feat: added the third experimentHEADmaster

6 files changed, 20 insertions, 26 deletions

diff --git a/python_scripts/src/python_scripts/__main__.py b/python_scripts/src/python_scripts/__main__.py
index 4760e17c..896c7c3c 100644
--- a/python_scripts/src/python_scripts/__main__.py
+++ b/python_scripts/src/python_scripts/__main__.py
@@ -1,6 +1,6 @@
 import redis
 import pandas as pd
-import module2
+import threshold_based
 import requests
 from redis.exceptions import (
     ConnectionError,
@@ -18,8 +18,6 @@ r = redis.Redis(redis_host)
 PATH = "/home/matt/src/sunfish/python_scripts/src/python_scripts/resources"
 threshold = 0
 dictionary = {}
-alert_dictionary_red = {}
-alert_dictionary_yellow = {}
 
 
 def iterate(frame):
@@ -62,22 +60,17 @@ As suggested in https://redis.readthedocs.io/en/stable/examples/redis-stream-exa
 toack = lambda k, g, e: r.xack(k, g, e)
 
 
-def print_xreadgroup_reply(reply, f):
+def print_xreadgroup_reply(reply, f, output_file):
     global threshold
     for d_stream in reply:
         for element in d_stream[1]:
-            module2.check_metric(
-                element[1],
-                f,
-                threshold,
-                dictionary,
-                alert_dictionary_red,
-                alert_dictionary_yellow,
+            threshold_based.check_metric(
+                element[1], f, threshold, dictionary, output_file
             )
             toack(d_stream[0], group, element[0])
 
 
-def read_entries(r, f):
+def read_entries(r, f, output_file):
     while True:
         d = r.xreadgroup(
             groupname=group,
@@ -86,15 +79,17 @@ def read_entries(r, f):
             count=10,
             streams={stream_key: ">"},
         )
-        print_xreadgroup_reply(d, f)
+        print_xreadgroup_reply(d, f, output_file)
 
 
 def main():
     try:
         frames = create_dataframes()
         caluclate_threshold(frames[0])
-        print(threshold)
-        read_entries(r, frames[0])
+
+        with open("output.txt", "w", encoding="utf-8") as f:
+            f.write(f"Threshold: {threshold}\n")
+            read_entries(r, frames[0], output_file=f)
 
     except Exception as e:
         print(f"exception caught: {e}")
diff --git a/python_scripts/src/python_scripts/__pycache__/__main__.cpython-314.pyc b/python_scripts/src/python_scripts/__pycache__/__main__.cpython-314.pyc
index f906b7d3..705a695c 100644
--- a/python_scripts/src/python_scripts/__pycache__/__main__.cpython-314.pyc
+++ b/python_scripts/src/python_scripts/__pycache__/__main__.cpython-314.pyc
diff --git a/python_scripts/src/python_scripts/__pycache__/module2.cpython-314.pyc b/python_scripts/src/python_scripts/__pycache__/module2.cpython-314.pyc
index 4dc64294..a88d583d 100644
--- a/python_scripts/src/python_scripts/__pycache__/module2.cpython-314.pyc
+++ b/python_scripts/src/python_scripts/__pycache__/module2.cpython-314.pyc
diff --git a/python_scripts/src/python_scripts/__pycache__/threshold_based.cpython-314.pyc b/python_scripts/src/python_scripts/__pycache__/threshold_based.cpython-314.pyc
new file mode 100644
index 00000000..8817f209
--- /dev/null
+++ b/python_scripts/src/python_scripts/__pycache__/threshold_based.cpython-314.pyc
diff --git a/python_scripts/src/python_scripts/resources/readme.txt b/python_scripts/src/python_scripts/resources/readme.txt
index f921b523..b00086b8 100644
--- a/python_scripts/src/python_scripts/resources/readme.txt
+++ b/python_scripts/src/python_scripts/resources/readme.txt
@@ -1,2 +1,7 @@
 This is the result of a raw simulation with the failureModels set to some statistical distribution in OpenDC.
 Based on the downtime in the `host.parquet` file, we calculate the threshold.
+These results are based on this failureModel:
+{
+    "type": "prefab",
+    "prefabName" : "Pl05Exp"
+}
diff --git a/python_scripts/src/python_scripts/module2.py b/python_scripts/src/python_scripts/threshold_based.py
index 1d54df75..13ce5e42 100644
--- a/python_scripts/src/python_scripts/module2.py
+++ b/python_scripts/src/python_scripts/threshold_based.py
@@ -5,33 +5,27 @@ import numpy as np
 """
 The threshold should be set based on a OpenDC failure model with statistical distribution.
 """
-confidence_red = 0.95
+confidence_red = 0.90
 confidence_yellow = 0.80
 sigma = 0
 
 
-def check_metric(
-    stream, frame, threshold, dictionary, alert_dictionary_red, alert_dictionary_yellow
-):
+def check_metric(stream, frame, threshold, dictionary, output_file):
     timestamp = int(stream[b"timestamp"].decode())
     host = str(stream[b"host_id"].decode())
 
     dictionary[str(timestamp)] = dictionary.get(str(timestamp), 0) + 1
 
     e_t = dictionary.get(str(timestamp))
-
+    # Heuristic based recognition
     if e_t > threshold * confidence_red:
-        print(f"Red,{timestamp}")
-        alert_dictionary_red[str(timestamp)] = alert_dictionary_red.get(str(timestamp), 0) + 1
-        print(alert_dictionary_red)
+        output_file.write(f"Timestamp: {timestamp}, Alarm: red\n")
         alert = {"Name": "Alert", "Type": "Red", "Timestamp": str(timestamp)}
         alert_dt(alert)
         return
 
     if e_t > threshold * confidence_yellow:
-        alert_dictionary_yellow[str(timestamp)] = alert_dictionary_yellow.get(str(timestamp), 0) + 1
-        print(alert_dictionary_yellow)
-        print(f"Yellow,{timestamp}")
+        output_file.write(f"Timestamp: {timestamp}, Alarm: yellow\n")
         alert = {"Name": "Alert", "Type": "Yellow", "Timestamp": str(timestamp)}
         alert_dt(alert)