make astyle

src/genmap-algo.c

@@ -112,7 +112,8 @@ GenmapScalar GenmapSign(GenmapScalar a, GenmapScalar b) {
 //
 // Routine to find eigenvectors and values of tri-diagonal matrix
 //
-int GenmapTQLI(GenmapHandle h, GenmapVector diagonal, GenmapVector upper,
+int GenmapTQLI(GenmapHandle h, GenmapVector diagonal,
+ GenmapVector upper,
  GenmapVector **eVectors, GenmapVector *eValues) {
  assert(diagonal->size == upper->size + 1);
 
@@ -124,7 +125,7 @@ int GenmapTQLI(GenmapHandle h, GenmapVector diagonal, GenmapVector upper,
  //printf("n is: %d\n", n);
  GenmapCreateVector(&e, n);
  GenmapCopyVector(e, upper);
- e->data[n-1] = 0.0;
+ e->data[n - 1] = 0.0;
 
  // Create the vector to store eigenvalues
  GenmapCreateVector(eValues, n);
@@ -144,7 +145,7 @@ int GenmapTQLI(GenmapHandle h, GenmapVector diagonal, GenmapVector upper,
  for(m = l; m < n - 1; m++) {
  GenmapScalar dd = fabs(d->data[m]) + fabs(d->data[m + 1]);
  // Should use a tolerance for this check
- if(fabs(e->data[m])/dd < GENMAP_DP_TOL) break;
+ if(fabs(e->data[m]) / dd < GENMAP_DP_TOL) break;
  }
 
  if(m != l) {
@@ -166,28 +167,28 @@ int GenmapTQLI(GenmapHandle h, GenmapVector diagonal, GenmapVector upper,
  GenmapScalar b = c * e->data[i];
 #if defined(GENMAP_PAUL)
  if(fabs(f) >= fabs(g)) {
- c = g/f;
- r = sqrt(c*c + 1.0);
- e->data[i+1] = f*r;
- s = 1.0/r;
- c = c*s;
+ c = g / f;
+ r = sqrt(c * c + 1.0);
+ e->data[i + 1] = f * r;
+ s = 1.0 / r;
+ c = c * s;
  } else {
- s = f/g;
- r = sqrt(s*s + 1.0);
- e->data[i+1] = g*r;
- c = 1.0/r;
- s = s*c;
+ s = f / g;
+ r = sqrt(s * s + 1.0);
+ e->data[i + 1] = g * r;
+ c = 1.0 / r;
+ s = s * c;
  }
 #else
- e->data[i+1] = r = sqrt(f*f + g*g);
+ e->data[i + 1] = r = sqrt(f * f + g * g);
 
  if(r < GENMAP_DP_TOL) {
- d->data[i+1] -= p;
+ d->data[i + 1] -= p;
  e->data[m] = 0.0;
  break;
  }
- s = f/r;
- c = g/r;
+ s = f / r;
+ c = g / r;
 #endif
  g = d->data[i + 1] - p;
  r = (d->data[i] - g) * s + 2.0 * c * b;
@@ -197,7 +198,7 @@ int GenmapTQLI(GenmapHandle h, GenmapVector diagonal, GenmapVector upper,
  // Find eigenvectors
  for(GenmapInt k = 0; k < n; k++) {
  f = (*eVectors)[k]->data[i + 1];
- (*eVectors)[k]->data[i+1] = s * (*eVectors)[k]->data[i] + c * f;
+ (*eVectors)[k]->data[i + 1] = s * (*eVectors)[k]->data[i] + c * f;
  (*eVectors)[k]->data[i] = c * (*eVectors)[k]->data[i] - s * f;
  }
  // Done with eigenvectors
@@ -228,7 +229,7 @@ int GenmapTQLI(GenmapHandle h, GenmapVector diagonal, GenmapVector upper,
  //}
  e->data[ko] = GenmapDotVector((*eVectors)[ko], (*eVectors)[ko]);
  if(e->data[ko] > 0.0) e->data[ko] = sqrt(fabs(e->data[ko]));
- GenmapScalar scale = 1.0/e->data[ko];
+ GenmapScalar scale = 1.0 / e->data[ko];
  GenmapScaleVector((*eVectors)[ko], (*eVectors)[ko], scale);
  }
 
@@ -543,7 +544,7 @@ GenmapInt GenmapSetProcessorId(GenmapHandle h) {
 }
 
 void GenmapGlobalMinMax(GenmapHandle h, GenmapLong *min,
-  GenmapLong *max) {
+ GenmapLong *max) {
  *min = LONG_MAX; *max = LONG_MIN;
 
  GenmapElements e = GenmapGetElements(h);
@@ -613,7 +614,7 @@ int GenmapFiedler(GenmapHandle h, GenmapComm c, int maxIter,
  }
 #else
  if(global > 0) {
-  initVec->data[i] = (GenmapScalar) elements[i].globalId;
+ initVec->data[i] = (GenmapScalar) elements[i].globalId;
  } else {
  for(i = 0; i < lelt; i++) {
  initVec->data[i] = elements[i].fiedler;

src/genmap.h

@@ -170,7 +170,8 @@ int GenmapPowerIterNew(GenmapVector eVector, void (*Ax)(GenmapVector ax,
 int GenmapInvPowerIter(GenmapVector eVector, GenmapVector alpha,
  GenmapVector beta, GenmapVector init, int iter);
 
-int GenmapTQLI(GenmapHandle h, GenmapVector diagonal, GenmapVector upper,
+int GenmapTQLI(GenmapHandle h, GenmapVector diagonal,
+ GenmapVector upper,
  GenmapVector **eVectors, GenmapVector *eValues);
 //
 // Evaluate partition quality