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| /* | |
| Copyright (c) 2008 - Chris Buckley. | |
| Permission is granted for use and modification of this file for | |
| research, non-commercial purposes. | |
| */ | |
| double log2(double x); | |
| static int | |
| te_calc_ndcg_p (const EPI *epi, const REL_INFO *rel_info, | |
| const RESULTS *results, const TREC_MEAS *tm, TREC_EVAL *eval); | |
| static PARAMS default_ndcg_gains = { NULL, 0, NULL}; | |
| /* See trec_eval.h for definition of TREC_MEAS */ | |
| TREC_MEAS te_meas_ndcg_p = | |
| {"ndcg_p", | |
| " Normalized Discounted Cumulative Gain\n\ | |
| Compute a traditional nDCG measure according to Jarvelin and\n\ | |
| Kekalainen (ACM ToIS v. 20, pp. 422-446, 2002).\n\ | |
| Gain values are set to the appropriate relevance level by default. \n\ | |
| The default gain can be overridden on the command line by having \n\ | |
| comma separated parameters 'rel_level=gain'.\n\ | |
| Eg, 'trec_eval -m ndcg_p.1=3.5,2=9.0,4=7.0 ...'\n\ | |
| will give gains 3.5, 9.0, 3.0, 7.0 for relevance levels 1,2,3,4\n\ | |
| respectively (level 3 remains at the default).\n\ | |
| Gains are allowed to be 0 or negative, and relevance level 0\n\ | |
| can be given a gain.\n\ | |
| Based on an implementation by Ian Soboroff\n", | |
| te_init_meas_s_float_p_pair, | |
| te_calc_ndcg_p, | |
| te_acc_meas_s, | |
| te_calc_avg_meas_s, | |
| te_print_single_meas_s_float, | |
| te_print_final_meas_s_float_p, | |
| &default_ndcg_gains, -1}; | |
| /* Keep track of valid rel_levels and associated gains */ | |
| /* Initialized in setup_gains */ | |
| typedef struct { | |
| long rel_level; | |
| long num_at_level; | |
| double gain; | |
| } REL_GAIN; | |
| typedef struct { | |
| REL_GAIN *rel_gains; | |
| long num_gains; | |
| long total_num_at_levels; | |
| } GAINS; | |
| static int setup_gains (const TREC_MEAS *tm, const RES_RELS *res_rels, | |
| GAINS *gains); | |
| static double get_gain (const long rel_level, const GAINS *gains); | |
| static int comp_rel_gain (); | |
| static int | |
| te_calc_ndcg_p (const EPI *epi, const REL_INFO *rel_info, | |
| const RESULTS *results, const TREC_MEAS *tm, TREC_EVAL *eval) | |
| { | |
| RES_RELS res_rels; | |
| double gain, sum; | |
| double ideal_dcg; /* ideal discounted cumulative gain */ | |
| long cur_lvl, lvl_count; | |
| long i; | |
| GAINS gains; | |
| if (UNDEF == te_form_res_rels (epi, rel_info, results, &res_rels)) | |
| return (UNDEF); | |
| if (UNDEF == setup_gains (tm, &res_rels, &gains)) | |
| return (UNDEF); | |
| sum = 0.0; | |
| for (i = 0; i < res_rels.num_ret; i++) { | |
| gain = get_gain (res_rels.results_rel_list[i], &gains); | |
| if (gain != 0) { | |
| if (i > 0) | |
| sum += gain / log2((double) (i+1)); | |
| else | |
| sum += gain; | |
| if (epi->debug_level > 0) | |
| printf("ndcg_p:%ld %3.1f %6.4f\n", i, gain, sum); | |
| } | |
| } | |
| /* Calculate ideal discounted cumulative gain for this topic */ | |
| cur_lvl = gains.num_gains - 1; | |
| lvl_count = 0; | |
| ideal_dcg = 0.0; | |
| for (i = 0; i < gains.total_num_at_levels; i++) { | |
| lvl_count++; | |
| while (lvl_count > gains.rel_gains[cur_lvl].num_at_level) { | |
| lvl_count = 1; | |
| cur_lvl--; | |
| if (cur_lvl < 0 || gains.rel_gains[cur_lvl].gain <= 0.0) | |
| break; | |
| } | |
| if (cur_lvl < 0 || gains.rel_gains[cur_lvl].gain <= 0.0) | |
| break; | |
| gain = gains.rel_gains[cur_lvl].gain; | |
| if (i == 0) | |
| ideal_dcg += gain; | |
| else | |
| ideal_dcg += gain / (float) log2((double)(i + 1)); | |
| if (epi->debug_level > 0) | |
| printf("ndcg_p:%ld %ld %3.1f %6.4f\n", i, cur_lvl, gain, ideal_dcg); | |
| } | |
| /* Compare sum to ideal NDCG */ | |
| if (res_rels.num_rel_ret > 0) { | |
| eval->values[tm->eval_index].value = | |
| sum / ideal_dcg; | |
| } | |
| Free (gains.rel_gains); | |
| return (1); | |
| } | |
| static int | |
| setup_gains (const TREC_MEAS *tm, const RES_RELS *res_rels, GAINS *gains) | |
| { | |
| FLOAT_PARAM_PAIR *pairs = NULL; | |
| long num_pairs = 0; | |
| long i,j; | |
| long num_gains; | |
| if (tm->meas_params) { | |
| pairs = (FLOAT_PARAM_PAIR *) tm->meas_params->param_values; | |
| num_pairs = tm->meas_params->num_params; | |
| } | |
| if (NULL == (gains->rel_gains = Malloc(res_rels->num_rel_levels + num_pairs, | |
| REL_GAIN))) | |
| return (UNDEF); | |
| num_gains = 0; | |
| for (i = 0; i < num_pairs; i++) { | |
| gains->rel_gains[num_gains].rel_level = atol (pairs[i].name); | |
| gains->rel_gains[num_gains].gain = (double) pairs[i].value; | |
| gains->rel_gains[num_gains].num_at_level = 0; | |
| num_gains++; | |
| } | |
| for (i = 0; i < res_rels->num_rel_levels; i++) { | |
| for (j = 0; j < num_gains && gains->rel_gains[j].rel_level != i; j++) | |
| ; | |
| if (j < num_gains) | |
| /* Was included in list of parameters. Update occurrence info */ | |
| gains->rel_gains[j].num_at_level = res_rels->rel_levels[i]; | |
| else { | |
| /* Not included in list of parameters. New gain level */ | |
| gains->rel_gains[num_gains].rel_level = i; | |
| gains->rel_gains[num_gains].gain = (double) i; | |
| gains->rel_gains[num_gains].num_at_level = res_rels->rel_levels[i]; | |
| num_gains++; | |
| } | |
| } | |
| /* Sort gains by increasing gain value */ | |
| qsort ((char *) gains->rel_gains, | |
| (int) num_gains, | |
| sizeof (REL_GAIN), | |
| comp_rel_gain); | |
| gains->total_num_at_levels = 0; | |
| for (i = 0; i < num_gains; i++) | |
| gains->total_num_at_levels += gains->rel_gains[i].num_at_level; | |
| gains->num_gains = num_gains; | |
| return (1); | |
| } | |
| static int comp_rel_gain (REL_GAIN *ptr1, REL_GAIN *ptr2) | |
| { | |
| return (ptr1->gain - ptr2->gain); | |
| } | |
| static double | |
| get_gain (const long rel_level, const GAINS *gains) | |
| { | |
| long i; | |
| for (i = 0; i < gains->num_gains; i++) | |
| if (rel_level == gains->rel_gains[i].rel_level) | |
| return (gains->rel_gains[i].gain); | |
| return (0.0); /* Print Error ?? */ | |
| } | |