Addressing Nits Updating README

Took Vishnu's feedback.
Updated README
Adding `reason` to example ack file

Signed-off-by: Joe Talerico aka rook <joe.talerico@gmail.com>

Author: jtaleric

README.md

@@ -164,17 +164,20 @@ You can open the match requirement by using the ```--node-count``` option to fin
 **_NOTE:_**  The ```cmr```, ```--hunter-analyze``` and ```--anomaly-detection``` flags are mutually exclusive. They cannot be used together because they represent different algorithms designed for distinct use cases.
 
 #### Ack known bugs
-To ack known regressions, you must provide a yaml file with the timestamp which the regression was identified at.
+To ack known regressions, you must provide a yaml file with the uuid and metric which the regression was identified at. Example below
 
 ```
 ---
 ack :
-  - timestamp: 1733490603,
+  - uuid: "af24e294-93da-4729-a9cc-14acf38454e1",
     metric: "etcdCPU_avg"
+    reason: "started thread with etcd team"
 ```
 
 ack'ing regressions will ensure Orion doesn't continue to notify users of the same issues.
 
+Engineers should add a `reason` that could link to a JIRA or Slack thread. Or the `reason` could be the changepoint % diff is too low to alert component teams. 
+
 ### Daemon mode
 The core purpose of Daemon mode is to operate Orion as a self-contained server, dedicated to handling incoming requests. By sending a POST request accompanied by a test name of predefined tests, users can trigger change point detection on the provided metadata and metrics. Following the processing, the response is formatted in JSON, providing a structured output for seamless integration and analysis. To trigger daemon mode just use the following commands
 

ack/ack.yaml renamed to ack/418ack.yaml

@@ -2,9 +2,13 @@
 ack :
   - uuid: "7f7337aa-cee3-4a36-b154-a7c48ed1fb75"
     metric: "etcdCPU_avg"
+    reason: "Under our 10% target"
   - uuid: "22e90f4e-1c79-4d9d-b2f6-b95a7072738c"
     metric: "kubelet_avg"
+    reason: "Opened Dialog with node team"
   - uuid: "22e90f4e-1c79-4d9d-b2f6-b95a7072738c"
     metric: "ovnCPU_avg"
+    reason: "OCPBUGS111111"
   - uuid: "93201652-b496-4594-b1ac-7eb9a32cd609"
     metric: "apiserverCPU_avg"
+    reason: "opened discussion with api team"

pkg/algorithms/edivisive/edivisive.py

@@ -21,29 +21,18 @@ def _analyze(self):
 
 
         # Process if we have ack'ed regression
-        ackList = []
+        ackSet = set()
         if len(self.options["ack"]) > 1 :
             for ack in self.options["ackMap"]["ack"]:
                 pos = series.find_by_attribute("uuid",ack["uuid"])
-                ackList.append(
-                    {"pos" : pos[0],
-                     "metric" : ack["metric"]})
+                ackSet.add(str(pos[0]) + "_" + ack["metric"])
 
         # filter by direction
         for metric, changepoint_list in change_points_by_metric.items():
             for i in range(len(changepoint_list)-1, -1, -1):
-                if ((self.metrics_config[metric]["direction"] == 1 and changepoint_list[i].stats.mean_1 > changepoint_list[i].stats.mean_2) or
-                    (self.metrics_config[metric]["direction"] == -1 and changepoint_list[i].stats.mean_1 < changepoint_list[i].stats.mean_2) ):
+                if ((self.metrics_config[metric]["direction"] == 1 and changepoint_list[i].stats.mean_1 > changepoint_list[i].stats.mean_2) or (self.metrics_config[metric]["direction"] == -1 and changepoint_list[i].stats.mean_1 < changepoint_list[i].stats.mean_2) or (str(changepoint_list[i].index) + "_" + changepoint_list[i].metric in ackSet)):
                     del changepoint_list[i]
 
-        # Filter ack'ed changes
-        for metric, changepoint_list in change_points_by_metric.items():
-            for i in range(len(changepoint_list)-1, -1, -1):
-                for acked in ackList:
-                    if len(changepoint_list) > 0 :
-                        if (changepoint_list[i].index == acked["pos"] and changepoint_list[i].metric == acked["metric"]):
-                            del changepoint_list[i]
-
         if [val for li in change_points_by_metric.values() for val in li]:
             self.regression_flag=True
         return series, change_points_by_metric