diff --git a/2024/runs/bholt_long_noprior/Makefile b/2024/runs/bholt_long_noprior/Makefile new file mode 100644 index 0000000..d9fddf1 --- /dev/null +++ b/2024/runs/bholt_long_noprior/Makefile @@ -0,0 +1,59 @@ +EXEC = pm +PROJ = spm + PROJDIST = ~/_mymods/afsc-assessments/spmR/src/ +ifeq ($(SAFE),TRUE) + DIST = ../../../source/ +else + DIST = ../../../source/ +endif +ARGS = -nox -iprint 150 +ARGS2 = -nox -iprint 150 -binp pm.bar -phase 22 -sdonly + +ifdef ComSpec + RM=del /F /Q +else + RM=rm -rf +endif + +all: mpd $(DIST)$(EXEC).tpl +$(EXEC): $(DIST)$(EXEC).tpl + ln -sf $(DIST)$(EXEC) $@ + ln -sf $(DIST)$(EXEC).tpl $@.tpl + ln -sf $(PROJDIST)$(PROJ) $(PROJ) + +$(DIST)$(EXEC).tpl: + $(MAKE) --directory=../../src + + +mpd: $(EXEC) + ./$(EXEC) $(ARGS) + @$(RM) $(EXEC).*[0123456789] *.rpt *.log variance gradient.* *tmp admodel.* *.eva + +mcmc: $(EXEC) + ./$(EXEC) $(ARGS) -mcmc 3000000 -mcsave 600 + ./$(EXEC) -mceval + +proj: $(EXEC) + ./$(EXEC) $(ARGS2) + $(MAKE) --directory=proj + +debug: $(EXEC) + ./$(EXEC) $(ARGS) + +plot: + R CMD BATCH plot.R + +clean: + @$(RM) $(EXEC) + @$(RM) $(EXEC) $(EXEC).[brces]* $(EXEC).*[0123456789] *.rpt *.log variance gradient.* *tmp + @$(RM) admodel.* + @$(RM) checkfile.rep + @$(RM) mcout.rep + @$(RM) plot.Rout + @$(RM) Rplots.pdf + @$(RM) *.rep + @$(RM) Fprof.yld + @$(RM) *.prj + @$(RM) pm.par + @$(RM) SIS_out.rep + @$(RM) mceval.dat diff --git a/2024/runs/bholt_long_noprior/README.md b/2024/runs/bholt_long_noprior/README.md new file mode 100644 index 0000000..c42021b --- /dev/null +++ b/2024/runs/bholt_long_noprior/README.md @@ -0,0 +1,2 @@ +#Simple directory containing the bare minimum files to start a run using pm(.tpl) + diff --git a/2024/runs/bholt_long_noprior/compweights.ctl b/2024/runs/bholt_long_noprior/compweights.ctl new file mode 100644 index 0000000..cf8edad --- /dev/null +++ b/2024/runs/bholt_long_noprior/compweights.ctl @@ -0,0 +1 @@ +1.0 1.0 1.0 1.0 \ No newline at end of file diff --git a/2024/runs/bholt_long_noprior/control.dat b/2024/runs/bholt_long_noprior/control.dat new file mode 100644 index 0000000..5fb8077 --- /dev/null +++ b/2024/runs/bholt_long_noprior/control.dat @@ -0,0 +1,175 @@ +#DoCovBTS +1 +#SrType +2 +#Do_Combined +0 +#use_age_err +0 +#use_age1_ats +1 +#age1_sigma_ats +1 +#use_endyr_len +0 +#use_popwts_ssb +1 +#natmortprior +0.3 +#cvnatmortprior +0.1 +#natmort_in +0.9 +0.45 +0.3 +0.3 +0.3 +0.3 +0.3 +0.3 +0.3 +0.3 +0.3 +0.3 +0.3 +0.3 +0.3 +#q_all_prior +0 +#q_all_sigma +2 +#q_bts_prior +0 +#q_bts_sigma +2 +#sigrprior +1 +#cvsigrprior +0.2 +#phase_sigr +6 +#steepnessprior +0.6 +#cvsteepnessprior +10.12 +#phase_steepness +5 +#use_spr_msy_pen +0 +#sigma_spr_msy +0.20 +#use_last_ats_ac +1 +#nyrs_sel_avg +2 +#do_bts_bio +1 +#do_ats_bio +1 +#srprior_a +14.93209877 +#srprior_b +14.93209877 +#nyrs_future +5 +#next_yrs_catch +1350 +#nscen +8 +#fixed_catch_fut2 +1400 +#fixed_catch_fut3 +1200 +#phase_F40 +6 +#robust_phase +1350 +#ats_robust_phase +1350 +#ats_like_type +0 +#phase_logist_fsh +-1 +#phase_logist_bts +2 +#phase_seldevs_fsh +4 +#phase_seldevs_bts +5 +#phase_age1devs_bts +3 +#phase_selcoffs_ats +3 +#phase_sel_ats_dev +5 +#phase_natmort +-6 +#phase_q_bts +3 +#phase_q_std_area +-4 +#phase_q_ats +4 +#phase_bt +-6 +#phase_rec_devs +3 +#phase_larv +-3 +#phase_sr +5 +#wt_fut_phase +6 +#last_age_sel_fsh +4 +#last_age_sel_bts +8 +#last_age_sel_ats +8 +#ctrl_flag +200 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +12.5 +1 +1 +1 +1 +1 +1 +3.125 +5 +1 +5 +0 +1 +2 +0 +0 +2 +1 +#sel_dev_shift +0 +#phase_coheff +1 +#phase_yreff +1 +#switch_temp_rec +0 +#phase_temp_rec +6 +#switch_pred_mort +0 +#phase_pred_mort +1 +#switch_mspp_func_resp +1 diff --git a/2024/runs/bholt_long_noprior/pm b/2024/runs/bholt_long_noprior/pm new file mode 100755 index 0000000..39af7d1 Binary files /dev/null and b/2024/runs/bholt_long_noprior/pm differ diff --git a/2024/runs/bholt_long_noprior/pm.dat b/2024/runs/bholt_long_noprior/pm.dat new file mode 100644 index 0000000..e724b27 --- /dev/null +++ b/2024/runs/bholt_long_noprior/pm.dat @@ -0,0 +1,10 @@ +UseVAST_AGE_Hulson_ISS +../data/pm_23.8.dat +../data/selvar23.dat +control.dat +../data/pm_fmsy_alt.dat +../data/cov_2023.dat +../data/wtage2023.dat +../data/surveycpue.dat +../data/temp_paul23.dat +../data/q_bts.dat diff --git a/2024/runs/bholt_long_noprior/pm.prj b/2024/runs/bholt_long_noprior/pm.prj new file mode 100644 index 0000000..6fa0b19 --- /dev/null +++ b/2024/runs/bholt_long_noprior/pm.prj @@ -0,0 +1,29 @@ +EBS_Pollock_2023 +1 # SSLn species... +0 # Buffer of Dorn +1 # Number of fsheries +1 # Number of sexes +0.237303 # averagei 5yr f + 1 # author f + 0.4 # ABC SPR + 0.35 # MSY/OFL SPR + 4 # Spawnmo +15 # Number of ages + 1 # Fratio + 0.9 0.45 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 # Natural Mortality +# Maturity + 0 0.008 0.289 0.641 0.842 0.901 0.947 0.963 0.97 1 1 1 1 1 1 +# Wt spawn + 0.0848817 0.195868 0.319566 0.490613 0.604994 0.738365 0.851658 0.960207 1.03066 1.10148 1.21865 1.26473 1.30452 1.35788 1.43261 +# Wt fsh + 0.0251823 0.186222 0.382396 0.514465 0.713513 0.783949 0.851316 0.960344 1.05614 1.10786 1.17923 1.29141 1.29349 1.30849 1.37907 +# selectivity + 0.00014647 0.0580014 0.218331 0.347531 0.536233 0.911763 1.46748 1.59033 1.51136 1.44769 1.46686 1.36107 1.36107 1.36107 1.36107 +# natage + 21987.8 8595.85 4649.01 2424.6 2255.9 5443.38 819.65 266.836 136.547 150.712 136.752 46.7647 9.40197 6.77993 15.4783 +# Nrec +45 +# rec + 23700.7 58115.3 24087 30138.7 17160.8 49088.9 13271.3 32996.9 12751.9 7222.43 5601.13 11570.3 48798.9 25503.9 21297.9 44508.6 14994.8 10339.9 22091.1 30273.5 14768.8 15803.7 24544 34287.3 22923.4 14043.7 6389.81 4573.53 11457.2 24376.9 13319.7 49160.7 21882.7 13123.1 11616.5 42740.5 48465.7 20761.2 7945.67 8541.89 15110.8 72487.4 18811.1 13452.5 18211.2 21143.1 +# SpawningBiomass + 1097.29 998.239 943.564 1129.34 1715.4 2343.46 3084.42 3154.02 3617.9 3541.34 3608.11 3448.78 3001.89 2542.29 2036.84 1952.23 2609.23 3028.19 3230.54 3169.52 3076.87 2608.47 2746.03 2670.05 2726.61 2545.58 2595.15 2902.27 2559.21 2338.85 1905.44 1444.55 1526.5 1567.17 1934.24 2366.94 2686.14 2615.13 2437.07 2696.77 3132.21 2983.67 2898.03 2222.34 2330.63 3121.06 diff --git a/2024/runs/bholt_long_noprior/pm.tpl b/2024/runs/bholt_long_noprior/pm.tpl new file mode 100644 index 0000000..f8d3d6d --- /dev/null +++ b/2024/runs/bholt_long_noprior/pm.tpl @@ -0,0 +1,6923 @@ +///////////////////////////////////////////////////////////// +// Conventions: // +// fsh - refers to fshery // +// bts - refers to trawl survey // +// ats - refers to hydroacoustic survey // +// eac - refers to expected age composition // +// oac - refers to observed age composition // +// et - refers to expected total numbers // +// ot - refers to observed total numbers // +/////////////////////////////////////////////////// +// \\ +// \\ +// ngears - number of gear types (including srv \\ +// n_ - refers to the number of observations \\ +// styr - first calendar year of model \\ +// endyr - last calendar year of model \\ +// styr_ - first year of data (suffix) \\ +// endyr_r - last year for retrospective run \\ +//\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ +// +// +DATA_SECTION + !! *(ad_comm::global_datafile) >> model_name; + !! *(ad_comm::global_datafile) >> datafile_name; + !! *(ad_comm::global_datafile) >> selchng_filename; + !! *(ad_comm::global_datafile) >> control_filename; + !! *(ad_comm::global_datafile) >> Alt_MSY_File; + !! *(ad_comm::global_datafile) >> Cov_Filename; + !! *(ad_comm::global_datafile) >> Wtage_file; + !! *(ad_comm::global_datafile) >> RawSurveyCPUE_file; + // !! *(ad_comm::global_datafile) >> control_temp_pred_filename; + !! *(ad_comm::global_datafile) >> Temp_Cons_Dist_file; + !! *(ad_comm::global_datafile) >> GenGamm_Filename; + // !! *(ad_comm::global_datafile) >> endyrn_file; + !! write_log(model_name); + !! write_log(datafile_name); + !! write_log(selchng_filename); + !! write_log(control_filename); + !! write_log(Alt_MSY_File); + !! write_log(Cov_Filename); + !! write_log(Wtage_file); + !! write_log(RawSurveyCPUE_file); + // !! write_log(control_temp_pred_filename); + !! write_log(Temp_Cons_Dist_file); + !! write_log(GenGamm_Filename); + // !! write_log(endyrn_file); + int count_Ffail; + int count_mcmc; + int count_mcsave; + !! count_mcmc=0; + !! count_mcsave=0; + int pflag; + int do_EIT1; + int q_amin + int q_amax + !! q_amin = 3; q_amax= 15; // age range overwhich q applies (for prior specifications) + vector selages(1,15) + !! selages=1.0;selages(1)=0;selages(2)=0; + vector sel_avo_in(1,15) + !! sel_avo_in(1)=0.0; sel_avo_in(2)=1; sel_avo_in(3)=1; sel_avo_in(4)=0.85; sel_avo_in(5)=0.7; sel_avo_in(6)=0.55; sel_avo_in(7)=0.3; sel_avo_in(8)=0.15; sel_avo_in(9)=0.05; sel_avo_in(10)=0.01; sel_avo_in(11)=0.01; sel_avo_in(12)=0.01; sel_avo_in(13)=0.01; sel_avo_in(14)=0.01; sel_avo_in(15)=0.01; + vector Cat_Fut(1,10); + !! do_EIT1=1; // flag to carry EIT out in future year (for simulations only) + !! pflag=0; + !!CLASS ofstream srecout("srec_Ass_out.rep") + !!CLASS ofstream projout("pm.prj") + !!CLASS ofstream nofish("nofish.rep") + !!CLASS ofstream projout2("pmsr.prj") + // writes when -mceval invoked (which uses pm.psv file from -mcmc 10000000 -mcsave 200) + !!CLASS ofstream eval("pm_eval.rep") + // Control file read from here-------------------------------------- + !! ad_comm::change_datafile_name(control_filename); cout<<"Opening "<0) // Use logistic selectivity + { + phase_selcoffs_fsh = -2; + if(phase_seldevs_fsh>0) + phase_selcoffs_fsh_dev = -phase_seldevs_fsh; + else + phase_selcoffs_fsh_dev = phase_seldevs_fsh; + + phase_logist_fsh_dev = phase_seldevs_fsh; + } + else // Use coefficient selectivities... + { + if(phase_seldevs_fsh>0) + phase_logist_fsh_dev = -phase_seldevs_fsh; + + phase_selcoffs_fsh_dev = phase_seldevs_fsh; + } + // Trawl Survey selectivity................ + if (phase_logist_bts>0) // Use logistic selectivites... + { + phase_selcoffs_bts = -2; + if(phase_seldevs_bts>0) + phase_selcoffs_bts_dev = -phase_seldevs_bts; + else + phase_selcoffs_bts_dev = phase_seldevs_bts; + + phase_logist_bts_dev = phase_seldevs_bts; + } + else // Use coefficient selectivites... + { + if(phase_seldevs_bts>0) + phase_logist_bts_dev = -phase_seldevs_bts; + + phase_selcoffs_bts_dev = phase_seldevs_bts; + } + + END_CALCS + init_int phase_selcoffs_ats + init_int phase_selcoffs_ats_dev + !! cout <<"Phase fsh coef: "<1978) // to test if styr is before 1978 + styr_est = styr; + else + styr_est = 1978; + } + else + { + styr_est = styr+1; + } + + // Set bounds for SRR params (depending on estimation and type) + if (phase_sr>0) + { + phase_nosr=-1; + phase_Rzero=3; + if (SrType==3) + phase_Rzero=-2; + } + else + { + phase_nosr=1; + phase_Rzero=-1; + } + + if (SrType==4) + Steepness_UB=4.; + else + Steepness_UB=.99; + + n_fsh_r=0; + n_bts_r=0; + n_ats_r=0; + n_avo_r=0; + endyr_r = endyr - int(ctrl_flag(28)); // where retrospective peels are set + endyr_est = endyr_r - int(ctrl_flag(29)); // lop off last couple of years + cout <<"Last yr of estimation..."<0) {ii++;} nch_ats=ii; + ii = 0; for(i=styr;i<=endyr_r;i++) if(fsh_ch_in(i)>0) {ii++;} nch_fsh=ii; + if (ctrl_flag(28)==0.) + { + n_fsh_r=n_fsh; + n_bts_r=n_bts; + n_ats_r=n_ats; + n_avo_r=n_avo; + } + else + { + int ii=0; + for (i=styr;i0) + phase_nosr = -1; + else + phase_nosr = 1; + END_CALCS + !! ad_comm::change_datafile_name(Cov_Filename);cout<<"Opening "<0) {ii++;sel_ch_sig_ats(ii)=ats_ch_in(i);yrs_ch_ats(ii)=i;} + ivector yrs_ch_fsh(1,nch_fsh); + vector sel_ch_sig_fsh(1,nch_fsh); + !! ii=0;for (i=styr;i<=endyr_r;i++) if(fsh_ch_in(i)>0) {ii++;sel_ch_sig_fsh(ii)=fsh_ch_in(i);yrs_ch_fsh(ii)=i;} + // Critical variables: yrs_ch_ats, sel_ch_sig_ats, and nch_ats + !! write_log(nch_fsh); write_log(yrs_ch_fsh); write_log(sel_ch_sig_fsh); + !! write_log(nch_ats); write_log(yrs_ch_ats); write_log(sel_ch_sig_ats); + matrix oac_fsh(1,n_fsh_r,1,nbins)//--Observed proportion at age in Fishery + matrix oac_bts(1,n_bts_r,1,nbins)//--Observed proportion at age in Survey + + // Set up whether last survey value is used or not (if ALK is from BTS instead of EIT) + int n_ats_ac_r; + !! if (use_last_ats_ac>0) n_ats_ac_r = n_ats_r; else n_ats_ac_r = n_ats_r-1; + !! if (use_last_ats_ac>0) nagecomp(3) = n_ats_r; else nagecomp(3) = n_ats_r-1; + + matrix oac_ats(1,n_ats_ac_r,1,nbins)//--Observed proportion at age in Survey + vector oa1_ats(1,n_ats_ac_r) //--Observed age 1 index from hydro survey + vector ot_fsh(1,n_fsh_r) //--Observed total numbers in Fishery + vector ot_bts(1,n_bts_r) //--Observed total numbers in BTS + vector std_ob_bts(1,n_bts_r) //--Observed total biomass in BTS + vector ob_bts(1,n_bts_r) //--Observed total biomass in BTS + + vector ot_ats(1,n_ats_r) //--Observed total numbers in HydroSurvey + vector ob_ats(1,n_ats_r) //--Observed total biomass in Survey + vector std_ob_ats(1,n_ats_r) //--Observed total biomass in Survey + int ignore_last_ats_age1; + vector lseb_ats(1,n_ats_r); + vector lvarb_ats(1,n_ats_r); + + // Stuff for passing seed via command line and for initializing new sequence + int iseed; + int condmsy; + !! iseed = 0; + !! condmsy = 0; + int do_fmort; + !! do_fmort=0; + vector adj_1(1,10) + vector adj_2(1,10) + vector SSB_1(1,10) + vector SSB_2(1,10) + int do_check // Placeholder to have debug checker flag... + int do_srrdevs // Flag to do deviations off the curve + LOCAL_CALCS + do_check=0; + do_srrdevs=0; + if (ad_comm::argc > 1) + { + int on=0; + if ( (on=option_match(argc,argv,"-srrdevs"))>-1) + do_srrdevs = 1; + + if ( (on=option_match(ad_comm::argc,ad_comm::argv,"-condmsy"))>-1) + { + if (on>ad_comm::argc-2 | ad_comm::argv[on+1][0] == '-') + { + cerr << "Invalid number of arguments for command line option -condmsy; option ignored" << endl; + } + else + { + condmsy = atoi(ad_comm::argv[on+1]); + cout<< "Currently using "<-1) + do_check = 1; + + if ( (on=option_match(ad_comm::argc,ad_comm::argv,"-iseed"))>-1) + { + if (on>ad_comm::argc-2 | ad_comm::argv[on+1][0] == '-') + { + cerr << "Invalid number of iseed arguements, command line option -iseed ignored" << endl; + } + else + { + iseed = atoi(ad_comm::argv[on+1]); + cout<< "Currently using "<-1) + do_fmort=1; + } + // Some defaults------------ + adj_1=1.0; + adj_2=1.0; + SSB_1=1.0; + SSB_2=1.0; + + END_CALCS + int phase_cpue_q + int phase_avo_q + !!long int lseed=iseed; + !!CLASS random_number_generator rng(iseed); + + // ------------------------------------------------------ + // Conditionally read in generalized Gamma Q values for BTS + matrix GenGamData(1,n_bts,1,2); + vector q_GenGam(1,n_bts); + vector sd_GenGam(1,n_bts); + + LOCAL_CALCS + // Flag to use covariance for bottom trawl survey, 0=use vector, 1=use cov matrix, 2=use GenGamma + if (DoCovBTS==2) + { + ad_comm::change_datafile_name(GenGamm_Filename);cout<<"Opening "<> GenGamData ; + } + q_GenGam = extract_column(GenGamData,1); + sd_GenGam = extract_column(GenGamData,2); + write_log(q_GenGam); + write_log(sd_GenGam); + write_log(GenGamData); //exit(1); + END_CALCS + // init_matrix GenGamData(1,n_bts,1,2); + + // ------------------------------------------------------ + // read in wt-age data by + !! ad_comm::change_datafile_name(Wtage_file);cout<<"Opening "<1) phase_d_scale = 3; else phase_d_scale = -1; + !! write_log(endyr_wt); + !! write_log(styr_wt); + !! write_log(log_sd_coh); + !! write_log(log_sd_yr); + !! write_log(wt_obs); + !! write_log(sd_obs); + !! endyr_wt = endyr_wt - int(ctrl_flag(28)); + int max_nyrs_data; + !! cout<<(endyr_wt)<0) + { + mnCPUE(iyr,ist) = mean(CPUE(iyr,ist)); + mntemp(iyr,ist) = mean(temp(iyr,ist)); + } + } + } + END_CALCS + vector FW_fsh(1,4); + number FW_bts; + number FW_ats; + + +// read in data for doing temp-recuitment model, and spatial predation + !! ad_comm::change_datafile_name(Temp_Cons_Dist_file); + int endyr_temp + // NOTE This is fixed so that simulation / OM can be done + !! endyr_temp = 2023; + init_vector SST(styr-1,endyr_temp-1); + number SST_fut + !! SST_fut = mean(SST(endyr_temp-7,endyr_temp-3)); + init_number n_pred_grp_nonpoll // the number of non-pollock predator groups + init_number n_pred_grp_poll // the number of pollock predator groups + number n_pred_grp // the total number of predator groups + !! n_pred_grp = n_pred_grp_nonpoll + n_pred_grp_poll; // the number of predator groups + init_matrix N_pred(1,n_pred_grp,styr,endyr_temp) // the abindance of the predator groups + init_int nstrata_pred // the number of strata for computing spatial predation + init_vector strata(1,nstrata_pred) // vector of strata names + init_number n_pred_ages // the number of ages which are preyed upon + init_vector pred_ages(1,n_pred_ages) // the ages which are preyed upon + init_3darray poll_dist(1,n_pred_ages,styr,endyr_temp,1,nstrata_pred) // the distribution of age 1 pollock across strata, by year + init_3darray pred_dist_nonpoll(1,n_pred_grp,styr,endyr_temp,1,nstrata_pred) // the distribution of predators by strata, by year + 3darray Npred_bystrata_nonpoll(styr,endyr_temp,1,n_pred_grp_nonpoll,1,nstrata_pred) // the number of non-pollock predators by strata for a given year + init_vector area_pred(1,nstrata_pred) // the strata area for getting predatuion by area (sq km) + // end test imput for ragged array + init_ivector nyrs_cons_nonpoll(1,n_pred_grp_nonpoll) // the number of years for which we have estimates of nonpollock predator consumption + init_matrix yrs_cons_nonpoll(1,n_pred_grp_nonpoll,1,nyrs_cons_nonpoll) // the years for which we have predator consumption estimates + init_matrix obs_cons_nonpoll(1,n_pred_grp_nonpoll,1,nyrs_cons_nonpoll) // the time series of consumption estiates for each predator (kilotons) + init_3darray oac_cons_nonpoll(1,n_pred_grp_nonpoll,1,nyrs_cons_nonpoll,1,n_pred_ages) // the observed age comps for predation for each predator, by year + init_matrix sam_oac_cons_nonpoll_raw(1,n_pred_grp_nonpoll,1,nyrs_cons_nonpoll) // the sample size for the consumption age comps + 3darray obs_cons_wgt_atage_nonpoll(1,n_pred_grp_nonpoll,1,nyrs_cons_nonpoll,1,n_pred_ages) // the observed weight consumed at age (by predator and year) + 3darray obs_cons_natage_nonpoll(1,n_pred_grp_nonpoll,1,nyrs_cons_nonpoll,1,n_pred_ages) // the observed consumed number at age (by predator and year) + 3darray obs_cpup_nonpoll(1,n_pred_grp_nonpoll,1,nyrs_cons_nonpoll,1,n_pred_ages) // the observed number consumed per unit predator + + + init_vector C_a_nonpoll(1,n_pred_grp_nonpoll) // C_a parameter for max consumption + init_vector C_b_nonpoll(1,n_pred_grp_nonpoll) // C_b parameter for max consumption + init_vector TCM_nonpoll(1,n_pred_grp_nonpoll) // TCM parameter for max consumption temperature function + init_vector TC0_nonpoll(1,n_pred_grp_nonpoll) // TC0 parameter for max consumption temperature funcion + init_vector CQ_nonpoll(1,n_pred_grp_nonpoll) // CQ parameter for max consumption temperature function + init_matrix temp_bystrata(styr,endyr_temp,1,nstrata_pred) // the temperature by strata (year before 1982 are an average) + init_matrix mn_wgt_nonpoll(1,n_pred_grp_nonpoll,styr,endyr_temp) // the mean weight of the predator groups + vector Y_nonpoll(1,n_pred_grp_nonpoll) // Y number for max consumption temperature function + vector Z_nonpoll(1,n_pred_grp_nonpoll) // Z number for max consumption temperature function + vector X_nonpoll(1,n_pred_grp_nonpoll) // X number for max consumption temperature function + 3darray V_nonpoll(styr,endyr_temp,1,n_pred_grp_nonpoll,1,nstrata_pred) // V matrix for max consumption temperature function + 3darray F_t_nonpoll(styr,endyr_temp,1,n_pred_grp_nonpoll,1,nstrata_pred) + 3darray Cmax_nonpoll(styr,endyr_temp,1,n_pred_grp_nonpoll,1,nstrata_pred) // Cmax by year, predator group, and region + init_vector Cmax_avg(1,n_pred_grp); // Cmax for avg weight and temperature, for functional response + vector atf_wgts(1,n_pred_grp); // mean atf weights for computing functional response + vector poll_wgts(1,n_pred_ages); // mean poll weights for computing functional response + ivector comp_nr_ub(1,n_pred_grp_nonpoll); // define upper bound for ragged matrix cons_nr as integer vector + !! comp_nr_ub = ivector(nyrs_cons_nonpoll*n_pred_ages); + init_int phase_cope; + init_int n_cope; + init_ivector yrs_cope(1,n_cope); + init_vector obs_cope(1,n_cope); + init_vector obs_cope_std(1,n_cope); + vector lse_cope(1,n_cope); + vector lvar_cope(1,n_cope); + + + int k // added by Paul (k,m,yr_ind,z) + int m + int yr_ind + int z + + LOCAL_CALCS + lse_cope = elem_div(obs_cope_std,obs_cope); + lse_cope = sqrt(log(square(lse_cope) + 1.)); + lvar_cope = square(lse_cope); + write_log(SST); + write_log( n_pred_grp_nonpoll); + write_log( n_pred_grp_poll); + write_log( n_pred_grp); + write_log( N_pred); + write_log( nstrata_pred); + write_log( strata); + write_log( n_pred_ages); + write_log( pred_ages); + write_log( poll_dist); + write_log( pred_dist_nonpoll); + write_log( area_pred); + write_log( nyrs_cons_nonpoll); + write_log( yrs_cons_nonpoll); + write_log( obs_cons_nonpoll); + write_log(sam_oac_cons_nonpoll_raw); + write_log(temp_phase); + write_log(C_a_nonpoll); + write_log(C_b_nonpoll); + write_log(TCM_nonpoll); + write_log(TC0_nonpoll); + write_log(CQ_nonpoll); + write_log(temp_bystrata); + write_log(mn_wgt_nonpoll); + write_log(Cmax_avg); + write_log(phase_cope); + write_log(n_cope); + write_log(yrs_cope); + write_log(obs_cope); + write_log(obs_cope_std); + + // Assign values to temperature and predation phases (if estimating predation mortality or climate enhanced recruitment) + if(do_pred==1 && do_mult_func_resp==1) + { + do_pred_phase_ms = pred_phase; + do_pred_phase_ss = -1; + do_pred_phase = pred_phase; + } + else if (do_pred==1 && do_mult_func_resp!=1) + { + do_pred_phase_ms = -1; + do_pred_phase_ss = pred_phase; + do_pred_phase = pred_phase; + } + else + { + do_pred_phase_ms = -1; + do_pred_phase_ss = -1; + do_pred_phase = -1; + } + if(do_temp==1) + do_temp_phase = temp_phase; + else + do_temp_phase = -1; + // If estimating predation mortality, do a bunch of preliminary calculations + if (do_pred==1) + { + //Rescale spatial distribution matrices to add to one, and compute predator by year and strata + for (i=1;i<=n_pred_ages;i++) + { + for (ii=styr;ii<=endyr;ii++) + { + poll_dist(i,ii) = poll_dist(i,ii)/sum(poll_dist(i,ii)); + } + } + + for (i=1;i<=n_pred_grp;i++) + { + for (ii=styr;ii<=endyr;ii++) + { + pred_dist_nonpoll(i,ii) = pred_dist_nonpoll(i,ii)/sum(pred_dist_nonpoll(i,ii)); + Npred_bystrata_nonpoll(ii,i) = N_pred(i,ii)*pred_dist_nonpoll(i,ii); + } + } + + // Compute the catch per unit predator (CPUP) in numbers + for (m=1;m<=n_pred_grp;m++) + { + for (i=1;i<=nyrs_cons_nonpoll(m);i++) + { + yr_ind = yrs_cons_nonpoll(m,i) - 1981; // for getting the index for the wt_bts + if(yr_ind<1) + yr_ind = 1; + if(yr_ind>38) + yr_ind = 38; + obs_cons_wgt_atage_nonpoll(m,i) = oac_cons_nonpoll(m,i)*obs_cons_nonpoll(m,i); // kilotons + obs_cons_natage_nonpoll(m,i) = elem_div(obs_cons_wgt_atage_nonpoll(m,i),wt_bts(yr_ind)(1,n_pred_ages)); + obs_cpup_nonpoll(m,i) = obs_cons_natage_nonpoll(m,i)/N_pred(m,yrs_cons_nonpoll(m,i)); + } + } + + // Compute things for Cmax + for (i=1;i<=n_pred_grp_nonpoll;i++) + { + Y_nonpoll(i) = log(CQ_nonpoll(i))*(TCM_nonpoll(i)-TC0_nonpoll(i)+2); + Z_nonpoll(i) = log(CQ_nonpoll(i))*(TCM_nonpoll(i)-TC0_nonpoll(i)); + X_nonpoll(i) = Z_nonpoll(i)*Z_nonpoll(i)*pow(1+sqrt(1+40.0/Y_nonpoll(i)),2)/400.0; + for (j=styr;j<=endyr;j++) + { + V_nonpoll(j,i) = (TCM_nonpoll(i) - temp_bystrata(j))/(TCM_nonpoll(i) - TC0_nonpoll(i)); + F_t_nonpoll(j,i) = elem_prod(pow(V_nonpoll(j,i),X_nonpoll(i)),mfexp(X_nonpoll(i)*(1.0- V_nonpoll(j,i)))); + Cmax_nonpoll(j,i) = 365*C_a_nonpoll(i)*pow(mn_wgt_nonpoll(i,j),C_b_nonpoll(i))*F_t_nonpoll(j,i); + } + } + + // Compute average of atf and pollock weights for computing functional response + for (i=1;i<=n_pred_grp;i++) + atf_wgts(i) = mean(mn_wgt_nonpoll(i)); + for(i=1;i<=n_pred_ages;i++) + poll_wgts(i) = 1000.0*mean(column(wt_bts,i)); // convert from kg to g + } + write_log(do_temp_phase); // copy the temperture phase here + write_log(do_pred_phase_ss); // phase for estimating the predation parameters, single species function response + write_log(do_pred_phase_ms); // phase for estimating the predation parameters, multi-species function response + write_log(do_pred_phase); // phase for estimating the residual M + + END_CALCS + init_number test_2 + !! write_log(test_2); + !! if(test_2!=1234567){ cout<<"Failed on data read "<0) ph_log_fsh2 = phase_logist_fsh+1;else ph_log_fsh2 = phase_logist_fsh; + init_number sel_dif2_fsh(ph_log_fsh2) + + init_bounded_dev_vector sel_dif1_fsh_dev(styr,endyr_r,-5,5,phase_logist_fsh_dev) // allow for variability in survey selectivity inflection + init_bounded_dev_vector sel_a501_fsh_dev(styr,endyr_r,-5,5,phase_logist_fsh_dev) // allow for variability in survey selectivity inflection + init_bounded_dev_vector sel_trm2_fsh_dev(styr,endyr_r,-.5,.5,-2) // allow for variability in survey selectivity inflection + + // Parameters for computing SPR rates + number SPR_ABC // (0.05,2.,phase_F40) + sdreport_vector endyr_N(1,nages); + sdreport_number B_Bnofsh; + sdreport_number Bzero; + sdreport_number Percent_Bzero; + sdreport_number Percent_Bzero_1; + sdreport_number Percent_Bzero_2; + sdreport_number Percent_B100; + sdreport_number Percent_B100_1; + sdreport_number Percent_B100_2; + // Added to test for significance of "mean temperature" from earlier assessments (effect on survey q) + // NOT presented as a sensitivity in 2008 nor 2009 + // sdreport_vector q_temp(1,5); + vector q_temp(1,5); + sdreport_number SPR_OFL // (0.05,2.,phase_F40) + sdreport_number F40 // (0.05,2.,phase_F40) + sdreport_number F35 // (0.05,2.,phase_F40) + sdreport_vector SSB(styr,endyr_r) + + // Stuff for SPR and yield projections + number sigmarsq_out + number ftmp + number SB0 + number SBF40 + number SBF35 + number sprpen + number F_pen + number meanrec + vector SR_resids(styr_est,endyr_est); + matrix Nspr(1,4,1,nages) + sdreport_vector sel_fut(1,nages) + + 3darray natage_future(1,nscen,styr_fut,endyr_fut,1,nages) + init_vector rec_dev_future(styr_fut,endyr_fut,phase_F40); + + 3darray F_future(1,nscen,styr_fut,endyr_fut,1,nages); + matrix Z_future(styr_fut,endyr_fut,1,nages); + matrix S_future(styr_fut,endyr_fut,1,nages); + matrix catage_future(styr_fut,endyr_fut,1,nages); + number avg_rec_dev_future + + matrix eac_fsh(1,n_fsh_r,1,nbins) //--Expected proportion at age in Fishery + vector elc_fsh(1,nlbins) //--Expected proportion at length in Fishery + matrix eac_bts(1,n_bts_r,1,nbins) //--Expected proportion at age in trawl survey + matrix eac_cmb(1,n_bts_r,1,nbins) //--Expected proportion at age in combined surveys + matrix oac_cmb(1,n_bts_r,1,nbins) //--observed proportion at age in combined surveys + matrix eac_ats(1,n_ats_ac_r,1,nbins)//--Expected proportion at age in hydro survey + vector ea1_ats(1,n_ats_ac_r) //--Expected age 1 index from hydro survey + vector et_fsh(1,n_fsh_r) //--Expected total numbers in Fishery + vector et_bts(1,n_bts_r) //--Expected total numbers in Survey + vector et_cmb(1,n_bts_r) //--Expected total numbers in HydroSurvey + vector avail_bts(1,n_bts_r) //--Availability estimates in BTS + vector avail_ats(1,n_bts_r) //--Availability estimates in HydroSurvey + vector sigma_cmb(1,n_bts_r) //--Std errors of combined surveys (by year) + vector var_cmb(1,n_bts_r) //--Std errors of combined surveys (by year) + vector ot_cmb(1,n_bts_r) //--Observed total numbers in combined Surveys + vector eb_bts(1,n_bts_r) //--Expected total biomass in Survey + vector eb_ats(1,n_ats_r) //--Expected total biomass in Survey + vector et_ats(1,n_ats_r) //--Expected total numbers in HydroSurvey + vector lse_ats(1,n_ats_r) + vector lvar_ats(1,n_ats_r) + vector et_avo(1,n_avo_r) //--Expected total numbers in HydroSurvey + vector et_cpue(1,n_cpue) //--Expected total numbers in CPUE + vector Fmort(styr,endyr_r) + + matrix catage(styr,endyr_r,1,nages) + vector pred_catch(styr,endyr_r) + vector Pred_N_bts(styr,endyr_r) + vector Pred_N_ats(styr,endyr_r) + vector pred_cpue(1,n_cpue) + vector pred_cope(1,n_cope) + sdreport_vector Nage_3(styr,endyr_r) + vector pred_avo(1,n_avo) + // vector SSB(styr,endyr_r) + matrix natage(styr,endyr_r,1,nages); + vector srmod_rec(styr_est,endyr_est); + matrix Z(styr,endyr_r,1,nages); + matrix F(styr,endyr_r,1,nages); + matrix S(styr,endyr_r,1,nages); + matrix M(styr,endyr_r,1,nages); + init_bounded_vector M_dev(styr+1,endyr_r,-1.,1.,-8); + matrix log_sel_fsh(styr,endyr_r,1,nages); + matrix sel_fsh(styr,endyr_r,1,nages); + matrix log_sel_bts(styr,endyr_r,1,nages); + matrix log_sel_ats(styr,endyr_r,1,nages); + number ff; + number catch_like; + number avgsel_fsh; + number avgsel_bts; + number avgsel_ats; + number bzero; + number surv; + number nthisage; + vector surv_like(1,3); + number cpue_like; + number cope_like; + number avo_like; + vector sel_like(1,3); + vector sel_like_dev(1,3); + vector age_like(1,ngears); + matrix age_like_yr(1,ngears,1,nagecomp) + number len_like; + number wt_like; + vector age_like_offset(1,ngears); + number len_like_offset; + number MN_const // Multinomial constant + !! MN_const = 1e-3; // Multinomial constant + vector Priors(1,4); + vector rec_like(1,7); + vector all_like(1,26); + number sumtmp; + number tmpsp; + vector log_initage(2,nages); + vector pred_biom(styr,endyr_r); + vector SRR_SSB(1,20) + vector fake_SST(1,40) // added by Paul + vector fake_dens(1,40) // added by Paul + + // Average weight stuff + init_bounded_number L1(10,50,2); + init_bounded_number L2(30,90,3); + init_number log_alpha(-1); + init_number log_K(4); + vector wt_inc(age_st,age_end-1); + init_matrix d_scale(1,nscale_parm,age_st,age_end,phase_d_scale); + number K; + // init_number log_t0(3); + // Predicted weight matrix + 3darray wt_hat(1,ndat_wt,1,max_nyrs_data,age_st,age_end); + number alphawt; + matrix wt_pre(styr_wt,endyr_wt,age_st,age_end) + vector mnwt(age_st,age_end); + init_bounded_vector coh_eff(styr_wt-nages_wt-age_st+1,endyr_wt-age_st+3,-15,15,phase_coheff); + init_bounded_vector yr_eff(styr_wt,endyr_wt+3,-15,15,phase_yreff); + + sdreport_vector wt_last(age_st,age_end); + sdreport_vector wt_cur(age_st,age_end); + sdreport_vector wt_next(age_st,age_end); + sdreport_vector wt_yraf(age_st,age_end); + + sdreport_number avg_age_msy; + // sdreport_number avgln_msy; + sdreport_number avgwt_msy; + sdreport_number MSY; + sdreport_number MSY_wt; + sdreport_number Fmsy; + sdreport_number Fmsy_wt; // includes vector on value...default is equal weight + sdreport_number Fmsy2; + sdreport_number Fmsy2_wt; + sdreport_vector Fmsy2_dec(1,10); // uncertain next year weight previous decade selectivity estimates + sdreport_vector Fmsy2_decwt(1,10); // uncertain next year selectivity but previous decade weight estimates + sdreport_number Bmsy2; + sdreport_number Bmsy2_wt; + sdreport_number lnFmsy; + sdreport_number lnFmsy2; + sdreport_number SER_Fmsy; + sdreport_number Fendyr_Fmsy; + sdreport_number Rmsy; + sdreport_number Bmsy; + + // Decision table variables............................... + sdreport_vector Fcur_Fmsy(1,nscen); + sdreport_vector Bcur_Bmsy(1,nscen); + sdreport_vector Bcur_Bmean(1,nscen); + sdreport_vector Bcur3_Bcur(1,nscen); + sdreport_vector Bcur3_Bmean(1,nscen); + sdreport_vector Bcur2_Bmsy(1,nscen); + sdreport_vector Bcur2_B20(1,nscen); + sdreport_vector LTA1_5R(1,nscen); // long term average age 1_5 Ratio + sdreport_vector LTA1_5(1,nscen); // long term average age 1_5 + sdreport_vector MatAgeDiv1(1,nscen); // Diversity of Age structure in mature population + sdreport_vector MatAgeDiv2(1,nscen); // Diversity of Age structure in mature population + vector H(styr,endyr_r); + vector avg_age_mature(styr,endyr_r); + sdreport_vector RelEffort(1,nscen); // Effort relative to endyr + + sdreport_number F40_spb; + // sdreport_number F40_catch; + sdreport_number begbiom; + sdreport_number DepletionSpawners; + sdreport_number SB100; + sdreport_number Current_Spawners; + sdreport_vector pred_rec(styr,endyr_r); + sdreport_vector age_3_plus_biom(styr,endyr_r+2); + sdreport_vector ABC_biom(1,10); + sdreport_vector ABC_biom2(1,10); + sdreport_vector rechat(1,20); + vector SRresidhat(1,40); // added by Paul, the predicted residual + sdreport_vector SER(styr,endyr_r); + matrix future_SER(1,nscen,styr_fut,endyr_fut); + matrix future_catch(1,nscen,styr_fut,endyr_fut); + sdreport_matrix future_R(1,nscen,styr_fut,endyr_fut) + sdreport_matrix future_SSB(1,nscen,endyr_r,endyr_fut) + sdreport_vector Age3_Abund(styr,endyr_r) + vector age_1_7_biomass(styr,endyr_r); + vector NLL(1,20) + objective_function_value fff; + + // Things for estimating the relation between temperature and SR residuals + init_number resid_temp_x1(do_temp_phase); + init_number resid_temp_x2(do_temp_phase); + vector SR_resids_temp(styr_est,endyr_est); + number SR_resids_like; + + // Things for estimating the predation mortality rates (added by Paul) + init_bounded_matrix log_a_II(1,n_pred_grp,1,n_pred_ages,-12,0,do_pred_phase_ss) // the "a" parameter for Holling type 2(log scale, by predator and age) + init_bounded_matrix log_b_II(1,n_pred_grp,1,n_pred_ages,0,12,do_pred_phase_ss) // the "b" parameter for Holling type 2(log scale, by predator and age) + init_bounded_vector log_a_II_vec(1,n_pred_grp,-12,0,do_pred_phase_ms) // the "a" parameter for Holling type 2(log scale, by predator) + init_bounded_vector log_b_II_vec(1,n_pred_grp,0,12,do_pred_phase_ms) // the "b" parameter for Holling type 2(log scale, by predator) + init_bounded_matrix log_rho(1,n_pred_grp,1,n_pred_ages,-12,0,do_pred_phase_ms) // the proportion of proportion for MS Holling + //matrix log_rho2(1,n_pred_grp,1,n_pred_ages); // after rescaling + + init_bounded_vector log_resid_M(1,n_pred_ages,-3,0.1,do_pred_phase) // the residual natural mortality for the ages that are preyed upon (on log scale) + vector resid_M(1,n_pred_ages) + vector resid_M_like(1,n_pred_ages) // the likelihood for fitting the residual natural mortality rates + matrix a_II(1,n_pred_grp,1,n_pred_ages) // unlogged versions of the Holling type II parameters + matrix b_II(1,n_pred_grp,1,n_pred_ages) + matrix rho(1,n_pred_grp,1,n_pred_ages) // the proportion of proportion for MS Holling + vector a_II_vec(1,n_pred_grp) // unlogged versions of the Holling type II parameters + vector b_II_vec(1,n_pred_grp) + + + 3darray natage_strat(styr,endyr_r,1,n_pred_ages,1,nstrata_pred) // the number of poll by strata for a given year and age + 3darray natage_strat_dens(styr,endyr_r,1,n_pred_ages,1,nstrata_pred) // the density of poll by strata for a given year and age + + matrix meannatage(styr,endyr_r,1,nages) // the mean N summed across the strata + 3darray meannatage_bystrata(styr,endyr_r,1,nages,1,nstrata_pred) // the mean N by strata + 3darray mean_dens_bystrata(styr,endyr_r,1,nages,1,nstrata_pred) // mean density at age by strata + matrix mean_dens(styr,endyr_r,1,n_pred_ages) // the mean density over all the area, within year and strata + 4darray cons(1,n_pred_grp,styr,endyr_r,1,n_pred_ages,1,nstrata_pred); // the consumption of pollock, by predator, year, pollock age, and area + 3darray natmort_pred(1,n_pred_ages,styr,endyr_r,1,nstrata_pred); // the natural mortality with spatial predation + 4darray M_pred(styr,endyr_r,1,n_pred_ages,1,nstrata_pred,1,n_pred_grp_nonpoll); // the inst predation rate for pollock, of pollock, by predator, year, pollock age, and area + matrix M_pred_tmp(1,n_pred_grp_nonpoll,1,n_pred_ages) // temporary place for output of function get_Mpred2 + 3darray M_pred_sum(styr,endyr_r,1,n_pred_ages,1,nstrata_pred) // the total M across predators within a year, pollock age, and strata + 3darray Z_pred(styr,endyr_r,1,n_pred_ages,1,nstrata_pred); // the Z for a1 pollock, by year and area + 3darray S_pred(styr,endyr_r,1,n_pred_ages,1,nstrata_pred); // the S for a1 pollock, by year and area + matrix M_pred_avg(1,n_pred_ages,styr,endyr_r); // average of predation mortality across the strata, weighted by poll abundance at start of year + 3darray cons_atage(1,n_pred_grp,styr,endyr_r,1,n_pred_ages); // total consumption by predator, year and age (sums over strata) + 3darray cons_atage_wt(1,n_pred_grp,styr,endyr_r,1,n_pred_ages); // total weight of consumption by predator, year and age (sums over strata) + matrix pred_cons(1,n_pred_grp,styr,endyr_r); // the predicted total consumption bny predator within a year (across ages) + 3darray eac_cons(1,n_pred_grp,styr,endyr_r,1,n_pred_ages); // the estimated age comp for consumption(by predator and year, sums over strata) + vector ssq_cons(1,n_pred_grp); // the sum of squares for total consumption + vector oac_cons_like_offset(1,n_pred_grp); // offset for multinomial + vector age_like_cons(1,n_pred_grp); // likelihood for the age comps + 3darray pred_cpup(1,n_pred_grp,styr,endyr_r,1,n_pred_ages) // the predicted CPUP by predator, year, and age + 4darray implied_cpuppa(1,n_pred_grp,styr,endyr_r,1,n_pred_ages,1,nstrata_pred); // predicted catch per unit predator per area + 4darray implied_obs_cons_bystrata(1,n_pred_grp,styr,endyr_r,1,n_pred_ages,1,nstrata_pred) // implied observed consumption by strata + 4darray implied_prop_Cmax(1,n_pred_grp,styr,endyr_r,1,n_pred_ages,1,nstrata_pred) // implied consumption rate as proportion of Cmax + + // things added by Paul for the yield curve + number max_F_yldcrv; // maximum F for yield curve, based on spr calc + vector F_yldcrv(1,40); // vector of values for yield curve + vector yield_curve(1,40); // equilibrium yield curve + //vector yield_curve_fut(1,40); // Eq. yield curve with future sst + vector natmort_fut(1,nages); // for getting yield curve and Fmsy; reflects recent predation morality + + // updated compweights -- added by Paul, uses McAllister-Ianelli method + vector compweightsnew(1,n_pred_grp_nonpoll) + matrix comp_mcian_wgt_inv(1,n_pred_grp_nonpoll,1,nyrs_cons_nonpoll) // inverse of McAllister-Ianelli weights, consumption estimates + matrix comp_mcian_wgt(1,n_pred_grp_nonpoll,1,nyrs_cons_nonpoll) + + // consumption estimates normalized resids -- added by Paul to use sdnr to iterate the consumtion weights + vector consweightsnew(1,n_pred_grp_nonpoll) + matrix cons_nr(1,n_pred_grp_nonpoll,1,nyrs_cons_nonpoll) + matrix comp_nr(1,n_pred_grp_nonpoll,1,comp_nr_ub) // for holding the composition standardized resids + + // alpha terms that scale the environment effect to log_avg_rec and modeled recruitment (following Maunder and Watters 2002 paper) + number pred_rec_alpha + number srmod_rec_alpha + + + + + +PRELIMINARY_CALCS_SECTION + // fixed_catch_fut1 = fixed_catch_fut1 + 0.1 ; + wt_fut = wt_fsh(endyr_r); // initializes estimates to correct values...Eq. 21 + // base_natmort(1)=.9; base_natmort(2)=.45; for (j=3 ;j<=nages;j++) base_natmort(j)=natmortprior; + base_natmort = natmort_in; + + natmort = base_natmort; + // cout <<"M input= "< 0.4 ) ignore_last_ats_age1 = 1; else ignore_last_ats_age1=0; + // cout <<" Last age comp in BTS: " << endl << oac_bts_data(n_bts) << endl; + // cout <<" Age_like_offset: " << endl << age_like_offset << endl; + Cat_Fut(1) = next_yrs_catch; // catch guess + // Simple decrement of future cathes to capture relationship between adjustments (below Bmsy) w/in same year + for (i=2;i<=10;i++) + Cat_Fut(i) = Cat_Fut(i-1)*.90; + write_log(Cat_Fut); + + // cout << "Next year's catch and decrements"<0)) + Profile_F(); + if (mceval_phase()) + write_eval(); + update_compweights(); // added by Paul + +FUNCTION update_compweights // added by Paul, update if the comp is estmated, otherwise carry over previous comp weight + if(active(log_resid_M)) + { + for (i=1;i<=n_pred_grp_nonpoll;i++) + { + compweightsnew(i) = 1.0/mean(comp_mcian_wgt_inv(i)); // weights for consumption age comps + consweightsnew(i) = std_dev(cons_nr(i)); // weights for consumption estimates + } + } + else + { + compweightsnew = compweights; + consweightsnew = consweights; + } + +FUNCTION Get_Selectivity + avgsel_fsh.initialize(); + avgsel_bts.initialize(); + avgsel_ats.initialize(); + //cout<<"InSel"<0) // For logistic fishery selectivity (not default, NOT USED) + { + dvariable dif; + dvariable inf; + if (active(sel_a501_fsh_dev)) + { + dvar_matrix seldevs_tmp(1,3,styr,endyr_r); + seldevs_tmp(1) = sel_dif1_fsh_dev; + seldevs_tmp(2) = sel_a501_fsh_dev; + seldevs_tmp(3) = sel_trm2_fsh_dev; + log_sel_fsh = compute_selectivity1(styr,sel_dif1_fsh,sel_a501_fsh,sel_trm2_fsh,seldevs_tmp); + } + else + log_sel_fsh = compute_selectivity1(styr,sel_dif1_fsh,sel_a501_fsh,sel_trm2_fsh); + } + + //cout<<"InSel"<38) + yr_ind = 38; + + for (k=1;k<=n_pred_ages;k++) // loop over ages of pollock that are preyed upon + { + natage_strat(i,k) = natage(i,pred_ages(k))*poll_dist(k,i); // distribute the age k pollock in each area + natage_strat_dens(i,k) = elem_div(natage_strat(i,k),area_pred); // the density of age k pollock in each area + } + + // do the multispecies funcction response thing + if (do_mult_func_resp==1) + { + for (j=1;j<=nstrata_pred;j++) // loop over strata, and get the mean abundance accounting for all mortality + { + M_pred_tmp = get_Mpred2(column(natage_strat_dens(i),j),resid_M,F(i)(1,n_pred_ages), + column(Npred_bystrata_nonpoll(i),j), + column(mn_wgt_nonpoll,i), + wt_bts(yr_ind)(1,n_pred_ages)*1000, + column(Cmax_nonpoll(i),j),rho, + a_II_vec,b_II_vec, j); + + // cout << "M_pred_tmp is " << M_pred_tmp << endl; + // loop to get the results in the right structure + for (ii=1;ii<=n_pred_ages;ii++) + { + for (jj=1;jj<=n_pred_grp;jj++) + { + M_pred(i,ii,j,jj) = M_pred_tmp(jj,ii); + //cout <<" prey age is " << ii<< " pred_grp is "<< jj << " strata is " << j << " M_pred is " << M_pred(i,ii,j,jj) << endl; + } + } + } + } // loop if doing the multispecies functional response + + // loop over ages of pollock that are preyed upon + for (k=1;k<=n_pred_ages;k++) + { + // loop over strata, and get the mean abundance accounting for all mortality + for (j=1;j<=nstrata_pred;j++) + { + if (do_mult_func_resp != 1) // loop is doing the single species functional response + { + // natage_strat(styr,endyr_r,1,n_pred_ages,1,nstrata_pred) // the number of poll by strata for a given year and age + // Jim thinks this may be easier implemented by passing the indices (i,j,k)... + M_pred(i,k,j) = get_Mpred(natage_strat_dens(i,k,j), + F(i,pred_ages(k)), + resid_M(k), + column(natage_strat_dens(i),j), + column(a_II,k), + column(b_II,k), + column(Npred_bystrata_nonpoll(i),j), + column(mn_wgt_nonpoll,i)/(wt_bts(yr_ind,k)*1000), + column(Cmax_nonpoll(i),j),rho); + // e.g.,: M_pred(i,k,j) = get_Mpred(i,k,j); + } + M_pred_sum(i,k,j) = sum(M_pred(i,k,j)); // sum across the different predators + natmort_pred(k,i,j) = M_pred_sum(i,k,j) + resid_M(k); + Z_pred(i,k,j) = F(i,pred_ages(k)) + natmort_pred(k,i,j); // get the total Z by year, pollock age, and strata + S_pred(i,k,j) = mfexp(-1.0*Z_pred(i,k,j)); + } // close strata loop + // cout << "M_pred is " << M_pred<< endl; + meannatage_bystrata(i,k) = elem_div(elem_prod(natage_strat(i,k),(1.-S_pred(i,k))),Z_pred(i,k)); // the mean number at age by strata + meannatage(i,k) = sum(meannatage_bystrata(i,k)); // the mean N summed across the strata + mean_dens_bystrata(i,k) = elem_div(meannatage_bystrata(i,k),area_pred); + mean_dens(i,k) = (meannatage(i,k))/sum(area_pred); // the mean density summed over the strata within a year and age + + for (j=1;j<=nstrata_pred;j++) + { // loop over strata, and get the mean abundance accounting for all mortality + for (m=1;m<=n_pred_grp;m++) + { // loop over predators, and get the consumption and M by predator, pollock age, year, and strata + cons(m,i,k,j) = M_pred(i,k,j,m)*meannatage_bystrata(i,k,j); + } + } + M_pred_avg(k,i) = (M_pred_sum(i,k)*meannatage_bystrata(i,k))/sum(meannatage_bystrata(i,k)); // get an average M_pred across the strata, weighted by the beginning abundance in each strata + // get the total survival by year, pollock age, and strata + if(i < endyr_r) + natage(i+1,k+1) = natage_strat(i,k)*S_pred(i,k); // the natage after predation (summed over strata) + SSB(i) += natage_strat(i,k)*pow(S_pred(i,k),yrfrac)*p_mature(pred_ages(k))*wt_ssb(i,pred_ages(k)); + } // end age loop + SSB(i) += elem_prod(elem_prod(natage(i)(n_pred_ages+1,nages), + pow(S(i)(n_pred_ages+1,nages),yrfrac)),p_mature(n_pred_ages+1,nages))*wt_ssb(i)(n_pred_ages+1,nages); // Eq. 1 + + meannatage(i)(n_pred_ages+1,nages) = elem_prod(elem_div(1.-S(i)(n_pred_ages+1,nages),Z(i)(n_pred_ages+1,nages)), + natage(i)(n_pred_ages+1,nages)); // the mean n at age for the ages not preyed upon + if (i < endyr_r) + { + natage(i+1)(n_pred_ages+2,nages) = ++elem_prod(natage(i)(n_pred_ages+1,nages-1), S(i)(n_pred_ages+1,nages-1)); + natage(i+1,nages) += natage(i,nages)*S(i,nages); // Eq. 1 + } + } // end year loop + // added by Paul to get M values the reflect the recent predation + for (i=1;i<=n_pred_ages;i++) + { + natmort_fut(i) = mean(M_pred_avg(i)(endyr_r-4,endyr_r) + resid_M(i)); + } + } // ********* end of thing by Paul ******************* + + //meanrec = mean(pred_rec(styr_est,endyr_r)); + meanrec = mean(pred_rec(1978,endyr_r)); // ***** changed by Paul to hard-wire mean rec to 1978 onwards + + /* // This function might replace the uglier one... +FUNCTION dvar_vector get_Mpred(const int& i,const int& j,const int& k) + dvariable tmp_abun_bg = natage_strat_dens(i,k,j); + dvariable tmp_F = F(i,pred_ages(k)); + dvariable tmp_M = resit_M(k); + dvar_vector tmp_abun_vec = column(natage_strat_dens(i),j); + dvar_vector a = column(a_II,k); + dvar_vector b = column(b_II,k); + dvector Npred = column(Npred_bystrata_nonpoll(i),j); + dvector wt_ratio = column(mn_wgt_nonpoll,i)/(wt_bts(yr_ind,k)*1000); + dvector tmp_Cmax = column(Cmax_nonpoll(i),j),rho); + dvariable tmp_abun_end; // the abundance at the end of the period + dvariable avg_N; // the average N within the year + dvar_vector M_pred(1,n_pred_grp); // Holling type II predation F (for each predator type) + dvariable M_pred_sum; // the total M_pred + dvariable prev_tmp_abun_end; // the abundance at the end of the period, from the previous time step + if (tmp_abun_bg >0) + { + tmp_abun_end = tmp_abun_bg*mfexp(-tmp_F -tmp_M); + avg_N = tmp_abun_bg*(1-mfexp(-tmp_F -tmp_M))/(tmp_F + tmp_M); + M_pred = elem_prod(elem_prod(wt_ratio,elem_prod(tmp_Cmax,elem_prod(a,Npred))),(1/(b+avg_N))); + M_pred_sum = sum(M_pred); + //M_pred = elem_prod(a,Npred)*(1/(b+avg_N)); + cout << "the weight ratio is " << endl; + cout << wt_ratio << endl; + cout << "the tmp_Cmax is " << endl; + cout << tmp_Cmax << endl; + cout << "the a_II " << endl; + cout << a << endl; + cout << "the Npred " << endl; + cout << Npred << endl; + cout << "The b_II " << endl; + cout << b << endl; + cout << "The avg_N " << endl; + cout << avg_N << endl; + cout << "the M_pred " << endl; + cout << elem_prod(wt_ratio,elem_prod(tmp_Cmax,elem_prod(a,Npred)))*(1/(b+avg_N)) << endl; + + // Check this should be double not dvariable... + double dd = 10.; + int iter = 0; + // Check differentiability here... + while (iter < 10) + { + iter++; + prev_tmp_abun_end = tmp_abun_end; + tmp_abun_end = tmp_abun_bg*mfexp(-tmp_F -tmp_M -M_pred_sum); + avg_N = tmp_abun_bg*(1-mfexp(-tmp_F -tmp_M -M_pred_sum))/(tmp_F + tmp_M + M_pred_sum); + M_pred = elem_prod(elem_prod(wt_ratio,elem_prod(tmp_Cmax,elem_prod(a,Npred))),(1/(b+avg_N))); + M_pred_sum = sum(M_pred); + //M_pred = elem_prod(a,Npred)*(1/(b+avg_N)); + + dd = value(prev_tmp_abun_end) / value(tmp_abun_end) - 1.; + if (dd<0.) dd *= -1.; + // if(active(log_a_II)){ + // cout <<"in loop "<0) + { + tmp_abun_end = tmp_abun_bg*mfexp(-tmp_F -tmp_M); + avg_N = tmp_abun_bg*(1-mfexp(-tmp_F -tmp_M))/(tmp_F + tmp_M); + M_pred = elem_prod(elem_prod(wt_ratio,elem_prod(tmp_Cmax,elem_prod(a,Npred))),(1/(b+avg_N))); + M_pred_sum = sum(M_pred); + //M_pred = elem_prod(a,Npred)*(1/(b+avg_N)); + /*cout << "the weight ratio is " << endl; + cout << wt_ratio << endl; + cout << "the tmp_Cmax is " << endl; + cout << tmp_Cmax << endl; + cout << "the a_II " << endl; + cout << a << endl; + cout << "the Npred " << endl; + cout << Npred << endl; + cout << "The b_II " << endl; + cout << b << endl; + cout << "The avg_N " << endl; + cout << avg_N << endl; + cout << "the M_pred " << endl; + cout << elem_prod(wt_ratio,elem_prod(tmp_Cmax,elem_prod(a,Npred)))*(1/(b+avg_N)) << endl; + */ + + // Check this should be double not dvariable... + dvariable dd = 10.; + int iter = 0; + // Check differentiability here... + while (dd > 1e-6) + { + iter++; + prev_tmp_abun_end = tmp_abun_end; + tmp_abun_end = tmp_abun_bg*mfexp(-tmp_F -tmp_M -M_pred_sum); + avg_N = tmp_abun_bg*(1-mfexp(-tmp_F -tmp_M -M_pred_sum))/(tmp_F + tmp_M + M_pred_sum); + M_pred = elem_prod(elem_prod(wt_ratio,elem_prod(tmp_Cmax,elem_prod(a,Npred))),(1/(b+avg_N))); + M_pred_sum = sum(M_pred); + dd = prev_tmp_abun_end / tmp_abun_end - 1.; + //M_pred = elem_prod(a,Npred)*(1/(b+avg_N)); + + if (dd<0.) + dd *= -1.; + // if(active(log_a_II)){ + // cout <<"in loop "<0.0) + { + tmp_abun_end_vec = elem_prod(tmp_abun_vec,mfexp(-F_vec -tmp_M_vec)); + avg_N_vec = elem_prod(tmp_abun_vec,elem_div((1-mfexp(-F_vec -tmp_M_vec)),(F_vec + tmp_M_vec))); + + for (ii=1;ii<=n_pred_ages;ii++) // loop over prey ages + { + for (jj=1;jj<=n_pred_grp;jj++) // loop over number of predators + { + M_pred_mat(jj,ii) = (tmp_Cmax(jj)* (wts_pred(jj)/wts_prey(ii)) *a_vec(jj)*Npred(jj)*rho(jj,ii))/ + (b_vec(jj) + rho(jj)*avg_N_vec); + } + M_pred_sum_vec(ii) = sum(column(M_pred_mat,ii)); + } + + dvector dd_vec(1,n_pred_ages); + double dd_vec_sum = 10; + int iter = 0; + + while (dd_vec_sum > 1e-6) + { + iter++; + prev_tmp_abun_end_vec = tmp_abun_end_vec; + tmp_abun_end_vec = elem_prod(tmp_abun_vec,mfexp(-F_vec -tmp_M_vec -M_pred_sum_vec)); + avg_N_vec = elem_prod(tmp_abun_vec,elem_div((1-mfexp(-F_vec -tmp_M_vec -M_pred_sum_vec)),(F_vec + tmp_M_vec +M_pred_sum_vec))); + + for (ii=1;ii<=n_pred_ages;ii++) // loop over prey ages + { + for (jj=1;jj<=n_pred_grp;jj++) // loop over number of predators + { + M_pred_mat(jj,ii) = (tmp_Cmax(jj)*(wts_pred(jj)/wts_prey(ii))*a_vec(jj)*Npred(jj)*rho(jj,ii))/(b_vec(jj) + rho(jj)*avg_N_vec); + } + M_pred_sum_vec(ii) = sum(column(M_pred_mat,ii)); + } + + for (ii=1;ii<=n_pred_ages;ii++) + { + if (tmp_abun_end_vec(ii)>0.0) + { + dd_vec(ii) = value(prev_tmp_abun_end_vec(ii)) / value(tmp_abun_end_vec(ii)) - 1.; + if (dd_vec(ii)<0.) dd_vec(ii) *= -1.; + } + else dd_vec(ii) = 0.0; + } + dd_vec_sum = sum(dd_vec); + } + } + else + { + M_pred_mat = 0.0; + } + for (ii=1;ii<=n_pred_ages;ii++) + { + if (tmp_abun_end_vec(ii)==0.0) + { + for (jj=1;jj<=n_pred_grp;jj++) M_pred_mat(jj,ii) = 0.0; + } + } + RETURN_ARRAYS_DECREMENT(); + return M_pred_mat; + + +FUNCTION GetDependentVar + // For making some output for spiffy output + // Spiffy SR output + tmpsp=1.1*max(SSB); + if (tmpsp=2020) + { + regime(2) = mean(pred_rec(1978,2020)); + regime(5) = mean(pred_rec(1990,2020)); + regime(7) = mean(pred_rec(2000,2020)); + regime(8) = mean(pred_rec(1964,2020)); + regime(6) = mean(pred_rec(1990,1999)); + regime(3) = mean(pred_rec(1978,1999)); + } + else + { + if (endyr_r<=2000) + regime(7) = pred_rec(endyr_r); + else + regime(7) = mean(pred_rec(2000,endyr_r)); + + regime(2) = mean(pred_rec(1978,endyr_r)); + regime(5) = mean(pred_rec(1990,endyr_r)); + regime(8) = mean(pred_rec(1964,endyr_r)); + if (endyr_r<=1999) + { + regime(3) = mean(pred_rec(1978,endyr_r)); + regime(6) = mean(pred_rec(1990,endyr_r)); + } + else + { + regime(6) = mean(pred_rec(1990,1999)); + regime(3) = mean(pred_rec(1978,1999)); + } + } + if (!mceval_phase()) get_msy(); + + dvar_vector res(1,4); + res.initialize(); + res = get_msy_wt(); + Fmsy_wt = res(1); + MSY_wt = res(2); + Bmsy2_wt = res(3); + Fmsy2_wt = res(4); + // cout <<"Msy stuff: "<=1;iyr--) + { + res.initialize(); + sel_fut = sel_fsh(endyr_r-iyr+1); + // sel_fut /=sel_fut(6); // NORMALIZE TO AGE 6 + sel_fut /= mean(sel_fut); // NORMALIZE TO mean + if (!mceval_phase()) res = get_msy_wt(); + Fmsy2_dec(iyr) = res(4); + // cout <=1;iyr--) + { + res.initialize(); + wt_fut(3,nages) = wt_pre(endyr_wt-iyr+1); + if (!mceval_phase()) res = get_msy_wt(); + Fmsy2_decwt(iyr) = res(4); + // cout <8) + ftmp= mean(F(endyr_r)) * ((double(k-1)-1.)*.05 + 0.5); // this takes endyr F and brackets it...for mean + else + ftmp = SolveF2(natage_future(k,styr_fut),dec_tab_catch(k)); + } + // if (k==8) ftmp=Fmsy; + for (i=styr_fut;i<=endyr_fut;i++) + { + F_future(k,i) = sel_fut*ftmp; + Z_future(i) = F_future(k,i) + natmort; + S_future(i) = mfexp(-Z_future(i)); + dvariable criterion; + dvariable Bref ; + future_SSB(k,i) = elem_prod(elem_prod(natage_future(k,i),pow(S_future(i),yrfrac)), p_mature) * wt_ssb(endyr_r); + // Now compute the time of spawning SSB for everything else.... + // future_SSB(k,i) = elem_prod(elem_prod(natage_future(k,i),pow(S_future(i),yrfrac)), p_mature) * wt_ssb(endyr_r); + + if (phase_sr<0) //No Stock-recruitment curve for future projections-------- + natage_future(k,i, 1) = mfexp(log_avgrec + rec_dev_future(i)); + else //Use Stock-recruitment curve --------- + { + Xspawn =future_SSB(k,i-1); + natage_future(k,i,1) = SRecruit(Xspawn) * mfexp(rec_dev_future(i) ); + } + + future_R(k,i) = natage_future(k,i,1); + if (i0 ) + { + for (i=endyr_r-(nyrs_sel_avg+1);i3) get_combined_index(); + +FUNCTION Get_Cons_at_Age + // added by Paul + // if doing the spatial predation thing, get the consumption at age + for (i=styr;i<=endyr_r;i++) + { + for (k=1;k<=n_pred_ages;k++) + { + for (m=1;m<=n_pred_grp;m++) + { + cons_atage(m,i,k) = sum(cons(m,i,k)); // get ths consumption by predator, year, and age (summed over strata) + pred_cpup(m,i,k) = cons_atage(m,i,k)/N_pred(m,i); + } // predator loop + } // age loop + } // year loop + + for (i=styr;i<=endyr_r;i++) + { + yr_ind = i-1981; // for getting the index for the wt_bts + if(yr_ind<1) + yr_ind = 1; + if(yr_ind>38) + yr_ind = 38; + for (m=1;m<=n_pred_grp;m++) + { + cons_atage_wt(m,i) = elem_prod(cons_atage(m,i),wt_bts(yr_ind)(1,n_pred_ages)); + pred_cons(m,i) = sum(cons_atage_wt(m,i)); // the predicted consumption by predator and year (summed over age and strata) + eac_cons(m,i) = cons_atage_wt(m,i)/pred_cons(m,i); // the predicted consumption age comp (by predator and year) + } // predator loop + } // year loop + + for (i=styr;i<=endyr_r;i++) + { + yr_ind = i-1981; // for getting the index for the wt_bts + if(yr_ind<1) + yr_ind = 1; + if(yr_ind>38) + yr_ind = 38; + + for (m=1;m<=n_pred_grp;m++) + { + for (k=1;k<=n_pred_ages;k++) + { + // implied_obs_cons_bystrata(m,i,k) = obs_cons_natage_nonpoll(m,i,k)*(cons(m,iyr,k)/cons_atage(m,iyr,k)); + implied_obs_cons_bystrata(m,i,k) = cons(m,i,k); + for (z=1;z<=nstrata_pred;z++) + { + if (Npred_bystrata_nonpoll(i,m,z)>0) + { + implied_cpuppa(m,i,k,z) = implied_obs_cons_bystrata(m,i,k,z)/(Npred_bystrata_nonpoll(i,m,z)*area_pred(z)); + implied_prop_Cmax(m,i,k,z) = (implied_cpuppa(m,i,k,z)*area_pred(z))/ + ((mn_wgt_nonpoll(m,i)/(wt_bts(yr_ind,k)*1000))*Cmax_nonpoll(i,m,z)); + + // old code here -- used in model runs for Brazil paper + // implied_cpuppa(m,i,k,z) = + // (implied_obs_cons_bystrata(m,i,k,z)*((wt_bts(yr_ind,k)*1000)/mn_wgt_nonpoll(m,iyr)))/ + // (Cmax_nonpoll(iyr,m,z)*Npred_bystrata_nonpoll(iyr,m,z)*area_pred(z)); + // implied_prop_Cmax(m,i,k,z) = implied_cpuppa(m,i,k,z)*area_pred(z); + } + else + { + implied_cpuppa(m,i,k,z) = -9; + implied_prop_Cmax(m,i,k,z) = -9; + } + + /*cout <<"year is "<5||F1<0.01)) + { + ii=9; + count_Ffail++; + cout<5||F1<0.01)) + { + ii=5; + count_Ffail++; + cout< 0) + //rec_like(5) += 10.*norm2(log_rec_devs(endyr_est,endyr_r))/(2.*sigmarsq_out+.001); + + /* Larval drift contribution to recruitment prediction (not used in recent years) Eq. 8 + if (active(larv_rec_devs)) + rec_like(3) += ctrl_flag(23)*norm2(larv_rec_devs); + if (ctrl_flag(27)>0) + { + larv_rec_trans=trans(larv_rec_devs); + // Do third differencing on spatial aspect... + for (i=1;i<=11;i++) + { + rec_like(6) += ctrl_flag(27)*norm2(first_difference( first_difference(first_difference( larv_rec_devs(i))))); + rec_like(6) += ctrl_flag(27)*norm2(first_difference( first_difference(first_difference(larv_rec_trans(i))))); + } + } + */ + + // +===+====+==+==+==+==+==+==+==+====+====+==+==+===+====+==+==+==+==+==+==+==+====+====+====+ +FUNCTION Evaluate_Objective_Function + // if (active(repl_F)) + Recruitment_Likelihood(); + Surv_Likelihood(); //-survey Deviations + Selectivity_Likelihood(); + + catch_like = norm2(log(obs_catch(styr,endyr_r)+1e-4)-log(pred_catch+1e-4)); + + if (current_phase() >= robust_phase) + Robust_Likelihood(); //-Robust AGE Likelihood part + else + Multinomial_Likelihood(); //-Multinomial AGE Likelihood part + + NLL.initialize(); + NLL(1) += ctrl_flag(1) * catch_like; + NLL(2) += ctrl_flag(2) * surv_like(1); + NLL(3) += ctrl_flag(2) * surv_like(2); + NLL(4) += ctrl_flag(2) * surv_like(3); + NLL(5) += ctrl_flag(12) * cpue_like; + NLL(6) += ctrl_flag(6) * avo_like; + NLL(7) += ctrl_flag(3) * sum(rec_like); + if (phase_cope>0 & current_phase()>=phase_cope) + NLL(8) += cope_like; + F_pen = norm2(log_F_devs); + NLL(9) += ctrl_flag(4) * F_pen; + + NLL(10) += ctrl_flag(7)*age_like(1); + NLL(11) += ctrl_flag(8)*age_like(2); + NLL(12) += ctrl_flag(9)*age_like(3); + + if (use_endyr_len>0) + NLL(13)+= ctrl_flag(7)*len_like; + + NLL(14)+= sum(sel_like); + NLL(15)+= sum(sel_like_dev); + + //COUT(sel_like_dev); + // COUT(age_like); + // COUT(avo_like); + // COUT(surv_like); + + // Condition model in early phases to stay reasonable + // Removed at the end + if (current_phase()<3) + { + fff += 10.*square(log(mean(Fmort)/.2)); + fff += 10.*square(log_avginit-log_avgrec) ; //This is to make the initial comp not stray too far + } + + Priors.initialize(); + + if (active(natmort_phi)) // Sensitivity approach for estimating natural mortality (as offset of input vector, NOT USED, NOT IN DOC) + Priors(3) = norm2( log(natmort(3,nages) / natmortprior) )/(2.*cvnatmortprior*cvnatmortprior); + + // Prior on combined-survey catchability, idea is to have sum of two surveys tend to the prior distribution + // q_all.initialize(); + dvariable q_bts_tmp; + dvariable q_ats_tmp; + q_bts_tmp.initialize(); + q_ats_tmp.initialize(); + + for (i=1;i<=n_bts_r;i++) + { + iyr = yrs_bts_data(i); + // Note this is to correct for reduced survey strata coverage pre 1985 and in 86 + if (!(iyr<1985||iyr==1986)) + { + q_bts_tmp += sum(mfexp(log_q_bts + log_sel_bts(iyr)(q_amin,q_amax))); + } + } + q_bts_tmp /= ((q_amax-q_amin+1)*(n_bts_r-4)) ; // 4 years not in main q calc...OjO will break if BTS series length changes between 1982 and 86 + for ( i=1;i<=n_ats_r;i++) + { + iyr = yrs_ats_data(i); + q_ats_tmp += sum(mfexp(log_q_ats + log_sel_ats(iyr)(q_amin,q_amax))); + } + q_ats_tmp /= ((q_amax-q_amin+1)*n_ats_r) ; + q_all= log(q_bts_tmp + q_ats_tmp) ; + + // Note: optional ability to put a prior on "combined" surveys overall catchability + if (q_all_sigma<1.) + Priors(2) = square( q_all- q_all_prior )/(2.*q_all_sigma*q_all_sigma); + q_all = exp(q_all); + + // Prior on BTS catchability + if (active(log_q_bts)&&q_bts_sigma<1.) + { + Priors(2) = square( log_q_bts - q_bts_prior )/(2.*q_bts_sigma*q_bts_sigma); + // cout<0&&last_phase()) + { + get_msy(); + // cout<<"SPR: "<log_sel_fsh(i,j+1)) + sel_like(1)+=ctrl_flag(13)*square(log_sel_fsh(i,j)-log_sel_fsh(i,j+1)); + + + if (active(sel_coffs_bts)) + { + for (i=styr_bts;i<= endyr_r;i++) //--This is for controlling the selectivity shape BOTTOM TRAWL SURVEY + for (j=6;j<=n_selages_bts;j++) + if (log_sel_bts(i,j)>log_sel_bts(i,j+1)) + sel_like(2)+=ctrl_flag(14)*square(log_sel_bts(i,j)-log_sel_bts(i,j+1)); + } + + for (i=styr_ats;i<= endyr_r;i++) //--This is for selectivity shape HYDROA TRAWL SURVEY + for (j=mina_ats;j<=n_selages_ats;j++) + if (log_sel_ats(i,j)0.){ + dvar_matrix lnseltmp = trans(log_sel_bts); + for (j=q_amin;j3) + { + for (i=1;i<=n_bts_r;i++) + { + // Under development--not used (yet). Idea to combine surveys for directly accounting for differences + // of water column densities... + surv_like(1) += square(ot_cmb(i)-et_cmb(i))/(2.*var_cmb(i)); + // slight penalty here to get the q to scale correctly (note--development, not used) + surv_like(1) += .01*square(ot_bts(i)-et_bts(i))/(2.*var_ot_bts(i)); + } + // slight penalty here to get the q to scale correctly + for (i=1;i<=n_ats_r;i++) + surv_like(2) += .01*square(log(ot_ats(i)+.01)-log(et_ats(i)+.01))/ (2.*lvar_ats(i)) ; + } + else + { + // This is used (standard approach) Eq. 19, historically used normal distribution since year-by-year var_bts avail + // for (i=1;i<=n_bts_r;i// ++) + // surv_like(1) += square(ot_bts(i)-et_bts(i))/(2.*var_bts(i)); + + //dvar_vector srv_tmp = log(ot_bts + 1e-8)-log(et_bts + 1e-8); + // Note not logged... + + dvar_vector srv_tmp(1,n_bts_r); + // eb_bts *= q_bts; + // NOTE for VAST estimates the biomass is simply scaled + q_bts =mean(ob_bts)/mean(eb_bts); + eb_bts *= q_bts; + if (do_bts_bio) + srv_tmp = (ob_bts) - (eb_bts ); + else + srv_tmp = (ot_bts )-(et_bts ); + + switch (DoCovBTS) + { + case 0: // normal design-based estimates (no Covariance) + if (do_bts_bio) + { + srv_tmp = log(ob_bts) - log(eb_bts ); + for (i=1;i<=n_bts_r;i++) + surv_like(1) += square(srv_tmp(i))/(2.*var_ob_bts(i)); + } + + case 1: + surv_like(1) = .5 * srv_tmp * inv_bts_cov * srv_tmp; + break; + + case 2: // Test gen gamma + if (do_bts_bio) + { + for (i=1;i<=n_bts_r;i++) + if (sd_GenGam(i)>0) + surv_like(1) += dgengamma(ob_bts(i), eb_bts(i), sd_GenGam(i), q_GenGam(i)); + else{ + surv_like(1) += square(log(ob_bts(i))- log(eb_bts(i)))/ (2*var_ob_bts(i)); + } + } + break; + case 3: // lognormal + if (do_bts_bio) + { + // Need to fix up variance for this option... + srv_tmp = log(ob_bts) - log(eb_bts ); + } + break; + } + } + /* else + { + if (do_bts_bio) + { + for (i=1;i<=n_bts_r;i++) + surv_like(1) += square(srv_tmp(i))/(2.*var_ob_bts(i)); + } + else + { + for (i=1;i<=n_bts_r;i++) + surv_like(1) += square(srv_tmp(i))/(2.*var_ot_bts(i)); + } + } + surv_like(1) *= ctrl_flag(5); + */ + + // AT Biomass section + /* + */ + if (do_ats_bio) + { + for (i=1;i<=n_ats_r;i++) // Eq. 19 + surv_like(2) += square(log(ob_ats(i)+.01)-log(eb_ats(i)+.01))/ (2.*lvarb_ats(i)) ; + // #surv_like(2) += square(log(ob_ats(i)+.01)-log(eb_ats(i)+.01))/ (2.*var_ob_ats(i)) ; + } + else + { + for (i=1;i<=n_ats_r;i++) // Eq. 19 + surv_like(2) += square(log(ot_ats(i)+.01)-log(et_ats(i)+.01))/ (2.*lvar_ats(i)) ; + } + surv_like(2) *= ctrl_flag(2); + + if (use_age1_ats) + { + // Compute q for this age1 index... + dvariable qtmp = mfexp(mean(log(oa1_ats)-log(ea1_ats))); + if (ignore_last_ats_age1) + surv_like(3) = 0.5*norm2(log(oa1_ats(1,n_ats_r-1)+.01)-log(ea1_ats(1,n_ats_r-1)*qtmp +.01))/(age1_sigma_ats*age1_sigma_ats) ; + else + surv_like(3) = 0.5*norm2(log(oa1_ats+.01)-log(ea1_ats*qtmp +.01))/(age1_sigma_ats*age1_sigma_ats) ; + } + avo_like.initialize(); + cpue_like.initialize(); + cope_like.initialize(); + + dvar_vector cpue_dev = obs_cpue-pred_cpue; + for (i=1;i<=n_cpue;i++) + cpue_like += square(cpue_dev(i))/(2.*obs_cpue_var(i)); + + dvar_vector avo_dev = obs_avo-pred_avo; + for (i=1;i<=n_avo_r;i++) + avo_like += square(avo_dev(i))/(2.*obs_avo_var(i)); + + // if (phase_cope>0 & current_phase()>=phase_cope) + if (last_phase()) + { + if (phase_cope>0) + { + // Compute q for this age1 index... + int ntmp = n_cope - (yrs_cope(n_cope)+3-endyr_r); + dvariable qtmp = mfexp(mean(log(obs_cope(1,ntmp))-log(pred_cope(1,ntmp)))); + for (i=ntmp+1;i<=n_cope;i++) + pred_cope(i) = obs_cope(i)/qtmp; + pred_cope *= qtmp; + + // dvar_vector cope_dev = obs_cope-pred_cope; + for (i=1;i<=n_cope;i++) + cope_like += square(log(obs_cope(i))-log(pred_cope(i)))/ (2.*lvar_cope(i)) ; + // cope_like += square(cope_dev(i))/(2.*square(obs_cope_std(i))); + } + } + /* // This is for projecting Nage_3 but left out for now + else + { + if (sd_phase()) + { + for (i=1;i<=n_cope;i++) + { + if (yrs_cope(i)>endyr_r) + Nage_3(i) = natage_future(3,yrs_cope(i),3); + else + Nage_3(i) = natage(yrs_cope(i),3); + } + } + } + */ + if (sd_phase()) + Nage_3 = column(natage,3); + +FUNCTION Robust_Likelihood + age_like.initialize(); + len_like.initialize(); + // dvariable robust_p(const dmatrix& obs,const dvar_matrix& pred,const dvariable& a,const dvariable& b) + dvariable rf=.1/nages; + age_like(1) = robust_p(oac_fsh,eac_fsh,rf,sam_fsh); + age_like(2) = robust_p(oac_bts,eac_bts,rf,sam_bts); + + + if (current_phase() >= ats_robust_phase ) // ats robustness phase big number means do multinomial, not robust + age_like(3) = robust_p(oac_ats,eac_ats,rf,sam_ats,mina_ats,nages); + else // Multinomial for EIT + for (i=1; i <= nagecomp(3); i++) + age_like(3) -= sam_ats(i)*oac_ats(i)(mina_ats,nages) * log(eac_ats(i)(mina_ats,nages) + MN_const); + + len_like = robust_p(olc_fsh,elc_fsh,rf,50); + +FUNCTION Multinomial_Likelihood + age_like.initialize(); + len_like.initialize(); + //-Likelihood due to Age compositions-------------------------------- + for (int igear =1;igear<=ngears;igear++) + { + for (i=1; i <= nagecomp(igear); i++) + { + switch (igear) + { + case 1: + age_like(igear) -= sam_fsh(i)*oac_fsh(i)*log(eac_fsh(i) + MN_const); + break; + case 2: + age_like(igear) -= sam_bts(i)*oac_bts(i)*log(eac_bts(i) + MN_const); + break; + case 3: + age_like(igear) -= sam_ats(i)*oac_ats(i)(mina_ats,nages) * log(eac_ats(i)(mina_ats,nages) + MN_const); + break; + } + } + age_like(igear)-=age_like_offset(igear); + } + if (sd_phase() || mceval_phase()) // This to write out annual likelihood components + { + for (int igear =1;igear<=ngears;igear++) + { + for (i=1; i <= nagecomp(igear); i++) + { + switch (igear) + { + case 1: + age_like_yr(igear,i) -= sam_fsh(i)*oac_fsh(i)*log(eac_fsh(i) + MN_const); + break; + case 2: + age_like_yr(igear,i) -= sam_bts(i)*oac_bts(i)*log(eac_bts(i) + MN_const); + break; + default: + age_like_yr(igear,i) -= sam_ats(i)*oac_ats(i)(mina_ats,nages)*log(eac_ats(i)(mina_ats,nages) +MN_const); + break; + } + } + } + } + //len_like = sam_fsh(n_fsh_r)*olc_fsh*log(elc_fsh+MN_const); + len_like = -50*olc_fsh*log(elc_fsh+MN_const) - len_like_offset ; + + // this one allows a concentrated range of ages (last two args are min and max age range) +FUNCTION dvariable robust_p(dmatrix& obs,dvar_matrix& pred,const dvariable& a, const data_ivector& b, const int amin, const int amax) + if (obs.indexmin() != pred.indexmin() || obs.indexmax() != pred.indexmax() ) + cerr << "Index limits on observed vector are not equal to the Index\n" + "limits on the predicted vector in robust_p function\n"; + RETURN_ARRAYS_INCREMENT(); //Need this statement because the function returns a variable type + dvar_matrix v(obs.indexmin(),obs.indexmax(),amin,amax); + // dvar_matrix l = elem_div(square(pred - obs), v); + dvariable log_likelihood = 0.; + for (i=obs.indexmin();i<= obs.indexmax() ;i++) + { + v(i) = a + 2. * elem_prod(obs(i)(amin,amax) ,1. - obs(i)(amin,amax)); + dvar_vector l = elem_div(square(pred(i)(amin,amax) - obs(i)(amin,amax)), v(i)); + log_likelihood -= sum(log(mfexp(-1.* double(b(i)) * l) + .01)); + } + log_likelihood += 0.5 * sum(log(v)); + RETURN_ARRAYS_DECREMENT(); // Need this to decrement the stack increment + return(log_likelihood); + +FUNCTION dvariable robust_p(const dmatrix& obs,const dvar_matrix& pred,const dvariable& a, const data_ivector& b) + RETURN_ARRAYS_INCREMENT(); //Need this statement because the function returns a variable type + if (obs.indexmin() != pred.indexmin() || obs.indexmax() != pred.indexmax() ) + cerr << "Index limits on observed vector are not equal to the Index\n" + "limits on the predicted vector in robust_p function\n"; + // dvar_matrix v = a + 2. * elem_prod(pred ,1. - pred ); + dvar_matrix v = a + 2. * elem_prod(obs ,1. - obs ); + dvar_matrix l = elem_div(square(pred - obs), v); + dvariable log_likelihood = 0.; + for (i=obs.indexmin();i<= obs.indexmax() ;i++) + { + log_likelihood -= sum(log(mfexp(-1.* double(b(i)) * l(i)) + .01)); + } + log_likelihood += 0.5 * sum(log(v)); + RETURN_ARRAYS_DECREMENT(); // Need this to decrement the stack increment + return(log_likelihood); + +FUNCTION dvariable robust_p(const dmatrix& obs, const dvar_matrix& pred, const dvariable& a, const dvariable& b) + RETURN_ARRAYS_INCREMENT(); //Need this statement because the function + if (obs.indexmin() != pred.indexmin() || obs.indexmax() != pred.indexmax() ) + cerr << "Index limits on observed vector are not equal to the Index\n" + "limits on the predicted vector in robust_p function\n"; + //returns a variable type + + // dvar_matrix v = a + 2. * elem_prod(pred ,1. - pred ); + dvar_matrix v = a + 2. * elem_prod(obs ,1. - obs ); + dvar_matrix l = mfexp(- b * elem_div(square(pred - obs), v )); + dvariable log_likelihood = -1.0*sum(log(l + .01)); + log_likelihood += 0.5 * sum(log(v)); + RETURN_ARRAYS_DECREMENT(); // Need this to decrement the stack increment + return(log_likelihood); + +FUNCTION dvariable robust_p(const dvector& obs, const dvar_vector& pred, const dvariable& a, const dvariable& b) + RETURN_ARRAYS_INCREMENT(); //Need this statement because the function + if (obs.indexmin() != pred.indexmin() || obs.indexmax() != pred.indexmax() ) + cerr << "Index limits on observed vector are not equal to the Index\n" + "limits on the predicted vector in robust_p function\n"; + //returns a variable type + + // dvar_matrix v = a + 2. * elem_prod(pred ,1. - pred ); + dvar_vector v = a + 2. * elem_prod(obs ,1. - obs ); + dvar_vector l = mfexp(- b * elem_div(square(pred - obs), v )); + dvariable log_likelihood = -1.0*sum(log(l + .01)); + log_likelihood += 0.5 * sum(log(v)); + RETURN_ARRAYS_DECREMENT(); // Need this to decrement the stack increment + return(log_likelihood); + +FUNCTION write_srec + srecout << "Yearclass SSB Recruit Pred_Rec Residual"<0) + SimulateData1(); + else + { + // if (!pflag) + /* + for (int k=1;k<=nscen;k++) + { + write_mceval(future_SSB(k)); + write_mceval(future_catch(k)); + } + write_mceval(Fcur_Fmsy); + write_mceval(Bcur_Bmsy); + write_mceval(Bcur_Bmean); + write_mceval(Bcur2_Bmsy); + write_mceval(Bcur2_B20); + write_mceval(Bcur3_Bcur); + write_mceval(Bcur3_Bmean); + write_mceval(LTA1_5R); + write_mceval(LTA1_5); + write_mceval(MatAgeDiv1); + write_mceval(MatAgeDiv2); + write_mceval(RelEffort); + write_mceval <>catchtmp; + catchin.close(); + obs_catch_sim(iproj_yr) = catchtmp; + for (int itmp=1;itmp<=iproj_yr;itmp++) + simdat << obs_catch_sim(itmp) <=1;iyr--) + { + sel_fut = sel_fsh(endyr_r-iyr+1); + sel_fut /= mean(sel_fut); // NORMALIZE TO mean + report<=1;iyr--) + { + wt_fut(3,nages) = wt_pre(endyr_wt-iyr+1); + report< age1tmp) report << age1tmp-1 << " " < age1tmp) report << age1tmp-1 << " " < age1tmp) report << age1tmp-1 << " " < age1tmp) report << age1tmp-1 << " " < age1tmp) report << age1tmp-1 << " " < age1tmp) report << age1tmp-1 << " " < age1tmp) report << age1tmp-1 << " " <LENGTH-------------------------------------------------- +FUNCTION Get_Age2length + // Linf=Linfprior;// Asymptotic length + // k_coeff=kprior; + // Lo=Loprior;// first length (corresponds to first age-group) + // sdage=sdageprior;// coefficient of variation of length-at-age + // if some of these are estimated. + // L1 25.23382299 k 0.139339914 Linf 68.43045172 + double Linf = 68.43045172 ; + double k_coeff = 0.139339914 ; + double Lo = 25.23382299 ; + double sdage = .06; + dvar_vector mu_age(1,nages); + dvar_vector sigma_age(1,nages); + int i, j; + mu_age(1)=Lo; // first length (modal) + for (i=2;i<=nages;i++) + mu_age(i) = Linf*(1.-exp(-k_coeff))+exp(-k_coeff)*mu_age(i-1); // the mean length by age group + // wt_age_vb(r) = lw_a * pow(mu_age, lw_b); + // maturity_vb(r) = 1/(1 + exp(32.93 - 1.45*mu_age(r))); + sigma_age = sdage*mu_age; // standard deviation of length-at-age + age_len = value(Age_Len_Conversion( mu_age, sigma_age, lens)); + write_log(sigma_age); + +FUNCTION dvar_matrix Age_Len_Conversion(dvar_vector& mu, dvar_vector& sig, dvector& x) + //RETURN_ARRAYS_INCREMENT(); + int i, j; + dvariable z1; + dvariable z2; + int si,ni; si=mu.indexmin(); ni=mu.indexmax(); + int sj,nj; sj=x.indexmin(); nj=x.indexmax(); + dvar_matrix pdf(si,ni,sj,nj); + double xs; + pdf.initialize(); + for(i=si;i<=ni;i++) //loop over ages + { + for(j=sj;j<=nj;j++) //loop over length bins + { + if (jint(1) ) + wt_hat(h,i) = elem_prod(d_scale(h-1) , wt_pre(iyr) ); + else + wt_hat(h,i) = wt_pre(iyr); + + for (int j=age_st;j<=age_end;j++) + { + wt_like += square(wt_obs(h,i,j) - mnwt(j)) /(2.*square(sd_obs(h,i,j))); + wt_like += square(wt_obs(h,i,j) - wt_hat(h,i,j))/(2.*square(sd_obs(h,i,j))); + } + } + } + wt_like += 0.5*norm2(coh_eff); + wt_like += 0.5*norm2( yr_eff); + fff += wt_like; + wt_last = wt_pre(endyr_wt-3); //*exp(sigma_coh*sigma_coh/2. + sigma_yr*sigma_yr/2.);; + wt_cur = wt_pre(endyr_wt-2); //*exp(sigma_coh*sigma_coh/2. + sigma_yr*sigma_yr/2.);; + wt_next = wt_pre(endyr_wt-1); //*exp(sigma_coh*sigma_coh/2. + sigma_yr*sigma_yr/2.);; + wt_yraf = wt_pre(endyr_wt); //*exp(sigma_coh*sigma_coh/2. + sigma_yr*sigma_yr/2.);; + // wt_last = wt_pre(endyr_r-1); //*exp(sigma_coh*sigma_coh/2. + sigma_yr*sigma_yr/2.);; + // wt_cur = wt_pre(endyr_r ); //*exp(sigma_coh*sigma_coh/2. + sigma_yr*sigma_yr/2.);; + // wt_next = wt_pre(endyr_r+1); //*exp(sigma_coh*sigma_coh/2. + sigma_yr*sigma_yr/2.);; + // wt_yraf = wt_pre(endyr_r+2); //*exp(sigma_coh*sigma_coh/2. + sigma_yr*sigma_yr/2.);; + + // Condition on using this based on wt flag + if (wt_fut_phase>0) + { + // Use cohort and year effects fits for current year catch + pred_catch(endyr_r) = catage(endyr_r)(3,nages) * wt_cur; + + // Set future catch equal to estimate from model + // Only model wts-at-age from 3+ so this is the 1's and 2's + pred_catch(endyr_r) = catage(endyr_r)(1,2) * wt_fsh(endyr_r)(1,2); + // wt_fut = wt_fsh(endyr_r); // initializes estimates to correct values...Eq. 21 + wt_fut(3,nages) = wt_next; // initializes estimates to correct values...Eq. 21 + } +FUNCTION dvariable dgengamma(const double& x, dvariable mean2, const double& sigma, const double& Q) + // returns negative log-likelihood of generalized gamma distribution + RETURN_ARRAYS_INCREMENT(); + double k = pow( Q, -2 ); + double Beta = pow( sigma, -1 ) * Q; + dvariable log_theta = log(mean2) - lgamma( (k*Beta+1)/Beta ) + lgamma( k ); + dvariable mu = log_theta + log(k) / Beta; + dvariable w = (log(x) - mu) / sigma; + double abs_q = sqrt(Q*Q); // = abs(Q); not differentiable! + double qi = 1/square(Q); + dvariable qw = Q*w; + dvariable logres = -log(sigma*x) + log(abs_q) * (1. - 2. * qi) + qi * + (qw - exp(qw)) - lgamma(qi); + RETURN_ARRAYS_DECREMENT(); + return(-logres); + +FUNCTION double sdnr(const dvector& obs, const dvar_vector& pred, const dvector& sig) + RETURN_ARRAYS_INCREMENT(); + double sdnr; + sdnr = std_dev(elem_div((obs-value(pred)),sig)); + RETURN_ARRAYS_DECREMENT(); + return sdnr; + + /* ****************************************************** + FUNCTION dvariable Check_Parm(const double& Pmin, const double& Pmax, const double& jitter, const prevariable& Pval) + { + dvariable NewVal; + dvariable temp; + NewVal=Pval; + if(PvalPmax) + {N_warn++; warning<<" parameter init value is greater than parameter max "< "<0.0) + { + temp=log((Pmax-Pmin+0.0000002)/(NewVal-Pmin+0.0000001)-1.)/(-2.); // transform the parameter + temp += randn(radm) * jitter; + NewVal=Pmin+(Pmax-Pmin)/(1.+mfexp(-2.*temp)); + } + return NewVal; + } + */ + + /** + * @brief Calculate sdnr and MAR + **/ + /** + FUNCTION void get_all_sdnr_MAR() + { + for ( int k = 1; k <= nSurveys; k++ ) + { + dvector stdtmp = cpue_sd(k) * 1.0 / cpue_lambda(k); + dvar_vector restmp = elem_div(log(elem_div(obs_cpue(k), pre_cpue(k))), stdtmp) + 0.5 * stdtmp; + sdnr_MAR_cpue(k) = calc_sdnr_MAR(value(restmp)); + } + for ( int k = 1; k <= nSizeComps; k++ ) + { + //dvector sdtmp = cpue_sd(k) * 1.0 / cpue_lambda(i); + sdnr_MAR_lf(k) = calc_sdnr_MAR(value(d3_res_size_comps(k))); + } + Francis_weights = calc_Francis_weights(); + } + + + FUNCTION dvector calc_sdnr_MAR(dvector tmpVec) + { + dvector out(1,2); + dvector tmp = fabs(tmpVec); + dvector w = sort(tmp); + out(1) = std_dev(tmpVec); // sdnr + out(2) = w(floor(0.5*(size_count(w)+1))); // MAR + return out; + } + + + FUNCTION dvector calc_sdnr_MAR(dmatrix tmpMat) + { + dvector tmpVec(1,size_count(tmpMat)); + dvector out(1,2); + int dmin,dmax; + dmin = 1; + for ( int ii = tmpMat.indexmin(); ii <= tmpMat.indexmax(); ii++ ) + { + dmax = dmin + size_count(tmpMat(ii)) - 1; + tmpVec(dmin,dmax) = tmpMat(ii).shift(dmin); + dmin = dmax + 1; + } + dvector tmp = fabs(tmpVec); + dvector w = sort(tmp); + out(1) = std_dev(tmpVec); // sdnr + out(2) = w(floor(0.5*(size_count(w)+1))); // MAR + return out; + } + **/ + +FUNCTION dvector rmultinomial(const dvector ptmp, const int n_sam) + int i1=ptmp.indexmin(); + int i2=ptmp.indexmax(); + dvector freq(i1,i2); + dvector p(i1,i2); + ivector bin(1,n_sam); + p = ptmp; + p /= sum(p); + bin.fill_multinomial(rng,p); // fill a vector v + for (int j=1;j<=n_sam;j++) + freq(bin(j))++; + // Apply ageing error to samples.............. + return( freq/sum(freq) ); + /** + * @brief Calculate Francis weights + * @details this code based on equation TA1.8 in Francis(2011) should be changed so separate weights if by sex + * + * Produces the new weight that should be used. + **/ +FUNCTION double calc_Francis_weights(const dmatrix oac, const dvar_matrix eac, const ivector sam ) + { + int nobs; + int i1=oac.rowmin(); + int i2=oac.rowmax(); + double lfwt,Var,Pre,Obs; + dvector ages(oac.colmin(),nages); + for (int i=oac.colmin();i<=nages;i++) + ages(i) = double(i)+.5; + nobs = oac.rowsize(); + dvector resid(i1,i2); + resid.initialize(); + for ( int i = i1; i <= i2; i++ ) + { + // Obs = sum(elem_prod(oac(i), ages+.5)); + Obs = oac(i) * (ages+.5); + // Pre = sum(elem_prod(value(eac(i)), ages+.5)); + Pre = value(eac(i)) * (ages+.5); + Var = value(eac(i)) * square(ages+.5); + Var -= square(Pre); + resid(i) = (Obs - Pre) / sqrt(Var * 1.0 / (sam(i) )); + // cout<<"FW "<0) + SimulateData1(); + //cout<< "Estimated and SR-predicted recruits"<0) + report<< -dgengamma(ob_bts(i), eb_bts(i), sd_GenGam(i), q_GenGam(i))< + #include + + #undef simwrite + #define simwrite(object) simdat << "#"<<#object << endl << object << endl; + + #undef simrep + #define simrep(object,n) for (int itmp=1;itmp<=n;itmp++) {simdat << object<<" "; } simdat<< endl; + + #undef COUT + #define COUT(object) cout << #object "," << object << endl; + + ofstream proj_df("proj_df.csv"); + #undef proj_df + #define proj_df(object) proj_df << #object "\n" << object << endl; + + ofstream misc_out("misc_out.rep"); + #undef misc_out + #define misc_out(object) misc_out << #object "\n" << object << endl; + + ofstream for_sd("extra_sd.rep"); + #undef for_sd + #define for_sd(object) for_sd << #object "\n" << object << endl; + + ofstream write_mcFmort("mcFmort.rep"); + #undef write_mcFmort + #define write_mcFmort(object) write_mcFmort << " " << object ; + + ofstream write_mcSRR("mcSRR.rep"); + #undef write_mcSRR + #define write_mcSRR(object) write_mcSRR << " " << object ; + + ofstream write_mceval("mceval.rep"); + #undef write_mceval + #define write_mceval(object) write_mceval << " " << object ; + + ofstream mceval_ac_ppl("mceval_ac_ppl.csv"); + #undef write_mceval_ac_ppl + #define write_mceval_ac_ppl(object) mceval_ac_ppl << "," << object ; + + + ofstream mceval_ppl("mceval_ppl.csv"); + #undef write_mceval_ppl + #define write_mceval_ppl(object) mceval_ppl << "," << object ; + + ofstream write_mceval_eb_bts("mceval_eb_bts.rep"); + #undef write_mceval_eb_bts + #define write_mceval_eb_bts(object) write_mceval_eb_bts << " " << object ; + + ofstream write_mceval_eb_ats("mceval_eb_ats.rep"); + #undef write_mceval_eb_ats + #define write_mceval_eb_ats(object) write_mceval_eb_ats << " " << object ; + + ofstream write_mceval_ea1_ats("mceval_ea1_ats.rep"); + #undef write_mceval_ea1_ats + #define write_mceval_ea1_ats(object) write_mceval_ea1_ats << " " << object ; + + ofstream write_mceval_pred_catch("mceval_pred_catch.rep"); + #undef write_mceval_pred_catch + #define write_mceval_pred_catch(object) write_mceval_pred_catch << " " << object ; + + ofstream write_mceval_eac_fsh("mceval_eac_fsh.rep"); + #undef write_mceval_eac_fsh + #define write_mceval_eac_fsh(object) write_mceval_eac_fsh << " " << object ; + + ofstream write_mceval_eac_bts("mceval_eac_bts.rep"); + #undef write_mceval_eac_bts + #define write_mceval_eac_bts(object) write_mceval_eac_bts << " " << object ; + + ofstream write_mceval_eac_ats("mceval_eac_ats.rep"); + #undef write_mceval_eac_ats + #define write_mceval_eac_ats(object) write_mceval_eac_ats << " " << object ; + + ofstream write_mceval_pred_cpue("mceval_pred_cpue.rep"); + #undef write_mceval_pred_cpue + #define write_mceval_pred_cpue(object) write_mceval_pred_cpue << " " << object ; + + ofstream write_mceval_pred_avo("mceval_pred_avo.rep"); + #undef write_mceval_pred_avo + #define write_mceval_pred_avo(object) write_mceval_pred_avo << " " << object ; + + ofstream write_mceval_mnwt("mceval_mnwt.rep"); + #undef write_mceval_mnwt + #define write_mceval_mnwt(object) write_mceval_mnwt << " " << object ; + + ofstream write_mceval_fsh_wt("mceval_fsh_wt.rep"); + #undef write_mceval_fsh_wt + #define write_mceval_fsh_wt(object) write_mceval_fsh_wt << " " << object ; + + ofstream write_mceval_srv_wt("mceval_srv_wt.rep"); + #undef write_mceval_srv_wt + #define write_mceval_srv_wt(object) write_mceval_srv_wt << " " << object ; + + ofstream write_mceval_ssb_rec("mceval_ssb_rec.rep"); + #undef write_mceval_ssb_rec + #define write_mceval_ssb_rec(object) write_mceval_ssb_rec << " " << object ; + + ofstream write_log("Input_Log.rep"); + #undef write_log + #define write_log(object) write_log << #object "\n" << object << endl; + + ofstream retro_out("retro.rep",ios::app); + #undef write_retro + #define write_retro(object) retro_out << #object " " <catch.dat +cat catch.dat diff --git a/2024/runs/om/em/pm b/2024/runs/om/em/pm new file mode 120000 index 0000000..d7569ef --- /dev/null +++ b/2024/runs/om/em/pm @@ -0,0 +1 @@ +../pm \ No newline at end of file diff --git a/2024/runs/om/em/pm.dat b/2024/runs/om/em/pm.dat new file mode 100644 index 0000000..c163197 --- /dev/null +++ b/2024/runs/om/em/pm.dat @@ -0,0 +1,10 @@ +sim +pm_data.dat +../selvar.dat +control.dat +../../data/pm_fmsy_alt.dat +../cov_2023.dat +../../data/wtage2023.dat +../../data/surveycpue.dat +../paul.dat +../q_bts.dat diff --git a/2024/runs/om/em/pm.prj b/2024/runs/om/em/pm.prj new file mode 100644 index 0000000..e69de29 diff --git a/2024/runs/om/em/pm_data.dat b/2024/runs/om/em/pm_data.dat new file mode 100644 index 0000000..fea9ee3 --- /dev/null +++ b/2024/runs/om/em/pm_data.dat @@ -0,0 +1,520 @@ +#styr +1964 +#styr_bts +1982 +#styr_ats +1994 +#endyr+iproj_yr +2027 +#recage +1 +#nages +15 +#2*p_mature + 0 0.008 0.289 0.641 0.842 0.901 0.947 0.963 0.97 1 1 1 1 1 1 +#ewnsindex + 8 7 2 9 7 7 7 7 8 6 5 7 8 8 7 5 4 6 7 8 3 7 7 7 7 8 4 6 2 1 6 6 4 4 10 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 + 5 6 6 8 5 8 5 4 8 4 5 5 6 5 8 11 6 7 9 10 4 4 6 5 7 9 5 7 3 5 3 5 4 6 11 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 +#wt_fsh + 0.0066 0.17 0.303 0.447 0.589 0.722 0.84 0.942 1.029 1.102 1.163 1.212 1.253 1.286 1.312 + 0.0066 0.17 0.303 0.447 0.589 0.722 0.84 0.942 1.029 1.102 1.163 1.212 1.253 1.286 1.312 + 0.0066 0.17 0.303 0.447 0.589 0.722 0.84 0.942 1.029 1.102 1.163 1.212 1.253 1.286 1.312 + 0.0066 0.17 0.303 0.447 0.589 0.722 0.84 0.942 1.029 1.102 1.163 1.212 1.253 1.286 1.312 + 0.0066 0.17 0.303 0.447 0.589 0.722 0.84 0.942 1.029 1.102 1.163 1.212 1.253 1.286 1.312 + 0.0066 0.17 0.303 0.447 0.589 0.722 0.84 0.942 1.029 1.102 1.163 1.212 1.253 1.286 1.312 + 0.0066 0.17 0.303 0.447 0.589 0.722 0.84 0.942 1.029 1.102 1.163 1.212 1.253 1.286 1.312 + 0.0066 0.17 0.303 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5.72e-37 4.96e-27 1.01e-18 4.86e-12 5.73e-07 0.00176 0.164 0.669 0.163535 0.00175627 5.73e-07 4.86e-12 0 0 + 1.53e-53 3.84e-42 3.73e-32 1.42e-23 2.12e-16 1.27e-10 3.13e-06 0.00336 0.18 0.634 0.179774 0.00335636 3.13e-06 1.27e-10 0 + 4.45e-58 6.52e-47 5.64e-37 2.88e-28 8.78e-21 1.6e-14 1.78e-09 1.24e-05 0.00569 0.194 0.600935 0.193828 0.00569276 1.24e-05 1.78e-09 + 3.32e-62 2.65e-51 1.75e-41 9.64e-33 4.43e-25 1.71e-18 5.57e-13 1.56e-08 3.86e-05 0.00881 0.206 0.570832 0.205734 0.00881111 3.86e-05 + 5.73e-66 2.39e-55 1.1e-45 5.57e-37 3.13e-29 1.95e-22 1.36e-16 1.06e-11 9.5e-08 9.93e-05 0.0127 0.215603 0.543205 0.215603 0.0127942 + 2.08e-69 4.47e-59 1.34e-49 5.65e-41 3.33e-33 2.76e-26 3.22e-20 5.34e-15 1.26e-10 4.33e-07 0.00022 0.0172757 0.223589 0.517829 0.241086 + 1.46e-72 1.62e-62 3.07e-53 9.94e-45 5.52e-37 5.26e-30 8.63e-24 2.44e-18 1.2e-13 1.03e-09 1.57e-06 0.000433888 0.0224485 0.229872 0.747244 +#nlbins +50 +#olc_fsh + 0.000155363 8.34256e-05 7.67429e-05 0.000118744 0.000131 0.000165676 0.000462502 0.000816164 0.0014853 0.00349217 0.00648251 0.0122926 0.0208559 0.0330352 0.0518852 0.0698884 0.0818884 0.0850309 0.0706065 0.0527404 0.0356825 0.0255196 0.0211611 0.0231594 0.0278773 0.0371028 0.0435329 0.0473829 0.046224 0.0418302 0.0367093 0.029873 0.0237344 0.0182052 0.012919 0.0102773 0.00712691 0.00557235 0.00390163 0.00293623 0.00219387 0.00146556 0.00121571 0.000831263 0.000627142 0.000379651 0.000319687 0.00024473 0.000171208 0.000130158 +#age_lenold + 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 + 0.99 0.00949 2.22e-05 2.22e-05 3.44e-07 8.89e-09 6.42e-10 3.83e-11 1.89e-12 7.67e-14 2.55e-15 1.11e-16 0 0 0 0 0 0 0 0 0 0 0 0 0 + 0.18 0.234 0.271 0.196 0.0746 0.0241 0.0118277 0.00514832 0.00198581 0.000678747 0.000205576 5.52e-05 1.31e-05 2.76e-06 5.16e-07 9.45e-08 5.14e-09 6.64e-11 5.32e-13 2.66e-15 0 0 0 0 0 + 0.00166 0.00913 0.0377 0.105 0.14 0.118 0.127 0.123 0.108 0.085343 0.0611639 0.0396254 0.0232061 0.0122851 0.00587894 0.00316157 0.000799915 7.79e-05 5.1e-06 2.24e-07 6.61e-09 1.31e-10 1.73e-12 1.53e-14 0 + 2.23e-06 3.45e-05 0.000382 0.00289 0.00901 0.0142 0.0258 0.0427 0.0641 0.0873 0.107986 0.121218 0.123525 0.11427 0.0959612 0.101111 0.0649271 0.019726 0.00410357 0.000584149 5.69e-05 3.78e-06 1.72e-07 5.32e-09 1.14e-10 + 2.71e-08 5.22e-07 7.65e-06 8.2e-05 0.000357 0.000736 0.00172 0.00373 0.00747 0.0138 0.0236 0.0372748 0.0543789 0.0733052 0.091312 0.160683 0.217652 0.166757 0.0937213 0.0386334 0.0116778 0.00258769 0.000420211 5e-05 4.65e-06 + 8.28e-10 1.75e-08 2.92e-07 3.73e-06 1.93e-05 4.59e-05 0.000123 0.00031 0.000728 0.0016 0.00327 0.00627 0.0112259 0.0187853 0.0293778 0.0702166 0.149284 0.1976 0.200435 0.155804 0.0928067 0.0423586 0.0148119 0.00396752 0.000958662 + 5.3e-11 1.16e-09 2.06e-08 2.88e-07 1.64e-06 4.24e-06 1.23e-05 3.38e-05 8.71e-05 0.000212 0.000485 0.00104 0.00212 0.00405257 0.00729594 0.0211652 0.0600186 0.112302 0.165885 0.193449 0.178104 0.129457 0.0742853 0.0336497 0.0163364 + 1.11e-11 2.24e-10 3.81e-09 5.24e-08 2.99e-07 7.82e-07 2.32e-06 6.53e-06 1.74e-05 4.4e-05 0.000106 0.00024 0.000517 0.00105806 0.0020515 0.00662611 0.0222172 0.0512141 0.09572 0.145061 0.178256 0.177621 0.143515 0.0940267 0.0816991 + 1.41e-11 2.2e-10 3.03e-09 3.49e-08 1.76e-07 4.27e-07 1.2e-06 3.2e-06 8.19e-06 2e-05 4.67e-05 0.000104 0.000222 0.0004529 0.00088199 0.00289994 0.0101866 0.0254174 0.0529996 0.0923566 0.134502 0.163705 0.166523 0.141568 0.208101 + 2.43e-11 3.02e-10 3.43e-09 3.33e-08 1.49e-07 3.34e-07 8.81e-07 2.23e-06 5.43e-06 1.27e-05 2.86e-05 6.18e-05 0.000128 0.000257 0.000493 0.00160724 0.0056728 0.0145423 0.031884 0.0597899 0.0958971 0.131557 0.154367 0.154929 0.348763 + 5.09e-11 5.12e-10 4.87e-09 4.03e-08 1.61e-07 3.35e-07 8.31e-07 1.99e-06 4.6e-06 1.03e-05 2.22e-05 4.63e-05 9.31e-05 0.000181 0.00034 0.00108314 0.00375339 0.00959398 0.0213601 0.0414229 0.0699713 0.102955 0.131954 0.147316 0.469891 + 1.18e-10 9.82e-10 7.95e-09 5.69e-08 2.04e-07 3.96e-07 9.28e-07 2.11e-06 4.64e-06 9.9e-06 2.05e-05 4.11e-05 7.98e-05 0.00015 0.000275 0.00085008 0.00285607 0.00715572 0.0158468 0.03102 0.0536731 0.0820898 0.11098 0.132623 0.56232 + 2.89e-10 2.01e-09 1.41e-08 8.85e-08 2.88e-07 5.22e-07 1.16e-06 2.5e-06 5.26e-06 1.07e-05 2.13e-05 4.11e-05 7.72e-05 0.000141 0.00025 0.000748308 0.00242205 0.00589158 0.0128208 0.0249597 0.0434717 0.0677361 0.0944239 0.117759 0.629216 + 2.36e-10 1.36e-09 8.28e-09 4.58e-08 1.36e-07 2.34e-07 4.97e-07 1.03e-06 2.09e-06 4.15e-06 8.02e-06 1.52e-05 2.8e-05 5.05e-05 8.89e-05 0.000265358 0.000866491 0.00216402 0.00492189 0.0101948 0.0192308 0.0330367 0.0516864 0.0736438 0.803791 +#EOF +1234567 diff --git a/2024/runs/om/em/pmsr.prj b/2024/runs/om/em/pmsr.prj new file mode 100644 index 0000000..e69de29 diff --git a/2024/runs/om/em/proj_df.csv b/2024/runs/om/em/proj_df.csv new file mode 100644 index 0000000..e69de29 diff --git a/2024/runs/om/paul.dat b/2024/runs/om/paul.dat new file mode 100644 index 0000000..c3dee8a --- /dev/null +++ b/2024/runs/om/paul.dat @@ -0,0 +1,471 @@ +# Data file for SST temperature, Consumption estimates, and spatial distribution of pollock and ATF +# To be consistent with 2020 pollock model, extend data (where appropriate) by one year +# with PLACEHOLDER VALUES, TO BE FINALIZED LATER + +# Summer SST (1963 to 2019, from Kearny hindcast (B10K-K20_CORECFS)) +# Summer SST (1963 to 2020, from Kearny hindcast (B10K-K20_CORECFS)) +9.156797693 8.853836656 9.024034595 9.36530107 10.45591739 9.78034906 10.06023983 9.129846 8.293262 9.578705 8.92675 9.747115 9.103794 9.255449 10.710193 10.172035 10.442624 10.083121 10.634558 9.290167 10.595447 10.274514 9.532808 9.344515 10.528864 9.94015 10.438807 9.892196 10.311824 9.296852 10.526982 9.760453 9.896575 9.380796 10.160248 9.045305 8.650129 9.27298 9.346503 10.527505 10.942544 11.709321 10.916911 9.360558 9.718449 9.030152 8.813312 9.262602 8.343 7.988732 9.296986 11.891247 10.442589 12.086488 9.945973 10.195702 11.760843 11 11 11 +# the number of non-pollock predators +2 +# the number of pollock predators +0 +# the abundance of the predators (millions, rows 1 = atf< 40 cm, row 2 = atf >= 40 cm, col = years (1964-2020)) +279.942 263.156 248.838 237.309 232.838 237.939 259.565 319.413 615.746 650.992 575.300 455.462 314.884 198.877 131.237 145.531 270.296 480.287 531.046 522.431 708.743 759.786 781.147 1032.219 1238.928 1346.196 1324.263 1149.172 1002.239 832.082 718.024 662.320 767.787 800.677 850.433 1092.355 1248.308 1299.061 1423.407 1460.651 1425.633 1316.788 1306.568 1228.328 1106.883 1012.786 893.258 793.306 773.338 869.873 921.653 901.745 881.964 1655.333 1769.465 926.185 1000.00 1000 1000 1000 +145.033 143.486 140.828 137.303 133.016 128.134 123.090 118.431 114.785 113.121 115.291 130.455 152.629 179.090 186.558 170.024 141.671 113.012 92.419 83.924 93.712 119.353 146.077 167.474 184.421 209.929 239.879 276.093 328.538 380.777 408.841 410.752 391.786 365.755 339.683 322.376 318.110 323.410 337.077 363.318 399.442 435.097 465.278 491.439 505.163 505.291 498.146 486.771 467.316 440.347 410.543 383.923 367.593 366.432 374.673 359.419 350.00 350 350 340 +# number of strata for computing spatial predation +5 +# strata index numbers +1020 30 40 50 60 +# the number of ages which are preyed upon +3 +# the ages which are preyed upon +1 2 3 +# distribution of age 1 pollock across strata, by year (rows) +0.22824 0.12391 0.31353 0.00471 0.32962 +0.22824 0.12391 0.31353 0.00471 0.32962 +0.22824 0.12391 0.31353 0.00471 0.32962 +0.22824 0.12391 0.31353 0.00471 0.32962 +0.22824 0.12391 0.31353 0.00471 0.32962 +0.22824 0.12391 0.31353 0.00471 0.32962 +0.22824 0.12391 0.31353 0.00471 0.32962 +0.22824 0.12391 0.31353 0.00471 0.32962 +0.22824 0.12391 0.31353 0.00471 0.32962 +0.22824 0.12391 0.31353 0.00471 0.32962 +0.22824 0.12391 0.31353 0.00471 0.32962 +0.22824 0.12391 0.31353 0.00471 0.32962 +0.22824 0.12391 0.31353 0.00471 0.32962 +0.22824 0.12391 0.31353 0.00471 0.32962 +0.22824 0.12391 0.31353 0.00471 0.32962 +0.22824 0.12391 0.31353 0.00471 0.32962 +0.22824 0.12391 0.31353 0.00471 0.32962 +0.22824 0.12391 0.31353 0.00471 0.32962 +0.053100424 0.158232561 0.325286708 0.047911089 0.415469218 +0.234586014 0.061901024 0.377765234 0.001437464 0.324310264 +0.222415876 0.111479245 0.310030569 0.00589687 0.35017744 +0.62616141 0.028870861 0.218398435 0.00027064 0.126298653 +0.322226113 0.155598397 0.333470566 0.002567808 0.186137115 +0.14189301 0.182171439 0.550407479 0.003889663 0.121638408 +0.104494783 0.076364944 0.114525884 0.001599518 0.703014871 +0.252957721 0.091862578 0.36368667 0.000375566 0.291117465 +0.195587127 0.13797882 0.244961664 0.002537561 0.418934828 +0.165280753 0.138211547 0.171849032 0.000837337 0.523821331 +0.22230492 0.040090997 0.357601641 0.021623632 0.358378809 +0.366588618 0.132313984 0.300063928 0.000113162 0.200920309 +0.136529061 0.151661303 0.000207909 0.000679575 0.710922151 +0.060881844 0.052761352 0.348704186 0.00155437 0.536098249 +0.09201895 0.199737889 0.233568799 0.025799594 0.448874767 +0.19399862 0.088766153 0.152502674 0.005966179 0.558766373 +0.281245593 0.109503306 0.315533636 0.003085623 0.290631842 +0.112828397 0.081878268 0.1894678 0.004502393 0.611323142 +0.270027103 0.110326212 0.366656586 0.001219317 0.251770781 +0.094628635 0.501074398 0.149176419 0.010392225 0.244728323 +0.245357733 0.13745755 0.34008228 0.002600797 0.274501641 +0.113430177 0.284954433 0.350196217 0.000148719 0.251270453 +0.154450631 0.050585061 0.296142025 0.00018997 0.498632314 +0.179048403 0.204541417 0.380339558 0.003516477 0.232554146 +0.455424031 0.172642619 0.145135378 0.009106983 0.21769099 +0.338583519 0.065532272 0.436971399 0.001107411 0.157805399 +0.286552565 0.035122198 0.594686547 0 0.083638691 +0.27368364 0.093144485 0.385473529 0.001421851 0.246276495 +0.231762969 0.085295748 0.487559893 0.000218076 0.195163314 +0.311616246 0.087451369 0.337669323 0.000174441 0.263088621 +0.271123375 0.034596597 0.546187658 1.0806E-07 0.148092262 +0.209483325 0.188320063 0.257992218 0.012742092 0.331462301 +0.175331389 0.218520419 0.353748061 0.000681026 0.251719106 +0.135664925 0.084475836 0.193555381 0.00149351 0.584810348 +0.156065801 0.025450013 0.413044783 4.01895E-07 0.405439001 +0.102621158 0.094345255 0.494985051 0.000442148 0.307606388 +0.440216481 0.07045412 0.297775323 0.000566618 0.190987458 +0.442832046 0.164824028 0.178769807 0.002152572 0.211421548 +0.442832046 0.164824028 0.178769807 0.002152572 0.211421548 +0.442832046 0.164824028 0.178769807 0.002152572 0.211421548 +# distribution of age 2 pollock across strata, by year (rows) +0.04599 0.10336 0.30293 0.00980 0.53791 +0.04599 0.10336 0.30293 0.00980 0.53791 +0.04599 0.10336 0.30293 0.00980 0.53791 +0.04599 0.10336 0.30293 0.00980 0.53791 +0.04599 0.10336 0.30293 0.00980 0.53791 +0.04599 0.10336 0.30293 0.00980 0.53791 +0.04599 0.10336 0.30293 0.00980 0.53791 +0.04599 0.10336 0.30293 0.00980 0.53791 +0.04599 0.10336 0.30293 0.00980 0.53791 +0.04599 0.10336 0.30293 0.00980 0.53791 +0.04599 0.10336 0.30293 0.00980 0.53791 +0.04599 0.10336 0.30293 0.00980 0.53791 +0.04599 0.10336 0.30293 0.00980 0.53791 +0.04599 0.10336 0.30293 0.00980 0.53791 +0.04599 0.10336 0.30293 0.00980 0.53791 +0.04599 0.10336 0.30293 0.00980 0.53791 +0.04599 0.10336 0.30293 0.00980 0.53791 +0.04599 0.10336 0.30293 0.00980 0.53791 +0.02881309 0.026100692 0.27486357 0.008883133 0.661339515 +0.001670803 0.024294771 0.145040665 0.096416217 0.732577545 +0.007170161 0.055632629 0.17192726 0.022300045 0.742969905 +0.003501511 0.114715372 0.014086636 0.028238985 0.839457496 +0.003146285 0.158026989 0.182399023 0.016568736 0.639858967 +0.006486934 0.305647517 0.117642202 0.065170302 0.505053046 +0.001485011 0.012343982 0.008052232 0.002770485 0.97534829 +0.002179193 0.056004195 0.209177457 0.004095275 0.728543879 +0.021274573 0.014440196 0.050710658 0.000220602 0.913353971 +0.03424826 0.05917312 0.027412488 0.001864024 0.877302109 +0.066432982 0.092983416 0.117670633 0.038707346 0.684205623 +0.261670505 0.07910027 0.519954799 0.00133317 0.137941256 +0.01571181 0.11767071 0.479135128 0.000146135 0.387336216 +0.001148847 0.037402891 0.006461906 0.00109113 0.953895227 +0.214655793 0.128555937 0.275887434 0 0.380900836 +0.037622421 0.049695804 0.037788804 0.003790962 0.87110201 +0.046428545 0.124274691 0.300820216 0.002521737 0.525954811 +0.000167903 0.084037232 0.139405214 0.004069038 0.772320612 +0.009083841 0.124719368 0.467208359 0.000704418 0.398284014 +0.117985329 0.468674144 0.305997679 5.02956E-07 0.107342345 +0.006450615 0.08719783 0.387023215 0.014425274 0.504903065 +0.005315784 0.084671077 0.746907499 1.5479E-05 0.163090161 +0.007481356 0.106507677 0.576786574 0.012740504 0.296483888 +0.040380207 0.050145205 0.292329743 8.30823E-07 0.617144014 +0.029171015 0.017044656 0.39697345 0.000411108 0.556399771 +0.004775437 0.109906049 0.089670762 0.001099103 0.794548649 +0.054227833 0.083132788 0.235498125 0.011723091 0.615418163 +0.017972867 0.139963282 0.105536624 0.000291891 0.736235335 +0.001599218 0.234302402 0.539420635 0.000517448 0.224160297 +0.026484898 0.110331206 0.408045448 0.001498836 0.453639612 +0.06234121 0.141851333 0.492924627 0.004008342 0.298874489 +0.016100509 0.091991555 0.228911478 0.000132221 0.662864236 +0.030234072 0.096949167 0.688833842 0.016551853 0.167431066 +0.184717339 0.10113436 0.27992363 0.000343938 0.433880733 +0.011107496 0.072314606 0.37079782 0.001025677 0.5447544 +0.104116475 0.200319167 0.550917624 0.00577183 0.138874904 +0.21384358 0.029229159 0.489102749 0.003039815 0.264784696 +0.050580193 0.037112001 0.780272003 1.20664E-06 0.132034596 +0.050580193 0.037112001 0.780272003 1.20664E-06 0.132034596 +0.050580193 0.037112001 0.780272003 1.20664E-06 0.132034596 +0.050580193 0.037112001 0.780272003 1.20664E-06 0.132034596 +0.050580193 0.037112001 0.780272003 1.20664E-06 0.132034596 +0.050580193 0.037112001 0.780272003 1.20664E-06 0.132034596 +# distribution of age 3 pollock across strata, by year (rows) +0.03000 0.21072 0.21861 0.03078 0.50988 +0.03000 0.21072 0.21861 0.03078 0.50988 +0.03000 0.21072 0.21861 0.03078 0.50988 +0.03000 0.21072 0.21861 0.03078 0.50988 +0.03000 0.21072 0.21861 0.03078 0.50988 +0.03000 0.21072 0.21861 0.03078 0.50988 +0.03000 0.21072 0.21861 0.03078 0.50988 +0.03000 0.21072 0.21861 0.03078 0.50988 +0.03000 0.21072 0.21861 0.03078 0.50988 +0.03000 0.21072 0.21861 0.03078 0.50988 +0.03000 0.21072 0.21861 0.03078 0.50988 +0.03000 0.21072 0.21861 0.03078 0.50988 +0.03000 0.21072 0.21861 0.03078 0.50988 +0.03000 0.21072 0.21861 0.03078 0.50988 +0.03000 0.21072 0.21861 0.03078 0.50988 +0.03000 0.21072 0.21861 0.03078 0.50988 +0.03000 0.21072 0.21861 0.03078 0.50988 +0.03000 0.21072 0.21861 0.03078 0.50988 +0.030530999 0.119957979 0.383492766 0.006729566 0.45928869 +5.13183E-07 0.060023623 0.225353739 0.055760871 0.658861253 +0.006254645 0.071861239 0.010276108 0.160238932 0.751369076 +0.000329313 0.183964125 0.009559363 0.303551438 0.502595761 +0.005774043 0.21094265 0.050790797 0.030034374 0.702458137 +0.00045265 0.278480162 0.088705885 0.068703786 0.563657517 +0.000538841 0.129314926 0.08298238 0.018069004 0.76909485 +0.000619991 0.026330741 0.107439003 0.014851236 0.850759028 +0.004061206 0.105452304 0.052717159 0.020890804 0.816878528 +0.007278566 0.10848901 0.011729493 0.003541759 0.868961172 +0.000120762 0.436748635 0.054369192 0.043185757 0.465575655 +0.031375366 0.64365643 0.097268853 0.086017096 0.141682256 +0.000333649 0.246982092 0.080600583 0.005773361 0.666310315 +0.001642774 0.080644862 0.159199276 7.53368E-05 0.758437751 +0.010942617 0.467284397 0.114114519 0 0.407658467 +0.002732981 0.157959901 0.457070832 0.014121985 0.368114302 +0.080707568 0.204257675 0.315839211 0.001314613 0.397880933 +8.67068E-05 0.041897407 0.059080678 0.008712399 0.89022281 +0.000398568 0.130853672 0.243264091 0.005476932 0.620006738 +0.047152425 0.272402771 0.252227088 0.001203874 0.427013842 +0.00334559 0.148262448 0.380017283 0.042337164 0.426037516 +0.000478283 0.376684798 0.341853988 0.024050686 0.256932245 +0.00069116 0.313727018 0.29792528 0.05582104 0.331835503 +0.003961498 0.095899679 0.126918487 1.06661E-06 0.77321927 +0.036683346 0.256101413 0.277391358 0.000357302 0.429466581 +0.001368989 0.127270315 0.04068109 0.001615673 0.829063934 +0.03789455 0.23207458 0.382386998 0.092994218 0.254649654 +0.000411879 0.036172256 0.017544171 0.011767083 0.934104612 +0.000999617 0.395679579 0.07197461 0.001428377 0.529917818 +0.013223249 0.156767671 0.165421165 0.006267775 0.65832014 +0.010373822 0.403783311 0.296800423 0.040701008 0.248341437 +0.016903701 0.101736591 0.320511572 0.000439169 0.560408967 +0.069578591 0.245569271 0.44027702 0.002966698 0.241608421 +0.089079765 0.561506289 0.170316938 0.007304332 0.171792676 +0.127905752 0.232724677 0.417170718 0.002081358 0.220117495 +0.023813069 0.20398643 0.677233016 0.007747902 0.087219582 +0.404821581 0.037257244 0.409037079 0.01114742 0.137736677 +0.067221378 0.104837436 0.617666255 0.01244343 0.197831501 +0.067221378 0.104837436 0.617666255 0.01244343 0.197831501 +0.067221378 0.104837436 0.617666255 0.01244343 0.197831501 +0.067221378 0.104837436 0.617666255 0.01244343 0.197831501 +0.067221378 0.104837436 0.617666255 0.01244343 0.197831501 +0.067221378 0.104837436 0.617666255 0.01244343 0.197831501 +# distribution of atf less 40 cm across strata, by year (rows) +0.00823 0.37123 0.08358 0.34939 0.18757 +0.00823 0.37123 0.08358 0.34939 0.18757 +0.00823 0.37123 0.08358 0.34939 0.18757 +0.00823 0.37123 0.08358 0.34939 0.18757 +0.00823 0.37123 0.08358 0.34939 0.18757 +0.00823 0.37123 0.08358 0.34939 0.18757 +0.00823 0.37123 0.08358 0.34939 0.18757 +0.00823 0.37123 0.08358 0.34939 0.18757 +0.00823 0.37123 0.08358 0.34939 0.18757 +0.00823 0.37123 0.08358 0.34939 0.18757 +0.00823 0.37123 0.08358 0.34939 0.18757 +0.00823 0.37123 0.08358 0.34939 0.18757 +0.00823 0.37123 0.08358 0.34939 0.18757 +0.00823 0.37123 0.08358 0.34939 0.18757 +0.00823 0.37123 0.08358 0.34939 0.18757 +0.00823 0.37123 0.08358 0.34939 0.18757 +0.00823 0.37123 0.08358 0.34939 0.18757 +0.00823 0.37123 0.08358 0.34939 0.18757 +0.00000 0.16927 0.18587 0.27264 0.37222 +0.00000 0.38809 0.12661 0.25541 0.22989 +0.00000 0.31648 0.07723 0.33811 0.26818 +0.01112 0.25323 0.08190 0.29891 0.35485 +0.00520 0.27654 0.06445 0.48527 0.16854 +0.01403 0.41275 0.10628 0.21742 0.24951 +0.00906 0.33290 0.15041 0.26790 0.23973 +0.02379 0.36354 0.14709 0.26581 0.19977 +0.01283 0.32266 0.09500 0.35404 0.21547 +0.00911 0.51437 0.06690 0.30292 0.10670 +0.00000 0.35840 0.04002 0.40231 0.19927 +0.01576 0.48394 0.09144 0.29217 0.11669 +0.00987 0.35848 0.13804 0.33503 0.15859 +0.00000 0.27056 0.11883 0.37963 0.23098 +0.00000 0.25808 0.05217 0.46766 0.22209 +0.00753 0.24022 0.08448 0.41598 0.25179 +0.01342 0.41310 0.06108 0.30558 0.20684 +0.00383 0.40491 0.03849 0.29261 0.26016 +0.00000 0.31844 0.04729 0.48077 0.15350 +0.00951 0.45766 0.03313 0.37332 0.12638 +0.01114 0.52624 0.03471 0.35794 0.06996 +0.02453 0.58037 0.09349 0.20892 0.09269 +0.01560 0.51672 0.11528 0.25756 0.09483 +0.01048 0.50756 0.15390 0.22769 0.10035 +0.00000 0.43417 0.07968 0.34821 0.13794 +0.00000 0.31091 0.06809 0.39913 0.22188 +0.00000 0.36830 0.05873 0.42034 0.15263 +0.00554 0.23363 0.03164 0.53177 0.19743 +0.00961 0.33534 0.04951 0.41450 0.19104 +0.00697 0.32432 0.02805 0.48987 0.15079 +0.00000 0.25344 0.02578 0.41263 0.30815 +0.00212 0.24883 0.01017 0.52688 0.21200 +0.00765 0.34748 0.03753 0.43586 0.17147 +0.01564 0.49224 0.05800 0.29414 0.13998 +0.04539 0.45078 0.12537 0.20044 0.17802 +0.00000 0.43914 0.11217 0.32425 0.12444 +0.01297 0.40688 0.18578 0.30327 0.09110 +0.00000 0.41679 0.10158 0.31991 0.16172 +0.00000 0.41679 0.10158 0.31991 0.16172 +0.00000 0.41679 0.10158 0.31991 0.16172 +0.00000 0.41679 0.10158 0.31991 0.16172 +0.00000 0.41679 0.10158 0.31991 0.16172 +0.00000 0.41679 0.10158 0.31991 0.16172 +# distribution of atf gt 40 cm across strata, by year (rows) +0.00280 0.22191 0.05262 0.30002 0.42264 +0.00280 0.22191 0.05262 0.30002 0.42264 +0.00280 0.22191 0.05262 0.30002 0.42264 +0.00280 0.22191 0.05262 0.30002 0.42264 +0.00280 0.22191 0.05262 0.30002 0.42264 +0.00280 0.22191 0.05262 0.30002 0.42264 +0.00280 0.22191 0.05262 0.30002 0.42264 +0.00280 0.22191 0.05262 0.30002 0.42264 +0.00280 0.22191 0.05262 0.30002 0.42264 +0.00280 0.22191 0.05262 0.30002 0.42264 +0.00280 0.22191 0.05262 0.30002 0.42264 +0.00280 0.22191 0.05262 0.30002 0.42264 +0.00280 0.22191 0.05262 0.30002 0.42264 +0.00280 0.22191 0.05262 0.30002 0.42264 +0.00280 0.22191 0.05262 0.30002 0.42264 +0.00280 0.22191 0.05262 0.30002 0.42264 +0.00280 0.22191 0.05262 0.30002 0.42264 +0.00280 0.22191 0.05262 0.30002 0.42264 +0.00000 0.17296 0.01236 0.38499 0.42969 +0.00000 0.26979 0.03709 0.40041 0.29271 +0.00000 0.20404 0.00000 0.35291 0.44305 +0.00000 0.12796 0.04503 0.36188 0.46513 +0.00000 0.14487 0.00000 0.36129 0.49384 +0.00369 0.16825 0.03289 0.31510 0.48008 +0.00000 0.25483 0.00329 0.30494 0.43694 +0.00000 0.18935 0.04060 0.21756 0.55249 +0.00000 0.11930 0.00524 0.31900 0.55647 +0.00000 0.20127 0.01514 0.37808 0.40551 +0.00000 0.21687 0.00751 0.40782 0.36779 +0.00889 0.22317 0.03203 0.30620 0.42971 +0.00970 0.29159 0.02653 0.35387 0.31831 +0.00000 0.33090 0.00000 0.36549 0.30362 +0.00588 0.33716 0.03228 0.32546 0.29921 +0.00000 0.22637 0.02369 0.42520 0.32474 +0.00000 0.28403 0.03851 0.26073 0.41673 +0.00000 0.22408 0.00000 0.52660 0.24931 +0.00000 0.15952 0.02830 0.26067 0.55151 +0.00000 0.20856 0.03181 0.29773 0.46190 +0.00000 0.14715 0.03950 0.26312 0.55023 +0.01053 0.24200 0.07916 0.15130 0.51701 +0.00632 0.26276 0.04664 0.26409 0.42019 +0.01598 0.28890 0.04479 0.23747 0.41286 +0.00401 0.35263 0.02344 0.30968 0.31025 +0.00000 0.27310 0.04066 0.29596 0.39028 +0.00000 0.23105 0.04274 0.30900 0.41721 +0.00000 0.16252 0.03301 0.36316 0.44131 +0.00286 0.21401 0.06592 0.24755 0.46966 +0.00200 0.25297 0.09077 0.21455 0.43971 +0.00000 0.16695 0.03304 0.27772 0.52229 +0.00000 0.15341 0.04140 0.32523 0.47997 +0.00000 0.15638 0.08509 0.21802 0.54050 +0.00000 0.16828 0.09603 0.17646 0.55923 +0.01231 0.18459 0.19672 0.15008 0.45631 +0.00756 0.19767 0.15248 0.25117 0.39112 +0.01082 0.29657 0.26082 0.19713 0.23466 +0.00591 0.32694 0.21512 0.22320 0.22882 +0.00591 0.32694 0.21512 0.22320 0.22882 +0.00591 0.32694 0.21512 0.22320 0.22882 +0.00591 0.32694 0.21512 0.22320 0.22882 +# the strata area for getting predatuion by area (thousands of sq km) +118.8982651 103.3002273 107.8222474 38.7924363 94.56232837 +## things to fit for estimating predation +# ATF consumption (ages 1-3) +# number of years of estimates of ATF consumption, by predator +11 26 +# years for which we have consumption estimatates +1983 1986 1990 2000 2001 2002 2006 2007 2008 2013 2014 +1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2006 2007 2009 2010 2011 2012 2013 2014 2015 2016 2017 +# consumption estimates (kilotons, row 1 = ATF < 40 cm, row 2 = ATF >= 40 cm) +92.42127731 254.9051043 462.0560324 177.3533664 571.8149268 394.9250921 285.4527615 407.3188444 93.51040347 311.8751716 178.1255589 +211.2031491 480.567643 534.6239051 550.6581612 480.4897172 432.4062727 177.9912012 390.9200764 326.6838292 311.107004 587.2882102 521.3420953 493.3565449 497.0190322 457.825571 184.3334696 263.0000969 354.8011986 560.7280808 689.5554756 632.3501607 735.3018615 928.5737963 712.9893128 358.9252958 128.4894649 +# catch proportions (ages 1-3, by weight) for ATF < 40 cm by year +0.85273 0.11976 0.02751 +0.78317 0.21683 0.00000 +0.83050 0.14559 0.02391 +0.62284 0.37716 0.00000 +0.71557 0.27751 0.00692 +0.18473 0.47193 0.34334 +0.98059 0.01941 0.00000 +0.92475 0.07525 0.00000 +0.20714 0.66475 0.12811 +0.99200 0.00800 0.00000 +0.58381 0.35492 0.06127 +# catch proportions (ages 1-3) for ATF >= 40 cm by year +0.14387 0.41604 0.44010 +0.43292 0.47727 0.08981 +0.27736 0.63473 0.08792 +0.03934 0.46767 0.49299 +0.25223 0.34153 0.40624 +0.06814 0.35137 0.58049 +0.05962 0.23588 0.70449 +0.36850 0.33874 0.29277 +0.30532 0.39612 0.29856 +0.05777 0.44040 0.50183 +0.03755 0.31741 0.64504 +0.10478 0.29525 0.59997 +0.25009 0.36604 0.38387 +0.04694 0.50200 0.45106 +0.08945 0.26378 0.64677 +0.21550 0.15835 0.62615 +0.22470 0.23619 0.53911 +0.11684 0.19976 0.68340 +0.21531 0.47051 0.31418 +0.21198 0.26212 0.52590 +0.03573 0.36834 0.59593 +0.75592 0.11137 0.13271 +0.30535 0.53760 0.15705 +0.12984 0.32507 0.54509 +0.06937 0.43064 0.49999 +0.12120 0.31362 0.56518 +# the sample sizes for the consmption age comps (rows = pred, col= predation year) +50 50 50 50 50 50 50 50 50 50 50 +50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 +# the C_a parameter for max compsumption rate +0.125 0.125 +# the C_a parameter for max compsumption rate +-0.199 -0.199 +# TCM parameter for max consumption temperature function +26 26 +# TC0 parameter for max consumption temperature function +20.512 20.512 +# CQ parameter for max consumption temperature function +2.497 2.497 +# the temperature by strata (from ACLIM_hindcast, years before 1982 are an average) +4.360253542 2.154195273 0.815437707 4.019796208 2.403877604 +4.360253542 2.154195273 0.815437707 4.019796208 2.403877604 +4.360253542 2.154195273 0.815437707 4.019796208 2.403877604 +4.360253542 2.154195273 0.815437707 4.019796208 2.403877604 +4.360253542 2.154195273 0.815437707 4.019796208 2.403877604 +4.360253542 2.154195273 0.815437707 4.019796208 2.403877604 +4.348134 2.3094573 -0.05061286 3.982983 2.074454 +2.497424 1.0066836 -0.42451541 3.461386 1.641736 +2.43973 0.6739367 -0.29773958 3.427912 1.973702 +4.058981 2.0488988 -0.10633813 4.337568 1.616081 +3.679798 0.5825206 0.41988467 3.0938 2.861539 +2.378325 0.718827 -0.2302499 3.705854 1.410105 +1.80307 0.2482798 -0.69947089 3.392617 2.132737 +4.393788 3.496997 1.30841686 5.364371 3.216115 +6.853687 3.8493368 1.93916972 4.679671 3.193864 +7.419447 4.5004021 3.37059741 5.085538 3.970347 +5.980524 3.5512466 1.52759133 4.68736 3.197166 +6.389247 3.8612869 2.20875674 5.01554 3.415832 +4.563606 2.0958243 2.17098285 4.390188 3.356535 +5.742435 3.7383416 1.28955181 4.995722 3.149884 +3.13395 1.9426122 0.04890082 4.233712 2.078837 +2.416033 1.7111861 0.79992939 4.334784 2.313044 +3.204918 1.8154874 0.14405379 4.114489 2.580028 +5.803015 3.6893004 1.61156194 5.139355 3.254879 +3.792504 1.7708332 0.75251748 4.060348 2.842735 +5.482235 2.6499909 2.20979032 3.973223 2.770019 +4.872173 2.6369295 0.68734487 4.170253 2.691204 +4.66501 2.4070466 0.20180992 3.94385 2.196864 +3.835402 1.3124922 -0.14128389 4.240232 1.515181 +6.969419 3.4238643 1.46426981 4.619817 3.085612 +4.741561 2.8153967 0.07686012 4.546096 2.158367 +3.620375 1.436322 0.04249977 3.403692 2.086332 +5.519602 2.5694187 1.63553084 3.760486 2.793872 +3.85777 1.2840163 1.33023494 3.18101 2.05341 +5.654973 3.2493535 1.99822017 4.245158 3.239017 +2.456438 0.8172659 0.21199293 3.323887 1.990556 +4.563776 1.9286108 0.93291589 3.532171 2.167298 +4.056245 2.6275127 1.25515774 4.124464 2.398734 +5.623387 2.5536491 1.83504781 3.814038 2.269554 +5.451068 2.9506266 2.3822157 4.654725 3.016224 +5.195829 2.6429888 1.4975723 4.031718 2.500495 +5.246613 2.910676 1.50302283 4.277883 2.516058 +3.735287 1.9141921 0.33831724 3.856958 2.213868 +2.886063 0.7841668 -0.36544597 2.85212 1.722475 +2.587398 0.7343266 -0.24733105 2.916441 1.576841 +3.853648 0.5890507 -0.16641168 3.146446 1.289574 +2.358028 0.5709882 -0.13665044 3.436174 2.141433 +3.237983 1.4533411 0.03288059 3.438194 2.131028 +2.96874 0.2116222 -0.55937721 2.522293 1.460926 +3.37734 0.8447977 -0.11282829 3.431688 1.541359 +5.075854 3.079051 1.3058004 4.183044 2.33708 +5.729849 3.5010319 0.92952536 4.970757 2.007836 +6.984331 4.4355349 2.36446119 5.211475 2.845619 +3.787157 1.4556509 0.85187968 3.638727 2.389669 +6.022971 3.499845 2.79231094 4.494286 3.252263 +6.720991108 3.911308965 2.687099921 4.78243868 3.131752405 +6.720991108 3.911308965 2.687099921 4.78243868 3.131752405 +6.720991108 3.911308965 2.687099921 4.78243868 3.131752405 +6.720991108 3.911308965 2.687099921 4.78243868 3.131752405 +6.720991108 3.911308965 2.687099921 4.78243868 3.131752405 +# mean weight of the predator groups (g) +210.946 211.943 211.352 209.033 202.754 193.198 179.514 158.547 110.908 138.766 192.961 264.054 336.013 376.550 337.639 194.540 106.058 94.749 131.061 177.539 163.244 170.183 176.032 153.328 150.616 162.464 185.128 223.077 244.019 253.923 241.451 218.882 175.656 171.441 174.254 156.741 158.744 172.019 176.526 187.222 196.966 210.180 206.676 208.995 215.691 219.090 228.204 229.410 210.223 178.230 171.172 185.453 200.602 128.812 143.285 194.677 195.0 195.0 195 195 +1641.212 1659.523 1682.611 1708.961 1738.114 1768.684 1797.055 1818.348 1826.221 1810.966 1756.017 1587.846 1352.105 1262.357 1303.898 1421.890 1577.294 1746.132 1877.951 1850.127 1588.961 1342.234 1246.091 1222.209 1201.228 1175.084 1165.318 1140.064 1116.420 1132.322 1189.513 1274.026 1375.087 1474.068 1561.433 1610.041 1612.332 1586.060 1540.150 1472.930 1409.522 1374.325 1364.788 1370.340 1396.310 1433.547 1470.987 1507.717 1552.116 1605.346 1662.007 1712.330 1730.439 1703.508 1667.113 1704.940 1700.00 1700 1700 1700 +# Cmax for functional respose (for avg wgt atf, at avg temperature across EBS shelf from 1982-2019) [UPDATED] +3.586083938 2.382786007 +# Copepod time series +# phase to estimate +-5 +# nyrs +15 +# Yrs of copepod +2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2014 2015 2016 2018 +# +# VAST estimates of copepod +824 762 2445 1663 2249 3623 23657 9733 12294 15393 30504 7023 2420 3896 5321 +# SE of VAST ests of copepod +404 360 856 556 708 721 9140 2236 2542 2986 5625 1709 740 1223 1899 +# +1234567 diff --git a/2024/runs/om/pm b/2024/runs/om/pm new file mode 120000 index 0000000..1a623d5 --- /dev/null +++ b/2024/runs/om/pm @@ -0,0 +1 @@ +../../../source/pm \ No newline at end of file diff --git a/2024/runs/om/pm.cpp b/2024/runs/om/pm.cpp new file mode 100644 index 0000000..eaeb67f --- /dev/null +++ b/2024/runs/om/pm.cpp @@ -0,0 +1,7475 @@ +#ifdef DEBUG + #ifndef __SUNPRO_C + #include + #include + #endif +#endif + extern "C" + { + void do_not_exit(const int exit_code) + { + // Does Nothing + } + } + #include + #include + #undef simwrite + #define simwrite(object) simdat << "#"<<#object << endl << object << endl; + #undef COUT + #define COUT(object) cout << #object "," << object << endl; + ofstream proj_df("proj_df.csv"); + #undef proj_df + #define proj_df(object) proj_df << #object "\n" << object << endl; + ofstream misc_out("misc_out.rep"); + #undef misc_out + #define misc_out(object) misc_out << #object "\n" << object << endl; + ofstream for_sd("extra_sd.rep"); + #undef for_sd + #define for_sd(object) for_sd << #object "\n" << object << endl; + ofstream write_mcFmort("mcFmort.rep"); + #undef write_mcFmort + #define write_mcFmort(object) write_mcFmort << " " << object ; + ofstream write_mcSRR("mcSRR.rep"); + #undef write_mcSRR + #define write_mcSRR(object) write_mcSRR << " " << object ; + ofstream write_mceval("mceval.rep"); + #undef write_mceval + #define write_mceval(object) write_mceval << " " << object ; + ofstream mceval_ac_ppl("mceval_ac_ppl.csv"); + #undef write_mceval_ac_ppl + #define write_mceval_ac_ppl(object) mceval_ac_ppl << "," << object ; + ofstream mceval_ppl("mceval_ppl.csv"); + #undef write_mceval_ppl + #define write_mceval_ppl(object) mceval_ppl << "," << object ; + ofstream write_mceval_eb_bts("mceval_eb_bts.rep"); + #undef write_mceval_eb_bts + #define write_mceval_eb_bts(object) write_mceval_eb_bts << " " << object ; + ofstream write_mceval_eb_ats("mceval_eb_ats.rep"); + #undef write_mceval_eb_ats + #define write_mceval_eb_ats(object) write_mceval_eb_ats << " " << object ; + ofstream write_mceval_ea1_ats("mceval_ea1_ats.rep"); + #undef write_mceval_ea1_ats + #define write_mceval_ea1_ats(object) write_mceval_ea1_ats << " " << object ; + ofstream write_mceval_pred_catch("mceval_pred_catch.rep"); + #undef write_mceval_pred_catch + #define write_mceval_pred_catch(object) write_mceval_pred_catch << " " << object ; + ofstream write_mceval_eac_fsh("mceval_eac_fsh.rep"); + #undef write_mceval_eac_fsh + #define write_mceval_eac_fsh(object) write_mceval_eac_fsh << " " << object ; + ofstream write_mceval_eac_bts("mceval_eac_bts.rep"); + #undef write_mceval_eac_bts + #define write_mceval_eac_bts(object) write_mceval_eac_bts << " " << object ; + ofstream write_mceval_eac_ats("mceval_eac_ats.rep"); + #undef write_mceval_eac_ats + #define write_mceval_eac_ats(object) write_mceval_eac_ats << " " << object ; + ofstream write_mceval_pred_cpue("mceval_pred_cpue.rep"); + #undef write_mceval_pred_cpue + #define write_mceval_pred_cpue(object) write_mceval_pred_cpue << " " << object ; + ofstream write_mceval_pred_avo("mceval_pred_avo.rep"); + #undef write_mceval_pred_avo + #define write_mceval_pred_avo(object) write_mceval_pred_avo << " " << object ; + ofstream write_mceval_mnwt("mceval_mnwt.rep"); + #undef write_mceval_mnwt + #define write_mceval_mnwt(object) write_mceval_mnwt << " " << object ; + ofstream write_mceval_fsh_wt("mceval_fsh_wt.rep"); + #undef write_mceval_fsh_wt + #define write_mceval_fsh_wt(object) write_mceval_fsh_wt << " " << object ; + ofstream write_mceval_srv_wt("mceval_srv_wt.rep"); + #undef write_mceval_srv_wt + #define write_mceval_srv_wt(object) write_mceval_srv_wt << " " << object ; + ofstream write_mceval_ssb_rec("mceval_ssb_rec.rep"); + #undef write_mceval_ssb_rec + #define write_mceval_ssb_rec(object) write_mceval_ssb_rec << " " << object ; + ofstream write_log("Input_Log.rep"); + #undef write_log + #define write_log(object) write_log << #object "\n" << object << endl; + ofstream retro_out("retro.rep",ios::app); + #undef write_retro + #define write_retro(object) retro_out << #object " " < +#endif +#include +#ifdef USE_ADMB_CONTRIBS +#include + +#endif + extern "C" { + void ad_boundf(int i); + } +#include + +model_data::model_data(int argc,char * argv[]) : ad_comm(argc,argv) +{ + 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] == '-') + { + cerr << "Invalid input data command line option" + " -- ignored" << endl; + } + else + { + tmpstring = adstring(argv[on+1]); + } + } + } + global_datafile = new cifstream(tmpstring); + if (!global_datafile) + { + cerr << "Error: Unable to allocate global_datafile in model_data constructor."; + ad_exit(1); + } + if (!(*global_datafile)) + { + delete global_datafile; + global_datafile=NULL; + } + *(ad_comm::global_datafile) >> model_name; + *(ad_comm::global_datafile) >> datafile_name; + *(ad_comm::global_datafile) >> selchng_filename; + *(ad_comm::global_datafile) >> control_filename; + *(ad_comm::global_datafile) >> Alt_MSY_File; + *(ad_comm::global_datafile) >> Cov_Filename; + *(ad_comm::global_datafile) >> Wtage_file; + *(ad_comm::global_datafile) >> RawSurveyCPUE_file; + *(ad_comm::global_datafile) >> Temp_Cons_Dist_file; + *(ad_comm::global_datafile) >> GenGamm_Filename; + write_log(model_name); + write_log(datafile_name); + write_log(selchng_filename); + write_log(control_filename); + write_log(Alt_MSY_File); + write_log(Cov_Filename); + write_log(Wtage_file); + write_log(RawSurveyCPUE_file); + write_log(Temp_Cons_Dist_file); + write_log(GenGamm_Filename); + count_mcmc=0; + count_mcsave=0; + q_amin = 3; q_amax= 15; // age range overwhich q applies (for prior specifications) + selages.allocate(1,15); + selages=1.0;selages(1)=0;selages(2)=0; + sel_avo_in.allocate(1,15); + sel_avo_in(1)=0.0; sel_avo_in(2)=1; sel_avo_in(3)=1; sel_avo_in(4)=0.85; sel_avo_in(5)=0.7; sel_avo_in(6)=0.55; sel_avo_in(7)=0.3; sel_avo_in(8)=0.15; sel_avo_in(9)=0.05; sel_avo_in(10)=0.01; sel_avo_in(11)=0.01; sel_avo_in(12)=0.01; sel_avo_in(13)=0.01; sel_avo_in(14)=0.01; sel_avo_in(15)=0.01; + Cat_Fut.allocate(1,10); + do_EIT1=1; // flag to carry EIT out in future year (for simulations only) + pflag=0; + pad_srecout = new ofstream("srec_Ass_out.rep"); + pad_projout = new ofstream("pm.prj"); + pad_nofish = new ofstream("nofish.rep"); + pad_projout2 = new ofstream("pmsr.prj"); + pad_eval = new ofstream("pm_eval.rep") ; + ad_comm::change_datafile_name(control_filename); cout<<"Opening "<0) // Use logistic selectivity + { + phase_selcoffs_fsh = -2; + if(phase_seldevs_fsh>0) + phase_selcoffs_fsh_dev = -phase_seldevs_fsh; + else + phase_selcoffs_fsh_dev = phase_seldevs_fsh; + phase_logist_fsh_dev = phase_seldevs_fsh; + } + else // Use coefficient selectivities... + { + if(phase_seldevs_fsh>0) + phase_logist_fsh_dev = -phase_seldevs_fsh; + phase_selcoffs_fsh_dev = phase_seldevs_fsh; + } + // Trawl Survey selectivity................ + if (phase_logist_bts>0) // Use logistic selectivites... + { + phase_selcoffs_bts = -2; + if(phase_seldevs_bts>0) + phase_selcoffs_bts_dev = -phase_seldevs_bts; + else + phase_selcoffs_bts_dev = phase_seldevs_bts; + phase_logist_bts_dev = phase_seldevs_bts; + } + else // Use coefficient selectivites... + { + if(phase_seldevs_bts>0) + phase_logist_bts_dev = -phase_seldevs_bts; + phase_selcoffs_bts_dev = phase_seldevs_bts; + } + phase_selcoffs_ats.allocate("phase_selcoffs_ats"); + phase_selcoffs_ats_dev.allocate("phase_selcoffs_ats_dev"); + cout <<"Phase fsh coef: "<1978) // to test if styr is before 1978 + styr_est = styr; + else + styr_est = 1978; + } + else + { + styr_est = styr+1; + } + // Set bounds for SRR params (depending on estimation and type) + if (phase_sr>0) + { + phase_nosr=-1; + phase_Rzero=3; + if (SrType==3) + phase_Rzero=-2; + } + else + { + phase_nosr=1; + phase_Rzero=-1; + } + if (SrType==4) + Steepness_UB=4.; + else + Steepness_UB=.99; + n_fsh_r=0; + n_bts_r=0; + n_ats_r=0; + n_avo_r=0; + endyr_r = endyr - int(ctrl_flag(28)); // where retrospective peels are set + endyr_est = endyr_r - int(ctrl_flag(29)); // lop off last couple of years + cout <<"Last yr of estimation..."<0) {ii++;} nch_ats=ii; + ii = 0; for(i=styr;i<=endyr_r;i++) if(fsh_ch_in(i)>0) {ii++;} nch_fsh=ii; + if (ctrl_flag(28)==0.) + { + n_fsh_r=n_fsh; + n_bts_r=n_bts; + n_ats_r=n_ats; + n_avo_r=n_avo; + } + else + { + int ii=0; + for (i=styr;i0) + phase_nosr = -1; + else + phase_nosr = 1; + ad_comm::change_datafile_name(Cov_Filename);cout<<"Opening "<0) {ii++;sel_ch_sig_ats(ii)=ats_ch_in(i);yrs_ch_ats(ii)=i;} + yrs_ch_fsh.allocate(1,nch_fsh); + sel_ch_sig_fsh.allocate(1,nch_fsh); + ii=0;for (i=styr;i<=endyr_r;i++) if(fsh_ch_in(i)>0) {ii++;sel_ch_sig_fsh(ii)=fsh_ch_in(i);yrs_ch_fsh(ii)=i;} + write_log(nch_fsh); write_log(yrs_ch_fsh); write_log(sel_ch_sig_fsh); + write_log(nch_ats); write_log(yrs_ch_ats); write_log(sel_ch_sig_ats); + oac_fsh.allocate(1,n_fsh_r,1,nbins); + oac_bts.allocate(1,n_bts_r,1,nbins); + if (use_last_ats_ac>0) n_ats_ac_r = n_ats_r; else n_ats_ac_r = n_ats_r-1; + if (use_last_ats_ac>0) nagecomp(3) = n_ats_r; else nagecomp(3) = n_ats_r-1; + oac_ats.allocate(1,n_ats_ac_r,1,nbins); + oa1_ats.allocate(1,n_ats_ac_r); + ot_fsh.allocate(1,n_fsh_r); + ot_bts.allocate(1,n_bts_r); + std_ob_bts.allocate(1,n_bts_r); + ob_bts.allocate(1,n_bts_r); + ot_ats.allocate(1,n_ats_r); + ob_ats.allocate(1,n_ats_r); + std_ob_ats.allocate(1,n_ats_r); + lseb_ats.allocate(1,n_ats_r); + lvarb_ats.allocate(1,n_ats_r); + iseed = 0; + condmsy = 0; + do_fmort=0; + adj_1.allocate(1,10); + adj_2.allocate(1,10); + SSB_1.allocate(1,10); + SSB_2.allocate(1,10); + do_check=0; + do_srrdevs=0; + if (ad_comm::argc > 1) + { + int on=0; + if ( (on=option_match(argc,argv,"-srrdevs"))>-1) + do_srrdevs = 1; + if ( (on=option_match(ad_comm::argc,ad_comm::argv,"-condmsy"))>-1) + { + if (on>ad_comm::argc-2 | ad_comm::argv[on+1][0] == '-') + { + cerr << "Invalid number of arguments for command line option -condmsy; option ignored" << endl; + } + else + { + condmsy = atoi(ad_comm::argv[on+1]); + cout<< "Currently using "<-1) + do_check = 1; + if ( (on=option_match(ad_comm::argc,ad_comm::argv,"-iseed"))>-1) + { + if (on>ad_comm::argc-2 | ad_comm::argv[on+1][0] == '-') + { + cerr << "Invalid number of iseed arguements, command line option -iseed ignored" << endl; + } + else + { + iseed = atoi(ad_comm::argv[on+1]); + cout<< "Currently using "<-1) + do_fmort=1; + } + // Some defaults------------ + adj_1=1.0; + adj_2=1.0; + SSB_1=1.0; + SSB_2=1.0; +long int lseed=iseed; + pad_rng = new random_number_generator(iseed);; + GenGamData.allocate(1,n_bts,1,2); + q_GenGam.allocate(1,n_bts); + sd_GenGam.allocate(1,n_bts); + // Flag to use covariance for bottom trawl survey, 0=use vector, 1=use cov matrix, 2=use GenGamma + if (DoCovBTS==2) + { + ad_comm::change_datafile_name(GenGamm_Filename);cout<<"Opening "<> GenGamData ; + } + q_GenGam = extract_column(GenGamData,1); + sd_GenGam = extract_column(GenGamData,2); + write_log(q_GenGam); + write_log(sd_GenGam); + write_log(GenGamData); //exit(1); + ad_comm::change_datafile_name(Wtage_file);cout<<"Opening "<1) phase_d_scale = 3; else phase_d_scale = -1; + write_log(endyr_wt); + write_log(styr_wt); + write_log(log_sd_coh); + write_log(log_sd_yr); + write_log(wt_obs); + write_log(sd_obs); + endyr_wt = endyr_wt - int(ctrl_flag(28)); + cout<<(endyr_wt)<0) + { + mnCPUE(iyr,ist) = mean(CPUE(iyr,ist)); + mntemp(iyr,ist) = mean(temp(iyr,ist)); + } + } + } + FW_fsh.allocate(1,4); + ad_comm::change_datafile_name(Temp_Cons_Dist_file); + endyr_temp = 2023; + SST.allocate(styr-1,endyr_temp-1,"SST"); + SST_fut = mean(SST(endyr_temp-7,endyr_temp-3)); + n_pred_grp_nonpoll.allocate("n_pred_grp_nonpoll"); + n_pred_grp_poll.allocate("n_pred_grp_poll"); + n_pred_grp = n_pred_grp_nonpoll + n_pred_grp_poll; // the number of predator groups + N_pred.allocate(1,n_pred_grp,styr,endyr_temp,"N_pred"); + nstrata_pred.allocate("nstrata_pred"); + strata.allocate(1,nstrata_pred,"strata"); + n_pred_ages.allocate("n_pred_ages"); + pred_ages.allocate(1,n_pred_ages,"pred_ages"); + poll_dist.allocate(1,n_pred_ages,styr,endyr_temp,1,nstrata_pred,"poll_dist"); + pred_dist_nonpoll.allocate(1,n_pred_grp,styr,endyr_temp,1,nstrata_pred,"pred_dist_nonpoll"); + Npred_bystrata_nonpoll.allocate(styr,endyr_temp,1,n_pred_grp_nonpoll,1,nstrata_pred); + area_pred.allocate(1,nstrata_pred,"area_pred"); + nyrs_cons_nonpoll.allocate(1,n_pred_grp_nonpoll,"nyrs_cons_nonpoll"); + yrs_cons_nonpoll.allocate(1,n_pred_grp_nonpoll,1,nyrs_cons_nonpoll,"yrs_cons_nonpoll"); + obs_cons_nonpoll.allocate(1,n_pred_grp_nonpoll,1,nyrs_cons_nonpoll,"obs_cons_nonpoll"); + oac_cons_nonpoll.allocate(1,n_pred_grp_nonpoll,1,nyrs_cons_nonpoll,1,n_pred_ages,"oac_cons_nonpoll"); + sam_oac_cons_nonpoll_raw.allocate(1,n_pred_grp_nonpoll,1,nyrs_cons_nonpoll,"sam_oac_cons_nonpoll_raw"); + obs_cons_wgt_atage_nonpoll.allocate(1,n_pred_grp_nonpoll,1,nyrs_cons_nonpoll,1,n_pred_ages); + obs_cons_natage_nonpoll.allocate(1,n_pred_grp_nonpoll,1,nyrs_cons_nonpoll,1,n_pred_ages); + obs_cpup_nonpoll.allocate(1,n_pred_grp_nonpoll,1,nyrs_cons_nonpoll,1,n_pred_ages); + C_a_nonpoll.allocate(1,n_pred_grp_nonpoll,"C_a_nonpoll"); + C_b_nonpoll.allocate(1,n_pred_grp_nonpoll,"C_b_nonpoll"); + TCM_nonpoll.allocate(1,n_pred_grp_nonpoll,"TCM_nonpoll"); + TC0_nonpoll.allocate(1,n_pred_grp_nonpoll,"TC0_nonpoll"); + CQ_nonpoll.allocate(1,n_pred_grp_nonpoll,"CQ_nonpoll"); + temp_bystrata.allocate(styr,endyr_temp,1,nstrata_pred,"temp_bystrata"); + mn_wgt_nonpoll.allocate(1,n_pred_grp_nonpoll,styr,endyr_temp,"mn_wgt_nonpoll"); + Y_nonpoll.allocate(1,n_pred_grp_nonpoll); + Z_nonpoll.allocate(1,n_pred_grp_nonpoll); + X_nonpoll.allocate(1,n_pred_grp_nonpoll); + V_nonpoll.allocate(styr,endyr_temp,1,n_pred_grp_nonpoll,1,nstrata_pred); + F_t_nonpoll.allocate(styr,endyr_temp,1,n_pred_grp_nonpoll,1,nstrata_pred); + Cmax_nonpoll.allocate(styr,endyr_temp,1,n_pred_grp_nonpoll,1,nstrata_pred); + Cmax_avg.allocate(1,n_pred_grp,"Cmax_avg"); + atf_wgts.allocate(1,n_pred_grp); + poll_wgts.allocate(1,n_pred_ages); + comp_nr_ub.allocate(1,n_pred_grp_nonpoll); + comp_nr_ub = ivector(nyrs_cons_nonpoll*n_pred_ages); + phase_cope.allocate("phase_cope"); + n_cope.allocate("n_cope"); + yrs_cope.allocate(1,n_cope,"yrs_cope"); + obs_cope.allocate(1,n_cope,"obs_cope"); + obs_cope_std.allocate(1,n_cope,"obs_cope_std"); + lse_cope.allocate(1,n_cope); + lvar_cope.allocate(1,n_cope); + lse_cope = elem_div(obs_cope_std,obs_cope); + lse_cope = sqrt(log(square(lse_cope) + 1.)); + lvar_cope = square(lse_cope); + write_log(SST); + write_log( n_pred_grp_nonpoll); + write_log( n_pred_grp_poll); + write_log( n_pred_grp); + write_log( N_pred); + write_log( nstrata_pred); + write_log( strata); + write_log( n_pred_ages); + write_log( pred_ages); + write_log( poll_dist); + write_log( pred_dist_nonpoll); + write_log( area_pred); + write_log( nyrs_cons_nonpoll); + write_log( yrs_cons_nonpoll); + write_log( obs_cons_nonpoll); + write_log(sam_oac_cons_nonpoll_raw); + write_log(temp_phase); + write_log(C_a_nonpoll); + write_log(C_b_nonpoll); + write_log(TCM_nonpoll); + write_log(TC0_nonpoll); + write_log(CQ_nonpoll); + write_log(temp_bystrata); + write_log(mn_wgt_nonpoll); + write_log(Cmax_avg); + write_log(phase_cope); + write_log(n_cope); + write_log(yrs_cope); + write_log(obs_cope); + write_log(obs_cope_std); + // Assign values to temperature and predation phases (if estimating predation mortality or climate enhanced recruitment) + if(do_pred==1 && do_mult_func_resp==1) + { + do_pred_phase_ms = pred_phase; + do_pred_phase_ss = -1; + do_pred_phase = pred_phase; + } + else if (do_pred==1 && do_mult_func_resp!=1) + { + do_pred_phase_ms = -1; + do_pred_phase_ss = pred_phase; + do_pred_phase = pred_phase; + } + else + { + do_pred_phase_ms = -1; + do_pred_phase_ss = -1; + do_pred_phase = -1; + } + if(do_temp==1) + do_temp_phase = temp_phase; + else + do_temp_phase = -1; + // If estimating predation mortality, do a bunch of preliminary calculations + if (do_pred==1) + { + //Rescale spatial distribution matrices to add to one, and compute predator by year and strata + for (i=1;i<=n_pred_ages;i++) + { + for (ii=styr;ii<=endyr;ii++) + { + poll_dist(i,ii) = poll_dist(i,ii)/sum(poll_dist(i,ii)); + } + } + for (i=1;i<=n_pred_grp;i++) + { + for (ii=styr;ii<=endyr;ii++) + { + pred_dist_nonpoll(i,ii) = pred_dist_nonpoll(i,ii)/sum(pred_dist_nonpoll(i,ii)); + Npred_bystrata_nonpoll(ii,i) = N_pred(i,ii)*pred_dist_nonpoll(i,ii); + } + } + // Compute the catch per unit predator (CPUP) in numbers + for (m=1;m<=n_pred_grp;m++) + { + for (i=1;i<=nyrs_cons_nonpoll(m);i++) + { + yr_ind = yrs_cons_nonpoll(m,i) - 1981; // for getting the index for the wt_bts + if(yr_ind<1) + yr_ind = 1; + if(yr_ind>38) + yr_ind = 38; + obs_cons_wgt_atage_nonpoll(m,i) = oac_cons_nonpoll(m,i)*obs_cons_nonpoll(m,i); // kilotons + obs_cons_natage_nonpoll(m,i) = elem_div(obs_cons_wgt_atage_nonpoll(m,i),wt_bts(yr_ind)(1,n_pred_ages)); + obs_cpup_nonpoll(m,i) = obs_cons_natage_nonpoll(m,i)/N_pred(m,yrs_cons_nonpoll(m,i)); + } + } + // Compute things for Cmax + for (i=1;i<=n_pred_grp_nonpoll;i++) + { + Y_nonpoll(i) = log(CQ_nonpoll(i))*(TCM_nonpoll(i)-TC0_nonpoll(i)+2); + Z_nonpoll(i) = log(CQ_nonpoll(i))*(TCM_nonpoll(i)-TC0_nonpoll(i)); + X_nonpoll(i) = Z_nonpoll(i)*Z_nonpoll(i)*pow(1+sqrt(1+40.0/Y_nonpoll(i)),2)/400.0; + for (j=styr;j<=endyr;j++) + { + V_nonpoll(j,i) = (TCM_nonpoll(i) - temp_bystrata(j))/(TCM_nonpoll(i) - TC0_nonpoll(i)); + F_t_nonpoll(j,i) = elem_prod(pow(V_nonpoll(j,i),X_nonpoll(i)),mfexp(X_nonpoll(i)*(1.0- V_nonpoll(j,i)))); + Cmax_nonpoll(j,i) = 365*C_a_nonpoll(i)*pow(mn_wgt_nonpoll(i,j),C_b_nonpoll(i))*F_t_nonpoll(j,i); + } + } + // Compute average of atf and pollock weights for computing functional response + for (i=1;i<=n_pred_grp;i++) + atf_wgts(i) = mean(mn_wgt_nonpoll(i)); + for(i=1;i<=n_pred_ages;i++) + poll_wgts(i) = 1000.0*mean(column(wt_bts,i)); // convert from kg to g + } + write_log(do_temp_phase); // copy the temperture phase here + write_log(do_pred_phase_ss); // phase for estimating the predation parameters, single species function response + write_log(do_pred_phase_ms); // phase for estimating the predation parameters, multi-species function response + write_log(do_pred_phase); // phase for estimating the residual M + test_2.allocate("test_2"); + write_log(test_2); + if(test_2!=1234567){ cout<<"Failed on data read "<0) ph_log_fsh2 = phase_logist_fsh+1;else ph_log_fsh2 = phase_logist_fsh; + sel_dif2_fsh.allocate(ph_log_fsh2,"sel_dif2_fsh"); + sel_dif1_fsh_dev.allocate(styr,endyr_r,-5,5,phase_logist_fsh_dev,"sel_dif1_fsh_dev"); + sel_a501_fsh_dev.allocate(styr,endyr_r,-5,5,phase_logist_fsh_dev,"sel_a501_fsh_dev"); + sel_trm2_fsh_dev.allocate(styr,endyr_r,-.5,.5,-2,"sel_trm2_fsh_dev"); + SPR_ABC.allocate("SPR_ABC"); + #ifndef NO_AD_INITIALIZE + SPR_ABC.initialize(); + #endif + endyr_N.allocate(1,nages,"endyr_N"); + B_Bnofsh.allocate("B_Bnofsh"); + Bzero.allocate("Bzero"); + Percent_Bzero.allocate("Percent_Bzero"); + Percent_Bzero_1.allocate("Percent_Bzero_1"); + Percent_Bzero_2.allocate("Percent_Bzero_2"); + Percent_B100.allocate("Percent_B100"); + Percent_B100_1.allocate("Percent_B100_1"); + Percent_B100_2.allocate("Percent_B100_2"); + q_temp.allocate(1,5,"q_temp"); + #ifndef NO_AD_INITIALIZE + q_temp.initialize(); + #endif + SPR_OFL.allocate("SPR_OFL"); + F40.allocate("F40"); + F35.allocate("F35"); + SSB.allocate(styr,endyr_r,"SSB"); + sigmarsq_out.allocate("sigmarsq_out"); + #ifndef NO_AD_INITIALIZE + sigmarsq_out.initialize(); + #endif + ftmp.allocate("ftmp"); + #ifndef NO_AD_INITIALIZE + ftmp.initialize(); + #endif + SB0.allocate("SB0"); + #ifndef NO_AD_INITIALIZE + SB0.initialize(); + #endif + SBF40.allocate("SBF40"); + #ifndef NO_AD_INITIALIZE + SBF40.initialize(); + #endif + SBF35.allocate("SBF35"); + #ifndef NO_AD_INITIALIZE + SBF35.initialize(); + #endif + sprpen.allocate("sprpen"); + #ifndef NO_AD_INITIALIZE + sprpen.initialize(); + #endif + F_pen.allocate("F_pen"); + #ifndef NO_AD_INITIALIZE + F_pen.initialize(); + #endif + meanrec.allocate("meanrec"); + #ifndef NO_AD_INITIALIZE + meanrec.initialize(); + #endif + SR_resids.allocate(styr_est,endyr_est,"SR_resids"); + #ifndef NO_AD_INITIALIZE + SR_resids.initialize(); + #endif + Nspr.allocate(1,4,1,nages,"Nspr"); + #ifndef NO_AD_INITIALIZE + Nspr.initialize(); + #endif + sel_fut.allocate(1,nages,"sel_fut"); + natage_future.allocate(1,nscen,styr_fut,endyr_fut,1,nages,"natage_future"); + #ifndef NO_AD_INITIALIZE + natage_future.initialize(); + #endif + rec_dev_future.allocate(styr_fut,endyr_fut,phase_F40,"rec_dev_future"); + F_future.allocate(1,nscen,styr_fut,endyr_fut,1,nages,"F_future"); + #ifndef NO_AD_INITIALIZE + F_future.initialize(); + #endif + Z_future.allocate(styr_fut,endyr_fut,1,nages,"Z_future"); + #ifndef NO_AD_INITIALIZE + Z_future.initialize(); + #endif + S_future.allocate(styr_fut,endyr_fut,1,nages,"S_future"); + #ifndef NO_AD_INITIALIZE + S_future.initialize(); + #endif + catage_future.allocate(styr_fut,endyr_fut,1,nages,"catage_future"); + #ifndef NO_AD_INITIALIZE + catage_future.initialize(); + #endif + avg_rec_dev_future.allocate("avg_rec_dev_future"); + #ifndef NO_AD_INITIALIZE + avg_rec_dev_future.initialize(); + #endif + eac_fsh.allocate(1,n_fsh_r,1,nbins,"eac_fsh"); + #ifndef NO_AD_INITIALIZE + eac_fsh.initialize(); + #endif + elc_fsh.allocate(1,nlbins,"elc_fsh"); + #ifndef NO_AD_INITIALIZE + elc_fsh.initialize(); + #endif + eac_bts.allocate(1,n_bts_r,1,nbins,"eac_bts"); + #ifndef NO_AD_INITIALIZE + eac_bts.initialize(); + #endif + eac_cmb.allocate(1,n_bts_r,1,nbins,"eac_cmb"); + #ifndef NO_AD_INITIALIZE + eac_cmb.initialize(); + #endif + oac_cmb.allocate(1,n_bts_r,1,nbins,"oac_cmb"); + #ifndef NO_AD_INITIALIZE + oac_cmb.initialize(); + #endif + eac_ats.allocate(1,n_ats_ac_r,1,nbins,"eac_ats"); + #ifndef NO_AD_INITIALIZE + eac_ats.initialize(); + #endif + ea1_ats.allocate(1,n_ats_ac_r,"ea1_ats"); + #ifndef NO_AD_INITIALIZE + ea1_ats.initialize(); + #endif + et_fsh.allocate(1,n_fsh_r,"et_fsh"); + #ifndef NO_AD_INITIALIZE + et_fsh.initialize(); + #endif + et_bts.allocate(1,n_bts_r,"et_bts"); + #ifndef NO_AD_INITIALIZE + et_bts.initialize(); + #endif + et_cmb.allocate(1,n_bts_r,"et_cmb"); + #ifndef NO_AD_INITIALIZE + et_cmb.initialize(); + #endif + avail_bts.allocate(1,n_bts_r,"avail_bts"); + #ifndef NO_AD_INITIALIZE + avail_bts.initialize(); + #endif + avail_ats.allocate(1,n_bts_r,"avail_ats"); + #ifndef NO_AD_INITIALIZE + avail_ats.initialize(); + #endif + sigma_cmb.allocate(1,n_bts_r,"sigma_cmb"); + #ifndef NO_AD_INITIALIZE + sigma_cmb.initialize(); + #endif + var_cmb.allocate(1,n_bts_r,"var_cmb"); + #ifndef NO_AD_INITIALIZE + var_cmb.initialize(); + #endif + ot_cmb.allocate(1,n_bts_r,"ot_cmb"); + #ifndef NO_AD_INITIALIZE + ot_cmb.initialize(); + #endif + eb_bts.allocate(1,n_bts_r,"eb_bts"); + #ifndef NO_AD_INITIALIZE + eb_bts.initialize(); + #endif + eb_ats.allocate(1,n_ats_r,"eb_ats"); + #ifndef NO_AD_INITIALIZE + eb_ats.initialize(); + #endif + et_ats.allocate(1,n_ats_r,"et_ats"); + #ifndef NO_AD_INITIALIZE + et_ats.initialize(); + #endif + lse_ats.allocate(1,n_ats_r,"lse_ats"); + #ifndef NO_AD_INITIALIZE + lse_ats.initialize(); + #endif + lvar_ats.allocate(1,n_ats_r,"lvar_ats"); + #ifndef NO_AD_INITIALIZE + lvar_ats.initialize(); + #endif + et_avo.allocate(1,n_avo_r,"et_avo"); + #ifndef NO_AD_INITIALIZE + et_avo.initialize(); + #endif + et_cpue.allocate(1,n_cpue,"et_cpue"); + #ifndef NO_AD_INITIALIZE + et_cpue.initialize(); + #endif + Fmort.allocate(styr,endyr_r,"Fmort"); + #ifndef NO_AD_INITIALIZE + Fmort.initialize(); + #endif + catage.allocate(styr,endyr_r,1,nages,"catage"); + #ifndef NO_AD_INITIALIZE + catage.initialize(); + #endif + pred_catch.allocate(styr,endyr_r,"pred_catch"); + #ifndef NO_AD_INITIALIZE + pred_catch.initialize(); + #endif + Pred_N_bts.allocate(styr,endyr_r,"Pred_N_bts"); + #ifndef NO_AD_INITIALIZE + Pred_N_bts.initialize(); + #endif + Pred_N_ats.allocate(styr,endyr_r,"Pred_N_ats"); + #ifndef NO_AD_INITIALIZE + Pred_N_ats.initialize(); + #endif + pred_cpue.allocate(1,n_cpue,"pred_cpue"); + #ifndef NO_AD_INITIALIZE + pred_cpue.initialize(); + #endif + pred_cope.allocate(1,n_cope,"pred_cope"); + #ifndef NO_AD_INITIALIZE + pred_cope.initialize(); + #endif + Nage_3.allocate(styr,endyr_r,"Nage_3"); + pred_avo.allocate(1,n_avo,"pred_avo"); + #ifndef NO_AD_INITIALIZE + pred_avo.initialize(); + #endif + natage.allocate(styr,endyr_r,1,nages,"natage"); + #ifndef NO_AD_INITIALIZE + natage.initialize(); + #endif + srmod_rec.allocate(styr_est,endyr_est,"srmod_rec"); + #ifndef NO_AD_INITIALIZE + srmod_rec.initialize(); + #endif + Z.allocate(styr,endyr_r,1,nages,"Z"); + #ifndef NO_AD_INITIALIZE + Z.initialize(); + #endif + F.allocate(styr,endyr_r,1,nages,"F"); + #ifndef NO_AD_INITIALIZE + F.initialize(); + #endif + S.allocate(styr,endyr_r,1,nages,"S"); + #ifndef NO_AD_INITIALIZE + S.initialize(); + #endif + M.allocate(styr,endyr_r,1,nages,"M"); + #ifndef NO_AD_INITIALIZE + M.initialize(); + #endif + M_dev.allocate(styr+1,endyr_r,-1.,1.,-8,"M_dev"); + log_sel_fsh.allocate(styr,endyr_r,1,nages,"log_sel_fsh"); + #ifndef NO_AD_INITIALIZE + log_sel_fsh.initialize(); + #endif + sel_fsh.allocate(styr,endyr_r,1,nages,"sel_fsh"); + #ifndef NO_AD_INITIALIZE + sel_fsh.initialize(); + #endif + log_sel_bts.allocate(styr,endyr_r,1,nages,"log_sel_bts"); + #ifndef NO_AD_INITIALIZE + log_sel_bts.initialize(); + #endif + log_sel_ats.allocate(styr,endyr_r,1,nages,"log_sel_ats"); + #ifndef NO_AD_INITIALIZE + log_sel_ats.initialize(); + #endif + ff.allocate("ff"); + #ifndef NO_AD_INITIALIZE + ff.initialize(); + #endif + catch_like.allocate("catch_like"); + #ifndef NO_AD_INITIALIZE + catch_like.initialize(); + #endif + avgsel_fsh.allocate("avgsel_fsh"); + #ifndef NO_AD_INITIALIZE + avgsel_fsh.initialize(); + #endif + avgsel_bts.allocate("avgsel_bts"); + #ifndef NO_AD_INITIALIZE + avgsel_bts.initialize(); + #endif + avgsel_ats.allocate("avgsel_ats"); + #ifndef NO_AD_INITIALIZE + avgsel_ats.initialize(); + #endif + bzero.allocate("bzero"); + #ifndef NO_AD_INITIALIZE + bzero.initialize(); + #endif + surv.allocate("surv"); + #ifndef NO_AD_INITIALIZE + surv.initialize(); + #endif + nthisage.allocate("nthisage"); + #ifndef NO_AD_INITIALIZE + nthisage.initialize(); + #endif + surv_like.allocate(1,3,"surv_like"); + #ifndef NO_AD_INITIALIZE + surv_like.initialize(); + #endif + cpue_like.allocate("cpue_like"); + #ifndef NO_AD_INITIALIZE + cpue_like.initialize(); + #endif + cope_like.allocate("cope_like"); + #ifndef NO_AD_INITIALIZE + cope_like.initialize(); + #endif + avo_like.allocate("avo_like"); + #ifndef NO_AD_INITIALIZE + avo_like.initialize(); + #endif + sel_like.allocate(1,3,"sel_like"); + #ifndef NO_AD_INITIALIZE + sel_like.initialize(); + #endif + sel_like_dev.allocate(1,3,"sel_like_dev"); + #ifndef NO_AD_INITIALIZE + sel_like_dev.initialize(); + #endif + age_like.allocate(1,ngears,"age_like"); + #ifndef NO_AD_INITIALIZE + age_like.initialize(); + #endif + age_like_yr.allocate(1,ngears,1,nagecomp,"age_like_yr"); + #ifndef NO_AD_INITIALIZE + age_like_yr.initialize(); + #endif + len_like.allocate("len_like"); + #ifndef NO_AD_INITIALIZE + len_like.initialize(); + #endif + wt_like.allocate("wt_like"); + #ifndef NO_AD_INITIALIZE + wt_like.initialize(); + #endif + age_like_offset.allocate(1,ngears,"age_like_offset"); + #ifndef NO_AD_INITIALIZE + age_like_offset.initialize(); + #endif + len_like_offset.allocate("len_like_offset"); + #ifndef NO_AD_INITIALIZE + len_like_offset.initialize(); + #endif + MN_const.allocate("MN_const"); + #ifndef NO_AD_INITIALIZE + MN_const.initialize(); + #endif + MN_const = 1e-3; // Multinomial constant + Priors.allocate(1,4,"Priors"); + #ifndef NO_AD_INITIALIZE + Priors.initialize(); + #endif + rec_like.allocate(1,7,"rec_like"); + #ifndef NO_AD_INITIALIZE + rec_like.initialize(); + #endif + all_like.allocate(1,26,"all_like"); + #ifndef NO_AD_INITIALIZE + all_like.initialize(); + #endif + sumtmp.allocate("sumtmp"); + #ifndef NO_AD_INITIALIZE + sumtmp.initialize(); + #endif + tmpsp.allocate("tmpsp"); + #ifndef NO_AD_INITIALIZE + tmpsp.initialize(); + #endif + log_initage.allocate(2,nages,"log_initage"); + #ifndef NO_AD_INITIALIZE + log_initage.initialize(); + #endif + pred_biom.allocate(styr,endyr_r,"pred_biom"); + #ifndef NO_AD_INITIALIZE + pred_biom.initialize(); + #endif + SRR_SSB.allocate(1,20,"SRR_SSB"); + #ifndef NO_AD_INITIALIZE + SRR_SSB.initialize(); + #endif + fake_SST.allocate(1,40,"fake_SST"); + #ifndef NO_AD_INITIALIZE + fake_SST.initialize(); + #endif + fake_dens.allocate(1,40,"fake_dens"); + #ifndef NO_AD_INITIALIZE + fake_dens.initialize(); + #endif + L1.allocate(10,50,2,"L1"); + L2.allocate(30,90,3,"L2"); + log_alpha.allocate(-1,"log_alpha"); + log_K.allocate(4,"log_K"); + wt_inc.allocate(age_st,age_end-1,"wt_inc"); + #ifndef NO_AD_INITIALIZE + wt_inc.initialize(); + #endif + d_scale.allocate(1,nscale_parm,age_st,age_end,phase_d_scale,"d_scale"); + K.allocate("K"); + #ifndef NO_AD_INITIALIZE + K.initialize(); + #endif + wt_hat.allocate(1,ndat_wt,1,max_nyrs_data,age_st,age_end,"wt_hat"); + #ifndef NO_AD_INITIALIZE + wt_hat.initialize(); + #endif + alphawt.allocate("alphawt"); + #ifndef NO_AD_INITIALIZE + alphawt.initialize(); + #endif + wt_pre.allocate(styr_wt,endyr_wt,age_st,age_end,"wt_pre"); + #ifndef NO_AD_INITIALIZE + wt_pre.initialize(); + #endif + mnwt.allocate(age_st,age_end,"mnwt"); + #ifndef NO_AD_INITIALIZE + mnwt.initialize(); + #endif + coh_eff.allocate(styr_wt-nages_wt-age_st+1,endyr_wt-age_st+3,-15,15,phase_coheff,"coh_eff"); + yr_eff.allocate(styr_wt,endyr_wt+3,-15,15,phase_yreff,"yr_eff"); + wt_last.allocate(age_st,age_end,"wt_last"); + wt_cur.allocate(age_st,age_end,"wt_cur"); + wt_next.allocate(age_st,age_end,"wt_next"); + wt_yraf.allocate(age_st,age_end,"wt_yraf"); + avg_age_msy.allocate("avg_age_msy"); + avgwt_msy.allocate("avgwt_msy"); + MSY.allocate("MSY"); + MSY_wt.allocate("MSY_wt"); + Fmsy.allocate("Fmsy"); + Fmsy_wt.allocate("Fmsy_wt"); + Fmsy2.allocate("Fmsy2"); + Fmsy2_wt.allocate("Fmsy2_wt"); + Fmsy2_dec.allocate(1,10,"Fmsy2_dec"); + Fmsy2_decwt.allocate(1,10,"Fmsy2_decwt"); + Bmsy2.allocate("Bmsy2"); + Bmsy2_wt.allocate("Bmsy2_wt"); + lnFmsy.allocate("lnFmsy"); + lnFmsy2.allocate("lnFmsy2"); + SER_Fmsy.allocate("SER_Fmsy"); + Fendyr_Fmsy.allocate("Fendyr_Fmsy"); + Rmsy.allocate("Rmsy"); + Bmsy.allocate("Bmsy"); + Fcur_Fmsy.allocate(1,nscen,"Fcur_Fmsy"); + Bcur_Bmsy.allocate(1,nscen,"Bcur_Bmsy"); + Bcur_Bmean.allocate(1,nscen,"Bcur_Bmean"); + Bcur3_Bcur.allocate(1,nscen,"Bcur3_Bcur"); + Bcur3_Bmean.allocate(1,nscen,"Bcur3_Bmean"); + Bcur2_Bmsy.allocate(1,nscen,"Bcur2_Bmsy"); + Bcur2_B20.allocate(1,nscen,"Bcur2_B20"); + LTA1_5R.allocate(1,nscen,"LTA1_5R"); + LTA1_5.allocate(1,nscen,"LTA1_5"); + MatAgeDiv1.allocate(1,nscen,"MatAgeDiv1"); + MatAgeDiv2.allocate(1,nscen,"MatAgeDiv2"); + H.allocate(styr,endyr_r,"H"); + #ifndef NO_AD_INITIALIZE + H.initialize(); + #endif + avg_age_mature.allocate(styr,endyr_r,"avg_age_mature"); + #ifndef NO_AD_INITIALIZE + avg_age_mature.initialize(); + #endif + RelEffort.allocate(1,nscen,"RelEffort"); + F40_spb.allocate("F40_spb"); + begbiom.allocate("begbiom"); + DepletionSpawners.allocate("DepletionSpawners"); + SB100.allocate("SB100"); + Current_Spawners.allocate("Current_Spawners"); + pred_rec.allocate(styr,endyr_r,"pred_rec"); + age_3_plus_biom.allocate(styr,endyr_r+2,"age_3_plus_biom"); + ABC_biom.allocate(1,10,"ABC_biom"); + ABC_biom2.allocate(1,10,"ABC_biom2"); + rechat.allocate(1,20,"rechat"); + SRresidhat.allocate(1,40,"SRresidhat"); + #ifndef NO_AD_INITIALIZE + SRresidhat.initialize(); + #endif + SER.allocate(styr,endyr_r,"SER"); + future_SER.allocate(1,nscen,styr_fut,endyr_fut,"future_SER"); + #ifndef NO_AD_INITIALIZE + future_SER.initialize(); + #endif + future_catch.allocate(1,nscen,styr_fut,endyr_fut,"future_catch"); + #ifndef NO_AD_INITIALIZE + future_catch.initialize(); + #endif + future_R.allocate(1,nscen,styr_fut,endyr_fut,"future_R"); + future_SSB.allocate(1,nscen,endyr_r,endyr_fut,"future_SSB"); + Age3_Abund.allocate(styr,endyr_r,"Age3_Abund"); + age_1_7_biomass.allocate(styr,endyr_r,"age_1_7_biomass"); + #ifndef NO_AD_INITIALIZE + age_1_7_biomass.initialize(); + #endif + NLL.allocate(1,20,"NLL"); + #ifndef NO_AD_INITIALIZE + NLL.initialize(); + #endif + fff.allocate("fff"); + prior_function_value.allocate("prior_function_value"); + likelihood_function_value.allocate("likelihood_function_value"); + resid_temp_x1.allocate(do_temp_phase,"resid_temp_x1"); + resid_temp_x2.allocate(do_temp_phase,"resid_temp_x2"); + SR_resids_temp.allocate(styr_est,endyr_est,"SR_resids_temp"); + #ifndef NO_AD_INITIALIZE + SR_resids_temp.initialize(); + #endif + SR_resids_like.allocate("SR_resids_like"); + #ifndef NO_AD_INITIALIZE + SR_resids_like.initialize(); + #endif + log_a_II.allocate(1,n_pred_grp,1,n_pred_ages,-12,0,do_pred_phase_ss,"log_a_II"); + log_b_II.allocate(1,n_pred_grp,1,n_pred_ages,0,12,do_pred_phase_ss,"log_b_II"); + log_a_II_vec.allocate(1,n_pred_grp,-12,0,do_pred_phase_ms,"log_a_II_vec"); + log_b_II_vec.allocate(1,n_pred_grp,0,12,do_pred_phase_ms,"log_b_II_vec"); + log_rho.allocate(1,n_pred_grp,1,n_pred_ages,-12,0,do_pred_phase_ms,"log_rho"); + log_resid_M.allocate(1,n_pred_ages,-3,0.1,do_pred_phase,"log_resid_M"); + resid_M.allocate(1,n_pred_ages,"resid_M"); + #ifndef NO_AD_INITIALIZE + resid_M.initialize(); + #endif + resid_M_like.allocate(1,n_pred_ages,"resid_M_like"); + #ifndef NO_AD_INITIALIZE + resid_M_like.initialize(); + #endif + a_II.allocate(1,n_pred_grp,1,n_pred_ages,"a_II"); + #ifndef NO_AD_INITIALIZE + a_II.initialize(); + #endif + b_II.allocate(1,n_pred_grp,1,n_pred_ages,"b_II"); + #ifndef NO_AD_INITIALIZE + b_II.initialize(); + #endif + rho.allocate(1,n_pred_grp,1,n_pred_ages,"rho"); + #ifndef NO_AD_INITIALIZE + rho.initialize(); + #endif + a_II_vec.allocate(1,n_pred_grp,"a_II_vec"); + #ifndef NO_AD_INITIALIZE + a_II_vec.initialize(); + #endif + b_II_vec.allocate(1,n_pred_grp,"b_II_vec"); + #ifndef NO_AD_INITIALIZE + b_II_vec.initialize(); + #endif + natage_strat.allocate(styr,endyr_r,1,n_pred_ages,1,nstrata_pred,"natage_strat"); + #ifndef NO_AD_INITIALIZE + natage_strat.initialize(); + #endif + natage_strat_dens.allocate(styr,endyr_r,1,n_pred_ages,1,nstrata_pred,"natage_strat_dens"); + #ifndef NO_AD_INITIALIZE + natage_strat_dens.initialize(); + #endif + meannatage.allocate(styr,endyr_r,1,nages,"meannatage"); + #ifndef NO_AD_INITIALIZE + meannatage.initialize(); + #endif + meannatage_bystrata.allocate(styr,endyr_r,1,nages,1,nstrata_pred,"meannatage_bystrata"); + #ifndef NO_AD_INITIALIZE + meannatage_bystrata.initialize(); + #endif + mean_dens_bystrata.allocate(styr,endyr_r,1,nages,1,nstrata_pred,"mean_dens_bystrata"); + #ifndef NO_AD_INITIALIZE + mean_dens_bystrata.initialize(); + #endif + mean_dens.allocate(styr,endyr_r,1,n_pred_ages,"mean_dens"); + #ifndef NO_AD_INITIALIZE + mean_dens.initialize(); + #endif + cons.allocate(1,n_pred_grp,styr,endyr_r,1,n_pred_ages,1,nstrata_pred,"cons"); + #ifndef NO_AD_INITIALIZE + cons.initialize(); + #endif + natmort_pred.allocate(1,n_pred_ages,styr,endyr_r,1,nstrata_pred,"natmort_pred"); + #ifndef NO_AD_INITIALIZE + natmort_pred.initialize(); + #endif + M_pred.allocate(styr,endyr_r,1,n_pred_ages,1,nstrata_pred,1,n_pred_grp_nonpoll,"M_pred"); + #ifndef NO_AD_INITIALIZE + M_pred.initialize(); + #endif + M_pred_tmp.allocate(1,n_pred_grp_nonpoll,1,n_pred_ages,"M_pred_tmp"); + #ifndef NO_AD_INITIALIZE + M_pred_tmp.initialize(); + #endif + M_pred_sum.allocate(styr,endyr_r,1,n_pred_ages,1,nstrata_pred,"M_pred_sum"); + #ifndef NO_AD_INITIALIZE + M_pred_sum.initialize(); + #endif + Z_pred.allocate(styr,endyr_r,1,n_pred_ages,1,nstrata_pred,"Z_pred"); + #ifndef NO_AD_INITIALIZE + Z_pred.initialize(); + #endif + S_pred.allocate(styr,endyr_r,1,n_pred_ages,1,nstrata_pred,"S_pred"); + #ifndef NO_AD_INITIALIZE + S_pred.initialize(); + #endif + M_pred_avg.allocate(1,n_pred_ages,styr,endyr_r,"M_pred_avg"); + #ifndef NO_AD_INITIALIZE + M_pred_avg.initialize(); + #endif + cons_atage.allocate(1,n_pred_grp,styr,endyr_r,1,n_pred_ages,"cons_atage"); + #ifndef NO_AD_INITIALIZE + cons_atage.initialize(); + #endif + cons_atage_wt.allocate(1,n_pred_grp,styr,endyr_r,1,n_pred_ages,"cons_atage_wt"); + #ifndef NO_AD_INITIALIZE + cons_atage_wt.initialize(); + #endif + pred_cons.allocate(1,n_pred_grp,styr,endyr_r,"pred_cons"); + #ifndef NO_AD_INITIALIZE + pred_cons.initialize(); + #endif + eac_cons.allocate(1,n_pred_grp,styr,endyr_r,1,n_pred_ages,"eac_cons"); + #ifndef NO_AD_INITIALIZE + eac_cons.initialize(); + #endif + ssq_cons.allocate(1,n_pred_grp,"ssq_cons"); + #ifndef NO_AD_INITIALIZE + ssq_cons.initialize(); + #endif + oac_cons_like_offset.allocate(1,n_pred_grp,"oac_cons_like_offset"); + #ifndef NO_AD_INITIALIZE + oac_cons_like_offset.initialize(); + #endif + age_like_cons.allocate(1,n_pred_grp,"age_like_cons"); + #ifndef NO_AD_INITIALIZE + age_like_cons.initialize(); + #endif + pred_cpup.allocate(1,n_pred_grp,styr,endyr_r,1,n_pred_ages,"pred_cpup"); + #ifndef NO_AD_INITIALIZE + pred_cpup.initialize(); + #endif + implied_cpuppa.allocate(1,n_pred_grp,styr,endyr_r,1,n_pred_ages,1,nstrata_pred,"implied_cpuppa"); + #ifndef NO_AD_INITIALIZE + implied_cpuppa.initialize(); + #endif + implied_obs_cons_bystrata.allocate(1,n_pred_grp,styr,endyr_r,1,n_pred_ages,1,nstrata_pred,"implied_obs_cons_bystrata"); + #ifndef NO_AD_INITIALIZE + implied_obs_cons_bystrata.initialize(); + #endif + implied_prop_Cmax.allocate(1,n_pred_grp,styr,endyr_r,1,n_pred_ages,1,nstrata_pred,"implied_prop_Cmax"); + #ifndef NO_AD_INITIALIZE + implied_prop_Cmax.initialize(); + #endif + max_F_yldcrv.allocate("max_F_yldcrv"); + #ifndef NO_AD_INITIALIZE + max_F_yldcrv.initialize(); + #endif + F_yldcrv.allocate(1,40,"F_yldcrv"); + #ifndef NO_AD_INITIALIZE + F_yldcrv.initialize(); + #endif + yield_curve.allocate(1,40,"yield_curve"); + #ifndef NO_AD_INITIALIZE + yield_curve.initialize(); + #endif + natmort_fut.allocate(1,nages,"natmort_fut"); + #ifndef NO_AD_INITIALIZE + natmort_fut.initialize(); + #endif + compweightsnew.allocate(1,n_pred_grp_nonpoll,"compweightsnew"); + #ifndef NO_AD_INITIALIZE + compweightsnew.initialize(); + #endif + comp_mcian_wgt_inv.allocate(1,n_pred_grp_nonpoll,1,nyrs_cons_nonpoll,"comp_mcian_wgt_inv"); + #ifndef NO_AD_INITIALIZE + comp_mcian_wgt_inv.initialize(); + #endif + comp_mcian_wgt.allocate(1,n_pred_grp_nonpoll,1,nyrs_cons_nonpoll,"comp_mcian_wgt"); + #ifndef NO_AD_INITIALIZE + comp_mcian_wgt.initialize(); + #endif + consweightsnew.allocate(1,n_pred_grp_nonpoll,"consweightsnew"); + #ifndef NO_AD_INITIALIZE + consweightsnew.initialize(); + #endif + cons_nr.allocate(1,n_pred_grp_nonpoll,1,nyrs_cons_nonpoll,"cons_nr"); + #ifndef NO_AD_INITIALIZE + cons_nr.initialize(); + #endif + comp_nr.allocate(1,n_pred_grp_nonpoll,1,comp_nr_ub,"comp_nr"); + #ifndef NO_AD_INITIALIZE + comp_nr.initialize(); + #endif + pred_rec_alpha.allocate("pred_rec_alpha"); + #ifndef NO_AD_INITIALIZE + pred_rec_alpha.initialize(); + #endif + srmod_rec_alpha.allocate("srmod_rec_alpha"); + #ifndef NO_AD_INITIALIZE + srmod_rec_alpha.initialize(); + #endif +} + +void model_parameters::preliminary_calculations(void) +{ + +#if defined(USE_ADPVM) + + admaster_slave_variable_interface(*this); + +#endif + // fixed_catch_fut1 = fixed_catch_fut1 + 0.1 ; + wt_fut = wt_fsh(endyr_r); // initializes estimates to correct values...Eq. 21 + // base_natmort(1)=.9; base_natmort(2)=.45; for (j=3 ;j<=nages;j++) base_natmort(j)=natmortprior; + base_natmort = natmort_in; + natmort = base_natmort; + // cout <<"M input= "< 0.4 ) ignore_last_ats_age1 = 1; else ignore_last_ats_age1=0; + // cout <<" Last age comp in BTS: " << endl << oac_bts_data(n_bts) << endl; + // cout <<" Age_like_offset: " << endl << age_like_offset << endl; + Cat_Fut(1) = next_yrs_catch; // catch guess + // Simple decrement of future cathes to capture relationship between adjustments (below Bmsy) w/in same year + for (i=2;i<=10;i++) + Cat_Fut(i) = Cat_Fut(i-1)*.90; + write_log(Cat_Fut); + // cout << "Next year's catch and decrements"<0)) + Profile_F(); + if (mceval_phase()) + write_eval(); + update_compweights(); // added by Paul +#ifdef DEBUG + std::cout << "DEBUG: Total gradient stack used is " << gradient_structure::get()->GRAD_STACK1->total() << " out of " << gradient_structure::get_GRADSTACK_BUFFER_SIZE() << std::endl;; + std::cout << "DEBUG: Total dvariable address used is " << gradient_structure::get()->GRAD_LIST->total_addresses() << " out of " << gradient_structure::get_MAX_DLINKS() << std::endl;; + std::cout << "DEBUG: Total dvariable address used is " << gradient_structure::get()->ARR_LIST1->get_max_last_offset() << " out of " << gradient_structure::get_ARRAY_MEMBLOCK_SIZE() << std::endl;; +#endif +} + +void model_parameters::update_compweights(void) +{ + ofstream& srecout= *pad_srecout; + ofstream& projout= *pad_projout; + ofstream& nofish= *pad_nofish; + ofstream& projout2= *pad_projout2; + ofstream& eval= *pad_eval; + random_number_generator& rng= *pad_rng; + if(active(log_resid_M)) + { + for (i=1;i<=n_pred_grp_nonpoll;i++) + { + compweightsnew(i) = 1.0/mean(comp_mcian_wgt_inv(i)); // weights for consumption age comps + consweightsnew(i) = std_dev(cons_nr(i)); // weights for consumption estimates + } + } + else + { + compweightsnew = compweights; + consweightsnew = consweights; + } +} + +void model_parameters::Get_Selectivity(void) +{ + ofstream& srecout= *pad_srecout; + ofstream& projout= *pad_projout; + ofstream& nofish= *pad_nofish; + ofstream& projout2= *pad_projout2; + ofstream& eval= *pad_eval; + random_number_generator& rng= *pad_rng; + avgsel_fsh.initialize(); + avgsel_bts.initialize(); + avgsel_ats.initialize(); + //cout<<"InSel"<0) // For logistic fishery selectivity (not default, NOT USED) + { + dvariable dif; + dvariable inf; + if (active(sel_a501_fsh_dev)) + { + dvar_matrix seldevs_tmp(1,3,styr,endyr_r); + seldevs_tmp(1) = sel_dif1_fsh_dev; + seldevs_tmp(2) = sel_a501_fsh_dev; + seldevs_tmp(3) = sel_trm2_fsh_dev; + log_sel_fsh = compute_selectivity1(styr,sel_dif1_fsh,sel_a501_fsh,sel_trm2_fsh,seldevs_tmp); + } + else + log_sel_fsh = compute_selectivity1(styr,sel_dif1_fsh,sel_a501_fsh,sel_trm2_fsh); + } + //cout<<"InSel"<38) + yr_ind = 38; + for (k=1;k<=n_pred_ages;k++) // loop over ages of pollock that are preyed upon + { + natage_strat(i,k) = natage(i,pred_ages(k))*poll_dist(k,i); // distribute the age k pollock in each area + natage_strat_dens(i,k) = elem_div(natage_strat(i,k),area_pred); // the density of age k pollock in each area + } + // do the multispecies funcction response thing + if (do_mult_func_resp==1) + { + for (j=1;j<=nstrata_pred;j++) // loop over strata, and get the mean abundance accounting for all mortality + { + M_pred_tmp = get_Mpred2(column(natage_strat_dens(i),j),resid_M,F(i)(1,n_pred_ages), + column(Npred_bystrata_nonpoll(i),j), + column(mn_wgt_nonpoll,i), + wt_bts(yr_ind)(1,n_pred_ages)*1000, + column(Cmax_nonpoll(i),j),rho, + a_II_vec,b_II_vec, j); + // cout << "M_pred_tmp is " << M_pred_tmp << endl; + // loop to get the results in the right structure + for (ii=1;ii<=n_pred_ages;ii++) + { + for (jj=1;jj<=n_pred_grp;jj++) + { + M_pred(i,ii,j,jj) = M_pred_tmp(jj,ii); + //cout <<" prey age is " << ii<< " pred_grp is "<< jj << " strata is " << j << " M_pred is " << M_pred(i,ii,j,jj) << endl; + } + } + } + } // loop if doing the multispecies functional response + // loop over ages of pollock that are preyed upon + for (k=1;k<=n_pred_ages;k++) + { + // loop over strata, and get the mean abundance accounting for all mortality + for (j=1;j<=nstrata_pred;j++) + { + if (do_mult_func_resp != 1) // loop is doing the single species functional response + { + // natage_strat(styr,endyr_r,1,n_pred_ages,1,nstrata_pred) // the number of poll by strata for a given year and age + // Jim thinks this may be easier implemented by passing the indices (i,j,k)... + M_pred(i,k,j) = get_Mpred(natage_strat_dens(i,k,j), + F(i,pred_ages(k)), + resid_M(k), + column(natage_strat_dens(i),j), + column(a_II,k), + column(b_II,k), + column(Npred_bystrata_nonpoll(i),j), + column(mn_wgt_nonpoll,i)/(wt_bts(yr_ind,k)*1000), + column(Cmax_nonpoll(i),j),rho); + // e.g.,: M_pred(i,k,j) = get_Mpred(i,k,j); + } + M_pred_sum(i,k,j) = sum(M_pred(i,k,j)); // sum across the different predators + natmort_pred(k,i,j) = M_pred_sum(i,k,j) + resid_M(k); + Z_pred(i,k,j) = F(i,pred_ages(k)) + natmort_pred(k,i,j); // get the total Z by year, pollock age, and strata + S_pred(i,k,j) = mfexp(-1.0*Z_pred(i,k,j)); + } // close strata loop + // cout << "M_pred is " << M_pred<< endl; + meannatage_bystrata(i,k) = elem_div(elem_prod(natage_strat(i,k),(1.-S_pred(i,k))),Z_pred(i,k)); // the mean number at age by strata + meannatage(i,k) = sum(meannatage_bystrata(i,k)); // the mean N summed across the strata + mean_dens_bystrata(i,k) = elem_div(meannatage_bystrata(i,k),area_pred); + mean_dens(i,k) = (meannatage(i,k))/sum(area_pred); // the mean density summed over the strata within a year and age + for (j=1;j<=nstrata_pred;j++) + { // loop over strata, and get the mean abundance accounting for all mortality + for (m=1;m<=n_pred_grp;m++) + { // loop over predators, and get the consumption and M by predator, pollock age, year, and strata + cons(m,i,k,j) = M_pred(i,k,j,m)*meannatage_bystrata(i,k,j); + } + } + M_pred_avg(k,i) = (M_pred_sum(i,k)*meannatage_bystrata(i,k))/sum(meannatage_bystrata(i,k)); // get an average M_pred across the strata, weighted by the beginning abundance in each strata + // get the total survival by year, pollock age, and strata + if(i < endyr_r) + natage(i+1,k+1) = natage_strat(i,k)*S_pred(i,k); // the natage after predation (summed over strata) + SSB(i) += natage_strat(i,k)*pow(S_pred(i,k),yrfrac)*p_mature(pred_ages(k))*wt_ssb(i,pred_ages(k)); + } // end age loop + SSB(i) += elem_prod(elem_prod(natage(i)(n_pred_ages+1,nages), + pow(S(i)(n_pred_ages+1,nages),yrfrac)),p_mature(n_pred_ages+1,nages))*wt_ssb(i)(n_pred_ages+1,nages); // Eq. 1 + meannatage(i)(n_pred_ages+1,nages) = elem_prod(elem_div(1.-S(i)(n_pred_ages+1,nages),Z(i)(n_pred_ages+1,nages)), + natage(i)(n_pred_ages+1,nages)); // the mean n at age for the ages not preyed upon + if (i < endyr_r) + { + natage(i+1)(n_pred_ages+2,nages) = ++elem_prod(natage(i)(n_pred_ages+1,nages-1), S(i)(n_pred_ages+1,nages-1)); + natage(i+1,nages) += natage(i,nages)*S(i,nages); // Eq. 1 + } + } // end year loop + // added by Paul to get M values the reflect the recent predation + for (i=1;i<=n_pred_ages;i++) + { + natmort_fut(i) = mean(M_pred_avg(i)(endyr_r-4,endyr_r) + resid_M(i)); + } + } // ********* end of thing by Paul ******************* + //meanrec = mean(pred_rec(styr_est,endyr_r)); + meanrec = mean(pred_rec(1978,endyr_r)); // ***** changed by Paul to hard-wire mean rec to 1978 onwards + /* // This function might replace the uglier one... +} + +dvar_vector model_parameters::get_Mpred(const int& i,const int& j,const int& k) +{ + ofstream& srecout= *pad_srecout; + ofstream& projout= *pad_projout; + ofstream& nofish= *pad_nofish; + ofstream& projout2= *pad_projout2; + ofstream& eval= *pad_eval; + random_number_generator& rng= *pad_rng; + dvariable tmp_abun_bg = natage_strat_dens(i,k,j); + dvariable tmp_F = F(i,pred_ages(k)); + dvariable tmp_M = resit_M(k); + dvar_vector tmp_abun_vec = column(natage_strat_dens(i),j); + dvar_vector a = column(a_II,k); + dvar_vector b = column(b_II,k); + dvector Npred = column(Npred_bystrata_nonpoll(i),j); + dvector wt_ratio = column(mn_wgt_nonpoll,i)/(wt_bts(yr_ind,k)*1000); + dvector tmp_Cmax = column(Cmax_nonpoll(i),j),rho); + dvariable tmp_abun_end; // the abundance at the end of the period + dvariable avg_N; // the average N within the year + dvar_vector M_pred(1,n_pred_grp); // Holling type II predation F (for each predator type) + dvariable M_pred_sum; // the total M_pred + dvariable prev_tmp_abun_end; // the abundance at the end of the period, from the previous time step + if (tmp_abun_bg >0) + { + tmp_abun_end = tmp_abun_bg*mfexp(-tmp_F -tmp_M); + avg_N = tmp_abun_bg*(1-mfexp(-tmp_F -tmp_M))/(tmp_F + tmp_M); + M_pred = elem_prod(elem_prod(wt_ratio,elem_prod(tmp_Cmax,elem_prod(a,Npred))),(1/(b+avg_N))); + M_pred_sum = sum(M_pred); + //M_pred = elem_prod(a,Npred)*(1/(b+avg_N)); + cout << "the weight ratio is " << endl; + cout << wt_ratio << endl; + cout << "the tmp_Cmax is " << endl; + cout << tmp_Cmax << endl; + cout << "the a_II " << endl; + cout << a << endl; + cout << "the Npred " << endl; + cout << Npred << endl; + cout << "The b_II " << endl; + cout << b << endl; + cout << "The avg_N " << endl; + cout << avg_N << endl; + cout << "the M_pred " << endl; + cout << elem_prod(wt_ratio,elem_prod(tmp_Cmax,elem_prod(a,Npred)))*(1/(b+avg_N)) << endl; + // Check this should be double not dvariable... + double dd = 10.; + int iter = 0; + // Check differentiability here... + while (iter < 10) + { + iter++; + prev_tmp_abun_end = tmp_abun_end; + tmp_abun_end = tmp_abun_bg*mfexp(-tmp_F -tmp_M -M_pred_sum); + avg_N = tmp_abun_bg*(1-mfexp(-tmp_F -tmp_M -M_pred_sum))/(tmp_F + tmp_M + M_pred_sum); + M_pred = elem_prod(elem_prod(wt_ratio,elem_prod(tmp_Cmax,elem_prod(a,Npred))),(1/(b+avg_N))); + M_pred_sum = sum(M_pred); + //M_pred = elem_prod(a,Npred)*(1/(b+avg_N)); + dd = value(prev_tmp_abun_end) / value(tmp_abun_end) - 1.; + if (dd<0.) dd *= -1.; + // if(active(log_a_II)){ + // cout <<"in loop "<0) + { + tmp_abun_end = tmp_abun_bg*mfexp(-tmp_F -tmp_M); + avg_N = tmp_abun_bg*(1-mfexp(-tmp_F -tmp_M))/(tmp_F + tmp_M); + M_pred = elem_prod(elem_prod(wt_ratio,elem_prod(tmp_Cmax,elem_prod(a,Npred))),(1/(b+avg_N))); + M_pred_sum = sum(M_pred); + //M_pred = elem_prod(a,Npred)*(1/(b+avg_N)); + /*cout << "the weight ratio is " << endl; + cout << wt_ratio << endl; + cout << "the tmp_Cmax is " << endl; + cout << tmp_Cmax << endl; + cout << "the a_II " << endl; + cout << a << endl; + cout << "the Npred " << endl; + cout << Npred << endl; + cout << "The b_II " << endl; + cout << b << endl; + cout << "The avg_N " << endl; + cout << avg_N << endl; + cout << "the M_pred " << endl; + cout << elem_prod(wt_ratio,elem_prod(tmp_Cmax,elem_prod(a,Npred)))*(1/(b+avg_N)) << endl; + */ + // Check this should be double not dvariable... + dvariable dd = 10.; + int iter = 0; + // Check differentiability here... + while (dd > 1e-6) + { + iter++; + prev_tmp_abun_end = tmp_abun_end; + tmp_abun_end = tmp_abun_bg*mfexp(-tmp_F -tmp_M -M_pred_sum); + avg_N = tmp_abun_bg*(1-mfexp(-tmp_F -tmp_M -M_pred_sum))/(tmp_F + tmp_M + M_pred_sum); + M_pred = elem_prod(elem_prod(wt_ratio,elem_prod(tmp_Cmax,elem_prod(a,Npred))),(1/(b+avg_N))); + M_pred_sum = sum(M_pred); + dd = prev_tmp_abun_end / tmp_abun_end - 1.; + //M_pred = elem_prod(a,Npred)*(1/(b+avg_N)); + if (dd<0.) + dd *= -1.; + // if(active(log_a_II)){ + // cout <<"in loop "<0.0) + { + tmp_abun_end_vec = elem_prod(tmp_abun_vec,mfexp(-F_vec -tmp_M_vec)); + avg_N_vec = elem_prod(tmp_abun_vec,elem_div((1-mfexp(-F_vec -tmp_M_vec)),(F_vec + tmp_M_vec))); + for (ii=1;ii<=n_pred_ages;ii++) // loop over prey ages + { + for (jj=1;jj<=n_pred_grp;jj++) // loop over number of predators + { + M_pred_mat(jj,ii) = (tmp_Cmax(jj)* (wts_pred(jj)/wts_prey(ii)) *a_vec(jj)*Npred(jj)*rho(jj,ii))/ + (b_vec(jj) + rho(jj)*avg_N_vec); + } + M_pred_sum_vec(ii) = sum(column(M_pred_mat,ii)); + } + dvector dd_vec(1,n_pred_ages); + double dd_vec_sum = 10; + int iter = 0; + while (dd_vec_sum > 1e-6) + { + iter++; + prev_tmp_abun_end_vec = tmp_abun_end_vec; + tmp_abun_end_vec = elem_prod(tmp_abun_vec,mfexp(-F_vec -tmp_M_vec -M_pred_sum_vec)); + avg_N_vec = elem_prod(tmp_abun_vec,elem_div((1-mfexp(-F_vec -tmp_M_vec -M_pred_sum_vec)),(F_vec + tmp_M_vec +M_pred_sum_vec))); + for (ii=1;ii<=n_pred_ages;ii++) // loop over prey ages + { + for (jj=1;jj<=n_pred_grp;jj++) // loop over number of predators + { + M_pred_mat(jj,ii) = (tmp_Cmax(jj)*(wts_pred(jj)/wts_prey(ii))*a_vec(jj)*Npred(jj)*rho(jj,ii))/(b_vec(jj) + rho(jj)*avg_N_vec); + } + M_pred_sum_vec(ii) = sum(column(M_pred_mat,ii)); + } + for (ii=1;ii<=n_pred_ages;ii++) + { + if (tmp_abun_end_vec(ii)>0.0) + { + dd_vec(ii) = value(prev_tmp_abun_end_vec(ii)) / value(tmp_abun_end_vec(ii)) - 1.; + if (dd_vec(ii)<0.) dd_vec(ii) *= -1.; + } + else dd_vec(ii) = 0.0; + } + dd_vec_sum = sum(dd_vec); + } + } + else + { + M_pred_mat = 0.0; + } + for (ii=1;ii<=n_pred_ages;ii++) + { + if (tmp_abun_end_vec(ii)==0.0) + { + for (jj=1;jj<=n_pred_grp;jj++) M_pred_mat(jj,ii) = 0.0; + } + } + RETURN_ARRAYS_DECREMENT(); + return M_pred_mat; +} + +void model_parameters::GetDependentVar(void) +{ + ofstream& srecout= *pad_srecout; + ofstream& projout= *pad_projout; + ofstream& nofish= *pad_nofish; + ofstream& projout2= *pad_projout2; + ofstream& eval= *pad_eval; + random_number_generator& rng= *pad_rng; + // For making some output for spiffy output + // Spiffy SR output + tmpsp=1.1*max(SSB); + if (tmpsp=2020) + { + regime(2) = mean(pred_rec(1978,2020)); + regime(5) = mean(pred_rec(1990,2020)); + regime(7) = mean(pred_rec(2000,2020)); + regime(8) = mean(pred_rec(1964,2020)); + regime(6) = mean(pred_rec(1990,1999)); + regime(3) = mean(pred_rec(1978,1999)); + } + else + { + if (endyr_r<=2000) + regime(7) = pred_rec(endyr_r); + else + regime(7) = mean(pred_rec(2000,endyr_r)); + regime(2) = mean(pred_rec(1978,endyr_r)); + regime(5) = mean(pred_rec(1990,endyr_r)); + regime(8) = mean(pred_rec(1964,endyr_r)); + if (endyr_r<=1999) + { + regime(3) = mean(pred_rec(1978,endyr_r)); + regime(6) = mean(pred_rec(1990,endyr_r)); + } + else + { + regime(6) = mean(pred_rec(1990,1999)); + regime(3) = mean(pred_rec(1978,1999)); + } + } + if (!mceval_phase()) get_msy(); + dvar_vector res(1,4); + res.initialize(); + res = get_msy_wt(); + Fmsy_wt = res(1); + MSY_wt = res(2); + Bmsy2_wt = res(3); + Fmsy2_wt = res(4); + // cout <<"Msy stuff: "<=1;iyr--) + { + res.initialize(); + sel_fut = sel_fsh(endyr_r-iyr+1); + // sel_fut /=sel_fut(6); // NORMALIZE TO AGE 6 + sel_fut /= mean(sel_fut); // NORMALIZE TO mean + if (!mceval_phase()) res = get_msy_wt(); + Fmsy2_dec(iyr) = res(4); + // cout <=1;iyr--) + { + res.initialize(); + wt_fut(3,nages) = wt_pre(endyr_wt-iyr+1); + if (!mceval_phase()) res = get_msy_wt(); + Fmsy2_decwt(iyr) = res(4); + // cout <8) + ftmp= mean(F(endyr_r)) * ((double(k-1)-1.)*.05 + 0.5); // this takes endyr F and brackets it...for mean + else + ftmp = SolveF2(natage_future(k,styr_fut),dec_tab_catch(k)); + } + // if (k==8) ftmp=Fmsy; + for (i=styr_fut;i<=endyr_fut;i++) + { + F_future(k,i) = sel_fut*ftmp; + Z_future(i) = F_future(k,i) + natmort; + S_future(i) = mfexp(-Z_future(i)); + dvariable criterion; + dvariable Bref ; + future_SSB(k,i) = elem_prod(elem_prod(natage_future(k,i),pow(S_future(i),yrfrac)), p_mature) * wt_ssb(endyr_r); + // Now compute the time of spawning SSB for everything else.... + // future_SSB(k,i) = elem_prod(elem_prod(natage_future(k,i),pow(S_future(i),yrfrac)), p_mature) * wt_ssb(endyr_r); + if (phase_sr<0) //No Stock-recruitment curve for future projections-------- + natage_future(k,i, 1) = mfexp(log_avgrec + rec_dev_future(i)); + else //Use Stock-recruitment curve --------- + { + Xspawn =future_SSB(k,i-1); + natage_future(k,i,1) = SRecruit(Xspawn) * mfexp(rec_dev_future(i) ); + } + future_R(k,i) = natage_future(k,i,1); + if (i0 ) + { + for (i=endyr_r-(nyrs_sel_avg+1);i3) get_combined_index(); +} + +void model_parameters::Get_Cons_at_Age(void) +{ + ofstream& srecout= *pad_srecout; + ofstream& projout= *pad_projout; + ofstream& nofish= *pad_nofish; + ofstream& projout2= *pad_projout2; + ofstream& eval= *pad_eval; + random_number_generator& rng= *pad_rng; + // added by Paul + // if doing the spatial predation thing, get the consumption at age + for (i=styr;i<=endyr_r;i++) + { + for (k=1;k<=n_pred_ages;k++) + { + for (m=1;m<=n_pred_grp;m++) + { + cons_atage(m,i,k) = sum(cons(m,i,k)); // get ths consumption by predator, year, and age (summed over strata) + pred_cpup(m,i,k) = cons_atage(m,i,k)/N_pred(m,i); + } // predator loop + } // age loop + } // year loop + for (i=styr;i<=endyr_r;i++) + { + yr_ind = i-1981; // for getting the index for the wt_bts + if(yr_ind<1) + yr_ind = 1; + if(yr_ind>38) + yr_ind = 38; + for (m=1;m<=n_pred_grp;m++) + { + cons_atage_wt(m,i) = elem_prod(cons_atage(m,i),wt_bts(yr_ind)(1,n_pred_ages)); + pred_cons(m,i) = sum(cons_atage_wt(m,i)); // the predicted consumption by predator and year (summed over age and strata) + eac_cons(m,i) = cons_atage_wt(m,i)/pred_cons(m,i); // the predicted consumption age comp (by predator and year) + } // predator loop + } // year loop + for (i=styr;i<=endyr_r;i++) + { + yr_ind = i-1981; // for getting the index for the wt_bts + if(yr_ind<1) + yr_ind = 1; + if(yr_ind>38) + yr_ind = 38; + for (m=1;m<=n_pred_grp;m++) + { + for (k=1;k<=n_pred_ages;k++) + { + // implied_obs_cons_bystrata(m,i,k) = obs_cons_natage_nonpoll(m,i,k)*(cons(m,iyr,k)/cons_atage(m,iyr,k)); + implied_obs_cons_bystrata(m,i,k) = cons(m,i,k); + for (z=1;z<=nstrata_pred;z++) + { + if (Npred_bystrata_nonpoll(i,m,z)>0) + { + implied_cpuppa(m,i,k,z) = implied_obs_cons_bystrata(m,i,k,z)/(Npred_bystrata_nonpoll(i,m,z)*area_pred(z)); + implied_prop_Cmax(m,i,k,z) = (implied_cpuppa(m,i,k,z)*area_pred(z))/ + ((mn_wgt_nonpoll(m,i)/(wt_bts(yr_ind,k)*1000))*Cmax_nonpoll(i,m,z)); + // old code here -- used in model runs for Brazil paper + // implied_cpuppa(m,i,k,z) = + // (implied_obs_cons_bystrata(m,i,k,z)*((wt_bts(yr_ind,k)*1000)/mn_wgt_nonpoll(m,iyr)))/ + // (Cmax_nonpoll(iyr,m,z)*Npred_bystrata_nonpoll(iyr,m,z)*area_pred(z)); + // implied_prop_Cmax(m,i,k,z) = implied_cpuppa(m,i,k,z)*area_pred(z); + } + else + { + implied_cpuppa(m,i,k,z) = -9; + implied_prop_Cmax(m,i,k,z) = -9; + } + /*cout <<"year is "<5||F1<0.01)) + { + ii=9; + count_Ffail++; + cout<5||F1<0.01)) + { + ii=5; + count_Ffail++; + cout< 0) + //rec_like(5) += 10.*norm2(log_rec_devs(endyr_est,endyr_r))/(2.*sigmarsq_out+.001); + /* Larval drift contribution to recruitment prediction (not used in recent years) Eq. 8 + if (active(larv_rec_devs)) + rec_like(3) += ctrl_flag(23)*norm2(larv_rec_devs); + if (ctrl_flag(27)>0) + { + larv_rec_trans=trans(larv_rec_devs); + // Do third differencing on spatial aspect... + for (i=1;i<=11;i++) + { + rec_like(6) += ctrl_flag(27)*norm2(first_difference( first_difference(first_difference( larv_rec_devs(i))))); + rec_like(6) += ctrl_flag(27)*norm2(first_difference( first_difference(first_difference(larv_rec_trans(i))))); + } + } + */ + // +===+====+==+==+==+==+==+==+==+====+====+==+==+===+====+==+==+==+==+==+==+==+====+====+====+ +} + +void model_parameters::Evaluate_Objective_Function(void) +{ + ofstream& srecout= *pad_srecout; + ofstream& projout= *pad_projout; + ofstream& nofish= *pad_nofish; + ofstream& projout2= *pad_projout2; + ofstream& eval= *pad_eval; + random_number_generator& rng= *pad_rng; + // if (active(repl_F)) + Recruitment_Likelihood(); + Surv_Likelihood(); //-survey Deviations + Selectivity_Likelihood(); + catch_like = norm2(log(obs_catch(styr,endyr_r)+1e-4)-log(pred_catch+1e-4)); + if (current_phase() >= robust_phase) + Robust_Likelihood(); //-Robust AGE Likelihood part + else + Multinomial_Likelihood(); //-Multinomial AGE Likelihood part + NLL.initialize(); + NLL(1) += ctrl_flag(1) * catch_like; + NLL(2) += ctrl_flag(2) * surv_like(1); + NLL(3) += ctrl_flag(2) * surv_like(2); + NLL(4) += ctrl_flag(2) * surv_like(3); + NLL(5) += ctrl_flag(12) * cpue_like; + NLL(6) += ctrl_flag(6) * avo_like; + NLL(7) += ctrl_flag(3) * sum(rec_like); + if (phase_cope>0 & current_phase()>=phase_cope) + NLL(8) += cope_like; + F_pen = norm2(log_F_devs); + NLL(9) += ctrl_flag(4) * F_pen; + NLL(10) += ctrl_flag(7)*age_like(1); + NLL(11) += ctrl_flag(8)*age_like(2); + NLL(12) += ctrl_flag(9)*age_like(3); + if (use_endyr_len>0) + NLL(13)+= ctrl_flag(7)*len_like; + NLL(14)+= sum(sel_like); + NLL(15)+= sum(sel_like_dev); + //COUT(sel_like_dev); + // COUT(age_like); + // COUT(avo_like); + // COUT(surv_like); + // Condition model in early phases to stay reasonable + // Removed at the end + if (current_phase()<3) + { + fff += 10.*square(log(mean(Fmort)/.2)); + fff += 10.*square(log_avginit-log_avgrec) ; //This is to make the initial comp not stray too far + } + Priors.initialize(); + if (active(natmort_phi)) // Sensitivity approach for estimating natural mortality (as offset of input vector, NOT USED, NOT IN DOC) + Priors(3) = norm2( log(natmort(3,nages) / natmortprior) )/(2.*cvnatmortprior*cvnatmortprior); + // Prior on combined-survey catchability, idea is to have sum of two surveys tend to the prior distribution + // q_all.initialize(); + dvariable q_bts_tmp; + dvariable q_ats_tmp; + q_bts_tmp.initialize(); + q_ats_tmp.initialize(); + for (i=1;i<=n_bts_r;i++) + { + iyr = yrs_bts_data(i); + // Note this is to correct for reduced survey strata coverage pre 1985 and in 86 + if (!(iyr<1985||iyr==1986)) + { + q_bts_tmp += sum(mfexp(log_q_bts + log_sel_bts(iyr)(q_amin,q_amax))); + } + } + q_bts_tmp /= ((q_amax-q_amin+1)*(n_bts_r-4)) ; // 4 years not in main q calc...OjO will break if BTS series length changes between 1982 and 86 + for ( i=1;i<=n_ats_r;i++) + { + iyr = yrs_ats_data(i); + q_ats_tmp += sum(mfexp(log_q_ats + log_sel_ats(iyr)(q_amin,q_amax))); + } + q_ats_tmp /= ((q_amax-q_amin+1)*n_ats_r) ; + q_all= log(q_bts_tmp + q_ats_tmp) ; + // Note: optional ability to put a prior on "combined" surveys overall catchability + if (q_all_sigma<1.) + Priors(2) = square( q_all- q_all_prior )/(2.*q_all_sigma*q_all_sigma); + q_all = exp(q_all); + // Prior on BTS catchability + if (active(log_q_bts)&&q_bts_sigma<1.) + { + Priors(2) = square( log_q_bts - q_bts_prior )/(2.*q_bts_sigma*q_bts_sigma); + // cout<0&&last_phase()) + { + get_msy(); + // cout<<"SPR: "<log_sel_fsh(i,j+1)) + sel_like(1)+=ctrl_flag(13)*square(log_sel_fsh(i,j)-log_sel_fsh(i,j+1)); + if (active(sel_coffs_bts)) + { + for (i=styr_bts;i<= endyr_r;i++) //--This is for controlling the selectivity shape BOTTOM TRAWL SURVEY + for (j=6;j<=n_selages_bts;j++) + if (log_sel_bts(i,j)>log_sel_bts(i,j+1)) + sel_like(2)+=ctrl_flag(14)*square(log_sel_bts(i,j)-log_sel_bts(i,j+1)); + } + for (i=styr_ats;i<= endyr_r;i++) //--This is for selectivity shape HYDROA TRAWL SURVEY + for (j=mina_ats;j<=n_selages_ats;j++) + if (log_sel_ats(i,j)0.){ + dvar_matrix lnseltmp = trans(log_sel_bts); + for (j=q_amin;j3) + { + for (i=1;i<=n_bts_r;i++) + { + // Under development--not used (yet). Idea to combine surveys for directly accounting for differences + // of water column densities... + surv_like(1) += square(ot_cmb(i)-et_cmb(i))/(2.*var_cmb(i)); + // slight penalty here to get the q to scale correctly (note--development, not used) + surv_like(1) += .01*square(ot_bts(i)-et_bts(i))/(2.*var_ot_bts(i)); + } + // slight penalty here to get the q to scale correctly + for (i=1;i<=n_ats_r;i++) + surv_like(2) += .01*square(log(ot_ats(i)+.01)-log(et_ats(i)+.01))/ (2.*lvar_ats(i)) ; + } + else + { + // This is used (standard approach) Eq. 19, historically used normal distribution since year-by-year var_bts avail + // for (i=1;i<=n_bts_r;i// ++) + // surv_like(1) += square(ot_bts(i)-et_bts(i))/(2.*var_bts(i)); + //dvar_vector srv_tmp = log(ot_bts + 1e-8)-log(et_bts + 1e-8); + // Note not logged... + dvar_vector srv_tmp(1,n_bts_r); + // eb_bts *= q_bts; + // NOTE for VAST estimates the biomass is simply scaled + q_bts =mean(ob_bts)/mean(eb_bts); + eb_bts *= q_bts; + if (do_bts_bio) + srv_tmp = (ob_bts) - (eb_bts ); + else + srv_tmp = (ot_bts )-(et_bts ); + switch (DoCovBTS) + { + case 0: // normal design-based estimates (no Covariance) + if (do_bts_bio) + { + srv_tmp = log(ob_bts) - log(eb_bts ); + for (i=1;i<=n_bts_r;i++) + surv_like(1) += square(srv_tmp(i))/(2.*var_ob_bts(i)); + } + case 1: + surv_like(1) = .5 * srv_tmp * inv_bts_cov * srv_tmp; + break; + case 2: // Test gen gamma + if (do_bts_bio) + { + for (i=1;i<=n_bts_r;i++) + if (sd_GenGam(i)>0) + surv_like(1) += dgengamma(ob_bts(i), eb_bts(i), sd_GenGam(i), q_GenGam(i)); + else{ + surv_like(1) += square(log(ob_bts(i))- log(eb_bts(i)))/ (2*var_ob_bts(i)); + } + } + break; + case 3: // lognormal + if (do_bts_bio) + { + // Need to fix up variance for this option... + srv_tmp = log(ob_bts) - log(eb_bts ); + } + break; + } + } + /* else + { + if (do_bts_bio) + { + for (i=1;i<=n_bts_r;i++) + surv_like(1) += square(srv_tmp(i))/(2.*var_ob_bts(i)); + } + else + { + for (i=1;i<=n_bts_r;i++) + surv_like(1) += square(srv_tmp(i))/(2.*var_ot_bts(i)); + } + } + surv_like(1) *= ctrl_flag(5); + */ + // AT Biomass section + /* + */ + if (do_ats_bio) + { + for (i=1;i<=n_ats_r;i++) // Eq. 19 + surv_like(2) += square(log(ob_ats(i)+.01)-log(eb_ats(i)+.01))/ (2.*lvarb_ats(i)) ; + // #surv_like(2) += square(log(ob_ats(i)+.01)-log(eb_ats(i)+.01))/ (2.*var_ob_ats(i)) ; + } + else + { + for (i=1;i<=n_ats_r;i++) // Eq. 19 + surv_like(2) += square(log(ot_ats(i)+.01)-log(et_ats(i)+.01))/ (2.*lvar_ats(i)) ; + } + surv_like(2) *= ctrl_flag(2); + if (use_age1_ats) + { + // Compute q for this age1 index... + dvariable qtmp = mfexp(mean(log(oa1_ats)-log(ea1_ats))); + if (ignore_last_ats_age1) + surv_like(3) = 0.5*norm2(log(oa1_ats(1,n_ats_r-1)+.01)-log(ea1_ats(1,n_ats_r-1)*qtmp +.01))/(age1_sigma_ats*age1_sigma_ats) ; + else + surv_like(3) = 0.5*norm2(log(oa1_ats+.01)-log(ea1_ats*qtmp +.01))/(age1_sigma_ats*age1_sigma_ats) ; + } + avo_like.initialize(); + cpue_like.initialize(); + cope_like.initialize(); + dvar_vector cpue_dev = obs_cpue-pred_cpue; + for (i=1;i<=n_cpue;i++) + cpue_like += square(cpue_dev(i))/(2.*obs_cpue_var(i)); + dvar_vector avo_dev = obs_avo-pred_avo; + for (i=1;i<=n_avo_r;i++) + avo_like += square(avo_dev(i))/(2.*obs_avo_var(i)); + // if (phase_cope>0 & current_phase()>=phase_cope) + if (last_phase()) + { + if (phase_cope>0) + { + // Compute q for this age1 index... + int ntmp = n_cope - (yrs_cope(n_cope)+3-endyr_r); + dvariable qtmp = mfexp(mean(log(obs_cope(1,ntmp))-log(pred_cope(1,ntmp)))); + for (i=ntmp+1;i<=n_cope;i++) + pred_cope(i) = obs_cope(i)/qtmp; + pred_cope *= qtmp; + // dvar_vector cope_dev = obs_cope-pred_cope; + for (i=1;i<=n_cope;i++) + cope_like += square(log(obs_cope(i))-log(pred_cope(i)))/ (2.*lvar_cope(i)) ; + // cope_like += square(cope_dev(i))/(2.*square(obs_cope_std(i))); + } + } + /* // This is for projecting Nage_3 but left out for now + else + { + if (sd_phase()) + { + for (i=1;i<=n_cope;i++) + { + if (yrs_cope(i)>endyr_r) + Nage_3(i) = natage_future(3,yrs_cope(i),3); + else + Nage_3(i) = natage(yrs_cope(i),3); + } + } + } + */ + if (sd_phase()) + Nage_3 = column(natage,3); +} + +void model_parameters::Robust_Likelihood(void) +{ + ofstream& srecout= *pad_srecout; + ofstream& projout= *pad_projout; + ofstream& nofish= *pad_nofish; + ofstream& projout2= *pad_projout2; + ofstream& eval= *pad_eval; + random_number_generator& rng= *pad_rng; + age_like.initialize(); + len_like.initialize(); + // dvariable robust_p(const dmatrix& obs,const dvar_matrix& pred,const dvariable& a,const dvariable& b) + dvariable rf=.1/nages; + age_like(1) = robust_p(oac_fsh,eac_fsh,rf,sam_fsh); + age_like(2) = robust_p(oac_bts,eac_bts,rf,sam_bts); + if (current_phase() >= ats_robust_phase ) // ats robustness phase big number means do multinomial, not robust + age_like(3) = robust_p(oac_ats,eac_ats,rf,sam_ats,mina_ats,nages); + else // Multinomial for EIT + for (i=1; i <= nagecomp(3); i++) + age_like(3) -= sam_ats(i)*oac_ats(i)(mina_ats,nages) * log(eac_ats(i)(mina_ats,nages) + MN_const); + len_like = robust_p(olc_fsh,elc_fsh,rf,50); +} + +void model_parameters::Multinomial_Likelihood(void) +{ + ofstream& srecout= *pad_srecout; + ofstream& projout= *pad_projout; + ofstream& nofish= *pad_nofish; + ofstream& projout2= *pad_projout2; + ofstream& eval= *pad_eval; + random_number_generator& rng= *pad_rng; + age_like.initialize(); + len_like.initialize(); + //-Likelihood due to Age compositions-------------------------------- + for (int igear =1;igear<=ngears;igear++) + { + for (i=1; i <= nagecomp(igear); i++) + { + switch (igear) + { + case 1: + age_like(igear) -= sam_fsh(i)*oac_fsh(i)*log(eac_fsh(i) + MN_const); + break; + case 2: + age_like(igear) -= sam_bts(i)*oac_bts(i)*log(eac_bts(i) + MN_const); + break; + case 3: + age_like(igear) -= sam_ats(i)*oac_ats(i)(mina_ats,nages) * log(eac_ats(i)(mina_ats,nages) + MN_const); + break; + } + } + age_like(igear)-=age_like_offset(igear); + } + if (sd_phase() || mceval_phase()) // This to write out annual likelihood components + { + for (int igear =1;igear<=ngears;igear++) + { + for (i=1; i <= nagecomp(igear); i++) + { + switch (igear) + { + case 1: + age_like_yr(igear,i) -= sam_fsh(i)*oac_fsh(i)*log(eac_fsh(i) + MN_const); + break; + case 2: + age_like_yr(igear,i) -= sam_bts(i)*oac_bts(i)*log(eac_bts(i) + MN_const); + break; + default: + age_like_yr(igear,i) -= sam_ats(i)*oac_ats(i)(mina_ats,nages)*log(eac_ats(i)(mina_ats,nages) +MN_const); + break; + } + } + } + } + //len_like = sam_fsh(n_fsh_r)*olc_fsh*log(elc_fsh+MN_const); + len_like = -50*olc_fsh*log(elc_fsh+MN_const) - len_like_offset ; + // this one allows a concentrated range of ages (last two args are min and max age range) +} + +dvariable model_parameters::robust_p(dmatrix& obs,dvar_matrix& pred,const dvariable& a, const data_ivector& b, const int amin, const int amax) +{ + ofstream& srecout= *pad_srecout; + ofstream& projout= *pad_projout; + ofstream& nofish= *pad_nofish; + ofstream& projout2= *pad_projout2; + ofstream& eval= *pad_eval; + random_number_generator& rng= *pad_rng; + if (obs.indexmin() != pred.indexmin() || obs.indexmax() != pred.indexmax() ) + cerr << "Index limits on observed vector are not equal to the Index\n" + "limits on the predicted vector in robust_p function\n"; + RETURN_ARRAYS_INCREMENT(); //Need this statement because the function returns a variable type + dvar_matrix v(obs.indexmin(),obs.indexmax(),amin,amax); + // dvar_matrix l = elem_div(square(pred - obs), v); + dvariable log_likelihood = 0.; + for (i=obs.indexmin();i<= obs.indexmax() ;i++) + { + v(i) = a + 2. * elem_prod(obs(i)(amin,amax) ,1. - obs(i)(amin,amax)); + dvar_vector l = elem_div(square(pred(i)(amin,amax) - obs(i)(amin,amax)), v(i)); + log_likelihood -= sum(log(mfexp(-1.* double(b(i)) * l) + .01)); + } + log_likelihood += 0.5 * sum(log(v)); + RETURN_ARRAYS_DECREMENT(); // Need this to decrement the stack increment + return(log_likelihood); +} + +dvariable model_parameters::robust_p(const dmatrix& obs,const dvar_matrix& pred,const dvariable& a, const data_ivector& b) +{ + ofstream& srecout= *pad_srecout; + ofstream& projout= *pad_projout; + ofstream& nofish= *pad_nofish; + ofstream& projout2= *pad_projout2; + ofstream& eval= *pad_eval; + random_number_generator& rng= *pad_rng; + RETURN_ARRAYS_INCREMENT(); //Need this statement because the function returns a variable type + if (obs.indexmin() != pred.indexmin() || obs.indexmax() != pred.indexmax() ) + cerr << "Index limits on observed vector are not equal to the Index\n" + "limits on the predicted vector in robust_p function\n"; + // dvar_matrix v = a + 2. * elem_prod(pred ,1. - pred ); + dvar_matrix v = a + 2. * elem_prod(obs ,1. - obs ); + dvar_matrix l = elem_div(square(pred - obs), v); + dvariable log_likelihood = 0.; + for (i=obs.indexmin();i<= obs.indexmax() ;i++) + { + log_likelihood -= sum(log(mfexp(-1.* double(b(i)) * l(i)) + .01)); + } + log_likelihood += 0.5 * sum(log(v)); + RETURN_ARRAYS_DECREMENT(); // Need this to decrement the stack increment + return(log_likelihood); +} + +dvariable model_parameters::robust_p(const dmatrix& obs, const dvar_matrix& pred, const dvariable& a, const dvariable& b) +{ + ofstream& srecout= *pad_srecout; + ofstream& projout= *pad_projout; + ofstream& nofish= *pad_nofish; + ofstream& projout2= *pad_projout2; + ofstream& eval= *pad_eval; + random_number_generator& rng= *pad_rng; + RETURN_ARRAYS_INCREMENT(); //Need this statement because the function + if (obs.indexmin() != pred.indexmin() || obs.indexmax() != pred.indexmax() ) + cerr << "Index limits on observed vector are not equal to the Index\n" + "limits on the predicted vector in robust_p function\n"; + //returns a variable type + // dvar_matrix v = a + 2. * elem_prod(pred ,1. - pred ); + dvar_matrix v = a + 2. * elem_prod(obs ,1. - obs ); + dvar_matrix l = mfexp(- b * elem_div(square(pred - obs), v )); + dvariable log_likelihood = -1.0*sum(log(l + .01)); + log_likelihood += 0.5 * sum(log(v)); + RETURN_ARRAYS_DECREMENT(); // Need this to decrement the stack increment + return(log_likelihood); +} + +dvariable model_parameters::robust_p(const dvector& obs, const dvar_vector& pred, const dvariable& a, const dvariable& b) +{ + ofstream& srecout= *pad_srecout; + ofstream& projout= *pad_projout; + ofstream& nofish= *pad_nofish; + ofstream& projout2= *pad_projout2; + ofstream& eval= *pad_eval; + random_number_generator& rng= *pad_rng; + RETURN_ARRAYS_INCREMENT(); //Need this statement because the function + if (obs.indexmin() != pred.indexmin() || obs.indexmax() != pred.indexmax() ) + cerr << "Index limits on observed vector are not equal to the Index\n" + "limits on the predicted vector in robust_p function\n"; + //returns a variable type + // dvar_matrix v = a + 2. * elem_prod(pred ,1. - pred ); + dvar_vector v = a + 2. * elem_prod(obs ,1. - obs ); + dvar_vector l = mfexp(- b * elem_div(square(pred - obs), v )); + dvariable log_likelihood = -1.0*sum(log(l + .01)); + log_likelihood += 0.5 * sum(log(v)); + RETURN_ARRAYS_DECREMENT(); // Need this to decrement the stack increment + return(log_likelihood); +} + +void model_parameters::write_srec(void) +{ + ofstream& srecout= *pad_srecout; + ofstream& projout= *pad_projout; + ofstream& nofish= *pad_nofish; + ofstream& projout2= *pad_projout2; + ofstream& eval= *pad_eval; + random_number_generator& rng= *pad_rng; + srecout << "Yearclass SSB Recruit Pred_Rec Residual"<0) + SimulateData1(); + else + { + // if (!pflag) + /* + for (int k=1;k<=nscen;k++) + { + write_mceval(future_SSB(k)); + write_mceval(future_catch(k)); + } + write_mceval(Fcur_Fmsy); + write_mceval(Bcur_Bmsy); + write_mceval(Bcur_Bmean); + write_mceval(Bcur2_Bmsy); + write_mceval(Bcur2_B20); + write_mceval(Bcur3_Bcur); + write_mceval(Bcur3_Bmean); + write_mceval(LTA1_5R); + write_mceval(LTA1_5); + write_mceval(MatAgeDiv1); + write_mceval(MatAgeDiv2); + write_mceval(RelEffort); + write_mceval <>catchtmp; + catchin.close(); + simdat << catchtmp <=1;iyr--) + { + sel_fut = sel_fsh(endyr_r-iyr+1); + sel_fut /= mean(sel_fut); // NORMALIZE TO mean + report<=1;iyr--) + { + wt_fut(3,nages) = wt_pre(endyr_wt-iyr+1); + report< age1tmp) report << age1tmp-1 << " " < age1tmp) report << age1tmp-1 << " " < age1tmp) report << age1tmp-1 << " " < age1tmp) report << age1tmp-1 << " " < age1tmp) report << age1tmp-1 << " " < age1tmp) report << age1tmp-1 << " " < age1tmp) report << age1tmp-1 << " " <int(1) ) + wt_hat(h,i) = elem_prod(d_scale(h-1) , wt_pre(iyr) ); + else + wt_hat(h,i) = wt_pre(iyr); + for (int j=age_st;j<=age_end;j++) + { + wt_like += square(wt_obs(h,i,j) - mnwt(j)) /(2.*square(sd_obs(h,i,j))); + wt_like += square(wt_obs(h,i,j) - wt_hat(h,i,j))/(2.*square(sd_obs(h,i,j))); + } + } + } + wt_like += 0.5*norm2(coh_eff); + wt_like += 0.5*norm2( yr_eff); + fff += wt_like; + wt_last = wt_pre(endyr_wt-3); //*exp(sigma_coh*sigma_coh/2. + sigma_yr*sigma_yr/2.);; + wt_cur = wt_pre(endyr_wt-2); //*exp(sigma_coh*sigma_coh/2. + sigma_yr*sigma_yr/2.);; + wt_next = wt_pre(endyr_wt-1); //*exp(sigma_coh*sigma_coh/2. + sigma_yr*sigma_yr/2.);; + wt_yraf = wt_pre(endyr_wt); //*exp(sigma_coh*sigma_coh/2. + sigma_yr*sigma_yr/2.);; + // wt_last = wt_pre(endyr_r-1); //*exp(sigma_coh*sigma_coh/2. + sigma_yr*sigma_yr/2.);; + // wt_cur = wt_pre(endyr_r ); //*exp(sigma_coh*sigma_coh/2. + sigma_yr*sigma_yr/2.);; + // wt_next = wt_pre(endyr_r+1); //*exp(sigma_coh*sigma_coh/2. + sigma_yr*sigma_yr/2.);; + // wt_yraf = wt_pre(endyr_r+2); //*exp(sigma_coh*sigma_coh/2. + sigma_yr*sigma_yr/2.);; + // Condition on using this based on wt flag + if (wt_fut_phase>0) + { + // Use cohort and year effects fits for current year catch + pred_catch(endyr_r) = catage(endyr_r)(3,nages) * wt_cur; + // Set future catch equal to estimate from model + // Only model wts-at-age from 3+ so this is the 1's and 2's + pred_catch(endyr_r) = catage(endyr_r)(1,2) * wt_fsh(endyr_r)(1,2); + // wt_fut = wt_fsh(endyr_r); // initializes estimates to correct values...Eq. 21 + wt_fut(3,nages) = wt_next; // initializes estimates to correct values...Eq. 21 + } +} + +dvariable model_parameters::dgengamma(const double& x, dvariable mean2, const double& sigma, const double& Q) +{ + ofstream& srecout= *pad_srecout; + ofstream& projout= *pad_projout; + ofstream& nofish= *pad_nofish; + ofstream& projout2= *pad_projout2; + ofstream& eval= *pad_eval; + random_number_generator& rng= *pad_rng; + // returns negative log-likelihood of generalized gamma distribution + RETURN_ARRAYS_INCREMENT(); + double k = pow( Q, -2 ); + double Beta = pow( sigma, -1 ) * Q; + dvariable log_theta = log(mean2) - lgamma( (k*Beta+1)/Beta ) + lgamma( k ); + dvariable mu = log_theta + log(k) / Beta; + dvariable w = (log(x) - mu) / sigma; + double abs_q = sqrt(Q*Q); // = abs(Q); not differentiable! + double qi = 1/square(Q); + dvariable qw = Q*w; + dvariable logres = -log(sigma*x) + log(abs_q) * (1. - 2. * qi) + qi * + (qw - exp(qw)) - lgamma(qi); + RETURN_ARRAYS_DECREMENT(); + return(-logres); +} + +double model_parameters::sdnr(const dvector& obs, const dvar_vector& pred, const dvector& sig) +{ + ofstream& srecout= *pad_srecout; + ofstream& projout= *pad_projout; + ofstream& nofish= *pad_nofish; + ofstream& projout2= *pad_projout2; + ofstream& eval= *pad_eval; + random_number_generator& rng= *pad_rng; + RETURN_ARRAYS_INCREMENT(); + double sdnr; + sdnr = std_dev(elem_div((obs-value(pred)),sig)); + RETURN_ARRAYS_DECREMENT(); + return sdnr; + /* ****************************************************** + FUNCTION dvariable Check_Parm(const double& Pmin, const double& Pmax, const double& jitter, const prevariable& Pval) + { + dvariable NewVal; + dvariable temp; + NewVal=Pval; + if(PvalPmax) + {N_warn++; warning<<" parameter init value is greater than parameter max "< "<0.0) + { + temp=log((Pmax-Pmin+0.0000002)/(NewVal-Pmin+0.0000001)-1.)/(-2.); // transform the parameter + temp += randn(radm) * jitter; + NewVal=Pmin+(Pmax-Pmin)/(1.+mfexp(-2.*temp)); + } + return NewVal; + } + */ + /** + * @brief Calculate sdnr and MAR + **/ + /** + FUNCTION void get_all_sdnr_MAR() + { + for ( int k = 1; k <= nSurveys; k++ ) + { + dvector stdtmp = cpue_sd(k) * 1.0 / cpue_lambda(k); + dvar_vector restmp = elem_div(log(elem_div(obs_cpue(k), pre_cpue(k))), stdtmp) + 0.5 * stdtmp; + sdnr_MAR_cpue(k) = calc_sdnr_MAR(value(restmp)); + } + for ( int k = 1; k <= nSizeComps; k++ ) + { + //dvector sdtmp = cpue_sd(k) * 1.0 / cpue_lambda(i); + sdnr_MAR_lf(k) = calc_sdnr_MAR(value(d3_res_size_comps(k))); + } + Francis_weights = calc_Francis_weights(); + } + FUNCTION dvector calc_sdnr_MAR(dvector tmpVec) + { + dvector out(1,2); + dvector tmp = fabs(tmpVec); + dvector w = sort(tmp); + out(1) = std_dev(tmpVec); // sdnr + out(2) = w(floor(0.5*(size_count(w)+1))); // MAR + return out; + } + FUNCTION dvector calc_sdnr_MAR(dmatrix tmpMat) + { + dvector tmpVec(1,size_count(tmpMat)); + dvector out(1,2); + int dmin,dmax; + dmin = 1; + for ( int ii = tmpMat.indexmin(); ii <= tmpMat.indexmax(); ii++ ) + { + dmax = dmin + size_count(tmpMat(ii)) - 1; + tmpVec(dmin,dmax) = tmpMat(ii).shift(dmin); + dmin = dmax + 1; + } + dvector tmp = fabs(tmpVec); + dvector w = sort(tmp); + out(1) = std_dev(tmpVec); // sdnr + out(2) = w(floor(0.5*(size_count(w)+1))); // MAR + return out; + } + **/ +} + +dvector model_parameters::rmultinomial(const dvector ptmp, const int n_sam) +{ + ofstream& srecout= *pad_srecout; + ofstream& projout= *pad_projout; + ofstream& nofish= *pad_nofish; + ofstream& projout2= *pad_projout2; + ofstream& eval= *pad_eval; + random_number_generator& rng= *pad_rng; + int i1=ptmp.indexmin(); + int i2=ptmp.indexmax(); + dvector freq(i1,i2); + dvector p(i1,i2); + ivector bin(1,n_sam); + p = ptmp; + p /= sum(p); + bin.fill_multinomial(rng,p); // fill a vector v + for (int j=1;j<=n_sam;j++) + freq(bin(j))++; + // Apply ageing error to samples.............. + return( freq/sum(freq) ); + /** + * @brief Calculate Francis weights + * @details this code based on equation TA1.8 in Francis(2011) should be changed so separate weights if by sex + * + * Produces the new weight that should be used. + **/ +} + +double model_parameters::calc_Francis_weights(const dmatrix oac, const dvar_matrix eac, const ivector sam ) +{ + ofstream& srecout= *pad_srecout; + ofstream& projout= *pad_projout; + ofstream& nofish= *pad_nofish; + ofstream& projout2= *pad_projout2; + ofstream& eval= *pad_eval; + random_number_generator& rng= *pad_rng; + { + int nobs; + int i1=oac.rowmin(); + int i2=oac.rowmax(); + double lfwt,Var,Pre,Obs; + dvector ages(oac.colmin(),nages); + for (int i=oac.colmin();i<=nages;i++) + ages(i) = double(i)+.5; + nobs = oac.rowsize(); + dvector resid(i1,i2); + resid.initialize(); + for ( int i = i1; i <= i2; i++ ) + { + // Obs = sum(elem_prod(oac(i), ages+.5)); + Obs = oac(i) * (ages+.5); + // Pre = sum(elem_prod(value(eac(i)), ages+.5)); + Pre = value(eac(i)) * (ages+.5); + Var = value(eac(i)) * square(ages+.5); + Var -= square(Pre); + resid(i) = (Obs - Pre) / sqrt(Var * 1.0 / (sam(i) )); + // cout<<"FW "<0) + SimulateData1(); + //cout<< "Estimated and SR-predicted recruits"<0) + report<< -dgengamma(ob_bts(i), eb_bts(i), sd_GenGam(i), q_GenGam(i))<(std::chrono::high_resolution_clock::now() - start).count() << " microseconds." << endl; + #ifndef __SUNPRO_C +bool failedtest = false; +if (std::fetestexcept(FE_DIVBYZERO)) + { cerr << "Error: Detected division by zero." << endl; failedtest = true; } +if (std::fetestexcept(FE_INVALID)) + { cerr << "Error: Detected invalid argument." << endl; failedtest = true; } +if (std::fetestexcept(FE_OVERFLOW)) + { cerr << "Error: Detected overflow." << endl; failedtest = true; } +if (std::fetestexcept(FE_UNDERFLOW)) + { cerr << "Error: Detected underflow." << endl; } +if (failedtest) { std::abort(); } + #endif +#endif + return 0; +} + +extern "C" { + void ad_boundf(int i) + { + /* so we can stop here */ + exit(i); + } +} diff --git a/2024/runs/om/pm.dat b/2024/runs/om/pm.dat new file mode 100644 index 0000000..44194f0 --- /dev/null +++ b/2024/runs/om/pm.dat @@ -0,0 +1,10 @@ +UseVAST_AGE_Hulson_ISS +../data/pm_23.8.dat +selvar.dat +control.dat +../data/pm_fmsy_alt.dat +cov_2023.dat +../data/wtage2023.dat +../data/surveycpue.dat +paul.dat +q_bts.dat diff --git a/2024/runs/om/pm.prj b/2024/runs/om/pm.prj new file mode 100644 index 0000000..e69de29 diff --git a/2024/runs/om/pm.tpl b/2024/runs/om/pm.tpl new file mode 120000 index 0000000..39cfc5c --- /dev/null +++ b/2024/runs/om/pm.tpl @@ -0,0 +1 @@ +../../../source/pm.tpl \ No newline at end of file diff --git a/2024/runs/om/pmsr.prj b/2024/runs/om/pmsr.prj new file mode 100644 index 0000000..e69de29 diff --git a/2024/runs/om/proj_df.csv b/2024/runs/om/proj_df.csv new file mode 100644 index 0000000..e69de29 diff --git a/2024/runs/om/q_bts.dat b/2024/runs/om/q_bts.dat new file mode 100644 index 0000000..2174aaf --- /dev/null +++ b/2024/runs/om/q_bts.dat @@ -0,0 +1,90 @@ +0.041397652 0.077967026 +-0.094271973 0.078807226 +0.107965203 0.078066357 +-0.072817665 0.077618805 +-3.32E-05 0 +-0.038860327 0.076888528 +-0.071983726 0.082532835 +0.055991447 0.080706478 +0.11997011 0.078684999 +-0.191838448 0.080249641 +-0.156793526 0.08447422 +-0.177803761 0.080490335 +-0.176536673 0.071562538 +0.129924716 0.082151562 +-0.027261169 0.074211538 +0.019924552 0.081143175 +0.019693939 0.073173216 +-0.07320967 0.077718778 +-0.025593308 0.07715557 +-0.193470006 0.079682886 +-0.123080768 0.076362844 +-0.231694252 0.094436353 +-0.076054169 0.0777744 +-0.072979419 0.080032809 +-0.120656817 0.082713774 +0.084734374 0.080998039 +-0.142072447 0.080313203 +-0.057769374 0.082250193 +-0.16996559 0.07626651 +-0.092711238 0.079451486 +-0.331641159 0.075984527 +-0.143078144 0.078877398 +-6.38E-05 0 +-0.162151725 0.07412531 +-0.124765443 0.07835984 +-0.100170464 0.077502704 +-0.052547387 0.08275179 +-0.134603539 0.078154903 +-0.233847782 0.076118822 +-0.13951359 0.077734856 +-0.13951359 0.077734856 +-0.13951359 0.077734856 +-0.13951359 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0.573715 0.689782 0.756873 0.841316 1.01066 1.12981 1.15975 1.26933 1.2145 1.40474 1.56049 + 0.0251823 0.186222 0.440141 0.50607 0.573913 0.724034 0.837484 0.883259 0.983697 0.972326 1.27147 1.04423 1.23453 0.910308 1.56049 + 0.0251823 0.186222 0.393757 0.548346 0.626292 0.731937 0.841516 0.910812 0.997666 1.12591 1.14196 1.17162 1.25531 1.33259 1.4725 + 0.0251823 0.186222 0.382396 0.514465 0.713513 0.783949 0.851316 0.960344 1.05614 1.10786 1.17923 1.29141 1.29349 1.30849 1.37907 +obs_effort + 0 0 5 6 3 8 5 0 0 3 8 4 2 5 0 0 3 5 3 6 2 0 0 6 7 9 4 6 0 0 6 2 6 9 5 0 0 6 0 3 3 5 1 0 0 3 8 4 8 1 0 5 5 6 9 3 1 0 5 3 6 +n_cpue +5 +obs_cpue + 4 3 1 0 5 +obs_cpue_std + 7 2 6 6 1 +n_avo +0 +yrs_avo + +obs_avo + +wt_avo + +ngears +4 +minind + 9 0 9 2 +n_bts +0 +yrs_fsh_data + 8 +yrs_bts_data + +yrs_ats_data + 0 2 +sam_fsh + 4 +sam_bts + +sam_ats + 1 0 +err_fsh + 5 +err_bts + +err_ats + 2 6 +oac_fsh_data + 9 5 1 0 5 2 1 9 5 1 0 5 1 9 5 +yrs_bts_data + +yrs_ats_data + 0 2 +obs_bts_data + +std_ob_bts_data + +wt_bts + +std_ot_bts + +oac_bts_data + +std_ot_ats + +oac_ats_data + 0 4 8 5 3 7 1 0 4 8 5 3 7 1 0 + 4 8 5 3 7 1 0 4 8 5 3 7 1 0 4 +std_ot_ats + 2 1 +obs_ats_data + 8 5 +std_ob_ats_data + 3 7 +wt_ats + 1 0 4 8 5 3 7 1 0 4 8 5 3 7 1 + 0 4 8 5 3 7 1 0 4 8 5 3 7 1 0 +bottom_temp + +n_age_err +4 +age_err + 8 5 3 7 1 0 4 8 5 3 7 1 0 4 8 + 5 3 7 1 0 4 8 5 3 7 1 0 4 8 5 + 3 7 1 0 4 8 5 3 7 1 0 4 8 5 3 + 7 1 0 4 8 5 3 7 1 0 4 8 5 3 7 + 1 0 4 8 5 3 7 1 0 4 8 5 3 7 1 + 0 4 8 5 3 7 1 0 4 8 5 3 7 1 0 + 4 8 5 3 7 1 0 5 1 0 5 1 0 5 1 + 0 5 1 0 5 1 0 5 1 0 5 1 0 5 1 + 0 5 1 0 5 1 0 5 1 0 5 1 0 5 1 + 0 5 1 0 5 1 0 5 1 0 5 1 0 5 1 + 0 5 1 0 5 1 0 4 1 0 4 1 2 1 9 + 6 5 1 9 6 6 1 9 6 7 1 9 6 8 1 + 9 6 9 1 9 7 0 1 9 7 1 1 9 7 2 + 1 9 7 3 1 9 7 4 1 9 7 5 1 9 7 + 6 2 8 1 6 0 4 4 3 4 7 3 0 5 8 + 3 8 0 2 0 1 7 5 2 5 7 0 3 6 7 + 1 2 0 4 7 5 6 7 9 0 8 1 5 2 5 + 7 0 3 3 5 7 2 6 0 7 4 4 7 8 7 + 0 9 2 4 7 4 0 0 9 9 4 2 7 1 0 + 5 7 4 3 1 8 0 5 2 5 6 3 0 2 8 + 7 6 9 4 0 7 1 6 7 6 0 0 4 3 4 + 1 0 5 1 0 4 6 1 3 4 2 0 4 9 1 + 1 3 5 0 9 6 1 0 5 1 0 4 7 1 1 + 4 5 0 3 5 9 5 7 0 5 8 5 9 4 8 + 0 1 9 9 8 5 4 0 3 1 5 8 6 3 0 + 7 0 5 1 7 2 0 0 6 2 0 0 7 2 0 + 0 8 2 0 0 9 2 0 1 0 2 0 1 1 2 + 0 1 2 2 0 1 3 2 0 1 4 2 0 1 5 + 2 0 1 6 2 0 1 7 2 0 1 8 2 0 1 + 9 2 0 2 1 2 0 2 2 2 0 2 3 1 0 + 7 4 1 4 8 2 0 0 0 1 9 1 0 0 9 + 9 1 5 4 3 0 0 6 9 5 1 1 0 9 2 + 1 8 1 0 7 0 3 8 2 1 0 5 2 0 6 + 2 0 1 7 7 6 3 3 0 0 7 6 9 3 0 + 5 9 2 7 2 0 8 3 1 9 2 0 2 6 3 + 2 0 0 8 4 1 2 0 8 2 9 2 2 0 4 + 1 0 1 2 0 9 0 3 1 2 0 4 8 1 0 + 0 4 0 7 9 7 4 0 0 7 9 5 4 3 8 + 0 0 2 9 2 8 6 5 0 0 3 9 0 0 9 + 6 0 0 5 7 9 1 9 3 0 0 4 4 7 6 + 7 8 0 0 3 7 1 9 3 8 0 0 3 9 0 + 1 1 6 0 0 5 8 0 2 4 6 0 0 4 0 + 6 2 5 7 0 0 3 7 9 0 9 3 0 0 3 + 1 7 3 8 9 0 0 2 5 4 9 6 1 0 0 + 6 3 5 3 9 5 0 0 5 2 9 9 2 9 0 + 0 4 5 4 7 8 0 0 3 3 5 3 4 9 0 + 0 0 1 9 3 8 0 8 0 0 1 0 1 4 6 + 0 0 2 4 4 1 4 5 0 0 3 7 8 1 4 + 6 0 0 5 2 6 9 9 2 0 0 6 5 2 0 + 6 7 0 0 7 6 3 6 0 4 0 0 8 4 6 + 6 6 8 0 0 9 3 3 5 2 0 0 9 7 1 + 4 3 7 1 0 0 0 1 1 5 1 0 1 4 9 + 5 3 1 0 2 1 1 6 9 1 0 2 8 1 0 + 5 1 0 1 7 9 9 2 0 0 0 1 8 4 9 + 5 6 0 0 0 8 7 1 9 3 4 0 0 2 7 + 9 2 4 7 0 0 4 3 7 1 8 8 0 0 5 + 8 2 4 8 9 0 0 6 8 6 6 3 2 0 0 + 7 8 8 2 3 6 0 0 8 7 1 0 0 9 7 + 0 1 1 0 1 0 2 7 1 1 0 1 0 5 6 + 7 1 0 2 3 6 9 5 1 0 2 3 5 4 9 +nlbins +1 +olc_fsh + 0 +lens + 20 +test +0 diff --git a/2024/runs/separable/Makefile b/2024/runs/separable/Makefile new file mode 100644 index 0000000..d9fddf1 --- /dev/null +++ b/2024/runs/separable/Makefile @@ -0,0 +1,59 @@ +EXEC = pm +PROJ = spm + PROJDIST = ~/_mymods/afsc-assessments/spmR/src/ +ifeq ($(SAFE),TRUE) + DIST = ../../../source/ +else + DIST = ../../../source/ +endif +ARGS = -nox -iprint 150 +ARGS2 = -nox -iprint 150 -binp pm.bar -phase 22 -sdonly + +ifdef ComSpec + RM=del /F /Q +else + RM=rm -rf +endif + +all: mpd $(DIST)$(EXEC).tpl +$(EXEC): $(DIST)$(EXEC).tpl + ln -sf $(DIST)$(EXEC) $@ + ln -sf $(DIST)$(EXEC).tpl $@.tpl + ln -sf $(PROJDIST)$(PROJ) $(PROJ) + +$(DIST)$(EXEC).tpl: + $(MAKE) --directory=../../src + + +mpd: $(EXEC) + ./$(EXEC) $(ARGS) + @$(RM) $(EXEC).*[0123456789] *.rpt *.log variance gradient.* *tmp admodel.* *.eva + +mcmc: $(EXEC) + ./$(EXEC) $(ARGS) -mcmc 3000000 -mcsave 600 + ./$(EXEC) -mceval + +proj: $(EXEC) + ./$(EXEC) $(ARGS2) + $(MAKE) --directory=proj + +debug: $(EXEC) + ./$(EXEC) $(ARGS) + +plot: + R CMD BATCH plot.R + +clean: + @$(RM) $(EXEC) + @$(RM) $(EXEC) $(EXEC).[brces]* $(EXEC).*[0123456789] *.rpt *.log variance gradient.* *tmp + @$(RM) admodel.* + @$(RM) checkfile.rep + @$(RM) mcout.rep + @$(RM) plot.Rout + @$(RM) Rplots.pdf + @$(RM) *.rep + @$(RM) Fprof.yld + @$(RM) *.prj + @$(RM) pm.par + @$(RM) SIS_out.rep + @$(RM) mceval.dat diff --git a/2024/runs/separable/README.md b/2024/runs/separable/README.md new file mode 100644 index 0000000..c42021b --- /dev/null +++ b/2024/runs/separable/README.md @@ -0,0 +1,2 @@ +#Simple directory containing the bare minimum files to start a run using pm(.tpl) + diff --git a/2024/runs/separable/compweights.ctl b/2024/runs/separable/compweights.ctl new file mode 100644 index 0000000..cf8edad --- /dev/null +++ b/2024/runs/separable/compweights.ctl @@ -0,0 +1 @@ +1.0 1.0 1.0 1.0 \ No newline at end of file diff --git a/2024/runs/separable/control.dat b/2024/runs/separable/control.dat new file mode 100644 index 0000000..fac87eb --- /dev/null +++ b/2024/runs/separable/control.dat @@ -0,0 +1,175 @@ +#DoCovBTS +1 +#SrType +1 +#Do_Combined +0 +#use_age_err +0 +#use_age1_ats +1 +#age1_sigma_ats +1 +#use_endyr_len +0 +#use_popwts_ssb +1 +#natmortprior +0.3 +#cvnatmortprior +0.1 +#natmort_in +0.9 +0.45 +0.3 +0.3 +0.3 +0.3 +0.3 +0.3 +0.3 +0.3 +0.3 +0.3 +0.3 +0.3 +0.3 +#q_all_prior +0 +#q_all_sigma +2 +#q_bts_prior +0 +#q_bts_sigma +2 +#sigrprior +1 +#cvsigrprior +0.2 +#phase_sigr +-6 +#steepnessprior +0.6 +#cvsteepnessprior +0.12 +#phase_steepness +5 +#use_spr_msy_pen +0 +#sigma_spr_msy +0.20 +#use_last_ats_ac +1 +#nyrs_sel_avg +2 +#do_bts_bio +1 +#do_ats_bio +1 +#srprior_a +14.93209877 +#srprior_b +14.93209877 +#nyrs_future +5 +#next_yrs_catch +1350 +#nscen +8 +#fixed_catch_fut2 +1400 +#fixed_catch_fut3 +1200 +#phase_F40 +6 +#robust_phase +1350 +#ats_robust_phase +1350 +#ats_like_type +0 +#phase_logist_fsh +-1 +#phase_logist_bts +2 +#phase_seldevs_fsh +4 +#phase_seldevs_bts +5 +#phase_age1devs_bts +3 +#phase_selcoffs_ats +3 +#phase_sel_ats_dev +5 +#phase_natmort +-6 +#phase_q_bts +3 +#phase_q_std_area +-4 +#phase_q_ats +4 +#phase_bt +-6 +#phase_rec_devs +3 +#phase_larv +-3 +#phase_sr +5 +#wt_fut_phase +6 +#last_age_sel_fsh +4 +#last_age_sel_bts +8 +#last_age_sel_ats +8 +#ctrl_flag +200 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +1 +12.5 +1 +1 +1 +1 +1 +1 +3.125 +5 +1 +5 +1 +1 +2 +0 +0 +2 +1 +#sel_dev_shift +0 +#phase_coheff +1 +#phase_yreff +1 +#switch_temp_rec +0 +#phase_temp_rec +6 +#switch_pred_mort +0 +#phase_pred_mort +1 +#switch_mspp_func_resp +1 diff --git a/2024/runs/separable/pm b/2024/runs/separable/pm new file mode 120000 index 0000000..1a623d5 --- /dev/null +++ b/2024/runs/separable/pm @@ -0,0 +1 @@ +../../../source/pm \ No newline at end of file diff --git a/2024/runs/separable/pm.dat b/2024/runs/separable/pm.dat new file mode 100644 index 0000000..50623c8 --- /dev/null +++ b/2024/runs/separable/pm.dat @@ -0,0 +1,10 @@ +UseVAST_AGE_Hulson_ISS +../data/pm_23.8.dat +../data/selvar_separable.dat +control.dat +../data/pm_fmsy_alt.dat +../data/cov_2023.dat +../data/wtage2023.dat +../data/surveycpue.dat +../data/temp_paul23.dat +../data/q_bts.dat diff --git a/2024/runs/separable/pm.prj b/2024/runs/separable/pm.prj new file mode 100644 index 0000000..eacd316 --- /dev/null +++ b/2024/runs/separable/pm.prj @@ -0,0 +1,29 @@ +EBS_Pollock_2023 +1 # SSLn species... +0 # Buffer of Dorn +1 # Number of fsheries +1 # Number of sexes +0.313712 # averagei 5yr f + 1 # author f + 0.4 # ABC SPR + 0.35 # MSY/OFL SPR + 4 # Spawnmo +15 # Number of ages + 1 # Fratio + 0.9 0.45 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 # Natural Mortality +# Maturity + 0 0.008 0.289 0.641 0.842 0.901 0.947 0.963 0.97 1 1 1 1 1 1 +# Wt spawn + 0.0848817 0.195868 0.319566 0.490613 0.604994 0.738365 0.851658 0.960207 1.03066 1.10148 1.21865 1.26473 1.30452 1.35788 1.43261 +# Wt fsh + 0.0251823 0.186222 0.382396 0.514465 0.713513 0.783949 0.851316 0.960344 1.05614 1.10786 1.17923 1.29141 1.29349 1.30849 1.37907 +# selectivity + 0.000148346 0.0131239 0.117286 0.424644 0.871257 1.33463 1.49571 1.49429 1.4298 1.36489 1.31909 1.28378 1.28378 1.28378 1.28378 +# natage + 24110.6 9849.16 9345.96 7587.49 5730.49 9627.74 523.466 126.016 60.643 95.23 148.373 82.7569 9.80727 5.54764 13.3708 +# Nrec +45 +# rec + 24208.1 59690.7 24740.3 31341.2 17335.6 50118.5 13183.3 33485 12112.8 6798.06 4909.71 10206.9 53401.6 27055.7 20478.7 42574.4 13352.1 9080.91 21739.6 32457.2 14623.2 15372.2 23885.2 35148.3 23056.2 14443.1 6559.43 4529.46 11866.4 27755.7 11355.7 46368.3 20244.5 11778.6 11012.3 49588.3 47661.7 16105.9 5145.08 5207.03 11039.5 114434 43527.2 40181.8 36111.2 24225.5 +# SpawningBiomass + 953.507 832.52 804.048 1049.01 1713.21 2402.71 3195.92 3280.05 3759.35 3670.72 3727.57 3545.29 3070.76 2584.54 2050.19 1976.66 2693.47 3178.16 3370.08 3254.31 3076.32 2559.68 2687.81 2641.07 2720.96 2535.8 2575.53 2878.85 2556.71 2354.73 1928.52 1474.77 1602.92 1661.47 2011.28 2354.89 2577.42 2459.34 2374.86 2737.02 3201.28 2943.57 2683.66 1894.74 2396.31 4116.76 diff --git a/2024/runs/separable/pm.tpl b/2024/runs/separable/pm.tpl new file mode 120000 index 0000000..39cfc5c --- /dev/null +++ b/2024/runs/separable/pm.tpl @@ -0,0 +1 @@ +../../../source/pm.tpl \ No newline at end of file diff --git a/2024/runs/separable/pmsr.prj b/2024/runs/separable/pmsr.prj new file mode 100644 index 0000000..98409f3 --- /dev/null +++ b/2024/runs/separable/pmsr.prj @@ -0,0 +1,41 @@ +EBS_Pollock +# Number of fsheries +1 +# Const Popln? +0 +# Recent TAC +1260 +# reserved +0 +# TAC Split +1 1 +# ABC Adjustment +1 +# Spawnmonth +4 +# NumberAges +15 + 1 # Fratio + 0.9 0.45 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 # Natural Mortality +# Maturity + 0 0.008 0.289 0.641 0.842 0.901 0.947 0.963 0.97 1 1 1 1 1 1 +# Wt spawn + 0.0848817 0.195868 0.319566 0.490613 0.604994 0.738365 0.851658 0.960207 1.03066 1.10148 1.21865 1.26473 1.30452 1.35788 1.43261 +# Wt fsh + 0.0251823 0.186222 0.382396 0.514465 0.713513 0.783949 0.851316 0.960344 1.05614 1.10786 1.17923 1.29141 1.29349 1.30849 1.37907 +# Wt fsh + 0.0251823 0.186222 0.382396 0.514465 0.713513 0.783949 0.851316 0.960344 1.05614 1.10786 1.17923 1.29141 1.29349 1.30849 1.37907 +# selectivity + 0.000148346 0.0131239 0.117286 0.424644 0.871257 1.33463 1.49571 1.49429 1.4298 1.36489 1.31909 1.28378 1.28378 1.28378 1.28378 +# selectivity + 0.000148346 0.0131239 0.117286 0.424644 0.871257 1.33463 1.49571 1.49429 1.4298 1.36489 1.31909 1.28378 1.28378 1.28378 1.28378 +# natage + 24225.5 14681.3 10392.6 8154.99 14483.9 834.231 204.893 98.5838 153.573 237.349 131.632 15.531 8.78536 8.01751 13.1568 +# natage + 24225.5 14681.3 10392.6 8154.99 14483.9 834.231 204.893 98.5838 153.573 237.349 131.632 15.531 8.78536 8.01751 13.1568 +# Nrec +46 +# rec + 24208.1 59690.7 24740.3 31341.2 17335.6 50118.5 13183.3 33485 12112.8 6798.06 4909.71 10206.9 53401.6 27055.7 20478.7 42574.4 13352.1 9080.91 21739.6 32457.2 14623.2 15372.2 23885.2 35148.3 23056.2 14443.1 6559.43 4529.46 11866.4 27755.7 11355.7 46368.3 20244.5 11778.6 11012.3 49588.3 47661.7 16105.9 5145.08 5207.03 11039.5 114434 43527.2 40181.8 36111.2 24225.5 +# SpawningBiomass + 953.507 832.52 804.048 1049.01 1713.21 2402.71 3195.92 3280.05 3759.35 3670.72 3727.57 3545.29 3070.76 2584.54 2050.19 1976.66 2693.47 3178.16 3370.08 3254.31 3076.32 2559.68 2687.81 2641.07 2720.96 2535.8 2575.53 2878.85 2556.71 2354.73 1928.52 1474.77 1602.92 1661.47 2011.28 2354.89 2577.42 2459.34 2374.86 2737.02 3201.28 2943.57 2683.66 1894.74 2396.31 4116.76 diff --git a/2024/runs/separable/proj_df.csv b/2024/runs/separable/proj_df.csv new file mode 100644 index 0000000..383bf5d --- /dev/null +++ b/2024/runs/separable/proj_df.csv @@ -0,0 +1,41 @@ +Scenario, Year, SSB, Catch, R, SER +1,2024,6171.38,1260,24110.6,0.0750949 +1,2025,6291.83,1362.24,22017.6,0.0845018 +1,2026,6006.82,1329.42,21573.6,0.0884319 +1,2027,5556.5,1226.7,22624.9,0.0890746 +1,2028,5134.37,1115.58,24277.4,0.0872084 +2,2024,6219.82,850,24110.6,0.0507266 +2,2025,6513.15,947.974,21838.9,0.0576652 +2,2026,6375.74,951.253,20761.4,0.0608331 +2,2027,6022.46,897.895,21265,0.0617677 +2,2028,5648.89,830.484,22567.2,0.0610786 +3,2024,6202.23,1000,24110.6,0.0596496 +3,2025,6431.86,1102.74,21903.8,0.0675586 +3,2026,6238.68,1095.35,21059,0.0710643 +3,2027,5847.48,1025.28,21769.4,0.0719506 +3,2028,5453.62,942.303,23212.4,0.0708961 +4,2024,6184.49,1150,24110.6,0.0685637 +4,2025,6350.94,1253.8,21969.2,0.0773655 +4,2026,6104.04,1232.77,21356.2,0.0811411 +4,2027,5677.73,1144.39,22266.1,0.0819118 +4,2028,5266.54,1045.31,23835.5,0.0804166 +5,2024,6166.59,1300,24110.6,0.0774687 +5,2025,6270.38,1401.18,22035.3,0.0870852 +5,2026,5971.79,1363.72,21652.6,0.0910623 +5,2027,5513.09,1255.61,22754.2,0.0916493 +5,2028,5087.33,1140.08,24434.9,0.0896382 +6,2024,6148.54,1450,24110.6,0.0863644 +6,2025,6190.2,1544.91,22101.9,0.096717 +6,2026,5841.9,1488.35,21948.2,0.100827 +6,2027,5353.43,1359.29,23232.9,0.101161 +6,2028,4915.71,1227.15,25009.3,0.0985598 +7,2024,6130.33,1600,24110.6,0.0952508 +7,2025,6110.39,1685,22169.1,0.10626 +7,2026,5714.35,1606.85,22242.7,0.110433 +7,2027,5198.65,1455.8,23701.4,0.110446 +7,2028,4751.38,1307.03,25557.3,0.107181 +8,2024,6315.66,10,24110.6,0.000598339 +8,2025,6974.99,11.8628,21485.9,0.000693982 +8,2026,7188.88,12.5993,19094.2,0.000743363 +8,2027,7105,12.4793,18340.2,0.000765692 +8,2028,6908.56,11.9983,18634.3,0.000770476 diff --git a/2024/runs/separable/spm b/2024/runs/separable/spm new file mode 120000 index 0000000..a26a7cd --- /dev/null +++ b/2024/runs/separable/spm @@ -0,0 +1 @@ +/Users/jim/_mymods/afsc-assessments/spmR/src/spm \ No newline at end of file