From 348f387122fb7c93a95c3396166c108e4857a676 Mon Sep 17 00:00:00 2001
From: Jim Ianelli <jim.ianelli@gmail.com>
Date: Tue, 27 Feb 2024 22:09:45 -0800
Subject: [PATCH] updated labels in atka

---
 examples/atka/F_profile.out   |      0
 examples/atka/Input_Log.rep   |    153 +
 examples/atka/alt_proj.out    |     99 +
 examples/atka/amak.prj        |     42 +
 examples/atka/cmpdiff.tmp     |      0
 examples/atka/elasticity.csv  |      0
 examples/atka/fmin.log        |      0
 examples/atka/gradfil1.tmp    |      0
 examples/atka/gradfil2.tmp    |      0
 examples/atka/means.out       |   1008 +
 examples/atka/oct22spm.tpl    |   2509 +
 examples/atka/percentdb.out   |   2205 +
 examples/atka/percentiles.out |    509 +
 examples/atka/spm             |      1 +
 examples/atka/spm.log         |      0
 examples/atka/spm_detail.csv  | 105001 +++++++++++++++++++++++++++++++
 examples/atka/varssave.tmp    |      0
 examples/yfs/Input_Log.rep    |    152 +
 examples/yfs/tacpar.dat       |     10 +
 examples/yfs/yfs.dat          |     47 +
 20 files changed, 111736 insertions(+)
 create mode 100644 examples/atka/F_profile.out
 create mode 100644 examples/atka/Input_Log.rep
 create mode 100644 examples/atka/alt_proj.out
 create mode 100644 examples/atka/amak.prj
 create mode 100755 examples/atka/cmpdiff.tmp
 create mode 100644 examples/atka/elasticity.csv
 create mode 100644 examples/atka/fmin.log
 create mode 100755 examples/atka/gradfil1.tmp
 create mode 100755 examples/atka/gradfil2.tmp
 create mode 100644 examples/atka/means.out
 create mode 100644 examples/atka/oct22spm.tpl
 create mode 100644 examples/atka/percentdb.out
 create mode 100644 examples/atka/percentiles.out
 create mode 120000 examples/atka/spm
 create mode 100644 examples/atka/spm.log
 create mode 100644 examples/atka/spm_detail.csv
 create mode 100755 examples/atka/varssave.tmp
 create mode 100644 examples/yfs/Input_Log.rep
 create mode 100644 examples/yfs/tacpar.dat
 create mode 100644 examples/yfs/yfs.dat

diff --git a/examples/atka/F_profile.out b/examples/atka/F_profile.out
new file mode 100644
index 0000000..e69de29
diff --git a/examples/atka/Input_Log.rep b/examples/atka/Input_Log.rep
new file mode 100644
index 0000000..35b7566
--- /dev/null
+++ b/examples/atka/Input_Log.rep
@@ -0,0 +1,153 @@
+run_name
+std
+Tier
+3
+nalts
+7
+alt_list
+ 1 2 3 4 5 6 7
+TAC_ABC
+1
+SrType
+2
+Rec_Gen
+1
+Fmsy_F35
+0
+Rec_Cond
+0
+Write_Big
+1
+npro
+15
+nsims
+1000
+styr
+2022
+bzero_in
+2.14289e-314
+phizero_in
+1.97626e-323
+alpha_in
+0
+sigmar_in
+2.14609e-314
+rho_in
+3.91012e-314
+nyrs_catch_in
+3
+nspp
+1
+OY_min
+0
+OY_max
+2e+06
+spp_file_name
+amak.prj
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ABC_Multiplier
+ 1
+N_scalar
+ 1
+Alt4_SPR
+ 0.75
+ntacspp
+1
+tac_ind
+ 1
+Obs_Catch
+ 2022 66481
+ 2023 83800
+ 2024 73495
+maxabc
+ 2.60197
+theta
+ 0.417
+ 0.372
+ 0.361
+ 0.296
+ 0.2733
+ 0.125
+ -0.300856
+SSL_spp(i)
+1
+Const_Buffer(i)
+0
+ngear(i)
+1
+nsexes(i)
+1
+avg_5yrF(i)
+0.466309
+FABC_Adj(i)
+1
+SPR_abc(i)
+0.4
+SPR_ofl(i)
+0.35
+spawnmo(i)
+8
+nages(i)
+11
+Fratiotmp(i)
+ 1 0 0 0 0
+M_Ftmp(i)
+ 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 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 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 0 0 0 0 0 0 0 0
+pmaturetmp_F(i)
+ 0.005 0.037 0.224 0.688 0.944 0.992 0.999 1 1 1 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 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 0 0 0 0 0 0 0 0
+pmaturetmp_M(i)
+ 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 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 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
+wt_Ftmp(i)
+ 53 170.51 438.746 532.373 702.888 741.487 835.179 913.014 933.513 899.299 961.619 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 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 0 0 0 0 0 0 0 0
+wt_gear_Ftmp(i)
+ 69 409.472 565.989 654.075 742.345 791.25 804.113 845.83 828.65 850.669 872.894 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 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 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 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 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 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 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 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 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 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 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 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 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 0 0 0 0 0 0 0 0 0
+wt_gear_Mtmp(i)
+ 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 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 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 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 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 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 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 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 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 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 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 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 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 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
+sel_Ftmp(i)
+ 0.00127026 0.0124189 0.0999134 0.292556 0.493402 0.661302 0.852503 1 0.923677 0.575225 0.575225 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 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 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 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 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 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 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 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 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 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 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 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 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 0 0 0 0 0 0 0 0 0
+sel_Mtmp(i)
+ 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 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 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 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 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 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 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 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 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 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 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 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 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 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
+n0_Ftmp(i)
+ 455.117 327.78 225.928 180.065 204.794 57.5847 48.566 11.1321 19.4992 16.1917 16.6349 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 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 0 0 0 0 0 0 0 0
+n0_Mtmp(i)
+ 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 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 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
+nrec
+ 43
+Rtmp
+ 2029.18 510.378 302.256 329.928 212.274 287.859 311.806 496.744 428.929 584.25 467.616 1174.85 563.228 330.767 513.567 854.815 340.554 334.724 862.518 199.665 307.073 717.886 1625.57 1059.21 1187.72 256.331 342.385 460.791 320.225 850.262 727.305 225.784 489.818 351.231 540.93 1000.95 702.742 197.174 468.108 340.657 775.326 458.576 413.419 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 0
+SSBtmp
+ 185063 194924 225633 281301 308840 278432 242762 204377 171283 153353 151813 157796 169000 189832 214867 217034 189390 167558 148283 131538 121405 125866 121836 113387 146360 209974 260828 270171 243816 203159 174091 152785 150435 155099 145082 139850 146641 154981 175310 180589 157355 136916 132864 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 0
diff --git a/examples/atka/alt_proj.out b/examples/atka/alt_proj.out
new file mode 100644
index 0000000..e207d99
--- /dev/null
+++ b/examples/atka/alt_proj.out
@@ -0,0 +1,99 @@
+Stock Alt Year Catch ABC OFL SSB TotBiom
+Model_16.0b 1 2023 83799.9 98588.3 118787 122541 615027
+Model_16.0b 1 2024 73495 86464.1 101188 111122 606662
+Model_16.0b 1 2025 80839 80839 95229.6 105236 623219
+Model_16.0b 1 2026 77777.1 77777.1 92491.4 106221 635879
+Model_16.0b 1 2027 80536.7 80536.7 96193 110493 655119
+Model_16.0b 1 2028 84714.7 84714.7 101278 113880 668308
+Model_16.0b 1 2029 87345.6 87345.6 104498 116270 673907
+Model_16.0b 1 2030 88654.4 88654.4 106073 117263 676706
+Model_16.0b 1 2031 89114.6 89114.6 106625 117281 677145
+Model_16.0b 1 2032 89109 89109 106561 117310 675478
+Model_16.0b 1 2033 88865.1 88865.1 106268 117279 674184
+Model_16.0b 1 2034 88605 88605 105985 116943 674838
+Model_16.0b 1 2035 88577 88577 105913 116752 677120
+Model_16.0b 1 2036 88884.6 88884.6 106282 117090 676236
+Model_16.0b 2 2023 83799.9 98588.3 118787 122541 615027
+Model_16.0b 2 2024 73495 86464.1 101188 111122 606662
+Model_16.0b 2 2025 80839 80839 95229.6 105236 623219
+Model_16.0b 2 2026 77777.1 77777.1 92491.4 106221 635879
+Model_16.0b 2 2027 80536.7 80536.7 96193 110493 655119
+Model_16.0b 2 2028 84714.7 84714.7 101278 113880 668308
+Model_16.0b 2 2029 87345.6 87345.6 104498 116270 673907
+Model_16.0b 2 2030 88654.4 88654.4 106073 117263 676706
+Model_16.0b 2 2031 89114.6 89114.6 106625 117281 677145
+Model_16.0b 2 2032 89109 89109 106561 117310 675478
+Model_16.0b 2 2033 88865.1 88865.1 106268 117279 674184
+Model_16.0b 2 2034 88605 88605 105985 116943 674838
+Model_16.0b 2 2035 88577 88577 105913 116752 677120
+Model_16.0b 2 2036 88884.6 88884.6 106282 117090 676236
+Model_16.0b 3 2023 83799.9 98588.3 118787 122541 615027
+Model_16.0b 3 2024 73495 86464.1 101188 111122 606662
+Model_16.0b 3 2025 68344.2 80839 95229.6 108351 623219
+Model_16.0b 3 2026 69221 81957.7 97490.8 112436 647097
+Model_16.0b 3 2027 72154.2 86261.3 103139 118834 671754
+Model_16.0b 3 2028 75774.3 91776.5 109884 123992 688996
+Model_16.0b 3 2029 78666.5 95717.8 114677 127796 698241
+Model_16.0b 3 2030 80417 97920.9 117310 129771 703659
+Model_16.0b 3 2031 81152.4 98951 118578 130390 705684
+Model_16.0b 3 2032 81426.3 99362.6 119018 130740 704965
+Model_16.0b 3 2033 81470.7 99350.2 118970 130856 704157
+Model_16.0b 3 2034 81307.9 99083.2 118660 130545 704901
+Model_16.0b 3 2035 81190.1 99035.9 118598 130365 707148
+Model_16.0b 3 2036 81341.3 99369.1 119028 130744 706319
+Model_16.0b 4 2023 83799.9 98588.3 118787 122541 615027
+Model_16.0b 4 2024 73495 86464.1 101188 111122 606662
+Model_16.0b 4 2025 21003.3 80839 95229.6 119949 623219
+Model_16.0b 4 2026 24298 97897.5 116802 139833 689852
+Model_16.0b 4 2027 27524.6 111949 134360 159044 746148
+Model_16.0b 4 2028 30646.8 124703 149899 174592 787778
+Model_16.0b 4 2029 33192.6 134763 161954 186748 816146
+Model_16.0b 4 2030 35022.6 141870 170413 195257 836518
+Model_16.0b 4 2031 36130.5 146239 175606 200665 849655
+Model_16.0b 4 2032 36748.2 148726 178615 204382 856897
+Model_16.0b 4 2033 37137.3 150326 180559 206960 861836
+Model_16.0b 4 2034 37319.3 151088 181474 208278 866485
+Model_16.0b 4 2035 37419.1 151568 182082 209150 871299
+Model_16.0b 4 2036 37561.6 152165 182813 210260 872217
+Model_16.0b 5 2023 83799.9 98588.3 118787 122541 615027
+Model_16.0b 5 2024 73495 86464.1 101188 111122 606662
+Model_16.0b 5 2025 0 80839 95229.6 124921 623219
+Model_16.0b 5 2026 0 104526 125007 153195 708936
+Model_16.0b 5 2027 0 123691 148718 180788 783248
+Model_16.0b 5 2028 0 141573 170203 204444 841782
+Model_16.0b 5 2029 0 156585 188071 224184 885856
+Model_16.0b 5 2030 0 168069 201697 239499 920489
+Model_16.0b 5 2031 0 175938 211053 250678 945953
+Model_16.0b 5 2032 0 181035 217164 259050 963406
+Model_16.0b 5 2033 0 184686 221539 265413 976626
+Model_16.0b 5 2034 0 187020 224357 269642 987739
+Model_16.0b 5 2035 0 188624 226301 272719 997501
+Model_16.0b 5 2036 0 190154 228155 275526 1.00221e+06
+Model_16.0b 6 2023 118787 98588.3 118787 113113 615027
+Model_16.0b 6 2024 84865.8 72133.3 84865.8 96078.5 575519
+Model_16.0b 6 2025 77259.5 65318.2 77259.5 92625 588393
+Model_16.0b 6 2026 80811 67848 80811 96169.1 611874
+Model_16.0b 6 2027 86630.1 72482.4 86630.1 100795 633722
+Model_16.0b 6 2028 91491 76593.8 91491 103763 646104
+Model_16.0b 6 2029 94377.6 78896.4 94377.6 105593 650398
+Model_16.0b 6 2030 95342.3 79743.3 95342.3 106143 651894
+Model_16.0b 6 2031 95520 79912.7 95520 105940 651629
+Model_16.0b 6 2032 95262.8 79713.7 95262.8 105926 649683
+Model_16.0b 6 2033 94991.2 79475.9 94991.2 105885 648387
+Model_16.0b 6 2034 94715 79259.4 94715 105560 649083
+Model_16.0b 6 2035 94591.9 79185.2 94591.9 105417 651418
+Model_16.0b 6 2036 94977.3 79490.3 94977.3 105799 650657
+Model_16.0b 7 2023 98588.2 98588.3 118787 118600 615027
+Model_16.0b 7 2024 80272.1 80272.2 94147.3 104213 593470
+Model_16.0b 7 2025 86618.4 73429.5 86618.4 97372.2 606706
+Model_16.0b 7 2026 83930.7 70518 83930.7 97839.8 617801
+Model_16.0b 7 2027 87523.1 73246.3 87523.1 101308 635406
+Model_16.0b 7 2028 91697.9 76767.8 91697.9 103909 646523
+Model_16.0b 7 2029 94395.6 78909.2 94395.6 105638 650488
+Model_16.0b 7 2030 95338 79737.9 95338 106163 651928
+Model_16.0b 7 2031 95521.2 79912.8 95521.2 105952 651652
+Model_16.0b 7 2032 95265.6 79715.6 95265.6 105932 649696
+Model_16.0b 7 2033 94992.9 79477.1 94992.9 105887 648393
+Model_16.0b 7 2034 94715.8 79260 94715.8 105562 649086
+Model_16.0b 7 2035 94592.2 79185.5 94592.2 105418 651419
+Model_16.0b 7 2036 94977.4 79490.4 94977.4 105799 650658
diff --git a/examples/atka/amak.prj b/examples/atka/amak.prj
new file mode 100644
index 0000000..24f551d
--- /dev/null
+++ b/examples/atka/amak.prj
@@ -0,0 +1,42 @@
+#runname
+Model_16.0b
+#ssl_spp
+1
+#Dorn_buffer
+0
+#nfsh
+1
+#nsex
+1
+#avgF5yr
+0.466309  
+#F40_mult
+1
+#spr_abc
+0.4
+#spr_msy
+0.35
+#sp_mo                                   
+8
+#nages
+11
+#Frat
+1
+#M
+0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 
+#pmat
+0.005 0.037 0.224 0.688 0.944 0.992 0.999 1 1 1 1
+#wtage_sp
+ 53 170.51 438.746 532.373 702.888 741.487 835.179 913.014 933.513 899.299 961.619
+#wtage_fsh
+ 69 409.472 565.989 654.075 742.345 791.25 804.113 845.83 828.65 850.669 872.894
+#sel
+ 0.00127026 0.0124189 0.0999134 0.292556 0.493402 0.661302 0.852503 1 0.923677 0.575225 0.575225
+#N
+ 455.117 327.78 225.928 180.065 204.794 57.5847 48.566 11.1321 19.4992 16.1917 16.6349
+#nyrs
+43
+#R
+ 2029.18 510.378 302.256 329.928 212.274 287.859 311.806 496.744 428.929 584.25 467.616 1174.85 563.228 330.767 513.567 854.815 340.554 334.724 862.518 199.665 307.073 717.886 1625.57 1059.21 1187.72 256.331 342.385 460.791 320.225 850.262 727.305 225.784 489.818 351.231 540.93 1000.95 702.742 197.174 468.108 340.657 775.326 458.576 413.419
+#SSB                                                 
+ 185063 194924 225633 281301 308840 278432 242762 204377 171283 153353 151813 157796 169000 189832 214867 217034 189390 167558 148283 131538 121405 125866 121836 113387 146360 209974 260828 270171 243816 203159 174091 152785 150435 155099 145082 139850 146641 154981 175310 180589 157355 136916 132864
diff --git a/examples/atka/cmpdiff.tmp b/examples/atka/cmpdiff.tmp
new file mode 100755
index 0000000..e69de29
diff --git a/examples/atka/elasticity.csv b/examples/atka/elasticity.csv
new file mode 100644
index 0000000..e69de29
diff --git a/examples/atka/fmin.log b/examples/atka/fmin.log
new file mode 100644
index 0000000..e69de29
diff --git a/examples/atka/gradfil1.tmp b/examples/atka/gradfil1.tmp
new file mode 100755
index 0000000..e69de29
diff --git a/examples/atka/gradfil2.tmp b/examples/atka/gradfil2.tmp
new file mode 100755
index 0000000..e69de29
diff --git a/examples/atka/means.out b/examples/atka/means.out
new file mode 100644
index 0000000..2e50e6d
--- /dev/null
+++ b/examples/atka/means.out
@@ -0,0 +1,1008 @@
+Alternative 1 Catch
+     Model_16.0b 
+Equil_Fabc 90158.7 
+Year 
+2022 66481 
+2023 83799.9 
+2024 73495 
+2025 80839 
+2026 77777.1 
+2027 80536.7 
+2028 84714.7 
+2029 87345.6 
+2030 88654.4 
+2031 89114.6 
+2032 89109 
+2033 88865.1 
+2034 88605 
+2035 88577 
+2036 88884.6 
+
+Alternative 1 ABCs
+     Model_16.0b 
+
+Year 
+2022 102578 
+2023 98588.3 
+2024 86464.1 
+2025 80839 
+2026 77777.1 
+2027 80536.7 
+2028 84714.7 
+2029 87345.6 
+2030 88654.4 
+2031 89114.6 
+2032 89109 
+2033 88865.1 
+2034 88605 
+2035 88577 
+2036 88884.6 
+
+Alternative 1 TACs
+     Model_16.0b 
+
+Year 
+2022  NA 
+2023  NA 
+2024  NA 
+2025 80839 
+2026 77777.1 
+2027 80536.7 
+2028 84714.7 
+2029 87345.6 
+2030 88654.4 
+2031 89114.6 
+2032 89109 
+2033 88865.1 
+2034 88605 
+2035 88577 
+2036 88884.6 
+
+Alternative 1 Sp_Biomass
+     Model_16.0b 
+Equil_Fabc 112182 
+Year 
+2022 137805 
+2023 122541 
+2024 111122 
+2025 105236 
+2026 106221 
+2027 110493 
+2028 113880 
+2029 116270 
+2030 117263 
+2031 117281 
+2032 117310 
+2033 117279 
+2034 116943 
+2035 116752 
+2036 117090 
+
+Alternative 1 Fishing Mortality
+     Model_16.0b 
+Equil_Fabc 0.60874 
+Year 
+2022 0.37197 
+2023 0.503755 
+2024 0.482975 
+2025 0.563903 
+2026 0.549328 
+2027 0.552255 
+2028 0.560896 
+2029 0.563196 
+2030 0.563517 
+2031 0.564228 
+2032 0.563868 
+2033 0.562784 
+2034 0.562439 
+2035 0.563452 
+2036 0.564489 
+
+Alternative 1 Biomass
+     Model_16.0b 
+
+Year 
+2022 631455 
+2023 615027 
+2024 606662 
+2025 623219 
+2026 635879 
+2027 655119 
+2028 668308 
+2029 673907 
+2030 676706 
+2031 677145 
+2032 675478 
+2033 674184 
+2034 674838 
+2035 677120 
+2036 676236 
+
+Alternative 1 Implied SPR rate 
+     Model_16.0b 
+Equil_Fabc 0.4 
+Year 
+2022 0.517114 
+2023 0.444118 
+2024 0.454137 
+2025 0.417939 
+2026 0.424954 
+2027 0.424269 
+2028 0.420625 
+2029 0.419643 
+2030 0.419572 
+2031 0.419342 
+2032 0.419413 
+2033 0.419781 
+2034 0.41992 
+2035 0.419453 
+2036 0.419029 
+
+  Model_16.0b 
+EquilAvgAgeF0  3.71599 
+EquilAvgAgeFabc  2.69344 
+AvgAgeYr2036 44.4789 
+Alternative 2 Catch
+     Model_16.0b 
+Equil_Fabc 90158.7 
+Year 
+2022 66481 
+2023 83799.9 
+2024 73495 
+2025 80839 
+2026 77777.1 
+2027 80536.7 
+2028 84714.7 
+2029 87345.6 
+2030 88654.4 
+2031 89114.6 
+2032 89109 
+2033 88865.1 
+2034 88605 
+2035 88577 
+2036 88884.6 
+
+Alternative 2 ABCs
+     Model_16.0b 
+
+Year 
+2022 102578 
+2023 98588.3 
+2024 86464.1 
+2025 80839 
+2026 77777.1 
+2027 80536.7 
+2028 84714.7 
+2029 87345.6 
+2030 88654.4 
+2031 89114.6 
+2032 89109 
+2033 88865.1 
+2034 88605 
+2035 88577 
+2036 88884.6 
+
+Alternative 2 TACs
+     Model_16.0b 
+
+Year 
+2022  NA 
+2023  NA 
+2024  NA 
+2025 80839 
+2026 77777.1 
+2027 80536.7 
+2028 84714.7 
+2029 87345.6 
+2030 88654.4 
+2031 89114.6 
+2032 89109 
+2033 88865.1 
+2034 88605 
+2035 88577 
+2036 88884.6 
+
+Alternative 2 Sp_Biomass
+     Model_16.0b 
+Equil_Fabc 112182 
+Year 
+2022 137805 
+2023 122541 
+2024 111122 
+2025 105236 
+2026 106221 
+2027 110493 
+2028 113880 
+2029 116270 
+2030 117263 
+2031 117281 
+2032 117310 
+2033 117279 
+2034 116943 
+2035 116752 
+2036 117090 
+
+Alternative 2 Fishing Mortality
+     Model_16.0b 
+Equil_Fabc 0.60874 
+Year 
+2022 0.37197 
+2023 0.503755 
+2024 0.482975 
+2025 0.563903 
+2026 0.549328 
+2027 0.552255 
+2028 0.560896 
+2029 0.563196 
+2030 0.563517 
+2031 0.564228 
+2032 0.563868 
+2033 0.562784 
+2034 0.562439 
+2035 0.563452 
+2036 0.564489 
+
+Alternative 2 Biomass
+     Model_16.0b 
+
+Year 
+2022 631455 
+2023 615027 
+2024 606662 
+2025 623219 
+2026 635879 
+2027 655119 
+2028 668308 
+2029 673907 
+2030 676706 
+2031 677145 
+2032 675478 
+2033 674184 
+2034 674838 
+2035 677120 
+2036 676236 
+
+Alternative 2 Implied SPR rate 
+     Model_16.0b 
+Equil_Fabc 0.4 
+Year 
+2022 0.517114 
+2023 0.444118 
+2024 0.454137 
+2025 0.417939 
+2026 0.424954 
+2027 0.424269 
+2028 0.420625 
+2029 0.419643 
+2030 0.419572 
+2031 0.419342 
+2032 0.419413 
+2033 0.419781 
+2034 0.41992 
+2035 0.419453 
+2036 0.419029 
+
+  Model_16.0b 
+EquilAvgAgeF0  3.71599 
+EquilAvgAgeFabc  2.69344 
+AvgAgeYr2036 44.4789 
+Alternative 3 Catch
+     Model_16.0b 
+Equil_Fabc 90158.7 
+Year 
+2022 66481 
+2023 83799.9 
+2024 73495 
+2025 68344.2 
+2026 69221 
+2027 72154.2 
+2028 75774.3 
+2029 78666.5 
+2030 80417 
+2031 81152.4 
+2032 81426.3 
+2033 81470.7 
+2034 81307.9 
+2035 81190.1 
+2036 81341.3 
+
+Alternative 3 ABCs
+     Model_16.0b 
+
+Year 
+2022 102578 
+2023 98588.3 
+2024 86464.1 
+2025 80839 
+2026 81957.7 
+2027 86261.3 
+2028 91776.5 
+2029 95717.8 
+2030 97920.9 
+2031 98951 
+2032 99362.6 
+2033 99350.2 
+2034 99083.2 
+2035 99035.9 
+2036 99369.1 
+
+Alternative 3 TACs
+     Model_16.0b 
+
+Year 
+2022  NA 
+2023  NA 
+2024  NA 
+2025 68344.2 
+2026 69221 
+2027 72154.2 
+2028 75774.3 
+2029 78666.5 
+2030 80417 
+2031 81152.4 
+2032 81426.3 
+2033 81470.7 
+2034 81307.9 
+2035 81190.1 
+2036 81341.3 
+
+Alternative 3 Sp_Biomass
+     Model_16.0b 
+Equil_Fabc 112182 
+Year 
+2022 137805 
+2023 122541 
+2024 111122 
+2025 108351 
+2026 112436 
+2027 118834 
+2028 123992 
+2029 127796 
+2030 129771 
+2031 130390 
+2032 130740 
+2033 130856 
+2034 130545 
+2035 130365 
+2036 130744 
+
+Alternative 3 Fishing Mortality
+     Model_16.0b 
+Equil_Fabc 0.60874 
+Year 
+2022 0.37197 
+2023 0.503755 
+2024 0.482975 
+2025 0.466309 
+2026 0.466309 
+2027 0.466309 
+2028 0.466309 
+2029 0.466309 
+2030 0.466309 
+2031 0.466309 
+2032 0.466309 
+2033 0.466309 
+2034 0.466309 
+2035 0.466309 
+2036 0.466309 
+
+Alternative 3 Biomass
+     Model_16.0b 
+
+Year 
+2022 631455 
+2023 615027 
+2024 606662 
+2025 623219 
+2026 647097 
+2027 671754 
+2028 688996 
+2029 698241 
+2030 703659 
+2031 705684 
+2032 704965 
+2033 704157 
+2034 704901 
+2035 707148 
+2036 706319 
+
+Alternative 3 Implied SPR rate 
+     Model_16.0b 
+Equil_Fabc 0.4 
+Year 
+2022 0.517114 
+2023 0.444118 
+2024 0.454137 
+2025 0.462515 
+2026 0.462515 
+2027 0.462515 
+2028 0.462515 
+2029 0.462515 
+2030 0.462515 
+2031 0.462515 
+2032 0.462515 
+2033 0.462515 
+2034 0.462515 
+2035 0.462515 
+2036 0.462515 
+
+  Model_16.0b 
+EquilAvgAgeF0  3.71599 
+EquilAvgAgeFabc  2.69344 
+AvgAgeYr2036 45.3994 
+Alternative 4 Catch
+     Model_16.0b 
+Equil_Fabc 90158.7 
+Year 
+2022 66481 
+2023 83799.9 
+2024 73495 
+2025 21003.3 
+2026 24298 
+2027 27524.6 
+2028 30646.8 
+2029 33192.6 
+2030 35022.6 
+2031 36130.5 
+2032 36748.2 
+2033 37137.3 
+2034 37319.3 
+2035 37419.1 
+2036 37561.6 
+
+Alternative 4 ABCs
+     Model_16.0b 
+
+Year 
+2022 102578 
+2023 98588.3 
+2024 86464.1 
+2025 80839 
+2026 97897.5 
+2027 111949 
+2028 124703 
+2029 134763 
+2030 141870 
+2031 146239 
+2032 148726 
+2033 150326 
+2034 151088 
+2035 151568 
+2036 152165 
+
+Alternative 4 TACs
+     Model_16.0b 
+
+Year 
+2022  NA 
+2023  NA 
+2024  NA 
+2025 21003.3 
+2026 24298 
+2027 27524.6 
+2028 30646.8 
+2029 33192.6 
+2030 35022.6 
+2031 36130.5 
+2032 36748.2 
+2033 37137.3 
+2034 37319.3 
+2035 37419.1 
+2036 37561.6 
+
+Alternative 4 Sp_Biomass
+     Model_16.0b 
+Equil_Fabc 112182 
+Year 
+2022 137805 
+2023 122541 
+2024 111122 
+2025 119949 
+2026 139833 
+2027 159044 
+2028 174592 
+2029 186748 
+2030 195257 
+2031 200665 
+2032 204382 
+2033 206960 
+2034 208278 
+2035 209150 
+2036 210260 
+
+Alternative 4 Fishing Mortality
+     Model_16.0b 
+Equil_Fabc 0.60874 
+Year 
+2022 0.37197 
+2023 0.503755 
+2024 0.482975 
+2025 0.131302 
+2026 0.131302 
+2027 0.131302 
+2028 0.131302 
+2029 0.131302 
+2030 0.131302 
+2031 0.131302 
+2032 0.131302 
+2033 0.131302 
+2034 0.131302 
+2035 0.131302 
+2036 0.131302 
+
+Alternative 4 Biomass
+     Model_16.0b 
+
+Year 
+2022 631455 
+2023 615027 
+2024 606662 
+2025 623219 
+2026 689852 
+2027 746148 
+2028 787778 
+2029 816146 
+2030 836518 
+2031 849655 
+2032 856897 
+2033 861836 
+2034 866485 
+2035 871299 
+2036 872217 
+
+Alternative 4 Implied SPR rate 
+     Model_16.0b 
+Equil_Fabc 0.4 
+Year 
+2022 0.517114 
+2023 0.444118 
+2024 0.454137 
+2025 0.75 
+2026 0.75 
+2027 0.75 
+2028 0.75 
+2029 0.75 
+2030 0.75 
+2031 0.75 
+2032 0.75 
+2033 0.75 
+2034 0.75 
+2035 0.75 
+2036 0.75 
+
+  Model_16.0b 
+EquilAvgAgeF0  3.71599 
+EquilAvgAgeFabc  2.69344 
+AvgAgeYr2036 50.4404 
+Alternative 5 Catch
+     Model_16.0b 
+Equil_Fabc 90158.7 
+Year 
+2022 66481 
+2023 83799.9 
+2024 73495 
+2025  NA 
+2026  NA 
+2027  NA 
+2028  NA 
+2029  NA 
+2030  NA 
+2031  NA 
+2032  NA 
+2033  NA 
+2034  NA 
+2035  NA 
+2036  NA 
+
+Alternative 5 ABCs
+     Model_16.0b 
+
+Year 
+2022 102578 
+2023 98588.3 
+2024 86464.1 
+2025 80839 
+2026 104526 
+2027 123691 
+2028 141573 
+2029 156585 
+2030 168069 
+2031 175938 
+2032 181035 
+2033 184686 
+2034 187020 
+2035 188624 
+2036 190154 
+
+Alternative 5 TACs
+     Model_16.0b 
+
+Year 
+2022  NA 
+2023  NA 
+2024  NA 
+2025  NA 
+2026  NA 
+2027  NA 
+2028  NA 
+2029  NA 
+2030  NA 
+2031  NA 
+2032  NA 
+2033  NA 
+2034  NA 
+2035  NA 
+2036  NA 
+
+Alternative 5 Sp_Biomass
+     Model_16.0b 
+Equil_Fabc 112182 
+Year 
+2022 137805 
+2023 122541 
+2024 111122 
+2025 124921 
+2026 153195 
+2027 180788 
+2028 204444 
+2029 224184 
+2030 239499 
+2031 250678 
+2032 259050 
+2033 265413 
+2034 269642 
+2035 272719 
+2036 275526 
+
+Alternative 5 Fishing Mortality
+     Model_16.0b 
+Equil_Fabc 0.60874 
+Year 
+2022 0.37197 
+2023 0.503755 
+2024 0.482975 
+2025  NA 
+2026  NA 
+2027  NA 
+2028  NA 
+2029  NA 
+2030  NA 
+2031  NA 
+2032  NA 
+2033  NA 
+2034  NA 
+2035  NA 
+2036  NA 
+
+Alternative 5 Biomass
+     Model_16.0b 
+
+Year 
+2022 631455 
+2023 615027 
+2024 606662 
+2025 623219 
+2026 708936 
+2027 783248 
+2028 841782 
+2029 885856 
+2030 920489 
+2031 945953 
+2032 963406 
+2033 976626 
+2034 987739 
+2035 997501 
+2036 1.00221e+06 
+
+Alternative 5 Implied SPR rate 
+     Model_16.0b 
+Equil_Fabc 0.4 
+Year 
+2022 0.517114 
+2023 0.444118 
+2024 0.454137 
+2025 1 
+2026 1 
+2027 1 
+2028 1 
+2029 1 
+2030 1 
+2031 1 
+2032 1 
+2033 1 
+2034 1 
+2035 1 
+2036 1 
+
+  Model_16.0b 
+EquilAvgAgeF0  3.71599 
+EquilAvgAgeFabc  2.69344 
+AvgAgeYr2036 53.8664 
+Alternative 6 Catch
+     Model_16.0b 
+Equil_Fabc 90158.7 
+Year 
+2022 66481 
+2023 118787 
+2024 84865.8 
+2025 77259.5 
+2026 80811 
+2027 86630.1 
+2028 91491 
+2029 94377.6 
+2030 95342.3 
+2031 95520 
+2032 95262.8 
+2033 94991.2 
+2034 94715 
+2035 94591.9 
+2036 94977.3 
+
+Alternative 6 ABCs
+     Model_16.0b 
+
+Year 
+2022 102578 
+2023 98588.3 
+2024 72133.3 
+2025 65318.2 
+2026 67848 
+2027 72482.4 
+2028 76593.8 
+2029 78896.4 
+2030 79743.3 
+2031 79912.7 
+2032 79713.7 
+2033 79475.9 
+2034 79259.4 
+2035 79185.2 
+2036 79490.3 
+
+Alternative 6 TACs
+     Model_16.0b 
+
+Year 
+2022  NA 
+2023 118787 
+2024 84865.8 
+2025 77259.5 
+2026 80811 
+2027 86630.1 
+2028 91491 
+2029 94377.6 
+2030 95342.3 
+2031 95520 
+2032 95262.8 
+2033 94991.2 
+2034 94715 
+2035 94591.9 
+2036 94977.3 
+
+Alternative 6 Sp_Biomass
+     Model_16.0b 
+Equil_Fabc 112182 
+Year 
+2022 137805 
+2023 113113 
+2024 96078.5 
+2025 92625 
+2026 96169.1 
+2027 100795 
+2028 103763 
+2029 105593 
+2030 106143 
+2031 105940 
+2032 105926 
+2033 105885 
+2034 105560 
+2035 105417 
+2036 105799 
+
+Alternative 6 Fishing Mortality
+     Model_16.0b 
+Equil_Fabc 0.60874 
+Year 
+2022 0.37197 
+2023 0.762078 
+2024 0.647326 
+2025 0.621865 
+2026 0.634472 
+2027 0.651284 
+2028 0.664372 
+2029 0.669778 
+2030 0.669961 
+2031 0.670505 
+2032 0.668777 
+2033 0.667404 
+2034 0.667139 
+2035 0.667585 
+2036 0.668659 
+
+Alternative 6 Biomass
+     Model_16.0b 
+
+Year 
+2022 631455 
+2023 615027 
+2024 575519 
+2025 588393 
+2026 611874 
+2027 633722 
+2028 646104 
+2029 650398 
+2030 651894 
+2031 651629 
+2032 649683 
+2033 648387 
+2034 649083 
+2035 651418 
+2036 650657 
+
+Alternative 6 Implied SPR rate 
+     Model_16.0b 
+Equil_Fabc 0.4 
+Year 
+2022 0.517114 
+2023 0.35 
+2024 0.386045 
+2025 0.395723 
+2026 0.392777 
+2027 0.387537 
+2028 0.382897 
+2029 0.381141 
+2030 0.38116 
+2031 0.381056 
+2032 0.381527 
+2033 0.381935 
+2034 0.382021 
+2035 0.381783 
+2036 0.381415 
+
+  Model_16.0b 
+EquilAvgAgeF0  3.71599 
+EquilAvgAgeFabc  2.69344 
+AvgAgeYr2036 43.3628 
+Alternative 7 Catch
+     Model_16.0b 
+Equil_Fabc 90158.7 
+Year 
+2022 66481 
+2023 98588.2 
+2024 80272.1 
+2025 86618.4 
+2026 83930.7 
+2027 87523.1 
+2028 91697.9 
+2029 94395.6 
+2030 95338 
+2031 95521.2 
+2032 95265.6 
+2033 94992.9 
+2034 94715.8 
+2035 94592.2 
+2036 94977.4 
+
+Alternative 7 ABCs
+     Model_16.0b 
+
+Year 
+2022 102578 
+2023 98588.3 
+2024 80272.2 
+2025 73429.5 
+2026 70518 
+2027 73246.3 
+2028 76767.8 
+2029 78909.2 
+2030 79737.9 
+2031 79912.8 
+2032 79715.6 
+2033 79477.1 
+2034 79260 
+2035 79185.5 
+2036 79490.4 
+
+Alternative 7 TACs
+     Model_16.0b 
+
+Year 
+2022  NA 
+2023 118787 
+2024 94147.3 
+2025 86618.4 
+2026 83930.7 
+2027 87523.1 
+2028 91697.9 
+2029 94395.6 
+2030 95338 
+2031 95521.2 
+2032 95265.6 
+2033 94992.9 
+2034 94715.8 
+2035 94592.2 
+2036 94977.4 
+
+Alternative 7 Sp_Biomass
+     Model_16.0b 
+Equil_Fabc 112182 
+Year 
+2022 137805 
+2023 118600 
+2024 104213 
+2025 97372.2 
+2026 97839.8 
+2027 101308 
+2028 103909 
+2029 105638 
+2030 106163 
+2031 105952 
+2032 105932 
+2033 105887 
+2034 105562 
+2035 105418 
+2036 105799 
+
+Alternative 7 Fishing Mortality
+     Model_16.0b 
+Equil_Fabc 0.60874 
+Year 
+2022 0.37197 
+2023 0.608739 
+2024 0.562892 
+2025 0.65535 
+2026 0.644657 
+2027 0.653947 
+2028 0.665081 
+2029 0.669965 
+2030 0.670046 
+2031 0.670554 
+2032 0.668802 
+2033 0.667415 
+2034 0.667143 
+2035 0.667587 
+2036 0.668659 
+
+Alternative 7 Biomass
+     Model_16.0b 
+
+Year 
+2022 631455 
+2023 615027 
+2024 593470 
+2025 606706 
+2026 617801 
+2027 635406 
+2028 646523 
+2029 650488 
+2030 651928 
+2031 651652 
+2032 649696 
+2033 648393 
+2034 649086 
+2035 651419 
+2036 650658 
+
+Alternative 7 Implied SPR rate 
+     Model_16.0b 
+Equil_Fabc 0.4 
+Year 
+2022 0.517114 
+2023 0.4 
+2024 0.418064 
+2025 0.383744 
+2026 0.388955 
+2027 0.386514 
+2028 0.38263 
+2029 0.38107 
+2030 0.381128 
+2031 0.381038 
+2032 0.381518 
+2033 0.381931 
+2034 0.382019 
+2035 0.381783 
+2036 0.381415 
+
+  Model_16.0b 
+EquilAvgAgeF0  3.71599 
+EquilAvgAgeFabc  2.69344 
+AvgAgeYr2036 43.5133 
diff --git a/examples/atka/oct22spm.tpl b/examples/atka/oct22spm.tpl
new file mode 100644
index 0000000..b791fc1
--- /dev/null
+++ b/examples/atka/oct22spm.tpl
@@ -0,0 +1,2509 @@
+ // DONT FORGET ABOU RHO!!!
+ ////////////////////////////////////////////////////////////////////////////
+ //   spm.tpl
+ //     Version 0.6 Released Oct 2022
+ //
+ // NOTE: Draft subject to change
+ // Conventions:
+ //   nspp,  ispp = index for species/stock
+ //   ngear, igear= index for gears used within age-structured species/stocks
+ //                                                                           
+ // Oct 2005 add ability to compute objective function for maximizing yield while minimizing variability
+ // want to have the ability to compute the average first-diff squared and avg yield for each trajectory
+ // Alt3b_obj_fun = avg_yield - 0.5 * sqrd_1st_diff
+ //
+ ////////////////////////////////////////////////////////////////////////////
+DATA_SECTION
+  !!CLASS ofstream means_out("means.out")
+  !!CLASS ofstream alts_proj("alt_proj.out")
+  !!CLASS ofstream percent_out("percentiles.out")
+  !!CLASS ofstream percent_db("percentdb.out")
+  // !!CLASS ofstream Alt3bstuff("alt3b.out")
+  !!CLASS ofstream detail_out("spm_detail.csv")
+  !!CLASS ofstream prof_F("F_profile.out");
+  !!CLASS ofstream elasticity("elasticity.csv");
+  int condition_SR
+  int ipro
+  int isim
+  number kink_adj
+  !! condition_SR = 0;//
+  int rnseed           // Random number seed
+  !! rnseed = 123;
+ ////////////////////////////////////////////////////////////////////////////
+  // !! ad_comm::change_datafile_name("setup.dat"); Jim changed to spm.dat file
+  !!    *(ad_comm::global_datafile) >>  run_name; // Read in the name of this run
+  init_int Tier
+  int alt ;            // Alternative specfications (relic of PSEIS)
+  vector rec_vector(1,300) // storage vector for historical and future recruitment...
+  vector wtd_rec(1,25)
+  vector wtd_div(1,25) // denominator of wtd recruitment
+  init_int nalts
+  init_ivector alt_list(1,nalts)
+  init_int TAC_ABC       // Flag to set TAC equal to ABC (1 means true, otherwise false)
+  init_int SrType        // Type of recruitment curve (1=Ricker, 2 Bholt)
+  // Specify form of recruitment generator (1 = use observed mean and std 
+  //                                        2 = use estimated SRR and estimated sigma R
+  //                                        3 = use input parameters from srecpar.dat :  
+  //                                        4 = use input parameters from srecpar.dat :  
+  init_int Rec_Gen       
+  init_int Fmsy_F35      // Specify if conditioned so that Fmsy = F35 (affects SRR fitting) may need to be species specific...
+  init_number Rec_Cond   // Specify prior condition that recruitment at half and double average SSB is similar to average historical Rec
+  init_int Write_Big     // Flag to write big file (of all simulations rather than a summary, 0 means don't do it, otherwise do it) 
+  init_int npro          // Number of projection years
+  init_int nsims         // Number of simulaions
+  init_int styr          // First year of projection
+  !! cout<< "First year:\t"<<styr<<endl;
+  // Open species level details
+  number bzero_in;
+  number phizero_in;
+  number alpha_in;
+  number sigmar_in;
+  number rho_in;
+  matrix rnorms(1,nsims,1,npro+1);
+  matrix unifs(1,nsims,1,npro+1);
+  vector sst(1,npro);
+ LOCAL_CALCS
+  write_log(run_name); 
+  write_log(Tier); 
+  write_log(nalts); 
+  write_log(alt_list); 
+  write_log(TAC_ABC); 
+  write_log(SrType); 
+  write_log(Rec_Gen); 
+  write_log(Fmsy_F35); 
+  write_log(Rec_Cond); 
+  write_log(Write_Big); 
+  write_log(npro); 
+  write_log(nsims); 
+  write_log(styr); 
+  write_log(bzero_in); 
+  write_log(phizero_in); 
+  write_log(alpha_in); 
+  write_log(sigmar_in); 
+  write_log(rho_in); 
+ END_CALCS
+  // !! ad_comm::change_datafile_name("spp_catch.dat"); Jim moved to spm.dat
+  int      nyrs_catch    // Number of years that catch is specified (starting at first year: styr) 
+  init_int nyrs_catch_in // Number of years that catch is specified (starting at first year: styr) 
+  !! cout<<"First year, and number of years catch is pre-specified. "<<styr<<" "<<nyrs_catch_in<<endl;
+  init_int nspp          // Number of species
+  init_number OY_min;    // !! OY_min = 1361.521;
+  init_number OY_max;
+ LOCAL_CALCS
+   for (int i=1;i<=nspp;i++)
+     *(ad_comm::global_datafile) >>  spp_file_name(i);
+
+  write_log(nyrs_catch_in); 
+  write_log(nspp); 
+  write_log(OY_min); 
+  write_log(OY_max); 
+  write_log(spp_file_name); 
+
+ END_CALCS
+  !! cout <<"OYMax "<<OY_max<<endl;
+  init_vector ABC_Multiplier(1,nspp) // ABC_Multiplier  
+  init_vector N_scalar(1,nspp)       // population scalar                           
+  init_vector Alt4_SPR(1,nspp)       // SPR values for Alt 4 (spp specific)         
+  vector     Alt4_Fabc(1,nspp)       // ABC values for Alt 4 (spp specific)         
+  int        Alt4_Fcalc              // Recalc F for Alt 4?  (spp specific)         
+  vector Alt3b_obj_fun(1,nspp)       // sum(avg_yld - half_sqrd_1st_diff)/nsims
+  init_int    ntacspp
+  init_ivector tac_ind(1,nspp)       // vector of tac-model indices 
+  vector model_tacs(1,ntacspp)
+  // !! for (int i=1;i<=nspp;i++) 
+  init_matrix Obs_Catch(1,nyrs_catch_in,0,nspp) // Pre-specified catch values (year is in column 0)
+
+ LOCAL_CALCS
+  if (Rec_Gen==3)
+  {
+    ad_comm::change_datafile_name("srecpar.dat");
+    //  Bzero,  PhiZero,  Alpha,
+    *(ad_comm::global_datafile) >>  bzero_in;
+    *(ad_comm::global_datafile) >>  phizero_in;
+    *(ad_comm::global_datafile) >>  alpha_in;
+    *(ad_comm::global_datafile) >>  sigmar_in;
+    *(ad_comm::global_datafile) >>  rho_in;
+    // rho_in=0.82;
+  }
+  // Open up tac-model parameters
+  ad_comm::change_datafile_name("tacpar.dat");
+ END_CALCS
+  init_int nntmp
+  init_int nnodes
+  init_vector maxabc(1,ntacspp)
+  init_matrix theta(0,nnodes,1,ntacspp)
+  !! cout<<"read tacpar"<<endl;
+
+  !! write_log(ABC_Multiplier); 
+  !! write_log(N_scalar); 
+  !! write_log(Alt4_SPR); 
+  !! write_log(ntacspp); 
+  !! write_log(tac_ind); 
+  !! write_log(Obs_Catch); 
+  !! write_log(maxabc); 
+  !! write_log(theta); 
+  vector agg_abc(1,ntacspp)
+  vector agg_cat(1,ntacspp)
+  vector agg_tac(1,ntacspp)
+  !! cout << spp_file_name(nspp) << endl;
+  !! cout << ABC_Multiplier << endl;
+  !! cout << N_scalar << endl;
+  !! cout << "Observed Catch "<<endl<<Obs_Catch<<endl;// exit(1);
+
+  int i
+  int k
+  int dolp
+  ivector SSL_spp(1,nspp)          // Flag to tell whether this species is a SSL or not...
+  ivector Const_Buffer(1,nspp)     // Flag to tell whether to use the "constant buffer" option for User ABC
+  number srprior_a
+  number srprior_b
+  !! srprior_a = 4;
+  !! srprior_b = 10;
+
+// "END: Read in dimensioning parameters and constraints"
+ ////////////////////////////////////////////////////////////////////////////
+  ivector ngear(1,nspp);
+  ivector isit_const(1,nspp);
+  vector  FABC_Adj(1,nspp);
+  vector spawnmo(1,nspp);
+  ivector nages(1,nspp);
+
+  matrix Fratiotmp(1,nspp,1,5)// temp placeholder for later ragged array
+  matrix M_Ftmp(1,nspp,1,69);
+  matrix M_Mtmp(1,nspp,1,69);
+  matrix pmaturetmp_F(1,nspp,1,69);
+  matrix pmaturetmp_M(1,nspp,1,69);
+  matrix wt_Ftmp(1,nspp,1,69); 
+  3darray wt_gear_Ftmp(1,nspp,1,5,1,69);
+  3darray wt_gear_Mtmp(1,nspp,1,5,1,69);
+  3darray sel_Ftmp(1,nspp,1,5,1,69);
+  3darray sel_Mtmp(1,nspp,1,5,1,69);
+  matrix n0_Ftmp(1,nspp,1,69);
+  matrix n0_Mtmp(1,nspp,1,69);
+  matrix Rtmp(1,nspp,1,69);
+  matrix SSBtmp(1,nspp,1,69);
+  ivector nrec(1,nspp);
+  vector Expl_Biom(1,nspp);
+
+  int ntargspp
+  vector reserved(1,nspp)
+  ivector nsexes(1,nspp)
+  vector avg_5yrF(1,nspp)
+
+  vector SPR_abc(1,nspp);
+  vector SPR_ofl(1,nspp);
+  vector targ_SPR(1,nspp);
+  !! SPR_abc = 0.40; // defaults, read in later
+  !! SPR_ofl = 0.35; // defaults, read in later
+  !! cout<<"ABC: "<<SPR_abc<< endl<<SPR_ofl<<endl;
+
+
+ LOCAL_CALCS
+  // Open species-specific level details
+   for (i=1;i<=nspp;i++)
+   {
+     cout<<spp_file_name(i)  <<endl;
+     ad_comm::change_datafile_name(spp_file_name(i));
+     *(ad_comm::global_datafile) >> spname(i);               // 1
+     cout<<spname(i)  <<endl;
+     *(ad_comm::global_datafile) >> SSL_spp(i);              // 2
+     *(ad_comm::global_datafile) >> Const_Buffer(i);         // 3
+     *(ad_comm::global_datafile) >> ngear(i);                // 4
+     *(ad_comm::global_datafile) >> nsexes(i);               // 6 
+     *(ad_comm::global_datafile) >> avg_5yrF(i);             // 7
+     *(ad_comm::global_datafile) >> FABC_Adj(i);             // 8
+     *(ad_comm::global_datafile) >> SPR_abc(i);              // 9
+     *(ad_comm::global_datafile) >> SPR_ofl(i);              // 10
+     *(ad_comm::global_datafile) >> spawnmo(i);              // 11
+     *(ad_comm::global_datafile) >> nages(i);                // 12
+         cout<<"nages: "<<nages(i)<<endl;
+     write_log( SSL_spp(i));              // 2
+     write_log( Const_Buffer(i));         // 3
+     write_log( ngear(i));                // 4
+     write_log( nsexes(i));               // 6 
+     write_log( avg_5yrF(i));             // 7
+     write_log( FABC_Adj(i));             // 8
+     write_log( SPR_abc(i));              // 9
+     write_log( SPR_ofl(i));              // 10
+     write_log( spawnmo(i));              // 11
+     write_log( nages(i));               
+     for (int j=1;j<=ngear(i);j++)                    
+       *(ad_comm::global_datafile) >> Fratiotmp(i,j);        // 13
+     write_log( Fratiotmp(i));               
+
+     for (int k=1;k<=nages(i);k++)
+       *(ad_comm::global_datafile) >> M_Ftmp(i,k);           // 14
+     if (nsexes(i)==2)
+       for (int k=1;k<=nages(i);k++)
+         *(ad_comm::global_datafile) >> M_Mtmp(i,k);         // 15
+     write_log( M_Ftmp(i));               
+
+     for (int k=1;k<=nages(i);k++)
+       *(ad_comm::global_datafile) >> pmaturetmp_F(i,k);       // 16
+     write_log( pmaturetmp_F(i));               
+
+     if (nsexes(i)==2)
+       for (int k=1;k<=nages(i);k++)
+         *(ad_comm::global_datafile) >> pmaturetmp_M(i,k);         // 15
+     write_log( pmaturetmp_M(i));               
+      cout << "Mature:  "<< pmaturetmp_F(i)(1,nages(i)) <<endl;
+
+     for (int k=1;k<=nages(i);k++)
+       *(ad_comm::global_datafile) >> wt_Ftmp(i,k);          // 17
+     write_log( wt_Ftmp(i));               
+     for (int j=1;j<=ngear(i);j++)
+       for (int k=1;k<=nages(i);k++)
+         *(ad_comm::global_datafile) >> wt_gear_Ftmp(i,j,k); // 18
+     write_log( wt_gear_Ftmp(i));               
+
+     if (nsexes(i)==2)
+       for (int j=1;j<=ngear(i);j++)
+         for (int k=1;k<=nages(i);k++)
+           *(ad_comm::global_datafile) >> wt_gear_Mtmp(i,j,k);// 19
+     write_log( wt_gear_Mtmp(i));               
+      
+     for (int j=1;j<=ngear(i);j++)
+       for (int k=1;k<=nages(i);k++)
+         *(ad_comm::global_datafile) >> sel_Ftmp(i,j,k);    // 20
+     write_log( sel_Ftmp(i));               
+
+     if (nsexes(i)==2)
+       for (int j=1;j<=ngear(i);j++)
+         for (int k=1;k<=nages(i);k++)
+           *(ad_comm::global_datafile) >> sel_Mtmp(i,j,k);  // 21
+     write_log( sel_Mtmp(i));               
+     for (int k=1;k<=nages(i);k++)
+       *(ad_comm::global_datafile) >> n0_Ftmp(i,k);         // 22
+     write_log(  n0_Ftmp(i));               
+
+     if (nsexes(i)==2)
+       for (int k=1;k<=nages(i);k++)
+         *(ad_comm::global_datafile) >> n0_Mtmp(i,k);       // 23
+     write_log(  n0_Mtmp(i));               
+
+         cout<<"N: "<<n0_Ftmp(i)(1,nages(i))<<endl;
+
+     *(ad_comm::global_datafile) >> nrec(i);                // 24
+         cout<<"nrec: "<<nrec(i)<<endl;
+     for (int j=1;j<=nrec(i);j++)
+       *(ad_comm::global_datafile) >> Rtmp(i,j);            // 25
+      cout<<"Rec: "<<Rtmp(i)(1,nrec(i))<<endl;
+     for (int j=1;j<=nrec(i);j++)
+       *(ad_comm::global_datafile) >> SSBtmp(i,j);          // 26
+      cout<<"SSB: "<<SSBtmp(i)(1,nrec(i))<<endl;
+  }
+	  write_log(nrec);
+	  write_log(Rtmp);
+	  write_log(SSBtmp);
+  // cout <<FABC_Adj<<" "<<ABC_Multiplier<<endl;exit(1);
+ END_CALCS
+  matrix M_F(1,nspp,1,nages);
+  matrix M_M(1,nspp,1,nages);
+  matrix pmature_F(1,nspp,1,nages);
+  matrix pmature_M(1,nspp,1,nages);
+  matrix wt_F(1,nspp,1,nages); 
+  matrix wt_M(1,nspp,1,nages);
+  matrix Frat(1,nspp,1,ngear);
+  3darray wt_gear_F(1,nspp,1,ngear,1,nages);
+  3darray wt_gear_M(1,nspp,1,ngear,1,nages);
+  3darray sel_F(1,nspp,1,ngear,1,nages);
+  3darray sel_M(1,nspp,1,ngear,1,nages);
+  matrix n0_F(1,nspp,1,nages);
+  matrix n0_M(1,nspp,1,nages);
+  matrix R(1,nspp,1,nrec);
+  matrix SSB(1,nspp,1,nrec);
+ LOCAL_CALCS
+  M_F.initialize();
+  M_M.initialize();
+  pmature_F.initialize();
+  pmature_M.initialize();
+  wt_F.initialize();
+  wt_M.initialize();
+  wt_gear_F.initialize();
+  wt_gear_F.initialize();
+  sel_F.initialize();
+  sel_M.initialize();
+  n0_F.initialize();
+  n0_M.initialize();
+  R.initialize();
+  SSB.initialize();
+  for (int i=1;i<=nspp;i++) {
+    cout<<spname(i)<<endl;
+    for (int k=1;k<=nages(i);k++) {
+      M_F(i,k) = M_Ftmp(i,k); 
+      pmature_F(i,k) = pmaturetmp_F(i,k); 
+      wt_F(i,k) = wt_Ftmp(i,k);  
+      for (int j=1;j<=ngear(i);j++) {
+        wt_gear_F(i,j,k) = wt_gear_Ftmp(i,j,k); 
+        sel_F(i,j,k) = sel_Ftmp(i,j,k); 
+
+        if (nsexes(i)==2) {
+          wt_gear_M(i,j,k) = wt_gear_Mtmp(i,j,k); 
+          sel_M(i,j,k) = sel_Mtmp(i,j,k);
+        }
+        else {
+          wt_gear_M(i,j,k) = wt_gear_Ftmp(i,j,k); 
+          sel_M(i,j,k) = sel_Ftmp(i,j,k);
+        }
+        wt_M(i,k) += wt_gear_M(i,j,k);  
+      }
+      if (nsexes(i)==2) {
+        pmature_M(i,k)  = pmaturetmp_M(i,k); 
+        M_M(i,k)  = M_Mtmp(i,k); 
+        n0_F(i,k) = n0_Ftmp(i,k); 
+        n0_M(i,k) = n0_Mtmp(i,k); 
+      }
+      else {
+        pmature_M(i,k)  = pmaturetmp_F(i,k); 
+        M_M(i,k)  = M_Ftmp(i,k); 
+        n0_F(i,k) = n0_Ftmp(i,k)/ 2.; 
+        n0_M(i,k) = n0_F(i,k); 
+      }
+    }
+    cout << "M_Female: "<< spname(i)<<" "<<M_F(i) <<endl;
+    cout << "M_Male:   "<< spname(i)<<" "<<M_M(i) <<endl;
+
+    wt_M(i) /= ngear(i);
+    n0_F(i) /= N_scalar(i);
+    n0_M(i) /= N_scalar(i);
+    for (int k=1;k<=nyrs_catch_in;k++)
+      Obs_Catch(k,i) /= N_scalar(i);
+
+    for (int k=1;k<=nyrs_catch_in;k++)
+      cout <<k<<" "<<spname(i)<<" "<< Obs_Catch(k,i)<<endl;
+
+    for (int k=1;k<=nrec(i);k++) {
+      R(i,k)    =  Rtmp(i,k);
+      SSB(i,k)  =  SSBtmp(i,k);
+    }
+    R(i) /= N_scalar(i);
+    SSB(i) /= N_scalar(i);
+
+    for (int j=1;j<=ngear(i);j++)
+      Frat(i,j) = Fratiotmp(i,j);
+  }
+  for (int ispp=1;ispp<=nspp;ispp++) agg_cat(tac_ind(ispp))  += Obs_Catch(1,ispp);
+  cout<<R<<endl;
+
+  wtd_div.initialize(); 
+  double sumtmp;
+  for (int ispp=1;ispp<=nspp;ispp++) { 
+    for (int i=nages(ispp)+1;i<=25;i++) { 
+      sumtmp=0.;
+      for (int j=1;j<i;j++) 
+        sumtmp -= M_F(ispp,nages(ispp));
+      wtd_div(i) +=  pmature_F(ispp,nages(ispp))*wt_F(ispp,nages(ispp))*exp(sumtmp);
+    }
+  }
+ END_CALCS
+  matrix wt_mature_F(1,nspp,1,nages)
+  matrix wt_mature_M(1,nspp,1,nages)
+  !! wt_mature_F =  elem_prod(wt_F,pmature_F); 
+  vector yrfrac(1,nspp)        // Fraction of year prior to spawning 
+  !! yrfrac= (spawnmo-1.)/12; 
+
+  vector Actual_Catch(1,nspp)
+  3darray   Rsim(1,nspp,1,nsims,1,npro+1)
+  3darray   Fsim(1,nspp,1,nsims,1,npro+1)
+  3darray   Bsim(1,nspp,1,nsims,1,npro+1) 
+  3darray   Nsim(1,nspp,1,nsims,1,npro+1) 
+  3darray  SRsim(1,nspp,1,nsims,1,npro+1) // Sex ratio
+  3darray  SBsim(1,nspp,1,nsims,1,npro+1) 
+  3darray SPRsim(1,nspp,1,nsims,1,npro+1) 
+  3darray   Csim(1,nspp,1,nsims,1,npro+1) 
+  matrix  TACs_by_yr(1,npro,1,nspp) 
+  matrix  ABCs_by_yr(1,npro,1,nspp) 
+  matrix  OFLs_by_yr(1,npro,1,nspp) 
+  matrix  FABCs_by_yr(1,npro,1,nspp) 
+  matrix  FOFLs_by_yr(1,npro,1,nspp) 
+
+  // Inverse Gaussian Distn parameters
+  number gi_beta         
+  number gamma       
+  vector cvrec(1,nspp)
+  number delta
+  vector TAC(1,nspp)
+  vector ABC(1,nspp)
+  vector OFL(1,nspp)
+
+  vector AMeanSSB(1,nspp)
+  vector AMeanRec(1,nspp)
+  vector AMaxSSB(1,nspp)
+  vector HMeanRec(1,nspp)
+  vector Bcurrent(1,nspp)        
+  !! for (int i=1;i<=nspp;i++) Bcurrent(i) = pmature_F(i)*elem_prod(n0_F(i),wt_F(i));
+
+  number alpha
+  !! alpha = 0.05;
+  int ii;
+  int m;
+  int j;
+  number alphaCI
+  !! alphaCI = 0.1;
+  int UCI;
+  int LCI;
+  !! LCI = ( 1.0 + (      alphaCI *0.5  * 1.*nsims));
+  !! UCI = (((1.-alphaCI*0.5)*(nsims+1)) - 1.0);
+
+  !! cout<< "UCI "<< (1.-alphaCI*0.5) <<" "<<UCI <<" "<<LCI<<endl;
+
+  matrix  N_F(1,nspp,1,nages)
+  matrix  N_M(1,nspp,1,nages) 
+  matrix Nnext_F(1,nspp,1,nages) ;
+  matrix Nnext_M(1,nspp,1,nages) ;
+  number chi_prev
+  number chi
+  matrix Z_F(1,nspp,1,nages) ;
+  matrix Z_M(1,nspp,1,nages) ;
+  matrix S_F(1,nspp,1,nages) ;
+  matrix S_M(1,nspp,1,nages) ;
+  vector Cabc(1,nspp)        // Catch at equilibrium abc level
+  vector Cofl(1,nspp)        // Catch at equilibrium ofl level
+  vector F35(1,nspp)
+  vector Ftarg(1,nspp)       // Option to set target to the Fofl, Fabc, or F35
+  number Btmp;
+  number SBtmp;
+  3darray C_F(1,nspp,1,ngear,1,nages) ;
+  3darray C_M(1,nspp,1,ngear,1,nages) ;
+  vector F_yr_one(1,nspp) ; // F that gives TAC in TAC year
+  matrix F_begin_yr(1,nyrs_catch_in,1,nspp) ; // F that gives TAC in TAC year
+  vector Fabc(1,nspp)
+  vector F40(1,nspp)
+  vector Fofl(1,nspp)
+  matrix Ftotabc(1,nspp,1,nages);
+  matrix Ftot40(1,nspp,1,nages);
+  matrix Ftotofl(1,nspp,1,nages);
+  matrix N(1,nspp,1,nages) ;
+  matrix NsprF0(1,nspp,1,nages)
+  matrix NsprM0(1,nspp,1,nages)
+  matrix NsprFabc(1,nspp,1,nages)
+  matrix NsprMabc(1,nspp,1,nages)
+  matrix NsprF40(1,nspp,1,nages)
+  matrix NsprM40(1,nspp,1,nages)
+  matrix NsprFofl(1,nspp,1,nages)
+  matrix NsprMofl(1,nspp,1,nages)
+  vector SB100(1,nspp)
+  vector SBzero(1,nspp)
+  vector SBFabc(1,nspp)
+  vector SBF40(1,nspp)
+  vector SBKink(1,nspp)
+  vector SBFofl(1,nspp)
+  vector Avg_Age_Mabc(1,nspp)
+  vector Avg_Age_M0(1,nspp)
+  vector Avg_Age_Fabc(1,nspp)
+  vector Avg_Age_F0(1,nspp)
+  vector Avg_Age_End(1,nspp)
+  vector Avg_Age_Mat(1,nspp)
+  vector Avg_Age_sum(1,nspp)
+  vector BFabc(1,nspp)
+  vector BF40(1,nspp)
+  vector BFofl(1,nspp)
+  vector B100(1,nspp)
+ LOCAL_CALCS
+   N_F.initialize();
+   N_M.initialize(); 
+   Nnext_F.initialize(); 
+   Nnext_M.initialize(); 
+   chi = 0.;
+   chi_prev = 0.;
+   Z_F.initialize(); 
+   Z_M.initialize(); 
+   S_F.initialize(); 
+   S_M.initialize(); 
+   Cabc.initialize();        // Catch at equilibrium abc level
+   Cofl.initialize();        // Catch at equilibrium ofl level
+   F35.initialize();
+   Ftarg.initialize();
+   Btmp=0.0;
+   SBtmp=0.0;
+   C_F.initialize(); 
+   C_M.initialize(); 
+   F_yr_one.initialize();  // F that gives TAC in TAC year
+   F_begin_yr.initialize(); // F that gives TAC in TAC year
+   Fabc.initialize();
+   F40.initialize();
+   Fofl.initialize();
+   Ftotabc.initialize();
+   Ftot40.initialize();
+   Ftotofl.initialize();
+   N.initialize(); ;
+   BF40.initialize();
+   NsprF0.initialize();
+   NsprFabc.initialize();
+   NsprF40.initialize();
+   NsprFofl.initialize();
+   NsprM0.initialize();
+   NsprMabc.initialize();
+   NsprM40.initialize();
+   NsprMofl.initialize();
+   SB100.initialize();
+   SBzero.initialize();
+   SBFabc.initialize();
+   SBF40.initialize();
+   SBKink.initialize();
+   SBFofl.initialize();
+   Avg_Age_Fabc.initialize();
+   Avg_Age_F0.initialize();
+   BFabc.initialize();
+   BFofl.initialize();
+   B100.initialize();
+   Alt4_Fabc.initialize();
+ END_CALCS
+   number R_guess
+ // Compute an initial Rzero value based on exploitation 
+ LOCAL_CALCS
+   double btmp=0.;
+   double ctmp=0.;
+   for (int ispp=1;ispp<=nspp;ispp++)
+   {
+     dvector ntmp(1,nages(ispp));
+     ntmp(1) = 1.;
+     for (int a=2;a<=nages(ispp);a++)
+       ntmp(a) = ntmp(a-1)*exp(-M_F(ispp, a)-.05);
+
+     btmp += wt_F(ispp) * ntmp;
+     cout << "Mean Catch"<<endl;
+     ctmp += (Obs_Catch(1,ispp));
+     cout << ctmp <<endl;
+     R_guess = log((ctmp/.02 )/btmp) ;
+     cout << "R_guess "<<endl;
+     cout << R_guess <<endl;
+   }
+ END_CALCS
+  number phase_sr
+  !! if (Rec_Gen==3||Rec_Gen==4) phase_sr = -3; else phase_sr=1;
+
+
+
+INITIALIZATION_SECTION
+  steepness 0.78
+  sigr      0.5
+  // log_Rzero 6.1
+  log_Rzero R_guess
+
+PARAMETER_SECTION
+  // init_bounded_vector Fabc(1,nspp,0.00001,5)
+  // init_bounded_vector F40(1,nspp,0.00001,5)
+  // init_bounded_vector Fofl(1,nspp,0.00001,5)
+  init_bounded_vector log_Rzero(1,nspp,0,13,phase_sr)
+  init_bounded_vector steepness(1,nspp,0.2,1.0,phase_sr+1)
+  init_bounded_vector sigr(1,nspp,0.1,1.5,phase_sr+2)
+  init_number dummy(1)
+
+  vector sr_alpha(1,nspp);
+  vector beta(1,nspp);
+  vector Rzero(1,nspp);
+  vector rec_like(1,nspp);
+  // matrix pred_rec(1,nspp,1,nrec);
+  sdreport_vector Bzero(1,nspp);
+  vector phizero(1,nspp)
+  vector phi(1,nspp)
+  vector sigmaRsq(1,nspp);
+
+  vector MSY(1,nspp);
+  vector Fmsy(1,nspp);
+  vector Bmsy(1,nspp);
+  vector Rmsy(1,nspp);
+
+
+  vector sigmar(1,nspp)
+
+  objective_function_value obj_fun   
+
+ LOCAL_CALCS 
+   // Fill out R matrix (dimensioned species, sims, proj_yr)
+  cout<<"finished random numbers"<<endl;
+  rnorms.fill_randn(rnseed);
+  unifs.fill_randu(rnseed);
+  cout<<"finished random numbers"<<endl;
+  for (int ispp=1;ispp<=nspp;ispp++)
+  {
+   // Get parameter values for InvGauss
+
+    if (nsexes(ispp)==1) 
+      AMeanRec(ispp) = mean(R(ispp));  // Arithmetic mean
+    else
+      AMeanRec(ispp) = 2.*mean(R(ispp));  // Arithmetic mean
+
+    AMeanSSB(ispp) = mean(SSB(ispp));  // Arithmetic mean
+    AMaxSSB(ispp) = max(SSB(ispp));  // Arithmetic mean
+    HMeanRec(ispp) = 1./ mean(1./R(ispp));   // Harmonic mean
+
+   // Given Amean and Hmean, solve for parameters of inv gaussian
+    gamma = AMeanRec(ispp) / HMeanRec(ispp) ;
+    gi_beta  = AMeanRec(ispp) ;
+    delta = 1./(gamma - 1.);
+    cvrec(ispp) = sqrt(1./delta);
+
+  // Simulate inv-gaussian RV's
+    ifstream envin("envmat.dat"); // note can't have comments in top
+    for (int i=1;i<=nsims;i++)
+    {
+      for (j=1;j<=npro;j++)
+      {
+        double psi   = (square( rnorms(i,j) ));
+        double omega = gi_beta*(1.+(psi-sqrt(4.*delta*psi+square(psi)))/ (2.*delta));
+        double zeta  = gi_beta*(1.+(psi+sqrt(4.*delta*psi+square(psi)))/ (2.*delta));
+        double gtheta = gi_beta/(gi_beta+omega);
+        if (unifs(i,j) <= gtheta)
+          Rsim(ispp,i,j) = omega;
+        else 
+          Rsim(ispp,i,j) = zeta;
+        if (Rec_Gen==4)// environmental index
+        {
+          envin >>  Rsim(ispp,i,j);
+          Rsim(ispp,i,j) *= exp(rnorms(i,j)*.375); // about 15% CV to get historical mean
+        }
+       if (nsims<=5) Rsim(ispp,i,j) = AMeanRec(ispp); // XXX constant recruitment
+      }
+    }
+    envin.close();
+    AMeanRec(ispp) *= .5;  // Arithmetic mean
+    cout <<"recruits"<<endl;
+    // cout<< " Solving spp "<<ispp<<" "<<spname(ispp)<<" "<<yr_one_catch(ispp)<<" "; // <<N_F*wt_mature(ispp)<<" "<<N_F*wt_F(ispp)+N_M(ispp)*wt_F(ispp)<<" ";
+    for (int k=1;k<=nyrs_catch_in;k++)
+    {
+      if (Obs_Catch(k,ispp) > 0 )
+        F_begin_yr(k,ispp) = SolveF2(n0_F(ispp), n0_M(ispp), Obs_Catch(k,ispp),ispp); // F_yr_one(ispp) = SolveF2(n0_F(ispp), n0_M(ispp), yr_one_catch(ispp),ispp);
+      else
+        F_begin_yr(ispp) = 0; // F_yr_one(ispp) = 0; // cout<<spname(ispp)<<" "<<F_yr_one(ispp)<<" "<<yr_one_catch(ispp)<<endl;
+    }
+  } 
+
+  if (ad_comm::argc > 1) // Debugging if LP to be done or not
+  {
+    int on=0;
+    if ( (on=option_match(ad_comm::argc,ad_comm::argv,"-nolp"))>-1)
+      dolp=0;
+    else
+      dolp=1;
+  }
+ END_CALCS
+
+
+PRELIMINARY_CALCS_SECTION
+  double tmp1;
+  write_alts_hdr();
+  get_SB100();
+  cout<<"SSB, Biomass at unfished: "<<endl<<SB100<<endl<<B100<<endl;
+  for (int ispp=1;ispp<=nspp;ispp++)
+  {
+    cout <<ispp<<" SPR F35 = "<<get_spr_rates(0.35,ispp)<<" "<< spname(ispp)<<endl;
+    Fabc(ispp) = (get_spr_rates(SPR_abc(ispp),ispp));
+    cout<<"Alt4 SPR "<<Alt4_SPR(ispp)<<endl;
+    Alt4_Fabc(ispp) = get_spr_rates(Alt4_SPR(ispp),ispp);
+    cout<<"Alt4 Fabc: "<<Alt4_Fabc(ispp)<<endl;
+
+     F40(ispp) = (get_spr_rates(0.4,ispp));
+    Fofl(ispp) = (get_spr_rates(SPR_ofl(ispp),ispp));
+    F35(ispp)  = (get_spr_rates(.35,ispp));
+    Ftarg(ispp)= Fofl(ispp); 
+    targ_SPR(ispp) = SPR_ofl(ispp);
+  }
+
+PROCEDURE_SECTION
+  compute_obj_fun();
+  if (mceval_phase()) cout<<log_Rzero<<" "<<steepness<<" "<<sigr<<" "<<endl;
+
+FUNCTION Run_Sim
+  detail_out<<"Stock,Alt,Sim,Yr,SSB,Rec,Tot_biom,SPR_Implied,F,Ntot,Catch,ABC,OFL,AvgAge,AvgAgeTot,SexRatio,B0,B40,B35"<<endl;
+  for (int ispp=1;ispp<=nspp;ispp++)
+  {
+    Get_SPR_Catches(ispp);
+    percent_out <<endl;
+    write_sim_hdr(ispp);
+  }
+  for (int ialt=1;ialt<=nalts;ialt++)
+  {
+    alt = alt_list(ialt);
+
+    if (alt==2 && nyrs_catch_in >1) 
+      nyrs_catch = nyrs_catch_in;
+    else 
+      nyrs_catch = 1;// NOTA BUENO: this is changed under the new EIS Alternatives (May 06)
+    Do_Sims();
+    // if (alt==2) write_alts();
+    write_alts();
+  }
+
+FUNCTION  compute_obj_fun
+  dvariable tmp1;
+  dvariable tmp2;
+  tmp1.initialize();
+  for (int ispp=1;ispp<=nspp;ispp++)
+  {
+    Get_Bzero(ispp);
+   // write_srec();exit(1);
+    if(Fmsy_F35>0) 
+    {
+      get_msy(ispp);
+      switch (current_phase())
+      {
+        case 1 : tmp1 =  1.e1*square(log(Fmsy(ispp))-log(F35(ispp))); break;
+        case 2 : tmp1 =  1.e2*square(log(Fmsy(ispp))-log(F35(ispp))); break;
+        case 3 : tmp1 =  1.e2*square(log(Fmsy(ispp))-log(F35(ispp))); break;
+        case 4 : tmp1 =  1.e3*square(log(Fmsy(ispp))-log(F35(ispp))); break;
+        default: tmp1 =  1.e3*square(log(Fmsy(ispp))-log(F35(ispp))); break;
+      }
+      if(Fmsy_F35==2) 
+      switch (current_phase())
+      {
+        case 1 : tmp1 +=  1.e1*square(log(Bmsy(ispp))-log(0.35 * SB100(ispp))); break;
+        case 2 : tmp1 +=  1.e2*square(log(Bmsy(ispp))-log(0.35 * SB100(ispp))); break;
+        case 3 : tmp1 +=  1.e2*square(log(Bmsy(ispp))-log(0.35 * SB100(ispp))); break;
+        case 4 : tmp1 +=  1.e3*square(log(Bmsy(ispp))-log(0.35 * SB100(ispp))); break;
+        default : tmp1+=  1.e3*square(log(Bmsy(ispp))-log(0.35 * SB100(ispp))); break;
+      }
+      obj_fun += tmp1;
+    }
+    if (Rec_Cond>0.)
+    {
+      // More conditioning here--make mean recruitment consistent with half and double 
+      // recruitment at avg spawning biomass...
+      double vartmp = 2.*Rec_Cond*Rec_Cond;
+      /* 
+      double ssb1 = AMeanSSB(ispp) * 0.5;
+      double ssb2 = AMeanSSB(ispp)      ;
+      double ssb3 = AMeanSSB(ispp) * 2.0;
+      // double ssb4 = value(Bzero(ispp)) ;
+      tmp2.initialize();
+      tmp2 +=      square(log(AMeanRec(ispp)) - log(SRecruit( ssb1, ispp)))/ vartmp;
+      tmp2 +=      square(log(AMeanRec(ispp)) - log(SRecruit( ssb2, ispp)))/ vartmp;
+      tmp2 +=      square(log(AMeanRec(ispp)) - log(SRecruit( ssb3, ispp)))/ vartmp;
+      // tmp2 += 24.* square(log(AMeanRec(ispp)) - log(SRecruit( ssb4, ispp)));
+      // tmp2 += 24.* square(log(AMeanSSB(ispp)) - log( ssb4 ));
+      */
+      tmp2 =      square(log(Bzero(ispp)) - log(SB100(ispp)))/ vartmp;
+      obj_fun += tmp2;
+      // cout << "SSB "<<ssb1<<" " <<ssb2<<" "<< ssb3<<" "<<ssb4<< " "<<tmp2<<endl;
+    }
+    Recruitment_Likelihood(ispp);
+    // cout<<"Tmp1 "<<tmp1<<" "<<rec_like<<" "<<obj_fun<<endl;
+
+    // Add a diffuse prior on steepness...
+    /* if (active(steepness)) {
+      dvariable steeptmp;
+      steeptmp = (steepness(ispp) - .2) /.8 ;
+      obj_fun -= ((srprior_a-1.)*log(steeptmp) + (srprior_b-1)*log(1.-steeptmp));
+    }
+    */
+  }
+  obj_fun += dummy*dummy;
+
+FUNCTION Do_Sims
+  /* Have to do in steps: 1) find TAC value for catch 2) compute constraint vector 3) optimize given those constraints 4) get realized catches based on optimization 5) project population to next year, restart from step 3) */
+  Avg_Age_End.initialize();
+  Avg_Age_sum.initialize();
+  OFLs_by_yr.initialize();
+  TACs_by_yr.initialize();
+  ABCs_by_yr.initialize();
+  for (int ispp=1;ispp<=nspp;ispp++) 
+  {
+    Get_Bzero(ispp);
+    get_msy(ispp);
+  }
+  for (isim=1;isim<=nsims;isim++)         // +++++++++++Sim
+  {
+    N_F = n0_F       ;  // Initialize N's only once per simulation
+    N_M = n0_M       ;
+   // Loop over projection years
+   for (ipro=1;ipro<=npro;ipro++) 
+   { // call and get TAC's fo this species in this year...
+     //////////////////////////////////////////////////////////////////////////////
+     //  TAC_ABC=1; // need to put bck
+     //////////////////////////////////////////////////////////////////////////////
+     TAC.initialize();
+     Expl_Biom.initialize();
+     for (int ispp=1;ispp<=nspp;ispp++) 
+     {
+       // cout<<rec_vector<<endl;
+       rec_vector(1,nrec(ispp)) = R(ispp);
+       // cout<<rec_vector<<endl;
+
+       // cout<< rec_vector(nrec(ispp)+1,nrec(ispp)+npro).indexmin()<<endl;
+       // cout<< rec_vector(nrec(ispp)+1,nrec(ispp)+npro+1).indexmax()<<endl;
+
+       // cout<<( Rsim(ispp,isim).shift(nrec(ispp)+1)).indexmin()<<endl;
+       // cout<<( Rsim(ispp,isim).shift(nrec(ispp)+1)).indexmax()<<endl;
+
+       rec_vector((nrec(ispp)+1),(nrec(ispp)+npro+1)) = Rsim(ispp,isim).shift(nrec(ispp)+1);
+       Rsim(ispp,isim).shift(1); 
+       // cout<<rec_vector<<endl;
+       
+       ABC(ispp)       =   ABC_Multiplier(ispp) * Get_Catch(alt,ispp); // ABC_multiplier is from setup.dat
+       OFL(ispp)       =    Get_Catch(6,ispp); 
+       // if (alt!=2) 
+        ABCs_by_yr(ipro,ispp) += Get_Catch(1,ispp);
+       // else 
+        // ABCs_by_yr(ipro,ispp) = ABC(ispp);  // Cumulate ABCs here for printout later...
+     }
+     // Now get actual catch...  
+     if (ipro <= nyrs_catch && !(alt == 6 || alt == 7)) // use observed catches from setup file for the first year(s)
+     {
+       for (int ispp=1;ispp<=nspp;ispp++) 
+       {
+         Actual_Catch(ispp) = Obs_Catch(ipro,ispp); 
+         // Actual_Catch(ispp) = min(ABC(ispp),Obs_Catch(ipro,ispp)); // NOTA BUENO: May 06 change
+         // cout<< alt<<" "<<spname(ispp)<<" "<< ABC(ispp)<<" "<<Obs_Catch(ipro,ispp)<<" "<<Actual_Catch(ispp)<<endl; // NOTA BUENO: May 06 change
+       }
+     }
+     else  // Build in condition to get TAC different than ABC...
+     {
+       if (ipro==1)
+       {
+         for (int ispp=1;ispp<=nspp;ispp++) 
+           Actual_Catch(ispp) = Obs_Catch(ipro,ispp); 
+       }
+       else // not the first year... for 7 and 6
+       {
+         if (TAC_ABC==1)
+         {
+           TAC = ABC;
+           if (alt == 4)
+             Alt4_TAC();       
+           if (alt == 6 || alt == 7) 
+             Status_Determ();
+           else // Most alternatives fall here...
+           {
+             if ((alt==2 ||alt==98||alt==97) && sum(TAC)>OY_max)
+               Actual_Catch   = TAC/sum(TAC)*OY_max; 
+             else
+               Actual_Catch   = TAC; 
+           }
+         /* ////////////////////////////////////////////////////////////////////////////// //int use_max = 1; // Need to move this into the setup file...  double max_catch=1500.;// EBS POllock special case (CHANGE THIS) //if (use_max==1) for (int ispp=1;ispp<=nspp;ispp++) Actual_Catch(ispp)   = min(TAC(ispp),max_catch); // cout<<"AC: "<<Actual_Catch(1,6)<<endl;; TAC_ABC=0; ////////////////////////////////////////////////////////////////////////////// */
+         }
+         else
+         {
+           Fit_TAC();
+         }
+       }
+     }
+
+     TACs_by_yr(ipro) += TAC; // Cumulate TACs here for printout later...
+     OFLs_by_yr(ipro) += OFL; // Cumulate OFLs here for printout later...
+     Project_Pops(isim,ipro); //cout << "Done projection"<<endl; //cout <<"Csim: "<<isim<<" "<<i<<" "<<Csim(1,isim,i) <<" "<< endl; //cout << "Yr_"<<i+styr-1<<"_Expl "<< Expl_Biom<<endl;
+   // OjO, looping for long term projections...need to compute the average coefficients from past
+    // Mainloop(npro+1,npro+15,isim);
+    Avg_Age();
+
+     for (int ispp=1;ispp<=nspp;ispp++) 
+       detail_out     <<      spname(ispp) 
+                      <<","<< alt        
+                      <<","<< isim        
+                      <<","<< styr+ipro-1
+                      <<","<<SBsim(ispp,isim,ipro)
+                      <<","<< Rsim(ispp,isim,ipro)
+                      <<","<<Bsim(ispp,isim,ipro)
+                      <<","<<SPRsim(ispp,isim,ipro)
+                      <<","<<Fsim(ispp,isim,ipro)  
+                      <<","<<Nsim(ispp,isim,ipro) 
+                      <<","<<Actual_Catch(ispp)
+                      <<","<<ABC(ispp)
+                      <<","<<OFL(ispp)
+                      <<","<<Avg_Age_Mat(ispp)
+                      <<","<<Avg_Age_End(ispp)
+                      <<","<<SRsim(ispp,isim,ipro)
+                      <<","<<SB100(ispp)
+                      <<","<<SB100(ispp)*.4
+                      <<","<<SB100(ispp)*.35
+											<< endl;
+   } // Loop over projection years
+
+  }  // Loop over Sims
+  for (int ispp=1;ispp<=nspp;ispp++)
+  {
+      // Get_SPR_Catches(ispp);
+    if (nsims>2)
+       write_sim("Alternative ",ispp);
+  }
+  write_by_time();
+
+
+FUNCTION Alt4_TAC
+  // Return vector of Alt4 TACs (given Alt4_Fabc, and the SSL prey condition to be at least up to SSL MaxPerm)
+  // Get all ABCs under Alt4_Fabc
+  // Sum and test if below OY_min
+     double sumabc;
+     sumabc = sum(ABC);
+     if (sumabc<OY_min&&nspp>3)
+     {
+       Alt4_Fcalc = 1;
+       double diff;
+       double ssl_sum=0.;
+       diff = OY_min-sumabc;
+       // if so, sum up SSL ABCs
+       ssl_sum = SSL_spp*ABC;
+       for (int ispp=1;ispp<=nspp;ispp++) 
+       {
+         // then apportion them to difference between current ABC and target (OY_min) difference
+         if (SSL_spp(ispp))
+         {
+           TAC(ispp) = ABC(ispp) + diff * ABC(ispp)/ssl_sum;
+           // Special for BSAI Pcod to subtract off 3%...and get the totals to match up
+           // if (ispp==2) TAC(ispp) /= 0.97; For EIS work
+         }
+         else
+         {
+           TAC(ispp) = ABC(ispp);
+         }
+       }
+       // cout << ipro<<" "<<sum(TAC)<<" "<<sumabc<<" "<<diff+sumabc<<endl;
+     }
+     else
+     {
+       Alt4_Fcalc = 0;
+       TAC = ABC;
+     }
+
+  // Then given new "catches" solve for Fabc for that species
+     // Ftmp = SolveF2(N_F(ispp),N_M(ispp),Actual_Catch(ispp),ispp);
+     // for (int ispp=1;ispp<=nspp;ispp++) Actual_Catch(ispp) = Obs_Catch(ipro,ispp); dd=   ABC_Multiplier(ispp) * Get_Catch(alt,ispp); // ABC_multiplier is from setup.dat
+
+ // Get_Catch ==============================================================================------------------
+FUNCTION double Get_Catch(const int& thisalt, const int& ispp)
+  double Ftmp;
+  dvector Ftottmp_F(1,nages(ispp));
+  dvector Ftottmp_M(1,nages(ispp));
+  // Set a good starting guess for spawning biomass 
+  SBtmp = (N_F(ispp) * elem_prod( wt_mature_F(ispp), mfexp( -yrfrac(ispp)*(M_F(ispp) + Ftotabc(ispp) )))); 
+
+  // Calls Get_F_t to compute the current year's F (as a function of stock size, species etc)
+  Ftmp = 0.0; 
+  Ftmp = Get_F(thisalt, ispp);
+  Ftottmp_F.initialize();
+  Ftottmp_M.initialize();
+  for (m=1;m<=ngear(ispp);m++)
+  {
+    Ftottmp_F += Ftmp*Frat(ispp,m)*sel_F(ispp,m);
+    Ftottmp_M += Ftmp*Frat(ispp,m)*sel_M(ispp,m);
+  }
+  SBtmp = N_F(ispp) * elem_prod( wt_mature_F(ispp), mfexp( -yrfrac(ispp)*(M_F(ispp) + Ftottmp_F))); 
+  
+  Z_F(ispp) = Ftottmp_F  + M_F(ispp); 
+  Z_M(ispp) = Ftottmp_M  + M_M(ispp); 
+  S_F(ispp) = mfexp( -Z_F(ispp) );
+  S_M(ispp) = mfexp( -Z_M(ispp) );
+  
+  // Get catch-at-age for each fishery (since avg wts may be different)...
+  double ctmp;
+  ctmp = 0.;
+  Ftottmp_F.initialize();
+  Ftottmp_M.initialize();
+  for (m=1;m<=ngear(ispp);m++)
+  {
+    Ftottmp_F = Ftmp*Frat(ispp,m)*sel_F(ispp,m);
+    Ftottmp_M = Ftmp*Frat(ispp,m)*sel_M(ispp,m);
+    ctmp += wt_gear_F(ispp,m) * elem_prod(elem_div(Ftottmp_F,  Z_F(ispp)),elem_prod(1.-S_F(ispp),N_F(ispp))); // Catch equation (vectors)
+    ctmp += wt_gear_M(ispp,m) * elem_prod(elem_div(Ftottmp_M,  Z_M(ispp)),elem_prod(1.-S_M(ispp),N_M(ispp))); // Catch equation (vectors)
+  }
+  // cout<< ipro<<" "<<ctmp<<" "<<wt_gear_M(ispp,1) * elem_prod(elem_div(Ftottmp_M,  Z_M(ispp)),elem_prod(1.-S_M(ispp),N_M(ispp))) ; cout<<" "<< wt_gear_F(ispp,1) * elem_prod(elem_div(Ftottmp_F,  Z_F(ispp)),elem_prod(1.-S_F(ispp),N_F(ispp)))<<endl;
+  // if (ipro==3) {cout<<"New "<<mean(wt_gear_F(ispp,1))<<" "<<N_F(ispp)<<endl;exit(1);}
+  // cout<<spname(2)<<" Ftotabc c "<<Ftotabc(2)(1,3)<<endl;
+  return(ctmp);
+  
+ // Get F and catch givent ALT==============================================================================
+FUNCTION double Get_F(const int& thisalt,const int& ispp)
+  double ftmp;
+  dvector F_age_tmp(1,nages(ispp));
+  F_age_tmp.initialize(); // THIS is for selectivity for combined gears...
+  for (m=1;m<=ngear(ispp);m++)
+    F_age_tmp += Frat(ispp,m) * sel_F(ispp,m);
+
+  if (Tier==1)
+  {
+    SBKink(ispp) = value(Bmsy(ispp));
+    SBzero(ispp) = value(Bzero(ispp));
+    // cout<<SBKink(ispp)<<endl;exit(1);
+  }
+  else
+  {
+    SBKink(ispp)=(SBF40(ispp));
+    SBzero(ispp) = SB100(ispp);
+  }
+  double F1;
+  double F2;
+  double temp_F;
+  // Test for FMP species else do basic F
+  {
+    switch (thisalt) 
+    {
+      case 1 : // Max ABC
+        ftmp = Get_F_t( F_age_tmp, N_F(ispp), ispp); 
+        break;
+
+      case 2 : // Auth ABC
+        if (Const_Buffer(ispp)) // Dorn's constant buffer (data file option)
+        {
+          // FABC_Adj is from the Species file
+          SBKink(ispp) = SBF40(ispp)*Fofl(ispp)/F40(ispp);
+          ftmp = FABC_Adj(ispp) * Get_F_t( F_age_tmp, N_F(ispp), ispp); 
+          SBKink(ispp) = SBF40(ispp);
+        }
+        else
+          ftmp = FABC_Adj(ispp) * Get_F_t( F_age_tmp, N_F(ispp), ispp); 
+
+        ftmp *= ABC_Multiplier(ispp); // use the multiplier in _spcat.dat file also...
+        break;
+
+      // Old case 3 : // Half max F ftmp = 0.5 * Get_F_t( F_age_tmp, N_F(ispp), ispp); 
+      case 3 :  // Old alt 4
+        ftmp = avg_5yrF(ispp); 
+        break;
+
+      case 4 : // New Alt 4
+        temp_F = Fabc(ispp);
+        F1 = Alt4_Fabc(ispp);// SolveF2(N_F(ispp),N_M(ispp),TAC(ispp),ispp);
+        F2 = Get_F_t( F_age_tmp, N_F(ispp), ispp); 
+        if (F1<F2)
+          ftmp = F1;
+        else
+          ftmp = F2;
+         // cout <<ipro<<" "<<spname(ispp)<<" "<<ftmp<<" "<<F1<<" "<<TAC(ispp)<<" "<<Actual_Catch(ispp)<<" "<<F2<<" "<<SBF40(ispp)<<" "<<SBtmp<<endl;
+        // Fabc(ispp) = Alt4_Fabc(ispp);
+        // Need to get minimum for SSL species...
+        if (Alt4_Fcalc && SSL_spp(ispp))
+        {
+         if (TAC(ispp)>0.01) ftmp = SolveF2(N_F(ispp),N_M(ispp),TAC(ispp),ispp);
+         // cout <<ipro<<" "<<spname(ispp)<<" "<<ftmp<<" "<<F1<<" "<<TAC(ispp)<<" "<<Actual_Catch(ispp)<<" "<<F2<<" "<<SBF40(ispp)<<" "<<SBtmp<<endl;
+        }
+        break;
+
+      case 5 : 
+        ftmp = 0.0;
+        break;
+
+      case 6:  //  Threshold Determination Note: uses TAC=ABC 
+        ftmp = Get_Fofl_t( F_age_tmp, N_F(ispp), ispp); 
+        break;
+      case 66:  //  Threshold Determination Note: uses TAC=ABC 
+        ftmp = Get_Fofl_t2( F_age_tmp, N_F(ispp), ispp); 
+        break;
+
+      case 7:  //  Threshold Determination Note: does NOT use TAC=ABC 
+        ftmp = Get_Fofl_t( F_age_tmp, N_F(ispp), ispp); 
+        break;
+
+      case 32 : 
+        // Alt 3.2 affects here (Grant's correction)
+        // Returns value of F for specified Fofl OR Ammendment 56 value, whichever is lower
+        // Risk-averse ARY Fabc level
+        // F1 = FABC_Adj(ispp) * value(Fofl(ispp));  // This is unadjusted
+        F1 = FABC_Adj(ispp) * Get_Fofl_t( F_age_tmp, N_F(ispp), ispp); // Apply adjustment to Amm56 OFL
+        F2 = Get_F_t( F_age_tmp, N_F(ispp), ispp); // Simply Amm 56 F with SSL protection
+        if (F1<F2)
+          ftmp = F1;
+        else
+          ftmp = F2;
+        break;
+      case 41 : 
+        ftmp = FABC_Adj(ispp) * Get_F_t( F_age_tmp, N_F(ispp), ispp); 
+        break;
+      case 42 : 
+        ftmp = .0;
+        break;
+      case 97 : 
+      // Teresa's wtd rec mean
+         
+        wtd_rec.initialize();
+        double sumtmp; 
+        for (int ii=1;ii<=nages(ispp);ii++)
+        {
+          sumtmp=0.;
+          for (int j=1;j<ii;j++) 
+            sumtmp -= M_F(ispp,j);
+          wtd_rec(ii) += pmature_F(ispp,ii)*wt_F(ispp,ii)*
+                         rec_vector(nrec(ispp)+1+ipro-ii)*exp(sumtmp);
+        }
+        for (int ii=nages(ispp)+1;ii<=25;ii++)
+        {
+          for (int j=1;j<ii;j++) 
+            sumtmp -= M_F(ispp,nages(ispp));
+          wtd_rec(ii) += pmature_F(ispp,nages(ispp))*wt_F(ispp,nages(ispp))*
+                         rec_vector(nrec(ispp)+1+ipro-ii)*exp(sumtmp);
+        }
+        kink_adj = .5*(sum(wtd_rec) / sum(wtd_div)) /AMeanRec(ispp);
+        // cout<<"Teresa "<<kink_adj<<endl;
+        SBKink(ispp) = kink_adj*SBF40(ispp);
+        SBzero(ispp) = kink_adj*SB100(ispp);
+        ftmp = Get_F_t( F_age_tmp, N_F(ispp), ispp); 
+        break;
+
+      // Special case to adjust kink by recent recruitments...
+      case 98 : 
+        kink_adj = .5*mean(rec_vector(nrec(ispp)+1+ipro-20,nrec(ispp)+ipro)) /AMeanRec(ispp);
+        // cout << "Isim "<<isim<<" "<<ipro<<" "<<kink_adj<<endl;// Rsim(ispp,isim,ipro)<<" "<<mean(R(ispp))<<" "<< mean(rec_vector(nrec(ispp)+1+ipro-20,nrec(ispp)+ipro)) <<" "<<AMeanRec(ispp)<<endl; // cout<<rec_vector<<endl;exit(1);
+        SBKink(ispp) = kink_adj*SBF40(ispp);
+        SBzero(ispp) = kink_adj*SB100(ispp);
+        ftmp = Get_F_t( F_age_tmp, N_F(ispp), ispp); 
+        break;
+      case 99 : 
+        // Simply a constant rate--equals the ABC, no cap?
+        ftmp = (Fabc(ispp));
+        break;
+
+      default  :
+        if (Const_Buffer(ispp)) // Constant Dorn buffer 
+        {
+          SBKink(ispp) = SBF40(ispp)*Fofl(ispp)/F40(ispp);
+          ftmp = FABC_Adj(ispp) * Get_F_t( F_age_tmp, N_F(ispp), ispp); 
+          SBKink(ispp) = SBF40(ispp);
+        }
+        else
+          ftmp = FABC_Adj(ispp) * Get_F_t( F_age_tmp, N_F(ispp), ispp); 
+        break;
+    }
+  }
+  return(ftmp);
+
+FUNCTION double Get_F_SSL_prey(const dvector& F_age, const dvector& N_females, const int ispp )
+  double Ftmp; // cout<< spname(ispp)<< endl;
+  for (ii=1;ii<=3;ii++) // Iterate to get month of spawning correct
+  {
+    if (SBtmp < 0.2*SBzero(ispp))  // NOTE 20% of SB100%
+      Ftmp = 0.;
+    if (SBtmp >= 0.2 *SBzero(ispp) & SBtmp < SBKink(ispp) )  // NOTE Same as Am 56 here (until 20% bzero reached)
+      Ftmp = (Fabc(ispp)*(1/(1-alpha ))*(SBtmp/SBKink(ispp) - alpha ));
+    if (SBtmp > SBKink(ispp) )
+      Ftmp = (Fabc(ispp));
+    SBtmp = N_females * elem_prod( wt_mature_F(ispp), mfexp( -yrfrac(ispp)*(M_F(ispp) + Ftmp*F_age ))); 
+  }
+  return(Ftmp);
+
+FUNCTION double Get_F_Am56(const dvector& F_age, const dvector& N_females, const int ispp )
+  double Ftmp; // cout<< spname(ispp)<< endl;
+  {
+    for (ii=1;ii<=3;ii++) // Iterate to get month of spawning correct
+    {
+      if (SBtmp < alpha*SBKink(ispp))
+        Ftmp = 0.;
+      if (SBtmp >= alpha*SBKink(ispp) & SBtmp < SBKink(ispp) )
+        Ftmp = (Fabc(ispp)*(1/(1-alpha))*(SBtmp/SBKink(ispp) - alpha));
+      if (SBtmp > SBKink(ispp) )
+        Ftmp = (Fabc(ispp));
+      SBtmp = N_females * elem_prod( wt_mature_F(ispp), mfexp( -yrfrac(ispp)*(M_F(ispp) + Ftmp*F_age ))); 
+    }
+  }
+  return(Ftmp);
+
+FUNCTION double Get_Fofl_t2(const dvector& F_age, const dvector& N_females, const int ispp )
+  double Ftmp; // cout<< spname(ispp)<< endl;
+  {
+    for (ii=1;ii<=3;ii++) // Iterate to get month of spawning correct
+    {
+      if (SBtmp < alpha*SBKink(ispp))
+        Ftmp = 0.;
+      if (SBtmp >= alpha*SBKink(ispp) & SBtmp < SBKink(ispp) )
+        Ftmp = (Fofl(ispp)*(1/(1-alpha))*(SBtmp/SBKink(ispp) - alpha));
+      if (SBtmp > SBKink(ispp) )
+        Ftmp = (Fofl(ispp));
+      SBtmp = N_females * elem_prod( wt_mature_F(ispp), mfexp( -yrfrac(ispp)*(M_F(ispp) + Ftmp*F_age ))); 
+    }
+  }
+  return(Ftmp);
+
+FUNCTION double Get_Fofl_t(const dvector& F_age, const dvector& N_females, const int ispp )
+  double Ftmp; // cout<< spname(ispp)<< endl;
+  {
+    for (ii=1;ii<=3;ii++) // Iterate to get month of spawning correct
+    {
+      if (SBtmp < alpha*SBKink(ispp))
+        Ftmp = 0.;
+      if (SBtmp >= alpha*SBKink(ispp) & SBtmp < SBKink(ispp) )
+        Ftmp = (Fofl(ispp)*(1/(1-alpha))*(SBtmp/SBKink(ispp) - alpha));
+      if (SBtmp > SBKink(ispp) )
+        Ftmp = (Fofl(ispp));
+      SBtmp = N_females * elem_prod( wt_mature_F(ispp), mfexp( -yrfrac(ispp)*(M_F(ispp) + Ftmp*F_age ))); 
+    }
+  }
+  return(Ftmp);
+
+
+FUNCTION double Get_F_t(const dvector& F_age, const dvector& N_females, const int ispp )
+  double Ftmp; // cout<< spname(ispp)<< endl;
+  if (SSL_spp(ispp))
+  {
+    Ftmp = Get_F_SSL_prey(F_age, N_females, ispp);
+  }
+  else
+  {
+    Ftmp = Get_F_Am56(F_age, N_females, ispp);
+  }
+  return(Ftmp);
+
+FUNCTION void Project_Pops(const int& isim, const int& i)
+  double ctmp;
+  if ( i == npro && isim%int(nsims/4)==0) cout << "Year "<<styr + i -1<<" Sim: "<< isim <<" Alternative "<<alt<<endl;
+  // This is where the populations get updated (after ACTUAL catches and F's have been figured out)
+  for (int ispp=1;ispp<=nspp;ispp++) // ++++++++++++++Species
+  {
+    // if ( ! isit_const(ispp) )
+    {
+      double Ftmp;
+      Ftmp=0.0;
+      dvector Ftottmp_spr(1,nages(ispp));
+      dvector Ftottmp_F(1,nages(ispp));
+      dvector Ftottmp_M(1,nages(ispp));
+      SBtmp = (N_F(ispp) * elem_prod( wt_mature_F(ispp), mfexp( -yrfrac(ispp)*(M_F(ispp) + Ftotabc(ispp) )))); 
+      
+      if (Actual_Catch(ispp) > 0)
+      {
+        if (i <= nyrs_catch || TAC_ABC==0) // Use TAC setting  algorithm for alt 2 only, for all others, set TAC==ABC
+        {
+          Ftmp = SolveF2(N_F(ispp),N_M(ispp),Actual_Catch(ispp),ispp);
+        }
+        else
+        {
+          if (alt==7 && i<=3)
+            Ftmp = Get_F(1,ispp); // Set to the F rather than solving every time...
+          else
+            if (alt==77 && i<=2)
+              Ftmp = Get_F(1,ispp); // Set to the F rather than solving every time...
+            else
+          {
+            // if (alt==2 && sum(TAC)>OY_max)
+             if ((alt==2 ||alt==98||alt==97) && sum(TAC)>OY_max)
+            {
+              Ftmp = SolveF2(N_F(ispp),N_M(ispp),OY_max*TAC(ispp)/sum(TAC),ispp);
+              // cout<<"HERE "<< Ftmp<<" "<<OY_max*TAC(ispp)/sum(TAC)<<endl;
+            }
+            else
+              Ftmp = Get_F(alt,ispp); // Set to the F rather than solving every time...
+          }
+        }
+      }
+      else
+      {
+        Ftmp = 0.;
+        SPRsim(ispp,isim,i) =  1.0;
+      }
+      
+      Ftottmp_F.initialize();
+      Ftottmp_M.initialize();
+      SBtmp = 0.;
+      Btmp = 0.;
+      for (m=1;m<=ngear(ispp);m++)
+      {
+        Ftottmp_F += Ftmp*Frat(ispp,m)*sel_F(ispp,m);
+        Ftottmp_M += Ftmp*Frat(ispp,m)*sel_M(ispp,m);
+      }
+      SBtmp = (N_F(ispp) * elem_prod( wt_mature_F(ispp), mfexp( -yrfrac(ispp)*(M_F(ispp) + Ftottmp_F)))); 
+      Btmp = (N_F(ispp) * wt_F(ispp) + N_M(ispp) * wt_M(ispp));
+      
+      Z_F(ispp) = Ftottmp_F  + M_F(ispp); 
+      Z_M(ispp) = Ftottmp_M  + M_M(ispp); 
+      S_F(ispp) = mfexp( -Z_F(ispp) );
+      S_M(ispp) = mfexp( -Z_M(ispp) );
+      
+      // Graduate to next year...
+      Nnext_F(ispp)(2,nages(ispp))= ++elem_prod(N_F(ispp)(1,nages(ispp)-1), S_F(ispp)(1,nages(ispp)-1));
+      Nnext_M(ispp)(2,nages(ispp))= ++elem_prod(N_M(ispp)(1,nages(ispp)-1), S_M(ispp)(1,nages(ispp)-1));
+      
+      Nnext_F(ispp)(nages(ispp))  += N_F(ispp)(nages(ispp))*S_F(ispp)(nages(ispp));
+      Nnext_M(ispp)(nages(ispp))  += N_M(ispp)(nages(ispp))*S_M(ispp)(nages(ispp));
+      
+      // Set populations in next year according to SRR (option 2) or standard approach (past recruitment levels and variation, option 1)
+      if (Rec_Gen==1||Rec_Gen==4)
+      {
+        Nnext_F(ispp)(1) = Rsim(ispp,isim,i)/2.;
+        Nnext_M(ispp)(1) = Rsim(ispp,isim,i)/2.;
+      }
+      else // use the curve...
+      {
+        // cout<<sigr(ispp)<<endl<<Bzero(ispp)<<endl<<SBtmp<<endl<<rnorms(isim,i)<<endl;
+        // Nnext_F(ispp)(1) = value(exp(rnorms(isim,i)*sigr(ispp)) *SRecruit( SBtmp, ispp))/2.;
+        chi = value(rho_in*chi_prev + sqrt(1.-rho_in*rho_in)*rnorms(isim,i)*sigr(ispp));
+        Rsim(ispp,isim,i) = value(exp(chi) * SRecruit(SBtmp, ispp));
+        // Rsim(ispp,isim,i) = value(exp(rnorms(isim,i)*sigr(ispp)) *SRecruit( SBtmp, ispp));
+        // cout<<SRecruit(SBtmp,ispp)<<" "<<Rsim(ispp,isim,i)<<" "<<sigr<<" "<<chi<<" "<<chi_prev<<" "<<rho_in<<endl;
+        Nnext_F(ispp)(1)  = Rsim(ispp,isim,i)/2;
+        Nnext_M(ispp)(1)  = Nnext_F(ispp)(1); 
+        chi_prev=chi;
+      }
+      // Get catch-at-age for each fishery (since avg wts may be different)...
+      Ftottmp_F.initialize();
+      Ftottmp_spr.initialize();
+      Ftottmp_M.initialize();
+      ctmp = 0.;
+      SPRsim(ispp,isim,i) =  1.0;
+      if (Ftmp > 0.)
+      {
+        for (m=1;m<=ngear(ispp);m++)
+        {
+          Ftottmp_F  = Ftmp*Frat(ispp,m)*sel_F(ispp,m);
+          Ftottmp_spr += Ftottmp_F ; 
+          Ftottmp_M  = Ftmp*Frat(ispp,m)*sel_M(ispp,m);
+          ctmp += (wt_gear_F(ispp,m) * elem_prod(elem_div(Ftottmp_F,  Z_F(ispp)),elem_prod(1.-S_F(ispp),N_F(ispp)))); // Catch equation (vectors)
+          ctmp += (wt_gear_M(ispp,m) * elem_prod(elem_div(Ftottmp_M,  Z_M(ispp)),elem_prod(1.-S_M(ispp),N_M(ispp)))); // Catch equation (vectors)
+        }
+        SPRsim(ispp,isim,i) =  Implied_SPR(Ftottmp_spr,ispp);
+        // cout <<spname(ispp)<<" "<<i<< " "<<SPRsim(ispp,isim,i)<<endl;
+      }
+      /* cout << spname(ispp) <<endl << elem_prod(elem_div(Ftottmp_F,  Z_F(ispp)),elem_prod(1.-S_F(ispp),N_F(ispp))) <<endl << N_F(ispp)<<endl << Ftottmp_F<<endl;;//<<" "<<Csim(ispp,isim,i)<<" "<<N_F(ispp)<<endl; */
+  
+      // Store results 
+      Csim(ispp,isim,i)   = ctmp ;
+      // if (nsims < 5) if ( ispp <=3 ) cout <<"solving "<< spname(ispp)<<" Act_Catch "<< Actual_Catch(ispp)<<" Csim_Catch "<< Csim(ispp,isim,i) <<endl;
+      Fsim(ispp,isim,i)   = Ftmp; 
+      SBsim(ispp,isim,i)  = SBtmp; 
+      double ntot_tmp_F   = pmature_F(ispp) * N_F(ispp); 
+      double ntot_tmp_M   = pmature_M(ispp) * N_M(ispp); 
+      Nsim(ispp,isim,i)  = ntot_tmp_F + ntot_tmp_M; // sum(N_F + N_M) ; 
+      SRsim(ispp,isim,i)  = ntot_tmp_F / Nsim(ispp,isim,i) ; 
+      // cout <<isim<<" "<<i<<" "<<Btmp<<" "<<N_F<<" "<<N_M<<" "<< wt_F <<" "<< wt_M<<endl;
+      Bsim(ispp,isim,i)   = Btmp; 
+      Expl_Biom(ispp)     = Btmp;
+  
+      // Since this is the projection part, make sure to store next year's numbers...
+      N_F(ispp) = Nnext_F(ispp);
+      N_M(ispp) = Nnext_M(ispp);
+    }
+  }   // Loop over species ending Projection Part
+
+FUNCTION Status_Determ
+  if (alt == 6)
+    for (int ispp=1;ispp<=nspp;ispp++) 
+      Actual_Catch   = Get_Catch(alt,ispp);
+  if (alt == 7)
+  {
+    if (ipro<=3)
+    {
+      for (int ispp=1;ispp<=nspp;ispp++) 
+        Actual_Catch = Get_Catch(1,ispp); // Fish 2 years at max permissible rate 
+    }
+    else 
+      for (int ispp=1;ispp<=nspp;ispp++) 
+        Actual_Catch = Get_Catch(7,ispp);
+  }
+
+
+
+FUNCTION Fit_TAC
+  int use_fit = 1; // Need to move this into the setup file...
+  //option to use "fit" program results (requires obtaining theta coef)
+  if (use_fit==1)
+  {
+    // Aggregate ABCs into main groups.....
+    agg_abc.initialize();
+    agg_tac.initialize();
+    TAC.initialize();
+    TAC = ABC;
+    for (int ispp=1;ispp<=nspp;ispp++) 
+      agg_abc(tac_ind(ispp))  += ABC(ispp)/1000;
+  
+    // Compute aggregate TACs based on aggregate ABCs from model
+    for (int itacspp=1;itacspp<=ntacspp;itacspp++) 
+    {
+      double abctmp = agg_abc(itacspp) / maxabc(itacspp) ;
+      int ijunk = min(nnodes,int(abctmp * nnodes)) ;
+      agg_tac(itacspp) = abctmp * mfexp(theta(ijunk,itacspp)) ;
+    }
+    agg_tac /= sum(agg_tac);
+    agg_tac *= 1945.; // Total catch in first year
+ 
+    // Now dis-aggregate TACs to individual spp
+    for (int ispp=1;ispp<=nspp;ispp++) 
+    {
+      TAC(ispp) = agg_tac(tac_ind(ispp)) * Obs_Catch(1,ispp)/agg_cat(tac_ind(ispp));  // Just break out TAC by fractions of ABCs
+      Actual_Catch(ispp)   = min(TAC(ispp),ABC(ispp));
+    }
+  }
+  else // use generic "write_tac.bat"
+  {
+   // Given ABC's, what is the TAC?  // Go get actual catches (with constraints)
+   //  First write out ABC to file
+     ofstream abc("abc.dat");
+     abc<<ABC<<endl;
+     abc.close();
+   //  Then run TAC job as function of ABC
+     system("write_tac.bat >NUL ");
+     ifstream tac("tac.dat");
+     tac>>TAC;
+     tac.close(); /* */
+     for (int ispp=1;ispp<=nspp;ispp++) 
+       Actual_Catch(ispp)   = min(TAC(ispp),ABC(ispp));
+  }
+ 
+
+FUNCTION Avg_Age
+    Avg_Age_End.initialize();
+    Avg_Age_Mat.initialize();
+    for (int ispp=1;ispp<=nspp;ispp++) 
+    {
+      // if(!isit_const(ispp) )
+      {
+        dvector age_seq(1,nages(ispp));
+        age_seq.initialize();
+        age_seq.fill_seqadd(1,1);
+        dvector ntmp(1,nages(ispp));
+        ntmp = N_F(ispp);
+        Avg_Age_End(ispp) += age_seq * ntmp /sum(ntmp);
+        Avg_Age_sum(ispp) += Avg_Age_End(ispp) ;
+        ntmp = elem_prod(ntmp,pmature_F(ispp)) ;
+        Avg_Age_Mat(ispp) += elem_prod(ntmp,pmature_F(ispp)) * age_seq/sum(ntmp);
+        // cout<<age_seq<<endl<<ntmp<<endl<<elem_prod(ntmp,pmature_F(ispp)) <<endl<<pmature_F(ispp)<<endl;exit(1);
+      }
+    }
+
+ //Begin SPR calc functions===================================================================================
+FUNCTION get_SB100
+  SB100.initialize();
+   B100.initialize();
+  Avg_Age_F0.initialize() ;
+  Avg_Age_M0.initialize() ;
+  for (int ispp=1;ispp<=nspp;ispp++)
+  {
+    NsprF0(ispp,1)    = 1.;
+    NsprM0(ispp,1)    = 1.;
+    for (j=2;j<nages(ispp);j++)
+    {
+      NsprF0(ispp,j)   = NsprF0(ispp,j-1)  * mfexp(-M_F(ispp,j-1));
+      NsprM0(ispp,j)   = NsprM0(ispp,j-1)  * mfexp(-M_M(ispp,j-1));
+    }
+  
+    NsprF0(ispp,nages(ispp))   = NsprF0(ispp,nages(ispp)-1)* mfexp(-M_F(ispp,nages(ispp)-1) )/ (1.- mfexp(-M_F(ispp,nages(ispp))));
+    NsprM0(ispp,nages(ispp))   = NsprM0(ispp,nages(ispp)-1)* mfexp(-M_M(ispp,nages(ispp)-1) )/ (1.- mfexp(-M_M(ispp,nages(ispp))));
+    {
+      dvector age_seq(1,nages(ispp)); // Note: need to sequence this to reflect actual ages modeled (rather than convenience)
+      age_seq.initialize();
+      age_seq.fill_seqadd(1,1);
+      Avg_Age_F0(ispp)  = age_seq * NsprF0(ispp)/sum(NsprF0(ispp)) ;
+      Avg_Age_M0(ispp)  = age_seq * NsprM0(ispp)/sum(NsprM0(ispp)) ;
+    }
+  
+    for (j=1;j<=nages(ispp);j++)
+    {
+    // Kill them off till spawning 
+      SB100(ispp)    += NsprF0(ispp,j)*pmature_F(ispp,j)*wt_F(ispp,j) * mfexp(-yrfrac(ispp) *M_F(ispp,j));
+    }
+    SB100(ispp)  *= AMeanRec(ispp) ;
+
+    // SB100(ispp)  *= .5 * AMeanRec(ispp) ;
+    //cout<<"SB100  " <<SB100(ispp)<<endl;
+    B100(ispp)   = (NsprF0(ispp)*wt_F(ispp) + NsprM0(ispp)*wt_M(ispp)) * AMeanRec(ispp);
+  }
+  // cout << setprecision(2) <<Fabc<<endl
+
+FUNCTION compute_spr_rates
+  SBFabc.initialize();
+  SBF40.initialize();
+  SBKink.initialize();
+  SBFofl.initialize();
+  BFabc.initialize();
+  BF40.initialize();
+  BFofl.initialize();
+  Ftotabc.initialize();
+  Ftot40.initialize();
+  Ftotofl.initialize();
+  Avg_Age_Fabc.initialize();
+  for (int ispp=1;ispp<=nspp;ispp++)
+  {
+    NsprFabc(ispp,1)   = 1.;
+    NsprF40(ispp,1)   = 1.;
+    NsprFofl(ispp,1)   = 1.;
+    NsprMabc(ispp,1)   = 1.;
+    NsprM40(ispp,1)   = 1.;
+    NsprMofl(ispp,1)   = 1.;
+    for (m=1;m<=ngear(ispp);m++)
+    {
+      Ftotabc(ispp) += Fabc(ispp)*Frat(ispp,m)*sel_F(ispp,m);
+      Ftot40(ispp)  +=  F40(ispp)*Frat(ispp,m)*sel_F(ispp,m);
+      Ftotofl(ispp) += Fofl(ispp)*Frat(ispp,m)*sel_F(ispp,m);
+    }
+  
+    for (j=2;j<nages(ispp);j++)
+    {
+      NsprFabc(ispp,j) = NsprFabc(ispp,j-1)* mfexp(-1.*(M_F(ispp,j-1) + Ftotabc(ispp,j-1) ));
+      NsprF40(ispp,j)  = NsprF40(ispp,j-1) * mfexp(-1.*(M_F(ispp,j-1) +  Ftot40(ispp,j-1) ));
+      NsprFofl(ispp,j) = NsprFofl(ispp,j-1)* mfexp(-1.*(M_F(ispp,j-1) + Ftotofl(ispp,j-1) ));
+      NsprMabc(ispp,j) = NsprMabc(ispp,j-1)* mfexp(-1.*(M_M(ispp,j-1) + Ftotabc(ispp,j-1) ));
+      NsprM40(ispp,j)  = NsprM40(ispp,j-1) * mfexp(-1.*(M_M(ispp,j-1) +  Ftot40(ispp,j-1) ));
+      NsprMofl(ispp,j) = NsprMofl(ispp,j-1)* mfexp(-1.*(M_M(ispp,j-1) + Ftotofl(ispp,j-1) ));
+    }
+    NsprFabc(ispp,nages(ispp)) = NsprFabc(ispp,nages(ispp)-1)* mfexp(-(M_F(ispp,nages(ispp)-1) + Ftotabc(ispp,nages(ispp)-1)))/ (1.- mfexp(-(M_F(ispp,nages(ispp)) + Ftotabc(ispp,nages(ispp)) )));
+    NsprF40(ispp,nages(ispp))  = NsprF40(ispp,nages(ispp)-1) * mfexp(-(M_F(ispp,nages(ispp)-1) +  Ftot40(ispp,nages(ispp)-1)))/ (1.- mfexp(-(M_F(ispp,nages(ispp)) +  Ftot40(ispp,nages(ispp)) )));
+    NsprFofl(ispp,nages(ispp)) = NsprFofl(ispp,nages(ispp)-1)* mfexp(-(M_F(ispp,nages(ispp)-1) + Ftotofl(ispp,nages(ispp)-1)))/ (1.- mfexp(-(M_F(ispp,nages(ispp)) + Ftotofl(ispp,nages(ispp)) )));
+    NsprMabc(ispp,nages(ispp)) = NsprMabc(ispp,nages(ispp)-1)* mfexp(-(M_M(ispp,nages(ispp)-1) + Ftotabc(ispp,nages(ispp)-1)))/ (1.- mfexp(-(M_M(ispp,nages(ispp)) + Ftotabc(ispp,nages(ispp)) )));
+    NsprM40(ispp,nages(ispp))  = NsprM40(ispp,nages(ispp)-1) * mfexp(-(M_M(ispp,nages(ispp)-1) +  Ftot40(ispp,nages(ispp)-1)))/ (1.- mfexp(-(M_M(ispp,nages(ispp)) +  Ftot40(ispp,nages(ispp)) )));
+    NsprMofl(ispp,nages(ispp)) = NsprMofl(ispp,nages(ispp)-1)* mfexp(-(M_M(ispp,nages(ispp)-1) + Ftotofl(ispp,nages(ispp)-1)))/ (1.- mfexp(-(M_M(ispp,nages(ispp)) + Ftotofl(ispp,nages(ispp)) )));
+
+    // if(!isit_const(ispp) )
+    {
+      dvector age_seq(1,nages(ispp));
+      age_seq.initialize();
+      age_seq.fill_seqadd(1,1);
+      Avg_Age_Fabc(ispp) = age_seq * NsprFabc(ispp)/sum(NsprFabc(ispp)) ;
+      Avg_Age_Mabc(ispp) = age_seq * NsprMabc(ispp)/sum(NsprMabc(ispp)) ;
+    }
+  
+    for (j=1;j<=nages(ispp);j++)
+    {
+    // Kill them off till spawning 
+      SBFabc(ispp) += NsprFabc(ispp,j)*pmature_F(ispp,j)*wt_F(ispp,j)* mfexp(-yrfrac(ispp) *( M_F(ispp,j) + Ftotabc(ispp,j) ));
+      SBF40(ispp)  +=  NsprF40(ispp,j)*pmature_F(ispp,j)*wt_F(ispp,j)* mfexp(-yrfrac(ispp) *( M_F(ispp,j) + Ftot40(ispp,j) ));
+      SBFofl(ispp) += NsprFofl(ispp,j)*pmature_F(ispp,j)*wt_F(ispp,j)* mfexp(-yrfrac(ispp) *( M_F(ispp,j) + Ftotofl(ispp,j) ));
+    }
+    // 
+    double sexratio_tmp=1.0;
+    SBFabc(ispp) = AMeanRec(ispp) * SBFabc(ispp);
+    SBF40(ispp)  = AMeanRec(ispp) *  SBF40(ispp);
+    SBFofl(ispp) = AMeanRec(ispp) * SBFofl(ispp);
+    BFabc(ispp)  = AMeanRec(ispp) * (NsprFabc(ispp)*wt_F(ispp) + NsprMabc(ispp)*wt_M(ispp) ) ;
+    BF40(ispp)   = AMeanRec(ispp) *  (NsprF40(ispp)*wt_F(ispp) +  NsprM40(ispp)*wt_M(ispp) ) ;
+    BFofl(ispp)  = AMeanRec(ispp) * (NsprFofl(ispp)*wt_F(ispp) + NsprMofl(ispp)*wt_M(ispp) ) ;
+  }
+  // cout << setprecision(2) <<Fabc<<endl
+
+FUNCTION double Implied_SPR( const dvector& F_age, const int& ispp)
+  // Function that returns SPR percentage given a realized value of F...
+    dvector ntmp0(1,nages(ispp));
+    dvector ntmp1(1,nages(ispp));
+    ntmp0(1) = 1.;
+    ntmp1(1) = 1.;
+    for (j=2;j<nages(ispp);j++)
+    {
+      ntmp0(j)  = ntmp0(j-1)* exp(-M_F(ispp,j-1));
+      ntmp1(j)  = ntmp1(j-1)* exp(-1.*(M_F(ispp,j-1) + F_age(j-1) ));
+    }
+    ntmp0(nages(ispp))  =  ntmp0(nages(ispp)-1)* exp(-M_F(ispp,nages(ispp)-1) )/ (1.- exp(-M_F(ispp,nages(ispp))));
+    ntmp1(nages(ispp))  =  ntmp1(nages(ispp)-1)* exp(-(M_F(ispp,nages(ispp)-1) + F_age(nages(ispp)-1)))/ (1.- mfexp(-(M_F(ispp,nages(ispp)) + F_age(nages(ispp)) )));
+    double sb0_tmp=0.;
+    double sb1_tmp=0.;
+    for (j=1;j<=nages(ispp);j++)
+    {
+    // Mortality till spawning 
+      sb0_tmp      += ntmp0(j)*pmature_F(ispp,j)*wt_F(ispp,j) * mfexp(-yrfrac(ispp) * M_F(ispp,j));
+      sb1_tmp      += ntmp1(j)*pmature_F(ispp,j)*wt_F(ispp,j) * mfexp(-yrfrac(ispp) * ( M_F(ispp,j) + F_age(j) ));
+    }
+    return(sb1_tmp / sb0_tmp);
+
+ // Solve for F given catch=================================================================================
+FUNCTION double SolveF2(const dvector& N_F, const dvector& N_M, const double&  TACin, const int& ispp)
+  double dd = 10.;
+  double cc;
+  cc = TACin;
+  dmatrix Fratsel_F(1,ngear(ispp),1,nages(ispp));
+  dmatrix Fratsel_M(1,ngear(ispp),1,nages(ispp));
+  dvector Z_F(1,nages(ispp)) ;
+  dvector Z_M(1,nages(ispp)) ;
+  dvector S_F(1,nages(ispp)) ;
+  dvector S_M(1,nages(ispp)) ;
+  for (m=1;m<=ngear(ispp);m++)
+  {
+    Fratsel_F(m)=Frat(ispp,m)*sel_F(ispp,m);
+    Fratsel_M(m)=Frat(ispp,m)*sel_M(ispp,m);
+  }
+
+  dvector Ftottmp_F(1,nages(ispp));
+  dvector Ftottmp_M(1,nages(ispp));
+  //dvariable btmp =  n0_M(ispp) * wt_M(ispp) + n0_F(ispp) * wt_F(ispp);
+  double btmp ;
+  btmp =  N_M * elem_prod(sel_M(ispp,1),wt_M(ispp)) + N_F * elem_prod(sel_M(ispp,1),wt_F(ispp));
+  double ftmp;
+  ftmp = TACin/btmp;
+  int iter=0;
+  while (dd > 1e-6)
+  {
+    iter++;
+    ftmp += (TACin-cc) / btmp;
+    Ftottmp_F.initialize();
+    Ftottmp_M.initialize();
+    for (m=1;m<=ngear(ispp);m++)
+    {
+      Ftottmp_F += ftmp*Fratsel_F(m);
+      Ftottmp_M += ftmp*Fratsel_M(m);
+    }
+    Z_F = Ftottmp_F  + M_F(ispp); 
+    Z_M = Ftottmp_M  + M_M(ispp); 
+    S_F = mfexp( -Z_F );
+    S_M = mfexp( -Z_M );
+    cc = 0.0;
+    for (m=1;m<=ngear(ispp);m++)
+    {
+      cc += (wt_gear_F(ispp,m) * elem_prod(elem_div(ftmp*Fratsel_F(m),  Z_F),elem_prod(1.-S_F,N_F))); // Catch equation (vectors)
+      cc += (wt_gear_M(ispp,m) * elem_prod(elem_div(ftmp*Fratsel_M(m),  Z_M),elem_prod(1.-S_M,N_M))); // Catch equation (vectors)
+    }
+    dd = cc / TACin - 1.;
+    //cout << ispp<<" "<< ftmp << " "<< cc << " "<<TACin<<endl; //cout << sel_F << endl << sel_M << endl << endl; //cout << Fratsel_F << endl << Fratsel_M << endl; //exit(1);
+    if (dd<0.) dd *= -1.;
+    // cout<<"CC Ftmp btmp "<<cc<<" "<< ftmp<<" "<<btmp<<" "<<dd<<endl;
+    if (iter>100) {cerr<<"Bombed on catch solver--check scales for "<<spname(ispp)<<" Catch was "<<TACin<<endl<<" Biomass: "<<btmp<<endl<<" Catch, F trial was: "<<cc<<" "<<ftmp<<" "<<dd<<endl<<sel_F(ispp);exit(1);}
+  }
+  return(ftmp);
+
+FUNCTION void Get_SPR_Catches(const int& ispp)
+  Cabc(ispp) = 0.0;
+  Cofl(ispp) = 0.0;
+  // Compute catch at spr rates
+  for (m=1;m<=ngear(ispp);m++)
+  {
+    Cabc(ispp) += ( wt_gear_F(ispp,m) * AMeanRec(ispp)*elem_prod(elem_div( Fabc(ispp)*Frat(ispp,m)*sel_F(ispp,m) ,
+                  M_F(ispp) + Ftotabc(ispp)),elem_prod(1.- mfexp(-(M_F(ispp)+Ftotabc(ispp))),NsprFabc(ispp))));
+    Cabc(ispp) += ( wt_gear_M(ispp,m) * AMeanRec(ispp)*elem_prod(elem_div( Fabc(ispp)*Frat(ispp,m)*sel_M(ispp,m) , 
+                  M_M(ispp) + Ftotabc(ispp)),elem_prod(1.- mfexp(-(M_M(ispp)+Ftotabc(ispp))),NsprMabc(ispp))));
+
+    Cofl(ispp) += ( wt_gear_F(ispp,m) * AMeanRec(ispp)*elem_prod(elem_div( Fofl(ispp)*Frat(ispp,m)*sel_F(ispp,m) , 
+                  M_F(ispp) + Ftotofl(ispp)),elem_prod(1.- mfexp(-(M_F(ispp)+Ftotofl(ispp))),NsprFofl(ispp))));
+    Cofl(ispp) += ( wt_gear_M(ispp,m) * AMeanRec(ispp)*elem_prod(elem_div( Fofl(ispp)*Frat(ispp,m)*sel_M(ispp,m) , 
+                  M_M(ispp) + Ftotofl(ispp)),elem_prod(1.- mfexp(-(M_M(ispp)+Ftotofl(ispp))),NsprMofl(ispp))));
+  }
+
+FINAL_SECTION
+    write_srec();
+    do_elasticity();
+    Run_Sim();
+    cout<< "---- Finished simulations using stochastic stock-recruitment relationship -----"<<endl;
+
+REPORT_SECTION
+ /*
+  if (last_phase())
+	{
+    do_elasticity();
+    if (Rec_Gen==1||Rec_Gen==4) {
+     Run_Sim();  cout<< "Finished simulations using standard (avg, var) stochastic approach"<<endl;
+    }
+   }
+ */
+
+
+  cout <<endl<< "Report section, phase: "<<current_phase()<<endl;
+  cout <<"===========================================  "<<endl;
+
+  report << "__ ";
+  for (int ispp=1;ispp<=nspp;ispp++) report<< spname(ispp)<<" ";
+  report<<endl;
+  report << "EquilAvgAgeF0  " ;
+    for (int ispp=1;ispp<=nspp;ispp++) report << Avg_Age_F0(ispp)<< " "; report << endl;
+  report << "EquilAvgAgeFabc  " ;
+    for (int ispp=1;ispp<=nspp;ispp++) report << Avg_Age_Fabc(ispp)<< " "; report << endl;
+  report << "Generation_Time_(assumes_recruitment_age=1)"<< " ";
+  for (int ispp=1;ispp<=nspp;ispp++) 
+  {
+    double Tg=0.;
+    double tmp=0.;
+    double ntmp=1.;
+    for (int ii=1;ii<=4*nages(ispp);ii++)
+    {
+      if (ii>nages(ispp))
+      {
+        Tg += double(ii) * wt_mature_F(ispp,nages(ispp)) * ntmp;
+        tmp +=  wt_mature_F(ispp,nages(ispp)) * ntmp;
+        ntmp *= exp(-M_F(ispp,nages(ispp)));
+      }
+      else
+      {
+        Tg += double(ii) * wt_mature_F(ispp,ii) * ntmp;
+        tmp +=  wt_mature_F(ispp,ii) * ntmp;
+        ntmp *= exp(-M_F(ispp,ii));
+      }
+    }
+    // Tg /= value(phizero(ispp));
+    Tg /= tmp;
+    report << Tg<<  " "; 
+  }
+  report << endl;
+  report << "Options SR_Type Project_Recr_Assmption SR_Condition"<<endl<<"  ";
+  report <<           SrType<<" "<< Rec_Gen<<" "<<Fmsy_F35<<" "<<Rec_Cond<<endl;
+
+
+
+  if (last_phase())
+  {
+    // do_elasticity();
+    // Run_Sim();
+    cout<< "---- Finished simulations using stochastic stock-recruitment relationship -----"<<endl;
+    report<<endl<<endl;
+    report << "Stock B100 B40 B35 F40 F35  F_"<<styr<<endl;
+    for (int ispp=1;ispp<=nspp;ispp++) report<< spname(ispp)<<" "<< SB100(ispp)<<" "<<.4*SB100(ispp)<<" "<<.35*SB100(ispp)<<" "<<F40(ispp)
+                                                          <<" "<<F35(ispp)<<" "<<Fsim(ispp,1,1)<<" "<<endl;
+    report<<endl<<endl;
+
+  }
+  // srec_out << Fabc << endl;
+  // srec_out<<"Selectivity " <<endl;
+  // report<<sel_F<<endl;
+
+FUNCTION write_srec
+  ofstream srec_out("srec.out");
+  srec_out << "S-r Parameters"<<endl;
+  srec_out << "Steepness Rzero Alpha Beta SigmaR Bzero Phi "<<endl;
+  srec_out << steepness<< " "
+           << sr_alpha << " "
+           << beta     << " "
+           << sigr     << " "
+           << Bzero    << " "
+           << phizero  << " "
+           << endl<<endl;
+  srec_out << "Stock Run Source SSB Rec"<<endl;
+  for (int i=1;i<=nspp;i++)
+  {
+    if(last_phase()) 
+    {
+      Profile_F(i);
+      cout <<spname(i)<<" "<< Fmsy(i)<<" "<<Fofl(i)<<" "<<get_spr_rates(0.35,i)<<" "<<get_spr_rates(0.4,i)<<endl;
+    }
+    for (int ii=1;ii<=nrec(i);ii++)
+    {
+      srec_out <<spname(i)<<" "<<run_name<< " Data "<<SSB(i,ii)<<" "<< R(i,ii)<<endl;
+    }
+  }
+  for (int i=1;i<=nspp;i++)
+  {
+    for (int ii=0;ii<=30;ii++)
+    {
+      double ssbtmp = double(ii) * value(Bzero(i)) * 1.5 / 30. ;
+      srec_out <<spname(i)<<" "<<run_name<< " Fit "<<ssbtmp<<" "<<SRecruit(ssbtmp,i)<<endl;
+    }
+    // cout <<spname(i)<<" "<< Fmsy(i)<<" "<<Fofl(i)<<" "<<get_spr_rates(0.35,i)<<" "<<get_spr_rates(0.4,i)<<endl;
+  }
+  srec_out <<endl;
+  // srec_out << "Bzero "<<Bzero << endl;
+  // srec_out << "B100 "<<SB100 << endl;
+  srec_out.close();
+
+    // Writing routines here ....
+FUNCTION write_by_time
+  write_sim("Catch",            Csim,Cabc);  // Total Catch
+  write_ABCs("ABCs"            );            // ABC Catch
+  write_TACs("TACs"            );            // ABC Catch
+  write_sim("Sp_Biomass",      SBsim,SBFabc);  // Spawn Biomass
+  write_sim("Fishing Mortality",Fsim,Fabc);  // Total Fishing mortality
+  write_sim("Biomass",          Bsim);       // Total Biomass
+  write_sim("Implied SPR rate ",SPRsim,SPR_abc);  // Total Fishing mortality
+
+  write_avg_age("Alternative ") ;
+
+FUNCTION void write_avg_age(const adstring& Title) 
+  means_out << "  ";
+  for (int ispp=1;ispp<=nspp;ispp++) means_out << spname(ispp)<< " "; means_out << endl;
+
+  means_out << "EquilAvgAgeF0  " ;
+    for (int ispp=1;ispp<=nspp;ispp++) means_out << Avg_Age_F0(ispp)<< " "; means_out << endl;
+  means_out << "EquilAvgAgeFabc  " ;
+    for (int ispp=1;ispp<=nspp;ispp++) means_out << Avg_Age_Fabc(ispp)<< " "; means_out << endl;
+  means_out << "AvgAgeYr"<< styr + npro -1 << " ";
+    for (int ispp=1;ispp<=nspp;ispp++) means_out << Avg_Age_sum(ispp)/nsims<< " "; means_out << endl;
+
+
+FUNCTION write_alts 
+  for (int ispp=1;ispp<=nspp;ispp++)
+  {
+    dmatrix ccc = trans(Csim(ispp));
+    dmatrix mtmp= trans(SBsim(ispp));
+    dmatrix btmpx = trans(Bsim(ispp));
+    for (int i=2;i<=npro;i++)
+    {
+      alts_proj << spname(ispp)<<" "<<alt<<" "<< i+styr-1 <<" "<<mean(ccc(i))
+                <<" "<<(ABCs_by_yr(i,ispp))/nsims<<" "<<
+                    OFLs_by_yr(i,ispp)/nsims<<" "<<mean(mtmp(i))<<" "<<mean(btmpx(i))<<endl;
+    }
+  }
+FUNCTION write_alts_hdr
+  alts_proj << "Stock Alt Year Catch ABC OFL SSB TotBiom"<<endl;
+
+FUNCTION void write_ABCs(const adstring& Title) 
+  // This one prints out species over time (means only), but without headings
+  means_out <<"Alternative "<<alt<<" "<<Title << endl; 
+  means_out << "     " ; for (int ispp=1;ispp<=nspp;ispp++) means_out << spname(ispp)<< " " ; means_out <<endl;
+  means_out << endl<< "Year " <<endl;
+
+  for (int i=1;i<=npro;i++)
+  {
+    means_out << i+styr-1 <<" ";
+    for (int ispp=1;ispp<=nspp;ispp++)
+    {
+      double mean_value = (ABCs_by_yr(i,ispp))/nsims;
+      if (mean_value > 1e-6) 
+        means_out << mean_value <<" "; 
+      else
+        means_out << " NA "; 
+    }
+    means_out << endl;
+  }
+  means_out << endl;
+
+FUNCTION void write_TACs(const adstring& Title) 
+  // This one prints out species over time (means only), but without headings
+  means_out <<"Alternative "<<alt<<" "<<Title << endl; 
+  means_out << "     " ; for (int ispp=1;ispp<=nspp;ispp++) means_out << spname(ispp)<< " " ; means_out <<endl;
+  means_out << endl<< "Year " <<endl;
+  for (int i=1;i<=npro;i++)
+  {
+    means_out << i+styr-1 <<" ";
+    for (int ispp=1;ispp<=nspp;ispp++)
+    {
+      double mean_value = (TACs_by_yr(i,ispp))/nsims;
+      if (mean_value > 1e-6) 
+        means_out << mean_value <<" "; 
+      else
+        means_out << " NA "; 
+    }
+    means_out << endl;
+  }
+  means_out << endl;
+  
+
+
+FUNCTION void write_sim(const adstring& Title, d3_array& Outtmp) 
+  // This one prints out species over time (means only), but without headings
+  d3_array mtmp(1,nspp,1,npro,1,nsims);
+  for (int ispp=1;ispp<=nspp;ispp++) for (int i=1;i<=npro;i++) for (int k=1;k<=nsims;k++)
+    mtmp(ispp,i,k)=Outtmp(ispp,k,i);
+  means_out <<"Alternative "<<alt<<" "<<Title << endl; 
+  means_out << "     " ; for (int ispp=1;ispp<=nspp;ispp++) means_out << spname(ispp)<< " " ; means_out <<endl;
+  means_out << endl<<"Year " <<endl;
+  for (int i=1;i<=npro;i++)
+  {
+    means_out << i+styr-1 <<" ";
+    double mean_value;
+    for (int ispp=1;ispp<=nspp;ispp++)
+    {
+      mean_value = mean(mtmp(ispp,i)) ;
+      if (mean_value > 1e-6) 
+        means_out << mean_value <<" "; 
+      else
+        means_out << " NA "; 
+    }
+    means_out << endl;
+  }
+  means_out << endl;
+  
+FUNCTION void write_sim(const adstring& Title,const  d3_array& Outtmp,const dvar_vector& bb) 
+  // This one prints out species over time (means only)
+  d3_array mtmp(1,nspp,1,npro,1,nsims);
+  for (int ispp=1;ispp<=nspp;ispp++) for (int i=1;i<=npro;i++) for (int k=1;k<=nsims;k++)
+    mtmp(ispp,i,k)=Outtmp(ispp,k,i);
+  means_out <<"Alternative "<<alt<<" "<<Title << endl; 
+  means_out << "     " ; for (int ispp=1;ispp<=nspp;ispp++) means_out << spname(ispp)<< " " ; means_out <<endl;
+  means_out << "Equil_Fabc " ; 
+  for (int ispp=1;ispp<=nspp;ispp++) 
+  {
+    {
+      means_out << bb(ispp) << " " ; 
+    }
+  }
+  means_out << endl;
+  means_out << "Year " <<endl; 
+  for (int i=1;i<=npro;i++)
+  {
+    means_out << i+styr-1 <<" ";
+    double mean_value;
+    for (int ispp=1;ispp<=nspp;ispp++)
+    {
+      mean_value = mean(mtmp(ispp,i)); 
+      if (mean_value>1e-6)
+        means_out << mean_value <<" "; 
+      else
+        means_out << " NA "; 
+    }
+    means_out << endl;
+  }
+  means_out << endl;
+  
+FUNCTION void write_sim(const adstring& Title,const int& ispp) 
+  // For each species separately
+  percent_out <<"Alternative "<<alt<<" "<<Title << " Stock: "<<spname(ispp)<< endl;
+  write_spp(ispp);
+
+FUNCTION void write_sim_hdr(const int& ispp) 
+  percent_out <<"SB0 SB40 SB35 MeanRec HarMeanRec Bnow"<<endl;
+  percent_out << SB100(ispp)       <<" "<<
+            SBF40(ispp)      <<" "<<
+            SBFofl(ispp)      <<" "<<
+            AMeanRec(ispp) <<" "<<
+            HMeanRec(ispp) <<" "<<
+            Bcurrent(ispp) <<" "<<
+            endl;
+  percent_out <<"CV Recruit" <<endl;
+  percent_out << cvrec(ispp)  <<" "<<endl;
+
+FUNCTION void write_spp(const int& ispp) 
+  // Write out afsd objective function
+  // for (int i=1;i<=nsims;i++)
+  // {
+    // // double avg_yld       = mean(Csim(ispp,i)); double sqrd_1st_diff = mean(square(first_difference(Csim(ispp,i)))); Alt3bstuff << ispp<<" "<<spname(ispp)<<" "<< alt<<" "<<i<<" "<< avg_yld <<" " << sqrd_1st_diff<<" "<<avg_yld - sqrd_1st_diff<<endl;
+  // }
+  // Write out each species individually (with confidence bounds)
+  percent_out <<"Catch "<<spname(ispp)<< endl<< "Year C0 Cabc Cofl LowCI_Catch Median_Catch Mean_Catch UpperCI_Catch Stdev_Catch "<<endl;
+  dmatrix mtmp = TranSort(Csim(ispp));
+  for (int i=1;i<=npro;i++)
+  {
+    int iyr=i+styr-1;
+    double sd_cat_tmp =      sqrt(norm2(mtmp(i)-mean(mtmp(i)))/nsims)          ;
+    percent_db << spname(ispp)<<" "<< alt<<" "<< iyr<<" Cabc " << Cabc(ispp)<<endl;
+    percent_db << spname(ispp)<<" "<< alt<<" "<< iyr<<" Cofl " << Cofl(ispp)<<endl;
+    percent_db << spname(ispp)<<" "<< alt<<" "<< iyr<<" CLCI " << mtmp(i,LCI)<<endl;
+    percent_db << spname(ispp)<<" "<< alt<<" "<< iyr<<" CUCI " << mtmp(i,UCI)<<endl;
+    percent_db << spname(ispp)<<" "<< alt<<" "<< iyr<<" CMedian " << mtmp(i,int((UCI+LCI)/2))<<endl;
+    percent_db << spname(ispp)<<" "<< alt<<" "<< iyr<<" CMean " << mean(mtmp(i))<<endl;
+    percent_db << spname(ispp)<<" "<< alt<<" "<< iyr<<" CStdn " << sd_cat_tmp <<endl;
+
+   percent_out << i+styr-1                  <<" "
+          << " 0"                       <<" "
+          << Cabc(ispp)                 <<" "
+          << Cofl(ispp)                 <<" "
+          << mtmp(i,LCI)                <<" "
+          << mtmp(i,int((UCI+LCI)/2))   <<" "
+          << mean(mtmp(i))              <<" "
+          << mtmp(i,UCI)                <<" "
+          << sd_cat_tmp           <<" "
+          << endl;
+  }
+  percent_out << endl;
+
+  percent_out <<"Spawning_Biomass "<<spname(ispp)<< endl<< "Year SSB100 SSBabc SSBofl LowCI_SSB Median_SSB Mean_SSB UpperCI_SSB Stdev_SSB "<<endl;
+  mtmp = TranSort(SBsim(ispp));
+  for (int i=1;i<=npro;i++)
+   {
+    int iyr=i+styr-1;
+    percent_db << spname(ispp)<<" "<< alt<<" "<< iyr<<" SSBF100 " << SB100(ispp)<<endl;
+    percent_db << spname(ispp)<<" "<< alt<<" "<< iyr<<" SSBFabc " << SBFabc(ispp)<<endl;
+    percent_db << spname(ispp)<<" "<< alt<<" "<< iyr<<" SSBFofl " << SBFofl(ispp)<<endl;
+    percent_db << spname(ispp)<<" "<< alt<<" "<< iyr<<" SSBLCI " << mtmp(i,LCI)<<endl;
+    percent_db << spname(ispp)<<" "<< alt<<" "<< iyr<<" SSBUCI " << mtmp(i,UCI)<<endl;
+    percent_db << spname(ispp)<<" "<< alt<<" "<< iyr<<" SSBMedian " << mtmp(i,int((UCI+LCI)/2))<<endl;
+    percent_db << spname(ispp)<<" "<< alt<<" "<< iyr<<" SSBMean " << mean(mtmp(i))<<endl;
+
+   percent_out << i+styr-1                         <<" ";
+     percent_out      << SB100(ispp)               <<" ";
+     percent_out      << SBFabc(ispp)              <<" ";
+     percent_out      << SBFofl(ispp)              <<" ";
+     percent_out      << mtmp(i,LCI)               <<" ";
+     percent_out      << mtmp(i,int((UCI+LCI)/2))  <<" ";
+     percent_out      << mean(mtmp(i))             <<" ";
+     percent_out      << mtmp(i,UCI)               <<" ";
+     percent_out      << sqrt(norm2(mtmp(i)-mean(mtmp(i)))/nsims)           <<" ";
+     percent_out      << endl;
+   }
+  percent_out << endl;
+
+  percent_out << "Fishing_mortality"<<spname(ispp)<< endl<< "Year F0 Fabc Fofl LowCI_F Median_F Mean_F UpperCI_F Stdev_F "<<endl;
+  mtmp = TranSort(Fsim(ispp));
+  for (int i=1;i<=npro;i++)
+   {
+    int iyr=i+styr-1;
+    percent_db << spname(ispp)<<" "<< alt<<" "<< iyr<<" F0 0 "<<endl; 
+    percent_db << spname(ispp)<<" "<< alt<<" "<< iyr<<" Fabc " << Fabc(ispp)<<endl;
+    percent_db << spname(ispp)<<" "<< alt<<" "<< iyr<<" Fofl " << Fofl(ispp)<<endl;
+    percent_db << spname(ispp)<<" "<< alt<<" "<< iyr<<"  F_LCI " << mtmp(i,LCI)<<endl;
+    percent_db << spname(ispp)<<" "<< alt<<" "<< iyr<<"  F_UCI " << mtmp(i,UCI)<<endl;
+    percent_db << spname(ispp)<<" "<< alt<<" "<< iyr<<"  F_Median " << mtmp(i,int((UCI+LCI)/2))<<endl;
+    percent_db << spname(ispp)<<" "<< alt<<" "<< iyr<<"  F_Mean " << mean(mtmp(i))<<endl;
+   percent_out << i+styr-1                  <<" "
+          << " 0"                       <<" "
+          << Fabc(ispp)                 <<" "
+          << Fofl(ispp)                 <<" "
+          << mtmp(i,LCI)                <<" "
+          << mtmp(i,int((UCI+LCI)/2))   <<" "
+          << mean(mtmp(i))              <<" "
+          << mtmp(i,UCI)                <<" "
+          << sqrt(norm2(mtmp(i)-mean(mtmp(i)))/nsims)           <<" "
+          << endl;
+   }
+  percent_out << endl;
+  
+  percent_out << "Total_Biomass"<<spname(ispp)<< endl<< "Year B100 Babc Bofl LowCI_Biom Median_Biom Mean_Biom UpperCI_Biom Stdev_Biom "<<endl;
+  mtmp = TranSort(Bsim(ispp));
+  for (int i=1;i<=npro;i++)
+  {
+   percent_out << i+styr-1                          <<" ";
+     percent_out      << B100(ispp)                 <<" ";
+     percent_out      << BFabc(ispp)                <<" ";
+     percent_out      << BFofl(ispp)                <<" ";
+     percent_out      << mtmp(i,LCI)                <<" ";
+     percent_out      << mtmp(i,int((UCI+LCI)/2))   <<" ";
+     percent_out      << mean(mtmp(i))              <<" ";
+     percent_out      << mtmp(i,UCI)                <<" ";
+     percent_out      << sqrt(norm2(mtmp(i)-mean(mtmp(i)))/nsims)           <<" ";
+     percent_out      << endl;
+   }
+  
+GLOBALS_SECTION
+  #include <admodel.h>
+  adstring xspname;
+  adstring_array targsppname(1,20);
+  adstring_array spp_file_name(1,20);
+  adstring_array gearname(1,8);
+  adstring_array spname(1,90);
+  adstring_array areaname(1,8);
+  adstring       run_name;
+ 
+  ofstream write_log("Input_Log.rep");
+  #undef write_log
+  #define write_log(object) write_log << #object "\n" << object << endl;
+
+  // A routine to get transpose, sort and return a matrix ---- 
+  dmatrix TranSort (const dmatrix m1)
+  {
+  RETURN_ARRAYS_INCREMENT();
+    dmatrix vtmp=trans(m1);
+    int npro=m1.colmax();
+    int nsim=m1.rowmax();
+    for (int i=1;i<=npro;i++)
+      vtmp(i) = sort(vtmp(i),nsim);
+
+    RETURN_ARRAYS_DECREMENT();
+    return(vtmp);
+  }
+  // #include <lpcode.cpp>
+
+FUNCTION dvariable SRecruit(const dvariable& Stmp,const int& ispp)
+  RETURN_ARRAYS_INCREMENT();
+  dvariable RecTmp;
+  switch (SrType)
+  {
+    case 1:
+      RecTmp = (Stmp / phizero(ispp)) * mfexp( sr_alpha(ispp) * ( 1. - Stmp / Bzero(ispp) )) ; //Ricker form from Dorn
+      break;
+    case 2:
+      RecTmp = Stmp / ( sr_alpha(ispp) + beta(ispp) * Stmp);        //Beverton-Holt form
+      break;
+    case 3:
+      // RecTmp = mfexp(log_avgrec);                    //Avg recruitment
+      break;
+    case 4:
+      RecTmp = Stmp * mfexp( sr_alpha(ispp)  - Stmp * beta(ispp)) ; //old Ricker form
+      break;
+  }
+
+  RETURN_ARRAYS_DECREMENT();
+  return RecTmp;
+
+
+FUNCTION dvar_vector SRecruit(const dvar_vector& Stmp,const int& ispp)
+  RETURN_ARRAYS_INCREMENT();
+  dvar_vector RecTmp(Stmp.indexmin(),Stmp.indexmax());
+  switch (SrType)
+  {
+    case 1:
+      RecTmp = elem_prod((Stmp / phizero(ispp)) , mfexp( sr_alpha(ispp) * ( 1. - Stmp / Bzero(ispp) ))) ; //Ricker form from Dorn
+      break;
+    case 2:
+      RecTmp = elem_prod(Stmp , 1. / ( sr_alpha(ispp) + beta(ispp) * Stmp)); //Beverton-Holt form
+      break;
+    case 3:
+      // RecTmp = mfexp(log_avgrec);                              //Avg recruitment
+      break;
+    case 4:
+      RecTmp = elem_prod(Stmp ,mfexp( sr_alpha(ispp) - Stmp * beta(ispp)));  //old Ricker form
+      break;
+  }
+  RETURN_ARRAYS_DECREMENT();
+  //cout <<RecTmp<<endl;
+  return RecTmp;
+
+ 
+FUNCTION dvariable Requil(const dvariable& phi,const int& ispp)
+  dvariable RecTmp;
+  switch (SrType)
+  {
+    case 1:
+      RecTmp =  Bzero(ispp) * (sr_alpha(ispp) + log(phi) - log(phizero(ispp)) ) / (sr_alpha(ispp)*phi);
+      break;
+    case 2:
+      RecTmp =  (phi-sr_alpha(ispp))/(beta(ispp)*phi);
+      break;
+    case 3:
+      // RecTmp =  mfexp(log_avgrec);
+      break;
+    case 4:
+      RecTmp =  (log(phi)+sr_alpha(ispp)) / (beta(ispp)*phi); //RecTmp =  (log(phi)/sr_alpha + 1.)*beta/phi;
+      break;
+  }
+  return RecTmp;
+
+ //=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=+=
+FUNCTION void Get_Bzero(const int& ispp) 
+  Bzero(ispp).initialize();
+  Rzero(ispp)    =  mfexp(log_Rzero(ispp)); 
+  dvar_vector Ntmp(1,nages(ispp));
+  dvar_vector survtmp = mfexp(-M_F(ispp));
+  Ntmp.initialize();
+
+  Ntmp(1) = Rzero(ispp);
+  for ( j=1 ; j < nages(ispp); j++ )
+  {
+    Ntmp(j+1)  =   Ntmp(j) * survtmp(j); // Begin numbers in the next year/age class
+    // cout <<Ntmp(j)<< " ";
+  }
+  Ntmp(nages(ispp))  /= (1.- survtmp(nages(ispp))); 
+  for ( j=1 ; j <= nages(ispp); j++ )
+    Ntmp(j) *= pow(survtmp(j),yrfrac(ispp));
+  // cout <<Ntmp(nages)<< endl;
+
+  if (nsexes(ispp)==1) 
+    Bzero(ispp) = 0.5* wt_mature_F(ispp)  * Ntmp ; // p_mature is of Females (half of adults)
+  else
+    Bzero(ispp) = wt_mature_F(ispp)  * Ntmp ; // p_mature 
+
+  switch (SrType)
+  {
+    case 1:
+      if (Rec_Gen==3)
+      {
+        sr_alpha(ispp) = alpha_in;
+        phizero(ispp)  = phizero_in;
+        Bzero(ispp)    = bzero_in;
+        sigr(ispp)    = sigmar_in;
+      }
+      else
+      {
+        if (Rec_Gen==4)
+        {
+        }
+        else
+        {
+          sr_alpha(ispp) = log(-4.*steepness(ispp)/(steepness(ispp)-1.));
+          phizero(ispp) = Bzero(ispp)/Rzero(ispp);
+        }
+      }
+      break;
+    case 2:
+      sr_alpha(ispp)  =  Bzero(ispp) * (1. - (steepness(ispp) - 0.2) / (0.8*steepness(ispp)) ) / Rzero(ispp);
+      beta(ispp)   = (5. * steepness(ispp) - 1.) / (4. * steepness(ispp) * Rzero(ispp));
+      phizero(ispp) = Bzero(ispp)/Rzero(ispp);
+      break;
+    case 4:
+    // R = S * EXP(sr_alpha - beta * S))
+      beta(ispp)  = log(5.*steepness(ispp))/(0.8*Bzero(ispp)) ;
+      sr_alpha = log(Rzero(ispp)/Bzero(ispp))+beta(ispp)*Bzero(ispp);
+      break;
+  }
+
+FUNCTION void Recruitment_Likelihood(const int& ispp)
+  sigmaRsq(ispp) = sigr(ispp)*sigr(ispp);
+  rec_like(ispp).initialize();
+  // Tune recruits to spawners via functional form of Srec (to estimate srec params) RAM's exp. value form of -ln like
+    rec_like(ispp) = (norm2( log(R(ispp)+1.e-8) - 
+                             log(SRecruit(SSB(ispp),ispp) +1.e-8) + sigmaRsq(ispp)/2. ) / 
+                             (2.*sigmaRsq(ispp))) + nrec(ispp) * log(sigr(ispp));
+  obj_fun += sum(rec_like);
+
+FUNCTION void Profile_F(const int& ispp)
+  cout << "Profiling over F for " <<spname(ispp)<<endl;
+ /* NOTE THis will need to be conditional on SrType too Function calculates used in calculating MSY and MSYL for a designated component of the
+  population, given values for stock recruitment and selectivity...  Fmsy is the trial value of MSY example of the use of "funnel" to reduce the amount of storage for derivative calculations */
+ dvariable sumF=0.;
+  dvariable Stmp;
+  dvariable Rtmp;
+  double df=1.e-7;
+  dvariable F1=.05;
+  dvariable F2;
+  dvariable F3;
+  dvariable yld1;
+  dvariable yld2;
+  dvariable yld3;
+  dvariable dyld;
+  dvariable dyldp;
+  // if (ispp==1) prof_F <<"Profile of stock, yield, and recruitment over F"<<endl;
+  // prof_F << spname(ispp)<<" "<<endl;
+  if (ispp==1) prof_F <<"Stock Run SSB F Yield SPR Recruit "<<endl;
+  prof_F <<spname(ispp)<<" "<<run_name<<" "<< Bzero(ispp) <<" 0.0 0.0 1.0 " <<Rzero(ispp)<<endl; 
+  dvar_vector ttt(1,5);
+  for (int ii=0;ii<=150;ii++)
+  {
+    F1    = double(ii)/100;
+    yld1  = yield(F1,Stmp,Rtmp,ispp);
+    if (yld1<0) {yld1=0.; Stmp=0.; Rtmp=0.;}
+    // ttt   = yld(Frat(ispp),F1);
+  //         "Stock                 Run         SSB         F         Yield         SPR                         Recruit "<<endl;
+    prof_F <<spname(ispp)<<" "<< run_name<<" "<<Stmp<<" "<<F1<<" "<<  yld1<<" "<<phi(ispp)/phizero(ispp)<<" "<< Rtmp<< endl; ;       // SPR
+  } 
+
+FUNCTION void get_msy(const int& ispp)
+ /*Function calculates used in calculating MSY and MSYL for a designated component of the
+  population, given values for stock recruitment and selectivity...  Fmsy is the trial value of MSY example of the use of "funnel" to reduce the amount of storage for derivative calculations */
+  dvariable Stmp;
+  dvariable Rtmp;
+  double df=1.e-6;
+  dvariable F1;
+  F1 = F35(ispp);
+  dvariable F2;
+  dvariable F3;
+  dvariable yld1;
+  dvariable yld2;
+  dvariable yld3;
+  dvariable dyld;
+  dvariable dyldp;
+  // Newton Raphson stuff to go here //cout <<endl<<endl<<"Iter  F  Stock  1Deriv  Yld  2Deriv"<<endl; //for (int ii=1;ii<=500;ii++)
+  for (int ii=1;ii<=5;ii++)
+  {
+    // if (mceval_phase()&&(F1>5||F1<0.01)) 
+    // {
+      // ii=5;
+      // F1=M(ispp,nages(ispp)); // When things bomb (F <0 or F really big then just set it to F35...)
+    // }
+    // else
+    {
+      F2     = F1 + df*.5;
+      F3     = F2 - df; //F1    = double(ii)/100;
+      yld1   = yield(F1,Stmp,Rtmp,ispp); //cout <<ii<<" " <<F1<<" "<< Stmp <<" "<<yld1<<" "<<Rtmp<<" "<<" "<< endl; } exit(1);/*
+      yld2   = yield(F2,Stmp,Rtmp,ispp);
+      yld3   = yield(F3,Stmp,Rtmp,ispp);
+      dyld   = (yld2 - yld3)/df;                          // First derivative (to find the root of this)
+      dyldp  = (yld2 + yld3 - 2.*yld1)/(.25*df*df);   // Second derivative (for Newton Raphson)
+      F1    -= dyld/dyldp;
+      // cout <<F1<<" "<<yld1<<" "<<endl;
+    }
+  }
+  Fmsy(ispp)  = F1;
+  dvariable msytmp;
+  msytmp =  yield(Fmsy(ispp),Stmp,Rtmp,ispp);
+  MSY(ispp)   = msytmp;
+  Bmsy(ispp)  = Stmp;
+  Rmsy(ispp)  = Rtmp;
+
+//+==+==+==+==+==+==+==+==+==+==+==+==+==+==+==+==+==+==+==+==+==+==+==+==+ 
+FUNCTION dvariable yield(const dvariable& Ftmp, dvariable& Stmp,dvariable& Rtmp,const int& ispp)
+  // cout<<spname(ispp)<<" "<<Ftmp<<" "<<Stmp<<" "<<Rtmp<<endl;
+  dvariable yldtmp;
+  dvariable phitmp;
+  dvariable Req;
+  
+  dvar_vector Ntmp_F(1,nages(ispp));
+  dvar_vector Ntmp_M(1,nages(ispp));
+
+  dvar_vector Fatmp_F(1,nages(ispp));
+  dvar_vector Fatmp_M(1,nages(ispp));
+
+  dvar_vector Ztmp_F(1,nages(ispp));
+  dvar_vector Ztmp_M(1,nages(ispp));
+
+  dvar_vector survtmp_F(1,nages(ispp));
+  dvar_vector survtmp_M(1,nages(ispp));
+
+  dvar_vector Ctmp(1,nages(ispp));
+
+  phitmp.initialize();
+  Ntmp_F.initialize();
+  Ntmp_M.initialize();
+  Ntmp_F(1) = 0.5;
+  Ntmp_M(1) = 0.5;
+  Fatmp_F.initialize();
+  Fatmp_M.initialize();
+  Ctmp.initialize();
+  int nagestmp=nages(ispp);
+  // Need catch of females and males separate since weights and selectivities are different...
+  // Catch equations needs to know total F (by sex) 
+  for ( j=1 ; j < nages(ispp); j++ )
+  {
+    for (m=1;m<=ngear(ispp);m++)
+    {
+      Fatmp_F(j) += Frat(ispp,m)* Ftmp*sel_F(ispp,m,j);
+      Fatmp_M(j) += Frat(ispp,m)* Ftmp*sel_M(ispp,m,j);
+    }
+    Ztmp_F(j)     = Fatmp_F(j) + M_F(ispp,j);
+    Ztmp_M(j)     = Fatmp_M(j) + M_M(ispp,j);
+    survtmp_F(j) = mfexp(-Ztmp_F(j));
+    survtmp_M(j) = mfexp(-Ztmp_M(j));
+
+    Ntmp_F(j+1)  =   Ntmp_F(j) * survtmp_F(j); // Begin numbers in the next year/age class
+    Ntmp_M(j+1)  =   Ntmp_M(j) * survtmp_M(j); // Begin numbers in the next year/age class
+  }
+  for (m=1;m<=ngear(ispp);m++)
+  {
+    Fatmp_F(nagestmp) += Frat(ispp,m)* Ftmp*sel_F(ispp,m,nagestmp);
+    Fatmp_M(nagestmp) += Frat(ispp,m)* Ftmp*sel_M(ispp,m,nagestmp);
+  }
+  Ztmp_F(nagestmp)     = Fatmp_F(nagestmp) + M_F(ispp,nagestmp);
+  Ztmp_M(nagestmp)     = Fatmp_M(nagestmp) + M_M(ispp,nagestmp);
+  survtmp_F(nagestmp) = mfexp(-Ztmp_F(nagestmp));
+  survtmp_M(nagestmp) = mfexp(-Ztmp_M(nagestmp));
+
+
+  Ntmp_F(nagestmp   )  /= (1.- survtmp_F(nagestmp   )); 
+  Ntmp_M(nagestmp   )  /= (1.- survtmp_M(nagestmp   )); 
+  //. for ( j=1 ; j <= nagestmp   ; j++ )
+  //. //. {
+    for (m=1;m<=ngear(ispp);m++)
+    {
+      // vector
+      Ctmp += elem_prod( wt_gear_F(ispp,m)  , elem_prod(elem_div( Ftmp*Frat(ispp,m)*sel_F(ispp,m) , Ztmp_F ),elem_prod(1.- survtmp_F,Ntmp_F)));
+      Ctmp += elem_prod( wt_gear_M(ispp,m)  , elem_prod(elem_div( Ftmp*Frat(ispp,m)*sel_M(ispp,m) , Ztmp_M ),elem_prod(1.- survtmp_M,Ntmp_M)));
+    }
+  //. }
+  // Ctmp(j)     = Ntmp(j) * Fatmp(j) * (1. - survtmp(j)) / Ztmp(j);
+
+  yldtmp = sum(Ctmp); //phi    = elem_prod(Ntmp , wttmp) * p_mature; // Kill these off till april as well!
+  phitmp = elem_prod( Ntmp_F , pow(survtmp_F,yrfrac(ispp)) ) * wt_mature_F(ispp)  ; //Req    = Requil(phi);
+  Req    = Requil(phitmp,ispp); 
+  yldtmp*= Req;
+  Stmp   = phitmp*Req;
+  Rtmp   = Req;   //cout<<Ntmp<<" "<<Ctmp<<" "<<wttmp; // cout<< Ftmp<<" "<<yldtmp<<" "<<phitmp<<endl;
+  phi(ispp) = phitmp;
+  return yldtmp;
+//+==+==+==+==+==+==+==+==+==+==+==+==+==+==+==+==+==+==+==+==+==+==+==+==+ 
+  /* FUNCTION dvar_vector yld(const dvar_vector& Fratio, const dvariable& Ftmp)
+  RETURN_ARRAYS_INCREMENT();
+  // dvariable utmp=1.-mfexp(-(Ftmp)); dvariable Ntmp; dvariable Btmp; dvariable yield; dvariable survtmp=exp(-1.*natmort); dvar_vector seltmp=sel_fsh(endyr); Ntmp = 1.; Btmp = Ntmp*wt(1)*seltmp(1); Stmp = .5*Ntmp*wt(1)*maturity(1); yield= 0.; for ( j=1 ; j < nages ; j++ ) { Ntmp  *= (1.-utmp*seltmp(j))*survtmp; Btmp  += Ntmp*wt(j+1)*seltmp(j+1); Stmp  += .5 * Ntmp *wt(j+1)*maturity(j+1); } //Max Age - 1 yr yield   += utmp * Btmp; Ntmp    /= (1-survtmp*(1.-utmp*seltmp(nages))); Btmp    += Ntmp*wt(nages)*seltmp(nages); Stmp    += 0.5 *wt(nages)* Ntmp *maturity(nages); yield   += utmp * Btmp; //cout<<yield<<" "<<Stmp<<" "<<Btmp<<" ";
+  dvar_vector msy_stuff(1,5);
+  dvariable phi;
+  dvar_vector Ntmp(1,nages);
+  dvar_vector Ctmp(1,nages);
+  msy_stuff.initialize();
+
+  dvar_matrix seltmp(1,nfsh,1,nages);
+  for (k=1;k<=nfsh;k++)
+   seltmp(k) = sel_fsh(k,endyr); // NOTE uses last-year of fishery selectivity for projections.
+
+  dvar_matrix Fatmp(1,nfsh,1,nages);
+  dvar_vector Ztmp(1,nages);
+
+  Ztmp = natmort;
+  for (k=1;k<=nfsh;k++)
+  { 
+    Fatmp(k) = Fratio(k) * Ftmp * seltmp(k);
+    Ztmp    += Fatmp(k);
+  } 
+  dvar_vector survtmp = exp(-Ztmp);
+
+  Ntmp(1) = 1.;
+  for ( j=1 ; j < nages; j++ )
+    Ntmp(j+1)  =   Ntmp(j) * survtmp(j); // Begin numbers in the next year/age class
+  Ntmp(nages)  /= (1.- survtmp(nages)); 
+
+  for (k=1;k<=nfsh;k++)
+  {
+    Ctmp.initialize();
+    for ( j=1 ; j <= nages; j++ )
+      Ctmp(j)      = Ntmp(j) * Fatmp(k,j) * (1. - survtmp(j)) / Ztmp(j);
+
+    msy_stuff(2)  += wt_fsh(k,endyr) * Ctmp;
+  }
+  phi    = elem_prod( Ntmp , pow(survtmp,spmo_frac ) ) * wt_mature_F;
+  // Req    = Requil(phi) * exp(sigmarsq/2);
+  msy_stuff(5)  = Ntmp * wt_pop;      
+  msy_stuff(4)  = phi/phizero ;       // SPR
+  msy_stuff(3)  = Requil(phi) ;       // Eq Recruitment
+  msy_stuff(5) *= msy_stuff(3);       // BmsyTot
+  msy_stuff(2) *= msy_stuff(3);       // MSY
+  msy_stuff(1)  = phi*(msy_stuff(3)); // Bmsy
+  RETURN_ARRAYS_DECREMENT();
+  return msy_stuff;
+  */ 
+
+
+FUNCTION double get_spr_rates(double spr_percent,int& ispp)
+  dmatrix sel_tmp_F(1,nages(ispp),1,ngear(ispp));
+  double df=1.e-4;
+  double F1 ;
+
+  sel_tmp_F.initialize();
+  sel_tmp_F = trans(sel_F(ispp));
+  F1 = 0.0; 
+  F1 = .8*(0.35/spr_percent)*M_F(ispp,2); // Start at some fraction of natural mortality
+  double F2;
+  double F3;
+  double yld1;
+  double yld2;
+  double yld3;
+  double dyld;
+  double dyldp;
+  // Newton Raphson stuff to go here, need to add gear type
+  for (int ii=1;ii<=9;ii++)
+  {
+    F2     = F1 + df;
+    F3     = F1 - df;
+    yld1   = -1000*square(log(spr_percent/spr_ratio(F1, sel_tmp_F, ispp)));
+    yld2   = -1000*square(log(spr_percent/spr_ratio(F2, sel_tmp_F, ispp)));
+    yld3   = -1000*square(log(spr_percent/spr_ratio(F3, sel_tmp_F, ispp)));
+    // cout<<F1<<" "<<F2<<" "<<F3<<" "<<yld1<<" "<<yld2<<endl;
+    // cout <<spr_percent<<" "<<spr_ratio(F1,sel_tmp)<<endl;
+    dyld   = (yld2 - yld3)/(2*df);                          // First derivative (to find the root of this)
+    dyldp  = (yld3-(2*yld1)+yld2)/(df*df);  // Newton-Raphson approximation for second derivitive
+    F1    -= dyld/dyldp;
+  }
+  return(F1);
+
+
+FUNCTION double spr_ratio(double& trial_F,dmatrix& sel_tmp_F, int& ispp)
+  double SBtmp;
+  dvector Ntmp(1,nages(ispp));
+  dvector srvtmp_F(1,nages(ispp));
+  dmatrix Ftmp_F(1,nages(ispp),1,ngear(ispp));
+  SBtmp = 0.0;
+  Ntmp.initialize();
+  srvtmp_F.initialize();
+  Ftmp_F.initialize();
+  Ftmp_F = sel_tmp_F;
+  for (j=1;j<=nages(ispp);j++) 
+  {
+    Ftmp_F(j) = elem_prod(Ftmp_F(j), trial_F * Frat(ispp));
+    srvtmp_F(j)  = mfexp(-sum(Ftmp_F(j)) - M_F(ispp,j));
+  }
+  Ntmp(1)=1.;
+  j=1;
+  SBtmp  += Ntmp(j)*wt_mature_F(ispp,j)*pow(srvtmp_F(j),yrfrac(ispp));
+  for (j=2;j<nages(ispp);j++)
+  {
+    Ntmp(j) = Ntmp(j-1)*srvtmp_F(j-1);
+    SBtmp  += Ntmp(j)*wt_mature_F(ispp,j)*pow(srvtmp_F(j),yrfrac(ispp));
+  }
+  Ntmp(nages(ispp))=Ntmp(nages(ispp)-1)*srvtmp_F(nages(ispp)-1)/(1.-srvtmp_F(nages(ispp)));
+
+  SBtmp  += Ntmp(nages(ispp))*wt_mature_F(ispp,nages(ispp))*pow(srvtmp_F(nages(ispp)),yrfrac(ispp));
+  SBtmp *=  AMeanRec(ispp) ;
+  // cout<<"Trial= "<<trial_F<<endl<<SBtmp/SB100(ispp)<<endl<<Ntmp(1,5)<<endl<<srvtmp_F(6,nages(ispp))<<endl;
+  return(SBtmp/SB100(ispp));
+
+FUNCTION void do_elasticity()
+  cout << "starting elasticities" << endl;
+
+  elasticity << "species,sex,age,parameter,value,elasticity" << endl;
+  int ispp=1;
+
+  int igear=1;
+  double lambda=exp(0.000001);
+  double x0, xminus, xplus, elas;
+  for(int ispp=1; ispp<=nspp; ispp++){
+    for(int a=1;a<=nages(ispp);a++){
+      // mortality
+      x0=M_F(ispp,a);
+      M_F(ispp,a)*=lambda;	  
+      xminus  = (get_spr_rates(.35,ispp));
+      M_F(ispp,a)/=lambda*lambda;
+      xplus  = (get_spr_rates(.35,ispp));
+      elas= (log(xplus)-log(xminus))/(2*log(lambda));
+      M_F(ispp,a)=x0;		// Reset parameter
+      elasticity << spname(ispp) << "," << "female," << a << "," << "M_F,"<< x0<< "," << elas << endl;
+      // Selectivity
+      x0=sel_F(ispp,igear,a);
+      sel_F(ispp,igear,a)*=lambda;	  
+      xminus  = (get_spr_rates(.35,ispp));
+      sel_F(ispp,igear,a)/=lambda*lambda;
+      xplus  = (get_spr_rates(.35,ispp));
+      elas= (log(xplus)-log(xminus))/(2*log(lambda));
+      sel_F(ispp,igear,a)=x0;     // Reset parameter
+      elasticity << spname(ispp) << "," << "female," << a << "," << "sel_F,"<< x0<< "," << elas << endl;
+      // // maturity
+      // x0=pmature_F(ispp,a);
+      // pmature_F(ispp,a)*=lambda;	  
+      // xminus  = (get_spr_rates(.35,ispp));
+      // pmature_F(ispp,a)/=lambda*lambda;
+      // xplus  = (get_spr_rates(.35,ispp));
+      // elas= (log(xplus)-log(xminus))/(2*log(lambda));
+      // pmature_F(ispp,a)=x0;     // Reset parameter
+      // elasticity << spname(ispp) << "," << "female," << a << "," << "pmature_F,"<< x0<< "," << elas << endl;
+      // spawning WAA
+      x0=wt_mature_F(ispp,a);
+      wt_mature_F(ispp,a)*=lambda;	  
+      xminus  = (get_spr_rates(.35,ispp));
+      wt_mature_F(ispp,a)/=lambda*lambda;
+      xplus  = (get_spr_rates(.35,ispp));
+      elas= (log(xplus)-log(xminus))/(2*log(lambda));
+      wt_mature_F(ispp,a)=x0;     // Reset parameter
+      elasticity << spname(ispp) << "," << "female," << a << "," << "wt_mature_F,"<< x0<< "," << elas << endl;
+    }
+  }
+  // */ 
+RUNTIME_SECTION
+   maximum_function_evaluations 100,200,5000
+   convergence_criteria .1,.01,1e-5
+
+TOP_OF_MAIN_SECTION
+  /*
+  gradient_structure::set_MAX_NVAR_OFFSET(1000);
+  gradient_structure::set_GRADSTACK_BUFFER_SIZE(100000);
+  gradient_structure::set_CMPDIF_BUFFER_SIZE(1000000);
+  */
+  arrmblsize  = 10000000 ;
+
diff --git a/examples/atka/percentdb.out b/examples/atka/percentdb.out
new file mode 100644
index 0000000..47ae89e
--- /dev/null
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+Model_16.0b 7 2033 CMean 94992.9
+Model_16.0b 7 2033 CStdn 30777.8
+Model_16.0b 7 2034 Cabc 90158.7
+Model_16.0b 7 2034 Cofl 97763.1
+Model_16.0b 7 2034 CLCI 52825.7
+Model_16.0b 7 2034 CUCI 148482
+Model_16.0b 7 2034 CMedian 91465.5
+Model_16.0b 7 2034 CMean 94715.8
+Model_16.0b 7 2034 CStdn 30630.9
+Model_16.0b 7 2035 Cabc 90158.7
+Model_16.0b 7 2035 Cofl 97763.1
+Model_16.0b 7 2035 CLCI 52408.5
+Model_16.0b 7 2035 CUCI 149433
+Model_16.0b 7 2035 CMedian 90370.8
+Model_16.0b 7 2035 CMean 94592.2
+Model_16.0b 7 2035 CStdn 30502.3
+Model_16.0b 7 2036 Cabc 90158.7
+Model_16.0b 7 2036 Cofl 97763.1
+Model_16.0b 7 2036 CLCI 53787.7
+Model_16.0b 7 2036 CUCI 145773
+Model_16.0b 7 2036 CMedian 91443
+Model_16.0b 7 2036 CMean 94977.4
+Model_16.0b 7 2036 CStdn 30522.4
+Model_16.0b 7 2022 SSBF100 280456
+Model_16.0b 7 2022 SSBFabc 112182
+Model_16.0b 7 2022 SSBFofl 98159.5
+Model_16.0b 7 2022 SSBLCI 137805
+Model_16.0b 7 2022 SSBUCI 137805
+Model_16.0b 7 2022 SSBMedian 137805
+Model_16.0b 7 2022 SSBMean 137805
+Model_16.0b 7 2023 SSBF100 280456
+Model_16.0b 7 2023 SSBFabc 112182
+Model_16.0b 7 2023 SSBFofl 98159.5
+Model_16.0b 7 2023 SSBLCI 118560
+Model_16.0b 7 2023 SSBUCI 118675
+Model_16.0b 7 2023 SSBMedian 118591
+Model_16.0b 7 2023 SSBMean 118600
+Model_16.0b 7 2024 SSBF100 280456
+Model_16.0b 7 2024 SSBFabc 112182
+Model_16.0b 7 2024 SSBFofl 98159.5
+Model_16.0b 7 2024 SSBLCI 103622
+Model_16.0b 7 2024 SSBUCI 105317
+Model_16.0b 7 2024 SSBMedian 104077
+Model_16.0b 7 2024 SSBMean 104213
+Model_16.0b 7 2025 SSBF100 280456
+Model_16.0b 7 2025 SSBFabc 112182
+Model_16.0b 7 2025 SSBFofl 98159.5
+Model_16.0b 7 2025 SSBLCI 90972.3
+Model_16.0b 7 2025 SSBUCI 109146
+Model_16.0b 7 2025 SSBMedian 95866.9
+Model_16.0b 7 2025 SSBMean 97372.2
+Model_16.0b 7 2026 SSBF100 280456
+Model_16.0b 7 2026 SSBFabc 112182
+Model_16.0b 7 2026 SSBFofl 98159.5
+Model_16.0b 7 2026 SSBLCI 79963.8
+Model_16.0b 7 2026 SSBUCI 127372
+Model_16.0b 7 2026 SSBMedian 94429.2
+Model_16.0b 7 2026 SSBMean 97839.8
+Model_16.0b 7 2027 SSBF100 280456
+Model_16.0b 7 2027 SSBFabc 112182
+Model_16.0b 7 2027 SSBFofl 98159.5
+Model_16.0b 7 2027 SSBLCI 75803.6
+Model_16.0b 7 2027 SSBUCI 139946
+Model_16.0b 7 2027 SSBMedian 97143
+Model_16.0b 7 2027 SSBMean 101308
+Model_16.0b 7 2028 SSBF100 280456
+Model_16.0b 7 2028 SSBFabc 112182
+Model_16.0b 7 2028 SSBFofl 98159.5
+Model_16.0b 7 2028 SSBLCI 75371.2
+Model_16.0b 7 2028 SSBUCI 146226
+Model_16.0b 7 2028 SSBMedian 99854.9
+Model_16.0b 7 2028 SSBMean 103909
+Model_16.0b 7 2029 SSBF100 280456
+Model_16.0b 7 2029 SSBFabc 112182
+Model_16.0b 7 2029 SSBFofl 98159.5
+Model_16.0b 7 2029 SSBLCI 75276.1
+Model_16.0b 7 2029 SSBUCI 147355
+Model_16.0b 7 2029 SSBMedian 101337
+Model_16.0b 7 2029 SSBMean 105638
+Model_16.0b 7 2030 SSBF100 280456
+Model_16.0b 7 2030 SSBFabc 112182
+Model_16.0b 7 2030 SSBFofl 98159.5
+Model_16.0b 7 2030 SSBLCI 75835
+Model_16.0b 7 2030 SSBUCI 149132
+Model_16.0b 7 2030 SSBMedian 101312
+Model_16.0b 7 2030 SSBMean 106163
+Model_16.0b 7 2031 SSBF100 280456
+Model_16.0b 7 2031 SSBFabc 112182
+Model_16.0b 7 2031 SSBFofl 98159.5
+Model_16.0b 7 2031 SSBLCI 75307.4
+Model_16.0b 7 2031 SSBUCI 148766
+Model_16.0b 7 2031 SSBMedian 102298
+Model_16.0b 7 2031 SSBMean 105952
+Model_16.0b 7 2032 SSBF100 280456
+Model_16.0b 7 2032 SSBFabc 112182
+Model_16.0b 7 2032 SSBFofl 98159.5
+Model_16.0b 7 2032 SSBLCI 75225.1
+Model_16.0b 7 2032 SSBUCI 152516
+Model_16.0b 7 2032 SSBMedian 100834
+Model_16.0b 7 2032 SSBMean 105932
+Model_16.0b 7 2033 SSBF100 280456
+Model_16.0b 7 2033 SSBFabc 112182
+Model_16.0b 7 2033 SSBFofl 98159.5
+Model_16.0b 7 2033 SSBLCI 75687.9
+Model_16.0b 7 2033 SSBUCI 153140
+Model_16.0b 7 2033 SSBMedian 100671
+Model_16.0b 7 2033 SSBMean 105887
+Model_16.0b 7 2034 SSBF100 280456
+Model_16.0b 7 2034 SSBFabc 112182
+Model_16.0b 7 2034 SSBFofl 98159.5
+Model_16.0b 7 2034 SSBLCI 76455.9
+Model_16.0b 7 2034 SSBUCI 152407
+Model_16.0b 7 2034 SSBMedian 101238
+Model_16.0b 7 2034 SSBMean 105562
+Model_16.0b 7 2035 SSBF100 280456
+Model_16.0b 7 2035 SSBFabc 112182
+Model_16.0b 7 2035 SSBFofl 98159.5
+Model_16.0b 7 2035 SSBLCI 76377.6
+Model_16.0b 7 2035 SSBUCI 152518
+Model_16.0b 7 2035 SSBMedian 100447
+Model_16.0b 7 2035 SSBMean 105418
+Model_16.0b 7 2036 SSBF100 280456
+Model_16.0b 7 2036 SSBFabc 112182
+Model_16.0b 7 2036 SSBFofl 98159.5
+Model_16.0b 7 2036 SSBLCI 77009.4
+Model_16.0b 7 2036 SSBUCI 149873
+Model_16.0b 7 2036 SSBMedian 101415
+Model_16.0b 7 2036 SSBMean 105799
+Model_16.0b 7 2022 F0 0 
+Model_16.0b 7 2022 Fabc 0.60874
+Model_16.0b 7 2022 Fofl 0.762079
+Model_16.0b 7 2022  F_LCI 0.37197
+Model_16.0b 7 2022  F_UCI 0.37197
+Model_16.0b 7 2022  F_Median 0.37197
+Model_16.0b 7 2022  F_Mean 0.37197
+Model_16.0b 7 2023 F0 0 
+Model_16.0b 7 2023 Fabc 0.60874
+Model_16.0b 7 2023 Fofl 0.762079
+Model_16.0b 7 2023  F_LCI 0.608739
+Model_16.0b 7 2023  F_UCI 0.608739
+Model_16.0b 7 2023  F_Median 0.608739
+Model_16.0b 7 2023  F_Mean 0.608739
+Model_16.0b 7 2024 F0 0 
+Model_16.0b 7 2024 Fabc 0.60874
+Model_16.0b 7 2024 Fofl 0.762079
+Model_16.0b 7 2024  F_LCI 0.559495
+Model_16.0b 7 2024  F_UCI 0.569247
+Model_16.0b 7 2024  F_Median 0.562111
+Model_16.0b 7 2024  F_Mean 0.562892
+Model_16.0b 7 2025 F0 0 
+Model_16.0b 7 2025 Fabc 0.60874
+Model_16.0b 7 2025 Fofl 0.762079
+Model_16.0b 7 2025  F_LCI 0.610428
+Model_16.0b 7 2025  F_UCI 0.741397
+Model_16.0b 7 2025  F_Median 0.645771
+Model_16.0b 7 2025  F_Mean 0.65535
+Model_16.0b 7 2026 F0 0 
+Model_16.0b 7 2026 Fabc 0.60874
+Model_16.0b 7 2026 Fofl 0.762079
+Model_16.0b 7 2026  F_LCI 0.531226
+Model_16.0b 7 2026  F_UCI 0.762079
+Model_16.0b 7 2026  F_Median 0.635303
+Model_16.0b 7 2026  F_Mean 0.644657
+Model_16.0b 7 2027 F0 0 
+Model_16.0b 7 2027 Fabc 0.60874
+Model_16.0b 7 2027 Fofl 0.762079
+Model_16.0b 7 2027  F_LCI 0.501486
+Model_16.0b 7 2027  F_UCI 0.762079
+Model_16.0b 7 2027  F_Median 0.654937
+Model_16.0b 7 2027  F_Mean 0.653947
+Model_16.0b 7 2028 F0 0 
+Model_16.0b 7 2028 Fabc 0.60874
+Model_16.0b 7 2028 Fofl 0.762079
+Model_16.0b 7 2028  F_LCI 0.498284
+Model_16.0b 7 2028  F_UCI 0.762079
+Model_16.0b 7 2028  F_Median 0.674486
+Model_16.0b 7 2028  F_Mean 0.665081
+Model_16.0b 7 2029 F0 0 
+Model_16.0b 7 2029 Fabc 0.60874
+Model_16.0b 7 2029 Fofl 0.762079
+Model_16.0b 7 2029  F_LCI 0.497486
+Model_16.0b 7 2029  F_UCI 0.762079
+Model_16.0b 7 2029  F_Median 0.685308
+Model_16.0b 7 2029  F_Mean 0.669965
+Model_16.0b 7 2030 F0 0 
+Model_16.0b 7 2030 Fabc 0.60874
+Model_16.0b 7 2030 Fofl 0.762079
+Model_16.0b 7 2030  F_LCI 0.501558
+Model_16.0b 7 2030  F_UCI 0.762079
+Model_16.0b 7 2030  F_Median 0.684848
+Model_16.0b 7 2030  F_Mean 0.670046
+Model_16.0b 7 2031 F0 0 
+Model_16.0b 7 2031 Fabc 0.60874
+Model_16.0b 7 2031 Fofl 0.762079
+Model_16.0b 7 2031  F_LCI 0.497977
+Model_16.0b 7 2031  F_UCI 0.762079
+Model_16.0b 7 2031  F_Median 0.692097
+Model_16.0b 7 2031  F_Mean 0.670554
+Model_16.0b 7 2032 F0 0 
+Model_16.0b 7 2032 Fabc 0.60874
+Model_16.0b 7 2032 Fofl 0.762079
+Model_16.0b 7 2032  F_LCI 0.497465
+Model_16.0b 7 2032  F_UCI 0.762079
+Model_16.0b 7 2032  F_Median 0.681547
+Model_16.0b 7 2032  F_Mean 0.668802
+Model_16.0b 7 2033 F0 0 
+Model_16.0b 7 2033 Fabc 0.60874
+Model_16.0b 7 2033 Fofl 0.762079
+Model_16.0b 7 2033  F_LCI 0.500613
+Model_16.0b 7 2033  F_UCI 0.762079
+Model_16.0b 7 2033  F_Median 0.680293
+Model_16.0b 7 2033  F_Mean 0.667415
+Model_16.0b 7 2034 F0 0 
+Model_16.0b 7 2034 Fabc 0.60874
+Model_16.0b 7 2034 Fofl 0.762079
+Model_16.0b 7 2034  F_LCI 0.506178
+Model_16.0b 7 2034  F_UCI 0.762079
+Model_16.0b 7 2034  F_Median 0.68459
+Model_16.0b 7 2034  F_Mean 0.667143
+Model_16.0b 7 2035 F0 0 
+Model_16.0b 7 2035 Fabc 0.60874
+Model_16.0b 7 2035 Fofl 0.762079
+Model_16.0b 7 2035  F_LCI 0.505546
+Model_16.0b 7 2035  F_UCI 0.762079
+Model_16.0b 7 2035  F_Median 0.678829
+Model_16.0b 7 2035  F_Mean 0.667587
+Model_16.0b 7 2036 F0 0 
+Model_16.0b 7 2036 Fabc 0.60874
+Model_16.0b 7 2036 Fofl 0.762079
+Model_16.0b 7 2036  F_LCI 0.510126
+Model_16.0b 7 2036  F_UCI 0.762079
+Model_16.0b 7 2036  F_Median 0.685856
+Model_16.0b 7 2036  F_Mean 0.668659
diff --git a/examples/atka/percentiles.out b/examples/atka/percentiles.out
new file mode 100644
index 0000000..e523f85
--- /dev/null
+++ b/examples/atka/percentiles.out
@@ -0,0 +1,509 @@
+
+SB0 SB40 SB35 MeanRec HarMeanRec Bnow
+280456 112182 98159.5 290.179 427.543 184017 
+CV Recruit
+0.59785 
+Alternative 1 Alternative  Stock: Model_16.0b
+Catch Model_16.0b
+Year C0 Cabc Cofl LowCI_Catch Median_Catch Mean_Catch UpperCI_Catch Stdev_Catch 
+2022  0 90158.7 97763.1 66481 66481 66481 66481 1.58616e-09 
+2023  0 90158.7 97763.1 83799.9 83799.9 83799.9 83799.9 0.000153662 
+2024  0 90158.7 97763.1 73494.9 73494.9 73495 73495 0.00619958 
+2025  0 90158.7 97763.1 71166 78758.1 80839 96876.5 8266.72 
+2026  0 90158.7 97763.1 55364.1 75043 77777.1 107224 16833.4 
+2027  0 90158.7 97763.1 49254.4 77801.6 80536.7 118114 21724 
+2028  0 90158.7 97763.1 48753 83719 84714.7 125866 23368.9 
+2029  0 90158.7 97763.1 49057 86452.6 87345.6 125675 24848.4 
+2030  0 90158.7 97763.1 49321 89352.8 88654.4 132010 25926.4 
+2031  0 90158.7 97763.1 49326.5 89682.3 89114.6 133609 25988.3 
+2032  0 90158.7 97763.1 48499.4 88803.5 89109 132479 26176.2 
+2033  0 90158.7 97763.1 50175.8 88274.1 88865.1 134981 26513.4 
+2034  0 90158.7 97763.1 51047.3 88282.6 88605 135081 26478.7 
+2035  0 90158.7 97763.1 50239.5 88306 88577 135030 26341.6 
+2036  0 90158.7 97763.1 51636.9 88832 88884.6 131597 26298.9 
+
+Spawning_Biomass Model_16.0b
+Year SSB100 SSBabc SSBofl LowCI_SSB Median_SSB Mean_SSB UpperCI_SSB Stdev_SSB 
+2022 280456 112182 98159.5 137805 137805 137805 137805 1.74623e-09 
+2023 280456 112182 98159.5 122497 122531 122541 122622 40.6215 
+2024 280456 112182 98159.5 110274 110924 111122 112705 793.717 
+2025 280456 112182 98159.5 98349.5 103547 105236 118623 6695.12 
+2026 280456 112182 98159.5 87086 102324 106221 138493 16987.7 
+2027 280456 112182 98159.5 82293.3 105040 110493 155635 23073.6 
+2028 280456 112182 98159.5 81831.7 108690 113880 163130 24663.9 
+2029 280456 112182 98159.5 81558.9 110176 116270 163302 26583.7 
+2030 280456 112182 98159.5 82450.7 111464 117263 168514 27780 
+2031 280456 112182 98159.5 82381.7 112257 117281 166820 27426.4 
+2032 280456 112182 98159.5 82076.7 111044 117310 168186 27945.6 
+2033 280456 112182 98159.5 82244.7 110735 117279 170753 28515.9 
+2034 280456 112182 98159.5 83475.6 111307 116943 170988 28138 
+2035 280456 112182 98159.5 82804.2 110655 116752 172108 28379.7 
+2036 280456 112182 98159.5 83884.9 110930 117090 165508 28430.8 
+
+Fishing_mortalityModel_16.0b
+Year F0 Fabc Fofl LowCI_F Median_F Mean_F UpperCI_F Stdev_F 
+2022  0 0.60874 0.762079 0.37197 0.37197 0.37197 0.37197 7.93809e-15 
+2023  0 0.60874 0.762079 0.503577 0.503777 0.503755 0.503849 8.81969e-05 
+2024  0 0.60874 0.762079 0.475132 0.483929 0.482975 0.48718 0.0039032 
+2025  0 0.60874 0.762079 0.529208 0.559087 0.563903 0.60874 0.0262081 
+2026  0 0.60874 0.762079 0.464733 0.552158 0.549328 0.60874 0.0508888 
+2027  0 0.60874 0.762079 0.437378 0.567755 0.552255 0.60874 0.0604702 
+2028  0 0.60874 0.762079 0.434827 0.588688 0.560896 0.60874 0.0600137 
+2029  0 0.60874 0.762079 0.433385 0.597219 0.563196 0.60874 0.0596282 
+2030  0 0.60874 0.762079 0.438385 0.604615 0.563517 0.60874 0.0606096 
+2031  0 0.60874 0.762079 0.437839 0.60874 0.564228 0.60874 0.0615347 
+2032  0 0.60874 0.762079 0.436318 0.602204 0.563868 0.60874 0.060332 
+2033  0 0.60874 0.762079 0.437409 0.60043 0.562784 0.60874 0.0592291 
+2034  0 0.60874 0.762079 0.444281 0.603707 0.562439 0.60874 0.0593928 
+2035  0 0.60874 0.762079 0.440319 0.599959 0.563452 0.60874 0.0584495 
+2036  0 0.60874 0.762079 0.446608 0.601539 0.564489 0.60874 0.0584525 
+
+Total_BiomassModel_16.0b
+Year B100 Babc Bofl LowCI_Biom Median_Biom Mean_Biom UpperCI_Biom Stdev_Biom 
+2022 1.00952e+06 661143 629123 631455 631455 631455 631455 9.54606e-09 
+2023 1.00952e+06 661143 629123 593268 609942 615027 656022 20433.9 
+2024 1.00952e+06 661143 629123 521363 589420 606662 747824 74036.8 
+2025 1.00952e+06 661143 629123 475587 598698 623219 846148 115782 
+2026 1.00952e+06 661143 629123 455001 610209 635879 901036 134079 
+2027 1.00952e+06 661143 629123 448273 630885 655119 913536 146637 
+2028 1.00952e+06 661143 629123 454916 647260 668308 945712 156059 
+2029 1.00952e+06 661143 629123 453365 651331 673907 963060 158341 
+2030 1.00952e+06 661143 629123 455796 655627 676706 964844 159772 
+2031 1.00952e+06 661143 629123 460586 650641 677145 971163 162772 
+2032 1.00952e+06 661143 629123 459585 647540 675478 994597 162630 
+2033 1.00952e+06 661143 629123 464828 650269 674184 981270 162731 
+2034 1.00952e+06 661143 629123 460766 651679 674838 959593 162657 
+2035 1.00952e+06 661143 629123 459223 651756 677120 959143 162095 
+2036 1.00952e+06 661143 629123 456284 656115 676236 966643 158265 
+Alternative 2 Alternative  Stock: Model_16.0b
+Catch Model_16.0b
+Year C0 Cabc Cofl LowCI_Catch Median_Catch Mean_Catch UpperCI_Catch Stdev_Catch 
+2022  0 90158.7 97763.1 66481 66481 66481 66481 1.58616e-09 
+2023  0 90158.7 97763.1 83799.9 83799.9 83799.9 83799.9 0.000153662 
+2024  0 90158.7 97763.1 73494.9 73494.9 73495 73495 0.00619958 
+2025  0 90158.7 97763.1 71166 78758.1 80839 96876.5 8266.72 
+2026  0 90158.7 97763.1 55364.1 75043 77777.1 107224 16833.4 
+2027  0 90158.7 97763.1 49254.4 77801.6 80536.7 118114 21724 
+2028  0 90158.7 97763.1 48753 83719 84714.7 125866 23368.9 
+2029  0 90158.7 97763.1 49057 86452.6 87345.6 125675 24848.4 
+2030  0 90158.7 97763.1 49321 89352.8 88654.4 132010 25926.4 
+2031  0 90158.7 97763.1 49326.5 89682.3 89114.6 133609 25988.3 
+2032  0 90158.7 97763.1 48499.4 88803.5 89109 132479 26176.2 
+2033  0 90158.7 97763.1 50175.8 88274.1 88865.1 134981 26513.4 
+2034  0 90158.7 97763.1 51047.3 88282.6 88605 135081 26478.7 
+2035  0 90158.7 97763.1 50239.5 88306 88577 135030 26341.6 
+2036  0 90158.7 97763.1 51636.9 88832 88884.6 131597 26298.9 
+
+Spawning_Biomass Model_16.0b
+Year SSB100 SSBabc SSBofl LowCI_SSB Median_SSB Mean_SSB UpperCI_SSB Stdev_SSB 
+2022 280456 112182 98159.5 137805 137805 137805 137805 1.74623e-09 
+2023 280456 112182 98159.5 122497 122531 122541 122622 40.6215 
+2024 280456 112182 98159.5 110274 110924 111122 112705 793.717 
+2025 280456 112182 98159.5 98349.5 103547 105236 118623 6695.12 
+2026 280456 112182 98159.5 87086 102324 106221 138493 16987.7 
+2027 280456 112182 98159.5 82293.3 105040 110493 155635 23073.6 
+2028 280456 112182 98159.5 81831.7 108690 113880 163130 24663.9 
+2029 280456 112182 98159.5 81558.9 110176 116270 163302 26583.7 
+2030 280456 112182 98159.5 82450.7 111464 117263 168514 27780 
+2031 280456 112182 98159.5 82381.7 112257 117281 166820 27426.4 
+2032 280456 112182 98159.5 82076.7 111044 117310 168186 27945.6 
+2033 280456 112182 98159.5 82244.7 110735 117279 170753 28515.9 
+2034 280456 112182 98159.5 83475.6 111307 116943 170988 28138 
+2035 280456 112182 98159.5 82804.2 110655 116752 172108 28379.7 
+2036 280456 112182 98159.5 83884.9 110930 117090 165508 28430.8 
+
+Fishing_mortalityModel_16.0b
+Year F0 Fabc Fofl LowCI_F Median_F Mean_F UpperCI_F Stdev_F 
+2022  0 0.60874 0.762079 0.37197 0.37197 0.37197 0.37197 7.93809e-15 
+2023  0 0.60874 0.762079 0.503577 0.503777 0.503755 0.503849 8.81969e-05 
+2024  0 0.60874 0.762079 0.475132 0.483929 0.482975 0.48718 0.0039032 
+2025  0 0.60874 0.762079 0.529208 0.559087 0.563903 0.60874 0.0262081 
+2026  0 0.60874 0.762079 0.464733 0.552158 0.549328 0.60874 0.0508888 
+2027  0 0.60874 0.762079 0.437378 0.567755 0.552255 0.60874 0.0604702 
+2028  0 0.60874 0.762079 0.434827 0.588688 0.560896 0.60874 0.0600137 
+2029  0 0.60874 0.762079 0.433385 0.597219 0.563196 0.60874 0.0596282 
+2030  0 0.60874 0.762079 0.438385 0.604615 0.563517 0.60874 0.0606096 
+2031  0 0.60874 0.762079 0.437839 0.60874 0.564228 0.60874 0.0615347 
+2032  0 0.60874 0.762079 0.436318 0.602204 0.563868 0.60874 0.060332 
+2033  0 0.60874 0.762079 0.437409 0.60043 0.562784 0.60874 0.0592291 
+2034  0 0.60874 0.762079 0.444281 0.603707 0.562439 0.60874 0.0593928 
+2035  0 0.60874 0.762079 0.440319 0.599959 0.563452 0.60874 0.0584495 
+2036  0 0.60874 0.762079 0.446608 0.601539 0.564489 0.60874 0.0584525 
+
+Total_BiomassModel_16.0b
+Year B100 Babc Bofl LowCI_Biom Median_Biom Mean_Biom UpperCI_Biom Stdev_Biom 
+2022 1.00952e+06 661143 629123 631455 631455 631455 631455 9.54606e-09 
+2023 1.00952e+06 661143 629123 593268 609942 615027 656022 20433.9 
+2024 1.00952e+06 661143 629123 521363 589420 606662 747824 74036.8 
+2025 1.00952e+06 661143 629123 475587 598698 623219 846148 115782 
+2026 1.00952e+06 661143 629123 455001 610209 635879 901036 134079 
+2027 1.00952e+06 661143 629123 448273 630885 655119 913536 146637 
+2028 1.00952e+06 661143 629123 454916 647260 668308 945712 156059 
+2029 1.00952e+06 661143 629123 453365 651331 673907 963060 158341 
+2030 1.00952e+06 661143 629123 455796 655627 676706 964844 159772 
+2031 1.00952e+06 661143 629123 460586 650641 677145 971163 162772 
+2032 1.00952e+06 661143 629123 459585 647540 675478 994597 162630 
+2033 1.00952e+06 661143 629123 464828 650269 674184 981270 162731 
+2034 1.00952e+06 661143 629123 460766 651679 674838 959593 162657 
+2035 1.00952e+06 661143 629123 459223 651756 677120 959143 162095 
+2036 1.00952e+06 661143 629123 456284 656115 676236 966643 158265 
+Alternative 3 Alternative  Stock: Model_16.0b
+Catch Model_16.0b
+Year C0 Cabc Cofl LowCI_Catch Median_Catch Mean_Catch UpperCI_Catch Stdev_Catch 
+2022  0 90158.7 97763.1 66481 66481 66481 66481 1.58616e-09 
+2023  0 90158.7 97763.1 83799.9 83799.9 83799.9 83799.9 0.000153662 
+2024  0 90158.7 97763.1 73494.9 73494.9 73495 73495 0.00619958 
+2025  0 90158.7 97763.1 63750.4 67284.6 68344.2 76661 4196.93 
+2026  0 90158.7 97763.1 57206.5 67037.1 69221 88421.8 10110.8 
+2027  0 90158.7 97763.1 53225.4 69327.4 72154.2 100265 14670.9 
+2028  0 90158.7 97763.1 52315.4 72858.8 75774.3 108134 16959.6 
+2029  0 90158.7 97763.1 52817.1 75849 78666.5 110890 18487.8 
+2030  0 90158.7 97763.1 53542.5 77918.2 80417 114561 19548.5 
+2031  0 90158.7 97763.1 53345.3 78822.3 81152.4 117067 19745.1 
+2032  0 90158.7 97763.1 53951.2 78613.6 81426.3 117481 19937.2 
+2033  0 90158.7 97763.1 54218.5 78449.5 81470.7 118087 20228 
+2034  0 90158.7 97763.1 54395.1 78449.6 81307.9 119727 20197 
+2035  0 90158.7 97763.1 54501.8 78157.7 81190.1 119416 20187.8 
+2036  0 90158.7 97763.1 54535.2 78876.1 81341.3 116069 20151.9 
+
+Spawning_Biomass Model_16.0b
+Year SSB100 SSBabc SSBofl LowCI_SSB Median_SSB Mean_SSB UpperCI_SSB Stdev_SSB 
+2022 280456 112182 98159.5 137805 137805 137805 137805 1.74623e-09 
+2023 280456 112182 98159.5 122497 122531 122541 122622 40.6215 
+2024 280456 112182 98159.5 110274 110924 111122 112705 793.717 
+2025 280456 112182 98159.5 100335 106491 108351 123260 7496.11 
+2026 280456 112182 98159.5 89111.6 108319 112436 149311 19572.8 
+2027 280456 112182 98159.5 83436.5 113284 118834 171470 27589 
+2028 280456 112182 98159.5 82189.6 118651 123992 183254 29933 
+2029 280456 112182 98159.5 83781.1 122961 127796 181188 32066.3 
+2030 280456 112182 98159.5 83186.1 125789 129771 188442 33620.8 
+2031 280456 112182 98159.5 83954.9 126008 130390 189264 33474.4 
+2032 280456 112182 98159.5 83844.7 126074 130740 191503 33864.3 
+2033 280456 112182 98159.5 85606.3 125782 130856 194073 34466.2 
+2034 280456 112182 98159.5 85986.1 125710 130545 193974 34145 
+2035 280456 112182 98159.5 86173.9 125698 130365 194029 34230.6 
+2036 280456 112182 98159.5 86755.9 125971 130744 188094 34222.7 
+
+Fishing_mortalityModel_16.0b
+Year F0 Fabc Fofl LowCI_F Median_F Mean_F UpperCI_F Stdev_F 
+2022  0 0.60874 0.762079 0.37197 0.37197 0.37197 0.37197 7.93809e-15 
+2023  0 0.60874 0.762079 0.503577 0.503777 0.503755 0.503849 8.81969e-05 
+2024  0 0.60874 0.762079 0.475132 0.483929 0.482975 0.48718 0.0039032 
+2025  0 0.60874 0.762079 0.466309 0.466309 0.466309 0.466309 9.10383e-15 
+2026  0 0.60874 0.762079 0.466309 0.466309 0.466309 0.466309 9.10383e-15 
+2027  0 0.60874 0.762079 0.466309 0.466309 0.466309 0.466309 9.10383e-15 
+2028  0 0.60874 0.762079 0.466309 0.466309 0.466309 0.466309 9.10383e-15 
+2029  0 0.60874 0.762079 0.466309 0.466309 0.466309 0.466309 9.10383e-15 
+2030  0 0.60874 0.762079 0.466309 0.466309 0.466309 0.466309 9.10383e-15 
+2031  0 0.60874 0.762079 0.466309 0.466309 0.466309 0.466309 9.10383e-15 
+2032  0 0.60874 0.762079 0.466309 0.466309 0.466309 0.466309 9.10383e-15 
+2033  0 0.60874 0.762079 0.466309 0.466309 0.466309 0.466309 9.10383e-15 
+2034  0 0.60874 0.762079 0.466309 0.466309 0.466309 0.466309 9.10383e-15 
+2035  0 0.60874 0.762079 0.466309 0.466309 0.466309 0.466309 9.10383e-15 
+2036  0 0.60874 0.762079 0.466309 0.466309 0.466309 0.466309 9.10383e-15 
+
+Total_BiomassModel_16.0b
+Year B100 Babc Bofl LowCI_Biom Median_Biom Mean_Biom UpperCI_Biom Stdev_Biom 
+2022 1.00952e+06 661143 629123 631455 631455 631455 631455 9.54606e-09 
+2023 1.00952e+06 661143 629123 593268 609942 615027 656022 20433.9 
+2024 1.00952e+06 661143 629123 521363 589420 606662 747824 74036.8 
+2025 1.00952e+06 661143 629123 475587 598698 623219 846148 115782 
+2026 1.00952e+06 661143 629123 462527 622425 647097 916547 136286 
+2027 1.00952e+06 661143 629123 458990 648529 671754 939046 151347 
+2028 1.00952e+06 661143 629123 468171 667188 688996 975250 162058 
+2029 1.00952e+06 661143 629123 460078 677206 698241 987913 165354 
+2030 1.00952e+06 661143 629123 470047 683461 703659 1.00744e+06 167174 
+2031 1.00952e+06 661143 629123 471890 678579 705684 1.01321e+06 170120 
+2032 1.00952e+06 661143 629123 478544 679073 704965 1.03752e+06 169951 
+2033 1.00952e+06 661143 629123 478479 680208 704157 1.02101e+06 169952 
+2034 1.00952e+06 661143 629123 477389 680769 704901 995803 169650 
+2035 1.00952e+06 661143 629123 480462 684593 707148 995414 168940 
+2036 1.00952e+06 661143 629123 473596 684023 706319 997203 165445 
+Alternative 4 Alternative  Stock: Model_16.0b
+Catch Model_16.0b
+Year C0 Cabc Cofl LowCI_Catch Median_Catch Mean_Catch UpperCI_Catch Stdev_Catch 
+2022  0 90158.7 97763.1 66481 66481 66481 66481 1.58616e-09 
+2023  0 90158.7 97763.1 83799.9 83799.9 83799.9 83799.9 0.000153662 
+2024  0 90158.7 97763.1 73494.9 73494.9 73495 73495 0.00619958 
+2025  0 90158.7 97763.1 19687.5 20698.1 21003.3 23389.5 1203.81 
+2026  0 90158.7 97763.1 20667.3 23642.7 24298 30046.6 3063.21 
+2027  0 90158.7 97763.1 21463.9 26575.4 27524.6 36888.7 4821.96 
+2028  0 90158.7 97763.1 22557.7 29545.3 30646.8 42423 6029.06 
+2029  0 90158.7 97763.1 23244.7 32179.2 33192.6 45724.1 6951.84 
+2030  0 90158.7 97763.1 24439.4 34109 35022.6 48607 7666.48 
+2031  0 90158.7 97763.1 24711.2 35197.6 36130.5 50261.7 7953.86 
+2032  0 90158.7 97763.1 25270.4 35844.6 36748.2 51576.5 8083.41 
+2033  0 90158.7 97763.1 25608.2 35962.2 37137.3 52571.3 8227.02 
+2034  0 90158.7 97763.1 26148.2 36131.4 37319.3 53082 8263.54 
+2035  0 90158.7 97763.1 26344 36235.8 37419.1 53012 8267.42 
+2036  0 90158.7 97763.1 26360 36447.5 37561.6 51997.9 8250.29 
+
+Spawning_Biomass Model_16.0b
+Year SSB100 SSBabc SSBofl LowCI_SSB Median_SSB Mean_SSB UpperCI_SSB Stdev_SSB 
+2022 280456 112182 98159.5 137805 137805 137805 137805 1.74623e-09 
+2023 280456 112182 98159.5 122497 122531 122541 122622 40.6215 
+2024 280456 112182 98159.5 110274 110924 111122 112705 793.717 
+2025 280456 112182 98159.5 111751 118032 119949 135194 7663.62 
+2026 280456 112182 98159.5 114640 135187 139833 180169 21295.4 
+2027 280456 112182 98159.5 117797 152392 159044 221999 32617.9 
+2028 280456 112182 98159.5 123955 167909 174592 247424 37363.4 
+2029 280456 112182 98159.5 128457 180825 186748 258966 41148.3 
+2030 280456 112182 98159.5 135919 189405 195257 272016 44186.9 
+2031 280456 112182 98159.5 135923 195025 200665 282481 45091 
+2032 280456 112182 98159.5 140572 198918 204382 288037 45726.9 
+2033 280456 112182 98159.5 144293 199918 206960 291869 46688.3 
+2034 280456 112182 98159.5 146184 201577 208278 298799 46643.7 
+2035 280456 112182 98159.5 146582 202324 209150 295452 46620.4 
+2036 280456 112182 98159.5 147459 205118 210260 289529 46538 
+
+Fishing_mortalityModel_16.0b
+Year F0 Fabc Fofl LowCI_F Median_F Mean_F UpperCI_F Stdev_F 
+2022  0 0.60874 0.762079 0.37197 0.37197 0.37197 0.37197 7.93809e-15 
+2023  0 0.60874 0.762079 0.503577 0.503777 0.503755 0.503849 8.81969e-05 
+2024  0 0.60874 0.762079 0.475132 0.483929 0.482975 0.48718 0.0039032 
+2025  0 0.60874 0.762079 0.131302 0.131302 0.131302 0.131302 1.83187e-15 
+2026  0 0.60874 0.762079 0.131302 0.131302 0.131302 0.131302 1.83187e-15 
+2027  0 0.60874 0.762079 0.131302 0.131302 0.131302 0.131302 1.83187e-15 
+2028  0 0.60874 0.762079 0.131302 0.131302 0.131302 0.131302 1.83187e-15 
+2029  0 0.60874 0.762079 0.131302 0.131302 0.131302 0.131302 1.83187e-15 
+2030  0 0.60874 0.762079 0.131302 0.131302 0.131302 0.131302 1.83187e-15 
+2031  0 0.60874 0.762079 0.131302 0.131302 0.131302 0.131302 1.83187e-15 
+2032  0 0.60874 0.762079 0.131302 0.131302 0.131302 0.131302 1.83187e-15 
+2033  0 0.60874 0.762079 0.131302 0.131302 0.131302 0.131302 1.83187e-15 
+2034  0 0.60874 0.762079 0.131302 0.131302 0.131302 0.131302 1.83187e-15 
+2035  0 0.60874 0.762079 0.131302 0.131302 0.131302 0.131302 1.83187e-15 
+2036  0 0.60874 0.762079 0.131302 0.131302 0.131302 0.131302 1.83187e-15 
+
+Total_BiomassModel_16.0b
+Year B100 Babc Bofl LowCI_Biom Median_Biom Mean_Biom UpperCI_Biom Stdev_Biom 
+2022 1.00952e+06 661143 629123 631455 631455 631455 631455 9.54606e-09 
+2023 1.00952e+06 661143 629123 593268 609942 615027 656022 20433.9 
+2024 1.00952e+06 661143 629123 521363 589420 606662 747824 74036.8 
+2025 1.00952e+06 661143 629123 475587 598698 623219 846148 115782 
+2026 1.00952e+06 661143 629123 503408 665058 689852 963706 138037 
+2027 1.00952e+06 661143 629123 527021 722571 746148 1.02713e+06 156501 
+2028 1.00952e+06 661143 629123 556149 767397 787778 1.09679e+06 170337 
+2029 1.00952e+06 661143 629123 560323 797761 816146 1.13419e+06 176639 
+2030 1.00952e+06 661143 629123 581222 814125 836518 1.17117e+06 180528 
+2031 1.00952e+06 661143 629123 596070 823445 849655 1.19929e+06 184586 
+2032 1.00952e+06 661143 629123 603048 830823 856897 1.20491e+06 185027 
+2033 1.00952e+06 661143 629123 608380 837755 861836 1.21047e+06 185311 
+2034 1.00952e+06 661143 629123 617219 841860 866485 1.19841e+06 184793 
+2035 1.00952e+06 661143 629123 617779 851117 871299 1.19043e+06 183727 
+2036 1.00952e+06 661143 629123 614271 848961 872217 1.19323e+06 180547 
+Alternative 5 Alternative  Stock: Model_16.0b
+Catch Model_16.0b
+Year C0 Cabc Cofl LowCI_Catch Median_Catch Mean_Catch UpperCI_Catch Stdev_Catch 
+2022  0 90158.7 97763.1 66481 66481 66481 66481 1.58616e-09 
+2023  0 90158.7 97763.1 83799.9 83799.9 83799.9 83799.9 0.000153662 
+2024  0 90158.7 97763.1 73494.9 73494.9 73495 73495 0.00619958 
+2025  0 90158.7 97763.1 0 0 0 0 0 
+2026  0 90158.7 97763.1 0 0 0 0 0 
+2027  0 90158.7 97763.1 0 0 0 0 0 
+2028  0 90158.7 97763.1 0 0 0 0 0 
+2029  0 90158.7 97763.1 0 0 0 0 0 
+2030  0 90158.7 97763.1 0 0 0 0 0 
+2031  0 90158.7 97763.1 0 0 0 0 0 
+2032  0 90158.7 97763.1 0 0 0 0 0 
+2033  0 90158.7 97763.1 0 0 0 0 0 
+2034  0 90158.7 97763.1 0 0 0 0 0 
+2035  0 90158.7 97763.1 0 0 0 0 0 
+2036  0 90158.7 97763.1 0 0 0 0 0 
+
+Spawning_Biomass Model_16.0b
+Year SSB100 SSBabc SSBofl LowCI_SSB Median_SSB Mean_SSB UpperCI_SSB Stdev_SSB 
+2022 280456 112182 98159.5 137805 137805 137805 137805 1.74623e-09 
+2023 280456 112182 98159.5 122497 122531 122541 122622 40.6215 
+2024 280456 112182 98159.5 110274 110924 111122 112705 793.717 
+2025 280456 112182 98159.5 116646 122984 124921 140302 7731.08 
+2026 280456 112182 98159.5 127221 148382 153195 195180 22020.4 
+2027 280456 112182 98159.5 136894 173759 180788 249038 34934.4 
+2028 280456 112182 98159.5 149168 197068 204444 284233 41133.8 
+2029 280456 112182 98159.5 158854 217260 224184 305391 46273.5 
+2030 280456 112182 98159.5 170337 232957 239499 328860 50623.7 
+2031 280456 112182 98159.5 175100 245231 250678 345171 52641.1 
+2032 280456 112182 98159.5 183264 252552 259050 358387 53850.2 
+2033 280456 112182 98159.5 189418 258402 265413 370133 55275.9 
+2034 280456 112182 98159.5 194615 262142 269642 373937 55609.7 
+2035 280456 112182 98159.5 195882 264959 272719 375999 55674.2 
+2036 280456 112182 98159.5 202128 268433 275526 374689 55601.9 
+
+Fishing_mortalityModel_16.0b
+Year F0 Fabc Fofl LowCI_F Median_F Mean_F UpperCI_F Stdev_F 
+2022  0 0.60874 0.762079 0.37197 0.37197 0.37197 0.37197 7.93809e-15 
+2023  0 0.60874 0.762079 0.503577 0.503777 0.503755 0.503849 8.81969e-05 
+2024  0 0.60874 0.762079 0.475132 0.483929 0.482975 0.48718 0.0039032 
+2025  0 0.60874 0.762079 0 0 0 0 0 
+2026  0 0.60874 0.762079 0 0 0 0 0 
+2027  0 0.60874 0.762079 0 0 0 0 0 
+2028  0 0.60874 0.762079 0 0 0 0 0 
+2029  0 0.60874 0.762079 0 0 0 0 0 
+2030  0 0.60874 0.762079 0 0 0 0 0 
+2031  0 0.60874 0.762079 0 0 0 0 0 
+2032  0 0.60874 0.762079 0 0 0 0 0 
+2033  0 0.60874 0.762079 0 0 0 0 0 
+2034  0 0.60874 0.762079 0 0 0 0 0 
+2035  0 0.60874 0.762079 0 0 0 0 0 
+2036  0 0.60874 0.762079 0 0 0 0 0 
+
+Total_BiomassModel_16.0b
+Year B100 Babc Bofl LowCI_Biom Median_Biom Mean_Biom UpperCI_Biom Stdev_Biom 
+2022 1.00952e+06 661143 629123 631455 631455 631455 631455 9.54606e-09 
+2023 1.00952e+06 661143 629123 593268 609942 615027 656022 20433.9 
+2024 1.00952e+06 661143 629123 521363 589420 606662 747824 74036.8 
+2025 1.00952e+06 661143 629123 475587 598698 623219 846148 115782 
+2026 1.00952e+06 661143 629123 521788 684173 708936 984302 138748 
+2027 1.00952e+06 661143 629123 559790 759283 783248 1.06823e+06 158780 
+2028 1.00952e+06 661143 629123 607227 821012 841782 1.15253e+06 174400 
+2029 1.00952e+06 661143 629123 621017 864406 885856 1.20733e+06 182734 
+2030 1.00952e+06 661143 629123 653678 901176 920489 1.26816e+06 188451 
+2031 1.00952e+06 661143 629123 676815 919327 945953 1.30782e+06 193889 
+2032 1.00952e+06 661143 629123 697130 937536 963406 1.33329e+06 195330 
+2033 1.00952e+06 661143 629123 706283 949311 976626 1.33622e+06 196215 
+2034 1.00952e+06 661143 629123 727995 962936 987739 1.33609e+06 195848 
+2035 1.00952e+06 661143 629123 728595 974798 997501 1.34591e+06 194640 
+2036 1.00952e+06 661143 629123 725522 981692 1.00221e+06 1.35498e+06 191681 
+Alternative 6 Alternative  Stock: Model_16.0b
+Catch Model_16.0b
+Year C0 Cabc Cofl LowCI_Catch Median_Catch Mean_Catch UpperCI_Catch Stdev_Catch 
+2022  0 90158.7 97763.1 66481 66481 66481 66481 1.58616e-09 
+2023  0 90158.7 97763.1 118766 118782 118787 118825 19.3219 
+2024  0 90158.7 97763.1 83664.6 84578.2 84865.8 87143.1 1139.6 
+2025  0 90158.7 97763.1 66674.3 74527.3 77259.5 97792.5 10063.3 
+2026  0 90158.7 97763.1 54664.3 75939.4 80811 120083 21003.9 
+2027  0 90158.7 97763.1 50501.8 81869.5 86630.1 132249 26172.6 
+2028  0 90158.7 97763.1 50771.5 87553.3 91491 141323 27554.3 
+2029  0 90158.7 97763.1 50605.4 90292.9 94377.6 140755 29251.7 
+2030  0 90158.7 97763.1 51903.3 91726.7 95342.3 145373 30190.4 
+2031  0 90158.7 97763.1 51640 93447.2 95520 144548 30096 
+2032  0 90158.7 97763.1 51482.6 91022.7 95262.8 147515 30390.7 
+2033  0 90158.7 97763.1 51804.5 90899.6 94991.2 148388 30777.5 
+2034  0 90158.7 97763.1 52824.7 91464.6 94715 148481 30630.8 
+2035  0 90158.7 97763.1 52408.5 90369.7 94591.9 149432 30502.3 
+2036  0 90158.7 97763.1 53787.5 91442.9 94977.3 145773 30522.3 
+
+Spawning_Biomass Model_16.0b
+Year SSB100 SSBabc SSBofl LowCI_SSB Median_SSB Mean_SSB UpperCI_SSB Stdev_SSB 
+2022 280456 112182 98159.5 137805 137805 137805 137805 1.74623e-09 
+2023 280456 112182 98159.5 113073 113104 113113 113188 37.2384 
+2024 280456 112182 98159.5 95500.1 95945.4 96078.5 97160.4 541.194 
+2025 280456 112182 98159.5 86169.3 91122.6 92625 104551 6065.32 
+2026 280456 112182 98159.5 78158.3 92779.1 96169.1 125720 15424 
+2027 280456 112182 98159.5 75167.6 96748.6 100795 139273 20335.5 
+2028 280456 112182 98159.5 75202.3 99747.1 103763 146100 21481 
+2029 280456 112182 98159.5 75257.9 101314 105593 147330 23200.1 
+2030 280456 112182 98159.5 75817.5 101300 106143 149118 24053.9 
+2031 280456 112182 98159.5 75298.5 102288 105940 148737 23594.7 
+2032 280456 112182 98159.5 75219.7 100830 105926 152510 24195.7 
+2033 280456 112182 98159.5 75685.8 100669 105885 153136 24615.4 
+2034 280456 112182 98159.5 76454.6 101238 105560 152405 24211.9 
+2035 280456 112182 98159.5 76377.4 100446 105417 152517 24582.3 
+2036 280456 112182 98159.5 77009.3 101415 105799 149873 24618.5 
+
+Fishing_mortalityModel_16.0b
+Year F0 Fabc Fofl LowCI_F Median_F Mean_F UpperCI_F Stdev_F 
+2022  0 0.60874 0.762079 0.37197 0.37197 0.37197 0.37197 7.93809e-15 
+2023  0 0.60874 0.762079 0.762078 0.762078 0.762078 0.762078 1.15725e-09 
+2024  0 0.60874 0.762079 0.643148 0.646365 0.647326 0.655141 0.00390898 
+2025  0 0.60874 0.762079 0.575817 0.611507 0.621865 0.708266 0.0414404 
+2026  0 0.60874 0.762079 0.518298 0.623438 0.634472 0.762079 0.0798553 
+2027  0 0.60874 0.762079 0.496941 0.652051 0.651284 0.762079 0.0911426 
+2028  0 0.60874 0.762079 0.497075 0.673706 0.664372 0.762079 0.0888418 
+2029  0 0.60874 0.762079 0.497355 0.684954 0.669778 0.762079 0.0904241 
+2030  0 0.60874 0.762079 0.501432 0.684762 0.669961 0.762079 0.0914704 
+2031  0 0.60874 0.762079 0.497913 0.692028 0.670505 0.762079 0.0924429 
+2032  0 0.60874 0.762079 0.497426 0.681516 0.668777 0.762079 0.0909534 
+2033  0 0.60874 0.762079 0.500598 0.680282 0.667404 0.762079 0.0904603 
+2034  0 0.60874 0.762079 0.506169 0.684587 0.667139 0.762079 0.0906086 
+2035  0 0.60874 0.762079 0.505545 0.678828 0.667585 0.762079 0.08906 
+2036  0 0.60874 0.762079 0.510125 0.685854 0.668659 0.762079 0.0888657 
+
+Total_BiomassModel_16.0b
+Year B100 Babc Bofl LowCI_Biom Median_Biom Mean_Biom UpperCI_Biom Stdev_Biom 
+2022 1.00952e+06 661143 629123 631455 631455 631455 631455 9.54606e-09 
+2023 1.00952e+06 661143 629123 593268 609942 615027 656022 20433.9 
+2024 1.00952e+06 661143 629123 490258 558279 575519 716603 74003.1 
+2025 1.00952e+06 661143 629123 442115 564300 588393 809963 114901 
+2026 1.00952e+06 661143 629123 432505 586885 611874 869888 132622 
+2027 1.00952e+06 661143 629123 430248 611686 633722 889728 143786 
+2028 1.00952e+06 661143 629123 438330 623832 646104 921901 152500 
+2029 1.00952e+06 661143 629123 438615 630673 650398 927733 154138 
+2030 1.00952e+06 661143 629123 435728 632753 651894 926721 155107 
+2031 1.00952e+06 661143 629123 444772 625704 651629 940122 158133 
+2032 1.00952e+06 661143 629123 438674 624484 649683 956920 157974 
+2033 1.00952e+06 661143 629123 446805 624777 648387 945651 157978 
+2034 1.00952e+06 661143 629123 442192 627128 649083 928949 158045 
+2035 1.00952e+06 661143 629123 440875 627103 651418 934055 157640 
+2036 1.00952e+06 661143 629123 439847 630882 650657 934966 153669 
+Alternative 7 Alternative  Stock: Model_16.0b
+Catch Model_16.0b
+Year C0 Cabc Cofl LowCI_Catch Median_Catch Mean_Catch UpperCI_Catch Stdev_Catch 
+2022  0 90158.7 97763.1 66481 66481 66481 66481 1.58616e-09 
+2023  0 90158.7 97763.1 98571.8 98584.4 98588.2 98619.2 15.4356 
+2024  0 90158.7 97763.1 79212.6 80018.7 80272.1 82280 1004.74 
+2025  0 90158.7 97763.1 75600.9 83861.6 86618.4 108157 10212.7 
+2026  0 90158.7 97763.1 57668 79172.3 83930.7 122471 20881.5 
+2027  0 90158.7 97763.1 51470.1 82803.3 87523.1 133607 26130.2 
+2028  0 90158.7 97763.1 51018.8 87825.9 91697.9 141756 27558.5 
+2029  0 90158.7 97763.1 50613.4 90293.3 94395.6 140789 29256.9 
+2030  0 90158.7 97763.1 51883.1 91712.1 95338 145361 30192.7 
+2031  0 90158.7 97763.1 51636.1 93453.4 95521.2 144541 30096.8 
+2032  0 90158.7 97763.1 51485.1 91024.4 95265.6 147520 30391.1 
+2033  0 90158.7 97763.1 51805.2 90905.7 94992.9 148390 30777.8 
+2034  0 90158.7 97763.1 52825.7 91465.5 94715.8 148482 30630.9 
+2035  0 90158.7 97763.1 52408.5 90370.8 94592.2 149433 30502.3 
+2036  0 90158.7 97763.1 53787.7 91443 94977.4 145773 30522.4 
+
+Spawning_Biomass Model_16.0b
+Year SSB100 SSBabc SSBofl LowCI_SSB Median_SSB Mean_SSB UpperCI_SSB Stdev_SSB 
+2022 280456 112182 98159.5 137805 137805 137805 137805 1.74623e-09 
+2023 280456 112182 98159.5 118560 118591 118600 118675 37.2426 
+2024 280456 112182 98159.5 103622 104077 104213 105317 552.367 
+2025 280456 112182 98159.5 90972.3 95866.9 97372.2 109146 6069.48 
+2026 280456 112182 98159.5 79963.8 94429.2 97839.8 127372 15450.4 
+2027 280456 112182 98159.5 75803.6 97143 101308 139946 20367.8 
+2028 280456 112182 98159.5 75371.2 99854.9 103909 146226 21499.4 
+2029 280456 112182 98159.5 75276.1 101337 105638 147355 23208.1 
+2030 280456 112182 98159.5 75835 101312 106163 149132 24057.5 
+2031 280456 112182 98159.5 75307.4 102298 105952 148766 23596.6 
+2032 280456 112182 98159.5 75225.1 100834 105932 152516 24196.7 
+2033 280456 112182 98159.5 75687.9 100671 105887 153140 24615.9 
+2034 280456 112182 98159.5 76455.9 101238 105562 152407 24212.1 
+2035 280456 112182 98159.5 76377.6 100447 105418 152518 24582.4 
+2036 280456 112182 98159.5 77009.4 101415 105799 149873 24618.5 
+
+Fishing_mortalityModel_16.0b
+Year F0 Fabc Fofl LowCI_F Median_F Mean_F UpperCI_F Stdev_F 
+2022  0 0.60874 0.762079 0.37197 0.37197 0.37197 0.37197 7.93809e-15 
+2023  0 0.60874 0.762079 0.608739 0.608739 0.608739 0.608739 9.54514e-10 
+2024  0 0.60874 0.762079 0.559495 0.562111 0.562892 0.569247 0.00317845 
+2025  0 0.60874 0.762079 0.610428 0.645771 0.65535 0.741397 0.039018 
+2026  0 0.60874 0.762079 0.531226 0.635303 0.644657 0.762079 0.076782 
+2027  0 0.60874 0.762079 0.501486 0.654937 0.653947 0.762079 0.0898088 
+2028  0 0.60874 0.762079 0.498284 0.674486 0.665081 0.762079 0.0884822 
+2029  0 0.60874 0.762079 0.497486 0.685308 0.669965 0.762079 0.0903153 
+2030  0 0.60874 0.762079 0.501558 0.684848 0.670046 0.762079 0.0914284 
+2031  0 0.60874 0.762079 0.497977 0.692097 0.670554 0.762079 0.0924214 
+2032  0 0.60874 0.762079 0.497465 0.681547 0.668802 0.762079 0.0909424 
+2033  0 0.60874 0.762079 0.500613 0.680293 0.667415 0.762079 0.0904554 
+2034  0 0.60874 0.762079 0.506178 0.68459 0.667143 0.762079 0.0906066 
+2035  0 0.60874 0.762079 0.505546 0.678829 0.667587 0.762079 0.0890592 
+2036  0 0.60874 0.762079 0.510126 0.685856 0.668659 0.762079 0.0888653 
+
+Total_BiomassModel_16.0b
+Year B100 Babc Bofl LowCI_Biom Median_Biom Mean_Biom UpperCI_Biom Stdev_Biom 
+2022 1.00952e+06 661143 629123 631455 631455 631455 631455 9.54606e-09 
+2023 1.00952e+06 661143 629123 593268 609942 615027 656022 20433.9 
+2024 1.00952e+06 661143 629123 508194 576230 593470 734586 74016.6 
+2025 1.00952e+06 661143 629123 460238 582664 606706 828472 115026 
+2026 1.00952e+06 661143 629123 438611 592792 617801 876606 132618 
+2027 1.00952e+06 661143 629123 431937 613602 635406 891900 143828 
+2028 1.00952e+06 661143 629123 438739 624307 646523 922068 152532 
+2029 1.00952e+06 661143 629123 438744 630688 650488 927818 154154 
+2030 1.00952e+06 661143 629123 435723 632770 651928 926768 155114 
+2031 1.00952e+06 661143 629123 444790 625727 651652 940244 158136 
+2032 1.00952e+06 661143 629123 438681 624500 649696 956962 157976 
+2033 1.00952e+06 661143 629123 446818 624783 648393 945659 157979 
+2034 1.00952e+06 661143 629123 442194 627131 649086 928954 158045 
+2035 1.00952e+06 661143 629123 440876 627104 651419 934056 157640 
+2036 1.00952e+06 661143 629123 439847 630882 650658 934967 153669 
diff --git a/examples/atka/spm b/examples/atka/spm
new file mode 120000
index 0000000..8a64023
--- /dev/null
+++ b/examples/atka/spm
@@ -0,0 +1 @@
+../../src/spm
\ No newline at end of file
diff --git a/examples/atka/spm.log b/examples/atka/spm.log
new file mode 100644
index 0000000..e69de29
diff --git a/examples/atka/spm_detail.csv b/examples/atka/spm_detail.csv
new file mode 100644
index 0000000..85d3ab4
--- /dev/null
+++ b/examples/atka/spm_detail.csv
@@ -0,0 +1,105001 @@
+Stock,Alternative,Sim,Yr,SSB,Rec,Tot_biom,SPR_Implied,F,Ntot,Catch,ABC,OFL,AvgAge,AvgAgeTot,SexRatio,B100,B40,B35
+Model_16.0b,1,1,2022,137805,648.267,631455,0.517114,0.37197,551.321,66481,102578,123759,4.73364,2.81101,0.5,280456,112182,98159.5
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+Model_16.0b,1,1,2028,100816,796.136,687713,0.426248,0.543472,452.345,73465.5,73465.5,86580.5,3.60264,2.54982,0.5,280456,112182,98159.5
+Model_16.0b,1,1,2029,109559,1068.46,723857,0.405745,0.593681,508.969,86283.9,86283.9,101751,3.69605,2.36666,0.5,280456,112182,98159.5
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diff --git a/examples/atka/varssave.tmp b/examples/atka/varssave.tmp
new file mode 100755
index 0000000..e69de29
diff --git a/examples/yfs/Input_Log.rep b/examples/yfs/Input_Log.rep
new file mode 100644
index 0000000..a7808cc
--- /dev/null
+++ b/examples/yfs/Input_Log.rep
@@ -0,0 +1,152 @@
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+sel_Ftmp(i)
+ 0.000701093 0.00157433 0.00353139 0.00790201 0.0175864 0.0386771 0.0829259 0.168903 0.313545 0.506555 0.697632 0.838332 0.920976 0.963226 0.983297 0.992499 0.996648 0.996648 0.996648 0.996648 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 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 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 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 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 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 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 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 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 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 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 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 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
+sel_Mtmp(i)
+ 0.000663833 0.0014836 0.00331236 0.00737866 0.0163549 0.0358564 0.076796 0.156873 0.293871 0.482098 0.675547 0.823232 0.91241 0.958847 0.981173 0.991494 0.996179 0.996179 0.996179 0.996179 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 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 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 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 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 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 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 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 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 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 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 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 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
+n0_Ftmp(i)
+ 1179.8 1033.99 934.165 1186.63 1173.63 564.941 178.599 250.413 660.076 421.127 310.649 287.582 182.132 119.927 221.512 114.413 97.0637 58.0578 75.7241 362.037 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 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
+n0_Mtmp(i)
+ 1179.8 1033.94 934.086 1186.45 1173.45 565.078 178.989 252.484 673.115 433.036 318.252 291.14 182.187 118.758 217.846 112.506 96.4746 58.1467 75.3316 360.317 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 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
+nrec
+ 33
+Rtmp
+ 2467.15 1574.56 3038.13 2258.42 6528.73 1209.19 5401.76 1868.12 1435.07 1959.89 2685 2682.95 1339.35 1503.37 3331.54 1988.83 1679.79 1692.19 4175.32 1805.51 1499.92 1839.24 2606.42 1658.83 2284.2 2219.71 3523.92 1533.48 1844.78 2349.6 2112.73 2434.22 3272.3 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 0 0 0 0 0 0 0 0 0 0 0
+SSBtmp
+ 293.496 409.183 526.225 656.554 776.716 843.983 945.256 1024.84 1071.79 1058.17 1051.2 993.336 965.759 976.509 1057.25 1139.5 1174.45 1177.44 1176.38 1110.03 1073.52 1009.26 1000.98 987.701 983.504 981.707 990.525 1021.07 1036.84 1056.94 1061.63 1036.55 1000.41 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 0 0 0 0 0 0 0 0 0 0 0
diff --git a/examples/yfs/tacpar.dat b/examples/yfs/tacpar.dat
new file mode 100644
index 0000000..6631707
--- /dev/null
+++ b/examples/yfs/tacpar.dat
@@ -0,0 +1,10 @@
+7
+6
+ 2.60197 0.417 0.372 0.361 0.296 0.2733 0.125
+ -0.300856 -0.741664 -1.26797 -1.78614 -2.15198 -2.39595 -2.59939
+ -0.00703968 -0.956592 -1.48909 -2.09122 -2.26005 -2.31812 -2.45321
+ 0.372276 -1.35066 -1.76076 -2.22163 -2.31726 -2.28107 -2.34758
+ 0.505535 -1.19926 -1.68812 -2.39543 -2.40752 -2.5904 -2.58726
+ 0.368722 -1.59025 -1.79548 -2.67422 -2.61358 -2.41092 -2.70204
+ 0.308248 -1.78052 -2.23264 -2.85605 -3.39375 -3.05209 -2.94219
+ 0.180676 -1.7586 -1.80222 -3.09402 -2.2618 -3.43215 -3.06417
diff --git a/examples/yfs/yfs.dat b/examples/yfs/yfs.dat
new file mode 100644
index 0000000..3052e9f
--- /dev/null
+++ b/examples/yfs/yfs.dat
@@ -0,0 +1,47 @@
+#runname
+BSAI_YFINSS                                        
+#ssl_spp
+0 
+#Dorn_buffer
+0 
+#nfsh
+1 
+#nsex
+2 
+#avgF5yr
+0.0522 
+#F40_mult
+1.0
+#spr_abc
+0.4
+#spr_msy
+0.35
+#sp_mo                                   
+5 
+#nages
+20  
+#Frat
+1
+#M
+0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 
+0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 
+#pmat
+0.0001	0.0003	0.0008	0.0018	0.0042	0.011	0.0382	0.097	0.2134	0.4134	0.6459	0.825	0.9195	0.9675	0.9855	0.996	0.9985	1	1	1
+0.00026 0.0006  0.00159 0.0035  0.0084  0.012 0.0463  0.1039  0.2167  0.3967  0.6118  0.7899  0.899 0.955 0.981 0.992 0.997 1 1 1       
+#wtage_sp
+0.006	0.008	0.011	0.016	0.039	0.053	0.122	0.21	0.273	0.36	0.399	0.42	0.434	0.453	0.471	0.508	0.529	0.537	0.546	0.59
+#wtage_fsh
+0.006	0.008	0.032	0.05	0.066	0.074	0.112	0.186	0.338	0.372	0.412	0.408	0.455	0.456	0.485	0.508	0.515	0.532	0.555	0.59
+0.004	0.008	0.043	0.057	0.063	0.082	0.116	0.171	0.253	0.319	0.318	0.331	0.338	0.346	0.381	0.383	0.408	0.434	0.413	0.46
+#sel
+0.000701093	0.00157433	0.00353139	0.00790201	0.0175864	0.0386771	0.0829259	0.168903	0.313545	0.506555	0.697632	0.838332	0.920976	0.963226	0.983297	0.992499	0.996648	0.996648	0.996648	0.996648
+0.000663833	0.0014836	0.00331236	0.00737866	0.0163549	0.0358564	0.076796	0.156873	0.293871	0.482098	0.675547	0.823232	0.91241	0.958847	0.981173	0.991494	0.996179	0.996179	0.996179	0.996179
+#N
+1179.8	1033.99	934.165	1186.63	1173.63	564.941	178.599	250.413	660.076	421.127	310.649	287.582	182.132	119.927	221.512	114.413	97.0637	58.0578	75.7241	362.037
+1179.8	1033.94	934.086	1186.45	1173.45	565.078	178.989	252.484	673.115	433.036	318.252	291.14	182.187	118.758	217.846	112.506	96.4746	58.1467	75.3316	360.317
+#nyrs
+33                                                    
+#R
+2467.15	1574.561	3038.13	2258.42	6528.73	1209.186	5401.76	1868.121	1435.065	1959.887	2685	2682.95	1339.353	1503.374	3331.54	1988.833	1679.79	1692.189	4175.32	1805.508	1499.919	1839.244	2606.42	1658.825	2284.2	2219.71	3523.92	1533.483	1844.777	2349.6	2112.732	2434.22	3272.3
+#SSB                                                 
+293.496	409.183	526.225	656.554	776.716	843.983	945.256	1024.84	1071.79	1058.17	1051.2	993.336	965.759	976.509	1057.25	1139.5	1174.45	1177.44	1176.38	1110.03	1073.52	1009.26	1000.98	987.701	983.504	981.707	990.525	1021.07	1036.84	1056.94	1061.63	1036.55	1000.41