Skip to content
Snippets Groups Projects
Commit cd24b73d authored by Mauricio Zambrano-Bigiarini's avatar Mauricio Zambrano-Bigiarini
Browse files

hydroPSO.Rd: improved documentation. hydroPSO.R: revised regrouping (still ongoing)

parent 4e91522c
No related branches found
No related tags found
No related merge requests found
Hide whitespace changes
Inline Side-by-side
DESCRIPTION
+ 2
− 2
View file @ cd24b73d
Package: hydroPSO
Type: Package
Title: Model-Independent Particle Swarm Optimisation for Environmental Models
Version: 0.1-58-17
Date: 2012-10-31
Version: 0.1-58-19
Date: 2012-11-06
Authors@R: c(person("Mauricio", "Zambrano-Bigiarini", email="mzb.devel@gmail.com", role=c("aut","cre")), person("Rodrigo", "Rojas", email="Rodrigo.RojasMujica@gmail.com", role=c("ctb")) )
Maintainer: Mauricio Zambrano-Bigiarini <mzb.devel@gmail.com>
Description: This package implements a state-of-the-art version of the Particle Swarm Optimisation (PSO) algorithm (SPSO-2011 and SPSO-2007 capable), with a special focus on the calibration of environmental models. hydroPSO is model-independent, allowing the user to easily interface any model code with the calibration engine (PSO). It includes a series of controlling options and PSO variants to fine-tune the performance of the calibration engine to different calibration problems. An advanced sensitivity analysis function together with user-friendly plotting summaries facilitate the interpretation and assessment of the calibration results. Bugs reports/comments/questions are very welcomed.
......
R/PSO_v2012.R
+ 27
− 29
View file @ cd24b73d
......@@ -1115,6 +1115,9 @@ ComputeSwarmRadiusAndDiameter <- function(x, gbest, Lmax, MinMax, pbest.fit) {
# local best
################################################################################
RegroupingSwarm <- function(x,
xini.type,
v,
vini.type,
gbest,
x.Range,
Lmax,
......@@ -1132,25 +1135,6 @@ RegroupingSwarm <- function(x,
#rf <- 6/(5*RG.thr) # Evers & Ghalia
#rf <- (1/RG.thr)/2 # MZB
## # Removing possible attributes
## gbest <- as.numeric( gbest )
## x.min.rng <- as.numeric( x.Range[ ,1] )
## x.max.rng <- as.numeric( x.Range[ ,2] )
##
## xmin <- x.min.rng + rf*abs(x.min.rng-gbest)
## xmax <- x.max.rng - rf*abs(x.max.rng-gbest)
## x.MinMax <- cbind(xmin, xmax)
##
## x <- InitializateX(npart, x.MinMax, x.ini.type="lhs")
## #x <- x+gbest
##
## # Maximum length of the parameter space in each dimension
## Lmax <- x.max.rng - x.min.rng
## Lnew <- Lmax
## # name of each parameter
## param.IDs <- row.names(x.Range)
# name of each parameter
param.IDs <- row.names(x.Range)
......@@ -1184,16 +1168,23 @@ RegroupingSwarm <- function(x,
# If needed, Clamping the particle positions to the minimum value
x[part, ] <- pmax(x[part,], x.min.rng)
} # FOR end
# Defining the new boundaries
xmin <- gbest - 0.5*Lnew
xmax <- gbest + 0.5*Lnew
xMinMax <- cbind(xmin, xmax)
v <- InitializateV(npart=npart, x.MinMax=xMinMax, v.ini.type=vini.type, Xini=x)
# Relative change achieved in each dimension
rel.change <- (Lnew-Lmax)/Lmax
names(rel.change) <- param.IDs
out <- list(2)
out <- list(3)
out[[1]] <- x
out[[2]] <- Lnew
names(out) <- c("X", "Lnew")
out[[2]] <- v
out[[3]] <- Lnew
names(out) <- c("X", "V", "Lnew")
return(out)
......@@ -2612,7 +2603,7 @@ hydroPSO <- function(
" Gbest:", formatC( gbest.fit, format="E", digits=digits, flag=" "),
" Gbest_rate:", format( round(gbest.fit.rate*100, 2), width=6, nsmall=2, justify="left"), "%",
" Iter_best_fit:", formatC(pbest.fit.iter, format="E", digits=digits, flag=" "),
" nSwarm_Radius:", formatC(NormSwarmRadius, format="E", digits=digits, flag=" "),
" nSwarm_Radius:", formatC(NormSwarmRadius, format="E", digits=2, flag=" "),
" |g-mean(p)|/mean(p):", format( round(GPbest.fit.rate*100, 2), width=6, nsmall=2, justify="left"), "%" )
##########################################################################
......@@ -2639,14 +2630,20 @@ hydroPSO <- function(
if (verbose) message("[ Re-grouping particles in the swarm (iter: ", iter, ") ... ]")
tmp <- RegroupingSwarm(x=X,
gbest= X.best.part[gbest.pos, ],
xini.type=Xini.type,
v=V,
vini.type=Vini.type,
gbest= X.best.part[gbest.pos, ],
x.Range=X.Boundaries,
#x.Range=X.Boundaries.current,
Lmax=Lmax,
RG.thr=RG.thr,
RG.r=RG.r)
X <- tmp[["X"]]
X <- tmp[["X"]]
V <- tmp[["V"]]
Lmax <- tmp[["Lnew"]]
# if (topology %in% c("gbest", "random") ) {
# X[gbest.pos,] <- x.bak
......@@ -2661,9 +2658,6 @@ hydroPSO <- function(
gbest.pos <- gbest.pos.bak
} # IF end
# V <- InitializateV(npart=npart, x.MinMax=X.Boundaries,
# v.ini.type=Vini.type, Xini=X)
pbest.fit <- rep(fn.worst.value, npart)
pbest.fit.iter <- fn.worst.value
pbest.fit.iter.prior <- fn.worst.value*2
......@@ -2672,6 +2666,10 @@ hydroPSO <- function(
gbest.fit.iter <- rep(gbest.fit, maxit)
gbest.fit.prior <- gbest.fit
gbest.pos <- 1
gbest.fit <- gbest.fit.bak
gbest.pos <- gbest.pos.bak
X[gbest.pos,] <- x.bak
GPbest.fit.rate <- +Inf
if (MinMax=="max") {
......
man/hydroPSO.Rd
+ 4
− 4
View file @ cd24b73d
......@@ -135,7 +135,7 @@ numeric, absolute convergence tolerance. The algorithm stops if \code{gbest <= a
By default it is set to \code{-Inf} or \code{+Inf} for minimisation or maximisation problems, respectively
}
\item{reltol}{
numeric, relative convergence tolerance. The algorithm stops if the absolute difference between the best \sQuote{personal best} in the current iteration and the best \sQuote{personal best} in the previous iteration is lower or equal to \code{reltol}. Defaults to \code{sqrt(.Machine$double.eps)}, typically, about 1e-8\cr
numeric, relative convergence tolerance. The algorithm stops if the absolute difference between the best \sQuote{personal best} in the current iteration and the best \sQuote{personal best} in the previous iteration is less or equal to \code{reltol}. Defaults to \code{sqrt(.Machine$double.eps)}, typically, about 1e-8\cr
If \code{reltol} is set to \code{0}, this stopping criterion is not used
}
\item{Xini.type}{
......@@ -348,9 +348,9 @@ three-element vector containing the number of function evaluations, number of it
\item{convergence}{
integer code where \code{0} indicates that the algorithm terminated by reaching the absolute tolerance, otherwise:
\describe{
\item{\code{1}:}{relative tolerance reached}
\item{\code{2}:}{maximum number of function evaluations reached}
\item{\code{3}:}{maximum number of iterations reached}
\item{1}{relative tolerance reached}
\item{2}{maximum number of function evaluations reached}
\item{3}{maximum number of iterations reached}
}
}
\item{message}{character string giving human-friendly information about \code{convergence}
......
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment