def processCategoricalHistogramData()

in lib/analysis.py [0:0]

• 19 lines of code
• 4 McCabe index (conditional complexity)

  def processCategoricalHistogramData(self, hist, data, branch, segment):
    hist_name = hist.split('.')[-1]
    print(f"      processing categorical histogram: {hist}")
    desc = self.config["histograms"][hist]["desc"]
    labels = data[branch][segment]["histograms"][hist]["bins"]
    counts = data[branch][segment]["histograms"][hist]["counts"]

    self.results[branch][segment]["histograms"][hist_name]["desc"] = desc
    self.results[branch][segment]["histograms"][hist_name]["labels"] = labels
    self.results[branch][segment]["histograms"][hist_name]["counts"] = counts
    total = sum(counts)

    self.results[branch][segment]["histograms"][hist_name]["sum"] = total
    ratios = [x/total for x in counts]
    self.results[branch][segment]["histograms"][hist_name]["ratios"] = ratios

    if branch != self.control:
      ratios_control = self.results[self.control][segment]["histograms"][hist_name]["ratios"]
      uplift = []
      for i in range(len(ratios)):
        uplift.append((ratios[i]-ratios_control[i])*100)
        self.results[branch][segment]["histograms"][hist_name]["uplift"] = uplift