slips_metrics_getter.py: add a function to directly get the metrics o…

…f a given threshold

scripts/slips_metrics_getter.py

@@ -16,7 +16,7 @@
 from metrics.calculator import Calculator
 
 
-THRESHOLDS_TO_BRUTEFORCE = range(1, 20)
+THRESHOLDS_TO_BRUTEFORCE = range(1, 400)
 
 def print_line():
     print("-"*20)
@@ -270,7 +270,19 @@ def get_metrics_for_each_threshold_for_all_experiments(
 
 
 def print_sum_of_metrics_for_each_threshold(
-    sum_of_confusion_matrix_per_threshold: dict):
+    sum_of_confusion_matrix_per_threshold:  Dict[int, Dict[str, float]]) \
+        -> Dict[int, Dict[str, float]]:
+    """
+    Calculates and prints the rest of the metrics
+    for each threshold in the given dict
+    :param sum_of_confusion_matrix_per_threshold: Dict with the sum of TP
+    FP TN FN for each threshold
+    returns somehting like this
+    {1: {'FPR': ., 'FNR': ., 'TPR': ., 'TNR': ., 'precision': ., 'F1': .,
+     'accuracy': ., 'MCC': .},
+     2: {'FPR': ., 'FNR': ., 'TPR': ., 'TNR': ., 'precision': ., 'F1': .,
+     'accuracy': ., 'MCC': .}
+    """
     print("Printing total error metrics for all thresholds")
     # example of error_rates = {1: {'MCC': 0, 'FPR': 0.2, etc..}}
     error_rates: Dict[int, Dict[str, float]] = {}
@@ -297,8 +309,38 @@ def print_sum_of_metrics_for_each_threshold(
         print_line()
     return error_rates
 
-def main():
+
+def print_error_rates_for_threshold(threshold):
+    """use this when you want to know the metrics of a specific threshold
+    directly without checking the plots"""
+    print(f"Error Rates for threshold: {threshold}")
+    print_line()
 
+    # for each experiment, what are the TPR, FPR, MCC, FP, etc. that
+    # slips would detect if used the given threshold?
+    metrics: Dict[str, Dict[str, float]]
+    metrics = get_experiments_metrics_for_threshold(threshold)
+
+    # is something like
+    # {threshold: {confusion_matrix_sum}}
+    # e.g.
+    # {1: {'TP': sum,  'TN': 'FP':  'FN': ..},
+    #  2: {'TP':sum,  'TN': 'FP': , 'FN': },}
+    sum_of_confusion_matrix: Dict[int, Dict[str, float]] = \
+        get_sum_of_metrics_per_threshold(
+            {threshold: metrics},
+            [
+                'TP',
+                'TN',
+                'FP',
+                'FN',
+            ]
+        )
+    print_sum_of_metrics_for_each_threshold(sum_of_confusion_matrix)
+
+
+
+def main():
     args = parse_args()
 
     expirements_number = len(extracted_threat_levels)