# Inverse Problem Solver! This sotfware will minimize a cost function and estimate a set of parameters using a Inverse Problem Solver. ```r invprob(parm_init) ``` ## Arguments - `parm_init`: Set of values to be considered as initial parameters for the Inverse Problem solution ## Returns A vector with the quadratic residue calculated, the parameters estimated and the number of function call needed to solve the inverse problem. ## Examples ```r # # Configure the name of the folder where each file with the parameter to be changed. # If the folder is 'wd' then it will not be changed. # You can change it to another location where your parameter files are. auxi <- system.file(package = "gripp") folder_name <- c(auxi,auxi) # # Configure the name of each file to be changed in the Direct Problem Solver. file_name <- c('f1.R','f1.R') # # Configure the name of each parameter to be changed. parm_name <- c('A','B') # # Configure alternative method using line number to enter each parameter # When line_number is zero, then the input method uses keywords. line_number <-c(0,0) # # Configure each parameter type, where: # 1 means a numeric variable informed as a string, such as parm <- "1.38" # 2 means a numeric vector informed as a string of numbers separated with a space character. # For example, parm <- "1.25 3.4". You must tell which one will be the variable considered. parm_type <- c(1,1) # # Informe the position of the variable to be considered in the problem in the vector. # If the parameter is a numeric variable, then its position is zero. parm_vector <- c(0,0) # # Configure the smallest value for each parameter parm_min <- c(0,0) # # Configure the larger value for each parameter parm_max <- c(2,5) # # Configure the name of the folder where the command must be called. # If the folder is 'wd' then it will not be changed. # You can change it to another location where your parameter files are. command_folder <- system.file(package = "gripp") # # This variable means that the Direct Problem is solved using R or outside # if this is FALSE, the results are to be read from a file. # When it is TRUE, results will be passed inside R using the variable "result" isitR <- TRUE # # Configure the command to be used to call the Direct Problem Solver. command <- 'f1.R' # # Configure a string to be used to attrib values in the Direct Problem file. attrib_str <- '<-' # # Configure the name of the file with the results obtained by the Direct Problem. # It must be a single column of values. # The results are changed at each run by the Direct Problem Solver. result <- 'result.dat' # # Configure the name of the folder where the results can be found after each run. # If the folder is 'wd' then it will not be changed. # You can change it to another location where your result file is. result_folder <- tempdir() # # Configure the name of the file to be used as a target by the cost function. # The file was built using parm <- c(1,3). # It is also a single column of values. target <- 'alvo.dat' # # Configure the name of the folder where the target file can be found. # If the folder is 'wd' then it will not be changed. # You can change it to another location where your target file is. target_folder <- auxi # # Configure the Inverse Problem Solver to be used: # 1) GRIPP can use the solver 'GenSA'. # Then configure the maximum number of function evaluation for the Inverse Problem Solution # using control <- list(max.time=60) # # 2) GRIPP can use the solver 'GA' # The configure the maximum number of function evaluation for the Inverse Problem Solution # control <- list(popSize = 50, maxiter = 1000, run = 100) solver <- 'GenSA' control <- list(max.time=1) # Configure the initial value for each parameter parm <- c(1.5,4) out<-invprob(parm) out ```

invprob function