Cleanup

.gitignore

@@ -32,4 +32,4 @@ tmp/
 .venv
 
 # Python cache files
-*.pyc
\ No newline at end of file
+*.pyc

execution/lib/trend_slope_computer.py

@@ -15,6 +15,5 @@ def compute(directory, filename, warmup_sec, threshold):
     Y_pred = linear_regressor.predict(X)  # make predictions
 
     trend_slope = linear_regressor.coef_[0][0]
-    #print(linear_regressor.coef_)
 
     return trend_slope
\ No newline at end of file

execution/strategies/strategies/domain_restriction/lower_bound_strategy.py

-# strats:
-# default: not end subexp when suitable instances found, increasing the number of instances with each iteration
-# H1 end subexp when suitable instances found, increasing the number of instances with each iteration.
-# H2 start with suitable instances from experiments for the last lower dim value -> outer loop over dim values, tracking suitable instances
-# H3 end subexp when suitable instances found, using binary search.
-
-# 3 Suchstrategien:
-#   1. H0 (Teste alle)
-#   2. H1 (Lineare Suche)
-#   3. H2 (Binäre Suche)
-
-# Optional: Einschränkung des Suchraumes:
-#   1. Keine Einschränkung
-#   2. Untere Schranke
-
-# Fragen: Erkläre vorgehen, verstehen wir dasselbe?
-# Zeithorizont?
-
-# linear regressor besprechen im lag_analysis.py skript
-
-# useful combinations
-
-# Zum Report:
-# Gegenüberstellung Suchstrategie & keine Suchstrategie (im Idealfall wdh. von Experimenten)
-
-
+# The lower bound strategy
 def execute(config):
     dim_value_index = 0
     lower_bound_replicas_index = 0

execution/strategies/strategies/domain_restriction/no_lower_bound_strategy.py

+# The strategy where the domain contains all amounts of instances
 def execute(config):
     dim_value_index = 0
     subexperiment_counter = 0

execution/strategies/strategies/search/binary_search_strategy.py

+# The binary search strategy
 import os
 from strategies.strategies.config import SubexperimentConfig
 

execution/strategies/strategies/search/check_all_strategy.py

-# Runs subexperiments for all numbers of replicas with an index > lower_replicas_bound_index
-
+# The check_all strategy
 import os
 from strategies.strategies.config import SubexperimentConfig
 

execution/strategies/strategies/search/linear_search_strategy.py

-# Perform linear search to determine the lowest number of replicas which is suitable for the dimension value with an index > lower_replicas_bound_index
+# The linear-search strategy
 
 import os
 from strategies.strategies.config import SubexperimentConfig

execution/strategies/subexperiment_evaluation/noop_subexperiment_evaluator.py

-def execute(config):
-    return
\ No newline at end of file

execution/theodolite.py

@@ -26,9 +26,9 @@ search_strategy=sys.argv[10] if len(sys.argv) >= 11 and (sys.argv[10] == "linear
 print(f"Domain restriction of search space activated: {domain_restriction}")
 print(f"Chosen search strategy: {search_strategy}")
 
-# use h3
+# domain restriction
 if domain_restriction:
-    # use h1 & h3
+    # domain restriction + linear-search
     if search_strategy == "linear-search":
         print(f"Going to execute at most {len(dim_values)+len(replicas)-1} subexperiments in total..")
         experiment_config = ExperimentConfig(
@@ -44,7 +44,7 @@ if domain_restriction:
             search_strategy=linear_search_strategy,
             subexperiment_executor=subexperiment_executor,
             subexperiment_evaluator=subexperiment_evaluator)
-    # use h2 & h3
+    # domain restriction + binary-search
     elif search_strategy == "binary-search":
         experiment_config = ExperimentConfig(
             use_case=uc,
@@ -59,7 +59,7 @@ if domain_restriction:
             search_strategy=binary_search_strategy,
             subexperiment_executor=subexperiment_executor,
             subexperiment_evaluator=subexperiment_evaluator)
-    # use h0 & h3
+    # domain restriction + check_all
     else:
         print(f"Going to execute {len(dim_values)*len(replicas)} subexperiments in total..")
         experiment_config = ExperimentConfig(
@@ -75,9 +75,9 @@ if domain_restriction:
             search_strategy=check_all_strategy,
             subexperiment_executor=subexperiment_executor,
             subexperiment_evaluator=subexperiment_evaluator)
-# not use h3
+# no domain restriction
 else:
-    # use h1 & !h3
+    # no domain restriction + linear-search
     if search_strategy == "linear-search":
         print(f"Going to execute at most {len(dim_values)+len(replicas)-1} subexperiments in total..")
         experiment_config = ExperimentConfig(
@@ -93,7 +93,7 @@ else:
             search_strategy=linear_search_strategy,
             subexperiment_executor=subexperiment_executor,
             subexperiment_evaluator=subexperiment_evaluator)
-    # use h2 & !h3
+    # no domain restriction + binary-search
     elif search_strategy == "binary-search":
         experiment_config = ExperimentConfig(
             use_case=uc,
@@ -108,7 +108,7 @@ else:
             search_strategy=binary_search_strategy,
             subexperiment_executor=subexperiment_executor,
             subexperiment_evaluator=subexperiment_evaluator)
-    # use h0 & !h3
+    # no domain restriction + check_all
     else:
         print(f"Going to execute {len(dim_values)*len(replicas)} subexperiments in total..")
         experiment_config = ExperimentConfig(