Function reference • gmr

Preparing runs and reading input files The following functions allow (i) read the various input files and (ii) create folders (and clean them) needed for the runs.
Functions to read input files
`readGMACSfiles()`	Read all the GMACS input files
`readGMACS.dat()`	Read the gmacs.dat file
`readGMACSdat()`	Read the GMACS data file
`readGMACSctl()`	readGMACSctl
`readGMACSprj()`	readGMACSprj
`getInpOutFiles()`	Read all input and output files
`GMACSversion()`	Function to extract the Version number of GMACS
Functions to create specific folders and clean output files from GMACS
`SetGMACSfold()`	Create the needed folders to run GMACS
`clean_bat()`	Clean gmacs output files in a folder
`clean_files()`	Clean files in a folder
`clean_root()`	Clean gmacs compilation-process files in the "root folder"
`clean_bat_Sim()`	Clean the output files of the Gmacs simulation module
`clean_Inputfiles()`	Clean Gmacs input files in a folder
Functions to (re)write the input/output files
`writeGmacs.dat()`	Write the gmacs.dat file
`writeGmacsdatfile()`	Write data file
`writeGmacsctlfile()`	Write the control file
`writeGmacsprjfile()`	Write the projection file
`writeGmacsPAR()`	Write the gmacs.par file
`write_Gmacs_InputFiles()`	Write all the stock-specific Gmacs input files
Conducting a stock assessment using GMACS Set of functions for working with GMACS while realizing specific tasks (building the gmacs executable, running a stock assessment for one or several stocks, making comparisons between model versions).
`GMACS()`	GMACS
`Do_GMACS()`	Do_GMACS
`Do_Comp()`	Do_Comp
`.GetGmacsExe()`	.GetGmacsExe
`createGmacsExe()`	Create the Gmacs executable from the tpl file
`.buildGMACS()`	.buildGMACS
`write_TPL()`	write_TPL
`copy_GMACSinputs()`	Copy specific GMACS input files
Updating a version of GMACS for a new release Set of functions for implementing and releasing a new version (including making comparison)
`set_DevStruct()`	Set up structure folder for new code version of Gmacs
`Do_Comp()`	Do_Comp
`UpdateGMACS()`	UpdateGMACS
`CompareCodeVersion()`	Compare Gmacs version
Realizing a simulation-estimation analysis Set of functions to generate simulated data and realize estimations in the context of a simulation-estimation approach.
`prepSim()`	Get the original input files for the simulation approach
`GenSimFiles()`	Generate the input files to get the simulated data for each simulation
`SimData()`	Generate the simulated data
`SaveSimFiles()`	Save the outputs of each simulation-estimation run
`Gen_GmacsSim()`	Generates the simulated data for a set of simulation
`RunGmacsSim()`	Run the GMACS simulation-estimation
Manipulating outputs from the GMACS function The following functions allow to read GMACS outputs and manipulate the results. These functions are called in the graphical functions.
Read GMACS outputs
`readGMACSpar()`	readGMACSpar
`readGMACSallOUT()`	Read GmacsAll.out
`readGMACSrep()`	Read Gmacs.rep
`readGMACSsimdat()`	readGMACSsimdat
`read_admb()`	Read ADMB output files
`read_fit()`	Read ADMB .par, .std, and .cor file and return an R object of type 'list' of estimates and correlations
`read_rep()`	Read ADMB .rep file
`read_psv()`	Read ADMB .psv file
`read_ctl()`	Read ADMB .ctl file
`read.OUT()`	read.OUT
Manipulate GMACS results
`.get_cpue_df()`	Get cpue or other indices
`.get_catch_df()`	Get observed and predicted catch values
`.get_gi_df()` `.get_gi_df()`	Get growth increment data
`.get_F_df()`	Get F parameters
`.get_dynB0_df()`	Extract spawning stock biomass (ssb) from gmacs run
`.get_length_weight_df()`	Get length-weight data
`.get_maturity_df()`	Get maturity data
`.get_mnLen_df()`	Get observed and predicted mean lengths
`.get_molt_prob_df()`	Get molting probability data
`.get_M_df()`	Get natural mortality data
`.get_numbers_df()`	Get numbers at length data
`.get_recruitment_df()`	Get recruitment data
`.get_recruitment_size_df()`	Get recruitment size distribution data
`.get_selectivity_df()`	Get the selectivity data
`.get_sizeComps_df()`	Get observed and predicted size composition values
`.get_ssb_df()`	Extract spawning stock biomass (ssb) from gmacs run
Making results tables The following functions can be used to create tables of catches, likelihoods and reference points
`table_catch()`	Create a table of catches
`table_likelihoods()`	Create a table of likelihoods
`table_penalties()`	Create a table of penalties
`table_priors()`	Create a table of priors
`table_spr()`	Create a table of SPR reference points
Creating plots The following functions are awesome for creating plots of data and model fits, model outputs estimates (biological, fisheries and, demographic parameters), model residuals and, stock status.
Do all plots from gmr
`plot_gmr()`	Do all gmr plots
`plot_basicOutput()`	Plotting the basic outputs of GMACS
`shiny_gmacs()`	Plot Gmacs on shiny app
Plotting data used and model fits
`plot_datarange()`	Plot data range by fleet and year
`plot_cpue()`	Plot cpue or other indices
`plot_catch()` `plot_catch()`	Plot observed and predicted catch values
`plot_size_comps()`	Plot fits to size composition data
`plot_size_ridges()`	Plot fits to size composition data
Plotting Biological parameters
`plot_growth_inc()` `plot_growth_inc()`	Plot growth from arbitrary start age
`plot_growth()`	Plot growth from arbitrary start age
`plot_length_weight()`	Plot length-weight relationship
`plot_length_maturity()`	Plot length-maturity relationship
`plot_molt_prob()`	Plot molting probability relationship
`plot_growth_transition()`	Plot growth transition
`plot_size_transition()`	Plot size transition
Plotting Fisheries parameters
`plot_F()`	Plot fishing mortality
`plot_fishing_mortality()`	Plot fishing mortality (F)
`plot_selectivity()`	Plot selectivity
`plot_selectivity_3d()`	Plot selectivity 3D
Plotting Demographic parameters
`plot_dynB0()`	Plot predicted spawning stock biomass (ssb)
`plot_natural_mortality()`	Plot natural mortality
`plot_numbers()`	Plot numbers at length
`plot_recruitment()`	Plot predicted recruitment and approximate asymptotic error-bars
`plot_recruitment_size()`	Plot recruitment size distribution
`plot_models_recruitment()`	Plot predicted recruitment across model runs
`plot_ssb()`	Plot predicted spawning stock biomass (ssb)
Plotting Model residuals
`plot_cpue_res()`	Plot residuals of cpue or other indices
`plot_size_comps_res()`	Plot fits to size composition data
Plotting Stock Status
`plot_kobe()`	Plot predicted spawning stock biomass (ssb)
Terminals These functions allow the user to launch a scpecific command in a R Terminal.
`.CallTerm()`	.CallTerm
Plotting options and ggplot utilities Set of functions for settings the type of plot, the rezolution, the size and disposition of the graphics as well as the colors.
`.gmr_options`	GMR plotting options
`BaseThemeGMR()`	Base theme for plotting with gmr
`.cbPalette1`	The color-blind friendly palette with grey
`.cbPalette2`	The color-blind friendly palette with black
`set_ggtheme()`	Set plotting theme for ggplot2 via gmr
`plot_type()`	Specify the type of plot you would like to create
`multiplot()`	Multi-Plot utility for ggplot2 ggplot objects can be passed in ..., or to plotlist (as a list of ggplot objects) - cols: Number of columns in layout - layout: A matrix specifying the layout. If present, 'cols' is ignored.
`plot_multiple()`	Plot multiple figures on a page

Reference

Preparing runs and reading input files

Functions to read input files

Functions to create specific folders and clean output files from GMACS

Functions to (re)write the input/output files

Conducting a stock assessment using GMACS

Updating a version of GMACS for a new release

Realizing a simulation-estimation analysis

Manipulating outputs from the GMACS function

Read GMACS outputs

Manipulate GMACS results

Making results tables

Creating plots

Do all plots from gmr

Plotting data used and model fits

Plotting Biological parameters

Plotting Fisheries parameters

Plotting Demographic parameters

Plotting Model residuals

Plotting Stock Status

Terminals

Plotting options and ggplot utilities