Extract an element from iamOutput-class and format this as a
tibble. This tibble is 6 column wide with specified format (see details)
Usage
IAM.format(object, name, sim_name = NA_character_, n = NA_real_)
# S4 method for iamOutput,character
IAM.format(object, name, sim_name = NA_character_, n = NA_real_)
format_vareco(object, name, sim_name = NA_character_, n = NA_real_)
format_varsp(object, name, sim_name = NA_character_, n = NA_real_)Arguments
- object
iamOutput-classobject created withIAM.model().- name
names of the exported variable from IAM. "summary" will select few variables that are usually displayed for most common scenarii ("Fbar", "SSB", "L_et", "N", "nbv_f", "effort2_f", "GVLav_f", "gva_f", "gp_f", "wageg_f", "wagen_f"). chr.
- sim_name
Name of the simulation, used for joining multiple scenarii iamOutput. NA by default, chr.
- n
Number of the simulation, used for joining replicated iamOutput. NA by default, dbl.
Value
Format : long format for ggplot and dplyr analysis to facilitate filter and summary computations. If the variable is not defined for a specific dimension (column), this column is filled with NA.
- sim_name
Simulation name. chr.
- n
Number of the simulation. dbl
- variable
Single value repeated, but is needed if multiple variables are assembled with
bind_row(). chr vector- species
Species names, can contain dynamic and static species depending on the variable selected.. chr vector
- fleet
Fleet names. fct vector
- metier
Metier names. fct vector
- age
Ages for dynamic species. fct vector
- year
year step for the simulation. dbl vector
- value
Value of the variable for every column place indicated on the same row. dbl vector
Details
The reconcilSPP variable return character value, so it can't be binded with other variable which are numeric.
Examples
data("IAM_input_2009")
data("IAM_argum_2009")
sim_statu_quo <- IAM::IAM.model(objArgs = IAM_argum_2009, objInput = IAM_input_2009)
#' cas vide return NULL
IAM.format(sim_statu_quo, "not a variable")
#> Warning: "not a variable" variable does not exist in an IAM output.
#> NULL
#' cas simple bio
IAM.format(sim_statu_quo, "SSB")
#> # A tibble: 36 × 9
#> sim_name n variable species fleet metier age year value
#> <chr> <dbl> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl>
#> 1 NA NA SSB ARC NA NA NA 2009 18723.
#> 2 NA NA SSB ARC NA NA NA 2010 17990.
#> 3 NA NA SSB ARC NA NA NA 2011 17220.
#> 4 NA NA SSB ARC NA NA NA 2012 16459.
#> 5 NA NA SSB ARC NA NA NA 2013 16194.
#> 6 NA NA SSB ARC NA NA NA 2014 16611.
#> 7 NA NA SSB ARC NA NA NA 2015 17817.
#> 8 NA NA SSB ARC NA NA NA 2016 19506.
#> 9 NA NA SSB ARC NA NA NA 2017 21242.
#> 10 NA NA SSB ARC NA NA NA 2018 22793.
#> # … with 26 more rows
#' cas complexe bio
IAM.format(sim_statu_quo, "F")
#> # A tibble: 40,656 × 9
#> sim_name n variable species fleet metier age year value
#> <chr> <dbl> <chr> <chr> <fct> <fct> <fct> <dbl> <dbl>
#> 1 NA NA F ARC Alis Filet_DAR 0 2009 0
#> 2 NA NA F ARC Antea Filet_DAR 0 2009 0
#> 3 NA NA F ARC Atalante Filet_DAR 0 2009 0
#> 4 NA NA F ARC Haliotis Filet_DAR 0 2009 0
#> 5 NA NA F ARC Marion_Dufresne Filet_DAR 0 2009 0
#> 6 NA NA F ARC Pourquoi_pas Filet_DAR 0 2009 0
#> 7 NA NA F ARC Thalassa Filet_DAR 0 2009 0
#> 8 NA NA F ARC Alis Filet_DP 0 2009 0
#> 9 NA NA F ARC Antea Filet_DP 0 2009 0
#> 10 NA NA F ARC Atalante Filet_DP 0 2009 0
#> # … with 40,646 more rows
IAM.format(sim_statu_quo, "N_S1M1")
#> # A tibble: 192 × 9
#> sim_name n variable species fleet metier age year value
#> <chr> <dbl> <chr> <chr> <chr> <chr> <fct> <dbl> <dbl>
#> 1 NA NA N_S1M1 DAR NA NA 0 2009 137653
#> 2 NA NA N_S1M1 DAR NA NA 1 2009 50556.
#> 3 NA NA N_S1M1 DAR NA NA 2 2009 21313.
#> 4 NA NA N_S1M1 DAR NA NA 3 2009 25389
#> 5 NA NA N_S1M1 DAR NA NA 4 2009 15481.
#> 6 NA NA N_S1M1 DAR NA NA 5 2009 2399.
#> 7 NA NA N_S1M1 DAR NA NA 6 2009 875.
#> 8 NA NA N_S1M1 DAR NA NA 7 2009 624.
#> 9 NA NA N_S1M1 DAR NA NA 8 2009 731.
#> 10 NA NA N_S1M1 DAR NA NA 9 2009 119.
#> # … with 182 more rows
#' cat eco
IAM.format(sim_statu_quo, name = "ratio_gp_K_f")
#> # A tibble: 84 × 9
#> sim_name n variable species fleet metier age year value
#> <chr> <dbl> <chr> <lgl> <chr> <chr> <chr> <dbl> <dbl>
#> 1 NA NA ratio_gp_K_f NA Alis NA NA 2009 -0.899
#> 2 NA NA ratio_gp_K_f NA Alis NA NA 2010 -0.899
#> 3 NA NA ratio_gp_K_f NA Alis NA NA 2011 -0.899
#> 4 NA NA ratio_gp_K_f NA Alis NA NA 2012 -0.899
#> 5 NA NA ratio_gp_K_f NA Alis NA NA 2013 -0.899
#> 6 NA NA ratio_gp_K_f NA Alis NA NA 2014 -0.899
#> 7 NA NA ratio_gp_K_f NA Alis NA NA 2015 -0.899
#> 8 NA NA ratio_gp_K_f NA Alis NA NA 2016 -0.899
#> 9 NA NA ratio_gp_K_f NA Alis NA NA 2017 -0.899
#> 10 NA NA ratio_gp_K_f NA Alis NA NA 2018 -0.899
#> # … with 74 more rows
#' Warning here values are string !
IAM.format(sim_statu_quo, name = "reconcilSPP")
#> Warning: reconcilSPP variable has character for value. This will cause problems if you need to rbind ouputs of IAM.format()
#> # A tibble: 924 × 9
#> sim_name n variable species fleet metier age year value
#> <chr> <dbl> <chr> <lgl> <fct> <fct> <chr> <dbl> <chr>
#> 1 NA NA reconcilSPP NA Alis Filet_D… NA 1 NA
#> 2 NA NA reconcilSPP NA Antea Filet_D… NA 1 NA
#> 3 NA NA reconcilSPP NA Atalante Filet_D… NA 1 NA
#> 4 NA NA reconcilSPP NA Haliotis Filet_D… NA 1 NA
#> 5 NA NA reconcilSPP NA Marion_Dufresne Filet_D… NA 1 NA
#> 6 NA NA reconcilSPP NA Pourquoi_pas Filet_D… NA 1 NA
#> 7 NA NA reconcilSPP NA Thalassa Filet_D… NA 1 NA
#> 8 NA NA reconcilSPP NA Alis Filet_DP NA 1 NA
#> 9 NA NA reconcilSPP NA Antea Filet_DP NA 1 NA
#> 10 NA NA reconcilSPP NA Atalante Filet_DP NA 1 NA
#> # … with 914 more rows