R Under development (unstable) (2025-04-18 r88159 ucrt) -- "Unsuffered Consequences"
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> if (!interactive()) options(warn=2, error = function() { sink(stderr()) ; traceback(3) ; q(status = 1) })
> library(magrittr)
> library(unittest)
> 
> library(gadget3)
> 
> 
> # Helper to generate ld from table string and attributes
> generate_ld <- function (tbl, all_stocks = list(), all_fleets = list(), all_predators = list(), model_history = "", use_preview = FALSE, ...) {
+     if (is.character(tbl)) tbl <- read.table(text = tbl, header = TRUE, stringsAsFactors = TRUE)
+     if (is.null(tbl$number)) tbl$number <- as.numeric(seq_len(nrow(tbl)))
+     all_stocks <- lapply(all_stocks, function (x) g3_stock(x, 1))
+     if (use_preview) {
+         # Use new public preview function
+         out <- list( obs_array = list(
+             num = g3_distribution_preview(structure(tbl, ...), stocks = all_stocks, fleets = all_fleets, predators = all_predators) ))
+     } else {
+         # Fall back to old behaviour
+         out <- gadget3:::g3l_likelihood_data('ut', structure(tbl, ...), all_stocks = all_stocks, all_fleets = all_fleets, all_predators = all_predators, model_history = model_history)
+     }
+ 
+     # NB: A failed merge would result in repeated instances
+     ok(ut_cmp_equal(
+         sort(as.numeric(out$obs_array$num[out$obs_array$num != 0])),
+         sort(as.numeric(tbl$number)),
+         deparse_frame = -2), "number array has all of source data")
+     return(out)
+ }
> 
> # Generate example of ld being stock_iterate()d or stock_intersect()ed
> generate_code <- function(ld, repl_fn, ...) {
+     model_fn <- g3_to_r(list(gadget3:::g3_step(gadget3:::call_to_formula(
+         substitute(
+             extractme(repl_fn_sym(st, stock_ss(st__num, vec = single))),
+             list(repl_fn_sym = as.symbol(repl_fn)) ),
+         list(
+             st = ld$obsstock,
+             st__num = ld$number,
+             ... )))))
+     gadget3:::f_find(body(model_fn), quote(extractme))[[1]][[2]]
+ }
> 
> # Dig minlen out of modelstock
> ld_minlen <- function (ld) {
+     x <- g3_stock_def(ld$modelstock, 'minlen')
+     # Bodge array back to (named) vector
+     as.matrix(x)[,1]
+ }
> 
> # Dig definitions out of modelstock
> ld_upperlen <- function (ld) g3_stock_def(ld$modelstock, 'upperlen')
> ld_dl <- function (ld) g3_stock_def(ld$modelstock, 'dl')
> ld_plusdl <- function (ld) g3_stock_def(ld$modelstock, 'plusdl')
> ld_minages <- function (ld) g3_stock_def(ld$modelstock, 'minages')
> 
> # Compare array by turning it back into a table first
> cmp_array <- function (ar, table_text) {
+     tbl <- read.table(
+         header = TRUE,
+         stringsAsFactors = FALSE,
+         colClasses = c(rep("character", length(dim(ar))), "numeric"),
+         text = table_text)
+     ut_cmp_identical(as.data.frame.table(ar, stringsAsFactors = FALSE), tbl, deparse_frame = -2)
+ }
> 
> 
> ok_group('g3l_likelihood_data:unknown', {
+     ld <- generate_ld(
+         data.frame(
+             year = 1990:1992,
+             number = 1:3,
+             camel = 10:12,
+             stringsAsFactors = FALSE),
+         end = NULL)
+     ok(ut_cmp_equal(ld$obs_array, list(
+         num = array(1:3, dim = c(length = 1L, time = 3L), dimnames = list(length = "0:Inf", time = c("1990", "1991", "1992"))),
+         camel = array(10:12, dim = c(length = 1L, time = 3L), dimnames = list(length = "0:Inf", time = c("1990", "1991", "1992"))) )), "Will create arrays from any unknown columns")
+ })
# g3l_likelihood_data:unknown
ok - number array has all of source data
ok - Will create arrays from any unknown columns
> 
> ok_group('g3l_likelihood_data:time', {
+     ok(ut_cmp_error({
+         ld <- generate_ld(
+             data.frame(
+                 number = 1:3,
+                 stringsAsFactors = FALSE),
+             end = NULL)
+     }, "year column"), "Noticed lack of year column")
+ 
+     ld <- generate_ld("
+         year number
+         1998 1
+         2002 2
+         2001 3
+     ")
+     ok(cmp_array(ld$obs_array$num, "
+         length time Freq
+           0:Inf 1998    1
+           0:Inf 2001    3
+           0:Inf 2002    2
+         "), "Year gap, wonky year order preserved")
+ 
+     ld <- generate_ld("
+         year step number
+         1998    1      1
+         1998    2      2
+         1999    1      3
+         2000    1      4
+         2000    2      5
+     ")
+     ok(cmp_array(ld$obs_array$num, "
+         length    time Freq
+           0:Inf 1998-01    1
+           0:Inf 1998-02    2
+           0:Inf 1999-01    3
+           0:Inf 2000-01    4
+           0:Inf 2000-02    5
+         "), "Year gap, wonky year order preserved")
+ 
+     ld <- generate_ld("
+         time number
+         1998 1
+         2002 2
+         2001 3
+     ")
+     ok(cmp_array(ld$obs_array$num, "
+         length time Freq
+           0:Inf 1998    1
+           0:Inf 2001    3
+           0:Inf 2002    2
+         "), "Time column used when year not present (i.e. can parse our own output)")
+ 
+     ld <- generate_ld("
+         time number
+         1998-01 2
+         1998-02 4
+         1999-01 3
+         1999-02 9
+     ")
+     ok(cmp_array(ld$obs_array$num, "
+         length time Freq
+           0:Inf 1998-01    2
+           0:Inf 1998-02    4
+           0:Inf 1999-01    3
+           0:Inf 1999-02    9
+         "), "Year-step separated in time column")
+ })
# g3l_likelihood_data:time
ok - Noticed lack of year column
ok - number array has all of source data
ok - Year gap, wonky year order preserved
ok - number array has all of source data
ok - Year gap, wonky year order preserved
ok - number array has all of source data
ok - Time column used when year not present (i.e. can parse our own output)
ok - number array has all of source data
ok - Year-step separated in time column
> 
> ok_group('g3l_likelihood_data:length', {
+     ld <- generate_ld("
+         year number
+         1999      1
+         2000      2
+         2001      3
+     ")
+     ok(cmp_array(ld$obs_array$num, "
+         length time Freq
+           0:Inf 1999    1
+           0:Inf 2000    2
+           0:Inf 2001    3
+         "), "Default single length dimension if none supplied")
+     ok(ut_cmp_identical(ld$modelstock$dimnames, list(
+         length = "0:Inf")), "modelstock got default length dimension if none supplied")
+ 
+     ld <- generate_ld("
+         year length number
+         1999      1      1
+         2000      1      2
+         2001      1      3
+         1999      5      4
+         2000      5      5
+         2001      5      6
+         1999     10      7
+         2001     10      9
+         2000     30     11
+         2001     30     12
+     ")
+     ok(cmp_array(ld$obs_array$num, "
+         length time Freq
+            1:5 1999    1
+           5:10 1999    4
+          10:30 1999    7
+         30:Inf 1999    0
+            1:5 2000    2
+           5:10 2000    5
+          10:30 2000    0
+         30:Inf 2000    11
+            1:5 2001    3
+           5:10 2001    6
+          10:30 2001    9
+         30:Inf 2001    12
+         "), "Lengths read from data, missing 2000/10 1999/30 filled in with 0")
+     ok(ut_cmp_identical(
+         ld_minlen(ld),
+         c("1:5" = 1, "5:10" = 5, "10:30" = 10, "30:Inf" = 30)), "minlen set via. data")
+     ok(ut_cmp_identical(ld_upperlen(ld), Inf), "If we guess from data, open-ended is only sensible option")
+ 
+     ok(ut_cmp_error(generate_ld("
+         year length number
+         1999      a      1999.1
+         2000      a      2000.1
+         2001      a      2001.1
+         1999      b      1999.2
+         2000      b      2000.2
+         2001      b      2001.2
+         1999      c      1999.3
+         2001      c      2001.3
+         ",
+         length = list(
+             a = structure(quote(seq(10, 20)), min = 10, max = 20),
+             b = structure(quote(seq(20, 40)), min = 20, max = 40),
+             c = structure(quote(seq(80, 100)), min = 80, max = 100))), "Gaps in length"), "Non-contiguous length groups cause an error")
+ 
+     ld <- generate_ld("
+         year length number
+         1999      a      1999.1
+         2000      a      2000.1
+         2001      a      2001.1
+         1999      b      1999.2
+         2000      b      2000.2
+         2001      b      2001.2
+         1999      c      1999.3
+         2001      c      2001.3
+         ",
+         length = list(
+             a = structure(quote(seq(10, 20)), min = 10, max = 20),
+             b = structure(quote(seq(20, 40)), min = 20, max = 40),
+             c = structure(quote(seq(40, 80)), min = 40, max = 80)))
+     ok(cmp_array(ld$obs_array$num, "
+         length time   Freq
+          10:20 1999 1999.1
+          20:40 1999 1999.2
+          40:80 1999 1999.3
+          10:20 2000 2000.1
+          20:40 2000 2000.2
+          40:80 2000    0.0
+          10:20 2001 2001.1
+          20:40 2001 2001.2
+          40:80 2001 2001.3
+         "), "Use lengths, removed names from attribute, gaps filled in")
+     ok(ut_cmp_identical(
+         ld_minlen(ld),
+         c("10:20" = 10, "20:40" = 20, "40:80" = 40)), "minlen set by attribute")
+     ok(ut_cmp_identical(ld_upperlen(ld), 80), "Upperlen set by attribute")
+     ok(ut_cmp_identical(ld_dl(ld), c(10, 20, 40)), "dl difference up to upper bound")
+     ok(ut_cmp_identical(ld_plusdl(ld), 10), "plusdl is the mode")
+ 
+     ld <- generate_ld("
+         year length number
+         1999      a      1999.1
+         2000      a      2000.1
+         2001      a      2001.1
+         1999      b      1999.2
+         2000      b      2000.2
+         2001      b      2001.2
+         1999      c      1999.3
+         2001      c      2001.3
+         ",
+         length = list(
+             a = structure(quote(seq(10, 20)), min = 10, max = 20),
+             b = structure(quote(seq(20, 40)), min = 20, max = 40),
+             c = structure(quote(seq(40, 80)), min = 40, max = 80) ),
+         use_preview = TRUE )
+     ok(cmp_array(ld$obs_array$num, "
+         length time   Freq
+          10:20 1999 1999.1
+          20:40 1999 1999.2
+          40:80 1999 1999.3
+          10:20 2000 2000.1
+          20:40 2000 2000.2
+          40:80 2000     NA
+          10:20 2001 2001.1
+          20:40 2001 2001.2
+          40:80 2001 2001.3
+         "), "Use lengths, removed names from attribute, gaps filled in (with new g3_distribution_preview)")
+ 
+     ld <- generate_ld("
+         year length number
+         1999      a      1999.1
+         2000      a      2000.1
+         2001      a      2001.1
+         1999      b      1999.2
+         2000      b      2000.2
+         2001      b      2001.2
+         1999      c      1999.3
+         2001      c      2001.3
+         ",
+         length = list(
+             a = structure(quote(seq(10, 20)), min = 10, max = 20),
+             b = structure(quote(seq(20, 40)), min = 20, max = 40),
+             c = structure(quote(seq(40, 80)), min = 40, max = 80, max_open_ended = TRUE)))
+     ok(cmp_array(ld$obs_array$num, "
+         length time   Freq
+          10:20 1999 1999.1
+          20:40 1999 1999.2
+         40:Inf 1999 1999.3
+          10:20 2000 2000.1
+          20:40 2000 2000.2
+         40:Inf 2000    0.0
+          10:20 2001 2001.1
+          20:40 2001 2001.2
+         40:Inf 2001 2001.3
+         "), "Use lengths, removed names from attribute, gaps filled in")
+     ok(ut_cmp_identical(ld_upperlen(ld), Inf), "upperlen now infinite")
+     ok(ut_cmp_identical(ld_dl(ld), c(10, 20, 10)), "dl assumes final group is as big as the mode")
+     ok(ut_cmp_identical(ld_plusdl(ld), 10), "plusdl is the mode")
+     ok(ut_cmp_identical(
+         ld_minlen(ld),
+         c("10:20" = 10, "20:40" = 20, "40:Inf" = 40)), "minlen doesn't include the plusgroup separately")
+ 
+     ld <- generate_ld("
+         year length number
+         1999      a      1999.1
+         2000      a      2000.1
+         2001      a      2001.1
+         1999      b      1999.2
+         2000      b      2000.2
+         2001      b      2001.2
+         1999      c      1999.3
+         2001      c      2001.3
+         ",
+         length = list(
+             "a" = structure(quote(seq(10, 20)), min = 10, max = 20, min_open_ended = TRUE),
+             "b" = structure(quote(seq(20, 40)), min = 20, max = 40),
+             "c" = structure(quote(seq(40, 80)), min = 40, max = 80)))
+     ok(ut_cmp_identical(ld_upperlen(ld), 80), "upperlen set by attribute")
+     ok(ut_cmp_identical(
+         ld_minlen(ld),
+         c("0:20" = 0, "20:40" = 20, "40:80" = 40)), "minlen down to zero due to min_open_ended")
+ })
# g3l_likelihood_data:length
ok - number array has all of source data
ok - Default single length dimension if none supplied
ok - modelstock got default length dimension if none supplied
ok - number array has all of source data
ok - Lengths read from data, missing 2000/10 1999/30 filled in with 0
ok - minlen set via. data
ok - If we guess from data, open-ended is only sensible option
ok - Non-contiguous length groups cause an error
ok - number array has all of source data
ok - Use lengths, removed names from attribute, gaps filled in
ok - minlen set by attribute
ok - Upperlen set by attribute
ok - dl difference up to upper bound
ok - plusdl is the mode
ok - number array has all of source data
ok - Use lengths, removed names from attribute, gaps filled in (with new g3_distribution_preview)
ok - number array has all of source data
ok - Use lengths, removed names from attribute, gaps filled in
ok - upperlen now infinite
ok - dl assumes final group is as big as the mode
ok - plusdl is the mode
ok - minlen doesn't include the plusgroup separately
ok - number array has all of source data
ok - upperlen set by attribute
ok - minlen down to zero due to min_open_ended
> 
> 
> ok_group('g3l_likelihood_data:length_factor', {
+     ld <- generate_ld(data.frame(
+         year = 1990,
+         length = cut(c(14, 28, 33, 33), seq(0, 50, by = 10), right = FALSE),
+         stringsAsFactors = TRUE))
+     ok(ut_cmp_identical(
+         ld_minlen(ld),
+         c("0:10" = 0, "10:20" = 10, "20:30" = 20, "30:40" = 30, "40:50" = 40)), "ld_minlen: Not open ended")
+     ok(ut_cmp_identical(ld_upperlen(ld), 50), "ld_upperlen: Not open ended")
+ 
+     ld <- generate_ld(data.frame(
+         year = 1990,
+         length = cut(c(14, 28, 33, 33), c(seq(0, 50, by = 10), Inf), right = FALSE),
+         stringsAsFactors = TRUE))
+     ok(ut_cmp_identical(
+         ld_minlen(ld),
+         c("0:10" = 0, "10:20" = 10, "20:30" = 20, "30:40" = 30, "40:50" = 40, "50:Inf" = 50)), "ld_minlen: Open ended")
+     ok(ut_cmp_identical(ld_upperlen(ld), Inf), "ld_upperlen: Open ended")
+ 
+     ok(ut_cmp_error({
+         ld <- generate_ld(data.frame(
+             year = 1990,
+             length = as.factor(c("a", "b", "b", "c")),
+             stringsAsFactors = TRUE))
+     }, "length levels.*a, b, c"), "Unrecognised column format, included levels in error")
+ 
+     ok(ut_cmp_error({
+         ld <- generate_ld(data.frame(
+             year = 1990,
+             length = cut(c(14, 28, 33, 33), c(seq(0, 50, by = 10), Inf), right = TRUE),
+             stringsAsFactors = TRUE))
+     }, "inclusive-lower.*\\(0,10\\], \\(10,20\\], \\(20,30\\], \\(30,40\\], \\(40,50\\], \\(50,Inf\\]"), "Unrecognised column format, included levels in error")  # ))))
+ 
+     ok(ut_cmp_error({
+         ld <- generate_ld(data.frame(
+             year = 1990,
+             # ((((
+             length = factor(c("[0,10)", "[20, 40)"), levels = c("[0,10)", "[20, 40)")),
+             stringsAsFactors = TRUE))
+     # ((
+     }, "Gaps in length groups are not supported: \\[0,10\\), \\[20, 40\\)"), "Complained about gaps in length groups")
+ })
# g3l_likelihood_data:length_factor
ok - number array has all of source data
ok - ld_minlen: Not open ended
ok - ld_upperlen: Not open ended
ok - number array has all of source data
ok - ld_minlen: Open ended
ok - ld_upperlen: Open ended
ok - Unrecognised column format, included levels in error
ok - Unrecognised column format, included levels in error
ok - Complained about gaps in length groups
> 
> 
> ok_group('g3l_likelihood_data:age_char', {
+     ld <- generate_ld(expand.grid(
+         year = 1990,
+         length = as.character(cut(seq(3, 47, by=5), seq(0, 50, by = 5), right = FALSE)),
+         age = 1:2,
+         stringsAsFactors = FALSE))
+     ok(cmp_array(ld$obs_array$num, "
+         length  age time   Freq
+            0:5 age1 1990    1
+           5:10 age1 1990    2
+          10:15 age1 1990    3
+          15:20 age1 1990    4
+          20:25 age1 1990    5
+          25:30 age1 1990    6
+          30:35 age1 1990    7
+          35:40 age1 1990    8
+          40:45 age1 1990    9
+            0:5 age2 1990   10
+           5:10 age2 1990   11
+          10:15 age2 1990   12
+          15:20 age2 1990   13
+          20:25 age2 1990   14
+          25:30 age2 1990   15
+          30:35 age2 1990   16
+          35:40 age2 1990   17
+          40:45 age2 1990   18
+         "), "Converted back to factor, preserving ordering of entries")
+ 
+     ld <- generate_ld(expand.grid(
+         year = 1990,
+         length = as.character(cut(seq(3, 47, by=5), seq(0, 50, by = 5), right = FALSE)),
+         age = c('[1,3]', '[4,9]'),
+         stringsAsFactors = FALSE))
+     ok(cmp_array(ld$obs_array$num, "
+         length  age time   Freq
+            0:5 1:3 1990    1
+           5:10 1:3 1990    2
+          10:15 1:3 1990    3
+          15:20 1:3 1990    4
+          20:25 1:3 1990    5
+          25:30 1:3 1990    6
+          30:35 1:3 1990    7
+          35:40 1:3 1990    8
+          40:45 1:3 1990    9
+            0:5 4:9 1990   10
+           5:10 4:9 1990   11
+          10:15 4:9 1990   12
+          15:20 4:9 1990   13
+          20:25 4:9 1990   14
+          25:30 4:9 1990   15
+          30:35 4:9 1990   16
+          35:40 4:9 1990   17
+          40:45 4:9 1990   18
+         "), "Can use intervals in strings, converted to groups")
+ 
+     ld <- generate_ld(data.frame(
+         year = 1990,
+         length = c(
+             as.character(cut(seq(23, 39, by=5), seq(0, 50, by = 5), right = FALSE)),
+             as.character(cut(seq(3, 47, by=5), seq(0, 50, by = 5), right = FALSE)),
+             NULL),
+         age = c(
+             rep(1, 4),
+             rep(2, 9),
+             NULL),
+         stringsAsFactors = FALSE))
+     ok(cmp_array(ld$obs_array$num, "
+         length  age time   Freq
+            0:5 age1 1990    0
+           5:10 age1 1990    0
+          10:15 age1 1990    0
+          15:20 age1 1990    0
+          20:25 age1 1990    1
+          25:30 age1 1990    2
+          30:35 age1 1990    3
+          35:40 age1 1990    4
+          40:45 age1 1990    0
+            0:5 age2 1990    5
+           5:10 age2 1990    6
+          10:15 age2 1990    7
+          15:20 age2 1990    8
+          20:25 age2 1990    9
+          25:30 age2 1990   10
+          30:35 age2 1990   11
+          35:40 age2 1990   12
+          40:45 age2 1990   13
+         "), "Partial ranges padded out with zeros")
+ 
+     ld <- generate_ld(data.frame(
+         year = 1990,
+         length = cut(c(4, 14, 28, 33, 33, 44), c(seq(0, 50, by = 10), Inf), right = FALSE),
+         stringsAsFactors = TRUE))
+     ld_loopback <- generate_ld(as.data.frame.table(ld$obs_array$num, responseName = 'number'))
+     ok(ut_cmp_equal(ld$obs_array$num, ld_loopback$obs_array$num), "Can parse our own output")
+ })
# g3l_likelihood_data:age_char
ok - number array has all of source data
ok - Converted back to factor, preserving ordering of entries
ok - number array has all of source data
ok - Can use intervals in strings, converted to groups
ok - number array has all of source data
ok - Partial ranges padded out with zeros
ok - number array has all of source data
ok - number array has all of source data
ok - Can parse our own output
> 
> ok_group('g3l_likelihood_data:age', {
+     ld <- generate_ld("
+         age year number
+           3 1999      1999.3
+           4 1999      1999.4
+           6 1999      1999.6
+           3 2000      2000.3
+           6 2000      2000.6
+           4 2001      2001.4
+           6 2001      2001.6
+         ")
+     ok(cmp_array(ld$obs_array$num, "
+         length  age time   Freq
+           0:Inf age3 1999 1999.3
+           0:Inf age4 1999 1999.4
+           0:Inf age5 1999    0.0
+           0:Inf age6 1999 1999.6
+           0:Inf age3 2000 2000.3
+           0:Inf age4 2000    0.0
+           0:Inf age5 2000    0.0
+           0:Inf age6 2000 2000.6
+           0:Inf age3 2001    0.0
+           0:Inf age4 2001 2001.4
+           0:Inf age5 2001    0.0
+           0:Inf age6 2001 2001.6
+         "), "Worked out age dimensions from data, filled in missing values, including entirely absent ones")
+ 
+     ld <- generate_ld("
+         age year number
+           x 1999      1999.1
+           y 1999      1999.2
+           x 2000      2000.1
+           x 2001      2001.1
+           y 2001      2001.2
+         ",
+         age = list(
+             x = structure(quote(seq(1, 3)), min = 1, max = 3),
+             y = structure(quote(seq(4, 6)), min = 4, max = 6),
+             z = structure(quote(seq(7, 10)), min = 7, max = 10)))
+     ok(cmp_array(ld$obs_array$num, "
+         length  age time   Freq
+           0:Inf 1:3 1999 1999.1
+           0:Inf 4:6 1999 1999.2
+           0:Inf 7:10 1999   0.0
+           0:Inf 1:3 2000 2000.1
+           0:Inf 4:6 2000    0.0
+           0:Inf 7:10 2000   0.0
+           0:Inf 1:3 2001 2001.1
+           0:Inf 4:6 2001 2001.2
+           0:Inf 7:10 2001   0.0
+         "), "Worked out age dimensions from attributes, filled in missing values")
+     ok(ut_cmp_identical(
+         ld_minages(ld),
+         gadget3:::force_vector("1:3" = 1L, "4:6" = 4L, "7:10" = 7L)), "agegroups using minages from attribute")
+ })
# g3l_likelihood_data:age
ok - number array has all of source data
ok - Worked out age dimensions from data, filled in missing values, including entirely absent ones
ok - number array has all of source data
ok - Worked out age dimensions from attributes, filled in missing values
ok - agegroups using minages from attribute
> 
> ok_group('g3l_likelihood_data:agegroup') ###########
# g3l_likelihood_data:agegroup
> ld <- generate_ld(expand.grid(
+      year = 2000:2005,
+      length = c(1,5,10),
+      age = c("[1,2)", "[3,3)")  )) # ((
ok - number array has all of source data
> ok(gadget3:::ut_cmp_code(generate_code(ld, 'stock_intersect', age = 1, cur_year = 1999, cur_step = 1), quote({
+     ut_obs__time_idx <- intlookup_getdefault(ut_obs__times, (cur_year *
+         100L + cur_step * 0L), -1L)
+     if (ut_obs__time_idx >= (1L)) {
+         for (ut_obs__agegroup_idx in seq_along(ut_obs__minages)) {
+             `_age` <- ut_obs__minages[[ut_obs__agegroup_idx]]
+             for (ut_obs__length_idx in seq_along(ut_obs__minlen)) {
+                 length <- ut_obs__midlen[[ut_obs__length_idx]]
+                 ut_obs__num[ut_obs__length_idx, ut_obs__agegroup_idx,
+                   ut_obs__time_idx]
+             }
+         }
+     }
+ }), optimize = TRUE), "stock_intersect: Renamed all vars, including ut_obs__agegroup")
ok - stock_intersect: Renamed all vars, including ut_obs__agegroup
> 
> ok(ut_cmp_equal(
+     g3_eval(attr(ld$obsstock$env$ut_obs__agegroup, "g3_global_init_val")),
+     structure(
+         list(1L, 2L, 2L),
+         key_var = "ut_obs__agegroup_keys",
+         value_var = "ut_obs__agegroup_values" )), "ut_obs__agegroup: Sub-parts also renamed")
ok - ut_obs__agegroup: Sub-parts also renamed
> 
> ########### g3l_likelihood_data:agegroup
> 
> ok_group('g3l_likelihood_data:age_factor', {
+     df <- data.frame(
+         year = 1990,
+         age = c(3,3,4,5),
+         number = 1,
+         stringsAsFactors = TRUE)
+     df$age <- cut(df$age, seq(3, 10, by = 1), right = FALSE)
+     df <- aggregate(number ~ year + age, df, sum)
+     ld <- generate_ld(df)
+     ok(cmp_array(ld$obs_array$num, "
+         length age time Freq
+          0:Inf 3:3 1990    2
+          0:Inf 4:4 1990    1
+          0:Inf 5:5 1990    1
+          0:Inf 6:6 1990    0
+          0:Inf 7:7 1990    0
+          0:Inf 8:8 1990    0
+          0:Inf 9:9 1990    0
+      "), "ld$obs_array$num: included all single ages")
+ 
+     ld <- generate_ld(data.frame(
+         year = 1990,
+         age = as.factor(c(3,4,5,8)),
+         stringsAsFactors = TRUE))
+     ok(cmp_array(ld$obs_array$num, "
+         length age time Freq
+         0:Inf 3:3 1990    1
+         0:Inf 4:4 1990    2
+         0:Inf 5:7 1990    3
+         0:Inf 8:8 1990    4
+      "), "ld$obs_array$num: can also use integer strings as factors")
+ 
+     df <- data.frame(
+         year = 1990,
+         age = c(3,3,4,5),
+         number = 1,
+         stringsAsFactors = TRUE)
+     df$age <- cut(df$age, seq(2, 10, by = 4), right = FALSE)
+     df <- aggregate(number ~ year + age, df, sum)
+     ld <- generate_ld(df)
+     ok(cmp_array(ld$obs_array$num, "
+         length age time Freq
+          0:Inf 2:5 1990    4
+          0:Inf 6:9 1990    0
+      "), "ld$obs_array$num: Everything grouped into first group, second compared to zero")
+ })
# g3l_likelihood_data:age_factor
ok - number array has all of source data
ok - ld$obs_array$num: included all single ages
ok - number array has all of source data
ok - ld$obs_array$num: can also use integer strings as factors
ok - number array has all of source data
ok - ld$obs_array$num: Everything grouped into first group, second compared to zero
> 
> 
> ok_group('g3l_likelihood_data:area', {
+     # Pull the area lookup definition back out
+     area_lookup <- function (ld) {
+         list(
+             keys = environment(g3_stock_def(ld$modelstock, 'areagroup_lookup'))$keys,
+             values = environment(g3_stock_def(ld$modelstock, 'areagroup_lookup'))$values)
+     }
+ 
+     ok(ut_cmp_error({
+         ld <- generate_ld("
+             area year number
+               a 1999      1999.1
+               b 1999      1999.2
+               c 1999      1999.3
+             ")
+     }, "Areas in data"), "If char areas are provided without aggregation, we can't do anything")
+ 
+     ok(ut_cmp_error({
+         ld <- generate_ld("
+             area year number
+               a 1999      1999.1
+               b 1999      1999.2
+               c 1999      1999.3
+             ", area = list(a = 1, b = 2, c = 3))
+     }, "Areas in data"), "If char areas are provided without aggregation, we can't do anything. MFDB aggregates don't count")
+ 
+     ld <- generate_ld("
+         area year number
+           1 1999      1999.1
+           2 1999      1999.2
+           3 1999      1999.3
+           2 2000      2000.2
+           3 2000      2000.3
+           1 2001      2001.1
+           2 2001      2001.2
+         ")
+     ok(cmp_array(ld$obs_array$num, "
+         length time area   Freq
+           0:Inf 1999    1 1999.1
+           0:Inf 2000    1    0.0
+           0:Inf 2001    1 2001.1
+           0:Inf 1999    2 1999.2
+           0:Inf 2000    2 2000.2
+           0:Inf 2001    2 2001.2
+           0:Inf 1999    3 1999.3
+           0:Inf 2000    3 2000.3
+           0:Inf 2001    3    0.0
+         "), "Worked out area dimensions from data, filled in missing values")
+ 
+     ld <- gadget3:::g3l_likelihood_data('ut', read.table(header = TRUE, stringsAsFactors = TRUE, text = "
+         area year number
+           a 1999      1999.1
+           b 1999      1999.2
+           c 1999      1999.3
+           b 2000      2000.2
+           c 2000      2000.3
+           a 2001      2001.1
+           b 2001      2001.2
+         "), area_group = list(a = 3, b = 4, c = c(1:2)))
+     ok(cmp_array(ld$obs_array$num, "
+         length time area   Freq
+           0:Inf 1999    a 1999.1
+           0:Inf 2000    a    0.0
+           0:Inf 2001    a 2001.1
+           0:Inf 1999    b 1999.2
+           0:Inf 2000    b 2000.2
+           0:Inf 2001    b 2001.2
+           0:Inf 1999    c 1999.3
+           0:Inf 2000    c 2000.3
+           0:Inf 2001    c    0.0
+         "), "Worked out area dimensions from data, filled in missing values")
+     ok(ut_cmp_identical(area_lookup(ld), list(keys = c(3L,4L,1L,2L), values = c(1L,2L,3L,3L))), "Areas 1 & 2 both mapped to index 3 (i.e. c)")
+ })
# g3l_likelihood_data:area
ok - If char areas are provided without aggregation, we can't do anything
ok - If char areas are provided without aggregation, we can't do anything. MFDB aggregates don't count
ok - number array has all of source data
ok - Worked out area dimensions from data, filled in missing values
ok - Worked out area dimensions from data, filled in missing values
ok - Areas 1 & 2 both mapped to index 3 (i.e. c)
> 
> ok_group('g3l_likelihood_data:tag', {
+     ld <- gadget3:::g3l_likelihood_data('ut', read.table(header = TRUE, stringsAsFactors = TRUE, text = "
+         tag year number
+           a 1999      1999.1
+           b 1999      1999.2
+           c 1999      1999.3
+           b 2000      2000.2
+           c 2000      2000.3
+           a 2001      2001.1
+           b 2001      2001.2
+         "))
+     ok(cmp_array(ld$obs_array$num, "
+         length    tag time   Freq
+         0:Inf        a 1999 1999.1
+         0:Inf        b 1999 1999.2
+         0:Inf        c 1999 1999.3
+         0:Inf        a 2000    0.0
+         0:Inf        b 2000 2000.2
+         0:Inf        c 2000 2000.3
+         0:Inf        a 2001 2001.1
+         0:Inf        b 2001 2001.2
+         0:Inf        c 2001    0.0
+         "), "Worked out tag dimensions from data")
+     ok(ut_cmp_identical(
+         g3_stock_def(ld$modelstock, 'tag_ids'),
+         gadget3:::force_vector(a = 1L, b = 2L, c = 3L)), "stock__tag_ids: Worked out from factor")
+ })
# g3l_likelihood_data:tag
ok - Worked out tag dimensions from data
ok - stock__tag_ids: Worked out from factor
> 
> ok_group('g3l_likelihood_data:stock', {
+     ld <- generate_ld("
+         age year number
+           3 1999      1999.3
+           4 1999      1999.4
+           6 1999      1999.6
+           3 2000      2000.3
+           6 2000      2000.6
+           4 2001      2001.4
+           6 2001      2001.6
+         ")
+     ok(is.null(ld$maps$stock), "No stock column, so no stock map")
+ 
+     ok(ut_cmp_error(generate_ld("
+         age year stock stock_re number
+           3 1999    a  a$       1999.3
+         "), "stock.*stock_re"), "Can't have both stock & stock_re")
+ 
+     ld <- generate_ld("
+         age year stock number
+           3 1999    a  1999.3
+           4 1999    b  1999.4
+           6 1999    a  1999.6
+           3 2000    a  2000.3
+           6 2000    b  2000.6
+           4 2001    b  2001.4
+           6 2001    b  2001.6
+         ", all_stocks = c('a', 'b'))
+     ok(ut_cmp_identical(dimnames(ld$obs_array$num)[['stock']], c("a", "b")), "Array has stocks a & b")
+     ok(ut_cmp_identical(ld$maps$stock, c(a = 'a', b = 'b')), "stock_map is 1:1 mapping")
+ 
+     ok(ut_cmp_error(generate_ld("
+         age year stock number
+           3 1999    a  1999.3
+           4 1999    b  1999.4
+           5 1999    kapow  1999.6
+           6 1999    zot  1999.6
+         ", all_stocks = c('a', 'b')), "kapow, zot"), "Unknown stock names in data an error")
+ 
+     # Generate a list of stocks "stock_(imm,mat)_(f,m)"
+     stock_names <- paste(
+         'stock',
+         rep(c('imm', 'mat'), each = 2),
+         c('f', 'm'),
+         sep = "_")
+     ld <- generate_ld("
+         age year stock_re number
+           3 1999    _f$  1999.3
+           4 1999    ^stock_mat  1999.4
+           6 1999    ^stock_imm  1999.6
+           3 2000    ^stock_mat  2000.3
+           6 2000    ^stock_imm  2000.6
+           4 2001    ^stock_imm  2001.4
+           6 2001    ^stock_mat  2001.6
+         ", all_stocks = stock_names, model_history = "late")
+     ok(ut_cmp_identical(
+         dimnames(ld$obs_array$num)[['stock_re']],
+         c("_f$", "^stock_mat", "^stock_imm")), "Array names are regexes")
+     ok(ut_cmp_identical(
+         ld$maps$stock,
+         c(
+             stock_imm_f = '_f$',
+             stock_imm_m = '^stock_imm',
+             stock_mat_f = '_f$',
+             stock_mat_m = '^stock_mat')), "Stock map used first regexes first")
+ 
+     # Generated intersect code works
+     model_fn <- g3_to_r(list(
+         g3a_time(1999, 2000),
+         gadget3:::g3_step(g3_formula(
+             stock_iterate(ms, stock_intersect(os, print(c(stock_ss(ms__x), stock_ss(os__x))))),
+             ms = ld$modelstock,
+             os = ld$obsstock,
+             ms__x = g3_stock_instance(ld$modelstock, seq_len(prod(unlist(ld$modelstock$dim)))),
+             os__x = g3_stock_instance(ld$obsstock, seq_len(prod(unlist(ld$obsstock$dim))) * 10) )),
+             NULL ))
+     ok(ut_cmp_identical(
+         capture.output(invisible(model_fn())),
+         paste0("[1]  ", 1:24, " ", 1:24 * 10)), "model_fn: Loop / intersect over modelstock/obsstock correctly")
+ 
+     ok(ut_cmp_error(generate_ld("
+         age year stock_re number
+           3 1999    _f$  1999.3
+           3 1999    _g$  1999.3
+           3 1999    _h$  1999.3
+         "), "_g\\$, _h\\$"), "Regexes that don't match anything an error")
+ 
+     # Generate a list of stocks "stock_(imm,mat)_f" (NB: not male)
+     stock_names <- paste(
+         'stock',
+         rep(c('imm', 'mat'), each = 2),
+         c('f', 'm'),
+         sep = "_")
+     ld <- generate_ld("
+         age year stock_re number
+           3 1999    _mat_f$  1999.3
+           4 1999    _mat_f$  1999.4
+           6 1999    _imm_f$  1999.6
+           3 2000    _mat_f$  2000.3
+           6 2000    _imm_f$  2000.6
+           4 2001    _imm_f$  2001.4
+           6 2001    _mat_f$  2001.6
+         ", all_stocks = stock_names)
+     ok(ut_cmp_identical(
+         dimnames(ld$obs_array$num)[['stock_re']],
+         c("_mat_f$", "_imm_f$")), "Array names are regexes")
+     ok(ut_cmp_identical(
+         ld$maps$stock,
+         c(
+             stock_imm_f = '_imm_f$',
+             stock_imm_m = NA,
+             stock_mat_f = '_mat_f$',
+             stock_mat_m = NA )), "Stock map ignored unused stocks")
+ })
# g3l_likelihood_data:stock
ok - number array has all of source data
ok - No stock column, so no stock map
ok - Can't have both stock & stock_re
ok - number array has all of source data
ok - Array has stocks a & b
ok - stock_map is 1:1 mapping
ok - Unknown stock names in data an error
ok - number array has all of source data
ok - Array names are regexes
ok - Stock map used first regexes first
ok - model_fn: Loop / intersect over modelstock/obsstock correctly
ok - Regexes that don't match anything an error
ok - number array has all of source data
ok - Array names are regexes
ok - Stock map ignored unused stocks
> 
> ok_group('g3l_likelihood_data:stock:name_parts', {
+     stock_groupings <- function (stock_names, stock_cols) {
+         tbl <- expand.grid(number = 0, stock = stock_cols, age = 3:6, year = 1999:2001)
+         tbl$number <- seq_len(nrow(tbl))
+         ld <- generate_ld(tbl, all_stocks = stock_names)
+         return(ld$maps$stock)
+     }
+     out <- stock_groupings(
+         list(c('fish', 'imm'), c('fish', 'mat'), c('fish', 'sen')),
+         c('fish'))
+     ok(ut_cmp_equal(out, c(
+         fish_imm = 'fish',
+         fish_mat = 'fish',
+         fish_sen = 'fish' )), '"fish": Groups both maturity groups together')
+ 
+     out <- stock_groupings(
+         list(c('fish', 'imm'), c('fish', 'mat'), c('fish', 'sen')),
+         c('fish_mat', 'fish'))
+     ok(ut_cmp_equal(out, c(
+         fish_imm = 'fish',
+         fish_mat = 'fish_mat',
+         fish_sen = 'fish' )), '"fish_mat": Overrides "fish" group due to longer length')
+ 
+     out <- stock_groupings(
+         list(c('a', 'imm'), c('a', 'mat'), c('b', 'imm'), c('b', 'mat'), c('c', 'mat')),
+         c('a', 'b', 'mat'))
+     ok(ut_cmp_equal(out, c(
+         a_imm = 'a',
+         a_mat = 'a',
+         b_imm = 'b',
+         b_mat = 'b',
+         c_mat = 'mat' )), "'b' wins over 'mat' because it comes first")
+ 
+     out <- stock_groupings(
+         list(c('a', 'imm'), c('a', 'mat'), c('b', 'imm'), c('b', 'mat'), c('c', 'mat')),
+         c('a', 'mat', 'b'))
+     ok(ut_cmp_equal(out, c(
+         a_imm = 'a',
+         a_mat = 'a',
+         b_imm = 'b',
+         b_mat = 'mat',
+         c_mat = 'mat' )), "'mat' wins over 'b' because it comes first")
+ 
+     out <- stock_groupings(
+         list(c('a', 'imm', 'f'), c('a', 'mat', 'f'), c('a', 'imm', 'm'), c('a', 'mat', 'm'), c('c', 'mat')),
+         c('a_f', 'a_m', 'c'))
+     ok(ut_cmp_equal(out, c(
+         a_imm_f = 'a_f',
+         a_mat_f = 'a_f',
+         a_imm_m = 'a_m',
+         a_mat_m = 'a_m',
+         c_mat = 'c' )), "Name part groupings don't have to be sequential")
+ })
# g3l_likelihood_data:stock:name_parts
ok - number array has all of source data
ok - "fish": Groups both maturity groups together
ok - number array has all of source data
ok - "fish_mat": Overrides "fish" group due to longer length
ok - number array has all of source data
ok - 'b' wins over 'mat' because it comes first
ok - number array has all of source data
ok - 'mat' wins over 'b' because it comes first
ok - number array has all of source data
ok - Name part groupings don't have to be sequential
> 
> ok_group('g3l_likelihood_data:predator', {
+     ld <- generate_ld("
+         age year number
+           3 1999      1999.3
+           4 1999      1999.4
+           6 1999      1999.6
+           3 2000      2000.3
+           6 2000      2000.6
+           4 2001      2001.4
+           6 2001      2001.6
+         ")
+     ok(is.null(ld$maps$predator), "No predator column, so no predator map")
+ 
+     ok(ut_cmp_error(generate_ld("
+         age year predator predator_re number
+           3 1999    a  a$       1999.3
+         "), "predator.*predator_re"), "Can't have both predator & predator_re")
+ 
+     ld <- generate_ld("
+         age year predator number
+           3 1999    a  1999.3
+           4 1999    b  1999.4
+           6 1999    a  1999.6
+           3 2000    a  2000.3
+           6 2000    b  2000.6
+           4 2001    b  2001.4
+           6 2001    b  2001.6
+         ", all_predators = list(g3_stock('a', c(0, 10)), g3_stock('b', c(0, 10)) ))
+     ok(ut_cmp_identical(dimnames(ld$obs_array$num)[['predator']], c("a", "b")), "Array has predators a & b")
+     ok(ut_cmp_identical(ld$maps$predator, c(a = 'a', b = 'b')), "predator_map is 1:1 mapping")
+ 
+     # Generate a list of predators "predator_(trawl|gil)_(f|m)"
+     predators <- lapply(paste(
+         'predator',
+         rep(c('trawl', 'gil'), each = 2),
+         c('is', 'no'),
+         sep = "_"), function (x) g3_stock(x, 1))
+     ld <- generate_ld("
+         age year predator_re number
+           3 1999    _is$  1999.3
+           4 1999    ^predator_trawl  1999.4
+           6 1999    ^predator_gil  1999.6
+           3 2000    ^predator_trawl  2000.3
+           6 2000    ^predator_gil  2000.6
+           4 2001    ^predator_gil  2001.4
+           6 2001    ^predator_trawl  2001.6
+         ", all_predators = predators)
+     ok(ut_cmp_identical(
+         dimnames(ld$obs_array$num)[['predator_re']],
+         c("_is$", "^predator_trawl", "^predator_gil")), "Array names are regexes")
+     ok(ut_cmp_identical(
+         ld$maps$predator,
+         c(
+             predator_trawl_is = '_is$',
+             predator_trawl_no = '^predator_trawl',
+             predator_gil_is = '_is$',
+             predator_gil_no = '^predator_gil' )), "predator map used first regexes first")
+ 
+     # Generate a list of predators "predator_(trawl|gil)_(f|m)"
+     predators <- lapply(paste(
+         'predator',
+         rep(c('trawl', 'gil'), each = 2),
+         c('is', 'no'),
+         sep = "_"), function (x) g3_stock(x, 1))
+     ld <- generate_ld("
+         age year predator_re number
+           3 1999    _gil_is$  1999.3
+           4 1999    _gil_is$  1999.4
+           6 1999    _trawl_is$  1999.6
+           3 2000    _gil_is$  2000.3
+           6 2000    _trawl_is$  2000.6
+           4 2001    _trawl_is$  2001.4
+           6 2001    _gil_is$  2001.6
+         ", all_predators = predators, model_history = "late")
+     ok(ut_cmp_identical(
+         dimnames(ld$obs_array$num)[['predator_re']],
+         c("_gil_is$", "_trawl_is$")), "Array names are regexes")
+     ok(ut_cmp_identical(
+         ld$maps$predator,
+         c(
+             predator_trawl_is = '_trawl_is$',
+             predator_trawl_no = NA,
+             predator_gil_is = '_gil_is$',
+             predator_gil_no = NA )), "predator map ignored unused predators")
+ 
+     # Generated intersect code works
+     model_fn <- g3_to_r(list(
+         g3a_time(1999, 2000),
+         gadget3:::g3_step(g3_formula(
+             stock_iterate(ms, stock_intersect(os, print(c(stock_ss(ms__x), stock_ss(os__x))))),
+             ms = ld$modelstock,
+             os = ld$obsstock,
+             ms__x = g3_stock_instance(ld$modelstock, seq_len(prod(unlist(ld$modelstock$dim)))),
+             os__x = g3_stock_instance(ld$obsstock, seq_len(prod(unlist(ld$obsstock$dim))) * 10) )),
+             NULL ))
+     ok(ut_cmp_identical(
+         capture.output(invisible(model_fn())),
+         paste0("[1]  ", 1:16, " ", 1:16 * 10) ), "model_fn: Loop / intersect over modelstock/obsstock correctly")
+ })
# g3l_likelihood_data:predator
ok - number array has all of source data
ok - No predator column, so no predator map
ok - Can't have both predator & predator_re
ok - number array has all of source data
ok - Array has predators a & b
ok - predator_map is 1:1 mapping
ok - number array has all of source data
ok - Array names are regexes
ok - predator map used first regexes first
ok - number array has all of source data
ok - Array names are regexes
ok - predator map ignored unused predators
ok - model_fn: Loop / intersect over modelstock/obsstock correctly
> 
> 
> ok_group('g3l_likelihood_data:fleet', {
+     ld <- generate_ld("
+         age year number
+           3 1999      1999.3
+           4 1999      1999.4
+           6 1999      1999.6
+           3 2000      2000.3
+           6 2000      2000.6
+           4 2001      2001.4
+           6 2001      2001.6
+         ")
+     ok(is.null(ld$maps$fleet), "No fleet column, so no fleet map")
+ 
+     ok(ut_cmp_error(generate_ld("
+         age year fleet fleet_re number
+           3 1999    a  a$       1999.3
+         "), "fleet.*fleet_re"), "Can't have both fleet & fleet_re")
+ 
+     ld <- generate_ld("
+         age year fleet number
+           3 1999    a  1999.3
+           4 1999    b  1999.4
+           6 1999    a  1999.6
+           3 2000    a  2000.3
+           6 2000    b  2000.6
+           4 2001    b  2001.4
+           6 2001    b  2001.6
+         ", all_fleets = list(g3_fleet('a'), g3_fleet('b')))
+     ok(ut_cmp_identical(dimnames(ld$obs_array$num)[['fleet']], c("a", "b")), "Array has fleets a & b")
+     ok(ut_cmp_identical(ld$maps$fleet, c(a = 'a', b = 'b')), "fleet_map is 1:1 mapping")
+ 
+     # Generate a list of fleets "fleet_(trawl|gil)_(f|m)"
+     fleets <- lapply(paste(
+         'fleet',
+         rep(c('trawl', 'gil'), each = 2),
+         c('is', 'no'),
+         sep = "_"), function (x) g3_stock(x, 1))
+     ld <- generate_ld("
+         age year fleet_re number
+           3 1999    _is$  1999.3
+           4 1999    ^fleet_trawl  1999.4
+           6 1999    ^fleet_gil  1999.6
+           3 2000    ^fleet_trawl  2000.3
+           6 2000    ^fleet_gil  2000.6
+           4 2001    ^fleet_gil  2001.4
+           6 2001    ^fleet_trawl  2001.6
+         ", all_fleets = fleets)
+     ok(ut_cmp_identical(
+         dimnames(ld$obs_array$num)[['fleet_re']],
+         c("_is$", "^fleet_trawl", "^fleet_gil")), "Array names are regexes")
+     ok(ut_cmp_identical(
+         ld$maps$fleet,
+         c(
+             fleet_trawl_is = '_is$',
+             fleet_trawl_no = '^fleet_trawl',
+             fleet_gil_is = '_is$',
+             fleet_gil_no = '^fleet_gil' )), "fleet map used first regexes first")
+ 
+     # Generate a list of fleets "fleet_(trawl|gil)_(f|m)"
+     fleets <- lapply(paste(
+         'fleet',
+         rep(c('trawl', 'gil'), each = 2),
+         c('is', 'no'),
+         sep = "_"), function (x) g3_stock(x, 1))
+     ld <- generate_ld("
+         age year fleet_re number
+           3 1999    _gil_is$  1999.3
+           4 1999    _gil_is$  1999.4
+           6 1999    _trawl_is$  1999.6
+           3 2000    _gil_is$  2000.3
+           6 2000    _trawl_is$  2000.6
+           4 2001    _trawl_is$  2001.4
+           6 2001    _gil_is$  2001.6
+         ", all_fleets = fleets, model_history = "late")
+     ok(ut_cmp_identical(
+         dimnames(ld$obs_array$num)[['fleet_re']],
+         c("_gil_is$", "_trawl_is$")), "Array names are regexes")
+     ok(ut_cmp_identical(
+         ld$maps$fleet,
+         c(
+             fleet_trawl_is = '_trawl_is$',
+             fleet_trawl_no = NA,
+             fleet_gil_is = '_gil_is$',
+             fleet_gil_no = NA )), "fleet map ignored unused fleets")
+ 
+     # Generated intersect code works
+     model_fn <- g3_to_r(list(
+         g3a_time(1999, 2000),
+         gadget3:::g3_step(g3_formula(
+             stock_iterate(ms, stock_intersect(os, print(c(stock_ss(ms__x), stock_ss(os__x))))),
+             ms = ld$modelstock,
+             os = ld$obsstock,
+             ms__x = g3_stock_instance(ld$modelstock, seq_len(prod(unlist(ld$modelstock$dim)))),
+             os__x = g3_stock_instance(ld$obsstock, seq_len(prod(unlist(ld$obsstock$dim))) * 10) )),
+             NULL ))
+     ok(ut_cmp_identical(
+         capture.output(invisible(model_fn())),
+         paste0("[1]  ", 1:16, " ", 1:16 * 10) ), "model_fn: Loop / intersect over modelstock/obsstock correctly")
+ })
# g3l_likelihood_data:fleet
ok - number array has all of source data
ok - No fleet column, so no fleet map
ok - Can't have both fleet & fleet_re
ok - number array has all of source data
ok - Array has fleets a & b
ok - fleet_map is 1:1 mapping
ok - number array has all of source data
ok - Array names are regexes
ok - fleet map used first regexes first
ok - number array has all of source data
ok - Array names are regexes
ok - fleet map ignored unused fleets
ok - model_fn: Loop / intersect over modelstock/obsstock correctly
> 
> ok_group('g3l_likelihood_data:predator') ##########
# g3l_likelihood_data:predator
> ld <- generate_ld(expand.grid(
+     length = 5:10,
+     predator_length = c(10, 50, 100),
+     predator_age = c('[0,5)', '[5,10)'), # ((
+     predator_tag = c('a', 'b'),
+     year = 1999:2000 ))
ok - number array has all of source data
> 
> ok(gadget3:::ut_cmp_code(generate_code(ld, 'stock_iterate', cur_year = 1999, cur_step = 1), quote({
+     ut_obs__time_idx <- intlookup_getdefault(ut_obs__times, (cur_year * 100L + cur_step * 0L), -1L)
+     if (ut_obs__time_idx >= (1L)) {
+         for (ut_obs__predator_tag_idx in seq_along(ut_obs__predator_tag_ids)) {
+             predator_tag <- ut_obs__predator_tag_ids[[ut_obs__predator_tag_idx]]
+             for (ut_obs__predator_agegroup_idx in seq_along(ut_obs__predator_minages)) {
+                 predator_age <- ut_obs__predator_minages[[ut_obs__predator_agegroup_idx]]
+                 for (ut_obs__predator_length_idx in seq_along(ut_obs__predator_midlen)) {
+                   predator_length <- ut_obs__predator_midlen[[ut_obs__predator_length_idx]]
+                   for (ut_obs__length_idx in seq_along(ut_obs__midlen)) {
+                     length <- ut_obs__midlen[[ut_obs__length_idx]]
+                     ut_obs__num[ut_obs__length_idx, ut_obs__predator_length_idx,
+                       ut_obs__predator_agegroup_idx, ut_obs__predator_tag_idx,
+                       ut_obs__time_idx]
+                   }
+                 }
+             }
+         }
+     }
+ }), optimize = TRUE), "stock_iterate: All predator dimensions included, with prefixed variables")
ok - stock_iterate: All predator dimensions included, with prefixed variables
> 
> ok(gadget3:::ut_cmp_code(generate_code(ld, 'stock_intersect', cur_year = 1999, cur_step = 1, predator_tag = 1, predator_length = 1, predator_age = 1), quote({
+     ut_obs__time_idx <- intlookup_getdefault(ut_obs__times, (cur_year * 100L + cur_step * 0L), -1L)
+     if (ut_obs__time_idx >= 1L) {
+         for (ut_obs__predator_tag_idx in seq_along(ut_obs__predator_tag_ids)) {
+             predator_tag <- ut_obs__predator_tag_ids[[ut_obs__predator_tag_idx]]
+             for (ut_obs__predator_agegroup_idx in seq_along(ut_obs__predator_minages)) {
+                 `_age` <- ut_obs__predator_minages[[ut_obs__predator_agegroup_idx]]
+                 for (ut_obs__predator_length_idx in seq_along(ut_obs__predator_minlen)) {
+                   predator_length <- ut_obs__predator_midlen[[ut_obs__predator_length_idx]]
+                   for (ut_obs__length_idx in seq_along(ut_obs__minlen)) {
+                     length <- ut_obs__midlen[[ut_obs__length_idx]]
+                     ut_obs__num[ut_obs__length_idx, ut_obs__predator_length_idx,
+                       ut_obs__predator_agegroup_idx, ut_obs__predator_tag_idx,
+                       ut_obs__time_idx]
+                   }
+                 }
+             }
+         }
+     }
+ }), optimize = TRUE), "stock_intersect: All predator dimensions included, with prefixed variables")
ok - stock_intersect: All predator dimensions included, with prefixed variables
> 
> ok(ut_cmp_equal(
+     ld$obsstock$env$stock__midlen,
+     gadget3:::force_vector(c("5:6" = 5.5, "6:7" = 6.5, "7:8" = 7.5, "8:9" = 8.5, "9:10" = 9.5, "10:Inf" = 10.5)) ), "stock__midlen: prey vars set")
ok - stock__midlen: prey vars set
> ok(ut_cmp_equal(
+     ld$obsstock$env$stock__predator_midlen,
+     gadget3:::force_vector(c("10:50" = 30, "50:100" = 75, "100:Inf" = 120)) ), "stock__predator_midlen: predator vars prefixed")
ok - stock__predator_midlen: predator vars prefixed
> ok(ut_cmp_equal(
+     environment(attr(ld$obsstock$env$ut_obs__predator_agegroup, "g3_global_init_val"))$ut_obs__predator_agegroup_keys,
+     gadget3:::force_vector(0:9)), "ut_obs__predator_agegroup_keys: initval keys got renamed")
ok - ut_obs__predator_agegroup_keys: initval keys got renamed
> ok(ut_cmp_equal(
+     environment(attr(ld$obsstock$env$ut_obs__predator_agegroup, "g3_global_init_val"))$ut_obs__predator_agegroup_values,
+     gadget3:::force_vector( rep(1:2, each = 5) )), "ut_obs__predator_agegroup_values: initval values got renamed")
ok - ut_obs__predator_agegroup_values: initval values got renamed
> 
> ########## g3l_likelihood_data:predator
> 
> proc.time()
   user  system elapsed 
   3.18    0.14    3.26 
1..134
# Looks like you passed all 134 tests.