lls: whitespace cosmetics

Signed-off-by: Mans Rullgard <mans@mansr.com>

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<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];
+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<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 (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; k<i; k++)
-                sum += 2*m->coeff[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 <stdlib.h>
 #include <stdio.h>
 
-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;