| /* |
| * 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. |
| */ |
| |
| #ifndef BOUNDS_ON_RATIOS_IN_SAMPLED_SETS_HPP_ |
| #define BOUNDS_ON_RATIOS_IN_SAMPLED_SETS_HPP_ |
| |
| #include <cstdint> |
| #include <string> |
| |
| #include "bounds_binomial_proportions.hpp" |
| |
| namespace datasketches { |
| |
| /** |
| * This class is used to compute the bounds on the estimate of the ratio <i>|B| / |A|</i>, where: |
| * <ul> |
| * <li><i>|A|</i> is the unknown size of a set <i>A</i> of unique identifiers.</li> |
| * <li><i>|B|</i> is the unknown size of a subset <i>B</i> of <i>A</i>.</li> |
| * <li><i>a</i> = <i>|S<sub>A</sub>|</i> is the observed size of a sample of <i>A</i> |
| * that was obtained by Bernoulli sampling with a known inclusion probability <i>f</i>.</li> |
| * <li><i>b</i> = <i>|S<sub>A</sub> ∩ B|</i> is the observed size of a subset |
| * of <i>S<sub>A</sub></i>.</li> |
| * </ul> |
| */ |
| class bounds_on_ratios_in_sampled_sets { |
| public: |
| static constexpr double NUM_STD_DEVS = 2.0; |
| |
| /** |
| * Return the approximate lower bound based on a 95% confidence interval |
| * @param a See class javadoc |
| * @param b See class javadoc |
| * @param f the inclusion probability used to produce the set with size <i>a</i> and should |
| * generally be less than 0.5. Above this value, the results not be reliable. |
| * When <i>f</i> = 1.0 this returns the estimate. |
| * @return the approximate upper bound |
| */ |
| static double lower_bound_for_b_over_a(uint64_t a, uint64_t b, double f) { |
| check_inputs(a, b, f); |
| if (a == 0) return 0.0; |
| if (f == 1.0) return static_cast<double>(b) / static_cast<double>(a); |
| return bounds_binomial_proportions::approximate_lower_bound_on_p(a, b, NUM_STD_DEVS * hacky_adjuster(f)); |
| } |
| |
| /** |
| * Return the approximate upper bound based on a 95% confidence interval |
| * @param a See class javadoc |
| * @param b See class javadoc |
| * @param f the inclusion probability used to produce the set with size <i>a</i>. |
| * @return the approximate lower bound |
| */ |
| static double upper_bound_for_b_over_a(uint64_t a, uint64_t b, double f) { |
| check_inputs(a, b, f); |
| if (a == 0) return 1.0; |
| if (f == 1.0) return static_cast<double>(b) / static_cast<double>(a); |
| return bounds_binomial_proportions::approximate_upper_bound_on_p(a, b, NUM_STD_DEVS * hacky_adjuster(f)); |
| } |
| |
| /** |
| * Return the estimate of b over a |
| * @param a See class javadoc |
| * @param b See class javadoc |
| * @return the estimate of b over a |
| */ |
| static double get_estimate_of_b_over_a(uint64_t a, uint64_t b) { |
| check_inputs(a, b, 0.3); |
| if (a == 0) return 0.5; |
| return static_cast<double>(b) / static_cast<double>(a); |
| } |
| |
| /** |
| * Return the estimate of A. See class javadoc. |
| * @param a See class javadoc |
| * @param f the inclusion probability used to produce the set with size <i>a</i>. |
| * @return the approximate lower bound |
| */ |
| static double estimate_of_a(uint64_t a, uint64_t f) { |
| check_inputs(a, 1, f); |
| return a / f; |
| } |
| |
| /** |
| * Return the estimate of B. See class javadoc. |
| * @param b See class javadoc |
| * @param f the inclusion probability used to produce the set with size <i>b</i>. |
| * @return the approximate lower bound |
| */ |
| static double estimate_of_b(uint64_t b, double f) { |
| check_inputs(b + 1, b, f); |
| return b / f; |
| } |
| |
| private: |
| /** |
| * This hackyAdjuster is tightly coupled with the width of the confidence interval normally |
| * specified with number of standard deviations. To simplify this interface the number of |
| * standard deviations has been fixed to 2.0, which corresponds to a confidence interval of |
| * 95%. |
| * @param f the inclusion probability used to produce the set with size <i>a</i>. |
| * @return the hacky Adjuster |
| */ |
| static double hacky_adjuster(double f) { |
| const double tmp = sqrt(1.0 - f); |
| return (f <= 0.5) ? tmp : tmp + (0.01 * (f - 0.5)); |
| } |
| |
| static void check_inputs(uint64_t a, uint64_t b, double f) { |
| if (a < b) { |
| throw std::invalid_argument("a must be >= b: a = " + std::to_string(a) + ", b = " + std::to_string(b)); |
| } |
| if ((f > 1.0) || (f <= 0.0)) { |
| throw std::invalid_argument("Required: ((f <= 1.0) && (f > 0.0)): " + std::to_string(f)); |
| } |
| } |
| |
| }; |
| |
| } /* namespace datasketches */ |
| |
| # endif |