fixing ci runtime errors

Author: cnpetra

src/Optimization/InnerProduct.cpp

@@ -92,7 +92,15 @@ bool InnerProduct::apply_M(const hiopVector& x, hiopVector& y) const
     return true;
   }
 }
-  
+
+// Applies lumped mass matrix;
+bool InnerProduct::apply_M_lumped(const hiopVector& x, hiopVector& y) const
+{
+  y.copyFrom(x);
+  y.componentMult(*M_lumped());
+  return true;
+}
+
 // Computes ||x||_M
 double InnerProduct::norm_M(const hiopVector& x) const
 {
@@ -130,9 +138,12 @@ double InnerProduct::norm_H_dual(const hiopVector& x) const
 double InnerProduct::norm_stationarity(const hiopVector& x) const
 {
   if(nlp_->useWeightedInnerProd()) {
-    nlp_->eval_H_inv(x, *vec_n_);
-    auto dp = x.dotProductWith(*vec_n_);
-    return ::std::sqrt(dp);
+    //nlp_->eval_H_inv(x, *vec_n_);
+    //auto dp = x.dotProductWith(*vec_n_);
+    //return ::std::sqrt(dp);
+    vec_n_->copyFrom(x);
+    vec_n_->componentDiv(*M_lumped());
+    return vec_n_->infnorm();
   } else {
     return x.infnorm();
   }

src/Optimization/InnerProduct.hpp

@@ -88,6 +88,9 @@ class InnerProduct
 
   // Compute y=M*x
   bool apply_M(const hiopVector& x, hiopVector& y) const;
+
+  // Appply lumped mass matrix, y=M_lumped*x
+  bool apply_M_lumped(const hiopVector& x, hiopVector& y) const;
 
   // Computes ||x||_M
   double norm_M(const hiopVector& x) const;

src/Optimization/hiopResidual.cpp

@@ -186,7 +186,7 @@ int hiopResidual::update(const hiopIterate& it,
   //using rxl as auxiliary variable to compute -M*zl+M*zu
   rxl->copyFrom(*it.zu);
   rxl->axpy(-1.0, *it.zl);
-  nlp->inner_prod()->apply_M(*rxl, *rx);
+  nlp->inner_prod()->apply_M_lumped(*rxl, *rx);
   //continue adding to rx
   jac_c.transTimesVec(1.0, *rx, 1.0, *it.yc);
   jac_d.transTimesVec(1.0, *rx, 1.0, *it.yd);
@@ -258,28 +258,28 @@ int hiopResidual::update(const hiopIterate& it,
   nlp->log->printf(hovScalars, "NLP resid [update]: inf norm ryd=%22.17e\n", buf);
 
   // rxl=x-sxl-xl
-  if(nlp->n_low_local() > 0) {
+  if(nlp->n_low() > 0) {
     rxl->copyFrom(*it.x);
     rxl->axpy(-1.0, *it.sxl);
     rxl->axpy(-1.0, nlp->get_xl());
     // zero out entries in the resid that don't correspond to a finite low bound
     if(nlp->n_low_local() < nx_loc) {
       rxl->selectPattern(nlp->get_ixl());
     }
-    buf = rxl->infnorm_local();   
+    buf = rxl->infnorm();   
     // nrmInf_nlp_feasib = fmax(nrmInf_nlp_feasib, buf);
     nlp->log->printf(hovScalars, "NLP resid [update]: inf norm rxl=%22.17e\n", buf);
   }
   // printf("  %10.4e (xl)", nrmInf_nlp_feasib);
   // rxu=-x-sxu+xu
-  if(nlp->n_upp_local() > 0) {
+  if(nlp->n_upp() > 0) {
     rxu->copyFrom(nlp->get_xu());
     rxu->axpy(-1.0, *it.x);
     rxu->axpy(-1.0, *it.sxu);
     if(nlp->n_upp_local() < nx_loc) {
       rxu->selectPattern(nlp->get_ixu());
     }
-    buf = rxu->infnorm_local();
+    buf = rxu->infnorm();
     // nrmInf_nlp_feasib = fmax(nrmInf_nlp_feasib, buf);
     nlp->log->printf(hovScalars, "NLP resid [update]: inf norm rxu=%22.17e\n", buf);
   }
@@ -311,7 +311,7 @@ int hiopResidual::update(const hiopIterate& it,
   nrmOne_bar_feasib = nrmOne_nlp_feasib;
 
   // rszl = \mu e - sxl * zl
-  if(nlp->n_low_local() > 0) { //! n_low()
+  if(nlp->n_low() > 0) { //! n_low()
     rszl->setToZero();
     rszl->axzpy(-1.0, *it.sxl, *it.zl);
     if(nlp->n_low_local() < nx_loc) {
@@ -328,7 +328,7 @@ int hiopResidual::update(const hiopIterate& it,
     nlp->log->printf(hovScalars, "NLP resid [update]: inf norm rszl=%22.17e\n", buf);
   }
   // rszu = \mu e - sxu * zu
-  if(nlp->n_upp_local() > 0) { //!
+  if(nlp->n_upp() > 0) {
     rszu->setToZero();
     rszu->axzpy(-1.0, *it.sxu, *it.zu);
     if(nlp->n_upp_local() < nx_loc) {
@@ -474,7 +474,7 @@ void hiopResidual::update_soc(const hiopIterate& it,
   nrmInf_bar_optim = nrmInf_bar_feasib = nrmInf_bar_complem = 0;
   nrmOne_nlp_feasib = nrmOne_bar_feasib = 0.;
   nrmOne_nlp_optim = nrmOne_bar_optim = 0.;
-  assert(false);
+
   size_type nx_loc = rx->get_local_size();
   const double& mu = logprob.mu;
   double buf;