sensitive_stics.RdMake sensitivity analysis on a particular output(s) given STICS input parameter(s) and their intercation if several are given.
sensitive_stics( dir.orig, dir.targ = getwd(), stics, obs_name, Parameters, Vars, method = c("fast99", "sobol"), n = 10 * length(Vars), q = "qunif", Plant = 1, Erase = T, values = rep(1, length(Parameters)), ... )
| dir.orig | Path to the directory from which to copy the simulation files. If
|
|---|---|
| dir.targ | Path to the target directory for evaluation. Created if missing. |
| stics | STICS executable path |
| obs_name | A vector of observation file name(s). It must have the form
|
| Parameters | A list of list of min and max values for each parameters, named after them (see details and example) |
| Vars | Output variables on which the sensitivity is performed |
| method | The sensitivity method to use, see sensitivity package |
| n | Sample size for simulation (must be an even number for |
| q | A vector of quantile function names corresponding to factors
distribution (see |
| Plant | The plant (i.e. Principal or associated) for which the parameters
will be set (only for plant or technical parameters in mixed crop simulations)
Set to |
| Erase | Should the simulations data be erased upon import ? (see details) |
| values | A named list of number of values given to each parameter (will repeat the value found in the DOE
by |
| ... | Further parameters passed to the sensitivity function called (see sensitivity package) |
A list of three :
gg_objects: A list of ggplot objects to plot the sensitivity of each variable to the parameter(s) along the rotation
sensi_objects: A list of the sensitivity analysis output, e.g. a list
of class fast99 for the fast99 method.
DOE: A list of the design of experiment, with parameter values used for each simulation.
The function uses the sensitivity package functions under the hood to
create the DOE (design of experiment) and then to compute the sensitivity index. For
sobol alike methods, the DOE is first computed using the
sensitivity::fast99() function using the q and Parameters (for
q.arg) parameters. The DOE is then splitted in two to fill the X1`` and X2parameters. TheParametersshould take the form of a list of arguments to pass to theqfunction for each parameter, named after the parameter of interest (see example). As the simulations can take a lot of space on disk while augmenting the parameters number, theEraseparameter allow the user to erase each simulation as soon as its data is imported. Thevalues` parameter is used to repeat the input value found in the DOE given to set_param.
It is usefull for plant parameters in intercrops that are still in the temporary parameter file
so they have two values (one for each plant).
stats::Distributions() if you use sensitivity::fast99().
if (FALSE) { library(sticRs) # Example using the fast99 method for a sensitivity analysis on the # "interrang" and "P_densitesem" parameters: sensitive_stics(dir.orig = "0-DATA/dummy/SC_Wheat", dir.targ = "2-Simulations/Sensitivity2", stics = "0-DATA/stics_executable/EquDens_trg/stics.exe", obs_name = "Wheat_N0.obs", Parameters= list(interrang= list(min=0.05, max=0.25), P_densitesem= list(min=140, max=280)), Vars = c("raint", "lai(n)", "masec(n)"), method= "fast99", n= 10, q= "qunif") # Example using the sobol method for a sensitivity analysis on the # "interrang" and "P_densitesem" parameters with different quantile functions: sensitive_stics(dir.orig = "0-DATA/dummy/SC_Wheat", dir.targ = "2-Simulations/Sensitivity2", stics = "0-DATA/stics_executable/EquDens_trg/stics.exe", obs_name = "Wheat_N0.obs", Parameters= list(interrang= list(min=0.05, max=0.25), P_densitesem= list(mean=210, sd=30)), Vars = c("raint", "lai(n)", "masec(n)"), method= "fast99", n= 10, q= c("qunif","qnorm")) }