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accuracy.c
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accuracy.c
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/************************************************************************
* *
* Program package 'lvq_pak': *
* *
* accuracy.c *
* -computes the recognition accuracy by the nearest-neighbor rule *
* *
* Version 3.0 *
* Date: 1 Mar 1995 *
* *
* NOTE: This program package is copyrighted in the sense that it *
* may be used for scientific purposes. The package as a whole, or *
* parts thereof, cannot be included or used in any commercial *
* application without written permission granted by its producents. *
* No programs contained in this package may be copied for commercial *
* distribution. *
* *
* All comments concerning this program package may be sent to the *
* e-mail address 'lvq@cochlea.hut.fi'. *
* *
************************************************************************/
#include <stdio.h>
#include <float.h>
#include "lvq_pak.h"
#include "datafile.h"
static char *usage[] = {
"accuracy - computes the recognition accuracy by the nearest-neighbor rule\n",
"Required parameters:\n",
" -cin filename codebook file\n",
" -din filename test data\n",
"Optional parameters:\n",
" -cfout filename output classification file\n",
" -buffer integer buffered reading of data, integer lines at a time\n",
" -selfuncs name select a set of functions\n",
NULL};
int compute_accuracy(struct teach_params *teach, struct file_info *of)
{
long total, stotal, noc;
struct winner_info winner;
struct hitlist *correct, *totals;
struct hit_entry *he;
FILE *ocf;
int datalabel;
struct entries *data = teach->data;
struct entries *codes = teach->codes;
WINNER_FUNCTION *find_winner = teach->winner;
struct data_entry *datatmp;
eptr p;
ocf = of ? fi2fp(of) : NULL;
if ((correct = new_hitlist()) == NULL)
{
return ERR_NOMEM;
}
if ((totals = new_hitlist()) == NULL)
{
free_hitlist(correct);
return ERR_NOMEM;
}
stotal = 0;
total = 0;
if ((datatmp = rewind_entries(data, &p)) == NULL)
{
fprintf(stderr, "compute_accuracy: can't get data\n");
goto end;
}
/* Number of data vectors */
noc = data->flags.totlen_known ? data->num_entries : 0;
/* Scan all input entries */
while (datatmp != NULL) {
find_winner(codes, datatmp, &winner, 1);
/* If classification was correct */
datalabel = get_entry_label(datatmp);
if (get_entry_label(winner.winner) == datalabel) {
/* Number of correct classifications */
stotal++;
/* Number of correct classifications in that class */
add_hit(correct, datalabel);
/* Write '1' to classification description file */
if (ocf != NULL) fprintf(ocf,"1\n");
} else {
/* Write '0' to classification description file */
if (ocf != NULL) fprintf(ocf,"0\n");
}
/* Total number of entries in that class */
add_hit(totals, datalabel);
/* Total number of entries */
total++;
/* Take the next input entry */
datatmp = next_entry(&p);
ifverbose(1)
if (noc)
mprint((long) noc--);
}
ifverbose(1)
{
mprint((long) 0);
fprintf(stderr, "\n");
}
fprintf(stdout, "\nRecognition accuracy:\n\n");
for (he = totals->head; he != NULL; he = he->next)
{
long res, tot;
tot = he->freq;
res = hitlist_label_freq(correct, he->label);
fprintf(stdout, "%9s: %4ld entries ", find_conv_to_lab(he->label), tot);
fprintf(stdout, "%6.2f %%\n", 100.0 * (float) res / tot);
}
fprintf(stdout, "\nTotal accuracy: %5ld entries %6.2f %%\n\n", total,
100.0 * (float) stotal / total);
end:
free_hitlist(correct);
free_hitlist(totals);
return 0;
}
int main(int argc, char **argv)
{
char *in_data_file;
char *in_code_file;
char *out_classification_file;
struct entries *data = NULL, *codes = NULL;
struct file_info *ocf=NULL;
int error = 0;
long buffer = 0;
struct teach_params params;
char *funcname = NULL;
global_options(argc, argv);
if (extract_parameter(argc, argv, "-help", OPTION2))
{
printhelp();
exit(0);
}
in_data_file = extract_parameter(argc, argv, IN_DATA_FILE, ALWAYS);
in_code_file = extract_parameter(argc, argv, IN_CODE_FILE, ALWAYS);
buffer = oatoi(extract_parameter(argc, argv, "-buffer", OPTION), 0);
out_classification_file =
extract_parameter(argc, argv, OUT_CLASSIFICATION_FILE, OPTION);
funcname = extract_parameter(argc, argv, "-selfuncs", OPTION);
ifverbose(2)
fprintf(stderr, "Input entries are read from file %s\n", in_data_file);
if ((data = open_entries(in_data_file)) == NULL)
{
fprintf(stderr, "Can't open data file '%s'\n", in_data_file);
error = 1;
goto end;
}
ifverbose(2)
fprintf(stderr, "Codebook entries are read from file %s\n", in_code_file);
if ((codes = open_entries(in_code_file)) == NULL)
{
fprintf(stderr, "Can't open code file '%s'\n", in_data_file);
error = 1;
goto end;
}
if (data->dimension != codes->dimension) {
fprintf(stderr, "Data and codebook vectors have different dimensions");
error = 1;
goto end;
}
if (out_classification_file != NULL) {
ifverbose(2)
fprintf(stderr, "Classifications are saved to file %s\n",
out_classification_file);
if ((ocf = open_file(out_classification_file, "w")) == NULL) {
fprintf(stderr, "Cannot open '%s' for output\n",out_classification_file);
error = 1;
goto end;
}
}
set_teach_params(¶ms, codes, data, buffer, funcname);
compute_accuracy(¶ms, ocf);
end:
if (ocf)
close_file(ocf);
if (data)
close_entries(data);
if (codes)
close_entries(codes);
return(error);
}