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Type 'q()' to quit R. > 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(), 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( + number = g3_distribution_preview(structure(tbl, ...), stocks = all_stocks, fleets = all_fleets) ) + } else { + # Fall back to old behaviour + out <- gadget3:::g3l_likelihood_data('ut', structure(tbl, ...), all_stocks = all_stocks, all_fleets = all_fleets) + } + + # NB: A failed merge would result in repeated instances + ok(ut_cmp_equal( + sort(as.numeric(out$number[out$number != 0])), + sort(as.numeric(tbl$number)), + deparse_frame = -2), "number array has all of source data") + return(out) + } > > # Dig minlen out of modelstock > ld_minlen <- function (ld) { + x <- g3_stock_def(ld$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', { + ok(ut_cmp_error({ + ld <- generate_ld( + data.frame( + year = 1990, + camel = 3, + dromedary = 1, + number = 1:3, + stringsAsFactors = FALSE), + end = NULL) + }, "camel, dromedary"), "Unrecognised camels columns") + }) # g3l_likelihood_data:unknown ok - Unrecognised camels 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$number, " + length time Freq + 0:Inf 1998 1 + 0:Inf 2001 3 + 0:Inf 2002 2 + "), "Year gap, wonky year order preserved") + + ld <- generate_ld(" + year step number + 1998 1 1 + 1998 2 2 + 1999 1 3 + 2000 1 4 + 2000 2 5 + ") + ok(cmp_array(ld$number, " + 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$number, " + length time Freq + 0:Inf 1998 1 + 0:Inf 2001 3 + 0:Inf 2002 2 + "), "Time column used when year not present (i.e. can parse our own output)") + + ld <- generate_ld(" + time number + 1998-01 2 + 1998-02 4 + 1999-01 3 + 1999-02 9 + ") + ok(cmp_array(ld$number, " + 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$number, " + length time Freq + 0:Inf 1999 1 + 0:Inf 2000 2 + 0:Inf 2001 3 + "), "Default single length dimension if none supplied") + ok(ut_cmp_identical(ld$modelstock$dimnames, list( + length = "0:Inf")), "modelstock got default length dimension if none supplied") + + ld <- generate_ld(" + year length number + 1999 1 1 + 2000 1 2 + 2001 1 3 + 1999 5 4 + 2000 5 5 + 2001 5 6 + 1999 10 7 + 2001 10 9 + 2000 30 11 + 2001 30 12 + ") + ok(cmp_array(ld$number, " + 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$number, " + length time Freq + 10:20 1999 1999.1 + 20:40 1999 1999.2 + 40:80 1999 1999.3 + 10:20 2000 2000.1 + 20:40 2000 2000.2 + 40:80 2000 0.0 + 10:20 2001 2001.1 + 20:40 2001 2001.2 + 40:80 2001 2001.3 + "), "Use lengths, removed names from attribute, gaps filled in") + ok(ut_cmp_identical( + ld_minlen(ld), + c("10:20" = 10, "20:40" = 20, "40:80" = 40)), "minlen set by attribute") + ok(ut_cmp_identical(ld_upperlen(ld), 80), "Upperlen set by attribute") + ok(ut_cmp_identical(ld_dl(ld), c(10, 20, 40)), "dl difference up to upper bound") + ok(ut_cmp_identical(ld_plusdl(ld), 10), "plusdl is the mode") + + ld <- generate_ld(" + year length number + 1999 a 1999.1 + 2000 a 2000.1 + 2001 a 2001.1 + 1999 b 1999.2 + 2000 b 2000.2 + 2001 b 2001.2 + 1999 c 1999.3 + 2001 c 2001.3 + ", + length = list( + a = structure(quote(seq(10, 20)), min = 10, max = 20), + b = structure(quote(seq(20, 40)), min = 20, max = 40), + c = structure(quote(seq(40, 80)), min = 40, max = 80) ), + use_preview = TRUE ) + ok(cmp_array(ld$number, " + 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$number, " + 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$number, " + 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$number, " + length age time Freq + 0:5 1:3 1990 1 + 5:10 1:3 1990 2 + 10:15 1:3 1990 3 + 15:20 1:3 1990 4 + 20:25 1:3 1990 5 + 25:30 1:3 1990 6 + 30:35 1:3 1990 7 + 35:40 1:3 1990 8 + 40:45 1:3 1990 9 + 0:5 4:9 1990 10 + 5:10 4:9 1990 11 + 10:15 4:9 1990 12 + 15:20 4:9 1990 13 + 20:25 4:9 1990 14 + 25:30 4:9 1990 15 + 30:35 4:9 1990 16 + 35:40 4:9 1990 17 + 40:45 4:9 1990 18 + "), "Can use intervals in strings, converted to groups") + + ld <- generate_ld(data.frame( + year = 1990, + length = c( + as.character(cut(seq(23, 39, by=5), seq(0, 50, by = 5), right = FALSE)), + as.character(cut(seq(3, 47, by=5), seq(0, 50, by = 5), right = FALSE)), + NULL), + age = c( + rep(1, 4), + rep(2, 9), + NULL), + stringsAsFactors = FALSE)) + ok(cmp_array(ld$number, " + 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$number, responseName = 'number')) + ok(ut_cmp_equal(ld$number, ld_loopback$number), "Can parse our own output") + }) # g3l_likelihood_data:age_char ok - number array has all of source data ok - Converted back to factor, preserving ordering of entries ok - number array has all of source data ok - Can use intervals in strings, converted to groups ok - number array has all of source data ok - Partial ranges padded out with zeros ok - number array has all of source data ok - number array has all of source data ok - Can parse our own output > > ok_group('g3l_likelihood_data:age', { + ld <- generate_ld(" + age year number + 3 1999 1999.3 + 4 1999 1999.4 + 6 1999 1999.6 + 3 2000 2000.3 + 6 2000 2000.6 + 4 2001 2001.4 + 6 2001 2001.6 + ") + ok(cmp_array(ld$number, " + 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$number, " + length age time Freq + 0:Inf 1:3 1999 1999.1 + 0:Inf 4:6 1999 1999.2 + 0:Inf 7:10 1999 0.0 + 0:Inf 1:3 2000 2000.1 + 0:Inf 4:6 2000 0.0 + 0:Inf 7:10 2000 0.0 + 0:Inf 1:3 2001 2001.1 + 0:Inf 4:6 2001 2001.2 + 0:Inf 7:10 2001 0.0 + "), "Worked out age dimensions from attributes, filled in missing values") + ok(ut_cmp_identical( + ld_minages(ld), + gadget3:::force_vector("1:3" = 1L, "4:6" = 4L, "7:10" = 7L)), "agegroups using minages from attribute") + }) # g3l_likelihood_data:age ok - number array has all of source data ok - Worked out age dimensions from data, filled in missing values, including entirely absent ones ok - number array has all of source data ok - Worked out age dimensions from attributes, filled in missing values ok - agegroups using minages from attribute > > > ok_group('g3l_likelihood_data:age_factor', { + df <- data.frame( + year = 1990, + age = c(3,3,4,5), + number = 1, + stringsAsFactors = TRUE) + df$age <- cut(df$age, seq(3, 10, by = 1), right = FALSE) + df <- aggregate(number ~ year + age, df, sum) + ld <- generate_ld(df) + ok(cmp_array(ld$number, " + 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$number: included all single ages") + + ld <- generate_ld(data.frame( + year = 1990, + age = as.factor(c(3,4,5,8)), + stringsAsFactors = TRUE)) + ok(cmp_array(ld$number, " + 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$number: can also use integer strings as factors") + + df <- data.frame( + year = 1990, + age = c(3,3,4,5), + number = 1, + stringsAsFactors = TRUE) + df$age <- cut(df$age, seq(2, 10, by = 4), right = FALSE) + df <- aggregate(number ~ year + age, df, sum) + ld <- generate_ld(df) + ok(cmp_array(ld$number, " + length age time Freq + 0:Inf 2:5 1990 4 + 0:Inf 6:9 1990 0 + "), "ld$number: Everything grouped into first group, second compared to zero") + }) # g3l_likelihood_data:age_factor ok - number array has all of source data ok - ld$number: included all single ages ok - number array has all of source data ok - ld$number: can also use integer strings as factors ok - number array has all of source data ok - ld$number: 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$number, " + length time area Freq + 0:Inf 1999 1 1999.1 + 0:Inf 2000 1 0.0 + 0:Inf 2001 1 2001.1 + 0:Inf 1999 2 1999.2 + 0:Inf 2000 2 2000.2 + 0:Inf 2001 2 2001.2 + 0:Inf 1999 3 1999.3 + 0:Inf 2000 3 2000.3 + 0:Inf 2001 3 0.0 + "), "Worked out area dimensions from data, filled in missing values") + + ld <- gadget3:::g3l_likelihood_data('ut', read.table(header = TRUE, stringsAsFactors = TRUE, text = " + area year number + a 1999 1999.1 + b 1999 1999.2 + c 1999 1999.3 + b 2000 2000.2 + c 2000 2000.3 + a 2001 2001.1 + b 2001 2001.2 + "), area_group = list(a = 3, b = 4, c = c(1:2))) + ok(cmp_array(ld$number, " + 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$number, " + length tag time Freq + 0:Inf a 1999 1999.1 + 0:Inf b 1999 1999.2 + 0:Inf c 1999 1999.3 + 0:Inf a 2000 0.0 + 0:Inf b 2000 2000.2 + 0:Inf c 2000 2000.3 + 0:Inf a 2001 2001.1 + 0:Inf b 2001 2001.2 + 0:Inf c 2001 0.0 + "), "Worked out tag dimensions from data") + ok(ut_cmp_identical( + g3_stock_def(ld$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$stock_map), "No stock column, so no stock map") + + ok(ut_cmp_error(generate_ld(" + age year stock stock_re number + 3 1999 a a$ 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$number)[['stock']], c("a", "b")), "Array has stocks a & b") + ok(ut_cmp_identical(ld$stock_map, list(a = 1L, b = 2L)), "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) + ok(ut_cmp_identical( + dimnames(ld$number)[['stock_re']], + c("_f$", "^stock_mat", "^stock_imm")), "Array names are regexes") + ok(ut_cmp_identical( + ld$stock_map, + list( + stock_imm_f = 1L, + stock_imm_m = 3L, + stock_mat_f = 1L, + stock_mat_m = 2L)), "Stock map used first regexes first") + + ok(ut_cmp_error(generate_ld(" + age year stock_re number + 3 1999 _f$ 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$number)[['stock_re']], + c("_mat_f$", "_imm_f$")), "Array names are regexes") + ok(ut_cmp_identical( + ld$stock_map, + list( + stock_imm_f = 2L, + stock_imm_m = NULL, + stock_mat_f = 1L, + stock_mat_m = NULL)), "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 - 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: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$fleet_map), "No fleet column, so no fleet map") + + ok(ut_cmp_error(generate_ld(" + age year fleet fleet_re number + 3 1999 a a$ 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 + ") + ok(ut_cmp_identical(dimnames(ld$number)[['fleet']], c("a", "b")), "Array has fleets a & b") + ok(ut_cmp_identical(ld$fleet_map, list(a = 1L, b = 2L)), "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$number)[['fleet_re']], + c("_is$", "^fleet_trawl", "^fleet_gil")), "Array names are regexes") + ok(ut_cmp_identical( + ld$fleet_map, + list( + fleet_trawl_is = 1L, + fleet_trawl_no = 2L, + fleet_gil_is = 1L, + fleet_gil_no = 3L)), "fleet map used first regexes first") + + # Generate a list of fleets "fleet_(trawl|gil)_(f|m)" + fleets <- lapply(paste( + 'fleet', + rep(c('trawl', 'gil'), each = 2), + c('is', 'no'), + sep = "_"), function (x) g3_stock(x, 1)) + ld <- generate_ld(" + age year fleet_re number + 3 1999 _gil_is$ 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) + ok(ut_cmp_identical( + dimnames(ld$number)[['fleet_re']], + c("_gil_is$", "_trawl_is$")), "Array names are regexes") + ok(ut_cmp_identical( + ld$fleet_map, + list( + fleet_trawl_is = 2L, + fleet_trawl_no = NULL, + fleet_gil_is = 1L, + fleet_gil_no = NULL)), "fleet map ignored unused fleets") + }) # 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 > > proc.time() user system elapsed 0.70 0.10 0.75 # Looks like you passed all 98 tests.