move waveform printing

src/BayesWaveMCMC.c

@@ -1106,7 +1106,10 @@ void RJMCMC(struct Data *data, struct Model **model, struct BayesLineParams ***b
   if(data->runPhase==0)snprintf(modelname,MAXSTRINGSIZE,"%sclean",data->runName);
   else
   {
-    if(!data->glitchFlag && !data->signalFlag)
+    if(data->cbcFlag) 
+      snprintf(modelname,MAXSTRINGSIZE,"%scbc",data->runName);
+    
+    else if(!data->glitchFlag && !data->signalFlag)
       snprintf(modelname,MAXSTRINGSIZE,"%snoise",data->runName);
 
     else if(data->glitchFlag && !data->signalFlag)
@@ -1429,6 +1432,15 @@ void RJMCMC(struct Data *data, struct Model **model, struct BayesLineParams ***b
           sprintf(filename,"waveforms/%s_colored_wave_%s_%d.dat", modelname, data->ifos[ifo], frame);
           print_colored_time_domain_waveforms(filename, model[chain->index[0]]->response[ifo], N, data->Tobs, data->imin, data->imax, prior->range[0][0], prior->range[0][1]);
         }
+
+        if(data->cbcFlag)
+        {
+          sprintf(filename,"waveforms/%s_cbc_%s_%d.dat", modelname, data->ifos[ifo], frame);
+          print_time_domain_waveforms(filename, model[chain->index[0]]->cbctemplate[ifo], N, model[chain->index[0]]->Snf[ifo], data->Tobs, data->imin, data->imax, prior->range[0][0], prior->range[0][1]);
+          
+          sprintf(filename,"waveforms/%s_colored_cbc_%s_%d.dat", modelname, data->ifos[ifo], frame);
+          print_colored_time_domain_waveforms(filename, model[chain->index[0]]->cbctemplate[ifo], N, data->Tobs, data->imin, data->imax, prior->range[0][0], prior->range[0][1]);
+        }
       }
       frame++;
     }
@@ -2631,7 +2643,8 @@ void EvolveBayesCBCParameters(struct Data *data, struct Model **model, struct ba
   projectCBCWaveform(model_x->cbcamphase, N, NI, fmin, data->Tobs, model_x->extParams, model_x->cbctemplate, projection->dtimes, projection->Fplus, projection->Fcross);
 
   // Save 200 waveforms temporarily for checking residuals + template
-  if (ic==0 && bayescbc->debug == 1 && chain->mc%(chain->count/200)==0) print_projected_cbc_waveform(bayescbc->SN, data->Tobs, data->trigtime, model_x->cbctemplate, bayescbc->D, N, bayescbc->mxc[0], bayescbc);
+  //if (ic==0 && bayescbc->debug == 1 && chain->mc%(chain->count/200)==0) print_projected_cbc_waveform(bayescbc->SN, data->Tobs, data->trigtime, model_x->cbctemplate, bayescbc->D, N, bayescbc->mxc[0], bayescbc);
+
 
   // Recompute likelihoods of current chain
   model_x->logLnorm = 0.0;