ready for release (black-conform)

Author: JensBlack

experiments/custom/classifier.py

@@ -11,7 +11,11 @@
 import pickle
 
 from utils.configloader import PATH_TO_CLASSIFIER, TIME_WINDOW
-from experiments.custom.featureextraction import SimbaFeatureExtractor, SimbaFeatureExtractorStandard14bp, BsoidFeatureExtractor
+from experiments.custom.featureextraction import (
+    SimbaFeatureExtractor,
+    SimbaFeatureExtractorStandard14bp,
+    BsoidFeatureExtractor,
+)
 
 
 class Classifier:
@@ -65,7 +69,7 @@ def load_classifier(path_to_sav):
         return classifier
 
     def _check_pure(self):
-        if 'pure' in str(self._classifier):
+        if "pure" in str(self._classifier):
             return True
         else:
             return False
@@ -147,10 +151,9 @@ def example_feat_classifier_pool_run(input_q: mp.Queue, output_q: mp.Queue):
             pass
 
 
-
 def simba_feat_classifier_pool_run(input_q: mp.Queue, output_q: mp.Queue):
     feature_extractor = SimbaFeatureExtractorStandard14bp(TIME_WINDOW)
-    #feature_extractor = SimbaFeatureExtractor(TIME_WINDOW)
+    # feature_extractor = SimbaFeatureExtractor(TIME_WINDOW)
     classifier = SiMBAClassifier()  # initialize classifier
     while True:
         skel_time_window = None
@@ -211,7 +214,9 @@ def __init__(self, pool_size: int):
         """
         self._running = False
         self._pool_size = pool_size
-        self._process_pool = self.initiate_pool(example_feat_classifier_pool_run, pool_size)
+        self._process_pool = self.initiate_pool(
+            example_feat_classifier_pool_run, pool_size
+        )
 
     @staticmethod
     def initiate_pool(process_func, pool_size: int):
@@ -285,7 +290,11 @@ def pass_time_window(self, skel_time_window: tuple, debug: bool = False):
             elif process["input"].empty() and process["output"].full():
                 process["input"].put(skel_time_window)
                 if debug:
-                    print("Input", process["process"].name, "ID: " + str(skel_time_window[1]))
+                    print(
+                        "Input",
+                        process["process"].name,
+                        "ID: " + str(skel_time_window[1]),
+                    )
                 break
 
     def get_result(self, debug: bool = False):
@@ -316,7 +325,9 @@ def __init__(self, pool_size: int):
         Setting up the three queues and the process itself
         """
         super().__init__(pool_size)
-        self._process_pool = super().initiate_pool(simba_feat_classifier_pool_run, pool_size)
+        self._process_pool = super().initiate_pool(
+            simba_feat_classifier_pool_run, pool_size
+        )
 
 
 class FeatBsoidProcessPool(FeatureExtractionClassifierProcessPool):
@@ -330,8 +341,9 @@ def __init__(self, pool_size: int):
         Setting up the three queues and the process itself
         """
         super().__init__(pool_size)
-        self._process_pool = super().initiate_pool(bsoid_feat_classifier_pool_run, pool_size)
-
+        self._process_pool = super().initiate_pool(
+            bsoid_feat_classifier_pool_run, pool_size
+        )
 
 
 """Simple process protocols """
@@ -651,4 +663,3 @@ def __init__(self, pool_size: int):
         """
         super().__init__(pool_size)
         self._process_pool = super().initiate_pool(bsoid_classifier_pool_run, pool_size)
-

experiments/custom/experiments.py

@@ -30,16 +30,15 @@
 from utils.plotter import plot_triggers_response
 from utils.analysis import angle_between_vectors
 from experiments.custom.stimulation import show_visual_stim_img, laser_switch
-from experiments.custom.classifier import (
-    FeatBsoidProcessPool,
-    FeatSimbaProcessPool
-)
+from experiments.custom.classifier import FeatBsoidProcessPool, FeatSimbaProcessPool
 
 
 from utils.configloader import THRESHOLD, POOL_SIZE, TRIGGER
 
 
 """ experimental classification experiment using Simba trained classifiers in a pool which are converted using the pure-predict package"""
+
+
 class SimbaBehaviorPoolExperiment:
     """
     Test experiment for Simba classification
@@ -52,8 +51,8 @@ def __init__(self):
         """Classifier process and initiation of behavior trigger"""
         self.experiment_finished = False
         self._process_experiment = ExampleProtocolProcess()
-        #this process has feature extraction and classification in one process
-        #simplifies everything if the feature extraction script is within the parallel process
+        # this process has feature extraction and classification in one process
+        # simplifies everything if the feature extraction script is within the parallel process
         self._process_pool = FeatSimbaProcessPool(POOL_SIZE)
         # pass classifier to trigger, so that check_skeleton is the only function that passes skeleton
         # initiate in experiment, so that process can be started with start_experiment
@@ -178,7 +177,7 @@ def __init__(self):
         # pass classifier to trigger, so that check_skeleton is the only function that passes skeleton
         # initiate in experiment, so that process can be started with start_experiment
         self._behaviortrigger = BsoidClassBehaviorPoolTrigger(
-            target_class=TRIGGER, class_process_pool=self._process_pool, debug= False
+            target_class=TRIGGER, class_process_pool=self._process_pool, debug=False
         )
         self._event = None
         # is not fully utilized in this experiment but is usefull to keep for further adaptation
@@ -226,7 +225,7 @@ def check_skeleton(self, frame, skeleton):
             self._process_experiment.set_trial(self._current_trial)
         else:
             pass
-        return result,response
+        return result, response
 
     @property
     def _trials(self):