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minccmp.c
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minccmp.c
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/* minccmp.c */
/* */
/* Copyright Andrew Janke - a.janke@gmail.com */
/* Permission to use, copy, modify, and distribute this software and its */
/* documentation for any purpose and without fee is hereby granted, */
/* provided that the above copyright notice appear in all copies. The */
/* author makes no representations about the */
/* suitability of this software for any purpose. It is provided "as is" */
/* without express or implied warranty. */
/* */
/* calculates measures of similarity/difference between 2 or more volumes */
/* */
/* Measures used (sum(x) denotes the sum of x over a volume): */
/* RMSE - Root Mean Squared Error */
/* = sqrt( 1/n * sum((a-b)^2)) */
/* xcorr - Cross Correlation */
/* = sum((a*b)^2) / (sqrt(sum(a^2)) * sqrt(sum(b^2)) */
/* zscore - z-score differences */
/* = sum( |((a - mean(a)) / stdev(a)) - */
/* ((b - mean(b)) / stdev(b))| ) / nvox */
/* */
/* Tue Jun 17 11:31:10 EST 2003 - initial version inspired by voldiff and */
/* peter's compare_volumes */
#include <stdio.h>
#include <stdlib.h>
#include <unistd.h>
#include <math.h>
#include <float.h>
#include <string.h>
#include <voxel_loop.h>
#include <ParseArgv.h>
#ifndef FALSE
# define FALSE 0
#endif
#ifndef TRUE
# define TRUE 1
#endif
#define SQR2(x) ((x) * (x))
/* For Dice statistics, this defines the largest label value on which
* we can report. We don't bother to report statistics for labels that
* are not present in the file.
*/
#define MAX_CMATRIX 10
/* Structure which is used to accumulate the overall similarity
* measures.
*/
struct aggregate_similarity {
double dice_num, dice_den; /* Dice. */
double sens_num, sens_den; /* Sensitivity. */
double spec_num, spec_den; /* Specificity. */
double acc_num, acc_den; /* Accuracy. */
double kappa_num, kappa_den; /* Kappa. */
};
typedef struct {
double nvox;
double sum; /* sum of valid voxels */
double ssum; /* squared sum of valid voxels */
double min;
double max;
double mean;
double var;
double sd;
double sum_prd0; /* sum of product of file[x] with file[0] */
double ssum_add0; /* squared sum of addition of file[x] with file[0] */
double ssum_dif0; /* squared sum of difference of file[x] with file[0] */
double ssum_prd0; /* squared sum of product of file[x] with file[0] */
double sum_zdif0; /* sum of zscore differences of file[x] and file[0] */
/* result stores */
double rmse;
double xcorr;
double zscore;
double vratio;
size_t cmatrix[MAX_CMATRIX][MAX_CMATRIX]; /* Confusion matrix */
} Vol_Data;
typedef struct {
int n_datafiles;
int mask;
int mask_idx;
/* individual volume data */
Vol_Data *vd;
} Loop_Data;
/* Function prototypes */
void pass_0(void *caller_data, long num_voxels,
int input_num_buffers, int input_vector_length,
double *input_data[],
int output_num_buffers, int output_vector_length,
double *output_data[], Loop_Info * loop_info);
void pass_1(void *caller_data, long num_voxels,
int input_num_buffers, int input_vector_length,
double *input_data[],
int output_num_buffers, int output_vector_length,
double *output_data[], Loop_Info * loop_info);
void print_result(char *title, double result);
void print_id_result(char *title, int id, double result);
void dump_stats(Loop_Data * ld);
void do_int_calcs(Loop_Data * ld);
void do_final_calcs(Loop_Data * ld);
/* Argument variables and table */
static int verbose = FALSE;
static int debug = FALSE;
static int quiet = FALSE;
static int clobber = FALSE;
static int max_buffer_size_in_kb = 4 * 1024;
static int check_dim_info = TRUE;
static char *mask_fname = NULL;
static double valid_range[2] = { -DBL_MAX, DBL_MAX };
static int do_all = FALSE;
static int do_ssq = FALSE;
static int do_rmse = FALSE;
static int do_xcorr = FALSE;
static int do_zscore = FALSE;
static int do_vratio = FALSE;
static int do_sim = FALSE;
ArgvInfo argTable[] = {
{"-verbose", ARGV_CONSTANT, (char *)TRUE, (char *)&verbose,
"be verbose"},
{"-debug", ARGV_CONSTANT, (char *)TRUE, (char *)&debug,
"dump all stats info"},
{"-quiet", ARGV_CONSTANT, (char *)TRUE, (char *)&quiet,
"print requested values only"},
{"-clobber", ARGV_CONSTANT, (char *)TRUE, (char *)&clobber,
"clobber existing files"},
{"-max_buffer_size_in_kb", ARGV_INT, (char *)1, (char *)&max_buffer_size_in_kb,
"maximum size of internal buffers."},
{"-check_dimensions", ARGV_CONSTANT, (char *) TRUE, (char *) &check_dim_info,
"Check that files have matching dimensions (default)."},
{"-nocheck_dimensions", ARGV_CONSTANT, (char *) FALSE, (char *) &check_dim_info,
"Do not check that files have matching dimensions."},
{NULL, ARGV_HELP, (char *)NULL, (char *)NULL,
"\nVoxel selection options (applies to first volume ONLY):"},
{"-floor", ARGV_FLOAT, (char *)1, (char *)&valid_range[0],
"Ignore voxels below this value. (incl)"},
{"-ceil", ARGV_FLOAT, (char *)1, (char *)&valid_range[1],
"Ignore voxels above this value. (incl)"},
{"-range", ARGV_FLOAT, (char *)2, (char *)&valid_range,
"Ignore voxels outside the range. (incl)"},
{"-mask", ARGV_STRING, (char *)1, (char *)&mask_fname,
"Use <mask.mnc> for calculations."},
{NULL, ARGV_HELP, (char *)NULL, (char *)NULL,
"\nImage Statistics (printed in this order)"},
{"-all", ARGV_CONSTANT, (char *)TRUE, (char *)&do_all,
"all statistics (default)."},
{"-ssq", ARGV_CONSTANT, (char *)TRUE, (char *)&do_ssq,
"sum of squared difference (2 volumes)"},
{"-rmse", ARGV_CONSTANT, (char *)TRUE, (char *)&do_rmse,
"root mean squared error (2 volumes)"},
{"-xcorr", ARGV_CONSTANT, (char *)TRUE, (char *)&do_xcorr,
"cross correlation (2 volumes)"},
{"-zscore", ARGV_CONSTANT, (char *)TRUE, (char *)&do_zscore,
"z-score (2 volumes)"},
{"-similarity", ARGV_CONSTANT, (char *)TRUE, (char *)&do_sim,
"Similarity measures for labeled volumes (2 volumes)"},
// {"-vr", ARGV_CONSTANT, (char *)TRUE, (char *)&do_vratio,
// "variance ratio (2 volumes)"},
// {NULL, ARGV_HELP, (char *)NULL, (char *)NULL,
// "\nBinary Image Only Statistics"},
// {"-kappa", ARGV_CONSTANT, (char *)TRUE, (char *)&do_kappa,
// "all statistics (default)."},
{NULL, ARGV_HELP, NULL, NULL, ""},
{NULL, ARGV_END, NULL, NULL, NULL}
};
int main(int argc, char *argv[]){
char **infiles;
int n_infiles;
Loop_Options *loop_opt;
Loop_Data ld;
int i;
/* Get arguments */
if(ParseArgv(&argc, argv, argTable, 0) || (argc < 3)){
fprintf(stderr, "\nUsage: %s [options] <in1.mnc> <in2.mnc> [<inn.mnc>]\n", argv[0]);
fprintf(stderr, " %s -help\n\n", argv[0]);
return (EXIT_FAILURE);
}
n_infiles = argc - 1;
infiles = &argv[1];
/* check arguments */
if(!do_rmse && !do_xcorr && !do_zscore && !do_vratio && !do_ssq && !do_sim){
do_all = TRUE;
}
if(do_all){
do_ssq = do_rmse = do_xcorr = do_zscore = do_vratio = TRUE;
}
/* check for infiles */
if(verbose){
fprintf(stderr, "\n+++ infiles +++\n");
}
for(i = 0; i < n_infiles; i++){
if(verbose){
fprintf(stderr, " | [%02d]: %s\n", i, infiles[i]);
}
if(access(infiles[i], F_OK) != 0){
fprintf(stderr, "%s: Couldn't find %s\n", argv[0], infiles[i]);
exit(EXIT_FAILURE);
}
}
/* set up Loop_Data struct and mask file */
ld.n_datafiles = n_infiles;
if(mask_fname != NULL){
if(verbose){
fprintf(stderr, " | mask: %s\n", mask_fname);
}
if(access(mask_fname, F_OK) != 0){
fprintf(stderr, "%s: Couldn't find mask file: %s\n", argv[0], mask_fname);
exit(EXIT_FAILURE);
}
ld.mask = TRUE;
ld.mask_idx = n_infiles;
infiles[n_infiles] = mask_fname;
n_infiles++;
}
else {
ld.mask = FALSE;
ld.mask_idx = 0;
}
/* allocate space and initialise volume stats data */
ld.vd = (Vol_Data *) malloc(sizeof(Vol_Data) * ld.n_datafiles);
for(i = 0; i < ld.n_datafiles; i++){
ld.vd[i].nvox = 0;
ld.vd[i].sum = 0;
ld.vd[i].ssum = 0;
ld.vd[i].min = DBL_MAX;
ld.vd[i].max = -DBL_MAX;
ld.vd[i].sum_prd0 = 0;
ld.vd[i].ssum_add0 = 0;
ld.vd[i].ssum_dif0 = 0;
ld.vd[i].ssum_prd0 = 0;
ld.vd[i].mean = 0;
ld.vd[i].var = 0;
ld.vd[i].sd = 0;
ld.vd[i].rmse = 0.0;
ld.vd[i].xcorr = 0.0;
ld.vd[i].zscore = 0.0;
ld.vd[i].vratio = 0.0;
memset(ld.vd[i].cmatrix, 0, sizeof(ld.vd[i].cmatrix));
}
/* set up and do voxel_loop(s) */
loop_opt = create_loop_options();
set_loop_verbose(loop_opt, verbose);
set_loop_buffer_size(loop_opt, (long)1024 * max_buffer_size_in_kb);
set_loop_check_dim_info(loop_opt, check_dim_info);
/* first pass */
voxel_loop(n_infiles, infiles, 0, NULL, NULL, loop_opt, pass_0, (void *)&ld);
/* intermediate calculations */
do_int_calcs(&ld);
/* run the second pass if we have to */
if(do_zscore){
voxel_loop(n_infiles, infiles, 0, NULL, NULL, loop_opt, pass_1, (void *)&ld);
}
/* final calculations */
do_final_calcs(&ld);
free_loop_options(loop_opt);
if(debug){
dump_stats(&ld);
}
/* calculate and print result(s) */
if(do_all && !quiet){
fprintf(stdout, "file[0]: %s\n", infiles[0]);
fprintf(stdout, "mask file: %s\n", mask_fname);
}
for (i = 1; i < ld.n_datafiles; i++) {
if(do_all && !quiet){
fprintf(stdout, "file[%d]: %s\n", i, infiles[i]);
}
if(do_ssq){
print_result("ssq: ", ld.vd[i].ssum_dif0);
}
if(do_rmse){
print_result("rmse: ", ld.vd[i].rmse);
}
if(do_xcorr){
print_result("xcorr: ", ld.vd[i].xcorr);
}
if(do_zscore){
print_result("zscore: ", ld.vd[i].zscore);
}
if (do_sim) {
double nvox = ld.vd[i].nvox;
int j, k;
struct aggregate_similarity agg_sim = {
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0
};
if (!quiet) {
printf("id dice sens. spec. acc. kappa\n");
}
/* Calculate the Jaccard or Dice coefficients */
for (j = 0; j < MAX_CMATRIX; j++) {
size_t true_pos = ld.vd[i].cmatrix[j][j];
size_t false_pos = 0;
size_t true_neg = 0;
size_t false_neg = 0;
size_t ab_total = 0; /* Total voxels with this label. */
size_t a_total = 0;
size_t b_total = 0;
double dice_similarity_coefficient;
double sensitivity;
double specificity;
double accuracy;
double kappa;
/* Sum all voxels either correctly or incorrectly classified as
* class 'j':
*/
for (k = 0; k < MAX_CMATRIX; k++) {
a_total += ld.vd[i].cmatrix[j][k];
b_total += ld.vd[i].cmatrix[k][j];
}
ab_total = a_total + b_total;
false_pos = b_total - true_pos;
false_neg = a_total - true_pos;
true_neg = nvox - (true_pos + false_pos + false_neg);
if (ab_total == 0) {
continue;
}
dice_similarity_coefficient = (2.0 * true_pos) / ab_total;
sensitivity = (double) true_pos / (true_pos + false_neg);
specificity = (double) true_neg / (true_neg + false_pos);
accuracy = (double) (true_pos + true_neg) / nvox;
kappa = (double) (nvox * true_pos - a_total * b_total) / (nvox * a_total - a_total * b_total);
printf("%2d %.4f %.4f %.4f %.4f %.4f\n",
j,
dice_similarity_coefficient,
sensitivity,
specificity,
accuracy,
kappa);
agg_sim.sens_num += true_pos;
agg_sim.sens_den += (true_pos + false_neg);
agg_sim.spec_num += true_neg;
agg_sim.spec_den += (true_neg + false_pos);
agg_sim.acc_num += (true_pos + true_neg);
agg_sim.acc_den += nvox;
agg_sim.kappa_num += nvox * true_pos - a_total * b_total;
agg_sim.kappa_den += nvox * a_total - a_total * b_total;
}
/* This code for the overall Dice statistic is copied more-or-less
* exactly from voldiff.c
*/
for (j = 1; j < MAX_CMATRIX; j++) {
for (k = 1; k < MAX_CMATRIX; k++) {
agg_sim.dice_num += ld.vd[i].cmatrix[j][k];
}
}
agg_sim.dice_den = 2.0 * agg_sim.dice_num;
for (j = 1; j < MAX_CMATRIX; j++) {
agg_sim.dice_num += ld.vd[i].cmatrix[j][j];
agg_sim.dice_den += ld.vd[i].cmatrix[0][j];
agg_sim.dice_den += ld.vd[i].cmatrix[j][0];
}
printf(" X %.4f %.4f %.4f %.4f %.4f\n",
agg_sim.dice_num / agg_sim.dice_den,
agg_sim.sens_num / agg_sim.sens_den,
agg_sim.spec_num / agg_sim.spec_den,
agg_sim.acc_num / agg_sim.acc_den,
agg_sim.kappa_num / agg_sim.kappa_den);
}
if(!quiet){
fprintf(stdout, "\n");
}
}
return EXIT_SUCCESS;
}
/* voxel loop function for first pass through data */
void pass_0(void *caller_data, long num_voxels,
int input_num_buffers, int input_vector_length,
double *input_data[],
int output_num_buffers, int output_vector_length,
double *output_data[], Loop_Info * loop_info){
long ivox;
double valuei, value0;
int i;
/* get pointer to loop data */
Loop_Data *ld = (Loop_Data *)caller_data;
/* shut the compiler up - yes I _know_ I don't use these */
(void)output_num_buffers;
(void)output_vector_length;
(void)output_data;
(void)loop_info;
/* sanity check */
if((input_num_buffers < 2) || (output_num_buffers != 0)){
fprintf(stderr, "Bad arguments to pass_0\n");
exit(EXIT_FAILURE);
}
/* for each voxel */
for(ivox = num_voxels * input_vector_length; ivox--;){
/* skip voxels out of the mask region */
if(ld->mask && !(int)input_data[ld->mask_idx][ivox]){
continue;
}
value0 = input_data[0][ivox];
if(value0 >= valid_range[0] && value0 <= valid_range[1]){
/* for each volume */
for(i = 0; i < ld->n_datafiles; i++){
valuei = input_data[i][ivox];
/* various voxel sums */
ld->vd[i].nvox++;
ld->vd[i].sum += valuei;
ld->vd[i].ssum += SQR2(valuei);
if (do_sim) {
unsigned int iv0 = floor(value0);
unsigned int ivi = floor(valuei);
if (fabs(iv0 - value0) > 0.01 || fabs(ivi - valuei) > 0.01) {
fprintf(stderr, "ERROR: This does not appear to be an integer volume, Dice or Jaccard statistics will not be useful.\n");
exit(EXIT_FAILURE);
}
if (iv0 < MAX_CMATRIX && ivi < MAX_CMATRIX) {
ld->vd[i].cmatrix[iv0][ivi]++;
}
else {
fprintf(stderr, "ERROR: Can only compute Dice or Jaccard statistics for labeled volumes with a maximum label value of %d.\n", MAX_CMATRIX - 1);
}
}
if(i != 0){
ld->vd[i].sum_prd0 += valuei * value0;
ld->vd[i].ssum_add0 += SQR2(valuei + value0);
ld->vd[i].ssum_dif0 += SQR2(valuei - value0);
ld->vd[i].ssum_prd0 += SQR2(valuei * value0);
}
/* min and max */
if(valuei < ld->vd[i].min){
ld->vd[i].min = valuei;
}
else if(valuei > ld->vd[i].max){
ld->vd[i].max = valuei;
}
}
}
}
return;
}
/* intermediate calculations */
void do_int_calcs(Loop_Data * ld){
int i;
double denom;
for(i = 0; i < ld->n_datafiles; i++){
/* mean */
ld->vd[i].mean = ld->vd[i].sum / ld->vd[i].nvox;
/* variance */
ld->vd[i].var = ((ld->vd[i].nvox * ld->vd[i].ssum) - SQR2(ld->vd[i].sum)) /
(ld->vd[i].nvox * (ld->vd[i].nvox - 1));
/* sd */
ld->vd[i].sd = sqrt(ld->vd[i].var);
/* RMSE */
ld->vd[i].rmse = sqrt((1.0 / ld->vd[0].nvox) * ld->vd[i].ssum_dif0);
/* xcorr */
denom = sqrt(ld->vd[0].ssum * ld->vd[i].ssum);
ld->vd[i].xcorr = (denom == 0.0) ? 0.0 : ld->vd[i].sum_prd0 / denom;
}
}
/* voxel loop function for second pass through data */
void pass_1(void *caller_data, long num_voxels,
int input_num_buffers, int input_vector_length,
double *input_data[],
int output_num_buffers, int output_vector_length,
double *output_data[], Loop_Info * loop_info){
long ivox;
double valuei, value0;
int i;
/* get pointer to loop data */
Loop_Data *ld = (Loop_Data *)caller_data;
/* shut the compiler up - yes I _know_ I don't use these */
(void)output_num_buffers;
(void)output_vector_length;
(void)output_data;
(void)loop_info;
/* sanity check */
if((input_num_buffers < 2) || (output_num_buffers != 0)){
fprintf(stderr, "Bad arguments to pass_1\n");
exit(EXIT_FAILURE);
}
/* for each voxel */
for(ivox = num_voxels * input_vector_length; ivox--;){
/* skip voxels out of the mask region */
if(ld->mask && !(int)input_data[ld->mask_idx][ivox]){
continue;
}
value0 = input_data[0][ivox];
if(value0 >= valid_range[0] && value0 <= valid_range[1]){
/* for each volume */
for(i = 0; i < ld->n_datafiles; i++){
valuei = input_data[i][ivox];
if(i != 0){
/* zscore total */
ld->vd[i].sum_zdif0 +=
fabs(((value0 - ld->vd[0].mean) / ld->vd[0].sd) -
((valuei - ld->vd[i].mean) / ld->vd[i].sd));
}
}
}
}
return;
}
/* final calculations */
void do_final_calcs(Loop_Data * ld){
int i;
for(i = 0; i < ld->n_datafiles; i++){
/* zscore */
ld->vd[i].zscore = ld->vd[i].sum_zdif0 / ld->vd[i].nvox;
}
}
/* dirty little function to print out results */
void print_result(char *title, double result){
if(!quiet){
fprintf(stdout, "%s", title);
}
fprintf(stdout, "%.10g\n", result);
}
void print_id_result(char *title, int id, double result){
if(!quiet){
fprintf(stdout, "%s", title);
}
fprintf(stdout, "%d %.10g\n", id, result);
}
/* debug function to dump stats structure */
void dump_stats(Loop_Data * ld){
int i;
fprintf(stdout, " + Main Loop data structure\n");
fprintf(stdout, " | n_datafiles %d\n", ld->n_datafiles);
fprintf(stdout, " | mask %d\n", ld->mask);
fprintf(stdout, " | mask_idx %d\n", ld->mask_idx);
fprintf(stdout, " +++ volume data stats\n");
for(i = 0; i < ld->n_datafiles; i++){
fprintf(stdout, " |---------------------------------\n");
fprintf(stdout, " | [%02d] nvox %10g\n", i, ld->vd[i].nvox);
fprintf(stdout, " | [%02d] sum %.10g\n", i, ld->vd[i].sum);
fprintf(stdout, " | [%02d] ssum %.10g\n", i, ld->vd[i].ssum);
fprintf(stdout, " | [%02d] min %.10g\n", i, ld->vd[i].min);
fprintf(stdout, " | [%02d] max %.10g\n", i, ld->vd[i].max);
fprintf(stdout, " | [%02d] mean %.10g\n", i, ld->vd[i].mean);
fprintf(stdout, " | [%02d] var %.10g\n", i, ld->vd[i].var);
fprintf(stdout, " | [%02d] sd %.10g\n", i, ld->vd[i].sd);
fprintf(stdout, " | [%02d] sum_prd0 %.10g\n", i, ld->vd[i].sum_prd0);
fprintf(stdout, " | [%02d] ssum_add0 %.10g\n", i, ld->vd[i].ssum_add0);
fprintf(stdout, " | [%02d] ssum_dif0 %.10g\n", i, ld->vd[i].ssum_dif0);
fprintf(stdout, " | [%02d] ssum_prd0 %.10g\n", i, ld->vd[i].ssum_prd0);
fprintf(stdout, " | [%02d] sum_zdif0 %.10g\n", i, ld->vd[i].sum_zdif0);
fprintf(stdout, " | [%02d] rmse %.10g\n", i, ld->vd[i].rmse);
fprintf(stdout, " | [%02d] xcorr %.10g\n", i, ld->vd[i].xcorr);
fprintf(stdout, " | [%02d] zscore %.10g\n", i, ld->vd[i].zscore);
fprintf(stdout, " | [%02d] vratio %.10g\n", i, ld->vd[i].vratio);
}
}