old_contents: #!/usr/bin/env python
  
  ###############################################################################
  # Copyright 2018 The Apollo Authors. All Rights Reserved.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  # http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  ###############################################################################
  
  import numpy as np
  
  
  class PrintColors:
      """ output color schema"""
      HEADER = '\033[95m'
      OKBLUE = '\033[94m'
      OKGREEN = '\033[92m'
      WARNING = '\033[93m'
      FAIL = '\033[91m'
      ENDC = '\033[0m'
      BOLD = '\033[1m'
      UNDERLINE = '\033[4m'
  
  
  class StatisticalAnalyzer:
      """statistical analzer class"""
  
      def print_statistical_results(self, data):
          """ statistical analyzer"""
          if len(data) == 0:
              print PrintColors.FAIL + "No Data Generated!" + PrintColors.ENDC
              return
  
          arr = np.array(data)
  
          v = np.average(arr)
          print PrintColors.OKBLUE + "Average: \t" + PrintColors.ENDC, \
              "{0:.2f}".format(v)
  
          std = np.std(arr)
          print PrintColors.OKBLUE + "STD: \t\t" + PrintColors.ENDC, \
              "{0:.2f}".format(std)
  
          p = np.percentile(arr, 10)
          print PrintColors.OKBLUE + "10 Percentile: \t" + PrintColors.ENDC, \
              "{0:.2f}".format(p)
  
          p = np.percentile(arr, 50)
          print PrintColors.OKBLUE + "50 Percentile: \t" + PrintColors.ENDC, \
              "{0:.2f}".format(p)
  
          p = np.percentile(arr, 90)
          print PrintColors.OKBLUE + "90 Percentile: \t" + PrintColors.ENDC, \
              "{0:.2f}".format(p)
  
          p = np.percentile(arr, 99)
          print PrintColors.OKBLUE + "99 Percentile: \t" + PrintColors.ENDC, \
              "{0:.2f}".format(p)
  
new_contents: #!/usr/bin/env python
  
  ###############################################################################
  # Copyright 2018 The Apollo Authors. All Rights Reserved.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  # http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  ###############################################################################
  
  import numpy as np
  
  
  class PrintColors:
      """ output color schema"""
      HEADER = '\033[95m'
      OKBLUE = '\033[94m'
      OKGREEN = '\033[92m'
      WARNING = '\033[93m'
      FAIL = '\033[91m'
      ENDC = '\033[0m'
      BOLD = '\033[1m'
      UNDERLINE = '\033[4m'
  
  
  class StatisticalAnalyzer:
      """statistical analzer class"""
  
      def print_statistical_results(self, data):
          """ statistical analyzer"""
          if len(data) == 0:
              print PrintColors.FAIL + "No Data Generated!" + PrintColors.ENDC
              return
  
          arr = np.array(data)
  
          v = np.average(arr)
          print PrintColors.OKBLUE + "Average: \t" + PrintColors.ENDC, \
              "{0:.2f}".format(v)
  
          std = np.std(arr)
          print PrintColors.OKBLUE + "STD: \t\t" + PrintColors.ENDC, \
              "{0:.2f}".format(std)
  
          p = np.percentile(arr, 10)
          print PrintColors.OKBLUE + "10 Percentile: \t" + PrintColors.ENDC, \
              "{0:.2f}".format(p)
  
          p = np.percentile(arr, 50)
          print PrintColors.OKBLUE + "50 Percentile: \t" + PrintColors.ENDC, \
              "{0:.2f}".format(p)
  
          p = np.percentile(arr, 90)
          print PrintColors.OKBLUE + "90 Percentile: \t" + PrintColors.ENDC, \
              "{0:.2f}".format(p)
  
          p = np.percentile(arr, 99)
          print PrintColors.OKBLUE + "99 Percentile: \t" + PrintColors.ENDC, \
              "{0:.2f}".format(p)
  
          p = np.min(arr)
          print PrintColors.OKBLUE + "min: \t" + PrintColors.ENDC, \
              "{0:.2f}".format(p)
  
          p = np.max(arr)
          print PrintColors.OKBLUE + "max: \t" + PrintColors.ENDC, \
              "{0:.2f}".format(p)
  
subject: add min/max stats.