From fdaf1d0640af0da11005a483de8533803a6ae42d Mon Sep 17 00:00:00 2001 From: Mans Rullgard Date: Fri, 8 Jul 2011 12:52:12 +0100 Subject: lls: whitespace cosmetics Signed-off-by: Mans Rullgard --- libavutil/lls.c | 133 +++++++++++++++++++++++++++++++------------------------- 1 file changed, 74 insertions(+), 59 deletions(-) (limited to 'libavutil/lls.c') diff --git a/libavutil/lls.c b/libavutil/lls.c index 679738530d..eba7375854 100644 --- a/libavutil/lls.c +++ b/libavutil/lls.c @@ -30,76 +30,88 @@ #include "lls.h" -void av_init_lls(LLSModel *m, int indep_count){ +void av_init_lls(LLSModel *m, int indep_count) +{ memset(m, 0, sizeof(LLSModel)); - - m->indep_count= indep_count; + m->indep_count = indep_count; } -void av_update_lls(LLSModel *m, double *var, double decay){ - int i,j; +void av_update_lls(LLSModel *m, double *var, double decay) +{ + int i, j; - for(i=0; i<=m->indep_count; i++){ - for(j=i; j<=m->indep_count; j++){ + for (i = 0; i <= m->indep_count; i++) { + for (j = i; j <= m->indep_count; j++) { m->covariance[i][j] *= decay; - m->covariance[i][j] += var[i]*var[j]; + m->covariance[i][j] += var[i] * var[j]; } } } -void av_solve_lls(LLSModel *m, double threshold, int min_order){ - int i,j,k; - double (*factor)[MAX_VARS+1]= (void*)&m->covariance[1][0]; - double (*covar )[MAX_VARS+1]= (void*)&m->covariance[1][1]; - double *covar_y = m->covariance[0]; - int count= m->indep_count; - - for(i=0; i=0; k--) - sum -= factor[i][k]*factor[j][k]; - - if(i==j){ - if(sum < threshold) - sum= 1.0; - factor[i][i]= sqrt(sum); - }else - factor[j][i]= sum / factor[i][i]; +void av_solve_lls(LLSModel *m, double threshold, int min_order) +{ + int i, j, k; + double (*factor)[MAX_VARS + 1] = (void *) &m->covariance[1][0]; + double (*covar) [MAX_VARS + 1] = (void *) &m->covariance[1][1]; + double *covar_y = m->covariance[0]; + int count = m->indep_count; + + for (i = 0; i < count; i++) { + for (j = i; j < count; j++) { + double sum = covar[i][j]; + + for (k = i - 1; k >= 0; k--) + sum -= factor[i][k] * factor[j][k]; + + if (i == j) { + if (sum < threshold) + sum = 1.0; + factor[i][i] = sqrt(sum); + } else { + factor[j][i] = sum / factor[i][i]; + } } } - for(i=0; i=0; k--) - sum -= factor[i][k]*m->coeff[0][k]; - m->coeff[0][i]= sum / factor[i][i]; + + for (i = 0; i < count; i++) { + double sum = covar_y[i + 1]; + + for (k = i - 1; k >= 0; k--) + sum -= factor[i][k] * m->coeff[0][k]; + + m->coeff[0][i] = sum / factor[i][i]; } - for(j=count-1; j>=min_order; j--){ - for(i=j; i>=0; i--){ - double sum= m->coeff[0][i]; - for(k=i+1; k<=j; k++) - sum -= factor[k][i]*m->coeff[j][k]; - m->coeff[j][i]= sum / factor[i][i]; + for (j = count - 1; j >= min_order; j--) { + for (i = j; i >= 0; i--) { + double sum = m->coeff[0][i]; + + for (k = i + 1; k <= j; k++) + sum -= factor[k][i] * m->coeff[j][k]; + + m->coeff[j][i] = sum / factor[i][i]; } - m->variance[j]= covar_y[0]; - for(i=0; i<=j; i++){ - double sum= m->coeff[j][i]*covar[i][i] - 2*covar_y[i+1]; - for(k=0; kcoeff[j][k]*covar[k][i]; - m->variance[j] += m->coeff[j][i]*sum; + m->variance[j] = covar_y[0]; + + for (i = 0; i <= j; i++) { + double sum = m->coeff[j][i] * covar[i][i] - 2 * covar_y[i + 1]; + + for (k = 0; k < i; k++) + sum += 2 * m->coeff[j][k] * covar[k][i]; + + m->variance[j] += m->coeff[j][i] * sum; } } } -double av_evaluate_lls(LLSModel *m, double *param, int order){ +double av_evaluate_lls(LLSModel *m, double *param, int order) +{ int i; - double out= 0; + double out = 0; - for(i=0; i<=order; i++) - out+= param[i]*m->coeff[order][i]; + for (i = 0; i <= order; i++) + out += param[i] * m->coeff[order][i]; return out; } @@ -109,26 +121,29 @@ double av_evaluate_lls(LLSModel *m, double *param, int order){ #include #include -int main(void){ +int main(void) +{ LLSModel m; int i, order; av_init_lls(&m, 3); - for(i=0; i<100; i++){ + for (i = 0; i < 100; i++) { double var[4]; double eval; - var[0] = (rand() / (double)RAND_MAX - 0.5)*2; - var[1] = var[0] + rand() / (double)RAND_MAX - 0.5; - var[2] = var[1] + rand() / (double)RAND_MAX - 0.5; - var[3] = var[2] + rand() / (double)RAND_MAX - 0.5; + + var[0] = (rand() / (double) RAND_MAX - 0.5) * 2; + var[1] = var[0] + rand() / (double) RAND_MAX - 0.5; + var[2] = var[1] + rand() / (double) RAND_MAX - 0.5; + var[3] = var[2] + rand() / (double) RAND_MAX - 0.5; av_update_lls(&m, var, 0.99); av_solve_lls(&m, 0.001, 0); - for(order=0; order<3; order++){ - eval= av_evaluate_lls(&m, var+1, order); + for (order = 0; order < 3; order++) { + eval = av_evaluate_lls(&m, var + 1, order); printf("real:%9f order:%d pred:%9f var:%f coeffs:%f %9f %9f\n", - var[0], order, eval, sqrt(m.variance[order] / (i+1)), - m.coeff[order][0], m.coeff[order][1], m.coeff[order][2]); + var[0], order, eval, sqrt(m.variance[order] / (i + 1)), + m.coeff[order][0], m.coeff[order][1], + m.coeff[order][2]); } } return 0; -- cgit v1.2.3