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/* | |
Copyright (c) 2008 - Chris Buckley. | |
Permission is granted for use and modification of this file for | |
research, non-commercial purposes. | |
*/ | |
static int | |
te_calc_P (const EPI *epi, const REL_INFO *rel_info, const RESULTS *results, | |
const TREC_MEAS *tm, TREC_EVAL *eval); | |
static long long_cutoff_array[] = {5, 10, 15, 20, 30, 100, 200, 500, 1000}; | |
static PARAMS default_P_cutoffs = { | |
NULL, sizeof (long_cutoff_array) / sizeof (long_cutoff_array[0]), | |
&long_cutoff_array[0]}; | |
/* See trec_eval.h for definition of TREC_MEAS */ | |
TREC_MEAS te_meas_P = | |
{"P", | |
" Precision at cutoffs\n\ | |
Precision measured at various doc level cutoffs in the ranking.\n\ | |
If the cutoff is larger than the number of docs retrieved, then\n\ | |
it is assumed nonrelevant docs fill in the rest. Eg, if a method\n\ | |
retrieves 15 docs of which 4 are relevant, then P20 is 0.2 (4/20).\n\ | |
Precision is a very nice user oriented measure, and a good comparison\n\ | |
number for a single topic, but it does not average well. For example,\n\ | |
P20 has very different expected characteristics if there 300\n\ | |
total relevant docs for a topic as opposed to 10.\n\ | |
Note: trec_eval -m P.50 ...\n\ | |
is different from \n\ | |
trec_eval -M 50 -m set_P ...\n\ | |
in that the latter will not fill in with nonrel docs if less than 50\n\ | |
docs retrieved\n\ | |
Cutoffs must be positive without duplicates\n\ | |
Default param: -m P.5,10,15,20,30,100,200,500,1000\n", | |
te_init_meas_a_float_cut_long, | |
te_calc_P, | |
te_acc_meas_a_cut, | |
te_calc_avg_meas_a_cut, | |
te_print_single_meas_a_cut, | |
te_print_final_meas_a_cut, | |
(void *) &default_P_cutoffs, -1}; | |
static int | |
te_calc_P (const EPI *epi, const REL_INFO *rel_info, const RESULTS *results, | |
const TREC_MEAS *tm, TREC_EVAL *eval) | |
{ | |
long *cutoffs = (long *) tm->meas_params->param_values; | |
long cutoff_index = 0; | |
long i; | |
RES_RELS res_rels; | |
long rel_so_far = 0; | |
if (UNDEF == te_form_res_rels (epi, rel_info, results, &res_rels)) | |
return (UNDEF); | |
for (i = 0; i < res_rels.num_ret; i++) { | |
if (i == cutoffs[cutoff_index]) { | |
/* Calculate previous cutoff threshold. | |
Note all guaranteed to be positive by init_meas */ | |
eval->values[tm->eval_index + cutoff_index].value = | |
(double) rel_so_far / (double) i; | |
if (++cutoff_index == tm->meas_params->num_params) | |
break; | |
} | |
if (res_rels.results_rel_list[i] >= epi->relevance_level) | |
rel_so_far++; | |
} | |
/* calculate values for those cutoffs not achieved */ | |
while (cutoff_index < tm->meas_params->num_params) { | |
eval->values[tm->eval_index+cutoff_index].value = | |
(double) rel_so_far / (double) cutoffs[cutoff_index]; | |
cutoff_index++; | |
} | |
return (1); | |
} | |