From c65276d0c511687b3e02749089bea5633af4afc5 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Rodolphe=20Qui=C3=A9deville?= Date: Wed, 23 Oct 2013 23:04:29 +0200 Subject: [PATCH] Add unit tests --- test/bear_test.erl | 232 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 232 insertions(+) create mode 100644 test/bear_test.erl diff --git a/test/bear_test.erl b/test/bear_test.erl new file mode 100644 index 0000000..10d447c --- /dev/null +++ b/test/bear_test.erl @@ -0,0 +1,232 @@ +%%% +%%% Copyright 2013, Rodolphe Quiedeville +%%% +%%% 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. +%%% + +%%% ==================================================================== +%%% file : bear_test.erl +%%% @author : Rodolphe Quiedeville +%%% @doc +%%% Unit test for functions defined in bear.erl +%%% @end +%%% ==================================================================== +-module(bear_test). + +-compile(export_all). + +-record(scan_result, {n=0, sumX=0, sumXX=0, sumInv=0, sumLog, max, min}). +-record(scan_result2, {x2=0, x3=0, x4=0}). + +-include_lib("eunit/include/eunit.hrl"). + +-define(PRECISION, 1.0e15). + +get_statistics_1_empty_test() -> + %% get_statistics/1 + %% Empty set of values + Percentile = [{50, 0.0},{75, 0.0},{90, 0.0},{95, 0.0},{99, 0.0},{999, 0.0}], + Stats = bear:get_statistics([]), + ?assertEqual({min, 0.0}, lists:keyfind(min, 1, Stats)), + ?assertEqual({max, 0.0}, lists:keyfind(max, 1, Stats)), + ?assertEqual({arithmetic_mean, 0.0}, lists:keyfind(arithmetic_mean, 1, Stats)), + ?assertEqual({geometric_mean, 0.0}, lists:keyfind(geometric_mean, 1, Stats)), + ?assertEqual({harmonic_mean, 0.0}, lists:keyfind(harmonic_mean, 1, Stats)), + ?assertEqual({median, 0.0}, lists:keyfind(median, 1, Stats)), + ?assertEqual({variance, 0.0}, lists:keyfind(variance, 1, Stats)), + ?assertEqual({standard_deviation, 0.0}, lists:keyfind(standard_deviation, 1, Stats)), + ?assertEqual({skewness, 0.0}, lists:keyfind(skewness, 1, Stats)), + ?assertEqual({kurtosis, 0.0}, lists:keyfind(kurtosis, 1, Stats)), + ?assertEqual({percentile, Percentile}, lists:keyfind(percentile, 1, Stats)), + ?assertEqual({histogram, [{0,0}]}, lists:keyfind(histogram, 1, Stats)), + ?assertEqual({n, 0}, lists:keyfind(n, 1, Stats)). + +get_statistics_1_regular_test() -> + %% get_statistics/1 + %% Non empty set of values + Percentile = [{50, 5},{75, 8},{90, 9},{95, 10},{99, 10},{999, 10}], + Stats = bear:get_statistics(lists:seq(1,10)), + + {geometric_mean, Geometric} = lists:keyfind(geometric_mean, 1, Stats), + {harmonic_mean, Harmonic} = lists:keyfind(harmonic_mean, 1, Stats), + {variance, Variance} = lists:keyfind(variance, 1, Stats), + {standard_deviation, StandardDeviation} = lists:keyfind(standard_deviation, 1, Stats), + {kurtosis, Kurtosis} = lists:keyfind(kurtosis, 1, Stats), + + ?assertEqual({min, 1}, lists:keyfind(min, 1, Stats)), + ?assertEqual({max, 10}, lists:keyfind(max, 1, Stats)), + ?assertEqual({arithmetic_mean, 5.5}, lists:keyfind(arithmetic_mean, 1, Stats)), + ?assertEqual(4528728688116766, erlang:trunc(?PRECISION * Geometric)), + ?assertEqual(3414171521474055, erlang:trunc(?PRECISION * Harmonic)), + ?assertEqual({median, 5}, lists:keyfind(median, 1, Stats)), + ?assertEqual(9166666666666666, erlang:trunc(?PRECISION * Variance)), + ?assertEqual(3027650354097491, erlang:trunc(?PRECISION * StandardDeviation)), + ?assertEqual({skewness, 0.0}, lists:keyfind(skewness, 1, Stats)), + ?assertEqual(-1561636363636363, erlang:trunc(?PRECISION * Kurtosis)), + ?assertEqual({percentile, Percentile}, lists:keyfind(percentile, 1, Stats)), + ?assertEqual({histogram, [{6,6},{11,4},{16,0}]}, lists:keyfind(histogram, 1, Stats)), + ?assertEqual({n, 10}, lists:keyfind(n, 1, Stats)). + +get_statistics_2_1_test() -> + %% get_statistics/2 + %% First set of values is empty + Stats = bear:get_statistics(lists:seq(1,10), []), + ?assertEqual(0.0, Stats). + +get_statistics_3_test() -> + %% get_statistics/2 + %% Second set of values is empty + Stats = bear:get_statistics([], lists:seq(1,10)), + ?assertEqual(0.0, Stats). + +get_statistics_4_test() -> + %% get_statistics/2 + %% Two set of values with different sizes + Stats = bear:get_statistics(lists:seq(1,10),lists:seq(1,20)), + ?assertEqual(0.0, Stats). + +get_statistics_5_test() -> + %% get_statistics/2 + %% Two set of values are valid + Stats = bear:get_statistics(lists:seq(0,10),lists:seq(4,24,2)), + ?assertEqual({covariance, 20.0}, lists:keyfind(covariance, 1, Stats)), + ?assertEqual({tau, 1.0}, lists:keyfind(tau, 1, Stats)), + ?assertEqual({rho, 1.0}, lists:keyfind(rho, 1, Stats)), + ?assertEqual({r, 1.0}, lists:keyfind(r, 1, Stats)). + +scan_values_test() -> + ?assertEqual(#scan_result{n=8}, bear:scan_values([], #scan_result{n=8})), + ?assertEqual(#scan_result{n=1,sumX=1,sumXX=1,sumInv=1.0,sumLog=0.0,max=1,min=1}, bear:scan_values([1])), + ?assertEqual(#scan_result{n=4,sumX=10,sumXX=30,sumInv=2.083333333333333,sumLog=3.1780538303479453,max=4,min=1}, + bear:scan_values([1,3,2,4])). + +scan_values2_test() -> + ?assertEqual(#scan_result{n=8}, bear:scan_values2([], 3, #scan_result{n=8})), + ?assertEqual(#scan_result2{x2=6.6875,x3=-13.359375,x4=28.07421875}, bear:scan_values2([4,3,5], #scan_result{n=8,sumX=42})). + +revsort_test() -> + ?assertEqual([], bear:revsort([])), + ?assertEqual([4,3,2], bear:revsort([3,2,4])). + +arithmetic_mean_test() -> + ?assertEqual(10.0, bear:arithmetic_mean(#scan_result{n=4, sumX=40})). + +geometric_mean_test() -> + ?assertEqual(25.790339917193062, bear:geometric_mean(#scan_result{n=4, sumLog=13})). + +harmonic_mean_test() -> + ?assertEqual(0, bear:harmonic_mean(#scan_result{n=100, sumInv=0})), + ?assertEqual(10.0, bear:harmonic_mean(#scan_result{n=100, sumInv=10})). + +percentile_test() -> + ?assertEqual(3, bear:percentile([1,2,3,4,5], #scan_result{n=5},0.5)), + ?assertEqual(5, bear:percentile([1,2,3,4,5], #scan_result{n=5},0.95)). + +variance_test() -> + ?assertEqual(7.0, bear:variance(#scan_result{n=7},#scan_result2{x2=42})). + +std_deviation_test() -> + ?assertEqual(3.0, bear:std_deviation(#scan_result{n=10},#scan_result2{x2=81})). + +skewness_test() -> + ?assertEqual(0.0, bear:skewness(#scan_result{n=10},#scan_result2{x2=0,x3=81})), + ?assertEqual(3.0, bear:skewness(#scan_result{n=10},#scan_result2{x2=81,x3=810})). + +kurtosis_test() -> + ?assertEqual(0.0, bear:kurtosis(#scan_result{n=10},#scan_result2{x2=0,x4=81})), + ?assertEqual(-2.0, bear:kurtosis(#scan_result{n=10},#scan_result2{x2=81,x4=810})). + +update_bin_1_test() -> + %% with empty dict + Dict = dict:new(), + C = bear:update_bin(4, [4], Dict), + ?assertEqual(1, dict:fetch(4, C)). + +get_covariance_test() -> + %% Array 1 is too short + ?assertEqual(0.0, bear:get_covariance([], [2,1,2,3,4,5,6])), + %% Array 2 is too short + ?assertEqual(0.0, bear:get_covariance([1,2,3,4,5,6], [])), + %% diffenrent arry length + ?assertEqual(0.0, bear:get_covariance([1,2,3,4,5,6], [1,2,3,4,5,6,7])), + %% Usual case + ?assertEqual(-30944444444444444, erlang:trunc(?PRECISION * bear:get_covariance([11,2,3,41,5,9], [34,2,23,4,5,6]))). + +ranks_of_test() -> + ?assertEqual([4.0,3.0,1.0,2.0], bear:ranks_of([3,4,15,6])). + +get_pearson_correlation_test() -> + ?assertEqual(0.0, bear:get_pearson_correlation([], 42)), + ?assertEqual(0.0, bear:get_pearson_correlation(42, [])), + ?assertEqual(0.0, bear:get_pearson_correlation(lists:seq(1,10), lists:seq(1,11))), + ?assertEqual(1.0, bear:get_pearson_correlation(lists:seq(1,10), lists:seq(1,10))), + ?assertEqual(1.0, bear:get_pearson_correlation(lists:seq(0,10), lists:seq(5,15))), + ?assertEqual(1.0, bear:get_pearson_correlation(lists:seq(40,60,2), lists:seq(10,20))). + + +round_bin_test() -> + ?assertEqual(10, bear:round_bin(10)), + ?assertEqual(10, bear:round_bin(10, 5)), + ?assertEqual(42, bear:round_bin(15, 42)), + ?assertEqual(45, bear:round_bin(42, 15)). + +get_bin_width_test() -> + ?assertEqual(1, bear:get_bin_width(0, 10)), + ?assertEqual(22, bear:get_bin_width(10.0, 4.0)). + +get_bin_count_test() -> + ?assertEqual(3, bear:get_bin_count(9, 15, 3)), + ?assertEqual(4, bear:get_bin_count(10.2, 20.2, 4)). + +get_kendall_correlation_test()-> + ?assertEqual(0.0, bear:get_kendall_correlation([], [])), + ?assertEqual(0.0, bear:get_kendall_correlation([], [1,2,3,4,5,6,7])), + ?assertEqual(0.0, bear:get_kendall_correlation([1,2,3,4,5,6,7],[])), + ?assertEqual(0.0, bear:get_kendall_correlation(lists:seq(1,10),lists:seq(1,11))), + ?assertEqual(1.0, bear:get_kendall_correlation([1,2,3,4,5,6,7], [2,3,4,5,6,7,9])). + +get_spearman_correlation_test()-> + ?assertEqual(0.0, bear:get_spearman_correlation([], [])), + ?assertEqual(0.0, bear:get_spearman_correlation([], [1,2,3,4,5,6,7])), + ?assertEqual(0.0, bear:get_spearman_correlation([1,2,3,4,5,6,7],[])), + ?assertEqual(0.0, bear:get_spearman_correlation(lists:seq(1,10),lists:seq(1,11))), + ?assertEqual(1.0, bear:get_spearman_correlation([1,2,3,4,5,6,7], [2,3,4,5,6,7,9])). + + +math_log_test() -> + ?assertEqual(1, bear:math_log(0)), + ?assertEqual(1.0, bear:math_log(0.0)), + ?assertEqual(3737669618283368, erlang:trunc(?PRECISION * bear:math_log(42))). + +inverse_test() -> + ?assertEqual(0, bear:inverse(0)), + ?assertEqual(0.0, bear:inverse(0.0)), + ?assertEqual(0.5, bear:inverse(2)). + +get_hist_bins_test() -> + ?assertEqual([4], bear:get_hist_bins(1, 4, 5, 10)). + +tied_ordered_ranking_test() -> + ?assertEqual([3,2,1], bear:tied_ordered_ranking([], [], [1,2,3])). + +kendall_right_off_test() -> + %% empty array + ?assertEqual("654321", bear:kendall_right_of([],"123456")). + +tied_add_prev_test() -> + ?assertEqual([{2.5,5},{2.5,5},{2.5,5},{2.5,5},{2,3}], bear:tied_add_prev([{2, 3}], {[1,2,3,4], 5})). + +tied_rank_worker_test() -> + ?assertEqual([{2.0,5},{2.0,5},{2.0,5},{2.0,5}], bear:tied_rank_worker([], [{2.0,5}], {[1,2,3], 5})), + ?assertEqual([{2.0,5},{2.0,5},{2.0,5},{2.0,5},{2.0,5},{2.0,5}], + bear:tied_rank_worker([{2.0,5},{2.0,5}], [{2.0,5}], {[1,2,3], 5})).