diff --git a/assessments/nrs/2018/fm.cpp b/assessments/nrs/2018/fm.cpp
index 074a60b..1a89156 100644
--- a/assessments/nrs/2018/fm.cpp
+++ b/assessments/nrs/2018/fm.cpp
@@ -4,116 +4,152 @@
     #include <cstdlib>
   #endif
 #endif
- # include "admodel.h"                      // Include AD class definitions
- // logs input for checking
-	/**
-	\def log_input(object)
-	Prints name and value of \a object on ADMB report %ofstream file.
-	*/
-	#undef log_input
-	#define log_input(object) writeinput << "# " #object "\n" << object << endl;
- // Shorter way to write to R_report
-	/**
-	\def REPORT(object)
-	Prints name and value of \a object on ADMB report %ofstream file.
-	*/
-	#undef REPORT
-	#define REPORT(object) R_report << "$" #object "\n" << object << endl;
-  #undef WriteData
-  #define WriteData(object) SimDat << "#" #object "\n" << object << endl;
-  ofstream writeinput("writeinput.log");
-  ofstream R_report("fm_R.rep");
-  ofstream report_sex_ratio("sex_ratio.rep");
-  ofstream SimDat("sim.dat");
-  adstring model_name;
-  adstring datafile;
-  adstring projfile_name;
-  adstring cntrlfile_name;
-  adstring tmpstring;
-  adstring repstring;
-  ofstream evalout("evalout.rep");
-  ofstream srecpar("srecpar.rep"); // To write srec-parameters for projection model
-  // ofstream ssb_retro("ssb_retro.rep",ios::app); // To write srec-parameters for projection model
-      
+	// Include AD class definitions
+  #include <admodel.h>
+ // logs input for checking
+	/**
+	\def log_input(object)
+	Prints name and value of \a object on ADMB report %ofstream file.
+	*/
+	#undef log_input
+	#define log_input(object) writeinput << "# " #object "\n" << object << endl;
+ // Shorter way to write to R_report
+	/**
+	\def REPORT(object)
+	Prints name and value of \a object on ADMB report %ofstream file.
+	*/
+	#undef REPORT
+	#define REPORT(object) R_report << #object "\n" << object << endl;
+  #undef WriteData
+  #define WriteData(object) SimDat << "#" #object "\n" << object << endl;
+  ofstream writeinput("writeinput.log");
+  ofstream R_report("fm.rep");
+  ofstream L_report("fm_legacy.rep");
+  ofstream report_sex_ratio("sex_ratio.rep");
+  ofstream SimDat("sim.dat");
+  adstring model_name;
+  adstring datafile;
+  adstring projfile_name;
+  adstring cntrlfile_name;
+  adstring tmpstring;
+  adstring repstring;
+  ofstream evalout("evalout.rep");
+  ofstream srecpar("srecpar.rep"); // To write srec-parameters for projection model
+  // ofstream ssb_retro("ssb_retro.rep",ios::app); // To write srec-parameters for projection model
+      
+#ifdef DEBUG
+  #include <chrono>
+#endif
 #include <admodel.h>
+#ifdef USE_ADMB_CONTRIBS
 #include <contrib.h>
 
+#include <gdbprintlib.cpp>
+#endif
   extern "C"  {
     void ad_boundf(int i);
   }
-#include <gdbprintlib.cpp>
-
 #include <fm.htp>
 
 model_data::model_data(int argc,char * argv[]) : ad_comm(argc,argv)
 {
-  oper_mod = 0;
-  mcmcmode = 0;
-  mcflag   = 1;
+  adstring tmpstring;
   tmpstring=adprogram_name + adstring(".dat");
   if (argc > 1)
   {
     int on=0;
     if ( (on=option_match(argc,argv,"-ind"))>-1)
     {
-      if (on>argc-2 | argv[on+1][0] == '-') 
-      { 
+      if (on>argc-2 || argv[on+1][0] == '-')
+      {
         cerr << "Invalid input data command line option"
-           " -- ignored" << endl;  
+                " -- ignored" << endl;
       }
       else
       {
-        cntrlfile_name = adstring(argv[on+1]);
+        tmpstring = adstring(argv[on+1]);
       }
     }
-    if ( (on=option_match(argc,argv,"-om"))>-1)
-    {
-      oper_mod  = 1;
-      cout<<"Got to operating model option "<<oper_mod<<endl;
-    }
-    if ( (on=option_match(argc,argv,"-mcmc"))>-1)
-    {
-      mcmcmode = 1;
-    }
   }
-  global_datafile= new cifstream(cntrlfile_name);
+  global_datafile = new cifstream(tmpstring);
   if (!global_datafile)
   {
+    cerr << "Error: Unable to allocate global_datafile in model_data constructor.";
+    ad_exit(1);
   }
-  else
+  if (!(*global_datafile))
   {
-    if (!(*global_datafile))
-    {
-      delete global_datafile;
-      global_datafile=NULL;
-    }
+    delete global_datafile;
+    global_datafile=NULL;
   }
-ad_comm::change_datafile_name("mod.ctl");  // GRID
  *(ad_comm::global_datafile) >>  model_name; 
  *(ad_comm::global_datafile) >>  datafile; 
+  oper_mod = 0;
+  mcmcmode = 0;
+  mcflag   = 1;
+  tmpstring=adprogram_name + adstring(".dat");
+  if (argc > 1)
+  {
+    int on=0;
+    if ( (on=option_match(argc,argv,"-ind"))>-1)
+    {
+      if (on>argc-2 | argv[on+1][0] == '-') 
+      { 
+        cerr << "Invalid input data command line option"
+           " -- ignored" << endl;  
+      }
+      else
+      {
+        cntrlfile_name = adstring(argv[on+1]);
+      }
+    }
+    if ( (on=option_match(argc,argv,"-om"))>-1)
+    {
+      oper_mod  = 1;
+      cout<<"Got to operating model option "<<oper_mod<<endl;
+    }
+    if ( (on=option_match(argc,argv,"-mcmc"))>-1)
+    {
+      mcmcmode = 1;
+    }
+  }
+  global_datafile= new cifstream(cntrlfile_name);
+  if (!global_datafile)
+  {
+  }
+  else
+  {
+    if (!(*global_datafile))
+    {
+      delete global_datafile;
+      global_datafile=NULL;
+    }
+  }
+ cout<<model_name<<endl<<datafile<<endl;
+ad_comm::change_datafile_name("mod.ctl");  // GRID
   Growth_Option.allocate("Growth_Option");
-  phase_grwth=-2;
-  phase_wt  = -1;
-  phase_growth_cov = -1;
-  switch (Growth_Option)
-  {
-    case 0 : // Use constant time-invariant growth (from base growth parameters)
-    break;
-    case 1 : // Use empirical (values in data file) mean wts at age
-    break;
-    case 2 : // start out with base growth values and deviations decomposed by year and age
-    {
-      phase_wt = 1;
-      phase_growth_cov=-1; 
-    }
-    break;
-    case 3 : // Use base growth values (not estimated) and deviations as fn of temperature and decomposed by year and age
-    {
-      phase_wt  = -1; 
-      phase_growth_cov =  1;
-    }
-    break;
-  }
+  phase_grwth=-2;
+  phase_wt  = -1;
+  phase_growth_cov = -1;
+  switch (Growth_Option)
+  {
+    case 0 : // Use constant time-invariant growth (from base growth parameters)
+    break;
+    case 1 : // Use empirical (values in data file) mean wts at age
+    break;
+    case 2 : // start out with base growth values and deviations decomposed by year and age
+    {
+      phase_wt = 1;
+      phase_growth_cov=-1; 
+    }
+    break;
+    case 3 : // Use base growth values (not estimated) and deviations as fn of temperature and decomposed by year and age
+    {
+      phase_wt  = -1; 
+      phase_growth_cov =  1;
+    }
+    break;
+  }
   ABC_age_lb.allocate("ABC_age_lb");
   phase_age_incr.allocate("phase_age_incr");
   phase_init_age_comp.allocate("phase_init_age_comp");
@@ -149,40 +185,40 @@ ad_comm::change_datafile_name("mod.ctl");  // GRID
   sigmaR_exp.allocate("sigmaR_exp");
   sigmaR_sigma.allocate("sigmaR_sigma");
   nselages.allocate("nselages");
-    log_input(datafile);
-    log_input(model_name);
-    log_input(Growth_Option);
-    log_input(phase_grwth);
-    log_input(phase_wt);
-    log_input(phase_age_incr);
-    log_input(phase_growth_cov);
-    log_input(ABC_age_lb);
-    log_input(phase_F40);           //Phase to begin spawning biomass estimation
-    log_input(phase_fmort);         //Phase to begin mortality estimation
-    log_input(phase_proj);          //Phase to begin future projections
-    log_input(phase_logist_sel);    //Phase to begin logistic selectivity estimation
-    log_input(phase_male_sel);      //Phase to begin logistic selectivity estimation
-    log_input(phase_q);
-    log_input(q_alpha_prior);
-    log_input(phase_q_alpha);
-    log_input(q_beta_prior);
-    log_input(phase_q_beta_in);
-    log_input(phase_m_f);
-    log_input(phase_m_m);
-    log_input(phase_sr);
-    log_input(phase_env_cov);  //
-    log_input(phase_sigmaR);        //
-    log_input(phase_wtfmsy);        //
-    log_input(pf_sigma);         // penalty cv for selectivity used in Fmsy calcs
-    log_input(a50_sigma);        // 
-    log_input(slp_sigma);        //
-    log_input(q_exp);
-    log_input(q_sigma);
-    log_input(m_exp);
-    log_input(m_sigma);
-    log_input(sigmaR_exp);
-    log_input(sigmaR_sigma);
-    log_input(nselages);
+    log_input(datafile);
+    log_input(model_name);
+    log_input(Growth_Option);
+    log_input(phase_grwth);
+    log_input(phase_wt);
+    log_input(phase_age_incr);
+    log_input(phase_growth_cov);
+    log_input(ABC_age_lb);
+    log_input(phase_F40);           //Phase to begin spawning biomass estimation
+    log_input(phase_fmort);         //Phase to begin mortality estimation
+    log_input(phase_proj);          //Phase to begin future projections
+    log_input(phase_logist_sel);    //Phase to begin logistic selectivity estimation
+    log_input(phase_male_sel);      //Phase to begin logistic selectivity estimation
+    log_input(phase_q);
+    log_input(q_alpha_prior);
+    log_input(phase_q_alpha);
+    log_input(q_beta_prior);
+    log_input(phase_q_beta_in);
+    log_input(phase_m_f);
+    log_input(phase_m_m);
+    log_input(phase_sr);
+    log_input(phase_env_cov);  //
+    log_input(phase_sigmaR);        //
+    log_input(phase_wtfmsy);        //
+    log_input(pf_sigma);         // penalty cv for selectivity used in Fmsy calcs
+    log_input(a50_sigma);        // 
+    log_input(slp_sigma);        //
+    log_input(q_exp);
+    log_input(q_sigma);
+    log_input(m_exp);
+    log_input(m_sigma);
+    log_input(sigmaR_exp);
+    log_input(sigmaR_sigma);
+    log_input(nselages);
   lambda.allocate(1,10,"lambda");
   styr_sr.allocate("styr_sr");
   endyr_sr.allocate("endyr_sr");
@@ -191,11 +227,18 @@ ad_comm::change_datafile_name("mod.ctl");  // GRID
   yr1_futcat.allocate("yr1_futcat");
   yr2_futcat.allocate("yr2_futcat");
   n_retro.allocate("n_retro");
+  surv_dwnwt.allocate("surv_dwnwt");
+  cv_inc.allocate("cv_inc");
+  n_comp.allocate("n_comp");
+  eof_check.allocate("eof_check");
+ if (eof_check!=123456) { cout <<" Control file read error, survey sensitivity evaluated?"<<endl; exit(1); }
+ phase_male_sel_offset = lambda(4); 
  log_input(lambda); 
  log_input(styr_sr); log_input(endyr_sr);
  log_input(styr_wt); log_input(endyr_wt);
  log_input(yr1_futcat); log_input(yr1_futcat);
  log_input(n_retro); 
+ log_input(phase_male_sel_offset);      //Phase to begin logistic selectivity estimation
 ad_comm::change_datafile_name("fut_temp.dat");  
   nyrs_fut.allocate("nyrs_fut");
   fut_temp.allocate(1,nyrs_fut,"fut_temp");
@@ -227,16 +270,16 @@ log_input(oac_fsh_s);
   wt_fsh_b_in.allocate(1,nfsh,styr,endyr,1,nages);
   wt_fsh_f_in.allocate(1,nfsh,styr,endyr,1,nages);
   wt_fsh_m_in.allocate(1,nfsh,styr,endyr,1,nages);
-  for (int k=1;k<=nfsh;k++) 
-    for (int i=styr;i<=endyr;i++) 
-      for (int j=1;j<=nages;j++) 
-      {
-        wt_fsh_f_in(k,i,j) = wt_fsh_in(k,i,j);
-        wt_fsh_m_in(k,i,j) = wt_fsh_in(k,i,nages+j);
-      }
-  wt_fsh_b_in = (wt_fsh_m_in + wt_fsh_f_in)/2.;
-  log_input(wt_fsh_f_in(1,endyr));
-  log_input(wt_fsh_m_in(1,endyr));
+  for (int k=1;k<=nfsh;k++) 
+    for (int i=styr;i<=endyr;i++) 
+      for (int j=1;j<=nages;j++) 
+      {
+        wt_fsh_f_in(k,i,j) = wt_fsh_in(k,i,j);
+        wt_fsh_m_in(k,i,j) = wt_fsh_in(k,i,nages+j);
+      }
+  wt_fsh_b_in = (wt_fsh_m_in + wt_fsh_f_in)/2.;
+  log_input(wt_fsh_f_in(1,endyr));
+  log_input(wt_fsh_m_in(1,endyr));
   wt_fsh_tmp_f.allocate(1,nages,styr_wt,endyr_wt);
   wt_fsh_tmp_m.allocate(1,nages,styr_wt,endyr_wt);
   wt_pop_tmp_f.allocate(1,nages,styr_wt,endyr_wt);
@@ -260,6 +303,7 @@ log_input(nsmpl_fsh_s);
 log_input(nsrv);
   yrs_srv.allocate(1,nsrv,1,nyrs_srv,"yrs_srv");
   mo_srv.allocate(1,nsrv,"mo_srv");
+cout<<"mo_srv="<<mo_srv<<endl;
   obs_srv.allocate(1,nsrv,1,nyrs_srv,"obs_srv");
   obs_se_srv.allocate(1,nsrv,1,nyrs_srv,"obs_se_srv");
   obs_lse_srv.allocate(1,nsrv,1,nyrs_srv);
@@ -299,17 +343,17 @@ log_input(n_env_cov);
   env_cov.allocate(1,nsrv,1,n_env_cov,1,nyrs_srv,"env_cov");
   for (int j=1;j<=nsrv;j++) for (int k=1;k<=n_env_cov(j);k++) { env_cov(j,k) -= mean(env_cov(j,k)); }
 log_input(env_cov);
-  rec_lag=1;    //Lag between year-class and recruitment
-  if (phase_init_age_comp>0&&init_age_comp > 0)
-  {
-    styr_rec            = styr ;  // Change in two places (see below)
-    phase_init_age_comp = 2;
-  }
-  else
-  {
-    styr_rec            = styr - nages+1; // Extend recruitment devs back in time to estimate init_age from rec_dev
-    phase_init_age_comp = -2; // Don't estimate initial age comp parameters
-  }
+  rec_lag=1;    //Lag between year-class and recruitment
+  if (phase_init_age_comp>0&&init_age_comp > 0)
+  {
+    styr_rec            = styr ;  // Change in two places (see below)
+    phase_init_age_comp = 2;
+  }
+  else
+  {
+    styr_rec            = styr - nages+1; // Extend recruitment devs back in time to estimate init_age from rec_dev
+    phase_init_age_comp = -2; // Don't estimate initial age comp parameters
+  }
   spawnmo.allocate("spawnmo");
 spmo_frac    =(spawnmo-1)/12.;
 log_input(spawnmo);
@@ -321,85 +365,157 @@ log_input(srv_mo);
  log_input(n_wts);
   growth_cov.allocate(styr,endyr,"growth_cov");
  log_input(growth_cov);
+  Check.allocate("Check");
+ log_input(Check);
+ cout << Check << endl;
+ if (Check != 123456) { cout << "Invalid data file " << Check << endl; exit(1); }
  num_proj_Fs = 5;
   offset_srv.allocate(1,nsrv);
   offset_fsh.allocate(1,nfsh);
-  offset_fsh.initialize();
-  offset_srv.initialize();
-  for (int k=1;k<=nfsh;k++)
-  {
-    for (i=1;i<=nyrs_fsh_age_c(k);i++)
-    {
-      oac_fsh_c(k,i) /= sum(oac_fsh_c(k,i));
-      offset_fsh(k)  -= nsmpl_fsh_c(k,i)*(oac_fsh_c(k,i) + 0.001) * log(oac_fsh_c(k,i) + 0.001); 
-    }
-    for (i=1;i<=nyrs_fsh_age_s(k);i++)
-    {
-      oac_fsh_s(k,i) /= sum(oac_fsh_s(k,i));
-      offset_fsh(k)  -= nsmpl_fsh_s(k,i)*(oac_fsh_s(k,i) + 0.001) * log(oac_fsh_s(k,i) + 0.001); 
-    }
-  }
-  for (int k=1;k<=nsrv;k++)
-  {
-    for (i=1;i<=nyrs_srv_age_c(k);i++)
-    {
-      oac_srv_c(k,i) /= sum(oac_srv_c(k,i));
-      offset_srv(k)-= nsmpl_srv_c(k,i)*(oac_srv_c(k,i) + 0.001) * log(oac_srv_c(k,i) + 0.001);  
-    }
-    for (int i=1;i<=nyrs_srv_age_s(k);i++)
-    {
-      oac_srv_s(k,i) /= sum(oac_srv_s(k,i));
-      offset_srv(k)-= nsmpl_srv_s(k,i)*(oac_srv_s(k,i) + 0.001) * log(oac_srv_s(k,i) + 0.001); 
-    }
+  offset_fsh.initialize();
+  offset_srv.initialize();
+   double btmp=0.;
+   double ctmp=0.;
+   dvector ntmp(1,nages);
+   ntmp(1) = 1.;
+   for (int a=2;a<=nages;a++)
+     ntmp(a) = ntmp(a-1)*exp(-m_exp-.05);
+   btmp = wt_pop_f_in(endyr)(1,nages) * ntmp;
+   ctmp = mean(obs_catch);
+   log_input( ctmp );
+   R_guess = log((ctmp/.02 )/btmp) ;
+   log_input( R_guess );
+	 // Now that everything is read in, can change the "endyr" to reflect retrospective year
+	 endyr = endyr - n_retro;
+	 // Lag between weights and years
+	 if (endyr <= endyr_wt) endyr_wt = endyr - (endyr_in-endyr_wt );
+	 if (endyr <= endyr_wt) endyr_wt = endyr - (endyr_in-endyr_wt );
+	 endyr_sr = endyr - (endyr_in-endyr_sr );
+   styr_fut=endyr+1;
+   endyr_fut=endyr+nyrs_fut;
+   //Modified retro.....................................................................
+   int nyrs_srv_tmp;
+   
+   for (int isrv=1;isrv<=nsrv;isrv++)
+   {
+          //survey biomass
+          for(int iyr=1; iyr<=nyrs_srv(isrv);iyr++)
+          {
+           if(yrs_srv(isrv,iyr)<=endyr) nyrs_srv_tmp=iyr;
+           if(surv_dwnwt==1 & yrs_srv(isrv,iyr)>= endyr) obs_lse_srv(isrv,iyr)=cv_inc;
+          }
+          nyrs_srv(isrv)=nyrs_srv_tmp;
+     //reset temporary variable
+     nyrs_srv_tmp=0;
+     for (int iyr=1;iyr<=nyrs_srv_age_c(isrv);iyr++)
+     {
+       if (yrs_srv_age_c(isrv,iyr)<= endyr) nyrs_srv_tmp=iyr;
+       if(surv_dwnwt==1 & yrs_srv_age_c(isrv,iyr)>= endyr) nsmpl_srv_c(isrv,iyr)=n_comp;
+     }
+     nyrs_srv_age_c(isrv)=nyrs_srv_tmp;
+     //reset temporary variable     
+     nyrs_srv_tmp=0;
+     for (int iyr=1;iyr<=nyrs_srv_age_s(isrv);iyr++)
+     {
+       if (yrs_srv_age_s(isrv,iyr)<= endyr) nyrs_srv_tmp=iyr;
+       if(surv_dwnwt==1 & yrs_srv_age_s(isrv,iyr)>= endyr) nsmpl_srv_s(isrv,iyr)=n_comp;
+     }
+     nyrs_srv_age_s(isrv)=nyrs_srv_tmp;
+   }
+   
+   for (int ifsh=1;ifsh<=nfsh;ifsh++)
+   {
+     for (int iyr=1;iyr<=nyrs_fsh_age_s(ifsh);iyr++)
+       if (endyr <= yrs_fsh_age_s(ifsh,iyr))
+         nyrs_fsh_age_s(ifsh) = min(nyrs_fsh_age_s(ifsh),iyr);
+	 
+     for (int iyr=1;iyr<=nyrs_fsh_age_c(ifsh);iyr++)
+       if (endyr <= yrs_fsh_age_c(ifsh,iyr))
+         nyrs_fsh_age_c(ifsh) = min(nyrs_fsh_age_c(ifsh),iyr);
+   }
+  
+  //retained from original 
+  for (int k=1;k<=nfsh;k++)
+  {
+    for (i=1;i<=nyrs_fsh_age_c(k);i++)
+    {
+      oac_fsh_c(k,i) /= sum(oac_fsh_c(k,i));
+      offset_fsh(k)  -= nsmpl_fsh_c(k,i)*(oac_fsh_c(k,i) + 0.001) * log(oac_fsh_c(k,i) + 0.001); 
+    }
+    for (i=1;i<=nyrs_fsh_age_s(k);i++)
+    {
+    
+      oac_fsh_s(k,i) /= sum(oac_fsh_s(k,i));
+      offset_fsh(k)  -= nsmpl_fsh_s(k,i)*(oac_fsh_s(k,i) + 0.001) * log(oac_fsh_s(k,i) + 0.001); 
+      // cout<<"i="<<i<<"nyrs_fsh_age_s="<<nyrs_fsh_age_s(k)<<endl;
+      // cout<<"nsmpl="<<nsmpl_fsh_s(k,i)<<endl;
+    } 
+  }
+   
+  for (int k=1;k<=nsrv;k++)
+  {
+    for (i=1;i<=nyrs_srv_age_c(k);i++)
+    {
+      oac_srv_c(k,i) /= sum(oac_srv_c(k,i));
+      offset_srv(k)-= nsmpl_srv_c(k,i)*(oac_srv_c(k,i) + 0.001) * log(oac_srv_c(k,i) + 0.001); 
+    }
+    for (int i=1;i<=nyrs_srv_age_s(k);i++)
+    {
+      oac_srv_s(k,i) /= sum(oac_srv_s(k,i));
+      offset_srv(k)-= nsmpl_srv_s(k,i)*(oac_srv_s(k,i) + 0.001) * log(oac_srv_s(k,i) + 0.001); 
+      
+    }
+  }
+    
+  log_input(offset_fsh);
+  log_input(offset_srv); 
+  
+     ofstream out_retro("Retro_check.rep");
+     out_retro<<"endyr"<<endl;
+     out_retro<<endyr<<endl;
+     out_retro<<"endyr_wt"<<endl;
+     out_retro<<endyr_wt<<endl;
+     out_retro<<"endyr_sr"<<endl;
+     out_retro<<endyr_sr<<endl;
+     out_retro<<"nsrv"<<endl;
+     out_retro<<nsrv<<endl;
+     out_retro<<"nyrs_srv"<<endl;
+     out_retro<<nyrs_srv<<endl;
+     out_retro<<"yrs_srv"<<endl;
+     for(i=1;i<=nyrs_srv(nsrv);i++)
+     	out_retro<<yrs_srv(nsrv,i)<<endl;
+     out_retro<<"obs_srv"<<endl;
+     for(i=1;i<=nyrs_srv(nsrv);i++)
+     	out_retro<<obs_srv(nsrv,i)<<endl;
+     out_retro<<"obs_lse_srv"<<endl;
+     for(i=1;i<=nyrs_srv(nsrv);i++)
+     	out_retro<<obs_lse_srv(nsrv,i)<<endl;
+     out_retro<<"nyrs_srv_age_c"<<endl;
+     out_retro<<nyrs_srv_age_c<<endl;
+     out_retro<<"nyrs_srv_age_s"<<endl;
+     out_retro<<nyrs_srv_age_s<<endl;
+     out_retro<<"yrs_srv_age_s"<<endl;
+     for(i=1;i<=nyrs_srv_age_s(nsrv);i++)
+     	out_retro<<yrs_srv_age_s(nsrv,i)<<endl;
+     out_retro<<"nsmpl_srv_c"<<endl;
+     out_retro<<nsmpl_srv_c<<endl;
+     out_retro<<"nsmpl_srv_s"<<endl;
+     for(i=1;i<=nyrs_srv_age_s(nsrv);i++)     
+     	out_retro<<nsmpl_srv_s(nsrv,i)<<endl;
+     out_retro<<"nyrs_fsh_age_c"<<endl;
+     out_retro<<nyrs_fsh_age_c<<endl;
+     out_retro<<"yrs_fsh_age_s"<<endl;
+     for(i=1;i<=nyrs_fsh_age_s(nsrv);i++)
+     	out_retro<<yrs_fsh_age_s(nsrv,i)<<endl;
+          
+ad_comm::change_datafile_name("future_catch.dat");  
+  future_ABC.allocate(1,nfsh,styr_fut,endyr_fut,"future_ABC");
+ log_input(future_ABC); 
+  if (global_datafile)
+  {
+    delete global_datafile;
+    global_datafile = NULL;
   }
-  log_input(offset_fsh);
-  log_input(offset_srv);
-   double btmp=0.;
-   double ctmp=0.;
-   dvector ntmp(1,nages);
-   ntmp(1) = 1.;
-   for (int a=2;a<=nages;a++)
-     ntmp(a) = ntmp(a-1)*exp(-m_exp-.05);
-   btmp = wt_pop_f_in(endyr)(1,nages) * ntmp;
-   ctmp = mean(obs_catch);
-   log_input( ctmp );
-   R_guess = log((ctmp/.02 )/btmp) ;
-   log_input( R_guess );
-	 // Now that everything is read in, can change the "endyr" to reflect retrospective year
-	 endyr = endyr - n_retro;
-	 // Lag between weights and years
-	 if (endyr <= endyr_wt) endyr_wt = endyr - (endyr_in-endyr_wt );
-	 if (endyr <= endyr_wt) endyr_wt = endyr - (endyr_in-endyr_wt );
-	 endyr_sr = endyr - (endyr_in-endyr_sr );
-   styr_fut=endyr+1;
-   endyr_fut=endyr+nyrs_fut;
-   for (int isrv=1;isrv<=nsrv;isrv++)
-   {
-    // need to adjust survey observation dimensions
-     for (int iyr=1;iyr<=nyrs_srv(isrv);iyr++)
-		 {
-       if (endyr <= yrs_srv(isrv,iyr))
-         nyrs_srv(isrv) = min(nyrs_srv(isrv),iyr);
-			// cout<<iyr<<" "<<nyrs_srv(isrv)<<" "<<yrs_srv(isrv,iyr)<<" "<<endyr<<endl;
-		 }
-		 // exit(1);
-     for (int iyr=1;iyr<=nyrs_srv_age_c(isrv);iyr++)
-       if (endyr <= yrs_srv_age_c(isrv,iyr))
-         nyrs_srv_age_c(isrv) = min(nyrs_srv_age_c(isrv),iyr);
-     for (int iyr=1;iyr<=nyrs_srv_age_s(isrv);iyr++)
-       if (endyr <= yrs_srv_age_s(isrv,iyr))
-         nyrs_srv_age_s(isrv) = min(nyrs_srv_age_s(isrv),iyr);
-     //cout << nyrs_srv(isrv)<<endl;exit(1);
-   }
-   for (int ifsh=1;ifsh<=nfsh;ifsh++)
-   {
-     for (int iyr=1;iyr<=nyrs_fsh_age_s(ifsh);iyr++)
-       if (endyr <= yrs_fsh_age_s(ifsh,iyr))
-         nyrs_fsh_age_s(ifsh) = min(nyrs_fsh_age_s(ifsh),iyr);
-     for (int iyr=1;iyr<=nyrs_fsh_age_c(ifsh);iyr++)
-       if (endyr <= yrs_fsh_age_c(ifsh,iyr))
-         nyrs_fsh_age_c(ifsh) = min(nyrs_fsh_age_c(ifsh),iyr);
-   }
 }
 
 model_parameters::model_parameters(int sz,int argc,char * argv[]) : 
@@ -484,6 +600,7 @@ model_parameters::model_parameters(int sz,int argc,char * argv[]) :
   sel50_tmp.initialize();
   #endif
   sel_slope_fsh_m.allocate(1,nfsh,phase_logist_sel,"sel_slope_fsh_m");
+  male_sel_offset.allocate(-4,4,phase_male_sel_offset,"male_sel_offset");
   sel_slope_fsh_devs_m.allocate(1,nfsh,styr,endyr,-5,5,phase_logist_sel_devs,"sel_slope_fsh_devs_m");
   sel50_fsh_m.allocate(1,nfsh,phase_logist_sel,"sel50_fsh_m");
   sel50_fsh_devs_m.allocate(1,nfsh,styr,endyr,-10,10,phase_logist_sel_devs,"sel50_fsh_devs_m");
@@ -872,6 +989,7 @@ model_parameters::model_parameters(int sz,int argc,char * argv[]) :
   depletion.allocate("depletion");
  npfs = num_proj_Fs-2;
   future_catch.allocate(1,npfs,styr_fut,endyr_fut,"future_catch");
+  future_Fs.allocate(styr_fut,endyr_fut,"future_Fs");
   future_SSB.allocate(1,num_proj_Fs,styr_fut,endyr_fut,"future_SSB");
   future_TotBiom.allocate(1,num_proj_Fs,styr_fut,endyr_fut,"future_TotBiom");
 }
@@ -884,156 +1002,156 @@ void model_parameters::preliminary_calculations(void)
   admaster_slave_variable_interface(*this);
 
 #endif
-  // Initialize matrices used in the model
-  // exit(1);
-  for (i=styr;i<=endyr;i++) 
-  {
-    for (int ifsh=1;ifsh<=nfsh;ifsh++) 
-	  {
-      wt_fsh_f(ifsh,i) = wt_fsh_f_in(ifsh,i);
-      wt_fsh_m(ifsh,i) = wt_fsh_m_in(ifsh,i);
-		}
-    for (int isrv=1;isrv<=nsrv;isrv++) 
-	  {
-      wt_srv_f(isrv,i) = wt_srv_f_in(isrv,i);
-      wt_srv_m(isrv,i) = wt_srv_m_in(isrv,i);
-		}
-    wt_pop_f(i) = wt_pop_f_in(i);
-    wt_pop_m(i) = wt_pop_m_in(i);
-	}
-  for (i=styr_wt;i<=endyr_wt;i++) 
-  {
-    for (j=1;j<=nages;j++) 
-    {
-      //note, only uses fishery 1 for this... needs to be updated for more than 1 fishery
-      wt_fsh_tmp_f(j,i) = wt_fsh_f_in(1,i,j);
-      wt_fsh_tmp_m(j,i) = wt_fsh_m_in(1,i,j);
-      wt_pop_tmp_f(j,i) = value(wt_pop_f(i,j));//note, only uses fishery 1 for this... needs to be updated for more than 1 fishery
-      wt_pop_tmp_m(j,i) = value(wt_pop_m(i,j));//note, only uses fishery 1 for this... needs to be updated for more than 1 fishery
-		}
-  }
-  // cout<<"tmp wt fsh"<<endl;
-  // cout<<wt_fsh_tmp_f<<endl;
-  for (j=1;j<=nages;j++)
-  {
-    wt_fsh_mn_f(j) = mean(wt_fsh_tmp_f(j));
-    wt_fsh_mn_m(j) = mean(wt_fsh_tmp_m(j));
-    wt_pop_mn_f(j) = mean(wt_pop_tmp_f(j));
-    wt_pop_mn_m(j) = mean(wt_pop_tmp_m(j));
-    wt_fsh_sigma_f(j) = sqrt(norm2(wt_fsh_tmp_f(j)-wt_fsh_mn_f(j))/(endyr_wt-styr_wt+1) );
-    wt_fsh_sigma_m(j) = sqrt(norm2(wt_fsh_tmp_m(j)-wt_fsh_mn_m(j))/(endyr_wt-styr_wt+1) );
-    wt_pop_sigma_f(j) = sqrt(norm2(wt_pop_tmp_f(j)-wt_pop_mn_f(j))/(endyr_wt-styr_wt+1) );
-    wt_pop_sigma_m(j) = sqrt(norm2(wt_pop_tmp_m(j)-wt_pop_mn_m(j))/(endyr_wt-styr_wt+1) );
-    //check for zero values or no variance 
-    if (wt_pop_mn_f(j)==0.)
-    {
-      wt_pop_mn_f(j)=.03;
-      wt_pop_mn_m(j)=.03;
-    }
-    if (wt_fsh_mn_m(j)==0.)
-    {
-      wt_fsh_mn_f(j)=.03;
-      wt_fsh_mn_m(j)=.03;
-    }
-    if (wt_pop_sigma_f(j)<0.03)
-    {
-      wt_pop_sigma_f(j)=.03*wt_pop_mn_f(j);
-      wt_pop_sigma_m(j)=.03*wt_pop_mn_m(j);
-    }
-    if (wt_fsh_sigma_f(j)<0.03)
-    {
-      wt_fsh_sigma_f(j)=.03*wt_fsh_mn_f(j);
-      wt_fsh_sigma_m(j)=.03*wt_fsh_mn_m(j);
-    }
-  }
-  adj_1=1.0;
-  adj_2=1.0; 
-  SSB_1=1.0;
-  SSB_2=1.0; 
-  if(phase_wtfmsy>0)
-  {
-    wt_fsh_fut_f= wt_fsh_mn_f; // initializes estimates to correct values...
-    wt_fsh_fut_m= wt_fsh_mn_m; // initializes estimates to correct values...
-    wt_pop_fut_f= wt_pop_mn_f; // initializes estimates to correct values...
-    wt_pop_fut_m= wt_pop_mn_m; // initializes estimates to correct values...
-  }
-  else
-  {
-    wt_fsh_fut_f = wt_fsh_f_in(1,endyr) ; // initializes estimates to correct values...
-    wt_fsh_fut_m = wt_fsh_m_in(1,endyr) ;
-    wt_pop_fut_f = wt_pop_f(endyr)   ; // initializes estimates to correct values...
-    wt_pop_fut_m = wt_pop_m(endyr)   ; // initializes estimates to correct values...
-  }
-  for (int j=1;j<=nages;j++)
-  {
-      wt_vbg_f(j) = value(a_lw_f * pow(Linf_f*(1.-exp(-K_f*(double(j)-t0_f))),b_lw_f));
-      wt_vbg_m(j) = value(a_lw_m * pow(Linf_m*(1.-exp(-K_m*(double(j)-t0_m))),b_lw_m));
-  }
-  base_incr_f(2,nages) = wt_vbg_f(2,nages) - ++wt_vbg_f(1,nages-1);
-  base_incr_m(2,nages) = wt_vbg_m(2,nages) - ++wt_vbg_m(1,nages-1);
-  // cout <<base_incr_f<<endl<<base_incr_m<<endl;exit(1);
-  switch (Growth_Option)
-  {
-    case 0 : // Use constant time-invariant growth (from base growth parameters)
-    {
-      for (k=1;k<=nfsh;k++)
-        for (i=styr;i<=endyr;i++)
-        {
-          wt_fsh_f(k,i) = wt_vbg_f;
-          wt_fsh_m(k,i) = wt_vbg_m;
-        }
-      for (k=1;k<=nsrv;k++)
-        for (i=styr;i<=endyr;i++)
-        {
-          wt_srv_f(k,i) = wt_vbg_f;
-          wt_srv_m(k,i) = wt_vbg_m;
-        }
-        for (i=styr;i<=endyr;i++)
-        {
-          wt_pop_f(i) = wt_vbg_f;
-          wt_pop_m(i) = wt_vbg_m;
-        }
-    }
-    // cout<<wt_srv_f<<endl;exit(1);
-    break;
-    case 1 : // Use empirical (values in data file) mean wts at age
-    {
-      // No need to do anything since they are initialized at these values...
-    }
-    break;
-    case 2 : // start out with base growth values and deviations decomposed by year and age
-    {
-      for (k=1;k<=nfsh;k++)
-        for (i=styr;i<=endyr;i++)
-        {
-          wt_fsh_f(k,i) = wt_vbg_f;
-          wt_fsh_m(k,i) = wt_vbg_m;
-        }
-      for (k=1;k<=nsrv;k++)
-        for (i=styr;i<=endyr;i++)
-        {
-          wt_srv_f(k,i) = wt_vbg_f;
-          wt_srv_m(k,i) = wt_vbg_m;
-        }
-        for (i=styr;i<=endyr;i++)
-        {
-          wt_pop_f(i) = wt_vbg_f;
-          wt_pop_m(i) = wt_vbg_m;
-        }
-    }
-    break;
-    case 3 : // Use base growth values (not estimated) and deviations as fn of temperature and
-             // decomposed by year and age
-    {
-    }
-    break;
-  }
-  log_input(wt_fsh_f);
-  log_input(wt_fsh_m);
-  log_input(wt_srv_f);
-  log_input(wt_srv_m);
-  log_input(wt_pop_f);
-  log_input(wt_pop_m);
+  // Initialize matrices used in the model
+  // exit(1);
+  for (i=styr;i<=endyr;i++) 
+  {
+    for (int ifsh=1;ifsh<=nfsh;ifsh++) 
+	  {
+      wt_fsh_f(ifsh,i) = wt_fsh_f_in(ifsh,i);
+      wt_fsh_m(ifsh,i) = wt_fsh_m_in(ifsh,i);
+		}
+    for (int isrv=1;isrv<=nsrv;isrv++) 
+	  {
+      wt_srv_f(isrv,i) = wt_srv_f_in(isrv,i);
+      wt_srv_m(isrv,i) = wt_srv_m_in(isrv,i);
+		}
+    wt_pop_f(i) = wt_pop_f_in(i);
+    wt_pop_m(i) = wt_pop_m_in(i);
+	}
+  for (i=styr_wt;i<=endyr_wt;i++) 
+  {
+    for (j=1;j<=nages;j++) 
+    {
+      //note, only uses fishery 1 for this... needs to be updated for more than 1 fishery
+      wt_fsh_tmp_f(j,i) = wt_fsh_f_in(1,i,j);
+      wt_fsh_tmp_m(j,i) = wt_fsh_m_in(1,i,j);
+      wt_pop_tmp_f(j,i) = value(wt_pop_f(i,j));//note, only uses fishery 1 for this... needs to be updated for more than 1 fishery
+      wt_pop_tmp_m(j,i) = value(wt_pop_m(i,j));//note, only uses fishery 1 for this... needs to be updated for more than 1 fishery
+		}
+  }
+  // cout<<"tmp wt fsh"<<endl;
+  // cout<<wt_fsh_tmp_f<<endl;
+  for (j=1;j<=nages;j++)
+  {
+    wt_fsh_mn_f(j) = mean(wt_fsh_tmp_f(j));
+    wt_fsh_mn_m(j) = mean(wt_fsh_tmp_m(j));
+    wt_pop_mn_f(j) = mean(wt_pop_tmp_f(j));
+    wt_pop_mn_m(j) = mean(wt_pop_tmp_m(j));
+    wt_fsh_sigma_f(j) = sqrt(norm2(wt_fsh_tmp_f(j)-wt_fsh_mn_f(j))/(endyr_wt-styr_wt+1) );
+    wt_fsh_sigma_m(j) = sqrt(norm2(wt_fsh_tmp_m(j)-wt_fsh_mn_m(j))/(endyr_wt-styr_wt+1) );
+    wt_pop_sigma_f(j) = sqrt(norm2(wt_pop_tmp_f(j)-wt_pop_mn_f(j))/(endyr_wt-styr_wt+1) );
+    wt_pop_sigma_m(j) = sqrt(norm2(wt_pop_tmp_m(j)-wt_pop_mn_m(j))/(endyr_wt-styr_wt+1) );
+    //check for zero values or no variance 
+    if (wt_pop_mn_f(j)==0.)
+    {
+      wt_pop_mn_f(j)=.03;
+      wt_pop_mn_m(j)=.03;
+    }
+    if (wt_fsh_mn_m(j)==0.)
+    {
+      wt_fsh_mn_f(j)=.03;
+      wt_fsh_mn_m(j)=.03;
+    }
+    if (wt_pop_sigma_f(j)<0.03)
+    {
+      wt_pop_sigma_f(j)=.03*wt_pop_mn_f(j);
+      wt_pop_sigma_m(j)=.03*wt_pop_mn_m(j);
+    }
+    if (wt_fsh_sigma_f(j)<0.03)
+    {
+      wt_fsh_sigma_f(j)=.03*wt_fsh_mn_f(j);
+      wt_fsh_sigma_m(j)=.03*wt_fsh_mn_m(j);
+    }
+  }
+  adj_1=1.0;
+  adj_2=1.0; 
+  SSB_1=1.0;
+  SSB_2=1.0; 
+  if(phase_wtfmsy>0)
+  {
+    wt_fsh_fut_f= wt_fsh_mn_f; // initializes estimates to correct values...
+    wt_fsh_fut_m= wt_fsh_mn_m; // initializes estimates to correct values...
+    wt_pop_fut_f= wt_pop_mn_f; // initializes estimates to correct values...
+    wt_pop_fut_m= wt_pop_mn_m; // initializes estimates to correct values...
+  }
+  else
+  {
+    wt_fsh_fut_f = wt_fsh_f_in(1,endyr) ; // initializes estimates to correct values...
+    wt_fsh_fut_m = wt_fsh_m_in(1,endyr) ;
+    wt_pop_fut_f = wt_pop_f(endyr)   ; // initializes estimates to correct values...
+    wt_pop_fut_m = wt_pop_m(endyr)   ; // initializes estimates to correct values...
+  }
+  for (int j=1;j<=nages;j++)
+  {
+      wt_vbg_f(j) = value(a_lw_f * pow(Linf_f*(1.-exp(-K_f*(double(j)-t0_f))),b_lw_f));
+      wt_vbg_m(j) = value(a_lw_m * pow(Linf_m*(1.-exp(-K_m*(double(j)-t0_m))),b_lw_m));
+  }
+  base_incr_f(2,nages) = wt_vbg_f(2,nages) - ++wt_vbg_f(1,nages-1);
+  base_incr_m(2,nages) = wt_vbg_m(2,nages) - ++wt_vbg_m(1,nages-1);
+  // cout <<base_incr_f<<endl<<base_incr_m<<endl;exit(1);
+  switch (Growth_Option)
+  {
+    case 0 : // Use constant time-invariant growth (from base growth parameters)
+    {
+      for (k=1;k<=nfsh;k++)
+        for (i=styr;i<=endyr;i++)
+        {
+          wt_fsh_f(k,i) = wt_vbg_f;
+          wt_fsh_m(k,i) = wt_vbg_m;
+        }
+      for (k=1;k<=nsrv;k++)
+        for (i=styr;i<=endyr;i++)
+        {
+          wt_srv_f(k,i) = wt_vbg_f;
+          wt_srv_m(k,i) = wt_vbg_m;
+        }
+        for (i=styr;i<=endyr;i++)
+        {
+          wt_pop_f(i) = wt_vbg_f;
+          wt_pop_m(i) = wt_vbg_m;
+        }
+    }
+    // cout<<wt_srv_f<<endl;exit(1);
+    break;
+    case 1 : // Use empirical (values in data file) mean wts at age
+    {
+      // No need to do anything since they are initialized at these values...
+    }
+    break;
+    case 2 : // start out with base growth values and deviations decomposed by year and age
+    {
+      for (k=1;k<=nfsh;k++)
+        for (i=styr;i<=endyr;i++)
+        {
+          wt_fsh_f(k,i) = wt_vbg_f;
+          wt_fsh_m(k,i) = wt_vbg_m;
+        }
+      for (k=1;k<=nsrv;k++)
+        for (i=styr;i<=endyr;i++)
+        {
+          wt_srv_f(k,i) = wt_vbg_f;
+          wt_srv_m(k,i) = wt_vbg_m;
+        }
+        for (i=styr;i<=endyr;i++)
+        {
+          wt_pop_f(i) = wt_vbg_f;
+          wt_pop_m(i) = wt_vbg_m;
+        }
+    }
+    break;
+    case 3 : // Use base growth values (not estimated) and deviations as fn of temperature and
+             // decomposed by year and age
+    {
+    }
+    break;
+  }
+  log_input(wt_fsh_f);
+  log_input(wt_fsh_m);
+  log_input(wt_srv_f);
+  log_input(wt_srv_m);
+  log_input(wt_pop_f);
+  log_input(wt_pop_m);
 }
 
 void model_parameters::initializationfunction(void)
@@ -1061,6 +1179,7 @@ void model_parameters::initializationfunction(void)
   ln_q_srv.set_initial_value(0.);
   sel_slope_fsh_f.set_initial_value(0.8);
   sel_slope_fsh_m.set_initial_value(.8);
+  sel_slope_fsh_m.set_initial_value(.8);
   sel_slope_srv.set_initial_value(.8);
   sel50_fsh_f.set_initial_value(5.);
   sel50_fsh_m.set_initial_value(5.);
@@ -1074,935 +1193,970 @@ void model_parameters::initializationfunction(void)
 void model_parameters::userfunction(void)
 {
   obj_fun =0.0;
-  // if (Growth_Option>1&&(current_phase()<=1))
-  if (Growth_Option>1 && (last_phase()||current_phase()<=phase_wt))
-    Get_wt_age();
-  if(!do_wt_only)
-  {
-    get_selectivity();
-    get_mortality();
-    get_numbers_at_age();
-    //if(active(R_logalpha))
-    compute_sr_fit();
-    if (sd_phase() || mceval_phase())
-    {
-      get_msy();
-      dvariable maxspawn=max(SSB)*1.2;
-      for (i=0;i<=30;i++)
-      {
-        SRR_SSB(i) = double(i+.001)*maxspawn/30; 
-        rechat(i)  = R_alpha*SRR_SSB(i)*(mfexp(-R_beta*SRR_SSB(i)));
-      }
-      Future_projections();
-      for (i=styr;i<=endyr;i++)
-        pred_rec(i) = 2.*natage_f(i,1);
-    }
-    catch_at_age();
-  }
-  evaluate_the_objective_function();
-  // next part returns the Byesian posterior for the listed parameters
-  if (mceval_phase())
-  {
-    // if (oper_mod)
-      // Oper_Model();
-    // else
-    {
-     // compute_spr_rates();
-      // write_mceval();
-    }
-   //  inf  0 0 0  inf 0.0814782  13.984 1.64572 8.52093 0  32.6187 30.3609 0 0.00937666  90.4879  586.823  539.73  0.846482 0.93861 0.861563 0.874594 0.822898 0.948608 0.870741 0.929537 0.887822 0.921366 0.841266 0.939439 0.807067 0.819997 0.964657 0.898865 0.970638 0.741473 0.857768 0.890177 0.962105 1.0011 0.968926 0.974933 0.821446 0.819997 0.781815 0.786663 0.783197 0.880017 0.762049 0.828732 0.960408 0.964657 1.10127 0.901082 0.108481 0.125338 0.123776 2632.62 2541.99 495.109 441.419  2316.82 2297.56 2273.5 2244.68 2231.11 2214.01 2063.31 1643.45 1145.61 793.073 833.721 829.768 875.837 862.19 791.983 824.822 792.25 838.237 904.882 1148.06 1380.96 1709.52 2009.46 2315.49 2608.21 2768.31 2952.35 3121.75 3236.7 3229.15 3448.95 3467.12 3193.03 3159.11 3057.89 3100.9 2971.87 3087 3290.59 3314.14 3346.24 3133.91 3044.85 3058.49 2791.15 2621.02 2668.73 2599.82 2643.57 2849.5 3060.22 3170.87 3163.42 3178.93 3055.94 2894.21 2962.15 2996.96 2993.04 2952.77 2742.2 2761.32 2915.27 2940.14  901.167 920.002 921.81 908.759 883.521 817.961 640.2 342.496 40.5581 8.5617 19.2127 39.7057 66.8238 90.8636 115.809 123.692 93.8937 67.3402 55.344 58.6771 65.6652 106.58 162.363 251.184 368.564 493.526 636.116 771.942 853.952 970.539 1064.57 1123.49 1117.1 1116.88 1059.53 1031.97 1044.92 1132.33 1219.69 1258.41 1264.11 1264.75 1197.41 1158.19 1088.47 1080.12 1068.13 1063.64 1063.77 1073.22 1106.35 1125.56 1150.04 1158.91 1135.78 1101.19 1079.63 1059.48 1045.84 1042.59 1005.04 1009.94 1029.02 1038.32 0.807464  0.0837012 0.188333 0.359539 0.565576 0.749304 0.873568  1.58871  5.05441  0.0245567  -0.00616844
-    evalout <<obj_fun<<" "<<
-              wt_like<<" "<<
-              q_prior<<" "<<
-              m_prior<<" "<<
-             rec_like<<" "<<
-             sel_like<<" "<<
-           catch_like<<" "<<
-             srv_like<<" "<<
-             age_like_fsh<<" "<<
-             age_like_srv<<" "<<
-		        q_srv(1)(1982,endyr)<<" "<<
-		        natmort_f<<" "<< 
-		        natmort_m<<" "<< 
-						Fmsyr <<" "<<ABC_biom<<" "<<Bmsy<<" "<<msy<<" "<< TotBiom 
-                     << " "<<SSB <<" "<< mean_log_rec <<" "<<partial_F_f(7,12)<<
-                        " "<<sel_slope_srv<<" "<<sel50_srv<<
-                        " "<<sel_slope_srv_m<<" "<<sel50_srv_m;
-	  double mean_N_fsh_age=0;
-    for (k=1;k<=nfsh;k++)
-    {
-      for (i=1;i<=nyrs_fsh_age_c(k);i++) // combined sexes
-        mean_N_fsh_age += Eff_N(oac_fsh_c(k,i),eac_fsh_c(k,i));
-      for (i=1;i<=nyrs_fsh_age_s(k);i++) // split sexes
-			  mean_N_fsh_age += Eff_N(oac_fsh_s(k,i),eac_fsh_s(k,i));
-			mean_N_fsh_age /= double(nyrs_fsh_age_c(k) + nyrs_fsh_age_s(k));
-    }
-    evalout << " " <<mean_N_fsh_age;
-		double mean_N_srv_age=0;
-    for (k=1;k<=nsrv;k++)
-    {
-      for (i=1;i<=nyrs_srv_age_c(k);i++) // combined sexes
-        mean_N_srv_age += Eff_N(oac_srv_c(k,i),eac_srv_c(k,i));
-      for (i=1;i<=nyrs_srv_age_s(k);i++) // split sexes
-			  mean_N_srv_age += Eff_N(oac_srv_s(k,i),eac_srv_s(k,i));
-			mean_N_srv_age /= double(nyrs_srv_age_c(k) + nyrs_srv_age_s(k));
-    }
-    evalout << " " <<mean_N_srv_age;
-  } 
-	// Alpha and beta of SRR
-  evalout << " " <<R_alpha<<" "<<R_beta<<endl;
+  // if (Growth_Option>1&&(current_phase()<=1))
+  if (Growth_Option>1 && (last_phase()||current_phase()<=phase_wt))
+    Get_wt_age();
+  if(!do_wt_only)
+  {
+    get_selectivity();
+    get_mortality();
+    get_numbers_at_age();
+    //if(active(R_logalpha))
+    compute_sr_fit();
+    if (sd_phase() || mceval_phase())
+    {
+      get_msy();
+      dvariable maxspawn=max(SSB)*1.2;
+      for (i=0;i<=30;i++)
+      {
+        SRR_SSB(i) = double(i+.001)*maxspawn/30; 
+        rechat(i)  = R_alpha*SRR_SSB(i)*(mfexp(-R_beta*SRR_SSB(i)));
+      }
+      Future_projections();
+      for (i=styr;i<=endyr;i++)
+        pred_rec(i) = 2.*natage_f(i,1);
+    }
+    catch_at_age();
+  }
+  evaluate_the_objective_function();
+  // next part returns the Byesian posterior for the listed parameters
+  if (mceval_phase())
+  {
+    // if (oper_mod)
+      // Oper_Model();
+    // else
+    {
+     // compute_spr_rates();
+      // write_mceval();
+    }
+   //  inf  0 0 0  inf 0.0814782  13.984 1.64572 8.52093 0  32.6187 30.3609 0 0.00937666  90.4879  586.823  539.73  0.846482 0.93861 0.861563 0.874594 0.822898 0.948608 0.870741 0.929537 0.887822 0.921366 0.841266 0.939439 0.807067 0.819997 0.964657 0.898865 0.970638 0.741473 0.857768 0.890177 0.962105 1.0011 0.968926 0.974933 0.821446 0.819997 0.781815 0.786663 0.783197 0.880017 0.762049 0.828732 0.960408 0.964657 1.10127 0.901082 0.108481 0.125338 0.123776 2632.62 2541.99 495.109 441.419  2316.82 2297.56 2273.5 2244.68 2231.11 2214.01 2063.31 1643.45 1145.61 793.073 833.721 829.768 875.837 862.19 791.983 824.822 792.25 838.237 904.882 1148.06 1380.96 1709.52 2009.46 2315.49 2608.21 2768.31 2952.35 3121.75 3236.7 3229.15 3448.95 3467.12 3193.03 3159.11 3057.89 3100.9 2971.87 3087 3290.59 3314.14 3346.24 3133.91 3044.85 3058.49 2791.15 2621.02 2668.73 2599.82 2643.57 2849.5 3060.22 3170.87 3163.42 3178.93 3055.94 2894.21 2962.15 2996.96 2993.04 2952.77 2742.2 2761.32 2915.27 2940.14  901.167 920.002 921.81 908.759 883.521 817.961 640.2 342.496 40.5581 8.5617 19.2127 39.7057 66.8238 90.8636 115.809 123.692 93.8937 67.3402 55.344 58.6771 65.6652 106.58 162.363 251.184 368.564 493.526 636.116 771.942 853.952 970.539 1064.57 1123.49 1117.1 1116.88 1059.53 1031.97 1044.92 1132.33 1219.69 1258.41 1264.11 1264.75 1197.41 1158.19 1088.47 1080.12 1068.13 1063.64 1063.77 1073.22 1106.35 1125.56 1150.04 1158.91 1135.78 1101.19 1079.63 1059.48 1045.84 1042.59 1005.04 1009.94 1029.02 1038.32 0.807464  0.0837012 0.188333 0.359539 0.565576 0.749304 0.873568  1.58871  5.05441  0.0245567  -0.00616844
+    evalout <<obj_fun<<" "<<
+              wt_like<<" "<<
+              q_prior<<" "<<
+              m_prior<<" "<<
+             rec_like<<" "<<
+             sel_like<<" "<<
+           catch_like<<" "<<
+             srv_like<<" "<<
+             age_like_fsh<<" "<<
+             age_like_srv<<" "<<
+		        q_srv(1)(1982,endyr)<<" "<<
+		        natmort_f<<" "<< 
+		        natmort_m<<" "<< 
+						Fmsyr <<" "<<ABC_biom<<" "<<Bmsy<<" "<<msy<<" "<< TotBiom 
+                     << " "<<SSB <<" "<< mean_log_rec <<" "<<partial_F_f(7,12)<<
+                        " "<<sel_slope_srv<<" "<<sel50_srv<<
+                        " "<<sel_slope_srv_m<<" "<<sel50_srv_m;
+	  double mean_N_fsh_age=0;
+    for (k=1;k<=nfsh;k++)
+    {
+      for (i=1;i<=nyrs_fsh_age_c(k);i++) // combined sexes
+        mean_N_fsh_age += Eff_N(oac_fsh_c(k,i),eac_fsh_c(k,i));
+      for (i=1;i<=nyrs_fsh_age_s(k);i++) // split sexes
+			  mean_N_fsh_age += Eff_N(oac_fsh_s(k,i),eac_fsh_s(k,i));
+			mean_N_fsh_age /= double(nyrs_fsh_age_c(k) + nyrs_fsh_age_s(k));
+    }
+    evalout << " " <<mean_N_fsh_age;
+		double mean_N_srv_age=0;
+    for (k=1;k<=nsrv;k++)
+    {
+      for (i=1;i<=nyrs_srv_age_c(k);i++) // combined sexes
+        mean_N_srv_age += Eff_N(oac_srv_c(k,i),eac_srv_c(k,i));
+      for (i=1;i<=nyrs_srv_age_s(k);i++) // split sexes
+			  mean_N_srv_age += Eff_N(oac_srv_s(k,i),eac_srv_s(k,i));
+			mean_N_srv_age /= double(nyrs_srv_age_c(k) + nyrs_srv_age_s(k));
+    }
+    evalout << " " <<mean_N_srv_age;
+  } 
+	// Alpha and beta of SRR
+  evalout << " " <<R_alpha<<" "<<R_beta<<endl;
 }
 
 void model_parameters::get_selectivity(void)
 {
-  //Logistic selectivity is modeled for the fishery and survey, by age
-  if (active(sel_slope_fsh_f))
-  {
-    dvariable slope_tmp;
-    dvariable sel50_tmp;
-  //   time invariant selectivy calculations
-  //  for (k=1;k<=nfsh;k++)
-  //  {
-  //    log_sel_fsh_f(k)(1,nselages) = -log( 1.0 + mfexp(-sel_slope_fsh(k) * (age_vector(1,nselages) - sel50_fsh(k)) ));
-  //    log_sel_fsh_f(k)(nselages,nages) = log_sel_fsh_f(k,nselages);
-  //
-  //    dvariable slope_tmp = sel_slope_fsh(k) * mfexp(sel_slope_fsh_m(k));
-  //    dvariable sel50_tmp = sel50_fsh(k)     * mfexp(sel50_fsh_m(k));
-  //   log_sel_fsh_m(k)(1,nselages) = -log( 1.0 + mfexp(-slope_tmp * (age_vector(1,nselages) - sel50_tmp) ));
-  //    log_sel_fsh_m(k)(nselages,nages) = log_sel_fsh_m(k,nselages);
-  //  }
-  //  time-varying selectivy calculations, by sex for the fishery, females first
-    for (k=1;k<=nfsh;k++)
-    {
-      for (i=styr;i<=endyr;i++)
-      {
-        // cout<<k<<" "<<i<<" "<<sel_slope_fsh_devs_f(k,i)<<endl;
-        slope_tmp = sel_slope_fsh_f(k)*mfexp(sel_slope_fsh_devs_f(k,i));
-        sel50_tmp = sel50_fsh_f(k)*mfexp(sel50_fsh_devs_f(k,i));
-        for (j=1;j<=nselages;j++)
-        {
-          log_sel_fsh_f(k,i,j) = -log(1.0 + mfexp(-slope_tmp*((j)-sel50_tmp)));
-        }
-     //  males
-        slope_tmp = sel_slope_fsh_m(k)*mfexp(sel_slope_fsh_devs_m(k,i));
-        sel50_tmp = sel50_fsh_m(k)*mfexp(sel50_fsh_devs_m(k,i));
-        for (j=1;j<=nselages;j++)
-        {
-          log_sel_fsh_m(k,i,j) = -log(1.0+mfexp(-slope_tmp*((j)-sel50_tmp)));
-        }
-        for (j=nselages+1;j<=nages;j++)
-        {
-          log_sel_fsh_f(k,i,j)=log_sel_fsh_f(k,i,j-1);
-          log_sel_fsh_m(k,i,j)=log_sel_fsh_m(k,i,j-1);
-        }
-      }
-    }
-    for (k=1;k<=nsrv;k++)
-    {
-      log_sel_srv_f(k)(1,nselages) = -log( 1.0 + mfexp(-1.*sel_slope_srv(k) * (age_vector(1,nselages) - sel50_srv(k)) ));
-      log_sel_srv_f(k)(nselages,nages) = log_sel_srv_f(k,nselages);
-      dvariable slope_tmp = sel_slope_srv(k) * mfexp(sel_slope_srv_m(k));
-      dvariable sel50_tmp = sel50_srv(k)     * mfexp(sel50_srv_m(k));
-      log_sel_srv_m(k)(1,nselages) = -log( 1.0 + mfexp(-slope_tmp * (age_vector(1,nselages) - sel50_tmp) ));
-      log_sel_srv_m(k)(nselages,nages) = log_sel_srv_m(k,nselages);
-    }
-  }
-  sel_srv_f=mfexp(log_sel_srv_f);
-  sel_srv_m=mfexp(log_sel_srv_m);
-  sel_fsh_f = mfexp(log_sel_fsh_f);
-  sel_fsh_m = mfexp(log_sel_fsh_m);
-  partial_F_f = mfexp(log_msy_sel_f);
-  partial_F_m = mfexp(log_msy_sel_m);
+  //Logistic selectivity is modeled for the fishery and survey, by age
+  if (active(sel_slope_fsh_f))
+  {
+    dvariable slope_tmp;
+    dvariable sel50_tmp;
+  //   time invariant selectivy calculations
+  //  for (k=1;k<=nfsh;k++)
+  //  {
+  //    log_sel_fsh_f(k)(1,nselages) = -log( 1.0 + mfexp(-sel_slope_fsh(k) * (age_vector(1,nselages) - sel50_fsh(k)) ));
+  //    log_sel_fsh_f(k)(nselages,nages) = log_sel_fsh_f(k,nselages);
+  //
+  //    dvariable slope_tmp = sel_slope_fsh(k) * mfexp(sel_slope_fsh_m(k));
+  //    dvariable sel50_tmp = sel50_fsh(k)     * mfexp(sel50_fsh_m(k));
+  //   log_sel_fsh_m(k)(1,nselages) = -log( 1.0 + mfexp(-slope_tmp * (age_vector(1,nselages) - sel50_tmp) ));
+  //    log_sel_fsh_m(k)(nselages,nages) = log_sel_fsh_m(k,nselages);
+  //  }
+  //  time-varying selectivy calculations, by sex for the fishery, females first
+    for (k=1;k<=nfsh;k++)
+    {
+      for (i=styr;i<=endyr;i++)
+      {
+        // cout<<k<<" "<<i<<" "<<sel_slope_fsh_devs_f(k,i)<<endl;
+        slope_tmp = sel_slope_fsh_f(k)*mfexp(sel_slope_fsh_devs_f(k,i));
+        sel50_tmp = sel50_fsh_f(k)*mfexp(sel50_fsh_devs_f(k,i));
+        for (j=1;j<=nselages;j++)
+        {
+          log_sel_fsh_f(k,i,j) = -log(1.0 + mfexp(-slope_tmp*((j)-sel50_tmp)));
+        }
+     //  males
+        slope_tmp = sel_slope_fsh_m(k)*mfexp(sel_slope_fsh_devs_m(k,i));
+        sel50_tmp = sel50_fsh_m(k)*mfexp(sel50_fsh_devs_m(k,i));
+        for (j=1;j<=nselages;j++)
+        {
+          log_sel_fsh_m(k,i,j) = -log(1.0+mfexp(-slope_tmp*((j)-sel50_tmp)));
+        }
+        for (j=nselages+1;j<=nages;j++)
+        {
+          log_sel_fsh_f(k,i,j)=log_sel_fsh_f(k,i,j-1);
+          log_sel_fsh_m(k,i,j)=log_sel_fsh_m(k,i,j-1);
+        }
+      }
+    }
+    for (k=1;k<=nsrv;k++)
+    {
+      log_sel_srv_f(k)(1,nselages) = -log( 1.0 + mfexp(-1.*sel_slope_srv(k) * (age_vector(1,nselages) - sel50_srv(k)) ));
+      log_sel_srv_f(k)(nselages,nages) = log_sel_srv_f(k,nselages);
+      dvariable slope_tmp = sel_slope_srv(k) * mfexp(sel_slope_srv_m(k));
+      dvariable sel50_tmp = sel50_srv(k)     * mfexp(sel50_srv_m(k));
+      log_sel_srv_m(k)(1,nselages) = -log( 1.0 + mfexp(-slope_tmp * (age_vector(1,nselages) - sel50_tmp) ));
+      log_sel_srv_m(k)(nselages,nages) = log_sel_srv_m(k,nselages);
+    }
+  }
+  sel_srv_f   = mfexp(log_sel_srv_f);
+  sel_srv_m   = mfexp(log_sel_srv_m);
+  sel_fsh_f   = mfexp(log_sel_fsh_f);
+  sel_fsh_m   = mfexp(log_sel_fsh_m);
+  if (active(male_sel_offset)) 
+    sel_fsh_m   = mfexp(log_sel_fsh_m+male_sel_offset);
+  partial_F_f = mfexp(log_msy_sel_f);
+  partial_F_m = mfexp(log_msy_sel_m);
 }
 
 void model_parameters::get_mortality(void)
 {
-  Z_f.initialize();
-  Z_m.initialize();
-  F_f.initialize();
-  F_m.initialize();
-  S_f.initialize();
-  S_m.initialize();
-  surv_f.initialize();
-  surv_m.initialize();
-  Fmort.initialize();
-  surv_f    = mfexp(-natmort_f);
-  surv_m    = mfexp(-natmort_m);
-  Z_f = natmort_f;
-  Z_m = natmort_m;
-  Fmort = 0.;
-  for (k=1;k<=nfsh;k++)
-  {
-    Fmort  += mfexp(log_avg_fmort(k) + fmort_dev(k));
-    for (i=styr;i<=endyr;i++)
-    {
-      F_f(k,i)  = (mfexp(log_avg_fmort(k) + fmort_dev(k,i))* sel_fsh_f(k,i)) ;
-      F_m(k,i)  = (mfexp(log_avg_fmort(k) + fmort_dev(k,i))* sel_fsh_m(k,i)) ;
-    }
-    Z_f += F_f(k);
-    Z_m += F_m(k);
-  }
-  S_f = mfexp(-Z_f);
-  S_m = mfexp(-Z_m);
+  Z_f.initialize();
+  Z_m.initialize();
+  F_f.initialize();
+  F_m.initialize();
+  S_f.initialize();
+  S_m.initialize();
+  surv_f.initialize();
+  surv_m.initialize();
+  Fmort.initialize();
+  surv_f    = mfexp(-natmort_f);
+  surv_m    = mfexp(-natmort_m);
+  Z_f = natmort_f;
+  Z_m = natmort_m;
+  Fmort = 0.;
+  for (k=1;k<=nfsh;k++)
+  {
+    Fmort  += mfexp(log_avg_fmort(k) + fmort_dev(k));
+    for (i=styr;i<=endyr;i++)
+    {
+      F_f(k,i)  = (mfexp(log_avg_fmort(k) + fmort_dev(k,i))* sel_fsh_f(k,i)) ;
+      F_m(k,i)  = (mfexp(log_avg_fmort(k) + fmort_dev(k,i))* sel_fsh_m(k,i)) ;
+    }
+    Z_f += F_f(k);
+    Z_m += F_m(k);
+  }
+  S_f = mfexp(-Z_f);
+  S_m = mfexp(-Z_m);
 }
 
 void model_parameters::get_numbers_at_age(void)
 {
-  //Initial age composition
-  // Initial age comp independent from recruitment...
-  if (styr_rec == styr)
-  {
-    for (j=2;j<=nages;j++)
-    {
-      natage_m(styr,j) = .5*mfexp(mean_log_init + init_dev_m(j) );
-      natage_f(styr,j) = .5*mfexp(mean_log_init + init_dev_f(j) );
-    }
-  }
-  else  // Initial age comp consistent with estimated recruitment levels
-  {
-    int itmp;
-    for (j=1;j<nages;j++)
-    {
-      itmp=styr+1-j;
-      natage_f(styr,j) = 0.5*mfexp(mean_log_rec-natmort_f*double(j-1)+rec_dev(itmp));
-      natage_m(styr,j) = 0.5*mfexp(mean_log_rec-natmort_m*double(j-1)+rec_dev(itmp));
-    }
-    //Plus group in the first year
-    itmp=styr+1-nages;
-    natage_f(styr,nages) = 0.5*mfexp(mean_log_rec+rec_dev(itmp) - natmort_f*(nages-1))/(1.-surv_f);
-    natage_m(styr,nages) = 0.5*mfexp(mean_log_rec+rec_dev(itmp) - natmort_m*(nages-1))/(1.-surv_m);
-  }
-  //Recruitment in subsequent years
-  for (i=styr;i<=endyr;i++)
-  {
-    natage_m(i,1) = 0.5*mfexp(mean_log_rec+rec_dev(i));
-    natage_f(i,1) = natage_m(i,1);
-  }
-  pred_rec(styr) = 2.*natage_m(styr,1);
-  //Fill in the rest of the matrix of numbers at age by applying F's
-  for (i=styr;i<endyr;i++)
-  {
-    natage_m(i+1)(2,nages)= ++elem_prod(natage_m(i)(1,nages-1),S_m(i)(1,nages-1));
-    natage_m(i+1,nages)  +=  natage_m(i,nages)*S_m(i,nages);
-    natage_f(i+1)(2,nages)= ++elem_prod(natage_f(i)(1,nages-1),S_f(i)(1,nages-1));
-    natage_f(i+1,nages)  +=  natage_f(i,nages)*S_f(i,nages);
-    TotBiom(i)=natage_f(i)*wt_pop_f(i) + natage_m(i)*wt_pop_m(i);
-    SSB(i)  =  elem_prod(natage_f(i),pow(S_f(i),spmo_frac)) * elem_prod(wt_pop_f(i),maturity(i));  //need to add recruitment lag
-		if (SSB(i)<0) cout <<i<<" "<<wt_pop_f(i)(1,5)<<" "<< maturity(i)(4,7) <<" "<< spmo_frac << endl;
-    // SSB_1         = value(elem_prod(elem_prod(Ntmp,pow(Stmp,spmo_frac)),maturity)*wt_pop_fut);
-    pred_rec(i+1) = 2.*natage_f(i+1,1);
-  }
- //  SSB(endyr) = (natage(endyr)/2) * elem_prod(wt_pop(endyr),maturity);
-  SSB(endyr)  =  elem_prod(natage_f(endyr),pow(S_f(endyr),spmo_frac)) * elem_prod(wt_pop_f(endyr),maturity(endyr));  //need to add recruitment lag
-  TotBiom(endyr)   =  natage_f(endyr)*wt_pop_f(endyr) + natage_m(endyr)*wt_pop_m(endyr);
-  if (sd_phase())
-  {
-    depletion = TotBiom(endyr)/TotBiom(styr);
-    endbiom=TotBiom(endyr);
-  }
-  //Survey computations
-  for (k=1;k<=nsrv;k++)
-  {
-    for (i=1;i<=nyrs_srv(k);i++)
-    {
-      int srvyrtmp = yrs_srv(k,i);
-      dvariable b1tmp = elem_prod(natage_f(srvyrtmp),exp( -Z_f(srvyrtmp) * srv_mo_frac(k) )) * elem_prod(sel_srv_f(k),wt_srv_f(k,srvyrtmp));
-      b1tmp          += elem_prod(natage_m(srvyrtmp),exp( -Z_m(srvyrtmp) * srv_mo_frac(k) )) * elem_prod(sel_srv_m(k),wt_srv_m(k,srvyrtmp));
-      if (active(q_beta(k))) 
-			{
-        q_srv(k,srvyrtmp) = mfexp(q_alpha(k));
-        for (int j=1;j<=n_env_cov(k);j++)
-					q_srv(k,srvyrtmp) *= mfexp( q_beta(k,j) * env_cov(k,j,i)) ;
-      }
-      else
-      {
-        q_srv(k) = mfexp(ln_q_srv(k));
-      }
-      pred_srv(k,srvyrtmp)     = q_srv(k,srvyrtmp) * b1tmp;
-    }
-    for (i=1;i<=nyrs_srv_age_c(k);i++)
-    {
-      int yrtmp = yrs_srv_age_c(k,i); 
-      eac_srv_c(k,i) = elem_prod(sel_srv_f(k),natage_f(yrtmp)) + elem_prod(sel_srv_m(k),natage_m(yrtmp)) ; 
-      eac_srv_c(k,i)/= sum(eac_srv_c(k,i));
-    }
-    for (i=1;i<=nyrs_srv_age_s(k);i++)
-    {
-      int yrtmp = yrs_srv_age_s(k,i); 
-      eac_srv_s(k,i)(1,nages) = elem_prod(sel_srv_f(k),natage_f(yrtmp));
-      // eac_srv_s(k,i)(nages+1,2*nages)  = elem_prod(sel_srv(k),natage_m(yrtmp)).shift(nages+1);
-      for (j=1;j<=nages;j++)
-        eac_srv_s(k,i,j+nages) = sel_srv_m(k,j) * natage_m(yrtmp,j);
-      eac_srv_s(k,i)/= sum(eac_srv_s(k,i));
-     }
-   }
+  //Initial age composition
+  // Initial age comp independent from recruitment...
+  if (styr_rec == styr)
+  {
+    for (j=2;j<=nages;j++)
+    {
+      natage_m(styr,j) = .5*mfexp(mean_log_init + init_dev_m(j) );
+      natage_f(styr,j) = .5*mfexp(mean_log_init + init_dev_f(j) );
+    }
+  }
+  else  // Initial age comp consistent with estimated recruitment levels
+  {
+    int itmp;
+    for (j=1;j<nages;j++)
+    {
+      itmp=styr+1-j;
+      natage_f(styr,j) = 0.5*mfexp(mean_log_rec-natmort_f*double(j-1)+rec_dev(itmp));
+      natage_m(styr,j) = 0.5*mfexp(mean_log_rec-natmort_m*double(j-1)+rec_dev(itmp));
+    }
+    //Plus group in the first year
+    itmp=styr+1-nages;
+    natage_f(styr,nages) = 0.5*mfexp(mean_log_rec+rec_dev(itmp) - natmort_f*(nages-1))/(1.-surv_f);
+    natage_m(styr,nages) = 0.5*mfexp(mean_log_rec+rec_dev(itmp) - natmort_m*(nages-1))/(1.-surv_m);
+  }
+  //Recruitment in subsequent years
+  for (i=styr;i<=endyr;i++)
+  {
+    natage_m(i,1) = 0.5*mfexp(mean_log_rec+rec_dev(i));
+    natage_f(i,1) = natage_m(i,1);
+  }
+  pred_rec(styr) = 2.*natage_m(styr,1);
+  //Fill in the rest of the matrix of numbers at age by applying F's
+  for (i=styr;i<endyr;i++)
+  {
+    natage_m(i+1)(2,nages)= ++elem_prod(natage_m(i)(1,nages-1),S_m(i)(1,nages-1));
+    natage_m(i+1,nages)  +=  natage_m(i,nages)*S_m(i,nages);
+    natage_f(i+1)(2,nages)= ++elem_prod(natage_f(i)(1,nages-1),S_f(i)(1,nages-1));
+    natage_f(i+1,nages)  +=  natage_f(i,nages)*S_f(i,nages);
+    TotBiom(i)=natage_f(i)*wt_pop_f(i) + natage_m(i)*wt_pop_m(i);
+    SSB(i)  =  elem_prod(natage_f(i),pow(S_f(i),spmo_frac)) * elem_prod(wt_pop_f(i),maturity(i));  //need to add recruitment lag
+		if (SSB(i)<0) cout <<i<<" "<<wt_pop_f(i)(1,5)<<" "<< maturity(i)(4,7) <<" "<< spmo_frac << endl;
+    // SSB_1         = value(elem_prod(elem_prod(Ntmp,pow(Stmp,spmo_frac)),maturity)*wt_pop_fut);
+    pred_rec(i+1) = 2.*natage_f(i+1,1);
+  }
+ //  SSB(endyr) = (natage(endyr)/2) * elem_prod(wt_pop(endyr),maturity);
+  SSB(endyr)  =  elem_prod(natage_f(endyr),pow(S_f(endyr),spmo_frac)) * elem_prod(wt_pop_f(endyr),maturity(endyr));  //need to add recruitment lag
+  TotBiom(endyr)   =  natage_f(endyr)*wt_pop_f(endyr) + natage_m(endyr)*wt_pop_m(endyr);
+  if (sd_phase())
+  {
+    depletion = TotBiom(endyr)/TotBiom(styr);
+    endbiom=TotBiom(endyr);
+  }
+  //Survey computations
+  for (k=1;k<=nsrv;k++)
+  {
+    for (i=1;i<=nyrs_srv(k);i++)
+    {
+      int srvyrtmp = yrs_srv(k,i);
+      dvariable b1tmp = elem_prod(natage_f(srvyrtmp),exp( -Z_f(srvyrtmp) * srv_mo_frac(k) )) * elem_prod(sel_srv_f(k),wt_srv_f(k,srvyrtmp));
+      b1tmp          += elem_prod(natage_m(srvyrtmp),exp( -Z_m(srvyrtmp) * srv_mo_frac(k) )) * elem_prod(sel_srv_m(k),wt_srv_m(k,srvyrtmp));
+      if (active(q_beta(k))) 
+			{
+        q_srv(k,srvyrtmp) = mfexp(q_alpha(k));
+        for (int j=1;j<=n_env_cov(k);j++)
+					q_srv(k,srvyrtmp) *= mfexp( q_beta(k,j) * env_cov(k,j,i)) ;
+      }
+      else
+      {
+        q_srv(k) = mfexp(ln_q_srv(k));
+      }
+      pred_srv(k,srvyrtmp)     = q_srv(k,srvyrtmp) * b1tmp;
+    }
+    for (i=1;i<=nyrs_srv_age_c(k);i++)
+    {
+      int yrtmp = yrs_srv_age_c(k,i); 
+      eac_srv_c(k,i) = elem_prod(sel_srv_f(k),natage_f(yrtmp)) + elem_prod(sel_srv_m(k),natage_m(yrtmp)) ; 
+      eac_srv_c(k,i)/= sum(eac_srv_c(k,i));
+    }
+    for (i=1;i<=nyrs_srv_age_s(k);i++)
+    {
+      int yrtmp = yrs_srv_age_s(k,i); 
+      eac_srv_s(k,i)(1,nages) = elem_prod(sel_srv_f(k),natage_f(yrtmp));
+      // eac_srv_s(k,i)(nages+1,2*nages)  = elem_prod(sel_srv(k),natage_m(yrtmp)).shift(nages+1);
+      for (j=1;j<=nages;j++)
+        eac_srv_s(k,i,j+nages) = sel_srv_m(k,j) * natage_m(yrtmp,j);
+      eac_srv_s(k,i)/= sum(eac_srv_s(k,i));
+     }
+   }
 }
 
 void model_parameters::catch_at_age(void)
 {
-  catage_f.initialize();
-  catage_m.initialize();
-  pred_catch.initialize();
-  for (k=1;k<=nfsh;k++)
-  {
-    for (i=styr;i<=endyr;i++)
-    {
-      catage_f(k,i) = elem_prod(elem_div(F_f(k,i),Z_f(i)),elem_prod(1. - S_f(i),natage_f(i)));
-      catage_m(k,i) = elem_prod(elem_div(F_m(k,i),Z_m(i)),elem_prod(1. - S_m(i),natage_m(i)));
-      pred_catch(k,i) = catage_f(k,i)*wt_fsh_f(k,i) ;
-      pred_catch(k,i)+= catage_m(k,i)*wt_fsh_m(k,i);
-    }
-    // if (sd_phase()) C_age = catage_f(1,endyr-2);
-    for (i=1;i<=nyrs_fsh_age_c(k);i++)
-    {
-      int yrtmp = yrs_fsh_age_c(k,i);
-      eac_fsh_c(k,i) = catage_f(k,yrtmp) + catage_m(k,yrtmp);
-      eac_fsh_c(k,i)/= sum(eac_fsh_c(k,i));
-    }
-    for (i=1;i<=nyrs_fsh_age_s(k);i++)
-    {
-      int yrtmp = yrs_fsh_age_s(k,i);
-      eac_fsh_s(k,i)(1,nages) = catage_f(k,yrtmp);
-      // eac_fsh_s(k,i)(nages+1,2*nages) = catage_f(k,yrtmp).shift(nages+1);
-      for (j=1;j<=nages;j++)
-        eac_fsh_s(k,i,j+nages) = catage_m(k,yrtmp,j);
-      eac_fsh_s(k,i) /= sum(eac_fsh_s(k,i));
-    }
-  }
+  catage_f.initialize();
+  catage_m.initialize();
+  pred_catch.initialize();
+  for (k=1;k<=nfsh;k++)
+  {
+    for (i=styr;i<=endyr;i++)
+    {
+      catage_f(k,i) = elem_prod(elem_div(F_f(k,i),Z_f(i)),elem_prod(1. - S_f(i),natage_f(i)));
+      catage_m(k,i) = elem_prod(elem_div(F_m(k,i),Z_m(i)),elem_prod(1. - S_m(i),natage_m(i)));
+      pred_catch(k,i) = catage_f(k,i)*wt_fsh_f(k,i) ;
+      pred_catch(k,i)+= catage_m(k,i)*wt_fsh_m(k,i);
+    }
+    // if (sd_phase()) C_age = catage_f(1,endyr-2);
+ 
+    for (i=1;i<=nyrs_fsh_age_c(k);i++)
+    {
+      int yrtmp = yrs_fsh_age_c(k,i);
+      eac_fsh_c(k,i) = catage_f(k,yrtmp) + catage_m(k,yrtmp);
+      eac_fsh_c(k,i)/= sum(eac_fsh_c(k,i));
+    }
+    for (i=1;i<=nyrs_fsh_age_s(k);i++)
+    {
+      int yrtmp = yrs_fsh_age_s(k,i);
+      eac_fsh_s(k,i)(1,nages) = catage_f(k,yrtmp);
+      // eac_fsh_s(k,i)(nages+1,2*nages) = catage_f(k,yrtmp).shift(nages+1);
+      for (j=1;j<=nages;j++)
+        eac_fsh_s(k,i,j+nages) = catage_m(k,yrtmp,j);
+      eac_fsh_s(k,i) /= sum(eac_fsh_s(k,i));
+    }
+  }
 }
 
 void model_parameters::evaluate_the_objective_function(void)
 {
-  if (active(F40))
-  {
-    // compute_spr_rates();
-    dvar_vector incr_dev_tmp(2,nages);
-    // two degree increase in temperature
-    incr_dev_tmp(5,nages-5)     = growth_alpha * 2.0 + age_incr;
-    incr_dev_tmp(nages-4,nages) = incr_dev_tmp(nages-5) ;
-    incr_dev_tmp(2,4)           = incr_dev_tmp(5) ;
-    wt_pop_fut_f(1)        = wt_vbg_f(1);
-    wt_pop_fut_m(1)        = wt_vbg_m(1);
-    wt_pop_fut_f(2,nages)  = ++wt_vbg_f(1,nages-1) + elem_prod(base_incr_f,mfexp(incr_dev_tmp)) ; // initializes estimates to correct values...
-    wt_pop_fut_m(2,nages)  = ++wt_vbg_m(1,nages-1) + elem_prod(base_incr_m,mfexp(incr_dev_tmp)) ; // initializes estimates to correct values...
-  }
-  fpen.initialize();
-  wt_like.initialize();
-  q_prior.initialize();
-  if(active(yr_incr)||active(age_incr)||active(growth_alpha))
-  {
-    // cout <<wt_pred_f(1988)(3,7)<<endl;
-    for (i=styr_wt;i<=endyr_wt;i++)
-    {
-      for (j=3;j<nages;j++)
-      {
-         // matrices for the period of wt-age data (modify to use sample size) divided by 2 to account for males and females...
-         wt_like(1) += 0.5*log(.1+ .5*n_wts(i,j)*square(log(wt_pred_f(i,j) + .1) - log(wt_obs_f(i,j) + .1)) ); 
-         wt_like(1) += 0.5*log(.1+ .5*n_wts(i,j)*square(log(wt_pred_m(i,j) + .1) - log(wt_obs_m(i,j) + .1)) ); // matrices for the period of wt-age data (modify to use sample size)
-         // wt_like(1) += 50.*(n_wts(i,j)*square(log(wt_pred_f(i,j) + .1) - log(wt_obs_f(i,j) + .1)) ); // matrices for the period of wt-age data (modify to use sample size)
-         // wt_like(1) += 50.*(n_wts(i,j)*square(log(wt_pred_m(i,j) + .1) - log(wt_obs_m(i,j) + .1)) ); // matrices for the period of wt-age data (modify to use sample size)
-      }
-    }
-    // wt_like(1) += 50.*norm2(log(wt_pred_f + .01) - log(wt_obs_f + .01)); // matrices for the period of wt-age data (modify to use sample size)
-    // wt_like(1) += 50.*norm2(log(wt_pred_m + .01) - log(wt_obs_m + .01)); // matrices for the period of wt-age data (modify to use sample size)
-    // obj_fun += 50.*norm2(incr_dev);
-    if(active(age_incr))
-      wt_like(2) += 12.5 * norm2(first_difference(first_difference(age_incr)));
-      // wt_like(2) += 12.5 * norm2(age_incr);
-    if(active(yr_incr))
-      wt_like(3) += 12.5 * norm2(yr_incr);
-    // cout<<"ObjFunWt: "<< norm2(log(wt_pred_m) - log(wt_obs_m))<< endl;; // matrices for the period of wt-age data (modify to use sample size)
-    obj_fun += sum(wt_like);
-  }
-  if (!do_wt_only)
-  {
-    if (active(rec_dev))
-    {
-      rec_like(1) = norm2(rec_dev);
-      sigma_rec = norm2(rec_dev);
-      var_rec = (sigma_rec/((endyr-styr)+1))+.0001;      //variance of Rbar from styr to endyr
-      rec_like(2)  = norm2(init_dev_m);
-      rec_like(2) += norm2(init_dev_f);
-      rec_like(4) = (1/(2*var_rec))*norm2(rec_dev_future);
-    }
-    if(active(R_logalpha))
-      rec_like(3) = (0.5*norm2(log(SAM_recruits)-log(SRC_recruits+1.0e-3)))/(sigmaR*sigmaR);
-    obj_fun += lambda(1)* sum(rec_like);
-    if (active(sigmaR))
-    {
-       sigmaR_prior = .5* square(log(sigmaR)-log(sigmaR_exp))/(sigmaR_sigma*sigmaR_sigma);
-       obj_fun  += sigmaR_prior;
-     }
-    // Note not general to multiple surveys...also ln_q_srv should be a "free" parameter because q_surve is an sdreport variable?
-    if (active(ln_q_srv)||active(q_alpha))
-    {
-       q_prior(1) = .5* norm2(log(q_srv(1)(1982,endyr))-log(q_exp))/(q_sigma*q_sigma);
-       obj_fun  += q_prior(1);
-     }
-    if (active(sel_slope_fsh_devs_f))
-    {
-      sel_like.initialize();
-      // Implies a CV of 0.5 on time-varying selectivity parameter
-      sel_like(1) += .5*norm2(sel_slope_fsh_devs_f)/(slp_sigma*slp_sigma);
-      sel_like(1) += .5*norm2(sel_slope_fsh_devs_m)/(slp_sigma*slp_sigma);
-      sel_like(2) += .5*norm2(sel50_fsh_devs_f)/(a50_sigma*a50_sigma);
-      sel_like(2) += .5*norm2(sel50_fsh_devs_m)/(a50_sigma*a50_sigma);
-      obj_fun += sum(sel_like);
-    }
-    if (active(natmort_f))
-    {
-       m_prior = .5* square(log(natmort_f)-log(m_exp))/(m_sigma*m_sigma);
-       obj_fun += m_prior;
-    }
-    if (current_phase()>phase_wt)
-    {
-      Age_Like();
-      Srv_Like();
-      if (phase_fmort>0)
-      {
-        catch_like = 0.;
-        for (int ifsh=1;ifsh<=nfsh;ifsh++)
-          catch_like += norm2(log(obs_catch(ifsh)(styr,endyr)+.000001)-log(pred_catch(ifsh)+.000001));
-        obj_fun += lambda(3) * catch_like;
-      }
-      Fmort_Pen();
-      obj_fun +=fpen;
-    }
-    if(active(wt_fsh_fut_f)) 
-	{
-	  wt_fut_like=0.;
-    for (int j=1;j<=nages;j++)
-    {
-      dvariable res = wt_fsh_mn_f(j)-wt_fsh_fut_f(j);
-      wt_fut_like += res*res / (2.*wt_fsh_sigma_f(j)*wt_fsh_sigma_f(j));
-      res           = wt_fsh_mn_m(j)-wt_fsh_fut_m(j);
-      wt_fut_like += res*res / (2.*wt_fsh_sigma_m(j)*wt_fsh_sigma_m(j));
-      res = wt_pop_mn_f(j)-wt_pop_fut_f(j);
-      wt_fut_like += res*res / (2.*wt_pop_sigma_f(j)*wt_pop_sigma_f(j));
-      res = wt_pop_mn_m(j)-wt_pop_fut_m(j);
-      wt_fut_like += res*res / (2.*wt_pop_sigma_m(j)*wt_pop_sigma_m(j));
-    }
-		obj_fun += wt_fut_like;
-  }
-  if(active(log_msy_sel_f)) 
-  {
-	  wt_msy_like=0.;
-    // dvar_vector pf_tmp = log(F(1,endyr)/F(1,endyr,nages)); // NOTE: For one fishery only!!!
-    // obj_fun += 0.5*norm2(pf_tmp - log_sel_coff)/(pf_sigma*pf_sigma);
-    dvar_vector log_sel_mean(1,nages);
-    log_sel_mean  = log_sel_fsh_f(1,endyr) ;
-    log_sel_mean += log_sel_fsh_f(1,endyr-1) ;
-    log_sel_mean += log_sel_fsh_f(1,endyr-2) ; 
-    log_sel_mean /= 3. ; 
-    wt_msy_like += 0.5*norm2(log_sel_mean - log_msy_sel_f)/(pf_sigma*pf_sigma);
-    log_sel_mean  = log_sel_fsh_m(1,endyr) ;
-    log_sel_mean += log_sel_fsh_m(1,endyr-1) ;
-    log_sel_mean += log_sel_fsh_m(1,endyr-2) ; 
-    log_sel_mean /= 3. ; 
-    wt_msy_like += 0.5*norm2(log_sel_mean - log_msy_sel_m)/(pf_sigma*pf_sigma);
-		obj_fun += wt_msy_like;
-  }
-  // small penalty to initialize stock to have similar values (unless data suggest otherwise)
-  if(active(init_dev_m))
-	{
-    init_like = norm2(init_dev_m-init_dev_f);
-		obj_fun += init_like;
-  }
-  }
+  if (active(F40))
+  {
+    compute_spr_rates();
+    dvar_vector incr_dev_tmp(2,nages);
+    // two degree increase in temperature
+    incr_dev_tmp(5,nages-5)     = growth_alpha * 2.0 + age_incr;
+    incr_dev_tmp(nages-4,nages) = incr_dev_tmp(nages-5) ;
+    incr_dev_tmp(2,4)           = incr_dev_tmp(5) ;
+    wt_pop_fut_f(1)        = wt_vbg_f(1);
+    wt_pop_fut_m(1)        = wt_vbg_m(1);
+    wt_pop_fut_f(2,nages)  = ++wt_vbg_f(1,nages-1) + elem_prod(base_incr_f,mfexp(incr_dev_tmp)) ; // initializes estimates to correct values...
+    wt_pop_fut_m(2,nages)  = ++wt_vbg_m(1,nages-1) + elem_prod(base_incr_m,mfexp(incr_dev_tmp)) ; // initializes estimates to correct values...
+  }
+  fpen.initialize();
+  wt_like.initialize();
+  q_prior.initialize();
+  if(active(yr_incr)||active(age_incr)||active(growth_alpha))
+  {
+   // cout <<wt_pred_f(1988)(3,7)<<endl;
+    for (i=styr_wt;i<=endyr_wt;i++)
+    {
+      for (j=3;j<nages;j++)
+      {
+         // matrices for the period of wt-age data (modify to use sample size) divided by 2 to account for males and females...
+         wt_like(1) += 0.5*log(.1+ .5*n_wts(i,j)*square(log(wt_pred_f(i,j) + .1) - log(wt_obs_f(i,j) + .1)) ); 
+         wt_like(1) += 0.5*log(.1+ .5*n_wts(i,j)*square(log(wt_pred_m(i,j) + .1) - log(wt_obs_m(i,j) + .1)) ); // matrices for the period of wt-age data (modify to use sample size)
+         // wt_like(1) += 50.*(n_wts(i,j)*square(log(wt_pred_f(i,j) + .1) - log(wt_obs_f(i,j) + .1)) ); // matrices for the period of wt-age data (modify to use sample size)
+         // wt_like(1) += 50.*(n_wts(i,j)*square(log(wt_pred_m(i,j) + .1) - log(wt_obs_m(i,j) + .1)) ); // matrices for the period of wt-age data (modify to use sample size)
+      }
+    }
+    // wt_like(1) += 50.*norm2(log(wt_pred_f + .01) - log(wt_obs_f + .01)); // matrices for the period of wt-age data (modify to use sample size)
+    // wt_like(1) += 50.*norm2(log(wt_pred_m + .01) - log(wt_obs_m + .01)); // matrices for the period of wt-age data (modify to use sample size)
+    // obj_fun += 50.*norm2(incr_dev);
+    if(active(age_incr))
+      wt_like(2) += 12.5 * norm2(first_difference(first_difference(age_incr)));
+      // wt_like(2) += 12.5 * norm2(age_incr);
+    if(active(yr_incr))
+      wt_like(3) += 12.5 * norm2(yr_incr);
+    // cout<<"ObjFunWt: "<< norm2(log(wt_pred_m) - log(wt_obs_m))<< endl;; // matrices for the period of wt-age data (modify to use sample size)
+    obj_fun += sum(wt_like);
+  }
+  if (!do_wt_only)
+  {
+    if (active(rec_dev))
+    {
+      rec_like(1) = norm2(rec_dev);
+      sigma_rec = norm2(rec_dev);
+      var_rec = (sigma_rec/((endyr-styr)+1))+.0001;      //variance of Rbar from styr to endyr
+  
+      rec_like(2)  = norm2(init_dev_m);
+      rec_like(2) += norm2(init_dev_f);
+      rec_like(4) = (1/(2*var_rec))*norm2(rec_dev_future);
+    }
+    if(active(R_logalpha))
+      rec_like(3) = (0.5*norm2(log(SAM_recruits)-log(SRC_recruits+1.0e-3)))/(sigmaR*sigmaR);
+  
+    obj_fun += lambda(1)* sum(rec_like);
+    if (active(sigmaR))
+    {
+       sigmaR_prior = .5* square(log(sigmaR)-log(sigmaR_exp))/(sigmaR_sigma*sigmaR_sigma);
+       obj_fun  += sigmaR_prior;
+       // cout<<"sigmaR_prior="<<sigmaR_prior<<endl;
+     }
+    // Note not general to multiple surveys...also ln_q_srv should be a "free" parameter because q_surve is an sdreport variable?
+    if (active(ln_q_srv)||active(q_alpha))
+    {
+       q_prior(1) = .5* norm2(log(q_srv(1)(1982,endyr))-log(q_exp))/(q_sigma*q_sigma);
+       obj_fun  += q_prior(1);
+       // cout<<"q_prior="<<q_prior<<endl;
+     }
+    if (active(sel_slope_fsh_devs_f))
+    {
+      sel_like.initialize();
+      // Implies a CV of 0.5 on time-varying selectivity parameter
+      sel_like(1) += .5*norm2(sel_slope_fsh_devs_f)/(slp_sigma*slp_sigma);
+      sel_like(1) += .5*norm2(sel_slope_fsh_devs_m)/(slp_sigma*slp_sigma);
+      sel_like(2) += .5*norm2(sel50_fsh_devs_f)/(a50_sigma*a50_sigma);
+      sel_like(2) += .5*norm2(sel50_fsh_devs_m)/(a50_sigma*a50_sigma);
+      obj_fun += sum(sel_like);
+      // cout<<"sel_like(1)="<<sel_like(1)<<endl;
+      // cout<<"sel_like(2)="<<sel_like(2)<<endl;
+    }
+  
+    if (active(natmort_f))
+    {
+       m_prior = .5* square(log(natmort_f)-log(m_exp))/(m_sigma*m_sigma);
+       obj_fun += m_prior;
+       // cout<<"m_prior="<<m_prior<<endl;
+    }
+  
+    if (current_phase()>phase_wt)
+    {
+      Age_Like();
+      Srv_Like();
+      if (phase_fmort>0)
+      {
+        catch_like = 0.;
+        for (int ifsh=1;ifsh<=nfsh;ifsh++)
+          catch_like += norm2(log(obs_catch(ifsh)(styr,endyr)+.000001)-log(pred_catch(ifsh)+.000001));
+        obj_fun += lambda(3) * catch_like;
+      }
+      Fmort_Pen();
+      obj_fun +=fpen;
+    }
+  
+    if(active(wt_fsh_fut_f)) 
+	{
+	  wt_fut_like=0.;
+    for (int j=1;j<=nages;j++)
+    {
+      dvariable res = wt_fsh_mn_f(j)-wt_fsh_fut_f(j);
+      wt_fut_like += res*res / (2.*wt_fsh_sigma_f(j)*wt_fsh_sigma_f(j));
+      res           = wt_fsh_mn_m(j)-wt_fsh_fut_m(j);
+      wt_fut_like += res*res / (2.*wt_fsh_sigma_m(j)*wt_fsh_sigma_m(j));
+      res = wt_pop_mn_f(j)-wt_pop_fut_f(j);
+      wt_fut_like += res*res / (2.*wt_pop_sigma_f(j)*wt_pop_sigma_f(j));
+      res = wt_pop_mn_m(j)-wt_pop_fut_m(j);
+      wt_fut_like += res*res / (2.*wt_pop_sigma_m(j)*wt_pop_sigma_m(j));
+    }
+		obj_fun += wt_fut_like;
+  }
+  if(active(log_msy_sel_f)) 
+  {
+	  wt_msy_like=0.;
+    // dvar_vector pf_tmp = log(F(1,endyr)/F(1,endyr,nages)); // NOTE: For one fishery only!!!
+    // obj_fun += 0.5*norm2(pf_tmp - log_sel_coff)/(pf_sigma*pf_sigma);
+    dvar_vector log_sel_mean(1,nages);
+    log_sel_mean  = log_sel_fsh_f(1,endyr) ;
+    log_sel_mean += log_sel_fsh_f(1,endyr-1) ;
+    log_sel_mean += log_sel_fsh_f(1,endyr-2) ; 
+    log_sel_mean /= 3. ; 
+    wt_msy_like += 0.5*norm2(log_sel_mean - log_msy_sel_f)/(pf_sigma*pf_sigma);
+    log_sel_mean  = log_sel_fsh_m(1,endyr) ;
+    log_sel_mean += log_sel_fsh_m(1,endyr-1) ;
+    log_sel_mean += log_sel_fsh_m(1,endyr-2) ; 
+    log_sel_mean /= 3. ; 
+    wt_msy_like += 0.5*norm2(log_sel_mean - log_msy_sel_m)/(pf_sigma*pf_sigma);
+		obj_fun += wt_msy_like;
+  }
+  // small penalty to initialize stock to have similar values (unless data suggest otherwise)
+  if(active(init_dev_m))
+	{
+    init_like = norm2(init_dev_m-init_dev_f);
+		obj_fun += init_like;
+  }
+  }
 }
 
 void model_parameters::Fmort_Pen(void)
 {
-  if (current_phase()<3)
-     fpen += 10.*norm2(Fmort - .2);
-  else
-     fpen += .01*norm2(Fmort - .2);
-  fpen += 100.*square(mean(fmort_dev));
+  if (current_phase()<3)
+     fpen += 10.*norm2(Fmort - .2);
+  else
+     fpen += .01*norm2(Fmort - .2);
+  fpen += 100.*square(mean(fmort_dev));
 }
 
 void model_parameters::Srv_Like(void)
 {
-  srv_like.initialize();
-  //cout<<pred_srv(1,yrs_srv(1,22)) <<" "<<pred_srv(1,yrs_srv(1,21)) <<endl;
-  for (k=1;k<=nsrv;k++)
-	{
-    for (i=1;i<=nyrs_srv(k);i++)
-		{
-     // Log-normal
-      srv_like(k) += lambda(2) * square(log(obs_srv(k,i) / pred_srv(k,yrs_srv(k,i)) ))/ (2.* obs_lse_srv(k,i) * obs_lse_srv(k,i)); 
-      // cout << i<<" "<<yrs_srv(k,i)<<" "<< lambda(2) * square(log(obs_srv(k,i) / pred_srv(k,yrs_srv(k,i)) ))/ (2.* obs_lse_srv(k,i) * obs_lse_srv(k,i))<<endl; 
-     // Normal
-      //srv_like(k) += lambda(2) * square(obs_srv(k,i) - pred_srv(k,yrs_srv(k,i)) )/ (2.* obs_se_srv(k,i) * obs_se_srv(k,i));
-    }
-  }
-  obj_fun += sum(srv_like);
+  srv_like.initialize();
+  //cout<<pred_srv(1,yrs_srv(1,22)) <<" "<<pred_srv(1,yrs_srv(1,21)) <<endl;
+  for (k=1;k<=nsrv;k++)
+	{
+    for (i=1;i<=nyrs_srv(k);i++)
+		{
+     // Log-normal
+      srv_like(k) += lambda(2) * square(log(obs_srv(k,i) / pred_srv(k,yrs_srv(k,i)) ))/ (2.* obs_lse_srv(k,i) * obs_lse_srv(k,i)); 
+      // cout << i<<" "<<yrs_srv(k,i)<<" "<< lambda(2) * square(log(obs_srv(k,i) / pred_srv(k,yrs_srv(k,i)) ))/ (2.* obs_lse_srv(k,i) * obs_lse_srv(k,i))<<endl; 
+     // Normal
+      //srv_like(k) += lambda(2) * square(obs_srv(k,i) - pred_srv(k,yrs_srv(k,i)) )/ (2.* obs_se_srv(k,i) * obs_se_srv(k,i));
+    }
+  }
+  obj_fun += sum(srv_like);
 }
 
 void model_parameters::Age_Like(void)
 {
-  age_like_fsh.initialize();
-  for (k=1;k<=nfsh;k++)
-  {
-      for (i=1;i<=nyrs_fsh_age_c(k);i++)
-         age_like_fsh(k) -= nsmpl_fsh_c(k,i)*(oac_fsh_c(k,i) + 0.001) * log(eac_fsh_c(k,i) + 0.001);
-      for (i=1;i<=nyrs_fsh_age_s(k);i++)
-         age_like_fsh(k) -= nsmpl_fsh_s(k,i)*(oac_fsh_s(k,i) + 0.001) * log(eac_fsh_s(k,i) + 0.001);
-  }
-  age_like_fsh-=offset_fsh;
-  obj_fun += sum(age_like_fsh);
-  age_like_srv.initialize();
-  for (k=1;k<=nsrv;k++)
-  {
-    for (i=1;i<=nyrs_srv_age_c(k);i++)
-      age_like_srv(k) -= nsmpl_srv_c(k,i)*(oac_srv_c(k,i) + 0.001) * log(eac_srv_c(k,i) + 0.001);
-    for (i=1;i<=nyrs_srv_age_s(k);i++)
-      age_like_srv(k) -= nsmpl_srv_s(k,i)*(oac_srv_s(k,i) + 0.001) * log(eac_srv_s(k,i) + 0.001);
-  }
-  age_like_srv-=offset_srv;
-  obj_fun += sum(age_like_srv);
+  age_like_fsh.initialize();
+  for (k=1;k<=nfsh;k++)
+  {
+      for (i=1;i<=nyrs_fsh_age_c(k);i++)
+         age_like_fsh(k) -= nsmpl_fsh_c(k,i)*(oac_fsh_c(k,i) + 0.001) * log(eac_fsh_c(k,i) + 0.001);
+	// cout<<"nyrs_fsh_age_s="<<nyrs_fsh_age_s(k)<<endl;
+      for (i=1;i<=nyrs_fsh_age_s(k);i++)
+      {
+         age_like_fsh(k) -= nsmpl_fsh_s(k,i)*(oac_fsh_s(k,i) + 0.001) * log(eac_fsh_s(k,i) + 0.001);
+        //cout<<"age_like_fsh="<<age_like_fsh(k)<<endl;
+	}
+  }
+  age_like_fsh-=offset_fsh;
+  obj_fun += sum(age_like_fsh);
+  age_like_srv.initialize();
+  for (k=1;k<=nsrv;k++)
+  {
+    for (i=1;i<=nyrs_srv_age_c(k);i++)
+      age_like_srv(k) -= nsmpl_srv_c(k,i)*(oac_srv_c(k,i) + 0.001) * log(eac_srv_c(k,i) + 0.001);
+    for (i=1;i<=nyrs_srv_age_s(k);i++)
+    {
+      age_like_srv(k) -= nsmpl_srv_s(k,i)*(oac_srv_s(k,i) + 0.001) * log(eac_srv_s(k,i) + 0.001);
+      // cout<<"age_like_srv="<<age_like_srv(k)<<endl;
+    }
+  }
+  age_like_srv-=offset_srv;
+  obj_fun += sum(age_like_srv);
+  
 }
 
 dvariable model_parameters::spr_ratio(dvariable trial_F,dvar_vector& sel)
 {
-  dvariable SBtmp;
-  dvar_vector Ntmp(1,nages);
-  dvar_vector srvtmp(1,nages);
-  SBtmp.initialize();
-  Ntmp.initialize();
-  srvtmp.initialize();
-  dvar_vector Ftmp(1,nages);
-  Ftmp = sel*trial_F;
-  srvtmp  = exp(-(Ftmp + natmort_f) );
-  dvar_vector wttmp = wt_pop_f(endyr);
-  Ntmp(1)=1.;
-  j=1;
-  // Sp_Biom_future(i) = elem_prod(wt_pop ,maturity) * elem_prod(nage_future(i),pow(S_future(i),yrfrac)) ;
-	// Note using end-year maturity for spr
-  SBtmp  += Ntmp(j)*maturity(endyr,j)*wttmp(j)*pow(srvtmp(j),spmo_frac);
-  for (j=2;j<nages;j++)
-  {
-    Ntmp(j) = Ntmp(j-1)*srvtmp(j-1);
-    SBtmp  += Ntmp(j)*maturity(endyr,j)*wttmp(j)*pow(srvtmp(j),spmo_frac);
-  }
-  Ntmp(nages)=Ntmp(nages-1)*srvtmp(nages-1)/(1.-srvtmp(nages));
-  SBtmp  += Ntmp(nages)*maturity(endyr,nages)*wttmp(nages)*pow(srvtmp(nages),spmo_frac);
-  // cout<<sel_tmp<<endl<< " Trial: "<<trial_F<<" "<<SBtmp<<" Phizero "<<phizero<<endl;
-  phizero=get_spr(0.0);
-  return(get_spr(trial_F)/phizero);
+  dvariable SBtmp;
+  dvar_vector Ntmp(1,nages);
+  dvar_vector srvtmp(1,nages);
+  SBtmp.initialize();
+  Ntmp.initialize();
+  srvtmp.initialize();
+  dvar_vector Ftmp(1,nages);
+  Ftmp = sel*trial_F;
+  srvtmp  = exp(-(Ftmp + natmort_f) );
+  dvar_vector wttmp = wt_pop_f(endyr);
+  Ntmp(1)=1.;
+  j=1;
+  // Sp_Biom_future(i) = elem_prod(wt_pop ,maturity) * elem_prod(nage_future(i),pow(S_future(i),yrfrac)) ;
+	// Note using end-year maturity for spr
+  SBtmp  += Ntmp(j)*maturity(endyr,j)*wttmp(j)*pow(srvtmp(j),spmo_frac);
+  for (j=2;j<nages;j++)
+  {
+    Ntmp(j) = Ntmp(j-1)*srvtmp(j-1);
+    SBtmp  += Ntmp(j)*maturity(endyr,j)*wttmp(j)*pow(srvtmp(j),spmo_frac);
+  }
+  Ntmp(nages)=Ntmp(nages-1)*srvtmp(nages-1)/(1.-srvtmp(nages));
+  SBtmp  += Ntmp(nages)*maturity(endyr,nages)*wttmp(nages)*pow(srvtmp(nages),spmo_frac);
+  // cout<<sel_tmp<<endl<< " Trial: "<<trial_F<<" "<<SBtmp<<" Phizero "<<phizero<<endl;
+  phizero=get_spr(0.0);
+  return(get_spr(trial_F)/phizero);
 }
 
 void model_parameters::compute_spr_rates(void)
 {
-  SB0=0.;
-  SBF40=0.; 
-  SBF35=0.;
-  SBF30=0.;
-  for (i=1;i<=4;i++)
-    Nspr(i,1)=1.;
-  // dvar_matrix sel_tmp(sel_fsh_f(1).colmin(),sel_fsh_f(1).colmax(),sel_fsh_f(1).rowmin(),sel_fsh_f(1).rowmax());
-  // sel_tmp = trans(sel_fsh_f(1));
-  dvar_matrix sel_tmpu(1,nfsh,1,nages);
-  dvar_matrix sel_tmp(1,nages,1,nfsh);
-  for (k=1;k<=nfsh;k++)
-    sel_tmpu(k) = sel_fsh_f(k,endyr);
-  sel_tmp = trans(sel_tmpu);
-  for (j=2;j<nages;j++)
-  {
-    Nspr(1,j) = Nspr(1,j-1)*exp(-natmort_f);
-    Nspr(2,j) = Nspr(2,j-1)*exp(-(natmort_f+F40*sel_tmp(j-1)));
-    Nspr(3,j) = Nspr(3,j-1)*exp(-(natmort_f+F35*sel_tmp(j-1)));
-    Nspr(4,j) = Nspr(4,j-1)*exp(-(natmort_f+F30*sel_tmp(j-1)));
-  }
-  Nspr(1,nages)=Nspr(1,nages-1)*exp(-natmort_f)/(1.-exp(-natmort_f));
-  Nspr(2,nages)=Nspr(2,nages-1)*exp(-(natmort_f+F40*sel_tmp(nages-1)))/(1.-exp(-(natmort_f+F40*sel_tmp(nages))));
-  Nspr(3,nages)=Nspr(3,nages-1)*exp(-(natmort_f+F35*sel_tmp(nages-1)))/(1.-exp(-(natmort_f+F35*sel_tmp(nages))));
-  Nspr(4,nages)=Nspr(4,nages-1)*exp(-(natmort_f+F30*sel_tmp(nages-1)))/(1.-exp(-(natmort_f+F30*sel_tmp(nages))));
-  for (j=1;j<=nages;j++)
-  {
-    SB0    += 0.5 * Nspr(1,j) * maturity(endyr,j) * wt_pop_fut_f(j) * exp(-spmo_frac*natmort_f);
-    SBF40  += 0.5 * Nspr(2,j) * maturity(endyr,j) * wt_pop_fut_f(j) * exp(-spmo_frac*(natmort_f+F40*sel_tmp(j)));
-    SBF35  += 0.5 * Nspr(3,j) * maturity(endyr,j) * wt_pop_fut_f(j) * exp(-spmo_frac*(natmort_f+F35*sel_tmp(j)));
-    SBF30  += 0.5 * Nspr(4,j) * maturity(endyr,j) * wt_pop_fut_f(j) * exp(-spmo_frac*(natmort_f+F30*sel_tmp(j)));
-  }
-  sprpen   =10.*square(SBF40-0.4*SB0);
-  sprpen  +=10.*square(SBF35-0.35*SB0);
-  sprpen  +=10.*square(SBF30-0.3*SB0);
-  obj_fun += sprpen;
+  SB0=0.;
+  SBF40=0.; 
+  SBF35=0.;
+  SBF30=0.;
+  for (i=1;i<=4;i++)
+    Nspr(i,1)=1.;
+  // dvar_matrix sel_tmp(sel_fsh_f(1).colmin(),sel_fsh_f(1).colmax(),sel_fsh_f(1).rowmin(),sel_fsh_f(1).rowmax());
+  // sel_tmp = trans(sel_fsh_f(1));
+  dvar_matrix sel_tmpu(1,nfsh,1,nages);
+  dvar_matrix sel_tmp(1,nages,1,nfsh);
+  for (k=1;k<=nfsh;k++)
+    sel_tmpu(k) = sel_fsh_f(k,endyr);
+  sel_tmp = trans(sel_tmpu);
+  for (j=2;j<nages;j++)
+  {
+    Nspr(1,j) = Nspr(1,j-1)*exp(-natmort_f);
+    Nspr(2,j) = Nspr(2,j-1)*exp(-(natmort_f+F40*sel_tmp(j-1)));
+    Nspr(3,j) = Nspr(3,j-1)*exp(-(natmort_f+F35*sel_tmp(j-1)));
+    Nspr(4,j) = Nspr(4,j-1)*exp(-(natmort_f+F30*sel_tmp(j-1)));
+  }
+  Nspr(1,nages)=Nspr(1,nages-1)*exp(-natmort_f)/(1.-exp(-natmort_f));
+  Nspr(2,nages)=Nspr(2,nages-1)*exp(-(natmort_f+F40*sel_tmp(nages-1)))/(1.-exp(-(natmort_f+F40*sel_tmp(nages))));
+  Nspr(3,nages)=Nspr(3,nages-1)*exp(-(natmort_f+F35*sel_tmp(nages-1)))/(1.-exp(-(natmort_f+F35*sel_tmp(nages))));
+  Nspr(4,nages)=Nspr(4,nages-1)*exp(-(natmort_f+F30*sel_tmp(nages-1)))/(1.-exp(-(natmort_f+F30*sel_tmp(nages))));
+  for (j=1;j<=nages;j++)
+  {
+    SB0    += 0.5 * Nspr(1,j) * maturity(endyr,j) * wt_pop_fut_f(j) * exp(-spmo_frac*natmort_f);
+    SBF40  += 0.5 * Nspr(2,j) * maturity(endyr,j) * wt_pop_fut_f(j) * exp(-spmo_frac*(natmort_f+F40*sel_tmp(j)));
+    SBF35  += 0.5 * Nspr(3,j) * maturity(endyr,j) * wt_pop_fut_f(j) * exp(-spmo_frac*(natmort_f+F35*sel_tmp(j)));
+    SBF30  += 0.5 * Nspr(4,j) * maturity(endyr,j) * wt_pop_fut_f(j) * exp(-spmo_frac*(natmort_f+F30*sel_tmp(j)));
+  }
+  sprpen   =10.*square(SBF40-0.4*SB0);
+  sprpen  +=10.*square(SBF35-0.35*SB0);
+  sprpen  +=10.*square(SBF30-0.3*SB0);
+  obj_fun += sprpen;
 }
 
 void model_parameters::compute_sr_fit(void)
 {
-  // sigmaR = 0.6;
-  R_alpha=mfexp(R_logalpha);
-  R_beta=mfexp(R_logbeta);
-  for (int i=styr_sr; i <= endyr_sr; i++)
-  {
-    SAM_recruits(i)= 2.*natage_f(i,1);
-    SRC_recruits(i) = SRecruit(SSB(i-rec_lag));
-  }
+  // sigmaR = 0.6;
+  R_alpha=mfexp(R_logalpha);
+  R_beta=mfexp(R_logbeta);
+  //R_alpha= 0.0160063;
+  // = 0.00302922;
+	
+  for (int i=styr_sr; i <= endyr_sr; i++)
+  {
+    SAM_recruits(i)= 2.*natage_f(i,1);
+    SRC_recruits(i) = SRecruit(SSB(i-rec_lag));
+  }
 }
 
 dvariable model_parameters::SRecruit(const dvariable& Stmp)
 {
-  RETURN_ARRAYS_INCREMENT();
-  dvariable RecTmp;
-  RecTmp = R_alpha*Stmp*mfexp(-R_beta*Stmp);              // Ricker model
-  /* switch (SrType)
-  {
-    case 1: // Eq. 12
-      break;
-    case 2:
-      RecTmp = Stmp / ( alpha + beta * Stmp);        //Beverton-Holt form
-      break;
-    case 3:
-      RecTmp = mfexp(log_avgrec);                    //Avg recruitment
-      break;
-    case 4:
-      RecTmp = Stmp * mfexp( alpha  - Stmp * beta) ; //old Ricker form
-      break;
-  }
-	*/
-  RETURN_ARRAYS_DECREMENT();
-  return RecTmp;
+  RETURN_ARRAYS_INCREMENT();
+  dvariable RecTmp;
+  RecTmp = R_alpha*Stmp*mfexp(-R_beta*Stmp);              // Ricker model
+  /* switch (SrType)
+  {
+    case 1: // Eq. 12
+      break;
+    case 2:
+      RecTmp = Stmp / ( alpha + beta * Stmp);        //Beverton-Holt form
+      break;
+    case 3:
+      RecTmp = mfexp(log_avgrec);                    //Avg recruitment
+      break;
+    case 4:
+      RecTmp = Stmp * mfexp( alpha  - Stmp * beta) ; //old Ricker form
+      break;
+  }
+	*/
+  RETURN_ARRAYS_DECREMENT();
+  return RecTmp;
 }
 
 dvariable model_parameters::get_yield(const dvariable& Ftmp)
 {
-  dvariable phi;  
-  dvariable ypr;
-  dvariable yield;
-  dvariable R_eq;
-  phi  = get_spr(Ftmp);
-  R_eq = -(log(1/(R_alpha*phi)))/(phi*R_beta);   // Ricker formulation of equilibrium recruitment at each F
-  ypr  = get_ypr(Ftmp);
-  yield=R_eq*ypr;
-  return(yield);
+  dvariable phi;  
+  dvariable ypr;
+  dvariable yield;
+  dvariable R_eq;
+  phi  = get_spr(Ftmp);
+  R_eq = -(log(1/(R_alpha*phi)))/(phi*R_beta);   // Ricker formulation of equilibrium recruitment at each F
+  ypr  = get_ypr(Ftmp);
+  yield=R_eq*ypr;
+  return(yield);
 }
 
 dvariable model_parameters::get_spr(dvariable Ftemp)
 {
-  dvariable phi;
-  dvar_vector sel_tmp(1,nages);
-  sel_tmp = partial_F_f; // Set selectivity to 
-  dvar_vector Ntmp(1,nages);
-  Ntmp(1)=1.;
-  for (j=2;j<=nages;j++)
-  {
-     Ntmp(j)=Ntmp(j-1)*exp(-(natmort_f+Ftemp*sel_tmp(j-1)));  // fills in matrix for ages 2 through nages-1
-   }   
-   Ntmp(nages)=Ntmp(nages-1)*exp(-(natmort_f+Ftemp*sel_tmp(nages-1)))/(1.-exp(-(natmort_f+Ftemp*sel_tmp(nages))));
-   phi = 0.5*elem_prod(Ntmp,maturity(endyr))*elem_prod(wt_pop_fut_f,exp(-spmo_frac*(natmort_f+Ftemp*sel_tmp)));
-   return(phi);
+  dvariable phi;
+  dvar_vector sel_tmp(1,nages);
+  sel_tmp = partial_F_f; // Set selectivity to 
+  dvar_vector Ntmp(1,nages);
+  Ntmp(1)=1.;
+  for (j=2;j<=nages;j++)
+  {
+     Ntmp(j)=Ntmp(j-1)*exp(-(natmort_f+Ftemp*sel_tmp(j-1)));  // fills in matrix for ages 2 through nages-1
+           
+   }   
+   Ntmp(nages)=Ntmp(nages-1)*exp(-(natmort_f+Ftemp*sel_tmp(nages-1)))/(1.-exp(-(natmort_f+Ftemp*sel_tmp(nages))));
+           
+   phi = 0.5*elem_prod(Ntmp,maturity(endyr))*elem_prod(wt_pop_fut_f,exp(-spmo_frac*(natmort_f+Ftemp*sel_tmp)));
+   return(phi);
+  
 }
 
 dvariable model_parameters::get_ypr(dvariable Ftemp)
 {
-  dvariable ypr;
-  dvar_vector sel_tmp_f(1,nages);
-  dvar_vector sel_tmp_m(1,nages);
-  sel_tmp_f = partial_F_f; // Set selectivity to 
-  sel_tmp_m = partial_F_m; // Set selectivity to 
-  dvar_vector Ntmp_f(1,nages);
-  dvar_vector Ntmp_m(1,nages);
-  Ntmp_f(1)=1.;
-  Ntmp_m(1)=1.;
-  for (j=2;j<=nages;j++)
-  {
-     Ntmp_f(j)=Ntmp_f(j-1)*exp(-(natmort_f+Ftemp*sel_tmp_f(j-1)));  // fills in matrix for ages 2 through nages-1
-     Ntmp_m(j)=Ntmp_m(j-1)*exp(-(natmort_m+Ftemp*sel_tmp_m(j-1)));  // fills in matrix for ages 2 through nages-1
-  }   
-   Ntmp_f(nages)=Ntmp_f(nages-1)*exp(-(natmort_f+Ftemp*sel_tmp_f(nages-1)))/(1.-exp(-(natmort_f+Ftemp*sel_tmp_f(nages))));
-   Ntmp_m(nages)=Ntmp_m(nages-1)*exp(-(natmort_m+Ftemp*sel_tmp_m(nages-1)))/(1.-exp(-(natmort_m+Ftemp*sel_tmp_m(nages))));
-   // ypr = elem_div(Ftemp*sel_tmp,Ftemp*sel_tmp+natmort)*elem_prod(elem_prod(Ntmp,wt_pop(endyr)),(1-exp(-(natmort+Ftemp*sel_tmp))));
-   ypr  = elem_div(Ftemp*sel_tmp_f,Ftemp*sel_tmp_f+natmort_f)*elem_prod(elem_prod(Ntmp_f,wt_fsh_fut_f),(1-exp(-(natmort_f+Ftemp*sel_tmp_f))));
-   ypr += elem_div(Ftemp*sel_tmp_m,Ftemp*sel_tmp_m+natmort_m)*elem_prod(elem_prod(Ntmp_m,wt_fsh_fut_m),(1-exp(-(natmort_m+Ftemp*sel_tmp_m))));
-   return(ypr);
+  dvariable ypr;
+  dvar_vector sel_tmp_f(1,nages);
+  dvar_vector sel_tmp_m(1,nages);
+  sel_tmp_f = partial_F_f; // Set selectivity to 
+  sel_tmp_m = partial_F_m; // Set selectivity to 
+ 
+  dvar_vector Ntmp_f(1,nages);
+  dvar_vector Ntmp_m(1,nages);
+  Ntmp_f(1)=1.;
+  Ntmp_m(1)=1.;
+  for (j=2;j<=nages;j++)
+  {
+     Ntmp_f(j)=Ntmp_f(j-1)*exp(-(natmort_f+Ftemp*sel_tmp_f(j-1)));  // fills in matrix for ages 2 through nages-1
+     Ntmp_m(j)=Ntmp_m(j-1)*exp(-(natmort_m+Ftemp*sel_tmp_m(j-1)));  // fills in matrix for ages 2 through nages-1
+  }   
+   Ntmp_f(nages)=Ntmp_f(nages-1)*exp(-(natmort_f+Ftemp*sel_tmp_f(nages-1)))/(1.-exp(-(natmort_f+Ftemp*sel_tmp_f(nages))));
+   Ntmp_m(nages)=Ntmp_m(nages-1)*exp(-(natmort_m+Ftemp*sel_tmp_m(nages-1)))/(1.-exp(-(natmort_m+Ftemp*sel_tmp_m(nages))));
+           
+   // ypr = elem_div(Ftemp*sel_tmp,Ftemp*sel_tmp+natmort)*elem_prod(elem_prod(Ntmp,wt_pop(endyr)),(1-exp(-(natmort+Ftemp*sel_tmp))));
+   ypr  = elem_div(Ftemp*sel_tmp_f,Ftemp*sel_tmp_f+natmort_f)*elem_prod(elem_prod(Ntmp_f,wt_fsh_fut_f),(1-exp(-(natmort_f+Ftemp*sel_tmp_f))));
+   ypr += elem_div(Ftemp*sel_tmp_m,Ftemp*sel_tmp_m+natmort_m)*elem_prod(elem_prod(Ntmp_m,wt_fsh_fut_m),(1-exp(-(natmort_m+Ftemp*sel_tmp_m))));
+   return(ypr);
 }
 
 dvariable model_parameters::get_biom_per_rec(dvariable Ftemp)
 {
- // calculation of equilibrium biomass for geometric mean calc determination
-  dvariable bpr;
-  dvar_vector sel_tmp_f(1,nages);
-  dvar_vector sel_tmp_m(1,nages);
-  dvar_vector Ntmp_f(1,nages);
-  dvar_vector Ntmp_m(1,nages);
-  sel_tmp_f = partial_F_f; // Set selectivity to 
-  sel_tmp_m = partial_F_m; // Set selectivity to 
-  Ntmp_f(1)=1.;
-  Ntmp_m(1)=1.;
-  for (j=2;j<=nages;j++)
-  {
-     Ntmp_f(j)=Ntmp_f(j-1)*exp(-(natmort_f+Ftemp*sel_tmp_f(j-1)));  // fills in matrix for ages 2 through nages-1
-     Ntmp_m(j)=Ntmp_m(j-1)*exp(-(natmort_m+Ftemp*sel_tmp_m(j-1)));  // fills in matrix for ages 2 through nages-1
-  }   
-   // bpr = Ntmp(6,nages)*wt_pop(endyr)(6,nages); //JNI? need to change here to wt_fmsy?
-   bpr  = Ntmp_f(ABC_age_lb,nages)*wt_pop_fut_f(ABC_age_lb,nages); 
-   bpr += Ntmp_m(ABC_age_lb,nages)*wt_pop_fut_m(ABC_age_lb,nages); 
-   return(bpr);
+ // calculation of equilibrium biomass for geometric mean calc determination
+  dvariable bpr;
+  dvar_vector sel_tmp_f(1,nages);
+  dvar_vector sel_tmp_m(1,nages);
+  dvar_vector Ntmp_f(1,nages);
+  dvar_vector Ntmp_m(1,nages);
+  sel_tmp_f = partial_F_f; // Set selectivity to 
+  sel_tmp_m = partial_F_m; // Set selectivity to 
+  Ntmp_f(1)=1.;
+  Ntmp_m(1)=1.;
+  for (j=2;j<=nages;j++)
+  {
+     Ntmp_f(j)=Ntmp_f(j-1)*exp(-(natmort_f+Ftemp*sel_tmp_f(j-1)));  // fills in matrix for ages 2 through nages-1
+     Ntmp_m(j)=Ntmp_m(j-1)*exp(-(natmort_m+Ftemp*sel_tmp_m(j-1)));  // fills in matrix for ages 2 through nages-1
+  }   
+   // bpr = Ntmp(6,nages)*wt_pop(endyr)(6,nages); //JNI? need to change here to wt_fmsy?
+   bpr  = Ntmp_f(ABC_age_lb,nages)*wt_pop_fut_f(ABC_age_lb,nages); 
+   bpr += Ntmp_m(ABC_age_lb,nages)*wt_pop_fut_m(ABC_age_lb,nages); 
+   return(bpr);
 }
 
 void model_parameters::get_msy(void)
 {
-    double d;
-    dvariable F1;
-    dvariable F2;
-    dvariable F3;
-    dvariable yld1;
-    dvariable yld2;
-    dvariable yld3;
-    dvariable Fprime;
-    dvariable F2prime;
-    dvariable R_eq;
-    dvariable phi;
-    F1 = 1.1* natmort_f;          //start with F=M
-    d=0.00001;
-    for (i=1;i<=6;i++)
-    {
-      F2      = F1+d;
-      F3      = F1-d;
-      yld1    = get_yield(F1);
-      yld2    = get_yield(F2);
-      yld3    = get_yield(F3);
-      Fprime  = (yld2-yld3)/(2*d);   //  Newton-Raphson approximation for first derivitive
-      F2prime = (yld3-(2*yld1)+yld2)/(d*d);  // Newton-Raphson approximation for second derivitive
-      F1     -= Fprime/F2prime;              // value to increment F for next time through the loop
-      // cout <<"F1= "<<F1<<" Fprime= "<<Fprime<<endl;
-    }
-    Fmsy    = F1;
-    phi     = get_spr(Fmsy);
-    R_eq    = -(log(1/(R_alpha*phi)))/(phi*R_beta);   // Ricker formulation of equilibrium recruitment at each F
-    Bmsy    = R_eq*phi;
-    msy     = get_yield(Fmsy);
-    logFmsy = log(Fmsy);
-    Bmsy    = R_eq*phi;
-    SPR_OFL = spr_ratio(Fmsy,partial_F_f);
-    Bmsyr   = R_eq*get_biom_per_rec(Fmsy)    ;
-    Fmsyr   = msy/Bmsyr;
-    logFmsyr= log(Fmsyr);
+    double d;
+    dvariable F1;
+    dvariable F2;
+    dvariable F3;
+    dvariable yld1;
+    dvariable yld2;
+    dvariable yld3;
+    dvariable Fprime;
+    dvariable F2prime;
+    dvariable R_eq;
+    dvariable phi;
+    F1 = 1.1* natmort_f;          //start with F=M
+    d=0.00001;
+    for (i=1;i<=6;i++)
+    {
+      F2      = F1+d;
+      F3      = F1-d;
+      yld1    = get_yield(F1);
+      yld2    = get_yield(F2);
+      yld3    = get_yield(F3);
+      Fprime  = (yld2-yld3)/(2*d);   //  Newton-Raphson approximation for first derivitive
+      F2prime = (yld3-(2*yld1)+yld2)/(d*d);  // Newton-Raphson approximation for second derivitive
+      F1     -= Fprime/F2prime;              // value to increment F for next time through the loop
+      // cout <<"F1= "<<F1<<" Fprime= "<<Fprime<<endl;
+    }
+    Fmsy    = F1;
+    phi     = get_spr(Fmsy);
+    R_eq    = -(log(1/(R_alpha*phi)))/(phi*R_beta);   // Ricker formulation of equilibrium recruitment at each F
+    Bmsy    = R_eq*phi;
+    msy     = get_yield(Fmsy);
+    logFmsy = log(Fmsy);
+    Bmsy    = R_eq*phi;
+    SPR_OFL = spr_ratio(Fmsy,partial_F_f);
+    Bmsyr   = R_eq*get_biom_per_rec(Fmsy)    ;
+    Fmsyr   = msy/Bmsyr;
+    logFmsyr= log(Fmsyr);
 }
 
 void model_parameters::Future_projections(void)
 {
-  nage_future_f(styr_fut)(2,nages) = ++elem_prod(natage_f(endyr)(1,nages-1),S_f(endyr)(1,nages-1));
-  nage_future_f(styr_fut,nages)   += natage_f(endyr,nages)*S_f(endyr,nages);
-  nage_future_m(styr_fut)(2,nages) = ++elem_prod(natage_m(endyr)(1,nages-1),S_m(endyr)(1,nages-1));
-  nage_future_m(styr_fut,nages)   += natage_m(endyr,nages)*S_m(endyr,nages);
-  dvar_vector meanF(1,nfsh) ;
-  // compute mean F based on last three years of Fs (assuming nages is fully selected and males and females the same...)
-  meanF(1) = mean(trans(F_m(1))(nages)(endyr-3,endyr));
-  future_SSB.initialize();
-  future_catch.initialize();
-  for (int m=1;m<=num_proj_Fs;m++)
-  {
-    switch (m)
-    {
-      case 1:
-        ftmp = F40;
-        break;
-      case 2:
-        ftmp = F35;
-        break;
-      case 3:
-        ftmp = meanF;
-        break;
-      case 4:
-        ftmp = 0.0;
-        break;
-      case 5:
-        ftmp = 0.0;
-        break;
-     }
-  //Calculation of future F's, Z and survival (S)
-     Z_future_f = natmort_f;
-     Z_future_m = natmort_m;
-     dvar_vector wt_tmp_f(1,nages);   
-     dvar_vector wt_tmp_m(1,nages);   
-     for (i=endyr+1;i<=endyr_fut;i++)
-     {
-       // compute future ssb/rec under no fishing (but only need to do that once...)
-       if (m==1)
-       {
-         // future_spr0(i) = get_spr(0.);
-       }
-       // Set growth if temperature related
-       if (Growth_Option==3)
-       {
-         dvar_vector incr_dev_tmp(2,nages);
-         incr_dev_tmp(5,nages-5)     = growth_alpha * fut_temp(i-endyr) ;
-         incr_dev_tmp(nages-4,nages) = incr_dev_tmp(nages-5) ;
-         incr_dev_tmp(2,4)           = incr_dev_tmp(5) ;
-         wt_tmp_f(1)        = wt_vbg_f(1);
-         wt_tmp_f(2,nages)  = ++wt_vbg_f(1,nages-1) + elem_prod(base_incr_f,mfexp(incr_dev_tmp)) ; // initializes estimates to correct values...
-         wt_tmp_m(1)        = wt_vbg_m(1);
-         wt_tmp_m(2,nages)  = ++wt_vbg_m(1,nages-1) + elem_prod(base_incr_m,mfexp(incr_dev_tmp)) ; // initializes estimates to correct values...
-         wt_pop_fut_f           = wt_tmp_f;
-         wt_pop_fut_m           = wt_tmp_m;
-         wt_fsh_fut_f           = wt_tmp_f;
-         wt_fsh_fut_m           = wt_tmp_m;
-       }
-       for (k=1;k<=nfsh;k++)
-       {
-         F_future_f(k,i) = sel_fsh_f(k,endyr) * ftmp(k);
-         Z_future_f(i)  += F_future_f(k,i);
-         F_future_m(k,i) = sel_fsh_m(k,endyr) * ftmp(k);
-         Z_future_m(i)  += F_future_m(k,i);
-       }
-       S_future_f(i) = exp(-Z_future_f(i));
-       S_future_m(i) = exp(-Z_future_m(i));
-     }
-  //Future recruitment and SSB
-  //Mean average recruitment of the time-series is used for the projection
-    //NOTE spawningbiomass is beginyear, NOT spawnmonth xxx
-  dvariable Rectmp=mfexp(mean_log_rec);
-  for (i=styr_fut;i<=endyr_fut;i++)
-  {
-		// cout<<"Future rec, 3-yr avg: "<<i<<" "<<Rectmp<< " "<< .5*mean(pred_rec(endyr-3,endyr))<< endl;
-    nage_future_f(i,1) = Rectmp*mfexp(rec_dev_future(i));
-    nage_future_m(i,1) = nage_future_f(i,1);
-		if (m==5) 
-		{
-      Z_future_f = natmort_f;
-      Z_future_m = natmort_m;
-      for (k=1;k<=nfsh;k++)
-      {
-        ftmp(k)         = SolveF2(nage_future_f(i),nage_future_m(i),yr1_futcat); // Only works for 1 fishery
-        F_future_f(k,i) = sel_fsh_f(k,endyr) * ftmp(k);
-        Z_future_f(i)  += F_future_f(k,i);
-        F_future_m(k,i) = sel_fsh_m(k,endyr) * ftmp(k);
-        Z_future_m(i)  += F_future_m(k,i);
-      }
-      S_future_f(i) = exp(-Z_future_f(i));
-      S_future_m(i) = exp(-Z_future_m(i));
-      ABC_biom(i)      = nage_future_f(i)(ABC_age_lb,nages) * wt_pop_fut_f(ABC_age_lb,nages); 
-      ABC_biom(i)     += nage_future_m(i)(ABC_age_lb,nages) * wt_pop_fut_m(ABC_age_lb,nages); 
-    }
-    SSB_future(i)      = elem_prod(nage_future_f(i),pow(S_future_f(i),spmo_frac)) * elem_prod(wt_pop_fut_f,maturity(endyr));  //need to add recruitment lag
-    Rectmp             = R_alpha*SSB_future(i)*(mfexp(-R_beta*SSB_future(i)));
-    TotBiom_future(i)  = nage_future_f(i)*wt_pop_fut_f; 
-    TotBiom_future(i) += nage_future_m(i)*wt_pop_fut_m; 
-  //Now graduate for the next year.....
-	  if (i!=endyr_fut)
-	  {
-      nage_future_f(i+1)(2,nages) = ++elem_prod(nage_future_f(i)(1,nages-1),S_future_f(i)(1,nages-1));
-      nage_future_f(i+1,nages)   += nage_future_f(i,nages) * S_future_f(i,nages);
-      nage_future_m(i+1)(2,nages) = ++elem_prod(nage_future_m(i)(1,nages-1),S_future_m(i)(1,nages-1));
-      nage_future_m(i+1,nages)   += nage_future_m(i,nages) * S_future_m(i,nages);
-    }
-    nage_future_f(endyr_fut,1) = .5*Rectmp*mfexp(rec_dev_future(endyr_fut));
-    nage_future_m(endyr_fut,1) = nage_future_f(endyr_fut,1) ;
-  }
-  SSB_future(endyr_fut) = elem_prod(nage_future_f(endyr_fut)/2,pow(S_future_f(endyr_fut),spmo_frac)) * elem_prod(wt_pop_fut_f,maturity(endyr));  //need to add recruitment lag
-  TotBiom_future(endyr_fut)  = nage_future_f(endyr_fut)*wt_pop_fut_f;
-  TotBiom_future(endyr_fut) += nage_future_m(endyr_fut)*wt_pop_fut_m;
-  //Calculations of catch at predicted future age composition
-  for (i=styr_fut;i<=endyr_fut;i++)
-  {
-    catage_future_f(i) = 0.;
-    catage_future_m(i) = 0.;
-    for (k=1;k<=nfsh;k++)
-    {
-      catage_future_f(i) += elem_prod(nage_future_f(i), elem_prod(F_future_f(k,i), elem_div( (1.-S_future_f(i) ),Z_future_f(i))));
-      catage_future_m(i) += elem_prod(nage_future_m(i), elem_prod(F_future_m(k,i), elem_div( (1.-S_future_m(i) ),Z_future_m(i))));
-    }
-    if (m<=npfs)  // catch biomass in future
-      future_catch(m,i)  += catage_future_f(i)*wt_fsh_fut_f + catage_future_m(i)*wt_fsh_fut_m      ;
-    future_SSB(m,i) = SSB_future(i);
-    future_TotBiom(m,i) = TotBiom_future(i);
-   }
-  }   //End of loop over F's
+  nage_future_f(styr_fut)(2,nages) = ++elem_prod(natage_f(endyr)(1,nages-1),S_f(endyr)(1,nages-1));
+  nage_future_f(styr_fut,nages)   += natage_f(endyr,nages)*S_f(endyr,nages);
+  nage_future_m(styr_fut)(2,nages) = ++elem_prod(natage_m(endyr)(1,nages-1),S_m(endyr)(1,nages-1));
+  nage_future_m(styr_fut,nages)   += natage_m(endyr,nages)*S_m(endyr,nages);
+  dvar_vector meanF(1,nfsh) ;
+  // compute mean F based on last three years of Fs (assuming nages is fully selected and males and females the same...)
+  meanF(1) = mean(trans(F_m(1))(nages)(endyr-3,endyr));
+  future_SSB.initialize();
+  future_Fs.initialize();
+  future_catch.initialize();
+  
+  for (int m=1;m<=num_proj_Fs;m++)
+  {
+    switch (m)
+    {
+      case 1:
+        ftmp = F40;
+        break;
+      case 2:
+        ftmp = F35;
+        break;
+      case 3:
+        ftmp = meanF;
+        break;
+      case 4:
+        ftmp = 0.0;
+        break;
+      case 5: // this is the case for fixed future catch
+        ftmp = 0.0;
+        break;
+     }
+  //Calculation of future F's, Z and survival (S)
+     Z_future_f = natmort_f;
+     Z_future_m = natmort_m;
+     dvar_vector wt_tmp_f(1,nages);   
+     dvar_vector wt_tmp_m(1,nages);   
+     for (i=endyr+1;i<=endyr_fut;i++)
+     {
+       // compute future ssb/rec under no fishing (but only need to do that once...)
+       if (m==1)
+       {
+         // future_spr0(i) = get_spr(0.);
+       }
+       // Set growth if temperature related
+       if (Growth_Option==3)
+       {
+         dvar_vector incr_dev_tmp(2,nages);
+         incr_dev_tmp(5,nages-5)     = growth_alpha * fut_temp(i-endyr) ;
+         incr_dev_tmp(nages-4,nages) = incr_dev_tmp(nages-5) ;
+         incr_dev_tmp(2,4)           = incr_dev_tmp(5) ;
+         wt_tmp_f(1)        = wt_vbg_f(1);
+         wt_tmp_f(2,nages)  = ++wt_vbg_f(1,nages-1) + elem_prod(base_incr_f,mfexp(incr_dev_tmp)) ; // initializes estimates to correct values...
+         wt_tmp_m(1)        = wt_vbg_m(1);
+         wt_tmp_m(2,nages)  = ++wt_vbg_m(1,nages-1) + elem_prod(base_incr_m,mfexp(incr_dev_tmp)) ; // initializes estimates to correct values...
+         wt_pop_fut_f           = wt_tmp_f;
+         wt_pop_fut_m           = wt_tmp_m;
+         wt_fsh_fut_f           = wt_tmp_f;
+         wt_fsh_fut_m           = wt_tmp_m;
+       }
+       for (k=1;k<=nfsh;k++)
+       {
+         F_future_f(k,i) = sel_fsh_f(k,endyr) * ftmp(k);
+         Z_future_f(i)  += F_future_f(k,i);
+         F_future_m(k,i) = sel_fsh_m(k,endyr) * ftmp(k);
+         Z_future_m(i)  += F_future_m(k,i);
+       }
+       S_future_f(i) = exp(-Z_future_f(i));
+       S_future_m(i) = exp(-Z_future_m(i));
+     }
+     
+  //Future recruitment and SSB
+  //Mean average recruitment of the time-series is used for the projection
+    //NOTE spawningbiomass is beginyear, NOT spawnmonth xxx
+  dvariable Rectmp=mfexp(mean_log_rec);
+  for (i=styr_fut;i<=endyr_fut;i++)
+  {
+		// cout<<"Future rec, 3-yr avg: "<<i<<" "<<Rectmp<< " "<< .5*mean(pred_rec(endyr-3,endyr))<< endl;
+    nage_future_f(i,1) = Rectmp*mfexp(rec_dev_future(i));
+    nage_future_m(i,1) = nage_future_f(i,1);
+		if (m==5) 
+		{
+      Z_future_f = natmort_f;
+      Z_future_m = natmort_m;
+      for (k=1;k<=nfsh;k++)
+      {
+        ftmp(k)         = SolveF2(nage_future_f(i),nage_future_m(i),future_ABC(k,i)); // Only works for 1 fishery
+				future_Fs(i)   += ftmp(k);
+        F_future_f(k,i) = sel_fsh_f(k,endyr) * ftmp(k);
+        Z_future_f(i)  += F_future_f(k,i);
+        F_future_m(k,i) = sel_fsh_m(k,endyr) * ftmp(k);
+        Z_future_m(i)  += F_future_m(k,i);
+      }
+      S_future_f(i) = exp(-Z_future_f(i));
+      S_future_m(i) = exp(-Z_future_m(i));
+      ABC_biom(i)      = nage_future_f(i)(ABC_age_lb,nages) * wt_pop_fut_f(ABC_age_lb,nages); 
+      ABC_biom(i)     += nage_future_m(i)(ABC_age_lb,nages) * wt_pop_fut_m(ABC_age_lb,nages); 
+    }
+    SSB_future(i)      = elem_prod(nage_future_f(i),pow(S_future_f(i),spmo_frac)) * elem_prod(wt_pop_fut_f,maturity(endyr));  //need to add recruitment lag
+    Rectmp             = R_alpha*SSB_future(i)*(mfexp(-R_beta*SSB_future(i)));
+    TotBiom_future(i)  = nage_future_f(i)*wt_pop_fut_f; 
+    TotBiom_future(i) += nage_future_m(i)*wt_pop_fut_m; 
+  //Now graduate for the next year.....
+	  if (i!=endyr_fut)
+	  {
+      nage_future_f(i+1)(2,nages) = ++elem_prod(nage_future_f(i)(1,nages-1),S_future_f(i)(1,nages-1));
+      nage_future_f(i+1,nages)   += nage_future_f(i,nages) * S_future_f(i,nages);
+      nage_future_m(i+1)(2,nages) = ++elem_prod(nage_future_m(i)(1,nages-1),S_future_m(i)(1,nages-1));
+      nage_future_m(i+1,nages)   += nage_future_m(i,nages) * S_future_m(i,nages);
+    }
+    nage_future_f(endyr_fut,1) = .5*Rectmp*mfexp(rec_dev_future(endyr_fut));
+    nage_future_m(endyr_fut,1) = nage_future_f(endyr_fut,1) ;
+  }
+  SSB_future(endyr_fut) = elem_prod(nage_future_f(endyr_fut),pow(S_future_f(endyr_fut),spmo_frac)) * elem_prod(wt_pop_fut_f,maturity(endyr));  //need to add recruitment lag
+  TotBiom_future(endyr_fut)  = nage_future_f(endyr_fut)*wt_pop_fut_f;
+  TotBiom_future(endyr_fut) += nage_future_m(endyr_fut)*wt_pop_fut_m;
+  //Calculations of catch at predicted future age composition
+  for (i=styr_fut;i<=endyr_fut;i++)
+  {
+    catage_future_f(i) = 0.;
+    catage_future_m(i) = 0.;
+    for (k=1;k<=nfsh;k++)
+    {
+      catage_future_f(i) += elem_prod(nage_future_f(i), elem_prod(F_future_f(k,i), elem_div( (1.-S_future_f(i) ),Z_future_f(i))));
+      catage_future_m(i) += elem_prod(nage_future_m(i), elem_prod(F_future_m(k,i), elem_div( (1.-S_future_m(i) ),Z_future_m(i))));
+    }
+    if (m<=npfs)  // catch biomass in future
+      future_catch(m,i)  += catage_future_f(i)*wt_fsh_fut_f + catage_future_m(i)*wt_fsh_fut_m      ;
+    future_SSB(m,i) = SSB_future(i);
+    future_TotBiom(m,i) = TotBiom_future(i);
+   }
+  }   //End of loop over F's
 }
 
 void model_parameters::write_srec(void)
 {
-  dvariable phi;  
-  phizero=get_spr(0.0);
-  // cout<<phizero<<endl;
-  dvariable Rzero = -(log(1/(R_alpha*phizero)))/(phizero*R_beta);   // Ricker formulation of equilibrium recruitment at each F
-  dvariable Bzero = Rzero*phizero;
-  dvariable Btmp  =  .8*Bzero;
-  srecpar << "# Bzero,  PhiZero,  Alpha, sigmaR"<<endl;
-  srecpar     << Bzero          <<
-         " "  << phizero/1000   <<
-         " "  << (log(R_alpha)-R_beta*Btmp+log(phizero))/(1.-Btmp/Bzero) <<
-         " "  << sigmaR         << endl;
-  R_report << "$Bzero" <<endl;
-  R_report << Bzero    <<endl;
-  R_report << "$phizero" <<endl;
-  R_report << phizero/1000<<endl;
-  R_report << "$alpha_sr" <<endl;
-  R_report << (log(R_alpha)-R_beta*Btmp+log(phizero))/(1.-Btmp/Bzero) <<endl;
-  R_report << "$R_alpha" <<endl;
-  R_report << R_alpha <<endl;
-  R_report << "$R_beta" <<endl;
-  R_report << R_beta <<endl;
-  R_report << "$sigmaR" <<endl;
-  R_report << sigmaR    <<endl;
+  dvariable phi;  
+  phizero=get_spr(0.0);
+  // cout<<phizero<<endl;
+  dvariable Rzero = -(log(1/(R_alpha*phizero)))/(phizero*R_beta);   // Ricker formulation of equilibrium recruitment at each F
+       rechat(i)  = R_alpha*SRR_SSB(i)*(mfexp(-R_beta*SRR_SSB(i)));
+	cout<<phizero<<" R0 "<<Rzero<<endl;
+  dvariable Bzero = Rzero*phizero;
+  dvariable Btmp  =  .8*Bzero;
+  srecpar << "# Bzero,  PhiZero,  Alpha, sigmaR"<<endl;
+  srecpar     << Bzero          <<
+         " "  << phizero/1000   <<
+         " "  << (log(R_alpha)-R_beta*Btmp+log(phizero))/(1.-Btmp/Bzero) <<
+         " "  << sigmaR         << endl;
+  R_report << "Bzero" <<endl;
+  R_report << Bzero    <<endl;
+  R_report << "phizero" <<endl;
+  R_report << phizero/1000<<endl;
+  R_report << "alpha_sr" <<endl;
+  R_report << (log(R_alpha)-R_beta*Btmp+log(phizero))/(1.-Btmp/Bzero) <<endl;
+  R_report << "R_alpha" <<endl;
+  R_report << R_alpha <<endl;
+  R_report << "R_beta" <<endl;
+  R_report << R_beta <<endl;
+  R_report << "sigmaR" <<endl;
+  R_report << sigmaR    <<endl;
 }
 
 void model_parameters::compute_spr_rates_2(void)
 {
-  //Compute SPR Rates 
-  F35 = get_spr_rates(.35);
-  F40 = get_spr_rates(.40);
+  //Compute SPR Rates 
+  F35 = get_spr_rates(.35);
+  F40 = get_spr_rates(.40);
 }
 
 dvariable model_parameters::get_spr_rates(double spr_percent)
 {
-  RETURN_ARRAYS_INCREMENT();
-  double df=1.e-3;
-  dvariable F1 ;
-  F1.initialize();
-  F1 = .9*natmort_f;
-  dvariable F2;
-  dvariable F3;
-  dvariable yld1;
-  dvariable yld2;
-  dvariable yld3;
-  dvariable dyld;
-  dvariable dyldp;
-  // Newton Raphson stuff to go here
-  for (int ii=1;ii<=6;ii++)
-  {
-    F2     = F1 + df;
-    F3     = F1 - df;
-    yld1   = -100.*square(log(spr_percent/spr_ratio(F1)));
-    yld2   = -100.*square(log(spr_percent/spr_ratio(F2)));
-    yld3   = -100.*square(log(spr_percent/spr_ratio(F3)));
-    dyld   = (yld2 - yld3)/(2*df);                          // First derivative (to find the root of this)
-    dyldp  = (yld3-(2*yld1)+yld2)/(df*df);  // Newton-Raphson approximation for second derivitive
-    F1    -= dyld/dyldp;
-  }
-  RETURN_ARRAYS_DECREMENT();
-  return(F1);
+  RETURN_ARRAYS_INCREMENT();
+  double df=1.e-3;
+  dvariable F1 ;
+  F1.initialize();
+  F1 = .9*natmort_f;
+  dvariable F2;
+  dvariable F3;
+  dvariable yld1;
+  dvariable yld2;
+  dvariable yld3;
+  dvariable dyld;
+  dvariable dyldp;
+  // Newton Raphson stuff to go here
+  for (int ii=1;ii<=6;ii++)
+  {
+    F2     = F1 + df;
+    F3     = F1 - df;
+    yld1   = -100.*square(log(spr_percent/spr_ratio(F1)));
+    yld2   = -100.*square(log(spr_percent/spr_ratio(F2)));
+    yld3   = -100.*square(log(spr_percent/spr_ratio(F3)));
+    dyld   = (yld2 - yld3)/(2*df);                          // First derivative (to find the root of this)
+    dyldp  = (yld3-(2*yld1)+yld2)/(df*df);  // Newton-Raphson approximation for second derivitive
+    F1    -= dyld/dyldp;
+  }
+  RETURN_ARRAYS_DECREMENT();
+  return(F1);
 }
 
 dvariable model_parameters::spr_ratio(dvariable trial_F)
 {
-  RETURN_ARRAYS_INCREMENT();
-  dvariable SBtmp;
-  dvar_vector Ntmp(1,nages);
-  dvar_vector srvtmp(1,nages);
-  SBtmp.initialize();
-  Ntmp.initialize();
-  srvtmp.initialize();
-  dvar_vector Ftmp(1,nages);
-  dvar_vector wttmp = wt_pop_fut_f;
-  Ftmp = sel_fsh_f(1,endyr) * trial_F;
-  srvtmp  = mfexp(-(Ftmp + natmort_f) );
-  Ntmp(1)=1.;
-  j=1;
-  SBtmp  += Ntmp(j)*maturity(endyr,j)*wttmp(j)*pow(srvtmp(j),spmo_frac);
-  for (j=2;j<nages;j++)
-  {
-    Ntmp(j) = Ntmp(j-1)*srvtmp(j-1);
-    SBtmp  += Ntmp(j)*maturity(endyr,j)*wttmp(j)*pow(srvtmp(j),spmo_frac);
-   // !!spmo_frac    =(spawnmo-1)/12.;
-  }
-  Ntmp(nages)=Ntmp(nages-1)*srvtmp(nages-1)/(1.-srvtmp(nages));
-  SBtmp  += Ntmp(nages)*maturity(endyr,nages)*wttmp(nages)*pow(srvtmp(nages),spmo_frac);
-  RETURN_ARRAYS_DECREMENT();
-  return(SBtmp/phizero);
+  RETURN_ARRAYS_INCREMENT();
+  dvariable SBtmp;
+  dvar_vector Ntmp(1,nages);
+  dvar_vector srvtmp(1,nages);
+  SBtmp.initialize();
+  Ntmp.initialize();
+  srvtmp.initialize();
+  dvar_vector Ftmp(1,nages);
+  dvar_vector wttmp = wt_pop_fut_f;
+  Ftmp = sel_fsh_f(1,endyr) * trial_F;
+  srvtmp  = mfexp(-(Ftmp + natmort_f) );
+  Ntmp(1)=1.;
+  j=1;
+  SBtmp  += Ntmp(j)*maturity(endyr,j)*wttmp(j)*pow(srvtmp(j),spmo_frac);
+  for (j=2;j<nages;j++)
+  {
+    Ntmp(j) = Ntmp(j-1)*srvtmp(j-1);
+    SBtmp  += Ntmp(j)*maturity(endyr,j)*wttmp(j)*pow(srvtmp(j),spmo_frac);
+   // !!spmo_frac    =(spawnmo-1)/12.;
+  }
+  Ntmp(nages)=Ntmp(nages-1)*srvtmp(nages-1)/(1.-srvtmp(nages));
+  SBtmp  += Ntmp(nages)*maturity(endyr,nages)*wttmp(nages)*pow(srvtmp(nages),spmo_frac);
+  RETURN_ARRAYS_DECREMENT();
+  return(SBtmp/phizero);
 }
 
 void model_parameters::report(const dvector& gradients)
@@ -2014,450 +2168,470 @@ void model_parameters::report(const dvector& gradients)
     cerr << "error trying to open report file"  << adprogram_name << ".rep";
     return;
   }
-  save_gradients(gradients);
-  dvar_vector wt_pop_tmp_f(1,nages);
-	int ilike=1;
-	nLogPosterior(ilike) = wt_like(1); ilike++;
-	nLogPosterior(ilike) = wt_like(2); ilike++;
-	nLogPosterior(ilike) = wt_like(3); ilike++;
-	nLogPosterior(ilike) = wt_fut_like; ilike++;
-	nLogPosterior(ilike) = wt_msy_like; ilike++;
-	nLogPosterior(ilike) = init_like  ; ilike++;
-	nLogPosterior(ilike) = srv_like(1);   ilike++;
-	nLogPosterior(ilike) = catch_like ; ilike++;
-	nLogPosterior(ilike) = age_like_fsh(1); ilike++;
-	nLogPosterior(ilike) = age_like_srv(1); ilike++;
-	nLogPosterior(ilike) = rec_like(1); ilike++;
-	nLogPosterior(ilike) = rec_like(2); ilike++;
-	nLogPosterior(ilike) = rec_like(3); ilike++;
-	nLogPosterior(ilike) = rec_like(4); ilike++;
-	nLogPosterior(ilike) = sel_like(1); ilike++;
-	nLogPosterior(ilike) = sel_like(2); ilike++;
-	nLogPosterior(ilike) = q_prior(1)  ; ilike++;
-	nLogPosterior(ilike) = sigmaR_prior; ilike++;
-	nLogPosterior(ilike) = m_prior     ; ilike++;
-	nLogPosterior(ilike) = fpen       ; ilike++;
-  for (int i=0;i<=3;i++)
-    {
-      dvar_vector incr_dev_tmp(2,nages);
-      incr_dev_tmp(5,nages-5)     = growth_alpha * double(i) ;
-      incr_dev_tmp(nages-4,nages) = incr_dev_tmp(nages-5) ;
-      incr_dev_tmp(2,4)           = incr_dev_tmp(5) ;
-      wt_pop_tmp_f(1)        = wt_vbg_f(1);
-      wt_pop_tmp_f(2,nages)  = ++wt_vbg_f(1,nages-1) + elem_prod(base_incr_f,mfexp(incr_dev_tmp)) ; // initializes estimates to correct values...
-      report <<i<<" "<<double(i)*growth_alpha<<" "<<wt_pop_tmp_f<<endl;
-    }
-    report << "wt_pop_f"<<endl;
-    report << wt_pop_f<<endl;
-    report << "wt_pop_m"<<endl;
-    report << wt_pop_m<<endl;
-  // This section to write s-rec parameters to input file for projection model
-  // need Rzero, phizero calculated then use alpha and beta
-  if (active(R_logbeta))
-    write_srec();
-  cout<<"Done with phase "<<current_phase()<<" --in report file"<<endl;
-  cout<<wt_pop_mn_f(4,10)<<endl;
-  cout<<wt_fsh_mn_f(4,10)<<endl;
-  report << model_name<<endl;
-  if (last_phase()&&!do_wt_only)
-  {
-  dvariable Ftemp;
-  Ftemp=0.01;
-  dvariable ypr;
-  dvariable yield;
-  dvariable phi;  
-  dvariable R_eq;
-   for (i=1;i<=60;i++) // range of F values to evaluate for Fmsy (0.02 to 0.31-30 steps)
-    {
-     Ftemp=Ftemp+0.01;            //increments F by 0.01 each pass through the loop
-     phi=get_spr(Ftemp);
-     R_eq = -(log(1/(R_alpha*phi)))/(phi*R_beta);   // Ricker formulation of equilibrium recruitment at each F
-     ypr=get_ypr(Ftemp);
-     yield=R_eq*ypr;
-     cout <<" Ftemp= "<<Ftemp<<" r= "<<yield/(R_eq*phi)<<" phi= "<<phi<<" R_eq= "<<R_eq<<" ypr= "<<ypr<<" yield= "<<yield<< endl;
-    }
-  }
-  report << "Estimated_numbers_of_fish year "<<age_vector << endl;
-   for (i=styr;i<=endyr;i++)
-     report << " "<<  i << ", "<< natage_f(i) << natage_m(i)<<endl;
-  report << endl<< "Estimated_F_mortality Fishery Year " << age_vector<< endl;
-   for (k=1;k<=nfsh;k++)
-     for (i=styr;i<=endyr;i++)
-       report << " "<< k <<" "<< i << " "<<F_f(k,i) << " " << F_m(k,i)<<endl;
-   report << endl << "Observed survey values " << endl;
-   for (k=1;k<=nsrv;k++)
-   {
-     int ii=1;
-     report <<endl<< "ObsSurvey "<< k <<"  " <<"predSurvey "<< endl;
-     for (i=styr;i<=endyr;i++)
-     {
-        if (yrs_srv(k,ii)==i)
-        {
-          report << i << ", " << obs_srv(k,ii) << ", " << pred_srv(k,i)<< endl;
-          ii++;
-        }
-        else
-         report << i<< ",NA, "<<pred_srv(k,i)<<endl;
-     }
-  }
-  report << endl<< "Observed_proportion "<<endl;
-  for (k=1;k<=nfsh;k++)
-  {
-    report << "Observed_fishery_age_comp "<< k <<"  "<<endl ;
-    for (i=1;i<=nyrs_fsh_age_c(k);i++)
-      report   << yrs_fsh_age_c(k,i)<< ", " << oac_fsh_c(k,i) << " "<<Eff_N(oac_fsh_c(k,i),eac_fsh_c(k,i))<< endl; 
-		if (last_phase()) 
-    {
-      if (nyrs_fsh_age_c(k) >0)
-      {
-        R_report << "$yrs_fsh_age_c" <<endl;
-        R_report << yrs_fsh_age_c(k) <<endl;
-        R_report << "$eac_fsh_c"<<endl;
-        for (i=1;i<=nyrs_fsh_age_c(k);i++)
-          R_report << eac_fsh_c(k,i) << endl; 
-        R_report << "$oac_fsh_c"<<endl;
-        for (i=1;i<=nyrs_fsh_age_c(k);i++)
-          R_report << oac_fsh_c(k,i) << endl; 
-        R_report << "$effN_fsh_c"<<endl;
-        for (i=1;i<=nyrs_fsh_age_c(k);i++)
-          R_report <<Eff_N(oac_fsh_c(k,i),eac_fsh_c(k,i)) <<" ";
-        R_report <<endl;
-      }
-      if (nyrs_fsh_age_s(k) >0)
-      {
-        R_report << "$yrs_fsh_age_s" <<endl;
-        R_report << yrs_fsh_age_s(k) <<endl;
-        R_report << "$eac_fsh_s"<<endl;
-        for (i=1;i<=nyrs_fsh_age_s(k);i++)
-          R_report << eac_fsh_s(k,i) << endl; 
-        R_report << "$oac_fsh_s"<<endl;
-        for (i=1;i<=nyrs_fsh_age_s(k);i++)
-          R_report << oac_fsh_s(k,i) << endl; 
-        R_report << "$effN_fsh_s"<<endl;
-        for (i=1;i<=nyrs_fsh_age_s(k);i++)
-          R_report <<Eff_N(oac_fsh_s(k,i),eac_fsh_s(k,i)) <<" ";
-        R_report <<endl;
-      }
-    }
-    for (i=1;i<=nyrs_fsh_age_s(k);i++)
-    {
-      report << yrs_fsh_age_s(k,i)<< ", " << oac_fsh_s(k,i) << ", Female/Total: "<< sum(oac_fsh_s(k,i)(1,nages)) 
-             << " "<<Eff_N(oac_fsh_s(k,i),eac_fsh_s(k,i)) 
-             << " "<<mn_age(oac_fsh_s(k,i))
-             << " "<<mn_age(eac_fsh_s(k,i))
-             << " "<<Sd_age(oac_fsh_s(k,i),eac_fsh_s(k,i))
-             << " "<<Eff_N2(oac_fsh_s(k,i),eac_fsh_s(k,i))
-             <<endl;
-    }
-  }
-  report << endl << "Predicted_prop_Fishery "<<endl;
-  for (k=1;k<=nfsh;k++)
-  {
-    report << "Pred_fishery_age_comp "<< k <<"  "<<endl ;
-    for (i=1;i<=nyrs_fsh_age_c(k);i++)
-      report << yrs_fsh_age_c(k,i)<< ", " << eac_fsh_c(k,i) << endl;
-    for (i=1;i<=nyrs_fsh_age_s(k);i++)
-      report << yrs_fsh_age_s(k,i)<< ", " << eac_fsh_s(k,i) << ", Female/Total: "<< sum(eac_fsh_s(k,i)(1,nages)) << endl; 
-  }
-  report << endl<< "Observed_prop_Survey "<<endl;
-  for (k=1;k<=nsrv;k++)
-  {
-    if(last_phase())
-    {
-      if (nyrs_srv_age_c(k) >0)
-      {
-        R_report << "$yrs_srv_age_c" <<endl;
-        R_report << yrs_srv_age_c(k) <<endl;
-        R_report << "$eac_srv_c"<<endl;
-        for (i=1;i<=nyrs_srv_age_c(k);i++)
-          R_report << eac_srv_c(k,i) << endl; 
-        R_report << "$oac_srv_c"<<endl;
-        for (i=1;i<=nyrs_srv_age_c(k);i++)
-          R_report << oac_srv_c(k,i) << endl; 
-        R_report << "$effN_srv_c"<<endl;
-        for (i=1;i<=nyrs_srv_age_c(k);i++)
-          R_report <<Eff_N(oac_srv_c(k,i),eac_srv_c(k,i)) <<" ";
-        R_report <<endl;
-      }
-      if (nyrs_srv_age_s(k) >0)
-      {
-        R_report << "$yrs_srv_age_s" <<endl;
-        R_report << yrs_srv_age_s(k) <<endl;
-        R_report << "$eac_srv_s"<<endl;
-        for (i=1;i<=nyrs_srv_age_s(k);i++)
-          R_report << eac_srv_s(k,i) << endl; 
-        R_report << "$oac_srv_s"<<endl;
-        for (i=1;i<=nyrs_srv_age_s(k);i++)
-          R_report << oac_srv_s(k,i) << endl; 
-        R_report << "$effN_srv_s"<<endl;
-        for (i=1;i<=nyrs_srv_age_s(k);i++)
-          R_report <<Eff_N(oac_srv_s(k,i),eac_srv_s(k,i))<<" ";
-        R_report <<endl;
-      }
-    }
-    report << "Obs_Survey_age_comp "<< k <<"  "<<endl ;
-    for (i=1;i<=nyrs_srv_age_c(k);i++)
-    {
-      report << yrs_srv_age_c(k,i)<< ", " << oac_srv_c(k,i)  << " "<<Eff_N(oac_srv_c(k,i),eac_srv_c(k,i))<< endl; 
-    }
-    for (i=1;i<=nyrs_srv_age_s(k);i++)
-    {
-      report << yrs_srv_age_s(k,i)<< ", " << oac_srv_s(k,i) << ", Female/Total: "<< sum(oac_srv_s(k,i)(1,nages))  << " "<<Eff_N(oac_srv_s(k,i),eac_srv_s(k,i))<< endl; 
-    }
-  }
-  report << endl << "Predicted_prop_Survey "<<endl;
-  for (k=1;k<=nsrv;k++)
-  {
-    report << "Pred_Survey_age_comp "<< k <<"  "<<endl ;
-    for (i=1;i<=nyrs_srv_age_c(k);i++)
-      report << yrs_srv_age_c(k,i)<< ", " << eac_srv_c(k,i) << endl;
-    for (i=1;i<=nyrs_srv_age_s(k);i++)
-      report << yrs_srv_age_s(k,i)<< ", " << eac_srv_s(k,i) << ", Female/Total: "<< sum(eac_srv_s(k,i)(1,nages)) << endl; 
-  }
-  report << endl<< "Observed_catch_biomass " << endl;
-  for (int ifsh=1;ifsh<=nfsh;ifsh++)
-    report << obs_catch(ifsh)(styr,endyr) << endl;
-  report << "predicted_catch_bomass" << endl;
-  for (int ifsh=1;ifsh<=nfsh;ifsh++)
-    report << pred_catch(ifsh) << endl;
-  report << endl << "Estimated_annual_Fishing_mortality "<< endl;
-  for (i=styr; i<endyr;i++)
-  {
-    report << i << " ";
-    for (k=1;k<=nfsh;k++)
-      report<< mean(F_f(k,i)) << " ";
-    report <<Fmort(i)<<endl;
-  }
-  report << endl<<"Selectivity sex fshry_age " << age_vector(1,nages)<<endl;
-  for (k=1;k<=nfsh;k++)
-  {
-  for (i=styr; i<=endyr;i++)
-    report << "Fishery female " << k <<" "<<i<<" "<< sel_fsh_f(k,i) << endl;
-    report<<endl;
-  for (i=styr; i<=endyr;i++)
-    report << "Fishery male "   << k <<" "<<i<<" "<< sel_fsh_m(k,i) << endl;
-    report<<endl;
-  }
-  report << "Partial_F  Female  0      " <<partial_F_f  << endl;
-  report << "Partial_F  Male    0      " <<partial_F_m  << endl;
-  for (k=1;k<=nsrv;k++)
-  {
-    report << "Survey female " << k <<"  " <<sel_srv_f(k) << endl;
-    report << "Survey male   " << k <<"  " <<sel_srv_m(k) << endl;
-  }
-  report << endl<<"Female_spawning_biomass " << endl;
-    for (i=styr;i<=endyr;i++)
-      report <<i<<", "<<SSB(i)<<endl;
-  report << endl<<"Total_biomass " << endl;
-    for (i=styr;i<=endyr;i++)
-      report <<i<<",  "<<TotBiom(i)<<endl;
-  report <<endl<<endl;
-  report <<"F40= " << F40 << endl;
-  report <<"F35= " << F35 << endl;
-  report <<"F30= " << F30 << endl;
-  report <<"Unfished_spawning_biomass_per_recruit " << SB0 << endl;
-  report << "Spawning_biomass_per_recruit_from_F40_harvest_rate " << SBF40<<endl;
-  report << "Spawning_biomass_per_recruit_from_F35_harvest_rate " << SBF35<<endl;
-  report << "Spawning_biomass_per_recruit_from_F30_harvest_rate " << SBF30<<endl;
-  report << "Projected_spawning_biomass " << endl;
-  report << "F40_spawning_biomass " << future_SSB(1) <<endl;
-  report << "F35_spawning_biomass " << future_SSB(2) <<endl;
-  report << "F30_spawning_biomass " << future_SSB(3) <<endl;
-  report << "F=0_spawning_biomass " << future_SSB(4) <<endl;
-  report << "Projected_total_biomass " << endl;
-  report << "F40_total_biomass " << future_TotBiom(1) <<endl;
-  report << "F35_total_biomass " << future_TotBiom(2) <<endl;
-  report << "F30_total_biomass " << future_TotBiom(3) <<endl;
-  report << "F=0_total_biomass " << future_TotBiom(4) <<endl;
-  report << "Projected_catch " << endl;
-  report << "F40_harvest " << future_catch(1) <<endl;
-  report << "F35_harvest " << future_catch(2) <<endl;
-  report << "three-yr-mean_harvest" << future_catch(3) <<endl;
-  report << "F=0_harvest " << " 0 0 0 0 0 0 0 0 0 0 0 " <<endl;
-  report << endl << "Likelihood_Components " << endl;
-  report << "survey_likelihood " << srv_like << endl;
-  report << "catch_likelihood " <<  catch_like << endl;
-  report << "age_likelihood_for_fishery " << age_like_fsh << endl;
-  report << "age_likeihood_for_survey " << age_like_srv << endl;
-  report << "recruitment_likelilhood " << rec_like << endl;
-  report << "selectivity_likelihood " << sel_like << endl;
-  report << "q_Prior " <<q_prior <<endl;
-  report << "m_Prior " <<m_prior <<endl;
-  report << "sigmaR_Prior " <<sigmaR_prior <<endl;
-  report << "F_penalty " << fpen << endl;
-   /*
-  if (phase_env_cov>0)
-  {
-    report << "alpha= " << alpha << endl;
-    report << "beta= " << beta << endl;
-    report << endl<<"Environmental_effect_q " << endl;
-    for (i=1;i<=nyrs_srv(1);i++)
-      for (k=1;k<=n_env_cov(1);k++)
-        report <<yrs_srv(1,i)<<", "<<env_cov(1,k,i)<<", "<<mfexp(-alpha(1)+q_beta(1,k)*env_cov(1,k,i))<<endl;
-  }
-  // if (phase_env_cov>0) report << " survey_q= " << mean(exp(-alpha+q_beta*env_cov(1)))<<endl; else
-   */
-  report << "survey_q = " << mean(q_srv(1))<<endl;
-  report << "M (F M)  = " << natmort_f<<" "<<natmort_m << endl;
-  report << endl << "Ricker_spawner-recruit_estimates" << endl;
-  report << "stock_assessment_model_recruitment_estimates" << endl;
-  report << SAM_recruits << endl;
-  report << "Ricker_model_predicted_recruitment"<<endl;
-  report << SRC_recruits << endl;
-  report << "Ricker_alpha= " << endl;
-  report << R_alpha << endl;
-  report << "Ricker_beta = " << endl;
-  report << R_beta << endl;
-  report << "Estimated_catch_at_age " << endl;
-  report <<"Fishery Year " << age_vector <<endl;
-  for (k=1;k<=nfsh;k++)
-    for (i=styr;i<=endyr;i++)
-      report <<k <<"  " << i << " "<< catage_f(1,i) <<", "<<catage_m(1,i)<< endl;
-  report << "Estimated_stock_recruitment_curve" << endl;
-  report << "Stock recruitment " << endl;
-  dvariable stmp;
-  dvariable maxspawn=max(SSB)*1.2;
-   for (i=0;i<=30;i++)
-   {
-     // SRR_SSB(i) = double(i+.001)*maxspawn/30; 
-     // rechat(i)  = R_alpha*stmp*(mfexp(-R_beta*SRR_SSB(i)));
-     report <<  stmp<<" "<< R_alpha*stmp*(mfexp(-R_beta*stmp))<<endl;  // Ricker model
-   }
-  report << "Estimated_sex_ratio Year Total Mature Age_7+"<< endl;
-   for (i=styr;i<=endyr;i++)
-     report << " "<<  i << ", "<< 
-     sum(natage_f(i))/sum(natage_f(i)+natage_m(i))<<" "<<
-     sum(elem_prod(maturity(i),natage_f(i)))/sum(elem_prod(maturity(i),natage_f(i)+natage_m(i)))<<" "<<
-     sum(natage_f(i)(7,nages))/sum(natage_f(i)(7,nages)+natage_m(i)(7,nages))<<" "<<
-     endl;
-  report << "Fishry_wts_age"<<endl;
-  report << wt_fsh_f <<endl<<endl;
-  report << wt_fsh_m <<endl<<endl;
-  report << "Survey_wts_age"<<endl;
-  report << wt_srv_f <<endl<<endl;
-  report << wt_srv_m <<endl;
-  report << "Increment_deviations"<<endl;
-  report << incr_dev <<endl<<endl;
-  report << "predicted_Observerd_wts"<<endl;
-  report << wt_pred_f       <<endl<<endl;
-  report << wt_obs_f       <<endl<<endl;
-  report << "Wt_Like"<<endl;
-  report << wt_like <<endl<<endl;
-  report << "Age_Incr_component"<<endl;
-  report << age_incr <<endl<<endl;
-  report << "Future_Mean_wt"<<endl;
-  report << "Female_wt_future: " <<wt_pop_fut_f <<endl<<endl;
-  report << "Male_wt_future: "   <<wt_pop_fut_m <<endl<<endl;
-  report << "Female_wt_base: " <<wt_vbg_f <<endl<<endl;
-  report << "Male_wt_base: "   <<wt_vbg_m <<endl<<endl;
-  // exit(1) ;
-  report << "SARA file for Angie Greig" << endl;
-  report << "Yellowfin sole       # stock  " << endl;
-  report << "BSAI       # region     (AI AK BOG BSAI EBS GOA SEO WCWYK)" << endl;
-  report << "2013       # ASSESS_YEAR - year assessment is presented to the SSC" << endl;
-  report << "1a         # TIER  (1a 1b 2a 2b 3a 3b 4 5 6) " << endl;
-  report << "none       # TIER2  if mixed (none 1a 1b 2a 2b 3a 3b 4 5 6)" << endl;
-  report << "full       # UPDATE (new benchmark full partial)" << endl;
-  report << "2          # LIFE_HIST - SAIP ratings (0 1 2 3 4 5)" << endl;
-  report << "3          # ASSES_FREQ - SAIP ratings (0 1 2 3 4 5) " << endl;
-  report << "5          # ASSES_LEV - SAIP ratings (0 1 2 3 4 5)" << endl;
-  report << "5          # CATCH_DAT - SAIP ratings (0 1 2 3 4 5) " << endl;
-  report << "3          # ABUND_DAT - SAIP ratings (0 1 2 3 4 5)" << endl;
-  report << "654300     # Minimum B  Lower 95% confidence interval for spawning biomass in assessment year" << endl;
-  report << "499000     # Maximum B  Upper 95% confidence interval for spawning biomass in assessment year" << endl;
-  report << "366000     # BMSY  is equilibrium spawning biomass at MSY (Tiers 1-2) or 7/8 x B40% (Tier 3)" << endl;
-  report << "ADMB       # MODEL - Required only if NMFS toolbox software used; optional otherwise " << endl;
-  report << "NA         # VERSION - Required only if NMFS toolbox software used; optional otherwise" << endl;
-  report << "2          # number of sexes  if 1 sex=ALL elseif 2 sex=(FEMALE, MALE) " << endl;
-  report << "1          # number of fisheries" << endl;
-  report << "1000000    # multiplier for recruitment, N at age, and survey number (1,1000,1000000)" << endl;
-  report << "1          # recruitment age used by model or size" << endl;
-  report << "1          # age+ or mmCW+ used for biomass estimate" << endl;
-  report << "\"Single age\"        # Fishing mortality type such as \"Single age\" or \"exploitation rate\"" << endl;
-  report << "\"Age model\"         # Fishing mortality source such as \"Model\" or \"(total catch (t))/(survey biomass (t))\"" << endl;
-  report << "\"Age of maximum F\"  # Fishing mortality range such as \"Age of maximum F\"" << endl; 
-  report << "#FISHERYDESC -list of fisheries (ALL TWL LGL POT FIX FOR DOM TWLJAN LGLMAY POTAUG ...)" << endl; 
-  report << "ALL" << endl; 
-  report <<"#FISHERYYEAR - list years used in the model " << endl;
-   for (i=styr;  i<=endyr; i++)
-      report << i << "	";
-      report<<endl;  
-  report<<"#AGE - list of ages used in the model"<<endl;
-   for (i=1; i<=20;i++)
-      report << i << "	";
-      report<<endl;    
-  report <<"#RECRUITMENT - Number of recruits by year " << endl;
-   for (i=styr;  i<=endyr;  i++)
-	   report  << natage_f(i,1)+natage_m(i,1) << "	";
-	   report<<endl;     
-  report <<"#SPAWNBIOMASS - Spawning biomass by year in metric tons " << endl;
-   for (i=styr;  i<=endyr;  i++)
-      report  << SSB(i) << "	";
-      report<<endl;  
-  report <<"#TOTALBIOMASS - Total biomass by year in metric tons " << endl;
-   for (i=styr;  i<=endyr;  i++)
-      report  << TotBiom << "	";
-      report<<endl;
- // cout <<F_f<<endl;
-   report <<"#TOTFSHRYMORT - Fishing mortality rate by year " << endl;
-  	for (i=styr;  i<=endyr;  i++)
-  	   report  << (F_f(1,i,20)+ F_m(1,i,20))/2<< "	";
-  	   report<<endl;
-  report <<"#TOTALCATCH - Total catch by year in metric tons " << endl;
-   for (i=styr;  i<=endyr;  i++)
-      report  << obs_catch(1,i) << "	";
-      report<<endl;
-  report <<"#MATURITY - Maturity ratio by age (females only)" << endl;  
-      report  << maturity(endyr) << endl; 
-  report <<"#SPAWNWT - Average spawning weight (in kg) for ages 8-20"<< endl; 
-      report <<"0.165 0.212 0.259 0.292 327.8 0.361 0.39 0.412 0.429 0.46 0.47 0.49 0.56"<<endl;                              
-      report<<endl;
-  report <<"#NATMORT - Natural mortality rate for females then males"<< endl; 
-  for (i=1;  i<=20;  i++) 
-  report  << 0.12 <<"	";
-  report<< endl;   
-  for (i=1;  i<=20;  i++) 
-  report  << 0.12 <<"	";
-  report<< endl;
-  report << "#N_AT_AGE - Estimated numbers of female (first) then male (second) fish at age " << endl;
-  for (i=styr; i<=endyr;i++)
-    report <<natage_f(i)<< "	";
-    report<<endl;
-  for (i=styr; i<=endyr;i++)
-    report <<natage_m (i)<< "	";
-    report<<endl;
-  report <<"#FSHRY_WT_KG - Fishery weight at age (in kg) females (first) males (second), only one fishery"<< endl;   
-   report <<wt_fsh_f_in(1,endyr)/1000  << "	";
-   report<<endl;         
-   report <<wt_fsh_m_in(1,endyr)/1000  << "	";
-   report<<endl;
-  report << "#SELECTIVITY - Estimated fishery selectivity for females (first) males (second) at age " << endl;
-   report <<" " <<sel_fsh_f(1,endyr);
-   report<<endl;
-   report <<" "  <<sel_fsh_m(1,endyr);
-   report<<endl;
-  report << "#SURVEYDESC"<<endl;
-  report<<"EBS_trawl_survey BS_slope_trawl_survey AI_trawl_survey"<<endl;
-  report<<"SURVEYMULT"<<endl;
-  report<<"1 1 1"<<endl;
-  report << "#EBS_trawl_survey - Bering Sea shelf survey biomass (Year, Obs_biomass, Pred_biomass) " << endl;
-   for (i=1; i<=nsrv;i++)
-     report << yrs_srv(i) << "	";
-     report<<endl;
-   for (i=1; i<=nsrv;i++) 
-     report<< obs_srv(i)<< "	";
-     report<< endl;
-  report<<"#STOCKNOTES"<<endl;
-  report<<"\"SAFE report indicates that this stock was not subjected to overfishing in 2012 and is neither overfished nor approaching a condition of being overfished in 2013.\""<<endl;
-  cout <<"End of report file for phase "<<current_phase()<<endl;
-	// if (last_phase()) ssb_retro << SSB <<endl;
+  save_gradients(gradients);
+  dvar_vector wt_pop_tmp_f(1,nages);
+	int ilike=1;
+	nLogPosterior(ilike) = wt_like(1); ilike++;
+	nLogPosterior(ilike) = wt_like(2); ilike++;
+	nLogPosterior(ilike) = wt_like(3); ilike++;
+	nLogPosterior(ilike) = wt_fut_like; ilike++;
+	nLogPosterior(ilike) = wt_msy_like; ilike++;
+	nLogPosterior(ilike) = init_like  ; ilike++;
+	nLogPosterior(ilike) = srv_like(1);   ilike++;
+	nLogPosterior(ilike) = catch_like ; ilike++;
+	nLogPosterior(ilike) = age_like_fsh(1); ilike++;
+	nLogPosterior(ilike) = age_like_srv(1); ilike++;
+	nLogPosterior(ilike) = rec_like(1); ilike++;
+	nLogPosterior(ilike) = rec_like(2); ilike++;
+	nLogPosterior(ilike) = rec_like(3); ilike++;
+	nLogPosterior(ilike) = rec_like(4); ilike++;
+	nLogPosterior(ilike) = sel_like(1); ilike++;
+	nLogPosterior(ilike) = sel_like(2); ilike++;
+	nLogPosterior(ilike) = q_prior(1)  ; ilike++;
+	nLogPosterior(ilike) = sigmaR_prior; ilike++;
+	nLogPosterior(ilike) = m_prior     ; ilike++;
+	nLogPosterior(ilike) = fpen       ; ilike++;
+  for (int i=0;i<=3;i++)
+  {
+      dvar_vector incr_dev_tmp(2,nages);
+      incr_dev_tmp(5,nages-5)     = growth_alpha * double(i) ;
+      incr_dev_tmp(nages-4,nages) = incr_dev_tmp(nages-5) ;
+      incr_dev_tmp(2,4)           = incr_dev_tmp(5) ;
+      wt_pop_tmp_f(1)        = wt_vbg_f(1);
+      wt_pop_tmp_f(2,nages)  = ++wt_vbg_f(1,nages-1) + elem_prod(base_incr_f,mfexp(incr_dev_tmp)) ; // initializes estimates to correct values...
+      report <<i<<" "<<double(i)*growth_alpha<<" "<<wt_pop_tmp_f<<endl;
+  }
+  report << "wt_pop_f"<<endl;
+  report << wt_pop_f  <<endl;
+  report << "wt_pop_m"<<endl;
+  report << wt_pop_m  <<endl;
+  // This section to write s-rec parameters to input file for projection model
+  // need Rzero, phizero calculated then use alpha and beta
+  // if (active(R_logbeta))
+  write_srec();
+  cout<<"Done with phase "<<current_phase()<<" --in report file"<<endl;
+  cout<<wt_pop_mn_f(4,10)<<endl;
+  cout<<wt_fsh_mn_f(4,10)<<endl;
+  report << model_name<<endl;
+  if (last_phase()&&!do_wt_only)
+  {
+  dvariable Ftemp;
+  Ftemp=0.01;
+  dvariable ypr;
+  dvariable yield;
+  dvariable phi;  
+  dvariable R_eq;
+   for (i=1;i<=60;i++) // range of F values to evaluate for Fmsy (0.02 to 0.31-30 steps)
+    {
+     Ftemp=Ftemp+0.01;            //increments F by 0.01 each pass through the loop
+     phi=get_spr(Ftemp);
+     R_eq = -(log(1/(R_alpha*phi)))/(phi*R_beta);   // Ricker formulation of equilibrium recruitment at each F
+     ypr=get_ypr(Ftemp);
+     yield=R_eq*ypr;
+     cout <<" Ftemp= "<<Ftemp<<" r= "<<yield/(R_eq*phi)<<" phi= "<<phi<<" R_eq= "<<R_eq<<" ypr= "<<ypr<<" yield= "<<yield<< endl;
+    }
+  }
+  report << "Estimated_numbers_of_fish year "<<age_vector << endl;
+   for (i=styr;i<=endyr;i++)
+     report << " "<<  i << ", "<< natage_f(i) << natage_m(i)<<endl;
+  report << endl<< "Estimated_F_mortality Fishery Year " << age_vector<< endl;
+   for (k=1;k<=nfsh;k++)
+     for (i=styr;i<=endyr;i++)
+       report << " "<< k <<" "<< i << " "<<F_f(k,i) << " " << F_m(k,i)<<endl;
+   report << endl << "Observed survey values " << endl;
+   for (k=1;k<=nsrv;k++)
+   {
+     int ii=1;
+     report <<endl<< "ObsSurvey "<< k <<"  " <<"predSurvey "<< endl;
+     for (i=styr;i<=endyr;i++)
+     {
+        if (yrs_srv(k,ii)==i)
+        {
+          report << i << ", " << obs_srv(k,ii) << ", " << pred_srv(k,i)<< endl;
+          ii++;
+        }
+        else
+         report << i<< ",NA, "<<pred_srv(k,i)<<endl;
+     }
+  }
+  report << endl<< "Observed_proportion "<<endl;
+  for (k=1;k<=nfsh;k++)
+  {
+    report << "Observed_fishery_age_comp "<< k <<"  "<<endl ;
+    for (i=1;i<=nyrs_fsh_age_c(k);i++)
+      report   << yrs_fsh_age_c(k,i)<< ", " << oac_fsh_c(k,i) << " "<<Eff_N(oac_fsh_c(k,i),eac_fsh_c(k,i))<< endl; 
+		if (last_phase()) 
+    {
+      if (nyrs_fsh_age_c(k) >0)
+      {
+        R_report << "yrs_fsh_age_c" <<endl;
+        R_report << yrs_fsh_age_c(k) <<endl;
+        R_report << "eac_fsh_c"<<endl;
+        for (i=1;i<=nyrs_fsh_age_c(k);i++)
+          R_report << eac_fsh_c(k,i) << endl; 
+        R_report << "oac_fsh_c"<<endl;
+        for (i=1;i<=nyrs_fsh_age_c(k);i++)
+          R_report << oac_fsh_c(k,i) << endl; 
+        R_report << "effN_fsh_c"<<endl;
+        for (i=1;i<=nyrs_fsh_age_c(k);i++)
+          R_report <<Eff_N(oac_fsh_c(k,i),eac_fsh_c(k,i)) <<" ";
+        R_report <<endl;
+      }
+  
+      if (nyrs_fsh_age_s(k) >0)
+      {
+        R_report << "yrs_fsh_age_s" <<endl;
+        R_report << yrs_fsh_age_s(k) <<endl;
+        R_report << "eac_fsh_s"<<endl;
+        for (i=1;i<=nyrs_fsh_age_s(k);i++)
+          R_report << eac_fsh_s(k,i) << endl; 
+        R_report << "oac_fsh_s"<<endl;
+        for (i=1;i<=nyrs_fsh_age_s(k);i++)
+          R_report << oac_fsh_s(k,i) << endl; 
+        R_report << "#effN_fsh_s"<<endl;
+        for (i=1;i<=nyrs_fsh_age_s(k);i++)
+          R_report <<Eff_N(oac_fsh_s(k,i),eac_fsh_s(k,i)) <<" ";
+        R_report <<endl;
+      }
+    }
+    for (i=1;i<=nyrs_fsh_age_s(k);i++)
+    {
+      report << yrs_fsh_age_s(k,i)<< ", " << oac_fsh_s(k,i) << ", Female/Total: "<< sum(oac_fsh_s(k,i)(1,nages)) 
+             << " "<<Eff_N(oac_fsh_s(k,i),eac_fsh_s(k,i)) 
+             << " "<<mn_age(oac_fsh_s(k,i))
+             << " "<<mn_age(eac_fsh_s(k,i))
+             << " "<<Sd_age(oac_fsh_s(k,i),eac_fsh_s(k,i))
+             << " "<<Eff_N2(oac_fsh_s(k,i),eac_fsh_s(k,i))
+             <<endl;
+    }
+  }
+  report << endl << "Predicted_prop_Fishery "<<endl;
+  for (k=1;k<=nfsh;k++)
+  {
+    report << "Pred_fishery_age_comp "<< k <<"  "<<endl ;
+    for (i=1;i<=nyrs_fsh_age_c(k);i++)
+      report << yrs_fsh_age_c(k,i)<< ", " << eac_fsh_c(k,i) << endl;
+    for (i=1;i<=nyrs_fsh_age_s(k);i++)
+      report << yrs_fsh_age_s(k,i)<< ", " << eac_fsh_s(k,i) << ", Female/Total: "<< sum(eac_fsh_s(k,i)(1,nages)) << endl; 
+  }
+  report << endl<< "Observed_prop_Survey "<<endl;
+  for (k=1;k<=nsrv;k++)
+  {
+    if(last_phase())
+    {
+      if (nyrs_srv_age_c(k) >0)
+      {
+        R_report << "yrs_srv_age_c" <<endl;
+        R_report << yrs_srv_age_c(k) <<endl;
+        R_report << "eac_srv_c"<<endl;
+        for (i=1;i<=nyrs_srv_age_c(k);i++)
+          R_report << eac_srv_c(k,i) << endl; 
+        R_report << "oac_srv_c"<<endl;
+        for (i=1;i<=nyrs_srv_age_c(k);i++)
+          R_report << oac_srv_c(k,i) << endl; 
+        R_report << "effN_srv_c"<<endl;
+        for (i=1;i<=nyrs_srv_age_c(k);i++)
+          R_report <<Eff_N(oac_srv_c(k,i),eac_srv_c(k,i)) <<" ";
+        R_report <<endl;
+      }
+  
+      if (nyrs_srv_age_s(k) >0)
+      {
+        R_report << "yrs_srv_age_s" <<endl;
+        R_report << yrs_srv_age_s(k) <<endl;
+        R_report << "eac_srv_s"<<endl;
+        for (i=1;i<=nyrs_srv_age_s(k);i++)
+          R_report << eac_srv_s(k,i) << endl; 
+        R_report << "oac_srv_s"<<endl;
+        for (i=1;i<=nyrs_srv_age_s(k);i++)
+          R_report << oac_srv_s(k,i) << endl; 
+        R_report << "effN_srv_s"<<endl;
+        for (i=1;i<=nyrs_srv_age_s(k);i++)
+          R_report <<Eff_N(oac_srv_s(k,i),eac_srv_s(k,i))<<" ";
+        R_report <<endl;
+      }
+    }
+    L_report << "Obs_Survey_age_comp "<< k <<"  "<<endl ;
+    for (i=1;i<=nyrs_srv_age_c(k);i++)
+    {
+      L_report << yrs_srv_age_c(k,i)<< ", " << oac_srv_c(k,i)  << " "<<Eff_N(oac_srv_c(k,i),eac_srv_c(k,i))<< endl; 
+    }
+    for (i=1;i<=nyrs_srv_age_s(k);i++)
+    {
+      L_report << yrs_srv_age_s(k,i)<< ", " << oac_srv_s(k,i) << ", Female/Total: "<< sum(oac_srv_s(k,i)(1,nages))  << " "<<Eff_N(oac_srv_s(k,i),eac_srv_s(k,i))<< endl; 
+    }
+  }
+  L_report << endl << "Predicted_prop_Survey "<<endl;
+  for (k=1;k<=nsrv;k++)
+  {
+    L_report << "Pred_Survey_age_comp "<< k <<"  "<<endl ;
+    for (i=1;i<=nyrs_srv_age_c(k);i++)
+      L_report << yrs_srv_age_c(k,i)<< ", " << eac_srv_c(k,i) << endl;
+    for (i=1;i<=nyrs_srv_age_s(k);i++)
+      L_report << yrs_srv_age_s(k,i)<< ", " << eac_srv_s(k,i) << ", Female/Total: "<< sum(eac_srv_s(k,i)(1,nages)) << endl; 
+  }
+      
+  L_report << endl<< "Observed_catch_biomass " << endl;
+  for (int ifsh=1;ifsh<=nfsh;ifsh++)
+    L_report << obs_catch(ifsh)(styr,endyr) << endl;
+  L_report << "predicted_catch_bomass" << endl;
+  for (int ifsh=1;ifsh<=nfsh;ifsh++)
+    L_report << pred_catch(ifsh) << endl;
+  L_report << endl << "Estimated_annual_Fishing_mortality "<< endl;
+  for (i=styr; i<endyr;i++)
+  {
+    L_report << i << " ";
+    for (k=1;k<=nfsh;k++)
+      L_report<< mean(F_f(k,i)) << " ";
+    L_report <<Fmort(i)<<endl;
+  }
+  L_report << endl<<"Selectivity sex fshry_age " << age_vector(1,nages)<<endl;
+  for (k=1;k<=nfsh;k++)
+  {
+  for (i=styr; i<=endyr;i++)
+    L_report << "Fishery female " << k <<" "<<i<<" "<< sel_fsh_f(k,i) << endl;
+    L_report<<endl;
+  for (i=styr; i<=endyr;i++)
+    L_report << "Fishery male "   << k <<" "<<i<<" "<< sel_fsh_m(k,i) << endl;
+    L_report<<endl;
+  }
+  L_report << "Partial_F  Female  0      " <<partial_F_f  << endl;
+  L_report << "Partial_F  Male    0      " <<partial_F_m  << endl;
+  for (k=1;k<=nsrv;k++)
+  {
+    L_report << "Survey female " << k <<"  " <<sel_srv_f(k) << endl;
+    L_report << "Survey male   " << k <<"  " <<sel_srv_m(k) << endl;
+  }
+  L_report << endl<<"Female_spawning_biomass " << endl;
+    for (i=styr;i<=endyr;i++)
+      L_report <<i<<", "<<SSB(i)<<endl;
+  
+  L_report << endl<<"Total_biomass " << endl;
+    for (i=styr;i<=endyr;i++)
+      L_report <<i<<",  "<<TotBiom(i)<<endl;
+  L_report <<endl<<endl;
+  L_report <<"F40= " << F40 << endl;
+  L_report <<"F35= " << F35 << endl;
+  L_report <<"F30= " << F30 << endl;
+  L_report <<"Unfished_spawning_biomass_per_recruit " << SB0 << endl;
+  L_report << "Spawning_biomass_per_recruit_from_F40_harvest_rate " << SBF40<<endl;
+  L_report << "Spawning_biomass_per_recruit_from_F35_harvest_rate " << SBF35<<endl;
+  L_report << "Spawning_biomass_per_recruit_from_F30_harvest_rate " << SBF30<<endl;
+  L_report << "Projected_spawning_biomass " << endl;
+  L_report << "F40_spawning_biomass " << future_SSB(1) <<endl;
+  L_report << "F35_spawning_biomass " << future_SSB(2) <<endl;
+  L_report << "F30_spawning_biomass " << future_SSB(3) <<endl;
+  L_report << "F=0_spawning_biomass " << future_SSB(4) <<endl;
+  L_report << "Projected_total_biomass " << endl;
+  L_report << "F40_total_biomass " << future_TotBiom(1) <<endl;
+  L_report << "F35_total_biomass " << future_TotBiom(2) <<endl;
+  L_report << "F30_total_biomass " << future_TotBiom(3) <<endl;
+  L_report << "F=0_total_biomass " << future_TotBiom(4) <<endl;
+  L_report << "Projected_catch " << endl;
+  L_report << "F40_harvest " << future_catch(1) <<endl;
+  L_report << "F35_harvest " << future_catch(2) <<endl;
+  L_report << "three-yr-mean_harvest" << future_catch(3) <<endl;
+  L_report << "F=0_harvest " << " 0 0 0 0 0 0 0 0 0 0 0 " <<endl;
+  
+  L_report << endl << "Likelihood_Components " << endl;
+  L_report << "survey_likelihood " << srv_like << endl;
+  L_report << "catch_likelihood " <<  catch_like << endl;
+  L_report << "age_likelihood_for_fishery " << age_like_fsh << endl;
+  L_report << "age_likeihood_for_survey " << age_like_srv << endl;
+  L_report << "recruitment_likelilhood " << rec_like << endl;
+  L_report << "selectivity_likelihood " << sel_like << endl;
+  L_report << "q_Prior " <<q_prior <<endl;
+  L_report << "m_Prior " <<m_prior <<endl;
+  L_report << "sigmaR_Prior " <<sigmaR_prior <<endl;
+  L_report << "F_penalty " << fpen << endl;
+  if (phase_env_cov>0)
+  {
+    // L_report << "alpha= " << q_alpha << endl;
+    // L_report << "beta= " << q_beta << endl;
+    // L_report << endl<<"Environmental_effect_q " << endl;
+  // init_ivector n_env_cov(1,nsrv)
+  // !!log_input(n_env_cov);
+  // init_3darray env_cov(1,nsrv,1,n_env_cov,1,nyrs_srv)
+  // !!  for (int j=1;j<=nsrv;j++) for (int k=1;k<=n_env_cov(j);k++) { env_cov(j,k) -= mean(env_cov(j,k)); }
+    // for (i=1;i<=nyrs_srv(1);i++)
+      // for (k=1;k<=n_env_cov(1);k++);
+        // L_report <<yrs_srv(1,i)<<", "<<env_cov(1,k,i)<<", "<<endl;// mfexp(-q_alpha(1)+q_beta(1,k)*env_cov(1,k,i))<<endl;
+  }
+  // if (phase_env_cov>0) L_report << " survey_q= " << mean(exp(-q_alpha+q_beta*env_cov(1)))<<endl; else
+   /*
+   */
+  L_report << "survey_q = " << mean(q_srv(1))<<endl;
+  L_report << "M (F M)  = " << natmort_f<<" "<<natmort_m << endl;
+  L_report << endl << "Ricker_spawner-recruit_estimates" << endl;
+  L_report << "stock_assessment_model_recruitment_estimates" << endl;
+  L_report << SAM_recruits << endl;
+  L_report << "Ricker_model_predicted_recruitment"<<endl;
+  L_report << SRC_recruits << endl;
+  L_report << "Ricker_alpha= " << endl;
+  L_report << R_alpha << endl;
+  L_report << "Ricker_beta = " << endl;
+  L_report << R_beta << endl;
+  L_report << "Estimated_catch_at_age " << endl;
+  L_report <<"Fishery Year " << age_vector <<endl;
+  for (k=1;k<=nfsh;k++)
+    for (i=styr;i<=endyr;i++)
+      L_report <<k <<"  " << i << " "<< catage_f(1,i) <<", "<<catage_m(1,i)<< endl;
+  L_report << "Estimated_stock_recruitment_curve" << endl;
+  L_report << "Stock recruitment " << endl;
+  dvariable stmp;
+  dvariable maxspawn=max(SSB)*1.2;
+   for (i=0;i<=30;i++)
+   {
+     // SRR_SSB(i) = double(i+.001)*maxspawn/30; 
+     // rechat(i)  = R_alpha*stmp*(mfexp(-R_beta*SRR_SSB(i)));
+     L_report <<  stmp<<" "<< R_alpha*stmp*(mfexp(-R_beta*stmp))<<endl;  // Ricker model
+   }
+  L_report << "Estimated_sex_ratio Year Total Mature Age_7+"<< endl;
+   for (i=styr;i<=endyr;i++)
+     L_report << " "<<  i << ", "<< 
+     sum(natage_f(i))/sum(natage_f(i)+natage_m(i))<<" "<<
+     sum(elem_prod(maturity(i),natage_f(i)))/sum(elem_prod(maturity(i),natage_f(i)+natage_m(i)))<<" "<<
+     sum(natage_f(i)(7,nages))/sum(natage_f(i)(7,nages)+natage_m(i)(7,nages))<<" "<<
+     endl;
+  L_report << "Fishry_wts_age"<<endl;
+  L_report << wt_fsh_f <<endl<<endl;
+  L_report << wt_fsh_m <<endl<<endl;
+  L_report << "Survey_wts_age"<<endl;
+  L_report << wt_srv_f <<endl<<endl;
+  L_report << wt_srv_m <<endl;
+  L_report << "Increment_deviations"<<endl;
+  L_report << incr_dev <<endl<<endl;
+  L_report << "predicted_Observerd_wts"<<endl;
+  L_report << wt_pred_f       <<endl<<endl;
+  L_report << wt_obs_f       <<endl<<endl;
+  L_report << "Wt_Like"<<endl;
+  L_report << wt_like <<endl<<endl;
+  L_report << "Age_Incr_component"<<endl;
+  L_report << age_incr <<endl<<endl;
+  L_report << "Future_Mean_wt"<<endl;
+  L_report << "Female_wt_future: " <<wt_pop_fut_f <<endl<<endl;
+  L_report << "Male_wt_future: "   <<wt_pop_fut_m <<endl<<endl;
+  L_report << "Female_wt_base: " <<wt_vbg_f <<endl<<endl;
+  L_report << "Male_wt_base: "   <<wt_vbg_m <<endl<<endl;
+  // exit(1) ;
+  
+  L_report << "SARA file for Angie Greig" << endl;
+  L_report << "xxxlowfin sole       # stock  " << endl;
+  L_report << "BSAI       # region     (AI AK BOG BSAI EBS GOA SEO WCWYK)" << endl;
+  L_report << "xxxx       # ASSESS_YEAR - year assessment is presented to the SSC" << endl;
+  L_report << "1a         # TIER  (1a 1b 2a 2b 3a 3b 4 5 6) " << endl;
+  L_report << "none       # TIER2  if mixed (none 1a 1b 2a 2b 3a 3b 4 5 6)" << endl;
+  L_report << "full       # UPDATE (new benchmark full partial)" << endl;
+  L_report << "2          # LIFE_HIST - SAIP ratings (0 1 2 3 4 5)" << endl;
+  L_report << "3          # ASSES_FREQ - SAIP ratings (0 1 2 3 4 5) " << endl;
+  L_report << "5          # ASSES_LEV - SAIP ratings (0 1 2 3 4 5)" << endl;
+  L_report << "5          # CATCH_DAT - SAIP ratings (0 1 2 3 4 5) " << endl;
+  L_report << "3          # ABUND_DAT - SAIP ratings (0 1 2 3 4 5)" << endl;
+  L_report << "xxxxx0     # Minimum B  Lower 95% confidence interval for spawning biomass in assessment year" << endl;
+  L_report << "xxxxx0     # Maximum B  Upper 95% confidence interval for spawning biomass in assessment year" << endl;
+  L_report << "xxxxx0     # BMSY  is equilibrium spawning biomass at MSY (Tiers 1-2) or 7/8 x B40% (Tier 3)" << endl;
+  L_report << "ADMB       # MODEL - Required only if NMFS toolbox software used; optional otherwise " << endl;
+  L_report << "NA         # VERSION - Required only if NMFS toolbox software used; optional otherwise" << endl;
+  L_report << "2          # number of sexes  if 1 sex=ALL elseif 2 sex=(FEMALE, MALE) " << endl;
+  L_report << "1          # number of fisheries" << endl;
+  L_report << "1000000    # multiplier for recruitment, N at age, and survey number (1,1000,1000000)" << endl;
+  L_report << "1          # recruitment age used by model or size" << endl;
+  L_report << "1          # age+ or mmCW+ used for biomass estimate" << endl;
+  L_report << "\"Single age\"        # Fishing mortality type such as \"Single age\" or \"exploitation rate\"" << endl;
+  L_report << "\"Age model\"         # Fishing mortality source such as \"Model\" or \"(total catch (t))/(survey biomass (t))\"" << endl;
+  L_report << "\"Age of maximum F\"  # Fishing mortality range such as \"Age of maximum F\"" << endl; 
+  L_report << "#FISHERYDESC -list of fisheries (ALL TWL LGL POT FIX FOR DOM TWLJAN LGLMAY POTAUG ...)" << endl; 
+  L_report << "ALL" << endl; 
+  
+  L_report <<"#FISHERYYEAR - list years used in the model " << endl;
+   for (i=styr;  i<=endyr; i++)
+      L_report << i << "	";
+      L_report<<endl;  
+  L_report<<"#AGE - list of ages used in the model"<<endl;
+   for (i=1; i<=20;i++)
+      L_report << i << "	";
+      L_report<<endl;    
+  L_report <<"#RECRUITMENT - Number of recruits by year " << endl;
+   for (i=styr;  i<=endyr;  i++)
+	   L_report  << natage_f(i,1)+natage_m(i,1) << "	";
+	   L_report<<endl;     
+	
+  L_report <<"#SPAWNBIOMASS - Spawning biomass by year in metric tons " << endl;
+   for (i=styr;  i<=endyr;  i++)
+      L_report  << SSB(i) << "	";
+      L_report<<endl;  
+  L_report <<"#TOTALBIOMASS - Total biomass by year in metric tons " << endl;
+   for (i=styr;  i<=endyr;  i++)
+      L_report  << TotBiom << "	";
+      L_report<<endl;
+ // cout <<F_f<<endl;
+ 	
+   L_report <<"#TOTFSHRYMORT - Fishing mortality rate by year " << endl;
+  	for (i=styr;  i<=endyr;  i++)
+  	   L_report  << (F_f(1,i,20)+ F_m(1,i,20))/2<< "	";
+  	   L_report<<endl;
+	  
+  L_report <<"#TOTALCATCH - Total catch by year in metric tons " << endl;
+   for (i=styr;  i<=endyr;  i++)
+      L_report  << obs_catch(1,i) << "	";
+      L_report<<endl;
+  L_report <<"#MATURITY - Maturity ratio by age (females only)" << endl;  
+      L_report  << maturity(endyr) << endl; 
+  L_report <<"#SPAWNWT - Average spawning weight (in kg) for ages 8-20"<< endl; 
+      L_report <<"0.165 0.212 0.259 0.292 327.8 0.361 0.39 0.412 0.429 0.46 0.47 0.49 0.56"<<endl;                              
+      L_report<<endl;
+                    
+  L_report <<"#NATMORT - Natural mortality rate for females then males"<< endl; 
+  for (i=1;  i<=20;  i++) 
+  L_report  << 0.12 <<"	";
+  L_report<< endl;   
+  for (i=1;  i<=20;  i++) 
+  L_report  << 0.12 <<"	";
+  L_report<< endl;
+  
+  L_report << "#N_AT_AGE - Estimated numbers of female (first) then male (second) fish at age " << endl;
+  for (i=styr; i<=endyr;i++)
+    L_report <<natage_f(i)<< "	";
+    L_report<<endl;
+  for (i=styr; i<=endyr;i++)
+    L_report <<natage_m (i)<< "	";
+    L_report<<endl;
+  
+  L_report <<"#FSHRY_WT_KG - Fishery weight at age (in kg) females (first) males (second), only one fishery"<< endl;   
+   L_report <<wt_fsh_f_in(1,endyr)/1000  << "	";
+   L_report<<endl;         
+ 
+   L_report <<wt_fsh_m_in(1,endyr)/1000  << "	";
+   L_report<<endl;
+  L_report << "#SELECTIVITY - Estimated fishery selectivity for females (first) males (second) at age " << endl;
+   L_report <<" " <<sel_fsh_f(1,endyr);
+   L_report<<endl;
+   L_report <<" "  <<sel_fsh_m(1,endyr);
+   L_report<<endl;
+  L_report << "#SURVEYDESC"<<endl;
+  L_report<<"EBS_trawl_survey BS_slope_trawl_survey AI_trawl_survey"<<endl;
+  L_report<<"SURVEYMULT"<<endl;
+  L_report<<"1 1 1"<<endl;
+ 
+  L_report << "#EBS_trawl_survey - Bering Sea shelf survey biomass (Year, Obs_biomass, Pred_biomass) " << endl;
+   for (i=1; i<=nsrv;i++)
+     L_report << yrs_srv(i) << "	";
+     L_report<<endl;
+   for (i=1; i<=nsrv;i++) 
+     L_report<< obs_srv(i)<< "	";
+     L_report<< endl;
+  L_report<<"#STOCKNOTES"<<endl;
+  L_report<<"\"SAFE report indicates that this stock was not subjected to overfishing in 2012 and is neither overfished nor approaching a condition of being overfished in 2013.\""<<endl;
+  cout <<"End of report file for phase "<<current_phase()<<endl;
+	// if (last_phase()) ssb_retro << SSB <<endl;
+ 
 }
 
 void model_parameters::between_phases_calculations(void)
 {
-  // Set the msy selectivity to something reasonable???
-  log_msy_sel_f = log_sel_fsh_f(1,endyr-2);
-  log_msy_sel_m = log_sel_fsh_m(1,endyr-2);
+  // Set the msy selectivity to something reasonable???
+  log_msy_sel_f = log_sel_fsh_f(1,endyr-2);
+  log_msy_sel_m = log_sel_fsh_m(1,endyr-2);
 }
 
 void model_parameters::set_runtime(void)
@@ -2472,893 +2646,583 @@ void model_parameters::set_runtime(void)
 
 double model_parameters::mn_age(const dvar_vector& pobs)
 {
-  int lb1 = pobs.indexmin();
-  int ub1 = pobs.indexmax();
-  dvector av = age_vector(lb1,ub1)  ;
-  double mobs = value(pobs*av);
-  return mobs;
+  int lb1 = pobs.indexmin();
+  int ub1 = pobs.indexmax();
+  dvector av = age_vector(lb1,ub1)  ;
+  double mobs = value(pobs*av);
+  return mobs;
 }
 
 double model_parameters::Sd_age(const dvar_vector& pobs, const dvar_vector& phat)
 {
-  int lb1 = pobs.indexmin();
-  int ub1 = pobs.indexmax();
-  dvector av = age_vector(lb1,ub1)  ;
-  double mobs = value(pobs*av);
-  double stmp = value(sqrt(elem_prod(av,av)*pobs - mobs*mobs));
-  return stmp;
+  int lb1 = pobs.indexmin();
+  int ub1 = pobs.indexmax();
+  dvector av = age_vector(lb1,ub1)  ;
+  double mobs = value(pobs*av);
+  double stmp = value(sqrt(elem_prod(av,av)*pobs - mobs*mobs));
+  return stmp;
 }
 
 double model_parameters::Eff_N_adj(const double, const dvar_vector& pobs, const dvar_vector& phat)
 {
-  int lb1 = pobs.indexmin();
-  int ub1 = pobs.indexmax();
-  dvector av = age_vector(lb1,ub1)  ;
-  double mobs = value(pobs*av);
-  double mhat = value(phat*av );
-  double rtmp = mobs-mhat;
-  double stmp = value(sqrt(elem_prod(av,av)*pobs - mobs*mobs));
-  return square(stmp)/square(rtmp);
+  int lb1 = pobs.indexmin();
+  int ub1 = pobs.indexmax();
+  dvector av = age_vector(lb1,ub1)  ;
+  double mobs = value(pobs*av);
+  double mhat = value(phat*av );
+  double rtmp = mobs-mhat;
+  double stmp = value(sqrt(elem_prod(av,av)*pobs - mobs*mobs));
+  return square(stmp)/square(rtmp);
 }
 
 double model_parameters::Eff_N2(const dvar_vector& pobs, const dvar_vector& phat)
 {
-  int lb1 = pobs.indexmin();
-  int ub1 = pobs.indexmax();
-  dvector av = age_vector(lb1,ub1)  ;
-  double mobs = value(pobs*av);
-  double mhat = value(phat*av );
-  double rtmp = mobs-mhat;
-  double stmp = value(sqrt(elem_prod(av,av)*pobs - mobs*mobs));
-  return square(stmp)/square(rtmp);
+  int lb1 = pobs.indexmin();
+  int ub1 = pobs.indexmax();
+  dvector av = age_vector(lb1,ub1)  ;
+  double mobs = value(pobs*av);
+  double mhat = value(phat*av );
+  double rtmp = mobs-mhat;
+  double stmp = value(sqrt(elem_prod(av,av)*pobs - mobs*mobs));
+  return square(stmp)/square(rtmp);
 }
 
 double model_parameters::Eff_N(const dvar_vector& pobs, const dvar_vector& phat)
 {
-  dvar_vector rtmp = elem_div((pobs-phat),sqrt(elem_prod(phat,(1-phat))));
-  double vtmp;
-  vtmp = value(norm2(rtmp)/size_count(rtmp));
-  return 1/vtmp;
+  dvar_vector rtmp = elem_div((pobs-phat),sqrt(elem_prod(phat,(1-phat))));
+  double vtmp;
+  vtmp = value(norm2(rtmp)/size_count(rtmp));
+  return 1/vtmp;
 }
 
 dvariable model_parameters::SolveF2(const dvar_vector& N_tmp_f, dvar_vector& N_tmp_m, double  TACin)
 {
-  dvariable dd = 10.;
-  dvariable cc = TACin;
-  dvar_vector wttmp_f   = wt_pop_fut_f;
-  dvar_vector wttmp_m   = wt_pop_fut_m;
-  dvariable btmp =  N_tmp_f * wttmp_f ;
-  dvariable ftmp;
-  ftmp = TACin/btmp;
-  dvar_vector Fatmp_f = ftmp * partial_F_f;
-  dvar_vector Fatmp_m = ftmp * partial_F_m;
-  dvar_vector Z_tmp_f   = Fatmp_f + natmort_f;
-  dvar_vector Z_tmp_m   = Fatmp_m + natmort_m;
-  dvar_vector S_tmp_f   = exp(-Z_tmp_f);
-  dvar_vector S_tmp_m   = exp(-Z_tmp_m);
-  int icount;
-  icount=0;
-  while (dd > 1e-5)
-  {
-    icount++;
-    ftmp   += (TACin-cc) / btmp;
-    Fatmp_f = ftmp * partial_F_f;
-    Z_tmp_f   = Fatmp_f + natmort_f;
-    S_tmp_f   = mfexp( -Z_tmp_f );
-    Fatmp_m = ftmp * partial_F_m;
-    Z_tmp_m   = Fatmp_m + natmort_m;
-    S_tmp_m   = mfexp( -Z_tmp_m );
-    cc  = (wttmp_f * elem_prod(elem_div(Fatmp_f,  Z_tmp_f),elem_prod(1.-S_tmp_f,N_tmp_f))); // Catch equation (vectors)
-    cc += (wttmp_m * elem_prod(elem_div(Fatmp_m,  Z_tmp_m),elem_prod(1.-S_tmp_m,N_tmp_m))); // Catch equation (vectors)
-    dd = cc / TACin - 1.;
-    //cout << ispp<<" "<< ftmp << " "<< cc << " "<<TACin<<endl; //cout << sel_F << endl << sel_M << endl << endl; //cout << Fratsel_F << endl << Fratsel_M << endl; //exit(1);
-    if (dd<0.) dd *= -1.;
-    // cout<<"Ftmp "<<cc<<" "<< ftmp<<endl;
-    if (icount>100) dd=1e-6;
-  }
-  return(ftmp);
-  /* FUNCTION dvariable SolveF2(const dvar_vector& N_tmp, double  TACin)
-  dvariable dd = 10.;
-  dvariable cc = TACin;
-  dvar_vector wttmp   = wt_pop_fut_f;
-  dvariable btmp =  N_tmp * wttmp ;
-  dvariable ftmp;
-  ftmp = TACin/btmp;
-  dvar_vector Fatmp   = ftmp * partial_F;
-  dvar_vector Z_tmp    = Fatmp+ natmort;
-  dvar_vector S_tmp = exp(-Z_tmp);
-  int icount;
-  icount=0;
-  while (dd > 1e-5)
-  {
-    icount++;
-    ftmp += (TACin-cc) / btmp;
-    Fatmp = ftmp * partial_F;
-    Z_tmp = Fatmp + natmort;
-    S_tmp = mfexp( -Z_tmp );
-    cc = (wttmp * elem_prod(elem_div(Fatmp,  Z_tmp),elem_prod(1.-S_tmp,N_tmp))); // Catch equation (vectors)
-    dd = cc / TACin - 1.;
-    //cout << ispp<<" "<< ftmp << " "<< cc << " "<<TACin<<endl; //cout << sel_F << endl << sel_M << endl << endl; //cout << Fratsel_F << endl << Fratsel_M << endl; //exit(1);
-    if (dd<0.) dd *= -1.;
-    // cout<<"Ftmp "<<cc<<" "<< ftmp<<endl;
-    if (icount>100) dd=1e-6;
-  }
-  return(ftmp);
-  */
+  dvariable dd = 10.;
+  dvariable cc = TACin;
+  dvar_vector wttmp_f   = wt_pop_fut_f;
+  dvar_vector wttmp_m   = wt_pop_fut_m;
+  dvariable btmp =  N_tmp_f * wttmp_f ;
+  dvariable ftmp;
+  ftmp = TACin/btmp;
+  dvar_vector Fatmp_f = ftmp * partial_F_f;
+  dvar_vector Fatmp_m = ftmp * partial_F_m;
+  dvar_vector Z_tmp_f   = Fatmp_f + natmort_f;
+  dvar_vector Z_tmp_m   = Fatmp_m + natmort_m;
+  dvar_vector S_tmp_f   = exp(-Z_tmp_f);
+  dvar_vector S_tmp_m   = exp(-Z_tmp_m);
+  int icount;
+  icount=0;
+  while (dd > 1e-5)
+  {
+    icount++;
+    ftmp   += (TACin-cc) / btmp;
+    Fatmp_f = ftmp * partial_F_f;
+    Z_tmp_f   = Fatmp_f + natmort_f;
+    S_tmp_f   = mfexp( -Z_tmp_f );
+    Fatmp_m = ftmp * partial_F_m;
+    Z_tmp_m   = Fatmp_m + natmort_m;
+    S_tmp_m   = mfexp( -Z_tmp_m );
+    cc  = (wttmp_f * elem_prod(elem_div(Fatmp_f,  Z_tmp_f),elem_prod(1.-S_tmp_f,N_tmp_f))); // Catch equation (vectors)
+    cc += (wttmp_m * elem_prod(elem_div(Fatmp_m,  Z_tmp_m),elem_prod(1.-S_tmp_m,N_tmp_m))); // Catch equation (vectors)
+    dd = cc / TACin - 1.;
+    //cout << ispp<<" "<< ftmp << " "<< cc << " "<<TACin<<endl; //cout << sel_F << endl << sel_M << endl << endl; //cout << Fratsel_F << endl << Fratsel_M << endl; //exit(1);
+    if (dd<0.) dd *= -1.;
+    // cout<<"Ftmp "<<cc<<" "<< ftmp<<endl;
+    if (icount>100) dd=1e-6;
+  }
+  return(ftmp);
+  /* FUNCTION dvariable SolveF2(const dvar_vector& N_tmp, double  TACin)
+  dvariable dd = 10.;
+  dvariable cc = TACin;
+  dvar_vector wttmp   = wt_pop_fut_f;
+  dvariable btmp =  N_tmp * wttmp ;
+  dvariable ftmp;
+  ftmp = TACin/btmp;
+  dvar_vector Fatmp   = ftmp * partial_F;
+  dvar_vector Z_tmp    = Fatmp+ natmort;
+  dvar_vector S_tmp = exp(-Z_tmp);
+  int icount;
+  icount=0;
+  while (dd > 1e-5)
+  {
+    icount++;
+    ftmp += (TACin-cc) / btmp;
+    Fatmp = ftmp * partial_F;
+    Z_tmp = Fatmp + natmort;
+    S_tmp = mfexp( -Z_tmp );
+    cc = (wttmp * elem_prod(elem_div(Fatmp,  Z_tmp),elem_prod(1.-S_tmp,N_tmp))); // Catch equation (vectors)
+    dd = cc / TACin - 1.;
+    //cout << ispp<<" "<< ftmp << " "<< cc << " "<<TACin<<endl; //cout << sel_F << endl << sel_M << endl << endl; //cout << Fratsel_F << endl << Fratsel_M << endl; //exit(1);
+    if (dd<0.) dd *= -1.;
+    // cout<<"Ftmp "<<cc<<" "<< ftmp<<endl;
+    if (icount>100) dd=1e-6;
+  }
+  return(ftmp);
+  */
+  
 }
 
 void model_parameters::Write_sd(void)
 {
- ofstream sdreport("extra_sd.rep");
- sdreport << "Year HM_Fmsyr AM_Fmsyr GM_Biom Catch_Assump ABC_HM OFL_AM Bmsy SSB Adjust "<<endl;
- dvariable hm_f = exp(logFmsyr - logFmsyr.sd*logFmsyr.sd /2.);
- dvariable am_f = exp(logFmsyr + logFmsyr.sd*logFmsyr.sd /2.);
- int m = 5; // the projection for Tier 1 stuff
- for (i = styr_fut;i<=endyr_fut;i++)
- {
-   dvariable cv_b = ABC_biom.sd(i)/ABC_biom(i);
-   dvariable gm_b = exp(log(ABC_biom(i))-(cv_b*cv_b)/2.);
-   if(future_SSB(m,i) < Bmsy)
-     adj_1 = value((future_SSB(m,i)/Bmsy - 0.05)/(1.-0.05));
-   sdreport << i                 <<" "<<
-	         hm_f                  <<" "<<
-	         am_f                  <<" "<<
-	         gm_b                  <<" "<<
-	         yr1_futcat            <<" "<<
-           gm_b  * hm_f * adj_1  <<" "<<
-           gm_b  * am_f * adj_1  <<" "<<
-           Bmsy                  <<" "<< 
-           future_SSB(m,i)       <<" "<< 
-           adj_1                 <<" "<< endl;
- }
- /*
-   sdreport <<"HM_F "
-            << hm_f << " "<<hm_f<<endl 
-            <<"AM_F "
-            << am_f << " "<<am_f<<endl 
-            <<"GM_6+Biom "
-            << gm_b << " "<<gm_b2<<endl 
-            <<"Catch_assumed " 
-            // << obs_catch(1,endyr)<<" "<<mean(obs_catch(1)(endyr-3,endyr)) <<endl
-            << yr1_futcat <<" "<< yr2_futcat <<endl
-            <<"ABC " 
-            << gm_b  * hm_f * adj_1         << " " 
-            << gm_b2 * hm_f * adj_1         << endl
-            <<"OFL " 
-            << gm_b  * am_f * adj_1         << " " 
-            << gm_b2 * am_f * adj_2         << endl
-            <<"SSB " 
-            << SSB_1                        << " " 
-            << SSB_2                        << endl
-            <<"Applied_Adjustments " 
-            <<                adj_1         << " " 
-            <<                adj_2         << " " <<endl
-            <<"Maturity_used "              <<endl
-            << maturity(endyr)              <<" "<<endl
-            << "wt "<<wt_pop_fut_f          <<endl ;
- */
-  sdreport.close();
-  // From AMAK 
- /* FUNCTION Oper_Model
- // Initialize things used here only
-  // Calc_Dependent_Vars();
-  int nsims;
-  ifstream sim_in("nsims.dat");
-  sim_in >> nsims; sim_in.close();
-  dvector ran_srv_vect(1,nsrv);
-  ofstream SaveOM("Om_Out.dat",ios::app);
-  double C_tmp;
-  dvariable Fnow;
-  dvariable meanrec;
-  meanrec=mean(recruits);
-  dvector new_srv(1,nsrv);
-  new_srv.initialize();
-  dvariable mean5plus;
-  mean5plus.initialize();
-  for (i=1975;i<=1999;i++)
-    mean5plus += natage(i)(5,nages)*wt_fsh(1,i)(5,nages);
-  mean5plus /= 25.;
-  system("cls"); cout<<"Number of replicates: "<<endl;
-  // Initialize recruitment in first year
-  nage_future(styr_fut,1) = meanrec;
-  nage_future(styr_fut)(2,nages)              = ++elem_prod(natage(endyr)(1,nages-1),S(endyr)(1,nages-1));
-  nage_future(styr_fut,nages)                += natage(endyr,nages)*S(endyr,nages);
-  for (int isim=1;isim<=nsims;isim++)
-  {
-    cout<<isim<<" ";
-    // Copy file to get mean for Mgt Strategies
-    system("init_stuff.bat");
-    for (i=styr_fut;i<=endyr_fut;i++)
-    {
-      // Some unit normals...
-      ran_srv_vect.fill_randn(rng);
-      // Create new survey observations
-      for (k = 1 ; k<= nsrv ; k++)
-        new_srv(k) = mfexp(ran_srv_vect(k)*.2)*value(nage_future(i)*q_srv(k)*sel_srv(k,endyr)); // use value function since converts to a double
-      // Append new survey observation to datafile
-      ofstream srv_out("NewSrv.dat",ios::app);
-      srv_out <<i<<" "<< new_srv<<endl; srv_out.close();
-      system("ComputeTAC.bat"); // commandline function to get TAC (catchnext.dat)
-      // Now read in TAC (actual catch)
-      ifstream CatchNext("CatchNext.dat");
-      CatchNext >> C_tmp; CatchNext.close();
-      Fnow = SolveF2(endyr,nage_future(i), C_tmp);
-      F_future(1,i) = sel_fsh(1,endyr) * Fnow;
-      Z_future(i)   = F_future(1,i) + natmort;
-      S_future(i)   = mfexp(-Z_future(i));
-      // nage_future(i,1)  = SRecruit( Sp_Biom_future(i-rec_age) ) * mfexp(rec_dev_future(i)) ;     
-      nage_future(i,1)  = meanrec;
-      Sp_Biom_future(i) = wt_mature * elem_prod(nage_future(i),pow(S_future(i),spmo_frac)) ;
-      // Now graduate for the next year....
-      if (i<endyr_fut)
-      {
-        nage_future(i+1)(2,nages) = ++elem_prod(nage_future(i)(1,nages-1),S_future(i)(1,nages-1));
-        nage_future(i+1,nages)   += nage_future(i,nages)*S_future(i,nages);
-      }
-      catage_future(i) = 0.; 
-      for (k = 1 ; k<= nfsh ; k++)
-        catage_future(i) += elem_prod(nage_future(i) , elem_prod(F_future(k,i) , elem_div( ( 1.- S_future(i) ) , Z_future(i))));
-      SaveOM << model_name       <<
-        " "  << isim             <<
-        " "  << i                <<
-        " "  << Fnow             <<
-        " "  << nage_future(i)(5,nages)*wt_fsh(1,endyr)(5,nages)/mean5plus <<
-        " "  << nage_future(i)(5,nages)*wt_fsh(1,endyr)(5,nages)<<
-        " "  << Sp_Biom_future(i)<<
-        " "  << catage_future(i)*wt_fsh(1,endyr)<<
-        " "  << nage_future(i)<<
-        " "  << F_future(1,i)<<
-      endl;
-    }
-  }
-  SaveOM.close  init_int styr
-  */
-  WriteData( endyr_in);
-  WriteData(nages);
-  WriteData( a_lw_f);
-  WriteData( b_lw_f);
-  WriteData( a_lw_m);
-  WriteData( b_lw_m);
-  WriteData( nfsh  );                                      //Number of fisheries
-  WriteData( obs_catch);
-  WriteData( nyrs_fsh_age_c);
-  WriteData( nyrs_fsh_age_s);
-  WriteData( yrs_fsh_age_c);
-  WriteData( yrs_fsh_age_s);
-  WriteData( oac_fsh_c);
-  WriteData( oac_fsh_s);
-  WriteData( wt_fsh_in);
-  WriteData( nsmpl_fsh_c);
-  WriteData( nsmpl_fsh_s);
-  WriteData( nsrv  );
-  WriteData( nyrs_srv);
-  WriteData( yrs_srv);
-  WriteData( mo_srv);
-  WriteData( obs_srv);
-  WriteData( obs_se_srv);
-  WriteData( nyrs_srv_age_c);
-  WriteData( nyrs_srv_age_s);
-  WriteData( yrs_srv_age_c);
-  WriteData( yrs_srv_age_s);
-  WriteData( nsmpl_srv_c);
-  WriteData( nsmpl_srv_s);
-  WriteData( oac_srv_c);
-  WriteData( oac_srv_s);
-  WriteData( wt_srv_f_in);
-  WriteData( wt_srv_m_in);
-  WriteData(  wt_pop_f_in); 
-  WriteData(  wt_pop_m_in); 
-  WriteData( maturity);
-  WriteData( init_age_comp);
-  WriteData( n_env_cov);
-  WriteData( env_cov);
-  WriteData( spawnmo);
-  WriteData( srv_mo); 
-  WriteData( n_wts);
-  WriteData( growth_cov);
+ int m = 5; // the projection for Tier 1 stuff
+ dvariable hm_f = exp(logFmsyr - logFmsyr.sd*logFmsyr.sd /2.);
+ dvariable am_f = exp(logFmsyr + logFmsyr.sd*logFmsyr.sd /2.);
+ ofstream ABCreport("future_ABC.rep");
+ for (i = styr_fut;i<=endyr_fut;i++)
+ {
+   dvariable cv_b = ABC_biom.sd(i)/ABC_biom(i);
+   dvariable gm_b = exp(log(ABC_biom(i))-(cv_b*cv_b)/2.);
+   if(future_SSB(m,i) < Bmsy)
+     adj_1 = value((future_SSB(m,i)/Bmsy - 0.05)/(1.-0.05));
+   ABCreport <<        gm_b  * hm_f * adj_1  <<" "<< endl;
+ }
+ ABCreport.close();
+ ofstream ABC_OFL("ABC_OFL.rep");
+ ABC_OFL << "Year HM_Fmsyr AM_Fmsyr GM_Biom Catch_Assump ABC_HM OFL_AM Bmsy SSB Adjust CV_Biom CV_SSB ABC_T3 OFL_T3"<<endl;
+ for (i = styr_fut;i<=endyr_fut;i++)
+ {
+   dvariable cv_ssb = future_SSB.sd(m,i)/future_SSB(m,i);
+   dvariable cv_b   = ABC_biom.sd(i)/ABC_biom(i);
+   dvariable gm_b   = exp(log(ABC_biom(i))-(cv_b*cv_b)/2.);
+   if(future_SSB(m,i) < Bmsy)
+     adj_1 = value((future_SSB(m,i)/Bmsy - 0.05)/(1.-0.05));
+   ABC_OFL << i                 <<" "<<
+	         hm_f                  <<" "<<
+	         am_f                  <<" "<<
+	         gm_b                  <<" "<<
+	         trans(future_ABC)(i)  <<" "<<
+           gm_b  * hm_f * adj_1  <<" "<<
+           gm_b  * am_f * adj_1  <<" "<<
+           Bmsy                  <<" "<< 
+           future_SSB(m,i)       <<" "<< 
+           adj_1                 <<" "<< 
+           cv_b                  <<" "<< 
+           cv_ssb                <<" "<< 
+           future_catch(1,i)     <<" "<<
+           future_catch(2,i)     <<" "<<
+      // dvariable b1tmp = elem_prod(natage_f(srvyrtmp),exp( -Z_f(srvyrtmp) * srv_mo_frac(k) )) * elem_prod(sel_srv_f(k),wt_srv_f(k,srvyrtmp));
+      // b1tmp          += elem_prod(natage_m(srvyrtmp),exp( -Z_m(srvyrtmp) * srv_mo_frac(k) )) * elem_prod(sel_srv_m(k),wt_srv_m(k,srvyrtmp));
+					 endl;
+ }
+ /*
+   ABC_OFL <<"HM_F "
+            << hm_f << " "<<hm_f<<endl 
+            <<"AM_F "
+            << am_f << " "<<am_f<<endl 
+            <<"GM_6+Biom "
+            << gm_b << " "<<gm_b2<<endl 
+            <<"Catch_assumed " 
+            // << obs_catch(1,endyr)<<" "<<mean(obs_catch(1)(endyr-3,endyr)) <<endl
+            << yr1_futcat <<" "<< yr2_futcat <<endl
+            <<"ABC " 
+            << gm_b  * hm_f * adj_1         << " " 
+            << gm_b2 * hm_f * adj_1         << endl
+            <<"OFL " 
+            << gm_b  * am_f * adj_1         << " " 
+            << gm_b2 * am_f * adj_2         << endl
+            <<"SSB " 
+            << SSB_1                        << " " 
+            << SSB_2                        << endl
+            <<"Applied_Adjustments " 
+            <<                adj_1         << " " 
+            <<                adj_2         << " " <<endl
+            <<"Maturity_used "              <<endl
+            << maturity(endyr)              <<" "<<endl
+            << "wt "<<wt_pop_fut_f          <<endl ;
+ */
+  ABC_OFL.close();
+  // From AMAK 
+ /* FUNCTION Oper_Model
+ // Initialize things used here only
+  // Calc_Dependent_Vars();
+  int nsims;
+  ifstream sim_in("nsims.dat");
+  sim_in >> nsims; sim_in.close();
+  dvector ran_srv_vect(1,nsrv);
+  ofstream SaveOM("Om_Out.dat",ios::app);
+  double C_tmp;
+  dvariable Fnow;
+  dvariable meanrec;
+  meanrec=mean(recruits);
+  dvector new_srv(1,nsrv);
+  new_srv.initialize();
+  dvariable mean5plus;
+  mean5plus.initialize();
+  for (i=1975;i<=1999;i++)
+    mean5plus += natage(i)(5,nages)*wt_fsh(1,i)(5,nages);
+  mean5plus /= 25.;
+  system("cls"); cout<<"Number of replicates: "<<endl;
+  // Initialize recruitment in first year
+  nage_future(styr_fut,1) = meanrec;
+  nage_future(styr_fut)(2,nages)              = ++elem_prod(natage(endyr)(1,nages-1),S(endyr)(1,nages-1));
+  nage_future(styr_fut,nages)                += natage(endyr,nages)*S(endyr,nages);
+  for (int isim=1;isim<=nsims;isim++)
+  {
+    cout<<isim<<" ";
+    // Copy file to get mean for Mgt Strategies
+    system("init_stuff.bat");
+    for (i=styr_fut;i<=endyr_fut;i++)
+    {
+      // Some unit normals...
+      ran_srv_vect.fill_randn(rng);
+      // Create new survey observations
+      for (k = 1 ; k<= nsrv ; k++)
+        new_srv(k) = mfexp(ran_srv_vect(k)*.2)*value(nage_future(i)*q_srv(k)*sel_srv(k,endyr)); // use value function since converts to a double
+      // Append new survey observation to datafile
+      ofstream srv_out("NewSrv.dat",ios::app);
+      srv_out <<i<<" "<< new_srv<<endl; srv_out.close();
+      system("ComputeTAC.bat"); // commandline function to get TAC (catchnext.dat)
+      // Now read in TAC (actual catch)
+      ifstream CatchNext("CatchNext.dat");
+      CatchNext >> C_tmp; CatchNext.close();
+      Fnow = SolveF2(endyr,nage_future(i), C_tmp);
+      F_future(1,i) = sel_fsh(1,endyr) * Fnow;
+      Z_future(i)   = F_future(1,i) + natmort;
+      S_future(i)   = mfexp(-Z_future(i));
+      // nage_future(i,1)  = SRecruit( Sp_Biom_future(i-rec_age) ) * mfexp(rec_dev_future(i)) ;     
+      nage_future(i,1)  = meanrec;
+      Sp_Biom_future(i) = wt_mature * elem_prod(nage_future(i),pow(S_future(i),spmo_frac)) ;
+      // Now graduate for the next year....
+      if (i<endyr_fut)
+      {
+        nage_future(i+1)(2,nages) = ++elem_prod(nage_future(i)(1,nages-1),S_future(i)(1,nages-1));
+        nage_future(i+1,nages)   += nage_future(i,nages)*S_future(i,nages);
+      }
+      catage_future(i) = 0.; 
+      for (k = 1 ; k<= nfsh ; k++)
+        catage_future(i) += elem_prod(nage_future(i) , elem_prod(F_future(k,i) , elem_div( ( 1.- S_future(i) ) , Z_future(i))));
+  
+      SaveOM << model_name       <<
+        " "  << isim             <<
+        " "  << i                <<
+        " "  << Fnow             <<
+        " "  << nage_future(i)(5,nages)*wt_fsh(1,endyr)(5,nages)/mean5plus <<
+        " "  << nage_future(i)(5,nages)*wt_fsh(1,endyr)(5,nages)<<
+        " "  << Sp_Biom_future(i)<<
+        " "  << catage_future(i)*wt_fsh(1,endyr)<<
+        " "  << nage_future(i)<<
+        " "  << F_future(1,i)<<
+      endl;
+    }
+  }
+  SaveOM.close  init_int styr
+  */
+  WriteData( endyr_in);
+  WriteData(nages);
+  WriteData( a_lw_f);
+  WriteData( b_lw_f);
+  WriteData( a_lw_m);
+  WriteData( b_lw_m);
+  WriteData( nfsh  );                                      //Number of fisheries
+  WriteData( obs_catch);
+  WriteData( nyrs_fsh_age_c);
+  WriteData( nyrs_fsh_age_s);
+  WriteData( yrs_fsh_age_c);
+  WriteData( yrs_fsh_age_s);
+  WriteData( oac_fsh_c);
+  WriteData( oac_fsh_s);
+  WriteData( wt_fsh_in);
+  WriteData( nsmpl_fsh_c);
+  WriteData( nsmpl_fsh_s);
+  WriteData( nsrv  );
+  WriteData( nyrs_srv);
+  WriteData( yrs_srv);
+  WriteData( mo_srv);
+  WriteData( obs_srv);
+  WriteData( obs_se_srv);
+  WriteData( nyrs_srv_age_c);
+  WriteData( nyrs_srv_age_s);
+  WriteData( yrs_srv_age_c);
+  WriteData( yrs_srv_age_s);
+  WriteData( nsmpl_srv_c);
+  WriteData( nsmpl_srv_s);
+  WriteData( oac_srv_c);
+  WriteData( oac_srv_s);
+  WriteData( wt_srv_f_in);
+  WriteData( wt_srv_m_in);
+  WriteData(  wt_pop_f_in); 
+  WriteData(  wt_pop_m_in); 
+  WriteData( maturity);
+  WriteData( init_age_comp);
+  WriteData( n_env_cov);
+  WriteData( env_cov);
+  WriteData( spawnmo);
+  WriteData( srv_mo); 
+  WriteData( n_wts);
+  WriteData( growth_cov);
 }
 
 void model_parameters::Get_wt_age(void)
 {
-  incr_dev.initialize();
-  if (active(yr_incr)||active(age_incr)||active(growth_alpha))
-  {
-    switch (Growth_Option)
-    {
-      case 0 : // Use constant time-invariant growth (from base growth parameters)
-        // No need to do anything since they are initialized at these values...
-      break;
-      case 1 : // Use empirical (values in data file) mean wts at age
-        // No need to do anything since they are initialized at these values...
-      break;
-      case 2 : // Use base growth values (not estimated) and deviations decomposed by year and age
-      {
-        // Do it once for all years then apply to each fishery and survey...
-        // initialize survey "1" and first year of growth to mean
-        Initial_wt();
-        for (i=styr+1;i<=endyr;i++)
-        {
-          // Age component estimated from 5-15
-          incr_dev(i)(5,nages-5)     = yr_incr(i) + age_incr;
-          incr_dev(i)(nages-4,nages) = incr_dev(i,nages-5) ;
-          incr_dev(i)(2,4) = incr_dev(i,5) ;
-          wt_srv_f(1,i,1) = wt_srv_f(1,i-1,1);
-          wt_srv_m(1,i,1) = wt_srv_m(1,i-1,1);
-          wt_srv_f(1,i)(2,nages) = ++wt_srv_f(1,i-1)(1,nages-1) + elem_prod(base_incr_f,mfexp(incr_dev(i))) ;
-          wt_srv_m(1,i)(2,nages) = ++wt_srv_m(1,i-1)(1,nages-1) + elem_prod(base_incr_m,mfexp(incr_dev(i))) ;
-          wt_pop_f(i) = wt_srv_f(1,i);
-          wt_pop_m(i) = wt_srv_m(1,i);
-        }
-        Get_Pred_wt();
-      }
-      break;
-      case 3 : // Use base growth values (not estimated) and deviations as fn of temperature and // decomposed by year and age
-      {
-        Initial_wt();
-        for (i=styr+1;i<=endyr;i++)
-        {
-          // Age component estimated from 5-15
-          // if (i >=1982)
-            incr_dev(i)(5,nages-5)     = growth_alpha * growth_cov(i) ; // + age_incr; vestigial
-          // else 
-          //   incr_dev(i)(5,nages-5)     = 0.;
-          incr_dev(i)(nages-4,nages) = incr_dev(i,nages-5) ;
-          incr_dev(i)(2,4) = incr_dev(i,5) ;
-          wt_srv_f(1,i,1) = wt_srv_f(1,i-1,1);
-          wt_srv_m(1,i,1) = wt_srv_m(1,i-1,1);
-          wt_srv_f(1,i)(2,nages) = ++wt_srv_f(1,i-1)(1,nages-1) + elem_prod(base_incr_f,mfexp(incr_dev(i))) ;
-          wt_srv_m(1,i)(2,nages) = ++wt_srv_m(1,i-1)(1,nages-1) + elem_prod(base_incr_m,mfexp(incr_dev(i))) ;
-          wt_pop_f(i) = wt_srv_f(1,i);
-          wt_pop_m(i) = wt_srv_m(1,i);
-        }
-        Get_Pred_wt();
-      }
-      break;
-    }
-  }
+  incr_dev.initialize();
+  if (active(yr_incr)||active(age_incr)||active(growth_alpha))
+  {
+    switch (Growth_Option)
+    {
+      case 0 : // Use constant time-invariant growth (from base growth parameters)
+        // No need to do anything since they are initialized at these values...
+      break;
+      case 1 : // Use empirical (values in data file) mean wts at age
+        // No need to do anything since they are initialized at these values...
+      break;
+      case 2 : // Use base growth values (not estimated) and deviations decomposed by year and age
+      {
+        // Do it once for all years then apply to each fishery and survey...
+        // initialize survey "1" and first year of growth to mean
+        Initial_wt();
+        for (i=styr+1;i<=endyr;i++)
+        {
+          // Age component estimated from 5-15
+          incr_dev(i)(5,nages-5)     = yr_incr(i) + age_incr;
+          incr_dev(i)(nages-4,nages) = incr_dev(i,nages-5) ;
+          incr_dev(i)(2,4) = incr_dev(i,5) ;
+          wt_srv_f(1,i,1) = wt_srv_f(1,i-1,1);
+          wt_srv_m(1,i,1) = wt_srv_m(1,i-1,1);
+          wt_srv_f(1,i)(2,nages) = ++wt_srv_f(1,i-1)(1,nages-1) + elem_prod(base_incr_f,mfexp(incr_dev(i))) ;
+          wt_srv_m(1,i)(2,nages) = ++wt_srv_m(1,i-1)(1,nages-1) + elem_prod(base_incr_m,mfexp(incr_dev(i))) ;
+          wt_pop_f(i) = wt_srv_f(1,i);
+          wt_pop_m(i) = wt_srv_m(1,i);
+        }
+        Get_Pred_wt();
+      }
+      break;
+      case 3 : // Use base growth values (not estimated) and deviations as fn of temperature and // decomposed by year and age
+      {
+        Initial_wt();
+        for (i=styr+1;i<=endyr;i++)
+        {
+          // Age component estimated from 5-15
+          // if (i >=1982)
+            incr_dev(i)(5,nages-5)     = growth_alpha * growth_cov(i) ; // + age_incr; vestigial
+          // else 
+          //   incr_dev(i)(5,nages-5)     = 0.;
+          incr_dev(i)(nages-4,nages) = incr_dev(i,nages-5) ;
+          incr_dev(i)(2,4) = incr_dev(i,5) ;
+          wt_srv_f(1,i,1) = wt_srv_f(1,i-1,1);
+          wt_srv_m(1,i,1) = wt_srv_m(1,i-1,1);
+          wt_srv_f(1,i)(2,nages) = ++wt_srv_f(1,i-1)(1,nages-1) + elem_prod(base_incr_f,mfexp(incr_dev(i))) ;
+          wt_srv_m(1,i)(2,nages) = ++wt_srv_m(1,i-1)(1,nages-1) + elem_prod(base_incr_m,mfexp(incr_dev(i))) ;
+          wt_pop_f(i) = wt_srv_f(1,i);
+          wt_pop_m(i) = wt_srv_m(1,i);
+        }
+        Get_Pred_wt();
+      }
+      break;
+    }
+  }
+  
 }
 
 void model_parameters::Initial_wt(void)
 {
-  wt_srv_f(1,styr) = wt_vbg_f;
-  wt_srv_m(1,styr) = wt_vbg_m;
-  wt_pop_f(styr)   = wt_vbg_f;
-  wt_pop_m(styr)   = wt_vbg_m;
+  wt_srv_f(1,styr) = wt_vbg_f;
+  wt_srv_m(1,styr) = wt_vbg_m;
+  wt_pop_f(styr)   = wt_vbg_f;
+  wt_pop_m(styr)   = wt_vbg_m;
 }
 
 void model_parameters::Get_Pred_wt(void)
 {
-  // Get predicted weights
-  for (i=styr_wt;i<=endyr_wt;i++)
-  {
-    wt_pred_f(i) = wt_srv_f(1,i);   
-    wt_pred_m(i) = wt_srv_m(1,i); 
-  }
-  // for other surveys set equal to survey 1...
-  for (k=2;k<=nsrv;k++)
-    for (i=styr;i<=endyr;i++)
-    {
-      wt_srv_f(k,i) = wt_srv_f(1,i) ;
-      wt_srv_m(k,i) = wt_srv_m(1,i) ;
-    }
-  // set fisheries equal to surveys 
-  for (k=1;k<=nfsh;k++)
-    for (i=styr;i<=endyr;i++)
-    {
-      wt_fsh_f(k,i) = wt_srv_f(1,i) ;
-      wt_fsh_m(k,i) = wt_srv_m(1,i) ;
-    }
+  // Get predicted weights
+  for (i=styr_wt;i<=endyr_wt;i++)
+  {
+    wt_pred_f(i) = wt_srv_f(1,i);   
+    wt_pred_m(i) = wt_srv_m(1,i); 
+  }
+  // for other surveys set equal to survey 1...
+  for (k=2;k<=nsrv;k++)
+    for (i=styr;i<=endyr;i++)
+    {
+      wt_srv_f(k,i) = wt_srv_f(1,i) ;
+      wt_srv_m(k,i) = wt_srv_m(1,i) ;
+    }
+  // set fisheries equal to surveys 
+  for (k=1;k<=nfsh;k++)
+    for (i=styr;i<=endyr;i++)
+    {
+      wt_fsh_f(k,i) = wt_srv_f(1,i) ;
+      wt_fsh_m(k,i) = wt_srv_m(1,i) ;
+    }
 }
 
 void model_parameters::Write_R_wts(void)
 {
-  R_report<<"$Yr"<<endl; for (i=styr;i<=endyr;i++) R_report<<i<<" "; R_report<<endl;
-  R_report<<"$Yr_wt"<<endl; for (i=styr_wt;i<=endyr_wt;i++) R_report<<i<<" "; R_report<<endl;
-  R_report<<"$wt_obs_f" <<endl;
-  R_report<<  wt_obs_f  <<endl;
-  R_report<<"$wt_pred_f"<<endl;
-  R_report<<  wt_pred_f <<endl;
-  R_report<<"$wt_obs_m" <<endl;
-  R_report<<  wt_obs_m  <<endl;
-  R_report<<"$wt_pred_m"<<endl;
-  R_report<< wt_pred_m  <<endl;
-  R_report<<"$wt_srv_f" <<endl;
-  R_report<<  wt_srv_f  <<endl;
-  R_report<<"$wt_srv_m" <<endl;
-  R_report<<  wt_srv_m  <<endl;
-  R_report<<"$wt_like"  <<endl;
-  R_report <<  wt_like(1)<<endl;
-  // Make a dataframe (long) with year, Population, report << "Estimated_sex_ratio Year Total Mature Age_7+"<< endl;
-  // R_report<<"$sex_ratio"  <<endl;
-  for (i=styr;i<=endyr;i++)
-    report_sex_ratio << i << " Population "<< sum(natage_f(i))/sum(natage_f(i)+natage_m(i))<<endl;
-  for (i=styr;i<=endyr;i++)
-    report_sex_ratio << i << " Mature "<< 
-     sum(elem_prod(maturity(i),natage_f(i)))/sum(elem_prod(maturity(i),natage_f(i)+natage_m(i)))<<endl;
-  for (i=styr;i<=endyr;i++)
-    report_sex_ratio << i << " Age_7_plus "<< 
-     sum(natage_f(i)(7,nages))/sum(natage_f(i)(7,nages)+natage_m(i)(7,nages))<<endl;
-  // init_3darray oac_fsh_s(1,nfsh,1,nyrs_fsh_age_s,1,2*nages)  //Fishery age compositions
-	for (k=1;k<=nfsh;k++)
-	{
-    for (i=1;i<=nyrs_fsh_age_s(k);i++)
-      report_sex_ratio << yrs_fsh_age_s(k,i) << " Fishery_obs "<< sum(oac_fsh_s(k,i)(1,nages)) /sum(oac_fsh_s(k,i)) << endl;
-    for (i=1;i<=nyrs_fsh_age_s(k);i++)
-      report_sex_ratio << yrs_fsh_age_s(k,i) << " Fishery_est "<< sum(eac_fsh_s(k,i)(1,nages)) /sum(eac_fsh_s(k,i)) << endl;
-    for (i=1;i<=nyrs_srv_age_s(k);i++)
-      report_sex_ratio << yrs_srv_age_s(k,i) << " Survey_est "<< sum(eac_srv_s(k,i)(1,nages)) /sum(eac_srv_s(k,i)) << endl;
-    for (i=1;i<=nyrs_srv_age_s(k);i++)
-      report_sex_ratio << yrs_srv_age_s(k,i) << " Survey_obs "<< sum(oac_srv_s(k,i)(1,nages)) /sum(oac_srv_s(k,i)) << endl;
-	}
+ 
+  R_report<<"Yr"<<endl; for (i=styr;i<=endyr;i++) R_report<<i<<" "; R_report<<endl;
+  R_report<<"Yr_wt"<<endl; for (i=styr_wt;i<=endyr_wt;i++) R_report<<i<<" "; R_report<<endl;
+  R_report<<"wt_obs_f" <<endl;
+  R_report<<  wt_obs_f  <<endl;
+  R_report<<"wt_pred_f"<<endl;
+  R_report<<  wt_pred_f <<endl;
+  R_report<<"wt_obs_m" <<endl;
+  R_report<<  wt_obs_m  <<endl;
+  R_report<<"wt_pred_m"<<endl;
+  R_report<< wt_pred_m  <<endl;
+  R_report<<"wt_srv_f" <<endl;
+  R_report<<  wt_srv_f  <<endl;
+  R_report<<"wt_srv_m" <<endl;
+  R_report<<  wt_srv_m  <<endl;
+  R_report<<"wt_like"  <<endl;
+  R_report <<  wt_like(1)<<endl;
+  // Make a dataframe (long) with year, Population, report << "Estimated_sex_ratio Year Total Mature Age_7+"<< endl;
+  // R_report<<"#sex_ratio"  <<endl;
+  for (i=styr;i<=endyr;i++)
+    report_sex_ratio << i << " Population "<< sum(natage_f(i))/sum(natage_f(i)+natage_m(i))<<endl;
+  for (i=styr;i<=endyr;i++)
+    report_sex_ratio << i << " Mature "<< 
+     sum(elem_prod(maturity(i),natage_f(i)))/sum(elem_prod(maturity(i),natage_f(i)+natage_m(i)))<<endl;
+  for (i=styr;i<=endyr;i++)
+    report_sex_ratio << i << " Age_7_plus "<< 
+     sum(natage_f(i)(7,nages))/sum(natage_f(i)(7,nages)+natage_m(i)(7,nages))<<endl;
+  // init_3darray oac_fsh_s(1,nfsh,1,nyrs_fsh_age_s,1,2*nages)  //Fishery age compositions
+	for (k=1;k<=nfsh;k++)
+	{
+    for (i=1;i<=nyrs_fsh_age_s(k);i++)
+      report_sex_ratio << yrs_fsh_age_s(k,i) << " Fishery_obs "<< sum(oac_fsh_s(k,i)(1,nages)) /sum(oac_fsh_s(k,i)) << endl;
+    for (i=1;i<=nyrs_fsh_age_s(k);i++)
+      report_sex_ratio << yrs_fsh_age_s(k,i) << " Fishery_est "<< sum(eac_fsh_s(k,i)(1,nages)) /sum(eac_fsh_s(k,i)) << endl;
+    for (i=1;i<=nyrs_srv_age_s(k);i++)
+      report_sex_ratio << yrs_srv_age_s(k,i) << " Survey_est "<< sum(eac_srv_s(k,i)(1,nages)) /sum(eac_srv_s(k,i)) << endl;
+    for (i=1;i<=nyrs_srv_age_s(k);i++)
+      report_sex_ratio << yrs_srv_age_s(k,i) << " Survey_obs "<< sum(oac_srv_s(k,i)(1,nages)) /sum(oac_srv_s(k,i)) << endl;
+	}
 }
 
 void model_parameters::Write_R(void)
 {
-  Write_R_wts();
-  // R_report<<"$TotF"<<endl << Ftot<<endl;
-  /* R_report<<"$TotBiom_NoFish"<<endl; for (i=styr;i<=endyr;i++) 
-  {
-    double lb=value(TotBiom_NoFish(i)/exp(2.*sqrt(log(1+square(TotBiom_NoFish.sd(i))/square(TotBiom_NoFish(i))))));
-    double ub=value(TotBiom_NoFish(i)*exp(2.*sqrt(log(1+square(TotBiom_NoFish.sd(i))/square(TotBiom_NoFish(i))))));
-    R_report<<i<<" "<<TotBiom_NoFish(i)<<" "<<TotBiom_NoFish.sd(i)<<" "<<lb<<" "<<ub<<endl;
-  }
-  R_report<<"$SSB_NoFishR"<<endl; for (i=styr;i<=endyr;i++) 
-  {
-    double lb=value(Sp_Biom_NoFishR(i)/exp(2.*sqrt(log(1+square(Sp_Biom_NoFishR.sd(i))/square(Sp_Biom_NoFishR(i))))));
-    double ub=value(Sp_Biom_NoFishR(i)*exp(2.*sqrt(log(1+square(Sp_Biom_NoFishR.sd(i))/square(Sp_Biom_NoFishR(i))))));
-    R_report<<i<<" "<<Sp_Biom_NoFishR(i)<<" "<<Sp_Biom_NoFishR.sd(i)<<" "<<lb<<" "<<ub<<endl;
-  }
-  */ 
-  REPORT(nLogPosterior);
-  REPORT(natmort_f);
-  REPORT(natmort_m);
-  REPORT(future_SSB);
-  REPORT(future_TotBiom);
-  REPORT(future_catch);
-  R_report << "$survey_likelihood "         << endl << srv_like     << endl;
-  R_report << "$catch_likelihood "          << endl << catch_like   << endl;
-  R_report << "$age_likelihood_for_fishery" << endl << age_like_fsh << endl;
-  R_report << "$age_likeihood_for_survey "  << endl << age_like_srv << endl;
-  R_report << "$recruitment_likelilhood "   << endl << rec_like     << endl;
-  R_report << "$selectivity_likelihood "    << endl << sel_like     << endl;
-  R_report << "$q_Prior "                   << endl << q_prior      << endl;
-  R_report << "$sigmaR_Prior "              << endl << sigmaR_prior << endl;
-  R_report << "$m_Prior "                   << endl << m_prior      << endl;
-  R_report << "$F_penalty"                  << endl << fpen         << endl;
-  R_report << "$SPR_penalty"                << endl << sprpen       << endl;
-  R_report << "$obj_fun"                    << endl << obj_fun      << endl;
-  R_report<<"$SSB"<<endl; 
-	for (i=styr;i<=endyr;i++) 
-  {
-    double lb=value(SSB(i)/exp(2.*sqrt(log(1+square(SSB.sd(i))/square(SSB(i))))));
-    double ub=value(SSB(i)*exp(2.*sqrt(log(1+square(SSB.sd(i))/square(SSB(i))))));
-    R_report<<i<<" "<<SSB(i)<<" "<<SSB.sd(i)<<" "<<lb<<" "<<ub<<endl;
-  }
-  R_report<<"$TotBiom"<<endl; 
-  for (i=styr;i<=endyr;i++) 
-  {
-    double lb=value(TotBiom(i)/exp(2.*sqrt(log(1+square(TotBiom.sd(i))/square(TotBiom(i))))));
-    double ub=value(TotBiom(i)*exp(2.*sqrt(log(1+square(TotBiom.sd(i))/square(TotBiom(i))))));
-    R_report<<i<<" "<<TotBiom(i)<<" "<<TotBiom.sd(i)<<" "<<lb<<" "<<ub<<endl;
-  }
-  R_report<<"$yr_bts"<<endl;
-  R_report<<yrs_srv(1)<<endl;
-  R_report<<"$eb_bts"<<endl;
-  double rmse=0.;
-  for (int i=1;i<=nyrs_srv(1);i++)
-  {
-    R_report<<pred_srv(1,yrs_srv(1,i))<<endl;
-    rmse += value(square(log(obs_srv(1,i)) - log(pred_srv(1,yrs_srv(1,i)))));
-  }
-  rmse = sqrt(rmse/nyrs_srv(1));
-  R_report << "$rmse_srv"                   << endl << rmse         << endl;
-  R_report<<"$ob_bts"<<endl;
-  R_report<<obs_srv(1)<<endl;
-  R_report<<"$sd_ob_bts"<<endl;
-  R_report<<obs_se_srv(1)<<endl;
-  R_report<<"$R"<<endl; for (i=styr;i<=endyr;i++) 
-  {
-    double lb=value(pred_rec(i)/exp(2.*sqrt(log(1+square(pred_rec.sd(i))/square(pred_rec(i))))));
-    double ub=value(pred_rec(i)*exp(2.*sqrt(log(1+square(pred_rec.sd(i))/square(pred_rec(i))))));
-    R_report<<i<<" "<<pred_rec(i)<<" "<<pred_rec.sd(i)<<" "<<lb<<" "<<ub<<endl;
-  }
-  int k=1;
-  R_report<<"$q"<<endl; for (i=1982;i<=endyr;i++) 
-  {
-    double lb=value(q_srv(k,i)/exp(2.*sqrt(log(1+square(q_srv.sd(k,i))/square(q_srv(k,i))))));
-    double ub=value(q_srv(k,i)*exp(2.*sqrt(log(1+square(q_srv.sd(k,i))/square(q_srv(k,i))))));
-    R_report<<i<<" "<<q_srv(k,i)<<" "<<q_srv.sd(k,i)<<" "<<lb<<" "<<ub<<endl;
-  }
-  for (k=1;k<=nsrv;k++)
-  {
-    R_report << endl<< "$yrs_srv"<<endl;
-    R_report << yrs_srv(k) << endl;
-    R_report << "$q_srv"<<endl;
-    for (i=1;i<=nyrs_srv(k);i++)
-      R_report<< q_srv(k,yrs_srv(k,i)) <<" ";
-	  R_report<< endl;
-	}
-  /* 
-  for (int k=1;k<=5;k++){
-    R_report<<"$SSB_fut_"<<k<<endl; 
-    for (i=styr_fut;i<=endyr_fut;i++) 
-    {
-      double lb=value(future_biomass(k,i)/exp(2.*sqrt(log(1+square(future_biomass.sd(k,i))/square(future_biomass(k,i))))));
-      double ub=value(future_biomass(k,i)*exp(2.*sqrt(log(1+square(future_biomass.sd(k,i))/square(future_biomass(k,i))))));
-      R_report<<i<<" "<<future_biomass(k,i)<<" "<<future_biomass.sd(k,i)<<" "<<lb<<" "<<ub<<endl;
-    }
-  }
-  double ctmp;
-  for (int k=1;k<=5;k++){
-    R_report<<"$Catch_fut_"<<k<<endl; 
-    for (i=styr_fut;i<=endyr_fut;i++) 
-    {
-      if (k==5) ctmp=0.;else ctmp=value(future_catch(k,i));
-      R_report<<i<<" "<<ctmp<<endl;
-    }
-  }
-    R_report << "$N"<<endl;
-    for (i=styr;i<=endyr;i++) 
-      R_report <<   i << " "<< natage(i) << endl;
-      R_report   << endl;
-    for (int k=1;k<=nfsh;k++)
-    {
-      R_report << "$F_age_"<< (k) <<""<< endl ;
-      for (i=styr;i<=endyr;i++) 
-        R_report <<i<<" "<<F(k,i)<<" "<< endl;
-        R_report   << endl;
-    }
-    R_report <<endl<< "$Fshry_names"<< endl;
-    for (int k=1;k<=nfsh;k++)
-      R_report << fshname(k) << endl ;
-    R_report <<endl<< "$Index_names"<< endl;
-    for (int k=1;k<=nsrv;k++)
-      R_report << srvname(k) << endl ;
-    for (int k=1;k<=nsrv;k++)
-    {
-      int ii=1;
-      R_report <<endl<< "$Obs_Survey_"<< k <<""<< endl ;
-      for (i=styr;i<=endyr;i++)
-      {
-        if (ii<=yrs_srv(k).indexmax())
-        {
-          if (yrs_srv(k,ii)==i)
-          {
-            R_report << i<< " "<< obs_srv(k,ii) << " "<< pred_srv(k,i) <<" "<< obs_se_srv(k,ii) <<endl; //values of survey index value (annual)
-            ii++;
-          }
-          else
-            R_report << i<< " -1 "<< " "<< pred_srv(k,i)<<" -1 "<<endl;
-        }
-        else
-          R_report << i<< " -1 "<< " "<< pred_srv(k,i)<<" -1 "<<endl;
-      }
-      R_report   << endl;
-    }
-    R_report   << endl;
-    for (int k=1;k<=nfsh;k++)
-    {
-      if (nyrs_fsh_age(k)>0) 
-      { 
-        R_report << "$pobs_fsh_"<< (k) <<""<< endl;
-        for (i=1;i<=nyrs_fsh_age(k);i++) 
-          R_report << yrs_fsh_age(k,i)<< " "<< oac_fsh(k,i) << endl;
-        R_report   << endl;
-      }
-    }
-    for (int k=1;k<=nfsh;k++)
-    {
-      if (nyrs_fsh_age(k)>0) 
-      { 
-        R_report << "$phat_fsh_"<< (k) <<""<< endl;
-        for (i=1;i<=nyrs_fsh_age(k);i++) 
-          R_report << yrs_fsh_age(k,i)<< " "<< eac_fsh(k,i) << endl;
-          R_report   << endl;
-      }
-    }
-    for (int k=1;k<=nsrv;k++)
-    {
-      if (nyrs_srv_age(k)>0) 
-      { 
-        R_report << "$pobs_srv_"<<(k)<<""<<  endl;
-        for (i=1;i<=nyrs_srv_age(k);i++) 
-          R_report << yrs_srv_age(k,i)<< " "<< oac_srv(k,i) << endl;
-          R_report   << endl;
-      }
-    }
-    for (int k=1;k<=nsrv;k++)
-    {
-      if (nyrs_srv_age(k)>0) 
-      { 
-        R_report << "$phat_srv_"<<(k)<<""<<  endl;
-        for (i=1;i<=nyrs_srv_age(k);i++) 
-          R_report << yrs_srv_age(k,i)<< " "<< eac_srv(k,i) << endl;
-          R_report   << endl;
-      }
-    }
-    for (int k=1;k<=nfsh;k++)
-    {
-      R_report << endl<< "$Obs_catch_"<<(k) << endl;
-      R_report << obs_catch(k)(styr,endyr)<< endl;
-      R_report   << endl;
-      R_report << "$Pred_catch_" <<(k) << endl;
-      R_report << pred_catch(k) << endl;
-      R_report   << endl;
-    }
-    for (int k=1;k<=nfsh;k++)
-    {
-      R_report << "$F_fsh_"<<(k)<<" "<<endl;
-      for (i=styr;i<=endyr;i++)
-      {
-        R_report<< i<< " ";
-        R_report<< mean(F(k,i)) <<" "<< mean(F(k,i))*max(sel_fsh(k,i)) << " ";
-        R_report<< endl;
-      }
-    }
-    for (int k=1;k<=nfsh;k++)
-    {
-      R_report << endl<< "$sel_fsh_"<<(k)<<"" << endl;
-      for (i=styr;i<=endyr;i++)
-        R_report << k <<"  "<< i<<" "<<sel_fsh(k,i) << endl; 
-      R_report   << endl;
-    }
-    for (int k=1;k<=nsrv;k++)
-    {
-      R_report << endl<< "$sel_srv_"<<(k)<<"" << endl;
-      for (i=styr;i<=endyr;i++)
-        R_report << k <<"  "<< i<<" "<<sel_srv(k,i) << endl;
-        R_report << endl;
-    }
-    R_report << endl<< "$Stock_Rec"<< endl;
-    for (i=styr_rec;i<=endyr;i++)
-      if (active(log_Rzero))
-        R_report << i<< " "<<Sp_Biom(i-rec_age)<< " "<< SRecruit(Sp_Biom(i-rec_age))<< " "<< mod_rec(i)<<endl;
-      else 
-        R_report << i<< " "<<Sp_Biom(i-rec_age)<< " "<< " 999" << " "<< mod_rec(i)<<endl;
-        R_report   << endl;
-    R_report <<"$stock_Rec_Curve"<<endl;
-    R_report <<"0 0"<<endl;
-    dvariable stock;
-    for (i=1;i<=30;i++)
-    {
-      stock = double (i) * Bzero /25.;
-      if (active(log_Rzero))
-        R_report << stock <<" "<< SRecruit(stock)<<endl;
-      else
-        R_report << stock <<" 99 "<<endl;
-    }
-    R_report   << endl;
-    R_report   << endl<<"$Like_Comp" <<endl;
-    obj_comps(11)= obj_fun - sum(obj_comps) ; // Residual
-    obj_comps(12)= obj_fun ;
-    R_report   <<obj_comps<<endl;
-    R_report   << endl;
-    R_report   << endl<<"$Like_Comp_names" <<endl;
-    R_report   <<"catch_like     "<<endl
-             <<"age_like_fsh     "<<endl
-             <<"sel_like_fsh     "<<endl
-             <<"surv_like        "<<endl
-             <<"age_like_srv     "<<endl
-             <<"sel_like_srv     "<<endl
-             <<"rec_like         "<<endl
-             <<"fpen             "<<endl
-             <<"post_priors_srvq "<<endl
-             <<"post_priors      "<<endl
-             <<"residual         "<<endl
-             <<"total            "<<endl;
-    for (int k=1;k<=nfsh;k++)
-    {
-      R_report << "$Sel_Fshry_"<< (k) <<""<<endl;
-      R_report << sel_like_fsh(k) << endl;
-    }
-    R_report   << endl;
-    for (int k=1;k<=nsrv;k++)
-    {
-      R_report << "$Survey_Index_"<< (k) <<"" <<endl;
-      R_report<< surv_like(k)<<endl;
-    }
-    R_report   << endl;
-    R_report << setw(10)<< setfixed() << setprecision(5) <<endl;
-    for (int k=1;k<=nsrv;k++)
-    {
-      R_report << "$Age_Survey_"<< (k) <<"" <<endl;
-      R_report << age_like_srv(k)<<endl;
-    }
-    R_report   << endl;
-    for (int k=1;k<=nsrv;k++)
-    {
-      R_report << "$Sel_Survey_"<< (k) <<""<<endl;
-      R_report<< sel_like_srv(k,1) <<" "<<sel_like_srv(k,2)<<" "<<sel_like_srv(k,3)<< endl;
-    }
-    R_report   << endl;
-    R_report << setw(10)<< setfixed() << setprecision(5) <<endl;
-    R_report   << "$Rec_Pen" <<endl<<sigmaR<<"  "<<rec_like<<endl;
-    R_report   << endl;
-    R_report   << "$F_Pen" <<endl;
-    R_report<<fpen(1)<<"  "<<fpen(2)<<endl;
-    R_report   << endl;
-    for (int k=1;k<=nsrv;k++)
-    {
-      R_report << "$Q_Survey_"<< (k) <<""<<endl
-             << " "<<post_priors_srvq(k)
-             << " "<< q_srv(k)
-             << " "<< qprior(k)
-             << " "<< cvqprior(k)<<endl;
-      R_report << "$Q_power_Survey_"<< (k) <<""<<endl
-             << " "<<post_priors_srvq(k)
-             << " "<< q_power_srv(k)
-             << " "<< q_power_prior(k)
-             << " "<< cvq_power_prior(k)<<endl;
-    }
-             R_report   << endl;
-    R_report << "$M"<<endl;
-    R_report << " "<< post_priors(1)
-             << " "<< M
-             << " "<< natmortprior
-             << " "<< cvnatmortprior <<endl;
-    R_report   << endl;
-    R_report << "$Steep"<<endl;
-    R_report << " "<< post_priors(2)
-             << " "<< steepness
-             << " "<< steepnessprior
-             << " "<< cvsteepnessprior <<endl;
-    R_report   << endl;
-    R_report << "$Sigmar"<<endl;
-    R_report << " "<< post_priors(3)
-             << " "<< sigmaR
-             << " "<< sigmaRprior
-             << " "<< cvsigmaRprior <<endl;
-    R_report   << endl;
-    R_report<<"$Num_parameters_Est"<<endl;
-    R_report<<initial_params::nvarcalc()<<endl;
-    R_report   << endl;
-  R_report<<"$Steep_Prior" <<endl;
-  R_report<<steepnessprior<<" "<<
-    cvsteepnessprior<<" "<<
-    phase_srec<<" "<< endl;
-    R_report   << endl;
-  R_report<<"$sigmaRPrior " <<endl;
-  R_report<<sigmaRprior<<" "<<  cvsigmaRprior <<" "<<phase_sigmaR<<endl;
-  R_report   << endl;
-  R_report<<"$Rec_estimated_in_styr_endyr " <<endl;
-  R_report<<styr_rec    <<" "<<endyr        <<" "<<endl;
-  R_report   << endl;
-  R_report<<"$SR_Curve_fit__in_styr_endyr " <<endl;
-  R_report<<styr_rec_est<<" "<<endyr_rec_est<<" "<<endl;
-  R_report   << endl;
-  R_report<<"$Model_styr_endyr" <<endl;
-  R_report<<styr        <<" "<<endyr        <<" "<<endl;
-  R_report   << endl;
-  R_report<<"$M_prior "<<endl;
-  R_report<< natmortprior<< " "<< cvnatmortprior<<" "<<phase_M<<endl;
-  R_report   << endl;
-  R_report<<"$qprior " <<endl;
-  R_report<< qprior<<" "<<cvqprior<<" "<< phase_q<<endl;
-  R_report<<"$q_power_prior " <<endl;
-  R_report<< q_power_prior<<" "<<cvq_power_prior<<" "<< phase_q_power<<endl;
-  R_report   << endl;
-  R_report<<"$cv_catchbiomass " <<endl;
-  R_report<<cv_catchbiomass<<" "<<endl;
-  R_report   << endl;
-  R_report<<"$Projection_years"<<endl;
-  R_report<< nproj_yrs<<endl;
-  R_report   << endl;
-  R_report << "$Fsh_sel_opt_fish "<<endl;
-  for (int k=1;k<=nfsh;k++)
-    R_report<<k<<" "<<fsh_sel_opt(k)<<" "<<sel_change_in_fsh(k)<<endl;
-    R_report   << endl;
-   R_report<<"$Survey_Sel_Opt_Survey " <<endl;
-  for (int k=1;k<=nsrv;k++)
-  R_report<<k<<" "<<(srv_sel_opt(k))<<endl;
-  R_report   << endl;
-  R_report <<"$Phase_survey_Sel_Coffs "<<endl;
-  R_report <<phase_selcoff_srv<<endl;
-  R_report   << endl;
-  R_report <<"$Fshry_Selages " << endl;
-  R_report << nselages_in_fsh  <<endl;
-  R_report   << endl;
-  R_report <<"$Survy_Selages " <<endl;
-  R_report <<nselages_in_srv <<endl;
-  R_report   << endl;
-  R_report << "$Phase_for_age_spec_fishery"<<endl;
-  R_report <<phase_selcoff_fsh<<endl;
-  R_report   << endl;
-  R_report << "$Phase_for_logistic_fishery"<<endl;
-  R_report <<phase_logist_fsh<<endl;
-  R_report   << endl;
-  R_report << "$Phase_for_dble_logistic_fishery "<<endl;
-  R_report <<phase_dlogist_fsh<<endl;
-  R_report   << endl;
-  R_report << "$Phase_for_age_spec_survey  "<<endl;
-  R_report <<phase_selcoff_srv<<endl;
-  R_report   << endl;
-  R_report << "$Phase_for_logistic_survey  "<<endl;
-  R_report <<phase_logist_srv<<endl;
-  R_report   << endl;
-  R_report << "$Phase_for_dble_logistic_srvy "<<endl;
-  R_report <<phase_dlogist_srv<<endl;
-  R_report   << endl;
-  for (int k=1;k<=nfsh;k++)
-  {
-    if (nyrs_fsh_age(k)>0)
-    {
-      R_report <<"$EffN_Fsh_"<<(k)<<""<<endl;
-      for (i=1;i<=nyrs_fsh_age(k);i++)
-      {
-        double sda_tmp = Sd_age(oac_fsh(k,i));
-        R_report << yrs_fsh_age(k,i);
-        R_report<< " "<<Eff_N(oac_fsh(k,i),eac_fsh(k,i)) ;
-        R_report << " "<<Eff_N2(oac_fsh(k,i),eac_fsh(k,i));
-        R_report << " "<<mn_age(oac_fsh(k,i));
-        R_report << " "<<mn_age(eac_fsh(k,i));
-        R_report << " "<<sda_tmp;
-        R_report << " "<<mn_age(oac_fsh(k,i)) - sda_tmp *2. / sqrt(n_sample_fsh_age(k,i));
-        R_report << " "<<mn_age(oac_fsh(k,i)) + sda_tmp *2. / sqrt(n_sample_fsh_age(k,i));
-        R_report <<endl;
-      }
-    }
-  }
-  for (int k=1;k<=nfsh;k++)
-  {
-    R_report <<"$C_fsh_" <<(k)<<"" << endl; 
-    for (i=styr;i<=endyr;i++)
-      R_report <<i<<" "<<catage(k,i)<< endl;
-  }
-  R_report <<"$wt_a_pop" << endl<< wt_pop  <<endl;
-  R_report <<"$mature_a" << endl<< maturity<<endl;
-  for (int k=1;k<=nfsh;k++)
-  {
-    R_report <<"$wt_fsh_"<<(k)<<""<<endl;
-    for (i=styr;i<=endyr;i++)
-      R_report <<i<<" "<<wt_fsh(k,i)<< endl;
-  }
-  for (int k=1;k<=nsrv;k++)
-  {
-    R_report <<"$wt_srv_"<<(k)<<""<<endl;
-    for (i=styr;i<=endyr;i++)
-      R_report <<i<<" "<<wt_srv(k,i)<< endl;
-  }
-  for (int k=1;k<=nsrv;k++)
-  {
-    if (nyrs_srv_age(k)>0)
-    {
-      R_report <<"$EffN_Survey_"<<(k)<<""<<endl;
-      for (i=1;i<=nyrs_srv_age(k);i++)
-      {
-        double sda_tmp = Sd_age(oac_srv(k,i));
-        R_report << yrs_srv_age(k,i)
-                << " "<<Eff_N(oac_srv(k,i),eac_srv(k,i)) 
-                 << " "<<Eff_N2(oac_srv(k,i),eac_srv(k,i))
-                 << " "<<mn_age(oac_srv(k,i))
-                 << " "<<mn_age(eac_srv(k,i))
-                 << " "<<sda_tmp
-                 << " "<<mn_age(oac_srv(k,i)) - sda_tmp *2. / sqrt(n_sample_srv_age(k,i))
-                 << " "<<mn_age(oac_srv(k,i)) + sda_tmp *2. / sqrt(n_sample_srv_age(k,i))
-                 <<endl;
-      }
-    }
-  }
-  */ 
-  R_report.close();
+  Write_R_wts();
+	REPORT(Z_f);
+	REPORT(Z_m);
+	REPORT(F_f);
+	REPORT(F_m);
+  // R_report<<"#TotF"<<endl << Ftot<<endl;
+  /* R_report<<"#TotBiom_NoFish"<<endl; for (i=styr;i<=endyr;i++) 
+  {
+    double lb=value(TotBiom_NoFish(i)/exp(2.*sqrt(log(1+square(TotBiom_NoFish.sd(i))/square(TotBiom_NoFish(i))))));
+    double ub=value(TotBiom_NoFish(i)*exp(2.*sqrt(log(1+square(TotBiom_NoFish.sd(i))/square(TotBiom_NoFish(i))))));
+    R_report<<i<<" "<<TotBiom_NoFish(i)<<" "<<TotBiom_NoFish.sd(i)<<" "<<lb<<" "<<ub<<endl;
+  }
+  R_report<<"#SSB_NoFishR"<<endl; for (i=styr;i<=endyr;i++) 
+  {
+    double lb=value(Sp_Biom_NoFishR(i)/exp(2.*sqrt(log(1+square(Sp_Biom_NoFishR.sd(i))/square(Sp_Biom_NoFishR(i))))));
+    double ub=value(Sp_Biom_NoFishR(i)*exp(2.*sqrt(log(1+square(Sp_Biom_NoFishR.sd(i))/square(Sp_Biom_NoFishR(i))))));
+    R_report<<i<<" "<<Sp_Biom_NoFishR(i)<<" "<<Sp_Biom_NoFishR.sd(i)<<" "<<lb<<" "<<ub<<endl;
+  }
+  */ 
+  REPORT(nLogPosterior);
+  REPORT(natmort_f);
+  REPORT(natmort_m);
+  REPORT(future_SSB);
+  REPORT(future_TotBiom);
+  REPORT(future_catch);
+  REPORT(sel_srv_f);
+  REPORT(sel_srv_m);
+  REPORT(sel_fsh_f);
+  REPORT(sel_fsh_m);
+  R_report << "survey_likelihood "         << endl << srv_like     << endl;
+  R_report << "catch_likelihood "          << endl << catch_like   << endl;
+  R_report << "age_likelihood_for_fishery" << endl << age_like_fsh << endl;
+  R_report << "age_likeihood_for_survey "  << endl << age_like_srv << endl;
+  R_report << "recruitment_likelilhood "   << endl << rec_like     << endl;
+  R_report << "selectivity_likelihood "    << endl << sel_like     << endl;
+  R_report << "q_Prior "                   << endl << q_prior      << endl;
+  R_report << "sigmaR_Prior "              << endl << sigmaR_prior << endl;
+  R_report << "m_Prior "                   << endl << m_prior      << endl;
+  R_report << "F_penalty"                  << endl << fpen         << endl;
+  R_report << "SPR_penalty"                << endl << sprpen       << endl;
+  R_report << "obj_fun"                    << endl << obj_fun      << endl; 
+  R_report << "Obs_catch"<< endl << obs_catch << endl;          //IS 9/2019
+  R_report << "Pred_catch" << endl << pred_catch << endl;       //IS 9/2019  
+  R_report << "Bottom_temp" << endl << env_cov << endl;         //IS 9/2019  
+  R_report << "pred_srv" << endl << pred_srv << endl;           //IS 9/2019  
+  R_report << "catage_f" << endl << catage_f << endl;           //IS 9/2019  
+  R_report << "catage_m" << endl << catage_m << endl;           //IS 9/2019
+  R_report << "natage_f" << endl << natage_f << endl;           //IS 10/2019
+  R_report << "natage_m" << endl << natage_m << endl;           //IS 10/2019 
+  R_report << "Fmort" << endl << Fmort << endl;           //IS 10/2019 
+  R_report << "sel_fsh_f" << endl << sel_fsh_f << endl; //IS 10/2019
+  R_report << "sel_fsh_m" << endl << sel_fsh_m << endl; //IS 10/2019
+  R_report << "maturity" <<endl << maturity << endl;
+   
+  R_report<<"Future_F"<<endl; 
+	for (i=styr_fut;i<=endyr_fut;i++) 
+  {
+    double lb=value(future_Fs(i)/exp(2.*sqrt(log(1+square(future_Fs.sd(i))/square(future_Fs(i))))));
+    double ub=value(future_Fs(i)*exp(2.*sqrt(log(1+square(future_Fs.sd(i))/square(future_Fs(i))))));
+    R_report<<i<<" "<<future_Fs(i)<<" "<<future_Fs.sd(i)<<" "<<lb<<" "<<ub<<endl;
+  }
+  R_report<<"SSB"<<endl; 
+	for (i=styr;i<=endyr;i++) 
+  {
+    double lb=value(SSB(i)/exp(2.*sqrt(log(1+square(SSB.sd(i))/square(SSB(i))))));
+    double ub=value(SSB(i)*exp(2.*sqrt(log(1+square(SSB.sd(i))/square(SSB(i))))));
+    R_report<<i<<" "<<SSB(i)<<" "<<SSB.sd(i)<<" "<<lb<<" "<<ub<<endl;
+  }
+  R_report<<"TotBiom"<<endl; 
+  for (i=styr;i<=endyr;i++) 
+  {
+    double lb=value(TotBiom(i)/exp(2.*sqrt(log(1+square(TotBiom.sd(i))/square(TotBiom(i))))));
+    double ub=value(TotBiom(i)*exp(2.*sqrt(log(1+square(TotBiom.sd(i))/square(TotBiom(i))))));
+    R_report<<i<<" "<<TotBiom(i)<<" "<<TotBiom.sd(i)<<" "<<lb<<" "<<ub<<endl;
+  }
+  R_report<<"yr_bts"<<endl;
+  R_report<<yrs_srv(1)<<endl;
+  R_report<<"eb_bts"<<endl;
+  double rmse=0.;
+  for (int i=1;i<=nyrs_srv(1);i++)
+  {
+    R_report<<pred_srv(1,yrs_srv(1,i))<<endl;
+    rmse += value(square(log(obs_srv(1,i)) - log(pred_srv(1,yrs_srv(1,i)))));
+  }
+  rmse = sqrt(rmse/nyrs_srv(1));
+  R_report << "rmse_srv"                   << endl << rmse         << endl;
+  R_report<<"ob_bts"<<endl;
+  R_report<<obs_srv(1)<<endl;
+  R_report<<"sd_ob_bts"<<endl;
+  R_report<<obs_se_srv(1)<<endl;
+  R_report<<"R"<<endl; for (i=styr;i<=endyr;i++) 
+  {
+    double lb=value(pred_rec(i)/exp(2.*sqrt(log(1+square(pred_rec.sd(i))/square(pred_rec(i))))));
+    double ub=value(pred_rec(i)*exp(2.*sqrt(log(1+square(pred_rec.sd(i))/square(pred_rec(i))))));
+    R_report<<i<<" "<<pred_rec(i)<<" "<<pred_rec.sd(i)<<" "<<lb<<" "<<ub<<endl;
+  }
+  int k=1;
+  R_report<<"q"<<endl; for (i=1982;i<=endyr;i++) 
+  {
+    double lb=value(q_srv(k,i)/exp(2.*sqrt(log(1+square(q_srv.sd(k,i))/square(q_srv(k,i))))));
+    double ub=value(q_srv(k,i)*exp(2.*sqrt(log(1+square(q_srv.sd(k,i))/square(q_srv(k,i))))));
+    R_report<<i<<" "<<q_srv(k,i)<<" "<<q_srv.sd(k,i)<<" "<<lb<<" "<<ub<<endl;
+  }
+  for (k=1;k<=nsrv;k++)
+  {
+    R_report << endl<< "yrs_srv"<<endl;
+    R_report << yrs_srv(k) << endl;
+    R_report << "q_srv"<<endl;
+    for (i=1;i<=nyrs_srv(k);i++)
+      R_report<< q_srv(k,yrs_srv(k,i)) <<" ";
+	  R_report<< endl;
+	}      
+  R_report.close();
 }
 
 void model_parameters::final_calcs()
 {
-  if (!do_wt_only)
-  {
-    write_srec();
-    REPORT(SRR_SSB);
-    REPORT(rechat);
-    REPORT(rechat.sd);
-    // REPORT(future_spr0);
-    // REPORT(future_spr0.sd);
-    Write_sd();
-    Write_R();
-  }
-  else
-    Write_R_wts();
-  /*
-		*/
+  if (!do_wt_only)
+  {
+    write_srec();
+    REPORT(SRR_SSB);
+    REPORT(future_ABC);
+    REPORT(rechat);
+    REPORT(rechat.sd);
+    // REPORT(future_spr0);
+    // REPORT(future_spr0.sd);
+    Write_sd();
+    Write_R();
+  }
+  else
+    Write_R_wts();
+  /*
+		*/
 }
 
 model_data::~model_data()
@@ -3382,16 +3246,17 @@ int main(int argc,char * argv[])
 {
     ad_set_new_handler();
   ad_exit=&ad_boundf;
-  gradient_structure::set_MAX_NVAR_OFFSET(1600);
-  gradient_structure::set_GRADSTACK_BUFFER_SIZE(200000);
-  gradient_structure::set_NUM_DEPENDENT_VARIABLES(1800); 
-  gradient_structure::set_CMPDIF_BUFFER_SIZE(2000000);
-  arrmblsize=10000000;
+  gradient_structure::set_MAX_NVAR_OFFSET(1600);
+  gradient_structure::set_GRADSTACK_BUFFER_SIZE(200000);
+  gradient_structure::set_NUM_DEPENDENT_VARIABLES(1800); 
+  gradient_structure::set_CMPDIF_BUFFER_SIZE(2000000);
+  arrmblsize=10000000;
     gradient_structure::set_NO_DERIVATIVES();
 #ifdef DEBUG
   #ifndef __SUNPRO_C
 std::feclearexcept(FE_ALL_EXCEPT);
   #endif
+  auto start = std::chrono::high_resolution_clock::now();
 #endif
     gradient_structure::set_YES_SAVE_VARIABLES_VALUES();
     if (!arrmblsize) arrmblsize=15000000;
@@ -3400,6 +3265,7 @@ std::feclearexcept(FE_ALL_EXCEPT);
     mp.preliminary_calculations();
     mp.computations(argc,argv);
 #ifdef DEBUG
+  std::cout << endl << argv[0] << " elapsed time is " << std::chrono::duration_cast<std::chrono::microseconds>(std::chrono::high_resolution_clock::now() - start).count() << " microseconds." << endl;
   #ifndef __SUNPRO_C
 bool failedtest = false;
 if (std::fetestexcept(FE_DIVBYZERO))
diff --git a/assessments/nrs/2018/fm.htp b/assessments/nrs/2018/fm.htp
index 1fac69a..fa3dc53 100644
--- a/assessments/nrs/2018/fm.htp
+++ b/assessments/nrs/2018/fm.htp
@@ -52,6 +52,11 @@ class model_data : public ad_comm{
   data_number yr1_futcat;
   data_number yr2_futcat;
   data_number n_retro;
+  data_number surv_dwnwt;
+  data_number cv_inc;
+  data_number n_comp;
+  data_number eof_check;
+  int phase_male_sel_offset;
   data_int nyrs_fut;
   data_vector fut_temp;
   data_int styr;
@@ -130,6 +135,7 @@ class model_data : public ad_comm{
   dvector srv_mo_frac;
   data_matrix n_wts;
   data_vector growth_cov;
+  data_int Check;
   int styr_fut;
   int endyr_fut;
   int num_proj_Fs;
@@ -137,6 +143,7 @@ class model_data : public ad_comm{
   dvector offset_srv;
   dvector offset_fsh;
   double R_guess;
+  data_matrix future_ABC;
   ~model_data();
   model_data(int argc,char * argv[]);
   friend class model_parameters;
@@ -149,7 +156,6 @@ public:
   ~model_parameters();
   void preliminary_calculations(void);
   void set_runtime(void);
-  virtual void * mycast(void) {return (void*)this;}
   static int mc_phase(void)
   {
     return initial_params::mc_phase;
@@ -176,6 +182,12 @@ public:
     return *objective_function_value::pobjfun;
   }
 private:
+  dvariable adromb(dvariable(model_parameters::*f)(const dvariable&), double a, double b, int ns)
+  {
+    using namespace std::placeholders;
+    _func func = std::bind(f, this, _1);
+    return function_minimizer::adromb(func, a, b, ns);
+  }
   ivector integer_control_flags;
   dvector double_control_flags;
   param_init_vector ln_q_srv;
@@ -217,6 +229,7 @@ private:
   param_number slope_tmp;
   param_number sel50_tmp;
   param_init_vector sel_slope_fsh_m;
+  param_init_bounded_number male_sel_offset;
   param_init_bounded_matrix sel_slope_fsh_devs_m;
   param_init_vector sel50_fsh_m;
   param_init_bounded_matrix sel50_fsh_devs_m;
@@ -343,6 +356,7 @@ private:
   param_stddev_number endbiom;
   param_stddev_number depletion;
   param_stddev_matrix future_catch;
+  param_stddev_vector future_Fs;
   param_stddev_matrix future_SSB;
   param_stddev_matrix future_TotBiom;
 public:
diff --git a/assessments/nrs/2018/mod.ctl b/assessments/nrs/2018/mod.ctl
index 711b8fd..42197dc 100644
--- a/assessments/nrs/2018/mod.ctl
+++ b/assessments/nrs/2018/mod.ctl
@@ -1,91 +1,92 @@
 #Growth_Option
-1
+0
 #ABC_age_lb
 6
-#
+#phase_age_incr
 -1
-#
+#phase_init_age_comp
 2
-#
+#phase_mn_rec
 1
-#
+#phase_rec_dev
 2
-#
+#phase_mn_f
 2
-#
--6
-#
+#phase_F40           
+8
+#phase_fmort        
 3
-#
-7
-#
+#phase_proj        
+6
+#phase_logist_sel    
 4
-#
+#phase_logist_sel_devs    
 4
-#
+#phase_male_sel      
 5
-#
+#phase_q
 5
-#
--0.136
-#
+#q_alpha_prior
+-0.336
+#phase_q_alpha
 -4
-#
-0.05
-#
--5
-#
+#q_beta_prior
+0.01
+#phase_q_beta_in
+-4
+#phase_m_f
 -6
-#
+#phase_m_m
 -7
-#
-6
-#
+#phase_sr
+-33
+#phase_env_cov  
 -4
-#
+#phase_sigmaR  
 -5
-#
+#phase_wtfmsy 
 -4
-#
+#pf_sigma    
 0.05
-#
+#a50_sigma   
 0.35
-#
+#slp_sigma   
 0.2
-#
-1.5
-#
-0.05
-#
+#q_exp   
+1.0
+#q_sigma
+0.056
+#m_exp
 0.15
-#
+#m_sigma
 0.2
-#
+#sigmaR_exp
 0.6
-#
+#sigmaR_sigma
 0.6
-#
+#nselages
 17
-1
-#
-1
-#
-300
--1
-1
-1
-1
-1
-1
-1
+#lambda
+1 1 200 1 1 1 1 1 1 1
+#styr_sr         
 1978
+#endyr_sr       
 2012
+#styr_wt       
 1982
+#endyr_wt     
 2012
+#yr1_futcat       
 65
+#yr2_futcat      
 65
+#n_retro
 0
-1
+#surv_dwnwt
+0
+#cv_inc
 10
+#n_comp
 1
+#eof_check
 123456
diff --git a/assessments/nrs/2018/sim.dat b/assessments/nrs/2018/sim.dat
index 56dd42d..e69de29 100644
--- a/assessments/nrs/2018/sim.dat
+++ b/assessments/nrs/2018/sim.dat
@@ -1,450 +0,0 @@
-#endyr_in
-2018
-#nages
-20
-#a_lw_f
-0.00618
-#b_lw_f
-3.1765
-#a_lw_m
-0.00505
-#b_lw_m
-3.2243
-#nfsh
-1
-#obs_catch
- 12.014 9.964 5.319 7.038 5.874 8.798 9.021 11.843 13.619 37.679 18.75 19.611 40.822 86.366 68.912 35.253 60.587 56.998 63.953 59.606 58.87 46.928 67.564 33.642 40.51 49.264 29.255 41.331 35.395 47.637 35.546 36.411 36.768 51.275 48.649 53.221 60.401 76.099 59.773 51.946 45.466 45.101 35.272 26
-#nyrs_fsh_age_c
- 0
-#nyrs_fsh_age_s
- 39
-#yrs_fsh_age_c
-
-#yrs_fsh_age_s
- 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
-#oac_fsh_c
-
-#oac_fsh_s
- 0 0 0 0.000209215 0.000164187 0.00105274 0.00855397 0.0430108 0.16303 0.165336 0.0530752 0.0546635 0.0552296 0.0440693 0.0226745 0.0156178 0.000257722 0 0.000109669 0 0 0 0 8.34e-05 0.000490169 0.00071514 0.0105632 0.0220274 0.0504313 0.0891616 0.0634365 0.0741637 0.0421945 0.0171758 0 0.00250299 0 0 0 0
- 0 0 0.0083923 0.0426667 0.0619307 0.0339029 0.069585 0.0435024 0.0345273 0.108745 0.0818106 0.0306045 0.0370014 0.0252498 0.0207391 0.00746879 0 0 0 0 0 0.00412853 0.0402993 0.0201805 0.0871304 0.0456849 0.0250792 0.0244199 0.0326448 0.0612131 0.0242412 0.0149257 0.0046968 0.00772301 0.00150626 0 0 0 0 0
- 0 9.56e-05 0.0247216 0.0443374 0.0170981 0.135341 0.044579 0.0232841 0.0221222 0.0351523 0.103036 0.0432597 0.0373161 0.0124538 0.0230018 0.0108101 0.00200773 0.000948094 0 0 0 0.00248542 0.0436621 0.0666117 0.036742 0.170666 0.0218895 0.0124747 0.01907 0.0310787 0.0132297 0.000801575 0.00057788 0.000216239 0.000654309 0.000208782 6.71e-05 0 0 0
- 0 0 0.0228433 0.0232455 0.02486 0.102162 0.120397 0.103473 0.043176 0.0521799 0.036704 0.0310351 0.0305334 0.0175662 0.00289661 0.00559083 0.00364145 0 0.000893811 0 0 0.00266761 0.0139902 0.0321786 0.0267495 0.0297795 0.08528 0.0483209 0.0167171 0.0211927 0.0189697 0.0525051 0.0229909 0.00745944 0 0 0 0 0 0
- 0 0 0.000588229 0.00996645 0.0288763 0.0259604 0.0783695 0.102075 0.0809289 0.0778122 0.0435105 0.0550334 0.110537 0.0526074 0.0392626 0.0393162 0.0075649 0.00464746 0.00150149 0 0 0 0.000159053 0.0085962 0.024337 0.0145772 0.028159 0.046841 0.0145069 0.0192653 0.00306176 0.0114916 0.0311677 0.0187086 0.0161173 0.00445347 0 0 0 0
- 0 0 0.00118123 0.0120689 0.0220672 0.0250627 0.0428066 0.0503348 0.0871745 0.0688083 0.0395793 0.0437519 0.0728678 0.0449348 0.041574 0.0319648 0.0090742 0 0.0090742 0 0 0.00221028 0.0103237 0.0670165 0.0413492 0.0176607 0.0650918 0.0318807 0.0603858 0.015145 0.0113024 0.0145822 0.00354485 0.0166578 0.0118675 0.0128456 0.00354485 0 0 0.0122657
- 0 0.00161257 0.00765731 0.0503106 0.102398 0.0602491 0.0635485 0.0608005 0.0319531 0.0525167 0.0132678 0.00646384 0.00275998 0.0057615 0.0137919 0.0172102 0.00225967 0.00218053 0.00154366 0.00409828 0 0.00735846 0.0284209 0.0918442 0.149259 0.0956978 0.0417413 0.0305614 0.0243179 0.0145571 0.00274121 0.000177466 0.00153442 0.007084 0.000539536 0.00153566 0.00224608 0 0 0
- 0 0 0 0.00216573 0.0338487 0.0705868 0.085543 0.0652861 0.0934052 0.0353335 0.0917138 0.0146466 0.0146426 0.0135543 0.00455297 0.0130549 0.0128471 0.000433488 0 0.0123717 0 0 0.00615786 0.0263261 0.0798486 0.151453 0.0731684 0.0406468 0.0303352 0 0.0280773 0 0 0 0 0 0 0 0 0
- 0 0 0.0117429 0.0363151 0.0282694 0.074118 0.145732 0.0443389 0.0267349 0.0307078 0.0249669 0.046963 0.0104157 0.00294368 0.00357015 0.00179279 0.00344148 0.00262337 0.000828639 0.00513328 0 0.000453553 0.0206048 0.0348645 0.0855514 0.0818842 0.127711 0.0414543 0.0510153 0.0249067 0 0.0278926 0 0 0 0 0.00302369 0 0 0
- 0 0 0.00369231 0.00753921 0.0980767 0.0476505 0.0784407 0.0760005 0.0495462 0.0164351 0.0375632 0.0133538 0.0204531 0.0153377 0 0.00217492 0.0032546 0.0117845 0.00382722 0.00461344 0 0.000727802 0.00343509 0.0234886 0.0834618 0.12815 0.136874 0.0479537 0.038455 0.00226799 0.0147268 0.0133213 0 0.00464416 0 0 0 0.00797763 0.00477258 0
- 0 6.74e-05 0.000900255 0.00781905 0.0320034 0.104736 0.0720494 0.0943765 0.0774478 0.0269036 0.0195251 0.0287651 0.0155577 0.0237553 0.0142206 0.00405958 0.00124015 0.00124015 0.0129599 0.00985688 0 0.000145763 0.00228764 0.0206002 0.0735003 0.109794 0.0810777 0.0462145 0.0423843 0.0235376 0.012929 0.00560115 0.00604701 0.0139579 0 0.0121412 0 0 0 0.00229791
- 0 0 0.00271205 0.0247631 0.0312153 0.050564 0.0669836 0.105965 0.0506072 0.027975 0.0257767 0.00359777 0.0207874 0.00782112 0.00985425 0.00595594 0.00373396 0 0 0.00599972 0 0 0.00648194 0.0604748 0.0567778 0.137462 0.108774 0.0787842 0.0355074 0.0274438 0.0220183 0.00363704 0.00828412 0.00588432 0.00207944 0 0 0.00207944 0 0
- 0 0 0.00389178 0.0190039 0.0125506 0.0194178 0.02342 0.0835602 0.0546366 0.0621456 0.0525464 0.0225517 0.0132746 0.0122757 0.0055364 0.0105467 0.000295804 0.00126835 0.000440628 0.00661304 0 0 0.00824389 0.0256207 0.0149657 0.0604514 0.0829786 0.154994 0.100687 0.0517644 0.0273773 0.0212026 0.0116407 0.00550966 0.0129874 0.00636405 0.00529517 0.0020802 0 0.00386101
- 0 0 0 0 0.0113467 0.0172252 0.0274425 0.0643971 0.0759103 0.0223691 0.069391 0.0455036 0.0190627 0.0189944 0.00703125 0.00127457 0.0104522 0.00317641 0.00305735 0.00525321 0 0 0.00117262 0.0059989 0.0407389 0.0372864 0.0589041 0.143365 0.114067 0.0588708 0.0636033 0.0213943 0.00740546 0.0129071 0.00734022 0 0.0250582 0 0 0
- 0 0 0.000191393 0.00119848 0.00580836 0.0171574 0.0490742 0.0464917 0.0678907 0.089414 0.02084 0.0416217 0.0336099 0.0199412 0.0131945 0.00324043 0 0 0.00292163 0.00292163 0 0.000168875 0.00198662 0.00444646 0.00820066 0.064668 0.11302 0.0630514 0.175778 0.0611359 0.0387964 0.0128835 0.0160976 0.0141038 0.00665559 0 0 0 0 0.00348918
- 0 0 0 0.000113603 0 0.0017924 0.0272155 0.044905 0.0584113 0.072605 0.0632355 0.0209212 0.0325375 0.0266759 0.00935679 0.00801341 0.0028284 0.000833089 0.00516263 0.00321781 0 0 0 0.00203077 0 0.00920701 0.0761423 0.174238 0.0780704 0.0881597 0.113501 0.0202647 0.0281619 0.0116294 0.00825383 0.00714249 0 0 0.00537321 0
- 0 0 0 0.00124409 0.0048206 0.00653413 0.00861229 0.0911706 0.0838905 0.0729401 0.0880909 0.0997974 0.0320127 0.0177618 0.0618317 0.00187602 0.00438011 0.0015414 0 0 0 0 0 0.0010817 0.00380235 0.00329652 0.0275104 0.0770279 0.101115 0.0560199 0.0544758 0.0464806 0.022951 0.0265801 0.00158425 0 0 0.0015702 0 0
- 0 0 0 0 6.1e-05 0.00404799 0.00296792 0.0240966 0.0832414 0.126572 0.0682683 0.0447842 0.0652933 0.0275654 0.0287515 0.0278799 0.00754735 0.00458888 0.00111759 0.00502915 0 0 0.000262131 0.000467131 0.00205 0.0187078 0.015223 0.0393537 0.11608 0.0795345 0.0545407 0.0204045 0.0212576 0.0175376 0.00572152 0.0435995 0.03382 0.00962828 0 0
- 0 0 0 0.00394245 0.00172021 0.00660511 0.046166 0.021658 0.0201258 0.121161 0.0689188 0.0401053 0.0722178 0.0317518 0.0248647 0.0239982 0.0137624 0.00905319 0 0 0 3.61208e-05 0.000500196 0.00500746 0.00511937 0.0105704 0.0538614 0.00643882 0.0744974 0.148755 0.0613702 0.0625155 0.0236541 0.0293054 0.0123185 0 0 0 0 0
- 0 0 0 0 0.000404221 0.00215593 0.00900707 0.0200852 0.0155733 0.0287624 0.115414 0.0673366 0.0535379 0.04623 0.0132943 0.00841338 0.0149203 0.00680645 0.000858621 0.00315014 0 0 0 0 0.00315667 0.00190288 0.00549893 0.0341562 0.0336215 0.0827791 0.228998 0.101039 0.0304191 0.0292039 0.0170037 0.00401437 0.0101047 0.0121521 0 0
- 0 0 0 0 0.00762444 0.0103979 0.0171583 0.00934154 0.0330866 0.0292881 0.055995 0.238225 0.0880103 0.0570559 0.0479814 0.00963996 0.00451749 0.00600735 0.000994222 0.0077425 0 0 0 0 0.00407855 0.00218994 0.011235 0.00675317 0.0715033 0.0272926 0.0586741 0.129199 0.0349307 0.0102926 0.0178064 0.002978 0 0 0 0
- 0 0 0 0 0.0028016 0.00582979 0.00350907 0.0144162 0.0395131 0.0906444 0.0255952 0.0656581 0.183834 0.0740764 0.0328868 0.0248465 0.0206922 0.00237586 0.00709364 0 0 0 0 0 0 0.00234402 0.0103962 0.0120066 0.0288337 0.113522 0.0454004 0.0337542 0.0860428 0.0348374 0.0230881 0.00939491 0.00219822 0.00168503 0.00162313 0.0011005
- 0 0 0 0 0.00254955 0.0191673 0.0218705 0.0218923 0.0235753 0.0348696 0.0995653 0.0557413 0.06927 0.130316 0.079011 0.0219259 0.0265666 0.00751362 0.00333481 0.00444566 0 0 0 0 0.00927867 0.00895288 0.0138651 0.0256718 0.0239647 0.0542235 0.102671 0.0355784 0.0350097 0.0428152 0.0191822 0.0059043 0.00126828 0 0 0
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- 0 8.52e-05 0.00111637 0.00295828 0.00212196 0.00830385 0.00492015 0 0.00251538 0.0258598 0.103176 0.093661 0.0906992 0.0967025 0.0582983 0.0194127 0.00265717 0.0110956 0.00406645 0.0263255 0 0 0.00661212 0.00902683 0.0170501 0.0267106 0.00825443 0.00733281 0.012687 0.035996 0.0934907 0.0863119 0.049382 0.027081 0.0373648 0.00729178 0.0027214 0.00688718 0.00221626 0.00960792
- 0 0 0 0.00301258 0.00895511 0.00933809 0.00237349 0 0.00620094 0.0016724 0.0196087 0.138407 0.08863 0.0808274 0.0917003 0.0602884 0.0203689 0.00715664 0.00174856 0.0228512 0 0 0.00147482 0.0035027 0.00352114 0.0393088 0.00407683 0.0217805 0.0155544 0.0109207 0.0336675 0.0780778 0.0715744 0.0722696 0.0242059 0.0321593 0.0176497 0 0.00103237 0.00608415
-#wt_fsh_in
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- 0.009 0.017 0.025 0.054 0.114 0.181 0.272 0.269 0.327 0.387 0.421 0.479 0.462 0.504 0.514 0.523 0.562 0.537 0.626 0.632 0.007 0.013 0.023 0.055 0.123 0.149 0.196 0.234 0.241 0.265 0.282 0.308 0.314 0.307 0.297 0.36 0.321 0.348 0.321 0.335
- 0.009 0.017 0.025 0.054 0.114 0.181 0.272 0.269 0.327 0.387 0.421 0.479 0.462 0.504 0.514 0.523 0.562 0.537 0.626 0.632 0.007 0.013 0.023 0.055 0.123 0.149 0.196 0.234 0.241 0.265 0.282 0.308 0.314 0.307 0.297 0.36 0.321 0.348 0.321 0.335
- 0.009 0.017 0.025 0.054 0.114 0.181 0.272 0.269 0.327 0.387 0.421 0.479 0.462 0.504 0.514 0.523 0.562 0.537 0.626 0.632 0.007 0.013 0.023 0.055 0.123 0.149 0.196 0.234 0.241 0.265 0.282 0.308 0.314 0.307 0.297 0.36 0.321 0.348 0.321 0.335
- 0.009 0.017 0.025 0.054 0.114 0.181 0.272 0.269 0.327 0.387 0.421 0.479 0.462 0.504 0.514 0.523 0.562 0.537 0.626 0.632 0.007 0.013 0.023 0.055 0.123 0.149 0.196 0.234 0.241 0.265 0.282 0.308 0.314 0.307 0.297 0.36 0.321 0.348 0.321 0.335
- 0.009 0.017 0.025 0.054 0.114 0.181 0.272 0.269 0.327 0.387 0.421 0.479 0.462 0.504 0.514 0.523 0.562 0.537 0.626 0.632 0.007 0.013 0.023 0.055 0.123 0.149 0.196 0.234 0.241 0.265 0.282 0.308 0.314 0.307 0.297 0.36 0.321 0.348 0.321 0.335
-#nsmpl_fsh_c
-
-#nsmpl_fsh_s
- 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200
-#nsrv
-1
-#nyrs_srv
- 37
-#yrs_srv
- 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
-#mo_srv
- 7
-#obs_srv
- 600.63 759.588 850.355 695.465 1086.29 1273.49 1480.56 1326.69 1384.45 1585.65 1549.54 1995.6 2724.85 2180.56 2070.26 2623.16 2196.17 1648.1 2080.73 2344.16 1883.59 2111.31 2196.17 2121.08 2216.43 2034.3 2031.89 1539 2065.7 1977.3 1920.42 1752.97 1857.45 1411.83 1461.27 1331.78 1051.5
-#obs_se_srv
- 74.082 81.8512 81.8245 58.7762 83.7444 91.228 101.509 91.0905 89.0219 95.9685 112.279 122.047 223.254 130.541 121.985 190.492 123.659 162.403 317.094 259.021 171.437 196.192 183.573 150.26 149.968 278.942 300.653 159 203.358 164.582 185.891 136.588 129.331 130.437 130.966 99.607 115.323
-#nyrs_srv_age_c
- 0
-#nyrs_srv_age_s
- 39
-#yrs_srv_age_c
-
-#yrs_srv_age_s
- 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
-#nsmpl_srv_c
-
-#nsmpl_srv_s
- 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200 200
-#oac_srv_c
-
-#oac_srv_s
- 0 0 0.0136616 0.0516972 0.0368 0.0828869 0.034087 0.0294129 0.0581352 0.0429907 0.0128967 0.0155924 0.0168259 0.0132449 0.00832478 0.00405219 0.000167022 0 0.000133788 0 0 0 0.0251897 0.0902536 0.0742152 0.100657 0.0619607 0.0452871 0.0755302 0.054815 0.0203411 0.018297 0.00410428 0.00817312 0 0.000266648 0 0 0 0
- 0 0 0.0467893 0.0681502 0.0836813 0.0467646 0.0438567 0.023393 0.0197666 0.0668525 0.0496389 0.0191993 0.0147037 0.0092504 0.00724254 0.00341622 0 0 0 0 0 0.0147965 0.0815959 0.0343737 0.124348 0.0565548 0.0293991 0.0240078 0.0345528 0.0571921 0.0197381 0.0109692 0.00283703 0.00637409 0.000555428 0 0 0 0 0
- 7.72e-05 0.0293619 0.0466587 0.104354 0.025706 0.115279 0.0277252 0.0147906 0.0121274 0.0183811 0.0381664 0.0161466 0.0133329 0.00518105 0.00816049 0.00380389 0.000950219 0.000629711 0 0 0 0.0613187 0.0524504 0.0878812 0.0395879 0.155023 0.0209604 0.0117543 0.0230272 0.035565 0.0174147 0.0050562 0.00289932 0.00140226 0.00355883 0.00096807 0.000299842 0 0 0
- 0 0.00319925 0.0428581 0.0528836 0.0464272 0.123795 0.0892074 0.0506215 0.0157058 0.0189127 0.0128934 0.0116451 0.011647 0.00595198 0.00199307 0.00276677 0.00245289 0 0.000467314 0 0 0.0185356 0.0341388 0.113706 0.123812 0.0453052 0.0839914 0.0298361 0.0116894 0.00571837 0.00530111 0.0238805 0.00850394 0.0021526 0 0 0 0 0 0
- 0 0.00109401 0.0785719 0.0659544 0.0792721 0.0402516 0.0528029 0.0534303 0.0237912 0.0234131 0.0103491 0.0134908 0.0207204 0.00999245 0.00609899 0.00645547 0.00136403 0.000581414 0.000239291 0 0 0.0171157 0.0953295 0.0928674 0.100156 0.0490098 0.0378402 0.0490353 0.0229741 0.0160118 0.00528492 0.00762632 0.00860499 0.00508741 0.00453808 0.000644977 0 0 0 0
- 0 0.0107706 0.0587272 0.0910345 0.0693067 0.0479454 0.0509053 0.0355007 0.0321908 0.0231048 0.00634141 0.00907413 0.0136109 0.00374737 0.00509383 0.00349449 0.000565488 0 0.000565488 0 0 0.0167818 0.0545217 0.167357 0.0847851 0.0357652 0.0821155 0.0228005 0.0412127 0.00577228 0.00570374 0.00429486 0.00138808 0.0052272 0.0064848 0.00173852 0.00138808 0 0 0.000683586
- 0.00121459 0.018996 0.036853 0.119193 0.119934 0.0500127 0.0445035 0.0370749 0.0169733 0.0284546 0.00659553 0.00349676 0.00149035 0.00286374 0.00634961 0.00844607 0.00121447 0.000570742 0.000548381 0.00214405 0.00115948 0.0197407 0.0603372 0.138833 0.129549 0.0665591 0.0277815 0.0184949 0.0149622 0.00736805 0.00142327 0 0.000113581 0.000854402 0.00383553 0.000122579 0.000714348 0.00122125 0 0
- 0 0 0.0276933 0.0704141 0.116134 0.0936193 0.0512805 0.0259664 0.0305942 0.00985681 0.021426 0.00390253 0.00369782 0.00339236 0.000976859 0.00353925 0.00314957 0.000127413 0 0.00226641 0 0 0.0527039 0.131608 0.125675 0.120626 0.0432719 0.0244007 0.0185944 0 0.0150825 0 0 0 0 0 0 0 0 0
- 0 0 0.03386 0.0950375 0.0629674 0.0812652 0.0984205 0.0231826 0.0154427 0.0166416 0.0126465 0.0237558 0.00522029 0.00146215 0.00178746 0.000641945 0.00162786 0.000753351 0.000423069 0.00305491 0 0.00294647 0.0916578 0.0831272 0.127088 0.0678208 0.0724463 0.0218633 0.0286666 0.0121542 0 0.0125083 0 0 0 0 0.00153064 0 0 0
- 0 0.0130576 0.0783142 0.0714233 0.145827 0.0402571 0.0492234 0.0425126 0.0249068 0.00783615 0.0155534 0.00539458 0.00869288 0.00632504 0 0.000812717 0.00135898 0.00509261 0.00157556 0.00174635 0 0.0228862 0.0558123 0.118034 0.0950914 0.0782868 0.062834 0.0189796 0.0127433 0.000523776 0.0048962 0.00559737 0 0.000983645 0 0 0 0.00210152 0.00131911 0
- 0 0.00862143 0.0579326 0.0662731 0.0703356 0.0973415 0.0516615 0.0506949 0.0365759 0.011486 0.00788089 0.0112238 0.0066212 0.00684562 0.00393244 0.00143703 0.000312994 0.000312994 0.0024195 0.00166464 0 0.00843848 0.06435 0.0822639 0.100966 0.0996371 0.0616687 0.0337238 0.0259736 0.0078744 0.00612987 0.00274235 0.0035684 0.0051301 0 0.0021679 0 0 0 0.00179219
- 0 0.00123886 0.0413765 0.129557 0.094419 0.0546788 0.0542887 0.029403 0.0315858 0.0176319 0.0096584 0.00463723 0.00445896 0.00104219 0.0024541 0.000123845 0 0.000869934 0 0.00245478 0 0.000859727 0.0671407 0.178067 0.0933132 0.0487836 0.0721872 0.00814843 0.019787 0.017339 0.00499005 0.00179112 0.00287121 0.00095265 0.00207683 0 0 0 0 0.00181307
- 0 0 0.00528693 0.120288 0.0979069 0.0796986 0.0445738 0.0470452 0.0292955 0.0201788 0.0146326 0.0126671 0.00472851 0.00506453 0.00292301 0.00148009 0 0.000382063 0.000528185 0.00278121 0 0.00120085 0.00490384 0.162234 0.127264 0.0602982 0.0560103 0.0393085 0.0177312 0.0224108 0.0118253 0.00114527 0.00404581 0.00127672 0.000884233 0 0 0 0 0
- 0 0 0.0190238 0.037889 0.123674 0.115747 0.0503127 0.044952 0.0270322 0.0226835 0.0223942 0.0129904 0.00781379 0.00519995 0.00356145 0.00175458 0.00102026 0 0.00113164 0.000536755 0 0.000775883 0.0109407 0.0358511 0.178581 0.113881 0.0357191 0.0594689 0.0278936 0.00857292 0.0104374 0.00662617 0.00647964 0.00443151 0.00143385 0.000912361 0.000278578 0 0 0
- 0 0.0010874 0.025653 0.0491341 0.0544853 0.128954 0.0754122 0.0404052 0.0331529 0.0293487 0.00541645 0.00889724 0.00848119 0.00495112 0.00264006 0.000840456 0 0 0.000399884 0.000399884 0 0.00191246 0.0511038 0.0577729 0.0421328 0.176828 0.0931047 0.0384206 0.0409344 0.0123976 0.00675374 0.00262541 0.00235772 0.00254059 0.00107784 0 0 0 0 0.000379113
- 0 0 0.0159997 0.055491 0.04632 0.040048 0.131897 0.0944954 0.0367952 0.0115435 0.0250814 0.0134067 0.00723503 0.00796324 0.00390406 0.0026604 0.000568758 0.000757579 0.00159789 0.00106852 0 0.00277943 0.0173669 0.0883212 0.0430133 0.0499232 0.166673 0.052979 0.0340257 0.0113887 0.0186485 0.00604837 0.00379933 0.00458208 0.00201426 0.000961601 0.000320767 0 0.000320767 0
- 0 0 0 0.0474658 0.0881594 0.0419804 0.0246369 0.114718 0.066959 0.0296182 0.031505 0.0237772 0.00881676 0.00426642 0.00928265 0 0.000947958 0.000338296 0.000338296 0.000850798 0 0 0.0145391 0.039938 0.106235 0.0444274 0.0401679 0.119969 0.0722064 0.0188559 0.0212502 0.0137526 0.00634964 0.00864734 0 0 0 0 0 0
- 0 0.000599032 0.0371301 0.0198039 0.0344042 0.0837626 0.0252828 0.0508143 0.0995062 0.065441 0.0164703 0.00802873 0.0138503 0.00477272 0.00490523 0.00534748 0.0014898 0.000896073 0.000140213 0.000888663 0 0.00287733 0.0543746 0.0243736 0.0355677 0.102724 0.0296162 0.0409285 0.117563 0.0638063 0.0210878 0.011392 0.00963441 0.00225941 0.0050167 0.00333902 0.00172439 0.000180851 0 0
- 0 0 0.017219 0.0644951 0.0119556 0.0293205 0.103348 0.0406492 0.0273777 0.08972 0.0313669 0.0204409 0.0266916 0.00713636 0.00857582 0.0108205 0.00528186 0.00242709 0 0.00116902 0 0.000281686 0.0260376 0.0583899 0.0353505 0.0475618 0.112856 0.00448456 0.0529491 0.0800129 0.0254735 0.0320555 0.00921663 0.0148345 0.00249951 0 0 0 0 0
- 0 0 0.0099016 0.0310561 0.0335513 0.0298391 0.0407772 0.0752763 0.0231981 0.0212211 0.112587 0.0556907 0.0183333 0.011599 0.0151164 0.00220389 0.00205673 0.00113255 0.00114511 0.00204044 0 0 0.0153304 0.0435984 0.0548727 0.0318597 0.0603186 0.109503 0.0270223 0.0396705 0.0547354 0.0541534 0.0161387 0.00139019 0.0016735 0.0015721 0.00135755 6.2e-05 0 1.57e-05
- 0 0 0.00289189 0.0052322 0.0140383 0.0379809 0.0122496 0.0468438 0.076335 0.0526063 0.0381413 0.101651 0.0252214 0.0203305 0.0082591 0.0131159 0.00311709 0.0022783 0.00152427 0.00023446 0 0 0.00556384 0.00898915 0.025922 0.0752541 0.00346632 0.0375401 0.123251 0.0600507 0.0412481 0.085539 0.0466265 0.012043 0.00698101 0.0035881 0.000514291 0.00137223 0 0
- 0 0 0 0.0204963 0.0176387 0.0274754 0.0468133 0.0281591 0.0356289 0.070206 0.0529828 0.0424266 0.0921314 0.0423772 0.0238291 0.0231133 0.0051909 0.000938249 0.000680208 0.00137172 0 0 0.00502269 0.0410172 0.0113055 0.0173222 0.0628215 0.0167788 0.0789625 0.102246 0.0378402 0.0356661 0.0367372 0.0116689 0.0054852 0.00225172 0.00214661 0.000210209 0.000632152 0.000425776
- 0 0.000912045 0.0112675 0.00870376 0.0210154 0.0190851 0.0165715 0.0498741 0.0366655 0.0434511 0.0830813 0.0229476 0.0351338 0.082104 0.0394299 0.0179968 0.00643517 0.00223644 0.0015918 0.000510944 0 0.00163627 0.00977877 0.0166215 0.0531073 0.0334935 0.0265999 0.0593018 0.022735 0.0936295 0.0557162 0.0366832 0.0402218 0.0330505 0.0089384 0.00400391 0.00132386 0.00389033 0.000254649 0
- 0 0.00556898 0.0348378 0.0111975 0.025576 0.0609732 0.0121461 0.0191021 0.0333271 0.0075377 0.0578497 0.0822254 0.0178648 0.0142209 0.0813875 0.0362263 0.0251944 0.0023511 0.000661697 0.00510118 0 0.00810966 0.0451862 0.0190017 0.0158374 0.0489508 0.0217234 0.0144255 0.0671974 0.0308194 0.0386929 0.0314138 0.0383835 0.01675 0.0570777 0.0124165 0.000332292 0.000332292 0 0
- 0.000507686 0.0286413 0.0567189 0.0249161 0.0241731 0.00869032 0.045959 0.0242883 0.0210155 0.0237215 0.00829085 0.019234 0.0697697 0.01317 0.0205126 0.0653315 0.0149698 0.0121293 0.00583968 0.00405455 0.000786406 0.0544482 0.0779166 0.0410876 0.029065 0.016792 0.040656 0.0181773 0.00332037 0.00739409 0.0117484 0.0467896 0.0714296 0.018318 0.0286309 0.0238199 0.00995272 0.00295193 0.00424008 0.000541692
- 0 0.00235147 0.0913502 0.0519694 0.0476334 0.0238938 0.0112696 0.0314731 0.0100426 0.00692417 0.031667 0.0315952 0.0155194 0.0207325 0.0136284 0.00790294 0.0394919 0.0314667 0.000508615 0.0153953 0 0.0091492 0.138312 0.0875164 0.0406683 0.0266092 0.0111638 0.02848 0.0183769 0 0.0419172 0.00545912 0.00875458 0.0518027 0.00545912 0.000557582 0.0202706 0.0132904 0 0.00739737
- 0 0.0125142 0.0675897 0.104169 0.0624207 0.0119803 0.0136362 0.0127545 0.0264104 0.00650506 0.0105461 0.00531234 0.0101999 0.0209416 0.0203769 0.0149187 0.0175622 0.0173835 0.0168353 0.0119736 0 0.00785487 0.124817 0.119004 0.0920933 0.0213741 0.0321625 0.0184565 0.0123113 0.00622528 0.0048715 0.00919723 0.000779987 0.0246022 0.00957148 0.00743772 0.00860252 0.0239152 0.00509106 0.00760297
- 0 0.00996569 0.0624665 0.142074 0.0613548 0.0412717 0.0165531 0.0155725 0.0109644 0.0224369 0.00839894 0.00667532 0.00475304 0.00564175 0.0145504 0.0181273 0.0116689 0.00790267 0.0136855 0.0100543 0 0.0115625 0.0816293 0.157391 0.0817218 0.0508006 0.0134324 0.00606071 0.0140032 0.0103348 0.0111834 0.00398271 0.0093656 0.00214855 0.0155333 0.0171219 0.00891639 0.00118912 0.0106044 0.00890071
- 0 0.00327355 0.0317198 0.0621971 0.0851622 0.0743477 0.0485079 0.0240452 0.00890689 0.0190867 0.0160781 0.0155334 0.014482 0.0151156 0.0131526 0.0188375 0.0110324 0.0126396 0.0112714 0.0136093 6.09e-05 0.00253293 0.0358408 0.101471 0.115121 0.0809707 0.0529931 0.0228478 0.00751816 0.0292015 0.00397549 0.00444687 0.00586543 0.00455804 0.0155922 0.00726791 0.00433117 0.0022372 0.00320208 0.00096678
- 0 0 0.0344111 0.0424868 0.0796966 0.0772555 0.0916975 0.0327863 0.0122933 0.0179609 0.0228138 0.00625173 0.0113883 0.00336252 0.012531 0.0177013 0.0211245 0.00271226 0.00752151 0.0175138 0 0 0.0425688 0.0554003 0.0709293 0.117846 0.0648924 0.0555367 0.0101616 0.00422208 0.0111434 0.0188283 0.00334709 0.00312444 0.00585303 0.000176584 0.00938788 0.00718688 0.00324751 0.00463887
- 0 0.000504653 0.0148974 0.0881125 0.0553365 0.0772244 0.0726467 0.0454582 0.0323436 0.00788498 0.0116349 0.00573325 0.0151473 0.00400105 0.00799328 0.00350256 0.0109356 0.0151092 0.00544297 0.0267347 0 0.000601272 0.0147293 0.0931159 0.0653975 0.0624505 0.0946837 0.0592804 0.0342451 0.0024633 0.0125343 0.001118 0.0085845 0.00582315 0.00294944 0.00721861 0.00159194 0.00685901 0.0191318 0.00657856
- 0 0.000759306 0.0138012 0.0456847 0.0674599 0.0644466 0.049129 0.0890244 0.0477929 0.0341627 0.00547581 0.0189408 0.00780478 0.0167746 0.00555011 0.00918621 0.00420152 0.00472521 0.00514165 0.0291873 0 0.00144152 0.0087358 0.0453191 0.0870117 0.0512841 0.0564068 0.0645264 0.0575988 0.0220036 0.0245491 0.00908294 0.00452125 0.00869478 0.00272153 0.00486203 0.00178087 0.00466251 0.0140126 0.0115362
- 0 0 0.0202741 0.0125799 0.0524462 0.115453 0.0393947 0.0584291 0.0622356 0.0485651 0.0307731 0.0177998 0.0118525 0.00913468 0.0144467 0.0034831 0.0019399 0.000583181 0.00259277 0.0317658 0 0 0.00945196 0.0260109 0.0434851 0.0643808 0.0789437 0.0736934 0.0857555 0.0302327 0.0234861 0.00596549 0.00471189 0.00245182 0.00302846 0 0.00323621 0.00577367 0.00125407 0.00438937
- 0 0 0 0.00718134 0.0294509 0.0364382 0.0796949 0.0404605 0.0974559 0.079104 0.0485066 0.0192858 0.0050687 0.012935 0.00312095 0.0122096 0.00411502 0.00374326 0.00296389 0.0211665 0 0.000893238 0.00406854 0.0108888 0.0425504 0.0677898 0.0861376 0.0516931 0.0295143 0.0726134 0.0354481 0.0134574 0.00277273 0.0164243 0.0105262 0.0278279 0 0.00395549 0.00688044 0.0136572
- 0 6.51e-05 0.0071384 0.00436796 0.00685575 0.0129497 0.0283406 0.0841571 0.0792142 0.0718438 0.05556 0.0457336 0.0219118 0.00250438 0.00998607 0.00243086 0.0126337 0.00338259 0.00954103 0.0218237 0 8.92e-05 0.018641 0.00244674 0.0117171 0.0289825 0.0516231 0.0889671 0.0691475 0.0728759 0.0555354 0.0488021 0.0272649 0.0108255 0.0124639 0.00114414 0.00302991 0.00224098 0.000355216 0.0134076
- 0 0.00224452 0.0145814 0.0240547 0.0101538 0.00826602 0.00262364 0.00135441 0.0816553 0.0468025 0.0628039 0.120696 0.00913073 0.0303426 0.0106852 0.0221673 0.00125521 0.011278 0.00652163 0.0252635 0 0.00570159 0.0252707 0.0254653 0.0027849 0.00976123 0.00901994 0.0224344 0.0633628 0.0347768 0.0698204 0.0840226 0.075326 0.0104973 0.00643538 0.011012 0.00183044 0.00490162 0.00940717 0.0362895
- 2.32008e-05 0.00165942 0.0261849 0.0307651 0.0291515 0.00527642 0.00777236 0.0197882 0.0148419 0.0722959 0.0696882 0.0550051 0.0542739 0.0255464 0.0160016 0.0149255 0.00389888 0.00175296 0.00433383 0.0186635 0 0.00103648 0.0495764 0.0374408 0.0395291 0.0057387 0.00738381 0.0188617 0.0414876 0.114429 0.059619 0.0416418 0.0574946 0.0211054 0.00915841 0.00236967 0 0 0.00798234 0.0132961
- 0 0.022062 0.00976476 0.0356541 0.0350966 0.0167524 0.0028152 0.001581 0.00600399 0.0211681 0.0643031 0.0482784 0.0708039 0.0574499 0.0406478 0.0286176 0.0162678 0.00730014 0.00668019 0.0232201 0.000204268 0.0315434 0.0142421 0.0557937 0.0341056 0.0217038 0.0106265 0.00736918 0.00639133 0.0117984 0.0509986 0.069958 0.072597 0.030317 0.0264798 0.0160671 0.00656604 0.000410476 0.0111363 0.00722419
- 0 0.0490837 0.110483 0.0228933 0.0267576 0.0224695 0.0138476 0.0108363 0.00322959 0.00254365 0.0186896 0.0689942 0.0478871 0.0292091 0.0456907 0.0243361 0.00736794 0.00166718 1.96398e-05 0.00575521 0.00217048 0.0711186 0.142872 0.0149199 0.0413636 0.0231652 0.00417979 0 0.0191885 0.00466386 0.00890604 0.0328651 0.0355019 0.0176895 0.0348926 0.0224031 0.00634763 0.000906658 0 0.00508483
-#wt_srv_f_in
- 0.009 0.015 0.03 0.059 0.112 0.183 0.267 0.363 0.439 0.489 0.577 0.57 0.612 0.667 0.714 0.79 0.862 0.939 0.889 0.815
- 0.009 0.015 0.03 0.059 0.112 0.183 0.267 0.363 0.439 0.489 0.577 0.57 0.612 0.667 0.714 0.79 0.862 0.939 0.889 0.815
- 0.009 0.015 0.03 0.059 0.112 0.183 0.267 0.363 0.439 0.489 0.577 0.57 0.612 0.667 0.714 0.79 0.862 0.939 0.889 0.815
- 0.009 0.015 0.03 0.059 0.112 0.183 0.267 0.363 0.439 0.489 0.577 0.57 0.612 0.667 0.714 0.79 0.862 0.939 0.889 0.815
- 0.009 0.015 0.03 0.059 0.112 0.183 0.267 0.363 0.439 0.489 0.577 0.57 0.612 0.667 0.714 0.79 0.862 0.939 0.889 0.815
- 0.009 0.015 0.03 0.059 0.112 0.183 0.267 0.363 0.439 0.489 0.577 0.57 0.612 0.667 0.714 0.79 0.862 0.939 0.889 0.815
- 0.009 0.015 0.03 0.059 0.112 0.183 0.267 0.363 0.439 0.489 0.577 0.57 0.612 0.667 0.714 0.79 0.862 0.939 0.889 0.815
- 0.009 0.018 0.052 0.077 0.101 0.153 0.212 0.282 0.391 0.421 0.538 0.494 0.643 0.614 0.908 0.969 0.935 0.935 0.948 0.88
- 0.009 0.013 0.032 0.102 0.154 0.2 0.277 0.312 0.431 0.418 0.497 0.466 0.608 0.63 0.817 0.864 0.992 1.08 1.022 0.88
- 0.009 0.014 0.029 0.06 0.133 0.205 0.249 0.331 0.421 0.473 0.588 0.543 0.584 0.799 0.729 0.803 0.963 1.022 0.983 0.88
- 0.009 0.021 0.033 0.068 0.152 0.249 0.33 0.397 0.511 0.503 0.615 0.62 0.539 0.615 0.717 0.757 0.896 1.013 0.993 0.91
- 0.009 0.015 0.029 0.044 0.104 0.188 0.295 0.369 0.43 0.51 0.545 0.515 0.611 0.547 0.72 0.777 0.875 1.015 0.97 0.864
- 0.009 0.015 0.034 0.065 0.115 0.205 0.339 0.494 0.521 0.487 0.614 0.598 0.634 0.746 0.647 0.755 0.866 1.02 0.956 0.864
- 0.009 0.015 0.028 0.048 0.117 0.192 0.311 0.419 0.414 0.508 0.604 0.708 0.615 0.647 0.631 0.731 0.806 0.913 0.881 0.83
- 0.009 0.016 0.025 0.055 0.093 0.175 0.236 0.38 0.495 0.559 0.609 0.564 0.566 0.723 0.661 0.727 0.801 0.908 0.87 0.83
- 0.009 0.009 0.015 0.039 0.082 0.145 0.235 0.335 0.431 0.547 0.612 0.62 0.614 0.685 0.68 0.793 0.838 0.896 0.835 0.794
- 0.009 0.009 0.022 0.031 0.072 0.117 0.184 0.306 0.349 0.462 0.549 0.574 0.705 0.667 0.694 0.802 0.856 0.855 0.798 0.819
- 0.009 0.009 0.018 0.037 0.058 0.095 0.166 0.218 0.332 0.416 0.445 0.544 0.585 0.628 0.716 0.767 0.841 0.826 0.795 0.806
- 0.009 0.009 0.022 0.031 0.082 0.108 0.182 0.228 0.305 0.41 0.534 0.629 0.555 0.645 0.72 0.79 0.854 0.851 0.828 0.826
- 0.009 0.009 0.025 0.047 0.075 0.105 0.174 0.207 0.325 0.43 0.442 0.544 0.555 0.656 0.696 0.788 0.87 0.838 0.803 0.813
- 0.009 0.009 0.025 0.039 0.072 0.112 0.157 0.218 0.268 0.39 0.41 0.465 0.681 0.673 0.666 0.729 0.869 0.803 0.785 0.812
- 0.009 0.007 0.022 0.053 0.072 0.128 0.171 0.245 0.281 0.354 0.448 0.514 0.52 0.621 0.638 0.686 0.856 0.78 0.821 0.813
- 0.009 0.016 0.021 0.045 0.082 0.102 0.173 0.199 0.238 0.344 0.393 0.418 0.468 0.665 0.632 0.66 0.808 0.782 0.824 0.81
- 0.009 0.016 0.023 0.049 0.072 0.115 0.173 0.198 0.226 0.318 0.339 0.393 0.42 0.556 0.604 0.659 0.791 0.758 0.811 0.808
- 0.009 0.016 0.017 0.029 0.045 0.086 0.114 0.178 0.237 0.245 0.32 0.387 0.437 0.489 0.591 0.646 0.745 0.737 0.803 0.838
- 0.009 0.016 0 0.033 0.062 0.094 0.136 0.2 0.245 0.293 0.339 0.406 0.41 0.472 0.56 0.617 0.687 0.735 0.816 0.851
- 0.009 0.016 0.04 0.082 0.08 0.114 0.169 0.23 0.236 0.298 0.336 0.37 0.439 0.462 0.52 0.584 0.641 0.751 0.786 0.851
- 0.002 0.012 0.037 0.075 0.12 0.13 0.185 0.205 0.322 0.325 0.378 0.378 0.44 0.462 0.502 0.575 0.637 0.692 0.723 0.838
- 0.002 0.012 0.037 0.075 0.12 0.13 0.185 0.205 0.322 0.325 0.378 0.378 0.44 0.462 0.503 0.526 0.601 0.66 0.672 0.826
- 0.002 0.033 0.035 0.089 0.175 0.203 0.43 0.268 0.293 0.432 0.418 0.479 0.458 0.457 0.502 0.527 0.565 0.622 0.699 0.761
- 0.002 0.015 0.024 0.055 0.134 0.244 0.23 0.307 0.326 0.381 0.435 0.494 0.432 0.501 0.508 0.522 0.559 0.572 0.64 0.697
- 0.002 0.011 0.022 0.039 0.087 0.156 0.222 0.264 0.346 0.368 0.375 0.492 0.472 0.531 0.515 0.517 0.551 0.527 0.607 0.666
- 0.002 0.007 0.02 0.033 0.062 0.123 0.205 0.237 0.342 0.369 0.458 0.451 0.486 0.525 0.518 0.519 0.56 0.536 0.614 0.654
- 0.004 0.014 0.019 0.039 0.052 0.123 0.157 0.326 0.336 0.477 0.437 0.568 0.499 0.595 0.494 0.528 0.565 0.541 0.618 0.648
- 0.004 0.014 0.016 0.033 0.054 0.101 0.161 0.254 0.313 0.316 0.391 0.432 0.456 0.443 0.501 0.531 0.57 0.557 0.578 0.65
- 0.004 0.014 0.022 0.049 0.072 0.117 0.151 0.232 0.307 0.347 0.453 0.461 0.449 0.534 0.521 0.539 0.567 0.573 0.564 0.655
- 0.004 0.014 0.031 0.087 0.123 0.138 0.174 0.221 0.299 0.359 0.421 0.447 0.485 0.537 0.521 0.578 0.595 0.626 0.519 0.649
- 0.004 0.014 0.028 0.032 0.14 0.147 0.189 0.254 0.304 0.365 0.447 0.519 0.54 0.642 0.53 0.593 0.623 0.651 0.517 0.631
- 0.004 0.009 0.039 0.095 0.112 0.153 0.227 0.224 0.319 0.358 0.409 0.5 0.528 0.539 0.554 0.622 0.629 0.69 0.525 0.606
- 0.004 0.013 0.031 0.066 0.103 0.193 0.169 0.13 0.316 0.33 0.376 0.459 0.536 0.57 0.573 0.617 0.681 0.698 0.483 0.573
- 0.004 0.016 0.033 0.092 0.138 0.267 0.273 0.308 0.322 0.394 0.455 0.504 0.509 0.565 0.578 0.628 0.715 0.742 0.535 0.605
- 0 0.024 0.069 0.071 0.194 0.184 0.252 0.216 0.393 0.414 0.46 0.484 0.494 0.528 0.588 0.603 0.702 0.696 0.609 0.644
- 0.004 0.035 0.102 0.172 0.276 0.287 0.318 0.371 0.5 0.462 0.486 0.527 0.509 0.555 0.585 0.63 0.709 0.79 0.681 0.716
- 0.004 0.035 0.102 0.172 0.276 0.287 0.318 0.371 0.5 0.462 0.486 0.527 0.509 0.555 0.585 0.63 0.709 0.79 0.681 0.716
-#wt_srv_m_in
- 0.007 0.011 0.013 0.026 0.055 0.1 0.153 0.213 0.256 0.259 0.311 0.301 0.314 0.353 0.367 0.33 0.455 0.342 0.366 0.36
- 0.007 0.011 0.013 0.026 0.055 0.1 0.153 0.213 0.256 0.259 0.311 0.301 0.314 0.353 0.367 0.33 0.455 0.342 0.366 0.36
- 0.007 0.011 0.013 0.026 0.055 0.1 0.153 0.213 0.256 0.259 0.311 0.301 0.314 0.353 0.367 0.33 0.455 0.342 0.366 0.36
- 0.007 0.011 0.013 0.026 0.055 0.1 0.153 0.213 0.256 0.259 0.311 0.301 0.314 0.353 0.367 0.33 0.455 0.342 0.366 0.36
- 0.007 0.011 0.013 0.026 0.055 0.1 0.153 0.213 0.256 0.259 0.311 0.301 0.314 0.353 0.367 0.33 0.455 0.342 0.366 0.36
- 0.007 0.011 0.013 0.026 0.055 0.1 0.153 0.213 0.256 0.259 0.311 0.301 0.314 0.353 0.367 0.33 0.455 0.342 0.366 0.36
- 0.002 0.014 0.047 0.078 0.088 0.145 0.176 0.205 0.208 0.282 0.339 0.239 0.273 0.352 0.31 0.582 0.373 0.325 0.36 0.399
- 0.002 0.014 0.047 0.078 0.088 0.145 0.176 0.205 0.208 0.282 0.339 0.239 0.273 0.352 0.31 0.582 0.373 0.325 0.36 0.399
- 0.002 0.015 0.029 0.093 0.132 0.149 0.191 0.219 0.201 0.24 0.208 0.255 0.297 0.306 0.306 0.49 0.373 0.325 0.36 0.399
- 0.002 0.018 0.023 0.053 0.12 0.13 0.198 0.216 0.228 0.284 0.256 0.251 0.292 0.293 0.294 0.447 0.346 0.325 0.36 0.399
- 0.002 0.018 0.034 0.061 0.135 0.206 0.228 0.256 0.252 0.327 0.335 0.327 0.575 0.369 0.298 0.481 0.353 0.325 0.36 0.399
- 0.002 0.018 0.027 0.037 0.092 0.168 0.261 0.252 0.253 0.26 0.299 0.327 0.575 0.369 0.3 0.501 0.357 0.325 0.36 0.399
- 0.002 0.012 0.029 0.065 0.101 0.176 0.257 0.303 0.277 0.26 0.299 0.327 0.575 0.369 0.3 0.501 0.354 0.325 0.36 0.399
- 0.002 0.014 0.022 0.049 0.11 0.172 0.233 0.301 0.337 0.438 0.324 0.278 0.345 0.458 0.302 0.538 0.352 0.342 0.36 0.399
- 0.002 0.012 0.022 0.048 0.097 0.156 0.208 0.293 0.286 0.368 0.313 0.356 0.345 0.341 0.31 0.562 0.365 0.358 0.36 0.372
- 0.002 0.006 0.014 0.033 0.066 0.125 0.203 0.29 0.305 0.292 0.314 0.377 0.336 0.398 0.32 0.542 0.363 0.374 0.36 0.35
- 0.002 0.012 0.011 0.03 0.062 0.105 0.174 0.225 0.243 0.312 0.322 0.425 0.351 0.422 0.34 0.521 0.36 0.391 0.36 0.35
- 0.002 0.008 0.013 0.031 0.053 0.089 0.166 0.202 0.244 0.234 0.323 0.311 0.345 0.318 0.347 0.477 0.376 0.407 0.36 0.35
- 0.002 0.007 0.019 0.035 0.069 0.096 0.149 0.166 0.263 0.309 0.353 0.34 0.471 0.355 0.369 0.432 0.391 0.407 0.36 0.35
- 0.002 0.011 0.02 0.041 0.066 0.093 0.143 0.216 0.216 0.242 0.286 0.317 0.361 0.362 0.383 0.42 0.399 0.407 0.368 0.377
- 0.002 0.011 0.029 0.039 0.069 0.093 0.153 0.175 0.218 0.247 0.281 0.303 0.379 0.306 0.387 0.408 0.406 0.407 0.375 0.399
- 0.002 0.006 0.02 0.045 0.07 0.113 0.152 0.205 0.205 0.232 0.302 0.294 0.245 0.359 0.352 0.391 0.42 0.422 0.383 0.399
- 0.002 0.006 0.018 0.04 0.071 0.112 0.147 0.208 0.215 0.219 0.272 0.263 0.323 0.255 0.362 0.398 0.419 0.437 0.39 0.399
- 0.002 0.006 0.023 0.041 0.072 0.083 0.148 0.174 0.225 0.225 0.232 0.257 0.245 0.325 0.356 0.407 0.417 0.478 0.398 0.399
- 0.002 0.006 0.015 0.031 0.041 0.092 0.142 0.155 0.19 0.2 0.239 0.255 0.229 0.262 0.338 0.404 0.425 0.505 0.398 0.399
- 0.002 0.006 0.015 0.038 0.034 0.068 0.12 0.163 0.205 0.205 0.23 0.26 0.277 0.269 0.318 0.382 0.406 0.52 0.406 0.399
- 0.002 0.018 0.028 0.053 0.066 0.095 0.147 0.194 0.227 0.229 0.221 0.263 0.286 0.257 0.339 0.365 0.396 0.484 0.434 0.399
- 0.002 0.015 0.037 0.067 0.093 0.112 0.173 0.195 0.224 0.219 0.247 0.258 0.256 0.285 0.317 0.349 0.389 0.467 0.415 0.407
- 0.002 0.012 0.035 0.064 0.104 0.107 0.166 0.161 0.218 0.227 0.291 0.266 0.261 0.26 0.294 0.326 0.369 0.415 0.396 0.415
- 0.002 0.024 0.036 0.099 0.195 0.148 0.186 0.244 0.228 0.227 0.272 0.292 0.297 0.278 0.295 0.341 0.346 0.367 0.384 0.392
- 0.002 0.012 0.021 0.054 0.15 0.175 0.226 0.238 0.256 0.306 0.356 0.329 0.398 0.272 0.295 0.34 0.344 0.332 0.363 0.371
- 0.002 0.009 0.018 0.037 0.083 0.149 0.208 0.209 0.23 0.246 0.245 0.3 0.287 0.352 0.285 0.343 0.332 0.348 0.316 0.357
- 0.002 0.005 0.015 0.03 0.063 0.126 0.166 0.246 0.25 0.243 0.253 0.312 0.273 0.325 0.292 0.346 0.322 0.349 0.32 0.355
- 0.002 0.01 0.019 0.029 0.047 0.111 0.146 0.234 0.243 0.234 0.324 0.279 0.36 0.337 0.299 0.394 0.318 0.35 0.32 0.34
- 0.002 0.01 0.015 0.031 0.054 0.091 0.153 0.206 0.232 0.292 0.285 0.368 0.303 0.285 0.305 0.363 0.334 0.36 0.313 0.341
- 0.002 0.01 0.027 0.039 0.065 0.103 0.136 0.187 0.24 0.292 0.253 0.315 0.29 0.306 0.329 0.355 0.348 0.364 0.314 0.344
- 0.002 0.01 0.023 0.056 0.078 0.11 0.163 0.192 0.254 0.223 0.264 0.275 0.36 0.341 0.339 0.363 0.353 0.355 0.331 0.353
- 0.002 0.01 0.016 0.038 0.114 0.148 0.182 0.188 0.267 0.269 0.287 0.303 0.379 0.303 0.347 0.354 0.355 0.34 0.347 0.329
- 0.002 0.008 0.038 0.046 0.088 0.185 0.177 0.195 0.228 0.265 0.272 0.309 0.344 0.306 0.355 0.329 0.374 0.354 0.382 0.326
- 0.002 0.016 0.036 0.074 0.108 0.119 0.176 0.186 0.234 0.247 0.262 0.293 0.278 0.375 0.368 0.332 0.374 0.37 0.383 0.339
- 0.002 0.02 0.036 0.089 0.137 0.158 0.234 0.238 0.257 0.283 0.281 0.312 0.329 0.333 0.355 0.359 0.373 0.383 0.388 0.361
- 0.004 0.022 0.056 0.078 0.175 0.197 0.22 0.262 0.278 0.251 0.303 0.303 0.295 0.305 0.356 0.358 0.373 0.427 0.373 0.392
- 0.005 0.014 0.036 0.091 0.167 0.212 0.208 0.234 0.272 0.292 0.256 0.294 0.303 0.331 0.346 0.368 0.378 0.46 0.395 0.434
- 0.005 0.014 0.036 0.091 0.167 0.212 0.208 0.234 0.272 0.292 0.256 0.294 0.303 0.331 0.346 0.368 0.378 0.46 0.395 0.434
-#wt_pop_f_in
- 0.009 0.015 0.03 0.059 0.112 0.183 0.267 0.363 0.439 0.489 0.577 0.57 0.612 0.667 0.714 0.79 0.862 0.939 0.889 0.815
- 0.009 0.015 0.03 0.059 0.112 0.183 0.267 0.363 0.439 0.489 0.577 0.57 0.612 0.667 0.714 0.79 0.862 0.939 0.889 0.815
- 0.009 0.015 0.03 0.059 0.112 0.183 0.267 0.363 0.439 0.489 0.577 0.57 0.612 0.667 0.714 0.79 0.862 0.939 0.889 0.815
- 0.009 0.015 0.03 0.059 0.112 0.183 0.267 0.363 0.439 0.489 0.577 0.57 0.612 0.667 0.714 0.79 0.862 0.939 0.889 0.815
- 0.009 0.015 0.03 0.059 0.112 0.183 0.267 0.363 0.439 0.489 0.577 0.57 0.612 0.667 0.714 0.79 0.862 0.939 0.889 0.815
- 0.009 0.015 0.03 0.059 0.112 0.183 0.267 0.363 0.439 0.489 0.577 0.57 0.612 0.667 0.714 0.79 0.862 0.939 0.889 0.815
- 0.009 0.015 0.03 0.059 0.112 0.183 0.267 0.363 0.439 0.489 0.577 0.57 0.612 0.667 0.714 0.79 0.862 0.939 0.889 0.815
- 0.009 0.018 0.052 0.077 0.101 0.153 0.212 0.282 0.391 0.421 0.538 0.494 0.643 0.614 0.908 0.969 0.935 0.935 0.948 0.88
- 0.009 0.013 0.032 0.102 0.154 0.2 0.277 0.312 0.431 0.418 0.497 0.466 0.608 0.63 0.817 0.864 0.992 1.08 1.022 0.88
- 0.009 0.014 0.029 0.06 0.133 0.205 0.249 0.331 0.421 0.473 0.588 0.543 0.584 0.799 0.729 0.803 0.963 1.022 0.983 0.88
- 0.009 0.021 0.033 0.068 0.152 0.249 0.33 0.397 0.511 0.503 0.615 0.62 0.539 0.615 0.717 0.757 0.896 1.013 0.993 0.91
- 0.009 0.015 0.029 0.044 0.104 0.188 0.295 0.369 0.43 0.51 0.545 0.515 0.611 0.547 0.72 0.777 0.875 1.015 0.97 0.864
- 0.009 0.015 0.034 0.065 0.115 0.205 0.339 0.494 0.521 0.487 0.614 0.598 0.634 0.746 0.647 0.755 0.866 1.02 0.956 0.864
- 0.009 0.015 0.028 0.048 0.117 0.192 0.311 0.419 0.414 0.508 0.604 0.708 0.615 0.647 0.631 0.731 0.806 0.913 0.881 0.83
- 0.009 0.016 0.025 0.055 0.093 0.175 0.236 0.38 0.495 0.559 0.609 0.564 0.566 0.723 0.661 0.727 0.801 0.908 0.87 0.83
- 0.009 0.009 0.015 0.039 0.082 0.145 0.235 0.335 0.431 0.547 0.612 0.62 0.614 0.685 0.68 0.793 0.838 0.896 0.835 0.794
- 0.009 0.009 0.022 0.031 0.072 0.117 0.184 0.306 0.349 0.462 0.549 0.574 0.705 0.667 0.694 0.802 0.856 0.855 0.798 0.819
- 0.009 0.009 0.018 0.037 0.058 0.095 0.166 0.218 0.332 0.416 0.445 0.544 0.585 0.628 0.716 0.767 0.841 0.826 0.795 0.806
- 0.009 0.009 0.022 0.031 0.082 0.108 0.182 0.228 0.305 0.41 0.534 0.629 0.555 0.645 0.72 0.79 0.854 0.851 0.828 0.826
- 0.009 0.009 0.025 0.047 0.075 0.105 0.174 0.207 0.325 0.43 0.442 0.544 0.555 0.656 0.696 0.788 0.87 0.838 0.803 0.813
- 0.009 0.009 0.025 0.039 0.072 0.112 0.157 0.218 0.268 0.39 0.41 0.465 0.681 0.673 0.666 0.729 0.869 0.803 0.785 0.812
- 0.009 0.007 0.022 0.053 0.072 0.128 0.171 0.245 0.281 0.354 0.448 0.514 0.52 0.621 0.638 0.686 0.856 0.78 0.821 0.813
- 0.009 0.016 0.021 0.045 0.082 0.102 0.173 0.199 0.238 0.344 0.393 0.418 0.468 0.665 0.632 0.66 0.808 0.782 0.824 0.81
- 0.009 0.016 0.023 0.049 0.072 0.115 0.173 0.198 0.226 0.318 0.339 0.393 0.42 0.556 0.604 0.659 0.791 0.758 0.811 0.808
- 0.009 0.016 0.017 0.029 0.045 0.086 0.114 0.178 0.237 0.245 0.32 0.387 0.437 0.489 0.591 0.646 0.745 0.737 0.803 0.838
- 0.009 0.016 0 0.033 0.062 0.094 0.136 0.2 0.245 0.293 0.339 0.406 0.41 0.472 0.56 0.617 0.687 0.735 0.816 0.851
- 0.009 0.016 0.04 0.082 0.08 0.114 0.169 0.23 0.236 0.298 0.336 0.37 0.439 0.462 0.52 0.584 0.641 0.751 0.786 0.851
- 0.002 0.012 0.037 0.075 0.12 0.13 0.185 0.205 0.322 0.325 0.378 0.378 0.44 0.462 0.502 0.575 0.637 0.692 0.723 0.838
- 0.002 0.012 0.037 0.075 0.12 0.13 0.185 0.205 0.322 0.325 0.378 0.378 0.44 0.462 0.503 0.526 0.601 0.66 0.672 0.826
- 0.002 0.033 0.035 0.089 0.175 0.203 0.43 0.268 0.293 0.432 0.418 0.479 0.458 0.457 0.502 0.527 0.565 0.622 0.699 0.761
- 0.002 0.015 0.024 0.055 0.134 0.244 0.23 0.307 0.326 0.381 0.435 0.494 0.432 0.501 0.508 0.522 0.559 0.572 0.64 0.697
- 0.002 0.011 0.022 0.039 0.087 0.156 0.222 0.264 0.346 0.368 0.375 0.492 0.472 0.531 0.515 0.517 0.551 0.527 0.607 0.666
- 0.002 0.007 0.02 0.033 0.062 0.123 0.205 0.237 0.342 0.369 0.458 0.451 0.486 0.525 0.518 0.519 0.56 0.536 0.614 0.654
- 0.004 0.014 0.019 0.039 0.052 0.123 0.157 0.326 0.336 0.477 0.437 0.568 0.499 0.595 0.494 0.528 0.565 0.541 0.618 0.648
- 0.004 0.014 0.016 0.033 0.054 0.101 0.161 0.254 0.313 0.316 0.391 0.432 0.456 0.443 0.501 0.531 0.57 0.557 0.578 0.65
- 0.004 0.014 0.022 0.049 0.072 0.117 0.151 0.232 0.307 0.347 0.453 0.461 0.449 0.534 0.521 0.539 0.567 0.573 0.564 0.655
- 0.004 0.014 0.031 0.087 0.123 0.138 0.174 0.221 0.299 0.359 0.421 0.447 0.485 0.537 0.521 0.578 0.595 0.626 0.519 0.649
- 0.004 0.014 0.028 0.032 0.14 0.147 0.189 0.254 0.304 0.365 0.447 0.519 0.54 0.642 0.53 0.593 0.623 0.651 0.517 0.631
- 0.004 0.009 0.039 0.095 0.112 0.153 0.227 0.224 0.319 0.358 0.409 0.5 0.528 0.539 0.554 0.622 0.629 0.69 0.525 0.606
- 0.004 0.013 0.031 0.066 0.103 0.193 0.169 0.13 0.316 0.33 0.376 0.459 0.536 0.57 0.573 0.617 0.681 0.698 0.483 0.573
- 0.004 0.016 0.033 0.092 0.138 0.267 0.273 0.308 0.322 0.394 0.455 0.504 0.509 0.565 0.578 0.628 0.715 0.742 0.535 0.605
- 0 0.024 0.069 0.071 0.194 0.184 0.252 0.216 0.393 0.414 0.46 0.484 0.494 0.528 0.588 0.603 0.702 0.696 0.609 0.644
- 0.004 0.035 0.102 0.172 0.276 0.287 0.318 0.371 0.5 0.462 0.486 0.527 0.509 0.555 0.585 0.63 0.709 0.79 0.681 0.716
- 0.004 0.035 0.102 0.172 0.276 0.287 0.318 0.371 0.5 0.462 0.486 0.527 0.509 0.555 0.585 0.63 0.709 0.79 0.681 0.716
-#wt_pop_m_in
- 0.007 0.011 0.013 0.026 0.055 0.1 0.153 0.213 0.256 0.259 0.311 0.301 0.314 0.353 0.367 0.33 0.455 0.342 0.366 0.36
- 0.007 0.011 0.013 0.026 0.055 0.1 0.153 0.213 0.256 0.259 0.311 0.301 0.314 0.353 0.367 0.33 0.455 0.342 0.366 0.36
- 0.007 0.011 0.013 0.026 0.055 0.1 0.153 0.213 0.256 0.259 0.311 0.301 0.314 0.353 0.367 0.33 0.455 0.342 0.366 0.36
- 0.007 0.011 0.013 0.026 0.055 0.1 0.153 0.213 0.256 0.259 0.311 0.301 0.314 0.353 0.367 0.33 0.455 0.342 0.366 0.36
- 0.007 0.011 0.013 0.026 0.055 0.1 0.153 0.213 0.256 0.259 0.311 0.301 0.314 0.353 0.367 0.33 0.455 0.342 0.366 0.36
- 0.007 0.011 0.013 0.026 0.055 0.1 0.153 0.213 0.256 0.259 0.311 0.301 0.314 0.353 0.367 0.33 0.455 0.342 0.366 0.36
- 0.002 0.014 0.047 0.078 0.088 0.145 0.176 0.205 0.208 0.282 0.339 0.239 0.273 0.352 0.31 0.582 0.373 0.325 0.36 0.399
- 0.002 0.014 0.047 0.078 0.088 0.145 0.176 0.205 0.208 0.282 0.339 0.239 0.273 0.352 0.31 0.582 0.373 0.325 0.36 0.399
- 0.002 0.015 0.029 0.093 0.132 0.149 0.191 0.219 0.201 0.24 0.208 0.255 0.297 0.306 0.306 0.49 0.373 0.325 0.36 0.399
- 0.002 0.018 0.023 0.053 0.12 0.13 0.198 0.216 0.228 0.284 0.256 0.251 0.292 0.293 0.294 0.447 0.346 0.325 0.36 0.399
- 0.002 0.018 0.034 0.061 0.135 0.206 0.228 0.256 0.252 0.327 0.335 0.327 0.575 0.369 0.298 0.481 0.353 0.325 0.36 0.399
- 0.002 0.018 0.027 0.037 0.092 0.168 0.261 0.252 0.253 0.26 0.299 0.327 0.575 0.369 0.3 0.501 0.357 0.325 0.36 0.399
- 0.002 0.012 0.029 0.065 0.101 0.176 0.257 0.303 0.277 0.26 0.299 0.327 0.575 0.369 0.3 0.501 0.354 0.325 0.36 0.399
- 0.002 0.014 0.022 0.049 0.11 0.172 0.233 0.301 0.337 0.438 0.324 0.278 0.345 0.458 0.302 0.538 0.352 0.342 0.36 0.399
- 0.002 0.012 0.022 0.048 0.097 0.156 0.208 0.293 0.286 0.368 0.313 0.356 0.345 0.341 0.31 0.562 0.365 0.358 0.36 0.372
- 0.002 0.006 0.014 0.033 0.066 0.125 0.203 0.29 0.305 0.292 0.314 0.377 0.336 0.398 0.32 0.542 0.363 0.374 0.36 0.35
- 0.002 0.012 0.011 0.03 0.062 0.105 0.174 0.225 0.243 0.312 0.322 0.425 0.351 0.422 0.34 0.521 0.36 0.391 0.36 0.35
- 0.002 0.008 0.013 0.031 0.053 0.089 0.166 0.202 0.244 0.234 0.323 0.311 0.345 0.318 0.347 0.477 0.376 0.407 0.36 0.35
- 0.002 0.007 0.019 0.035 0.069 0.096 0.149 0.166 0.263 0.309 0.353 0.34 0.471 0.355 0.369 0.432 0.391 0.407 0.36 0.35
- 0.002 0.011 0.02 0.041 0.066 0.093 0.143 0.216 0.216 0.242 0.286 0.317 0.361 0.362 0.383 0.42 0.399 0.407 0.368 0.377
- 0.002 0.011 0.029 0.039 0.069 0.093 0.153 0.175 0.218 0.247 0.281 0.303 0.379 0.306 0.387 0.408 0.406 0.407 0.375 0.399
- 0.002 0.006 0.02 0.045 0.07 0.113 0.152 0.205 0.205 0.232 0.302 0.294 0.245 0.359 0.352 0.391 0.42 0.422 0.383 0.399
- 0.002 0.006 0.018 0.04 0.071 0.112 0.147 0.208 0.215 0.219 0.272 0.263 0.323 0.255 0.362 0.398 0.419 0.437 0.39 0.399
- 0.002 0.006 0.023 0.041 0.072 0.083 0.148 0.174 0.225 0.225 0.232 0.257 0.245 0.325 0.356 0.407 0.417 0.478 0.398 0.399
- 0.002 0.006 0.015 0.031 0.041 0.092 0.142 0.155 0.19 0.2 0.239 0.255 0.229 0.262 0.338 0.404 0.425 0.505 0.398 0.399
- 0.002 0.006 0.015 0.038 0.034 0.068 0.12 0.163 0.205 0.205 0.23 0.26 0.277 0.269 0.318 0.382 0.406 0.52 0.406 0.399
- 0.002 0.018 0.028 0.053 0.066 0.095 0.147 0.194 0.227 0.229 0.221 0.263 0.286 0.257 0.339 0.365 0.396 0.484 0.434 0.399
- 0.002 0.015 0.037 0.067 0.093 0.112 0.173 0.195 0.224 0.219 0.247 0.258 0.256 0.285 0.317 0.349 0.389 0.467 0.415 0.407
- 0.002 0.012 0.035 0.064 0.104 0.107 0.166 0.161 0.218 0.227 0.291 0.266 0.261 0.26 0.294 0.326 0.369 0.415 0.396 0.415
- 0.002 0.024 0.036 0.099 0.195 0.148 0.186 0.244 0.228 0.227 0.272 0.292 0.297 0.278 0.295 0.341 0.346 0.367 0.384 0.392
- 0.002 0.012 0.021 0.054 0.15 0.175 0.226 0.238 0.256 0.306 0.356 0.329 0.398 0.272 0.295 0.34 0.344 0.332 0.363 0.371
- 0.002 0.009 0.018 0.037 0.083 0.149 0.208 0.209 0.23 0.246 0.245 0.3 0.287 0.352 0.285 0.343 0.332 0.348 0.316 0.357
- 0.002 0.005 0.015 0.03 0.063 0.126 0.166 0.246 0.25 0.243 0.253 0.312 0.273 0.325 0.292 0.346 0.322 0.349 0.32 0.355
- 0.002 0.01 0.019 0.029 0.047 0.111 0.146 0.234 0.243 0.234 0.324 0.279 0.36 0.337 0.299 0.394 0.318 0.35 0.32 0.34
- 0.002 0.01 0.015 0.031 0.054 0.091 0.153 0.206 0.232 0.292 0.285 0.368 0.303 0.285 0.305 0.363 0.334 0.36 0.313 0.341
- 0.002 0.01 0.027 0.039 0.065 0.103 0.136 0.187 0.24 0.292 0.253 0.315 0.29 0.306 0.329 0.355 0.348 0.364 0.314 0.344
- 0.002 0.01 0.023 0.056 0.078 0.11 0.163 0.192 0.254 0.223 0.264 0.275 0.36 0.341 0.339 0.363 0.353 0.355 0.331 0.353
- 0.002 0.01 0.016 0.038 0.114 0.148 0.182 0.188 0.267 0.269 0.287 0.303 0.379 0.303 0.347 0.354 0.355 0.34 0.347 0.329
- 0.002 0.008 0.038 0.046 0.088 0.185 0.177 0.195 0.228 0.265 0.272 0.309 0.344 0.306 0.355 0.329 0.374 0.354 0.382 0.326
- 0.002 0.016 0.036 0.074 0.108 0.119 0.176 0.186 0.234 0.247 0.262 0.293 0.278 0.375 0.368 0.332 0.374 0.37 0.383 0.339
- 0.002 0.02 0.036 0.089 0.137 0.158 0.234 0.238 0.257 0.283 0.281 0.312 0.329 0.333 0.355 0.359 0.373 0.383 0.388 0.361
- 0.004 0.022 0.056 0.078 0.175 0.197 0.22 0.262 0.278 0.251 0.303 0.303 0.295 0.305 0.356 0.358 0.373 0.427 0.373 0.392
- 0.005 0.014 0.036 0.091 0.167 0.212 0.208 0.234 0.272 0.292 0.256 0.294 0.303 0.331 0.346 0.368 0.378 0.46 0.395 0.434
- 0.005 0.014 0.036 0.091 0.167 0.212 0.208 0.234 0.272 0.292 0.256 0.294 0.303 0.331 0.346 0.368 0.378 0.46 0.395 0.434
-#maturity
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
- 0 0 0 0 0.001 0.008 0.061 0.2 0.505 0.75 0.888 0.929 0.955 0.979 0.983 0.991 0.996 0.997 0.997 0.997
-#init_age_comp
-1
-#n_env_cov
- 0
-#env_cov
-
-#spawnmo
-2
-#srv_mo
- 7
-#n_wts
- 2 24 40 49 87 77 57 79 39 44 42 53 53 41 19 16 12 4 4 16
- 0 1 3 29 43 94 95 45 60 45 38 61 55 43 51 20 13 10 0 20
- 0 0 11 55 82 79 79 61 53 56 58 38 42 43 53 34 21 12 5 34
- 0 0 5 33 89 125 60 80 67 38 45 41 37 40 44 42 24 20 3 42
- 0 0 2 9 40 86 162 53 66 48 46 34 39 30 35 27 32 11 12 27
- 0 0 1 20 26 173 89 122 45 39 42 31 34 22 24 29 24 23 25 29
- 0 0 2 3 52 7 146 69 51 12 19 15 18 31 19 10 12 12 16 10
- 0 0 1 6 27 121 31 199 89 59 13 16 27 19 28 17 10 8 22 17
- 0 0 2 18 27 62 151 31 187 58 56 12 13 17 9 26 21 13 14 26
- 0 0 1 20 44 19 45 134 15 170 38 57 11 17 12 19 24 18 7 19
- 0 0 1 31 57 54 23 26 91 11 98 14 32 11 14 19 12 18 12 19
- 0 0 3 11 36 58 32 21 21 111 8 93 15 17 8 9 13 16 8 9
- 0 2 6 9 17 45 78 45 32 21 94 1 61 5 25 10 5 8 16 10
- 0 0 3 35 33 26 79 67 22 21 7 85 3 96 13 12 18 11 14 12
- 0 0 5 16 122 36 28 44 43 28 17 21 71 14 89 15 12 16 15 15
- 0 0 10 40 51 84 21 18 37 18 11 16 12 46 6 30 7 11 8 30
- 0 0 7 15 41 49 101 31 27 32 35 33 15 16 21 9 40 20 14 9
- 0 0 2 32 48 55 57 176 33 25 57 42 26 12 16 32 20 41 21 32
- 0 0 1 4 29 23 28 63 92 20 30 25 21 12 15 16 24 24 30 16
- 0 2 1 15 31 80 42 59 64 88 34 11 21 13 11 17 11 21 8 17
- 0 0 11 22 28 45 120 56 55 43 75 32 15 32 19 20 14 15 23 20
- 0 0 6 24 43 42 41 158 35 44 24 36 17 9 20 18 13 11 14 18
- 1 13 24 42 89 81 42 40 112 24 15 20 24 12 5 20 19 12 9 20
- 0 6 27 48 31 71 59 26 47 94 15 12 15 20 10 7 16 11 12 7
- 0 1 20 40 44 28 48 34 18 22 41 9 10 9 8 9 3 8 12 9
- 0 1 13 105 73 79 47 83 39 19 32 57 15 19 16 12 14 18 16 12
- 0 0 4 16 119 102 99 68 75 34 21 35 53 16 11 11 20 11 13 11
- 0 1 7 18 27 144 90 95 48 39 38 18 17 35 13 9 7 10 14 9
- 0 0 9 45 70 66 149 82 80 32 35 21 15 16 23 14 8 14 21 11
- 0 0 9 45 70 66 149 82 80 32 35 21 15 16 23 14 8 14 21 11
- 0 0 9 45 70 66 149 82 80 32 35 21 15 16 23 14 8 14 21 11
-#growth_cov
- 0.468534 0.477176 0.056903 -0.286957 1.40687 1.44508 0.489911 0.897448 0.69368 0.57906 0.0951096 0.438969 0.426234 0.337085 1.49602 0.642738 0.910184 0.566324 -1.3058 -0.796378 -0.427047 0.515382 -0.719965 -1.50957 0.680944 1.40687 1.49602 1.19037 1.9545 -1.01288 0.540853 -1.01288 -1.28033 -1.19118 0.388027 -0.337899 -0.146866 -0.325163 -0.490725 -0.834585 0.846506 -0.669023 -1.03835 0.413498
diff --git a/assessments/nrs/data/nrs_2018.dat b/assessments/nrs/data/nrs_2018.dat
index a8653df..07b08d4 100644
--- a/assessments/nrs/data/nrs_2018.dat
+++ b/assessments/nrs/data/nrs_2018.dat
@@ -66,50 +66,51 @@
 #	wt_fsh	(begin	year	to	end	year)																																																								
 #	Female	Female	Female	Female	Female	Female	Female	Female	Female	Female	Female	Female	Female	Female	Female	Female	Female	Female	Female	Male	Male	Male	Male	Male	Male	Male	Male	Male	Male	Male	Male	Male	Male	Male	Male	Male	Male	Male	Male																							
 #	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20																							
-0.009	0.015	0.03	0.059	0.112	0.183	0.267	0.363	0.439	0.489	0.577	0.57	0.612	0.667	0.714	0.79	0.862	0.939	0.889	0.815	0.007	0.011	0.013	0.026	0.055	0.1	0.153	0.213	0.256	0.259	0.311	0.301	0.314	0.353	0.367	0.33	0.455	0.342	0.366	0.36																							
-0.009	0.015	0.03	0.059	0.112	0.183	0.267	0.363	0.439	0.489	0.577	0.57	0.612	0.667	0.714	0.79	0.862	0.939	0.889	0.815	0.007	0.011	0.013	0.026	0.055	0.1	0.153	0.213	0.256	0.259	0.311	0.301	0.314	0.353	0.367	0.33	0.455	0.342	0.366	0.36																							
-0.009	0.015	0.03	0.059	0.112	0.183	0.267	0.363	0.439	0.489	0.577	0.57	0.612	0.667	0.714	0.79	0.862	0.939	0.889	0.815	0.007	0.011	0.013	0.026	0.055	0.1	0.153	0.213	0.256	0.259	0.311	0.301	0.314	0.353	0.367	0.33	0.455	0.342	0.366	0.36																							
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+9	15	30	59	112	183	267	363	439	489	577	570	612	667	714	790	862	939	889	815	7	11	13	26	55	100	153	213	256	259	311	301	314	353	367	330	455	342	366	360
+9	15	30	59	112	183	267	363	439	489	577	570	612	667	714	790	862	939	889	815	7	11	13	26	55	100	153	213	256	259	311	301	314	353	367	330	455	342	366	360
+9	15	30	59	112	183	267	363	439	489	577	570	612	667	714	790	862	939	889	815	7	11	13	26	55	100	153	213	256	259	311	301	314	353	367	330	455	342	366	360
+9	15	30	59	112	183	267	363	439	489	577	570	612	667	714	790	862	939	889	815	7	11	13	26	55	100	153	213	256	259	311	301	314	353	367	330	455	342	366	360
+9	15	30	59	112	183	267	363	439	489	577	570	612	667	714	790	862	939	889	815	7	11	13	26	55	100	153	213	256	259	311	301	314	353	367	330	455	342	366	360
+9	15	30	59	112	183	267	363	439	489	577	570	612	667	714	790	862	939	889	815	7	11	13	26	55	100	153	213	256	259	311	301	314	353	367	330	455	342	366	360
+9	15	30	59	112	183	267	363	439	489	577	570	612	667	714	790	862	939	889	815	7	11	13	26	55	100	153	213	256	259	311	301	314	353	367	330	455	342	366	360
+9	15	30	59	112	183	267	363	439	489	577	570	612	667	714	790	862	939	889	815	7	11	13	26	55	100	153	213	256	259	311	301	314	353	367	330	455	342	366	360
+9	14	29	56	101	159	233	312	386	441	517	531	573	634	666	730	810	862	844	817	7	11	16	32	59	99	152	203	244	250	299	295	311	336	355	339	435	379	384	386
+9	12	27	53	90	134	199	261	332	393	457	491	535	600	619	670	758	785	799	819	7	11	20	38	63	97	151	194	233	241	286	289	309	318	343	348	414	416	402	412
+9	11	26	50	78	110	165	211	278	346	397	452	496	566	571	610	707	709	753	821	7	10	23	44	67	96	151	185	221	232	273	282	307	301	330	357	393	453	420	438
+9	11	26	50	78	110	165	211	278	346	397	452	496	566	571	610	707	709	753	821	7	10	23	44	67	96	151	185	221	232	273	282	307	301	330	357	393	453	420	438
+9	11	26	50	78	110	165	211	278	346	397	452	496	566	571	610	707	709	753	821	7	10	23	44	67	96	151	185	221	232	273	282	307	301	330	357	393	453	420	438
+9	11	26	50	78	110	165	211	278	346	397	452	496	566	571	610	707	709	753	821	7	10	23	44	67	96	151	185	221	232	273	282	307	301	330	357	393	453	420	438
+9	11	26	50	78	110	165	211	278	346	397	452	496	566	571	610	707	709	753	821	7	10	23	44	67	96	151	185	221	232	273	282	307	301	330	357	393	453	420	438
+9	11	26	50	78	110	165	211	278	346	397	452	496	566	571	610	707	709	753	821	7	10	23	44	67	96	151	185	221	232	273	282	307	301	330	357	393	453	420	438
+9	11	26	50	78	110	165	211	278	346	397	452	496	566	571	610	707	709	753	821	7	10	23	44	67	96	151	185	221	232	273	282	307	301	330	357	393	453	420	438
+9	11	26	50	78	110	165	211	278	346	397	452	496	566	571	610	707	709	753	821	7	10	23	44	67	96	151	185	221	232	273	282	307	301	330	357	393	453	420	438
+9	11	26	50	78	110	165	211	278	346	397	452	496	566	571	610	707	709	753	821	7	10	23	44	67	96	151	185	221	232	273	282	307	301	330	357	393	453	420	438
+9	11	26	50	78	110	165	211	278	346	397	452	496	566	571	610	707	709	753	821	7	10	23	44	67	96	151	185	221	232	273	282	307	301	330	357	393	453	420	438
+9	13	26	51	90	134	201	230	294	359	405	461	485	545	552	581	659	651	711	758	7	11	23	47	86	114	166	201	228	243	276	291	309	303	319	358	369	418	387	403
+9	15	26	53	102	158	236	249	311	373	413	470	473	524	533	552	611	594	668	695	7	12	23	51	104	132	181	218	234	254	279	300	311	305	308	359	345	383	354	369
+9	17	25	54	114	181	272	269	327	387	421	479	462	504	514	523	562	537	626	632	7	13	23	55	123	149	196	234	241	265	282	308	314	307	297	360	321	348	321	335
+9	17	25	54	114	181	272	269	327	387	421	479	462	504	514	523	562	537	626	632	7	13	23	55	123	149	196	234	241	265	282	308	314	307	297	360	321	348	321	335
+9	17	25	54	114	181	272	269	327	387	421	479	462	504	514	523	562	537	626	632	7	13	23	55	123	149	196	234	241	265	282	308	314	307	297	360	321	348	321	335
+9	17	25	54	114	181	272	269	327	387	421	479	462	504	514	523	562	537	626	632	7	13	23	55	123	149	196	234	241	265	282	308	314	307	297	360	321	348	321	335
+9	17	25	54	114	181	272	269	327	387	421	479	462	504	514	523	562	537	626	632	7	13	23	55	123	149	196	234	241	265	282	308	314	307	297	360	321	348	321	335
+9	17	25	54	114	181	272	269	327	387	421	479	462	504	514	523	562	537	626	632	7	13	23	55	123	149	196	234	241	265	282	308	314	307	297	360	321	348	321	335
+9	17	25	54	114	181	272	269	327	387	421	479	462	504	514	523	562	537	626	632	7	13	23	55	123	149	196	234	241	265	282	308	314	307	297	360	321	348	321	335
+9	17	25	54	114	181	272	269	327	387	421	479	462	504	514	523	562	537	626	632	7	13	23	55	123	149	196	234	241	265	282	308	314	307	297	360	321	348	321	335
+9	17	25	54	114	181	272	269	327	387	421	479	462	504	514	523	562	537	626	632	7	13	23	55	123	149	196	234	241	265	282	308	314	307	297	360	321	348	321	335
+9	17	25	54	114	181	272	269	327	387	421	479	462	504	514	523	562	537	626	632	7	13	23	55	123	149	196	234	241	265	282	308	314	307	297	360	321	348	321	335
+9	17	25	54	114	181	272	269	327	387	421	479	462	504	514	523	562	537	626	632	7	13	23	55	123	149	196	234	241	265	282	308	314	307	297	360	321	348	321	335
+9	17	25	54	114	181	272	269	327	387	421	479	462	504	514	523	562	537	626	632	7	13	23	55	123	149	196	234	241	265	282	308	314	307	297	360	321	348	321	335
+9	17	25	54	114	181	272	269	327	387	421	479	462	504	514	523	562	537	626	632	7	13	23	55	123	149	196	234	241	265	282	308	314	307	297	360	321	348	321	335
 #	nsmpl_fsh_age(1	nfsh	1	nyrs_fish_age)																																																										
 200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	200	
 #	nsrv																																																													
diff --git a/assessments/yfs/runs/surveyloss/orig/Makefile b/assessments/yfs/runs/surveyloss/orig/Makefile
index aff2b96..c76b22e 100644
--- a/assessments/yfs/runs/surveyloss/orig/Makefile
+++ b/assessments/yfs/runs/surveyloss/orig/Makefile
@@ -1,7 +1,6 @@
 EXEC = fm
 DIST = ../../../../../../src/
 ARGS = -nox -iprint 50 
-ARGS = -nox -iprint 50 -hbf 1
 
 ts := $(shell /bin/date "+%Y-%m-%d---%H-%M-%S")
 pn = fmpl_$(ts)
diff --git a/assessments/yfs/runs/surveyloss/orig/mod.ctl b/assessments/yfs/runs/surveyloss/orig/mod.ctl
index 6ea49d8..bdc989f 100644
--- a/assessments/yfs/runs/surveyloss/orig/mod.ctl
+++ b/assessments/yfs/runs/surveyloss/orig/mod.ctl
@@ -13,11 +13,11 @@
 #phase_mn_f
 	2
 #phase_F40           
-	6
+	4
 #phase_fmort        
 	3
 #phase_proj        
-	7
+	8
 #phase_logist_sel    
 	5
 #phase_logist_sel_devs    
@@ -49,9 +49,9 @@
 #pf_sigma    
 	0.05
 #a50_sigma   
-	0.2
+	0.1
 #slp_sigma   
-	0.4
+	0.2
 #q_exp   
 	1
 #q_sigma
@@ -67,7 +67,7 @@
 #nselages            
 	17
 #lambda
-1 1 300 -1 1 1 1 1 1 1 	
+1 1 200 -1 1 1 1 1 1 1 	
 #styr_sr         
 	1978
 #endyr_sr       
diff --git a/assessments/yfs/runs/surveyloss/yfs_red.R b/assessments/yfs/runs/surveyloss/yfs_red.R
index a9117ae..e6ec122 100644
--- a/assessments/yfs/runs/surveyloss/yfs_red.R
+++ b/assessments/yfs/runs/surveyloss/yfs_red.R
@@ -64,25 +64,33 @@ spp="yfs"
 #6.3. Get projection results
 ############################################################################################################################################################
 #files to copy to retrospective subfolders
-j=1
+j=2
+i=10
 #retro_sub = "retro" or "survRed_retro"
 	#6.1. Run for full time series
 	#Create main retrospective subfolder
+do_run <- FALSE
 df_res <- NULL
 for(j in 1:length(retros_sub)) {
+	setwd(master)
 	cpto <- 	paste0(main_dir,"/",retros_sub[j],"0" )
 	fc <- paste0("mkdir -p ",cpto," ; cp orig/* ",cpto)
 	system("fc")  #IS added "fc"
 	#Command line to run assessment model *.exe
 	setwd(file.path(main_dir,paste0(retros_sub[j],"0")))
-	system("make") #### CHANGE TO WHATEVER YOUR EXE IS CALLED 
+	if (do_run) system("rm fm.std; make") #### CHANGE TO WHATEVER YOUR EXE IS CALLED 
 	#6.2 Get tier one projections
 	dftmp        <- data.frame(read.table("ABC_OFL.rep",header=TRUE))
 	dftmp$peel   <- 0
 	dftmp$retros <- retros_sub[j] 
 	df_res       <- rbind(df_res,dftmp)
+<<<<<<< HEAD
 	setwd(master)
 	for(i in 0:length(endyrvec)){
+=======
+	for(i in 1:length(endyrvec)){
+	  setwd(master)
+>>>>>>> 85e590bda024c8467c4a2fe9a16e3e9e3af480cc
 	  cpto <- 	paste0(main_dir,"/",retros_sub[j],i )
 	  fc <- paste0("mkdir -p ",cpto," ; cp orig/* ",cpto)
 	  system(fc)
@@ -91,18 +99,17 @@ for(j in 1:length(retros_sub)) {
 	  ctl$n_retro     <- i
 	  ctl$surv_dwnwt  <- j-1
 	  write_dat(ctl,"mod.ctl")
-	  system("make") #### CHANGE TO WHATEVER YOUR EXE IS CALLED 
+	  if (do_run) system("rm fm.std; make") #### CHANGE TO WHATEVER YOUR EXE IS CALLED 
 	  dftmp        <- data.frame(read.table("ABC_OFL.rep",header=TRUE))
 	  dftmp$peel   <- -i
 	  dftmp$retros <- retros_sub[j] 
 	  df_res       <- rbind(df_res,dftmp)
-	  setwd(master)
 	}	
 }
 setwd(master)
 
 
-6. Summarize results
+#6. Summarize results
 write.csv(df_res,"yfs_results.csv")
 names(df_res)
 # Some dumb figure----------
@@ -111,10 +118,11 @@ ggplot(aes(x=Endyr,y=SSB,color=retros)) + geom_line(size=2) + theme_few()
 
 # Pool up retro results------------------
 df_retro <- data.frame(matrix(ncol=9,nrow=0, dimnames=list(NULL, c("Year","Peel","SSB","SSB_sd","Totbio","Totbio_sd","Rec","Rec_sd","run"))))
-j=1; i=2
+j=1; i=4
 for(j in 1:length(retros_sub)) {
-	for(i in 1:length(endyrvec)){
+	for(i in 0:length(endyrvec)){
 	  retro_dir <- 	paste0(main_dir,"/",retros_sub[j],i )
+	  print(c(retros_sub[j],i ))
 	  rep <- read_rep(paste0(retro_dir,"/fm.rep"))
 	  df_tmp <- data.frame(
 	  	Year      = rep$SSB[,1],
@@ -132,6 +140,7 @@ for(j in 1:length(retros_sub)) {
 	  df_retro <- rbind(df_retro,df_tmp)
   }
 }
+setwd(master)
 write.csv(df_retro,"yfs_retros.csv")
 
 ###--jim stopped here...-------------------------------------
diff --git a/src/fm.tpl b/src/fm.tpl
index c62e802..0ba540a 100644
--- a/src/fm.tpl
+++ b/src/fm.tpl
@@ -1010,8 +1010,6 @@ PROCEDURE_SECTION
     get_numbers_at_age();
     //if(active(R_logalpha))
     compute_sr_fit();
-
-
     if (sd_phase() || mceval_phase())
     {
       get_msy();
@@ -1598,6 +1596,9 @@ FUNCTION compute_sr_fit
   // sigmaR = 0.6;
   R_alpha=mfexp(R_logalpha);
   R_beta=mfexp(R_logbeta);
+  //R_alpha= 0.0160063;
+  // = 0.00302922;
+	
   for (int i=styr_sr; i <= endyr_sr; i++)
   {
     SAM_recruits(i)= 2.*natage_f(i,1);
@@ -1892,6 +1893,8 @@ FUNCTION write_srec
   phizero=get_spr(0.0);
   // cout<<phizero<<endl;
   dvariable Rzero = -(log(1/(R_alpha*phizero)))/(phizero*R_beta);   // Ricker formulation of equilibrium recruitment at each F
+       // rechat(i)  = R_alpha*SRR_SSB(i)*(mfexp(-R_beta*SRR_SSB(i)));
+	cout<<phizero<<" R0 "<<Rzero<<endl;
   dvariable Bzero = Rzero*phizero;
   dvariable Btmp  =  .8*Bzero;
   srecpar << "# Bzero,  PhiZero,  Alpha, sigmaR"<<endl;
@@ -1998,7 +2001,7 @@ REPORT_SECTION
 	nLogPosterior(ilike) = fpen       ; ilike++;
 
   for (int i=0;i<=3;i++)
-    {
+  {
       dvar_vector incr_dev_tmp(2,nages);
       incr_dev_tmp(5,nages-5)     = growth_alpha * double(i) ;
       incr_dev_tmp(nages-4,nages) = incr_dev_tmp(nages-5) ;
@@ -2006,15 +2009,15 @@ REPORT_SECTION
       wt_pop_tmp_f(1)        = wt_vbg_f(1);
       wt_pop_tmp_f(2,nages)  = ++wt_vbg_f(1,nages-1) + elem_prod(base_incr_f,mfexp(incr_dev_tmp)) ; // initializes estimates to correct values...
       report <<i<<" "<<double(i)*growth_alpha<<" "<<wt_pop_tmp_f<<endl;
-    }
-    report << "wt_pop_f"<<endl;
-    report << wt_pop_f<<endl;
-    report << "wt_pop_m"<<endl;
-    report << wt_pop_m<<endl;
+  }
+  report << "wt_pop_f"<<endl;
+  report << wt_pop_f  <<endl;
+  report << "wt_pop_m"<<endl;
+  report << wt_pop_m  <<endl;
   // This section to write s-rec parameters to input file for projection model
   // need Rzero, phizero calculated then use alpha and beta
-  if (active(R_logbeta))
-    write_srec();
+  // if (active(R_logbeta))
+  write_srec();
   cout<<"Done with phase "<<current_phase()<<" --in report file"<<endl;
   cout<<wt_pop_mn_f(4,10)<<endl;
   cout<<wt_fsh_mn_f(4,10)<<endl;
@@ -2467,7 +2470,6 @@ REPORT_SECTION
  
 BETWEEN_PHASES_SECTION
   // Set the msy selectivity to something reasonable???
-
   log_msy_sel_f = log_sel_fsh_f(1,endyr-2);
   log_msy_sel_m = log_sel_fsh_m(1,endyr-2);