# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you 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. # # Utility functions for calculating common mathematical measurements. Note that although # some of these functions are available in external python packages (ex. numpy), these # are simple enough that it is better to implement them ourselves to avoid extra # dependencies. import math import random import string def calculate_avg(values): return sum(values) / float(len(values)) def calculate_stddev(values): """Return the standard deviation of a numeric iterable.""" avg = calculate_avg(values) return math.sqrt(calculate_avg([(val - avg)**2 for val in values])) def calculate_median(values): """Return the median of a numeric iterable.""" if all([v is None for v in values]): return None sorted_values = sorted(values) length = len(sorted_values) if length % 2 == 0: return (sorted_values[length / 2] + sorted_values[length / 2 - 1]) / 2 else: return sorted_values[length / 2] def calculate_geomean(values): """ Calculates the geometric mean of the given collection of numerics """ if len(values) > 0: product = 1.0 exponent = 1.0 / len(values) for value in values: product *= value ** exponent return product def calculate_tval(avg, stddev, iters, ref_avg, ref_stddev, ref_iters): """ Calculates the t-test t value for the given result and refrence. Uses the Welch's t-test formula. For more information see: http://en.wikipedia.org/wiki/Student%27s_t-distribution#Table_of_selected_values http://en.wikipedia.org/wiki/Student's_t-test """ # SEM (standard error mean) = sqrt(var1/N1 + var2/N2) # t = (X1 - X2) / SEM sem = math.sqrt((math.pow(stddev, 2) / iters) + (math.pow(ref_stddev, 2) / ref_iters)) return (avg - ref_avg) / sem def get_random_id(length): return ''.join( random.choice(string.ascii_uppercase + string.digits) for _ in range(length))