code: def findCorrelationListPerAnomaly():
      ts = urllib.unquote(request.args.get("ts")[1:])
      all_ts = os.listdir(DATA_PATH)
      matrices = list()
      for t in all_ts:
          t = DATA_PATH + t
          if t.endswith(".csv") and t != ts:
              matrices.append(t)
      myluminol = RCA(ts, matrices)
      result = myluminol.output
      r = list()
      for t in result:
          l = result[t]
          data = list()
          for entry in l:
              data.append([entry[3]] + entry[2].values())
          data_sorted = sorted(data, key=lambda k: (-k[1], k[2], -k[3]))
          r.append([t, data_sorted])
      return jsonify(anom=r)
  
file_path: luminol/demo/src/start.py
imports: import csv
  import datetime
  import os
  import sys
  import time
  import urllib
  from flask import Flask, jsonify, render_template, request
  from luminol import utils, anomaly_detector, correlator
  from rca import RCA
label_desc: Use image node_id 5 for calling a global function with example usage: findCorrelationListPerAnomaly() and returns: jsonify