name == target.efeature
+                    and feat.protocol_name == f"{target.protocol}_{target.amplitude}"
+                )
+                feat.weight = target.weight
+            except StopIteration:
+                logger.debug(
+                    "Could not find efeature with name %s and protocol %s",
+                    target.efeature,
+                    target.protocol,
+                )
+
     if access_point.pipeline_settings.bound_max_std:
         threshold_efeatures_std(
             fitness_calculator_config, access_point.pipeline_settings.default_std_value

bluepyemodel/efeatures_extraction/target.py

@@ -32,6 +32,7 @@ def __init__(
         tolerance,
         efeature_name=None,
         efel_settings=None,
+        weight=1.0,
     ):
         """Constructor
 
@@ -50,6 +51,8 @@ def __init__(
             efeature_name (str): given name for this specific target. Can be different
                 from the efel efeature name.
             efel_settings (dict): target specific efel settings.
+            weight (float): weight of the efeature.
+                Basically multiplies the score of the efeature by this value.
         """
 
         self.efeature = efeature
@@ -60,6 +63,8 @@ def __init__(
 
         self.efeature_name = efeature_name
 
+        self.weight = weight
+
         if efel_settings is None:
             self.efel_settings = {"strict_stiminterval": True}
         else:

bluepyemodel/efeatures_extraction/targets_configuration.py

@@ -75,6 +75,7 @@ def __init__(
                         "protocol": "IDRest",
                         "amplitude": 150.,
                         "tolerance": 10.,
+                        "weight": 1.0,  # optional
                         "efel_settings": {
                             'stim_start': 200.,
                             'stim_end': 500.,

bluepyemodel/evaluation/efeature_configuration.py

@@ -33,6 +33,7 @@ def __init__(
         std=None,
         sample_size=None,
         default_std_value=1e-3,
+        weight=1.0,
     ):
         """Init.
 
@@ -57,6 +58,8 @@ def __init__(
                 the mean of the features value (optional).
             sample_size (float): number of data point that were used to compute the present
                 average and standard deviation.
+            weight (float): weight of the efeature.
+                Basically multiplies the score of the efeature by this value.
         """
 
         self.efel_feature_name = efel_feature_name
@@ -70,6 +73,7 @@ def __init__(
         self.sample_size = sample_size
 
         self.efeature_name = efeature_name
+        self.weight = weight
 
         if efel_settings is None:
             self.efel_settings = {"strict_stiminterval": True}

bluepyemodel/evaluation/efel_feature_bpem.py

@@ -44,6 +44,7 @@ class eFELFeatureBPEM(eFELFeature):
         "threshold",
         "comment",
     )
+    # pylint: disable=too-many-arguments
 
     def __init__(
         self,
@@ -61,6 +62,7 @@ def __init__(
         double_settings=None,
         int_settings=None,
         string_settings=None,
+        weight=1.0,
     ):
         """Constructor
 
@@ -76,6 +78,8 @@ def __init__(
             exp_std(float): experimental standard deviation of this eFeature
             threshold(float): spike detection threshold (mV)
             comment (str): comment
+            weight (float): weight of the efeature.
+                Basically multiplies the score of the efeature by this value.
         """
 
         super().__init__(
@@ -95,6 +99,7 @@ def __init__(
             string_settings,
             max_score=250.0,
         )
+        self.weight = weight  # used in objective
 
     def calculate_bpo_feature(self, responses):
         """Return internal feature which is directly passed as a response"""
@@ -270,6 +275,7 @@ def __init__(
         string_settings=None,
         decay=None,
         linear=None,
+        weight=1.0,
     ):
         """Constructor"""
         # pylint: disable=too-many-arguments
@@ -288,6 +294,7 @@ def __init__(
             double_settings,
             int_settings,
             string_settings,
+            weight,
         )
         self.decay = decay
         self.linear = linear

bluepyemodel/evaluation/evaluator.py

@@ -25,7 +25,7 @@
 from bluepyopt.ephys.locations import NrnSeclistCompLocation
 from bluepyopt.ephys.locations import NrnSomaDistanceCompLocation
 from bluepyopt.ephys.locations import NrnTrunkSomaDistanceCompLocation
-from bluepyopt.ephys.objectives import SingletonObjective
+from bluepyopt.ephys.objectives import SingletonWeightObjective
 from bluepyopt.ephys.objectivescalculators import ObjectivesCalculator
 from bluepyopt.ephys.simulators import NrnSimulator
 
@@ -269,6 +269,7 @@ def define_efeature(feature_config, protocol=None, global_efel_settings=None):
             string_settings=string_settings,
             decay=decay,
             linear=linear,
+            weight=feature_config.weight,
         )
     # protocol name contains list of location, e.g. 'apic[050,100,150]'
     elif "[" in feature_config.recording_name_for_instantiation[""]:
@@ -290,6 +291,7 @@ def define_efeature(feature_config, protocol=None, global_efel_settings=None):
             string_settings=string_settings,
             decay=decay,
             linear=linear,
+            weight=feature_config.weight,
         )
     else:
         efeature = eFELFeatureBPEM(
@@ -306,6 +308,7 @@ def define_efeature(feature_config, protocol=None, global_efel_settings=None):
             double_settings=double_settings,
             int_settings=int_settings,
             string_settings=string_settings,
+            weight=feature_config.weight,
         )
 
     return efeature
@@ -854,7 +857,7 @@ def define_fitness_calculator(features):
         ObjectivesCalculator
     """
 
-    objectives = [SingletonObjective(feat.name, feat) for feat in features]
+    objectives = [SingletonWeightObjective(feat.name, feat, feat.weight) for feat in features]
 
     return ObjectivesCalculator(objectives)
 

bluepyemodel/evaluation/fitness_calculator_configuration.py

@@ -114,6 +114,7 @@ def __init__(
                             "mean": 6.026,
                             "original_std": 4.016,
                             "efeature_name": "Spikecount",
+                            "weight": 1.0,  # optional
                             "efel_settings": {
                                 "strict_stiminterval": true,
                                 "Threshold": -30.0,

setup.py

@@ -67,7 +67,7 @@
         "tqdm",
         "pyyaml",
         "gitpython",
-        "bluepyopt>=1.14.8",
+        "bluepyopt>=1.14.10",
         "bluepyefe>=2.2.0",
         "neurom>=3.0,<4.0",
         "efel>=3.1",