From cd24b73d102997dc903dc477e2077614b0da39e8 Mon Sep 17 00:00:00 2001
From: Mauricio Zambrano-Bigiarini <hzambran@users.noreply.github.com>
Date: Tue, 6 Nov 2012 13:02:45 +0000
Subject: [PATCH] hydroPSO.Rd: improved documentation. hydroPSO.R: revised
regrouping (still ongoing)
---
DESCRIPTION | 4 ++--
R/PSO_v2012.R | 56 ++++++++++++++++++++++++-------------------------
man/hydroPSO.Rd | 8 +++----
3 files changed, 33 insertions(+), 35 deletions(-)
diff --git a/DESCRIPTION b/DESCRIPTION
index 5b25060..969e8f1 100755
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,8 +1,8 @@
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.
diff --git a/R/PSO_v2012.R b/R/PSO_v2012.R
index ce08141..7521a52 100755
--- a/R/PSO_v2012.R
+++ b/R/PSO_v2012.R
@@ -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") {
diff --git a/man/hydroPSO.Rd b/man/hydroPSO.Rd
index 0fa0b58..67d923a 100755
--- a/man/hydroPSO.Rd
+++ b/man/hydroPSO.Rd
@@ -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}
--
GitLab