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plot.segmented<-function (x, term, add = FALSE, res = FALSE, conf.level = 0,
interc=TRUE, link = TRUE, res.col = grey(.15, alpha = .4), rev.sgn = FALSE, const = NULL,
shade=FALSE, rug=!add, dens.rug=FALSE, dens.col = grey(0.8),
transf=I, isV=FALSE, is=FALSE, var.diff=FALSE, p.df="p", .vcov=NULL, .coef=NULL, prev.trend=FALSE,
smoos=NULL, hide.zeros=FALSE, leg="topleft", psi.lines=FALSE, ...){
#put leg=NA if you do not want the legend..
#funzione plot.segmented che consente di disegnare anche i pointwise CI
f.U<-function(nomiU, term=NULL){
#trasforma i nomi dei coeff U (o V) nei nomi delle variabili corrispondenti
#and if 'term' is provided (i.e. it differs from NULL) the index of nomiU matching term are returned
k<-length(nomiU)
nomiUsenzaU<-strsplit(nomiU, "\\.")
nomiU.ok<-vector(length=k)
for(i in 1:k){
nomi.i<-nomiUsenzaU[[i]][-1]
if(length(nomi.i)>1) nomi.i<-paste(nomi.i,collapse=".")
nomiU.ok[i]<-nomi.i
}
if(!is.null(term)) nomiU.ok<-(1:k)[nomiU.ok%in%term]
return(nomiU.ok)
}
#--------------
enl.range<-function(..., enlarge=TRUE){
#modifica il min dei valori in ...
r<-range(...)
if(enlarge) r[1]<-if(sign(r[1])>0) r[1]*.9 else r[1]*1.1
r
}
#--------------
#se l'oggetto e' segmented.Arima il nome dell'eventuale interc va sostituito..
#if((all(class(x)==c("segmented", "Arima")))) names(x$coef)<-gsub("intercept", "(Intercept)", names(coef(x)))
if(all(c("segmented", "Arima") %in% class(x))) names(x$coef)<-gsub("intercept", "(Intercept)", names(x$coef))
covv <- if(is.null(.vcov)) vcov(x, is=is, var.diff=var.diff) else .vcov
if(!is.null(.coef)) {
estcoef<- .coef
} else {
estcoef <- coef(x)
if(is.null(estcoef)) estcoef <- x$coef
if(is.null(estcoef)) stop("No coeffs in the fit? Please use '.coef'")
}
if(length(estcoef)==0) stop("No coefficient in the object fit?")
#browser()
if(!all(dim(covv)==c(length(estcoef), length(estcoef)))) stop("dimension of cov matrix and estimated coeffs do not match", call. = FALSE)
#--------------
linkinv <- !link
if (inherits(x, what = "glm", which = FALSE) && linkinv && !is.null(x$offset) && res) stop("residuals with offset on the response scale?")
if(conf.level< 0 || conf.level>.9999) stop("meaningless 'conf.level'")
if ((inherits(x, what = "glm", which = FALSE) && linkinv) || res) {
if(!(identical(transf, I) || identical(transf, "I"))) {transf<-I; warning("'transf' set to I with 'res=TRUE' and/or 'link=FALSE'.")}
}
if(missing(term)) {
if (length(x$nameUV$Z) > 1) {
stop("please, specify `term'")
} else {
term <- x$nameUV$Z
}
} else {
#browser()
if(is.numeric(term)) term <- x$nameUV$Z[term]
#if(!is.character(term)) stop("please specify correctly 'term' ")
#term<- deparse(substitute(term))
#if(dterm %in% x$nameUV$Z) term<-dterm
if (!isTRUE(all(term %in% x$nameUV$Z))) stop(paste("Unknown term. It should be numeric or one of: ", paste(" '", x$nameUV$Z, "' ", sep="", collapse="")))
}
if(length(term)>1){
opz<-list(...)
cols<- if(!is.null(opz$col)) opz$col else 1:length(term)+1
cols <- rep(cols, l=length(term))
res.cols<- rep(res.col, l=length(term))
lwds<- if("lwd"%in% names(opz)) opz$lwd else 2
lwds<- rep(lwds, l=length(term))
ltys<- if("lty"%in% names(opz)) opz$lty else 1
ltys<- rep(ltys, l=length(term))
cexs<- if("cex"%in% names(opz)) opz$cex else .75
cexs<- rep(cexs, l=length(term))
pchs<- if("pch"%in% names(opz)) opz$pch else 19
pchs<- rep(pchs, l=length(term))
if(!is.null(opz$ylim)) {
Ylim <- opz$ylim
} else {
if(inherits(x, "glm")){
if(link){
Ylim <- if(!res) range(x$linear.predictors) else range(x$linear.predictors+x$residuals)
} else {
Ylim <- if(!res) range(x$fitted.values) else range(x$fitted.values+ residuals(x, "response"))
}
} else {
Ylim <- if(!res) range(x$fitted.values) else range(x$fitted.values+x$residuals)
}
}
Ylab <- if(!is.null(opz$ylab)) opz$ylab else paste(formula(x))[2]
idTerm <- if(is.numeric(term)) term else match(term, x$nameUV$Z)
nomeX <- intersect(strsplit(x$nameUV$Z,":")[[idTerm[1]]], unlist(strsplit(x$nameUV$Z,":")[idTerm[-1]]))
Xlab <- if(!is.null(opz$xlab)) opz$xlab else nomeX
Xlim<- if(!is.null(opz$xlim)) opz$xlim else range(x$model[,nomeX])
int.all<-rep(NA, length(term))
plot.segmented(x, term[1], add = add, res = res, conf.level = conf.level,
interc=interc, link = link, res.col = res.cols[1], rev.sgn = rev.sgn, const = const,
shade=shade, rug=FALSE, dens.rug=FALSE, dens.col = grey(0.8),
transf=I, isV=FALSE, is=FALSE, var.diff=FALSE, p.df="p", .vcov=NULL, .coef=NULL, prev.trend=FALSE,
smoos=NULL, hide.zeros=TRUE, col=cols[1], ylim=Ylim, xlim=Xlim, ylab=Ylab,xlab=Xlab,
lty=ltys[1],pch=pchs[1],lwd=lwds[1],cex=cexs[1])
Term<- if(is.numeric(term[1])) x$nameUV$Z[term[1]] else term[1]
int.all[1]<-interc.gr<- strsplit(Term, ":")[[1]][2]
points.segmented(x, term[1], col=cols[1], const=estcoef[interc.gr], v=psi.lines, pch=20, link=link)
for(j in 2:length(term)){
plot.segmented(x, term[j], add = TRUE, res = res, conf.level = conf.level,
interc=interc, link = link, res.col = res.cols[j], rev.sgn = rev.sgn, const = const,
shade=shade, rug=FALSE, dens.rug=FALSE, dens.col = grey(0.8),
transf=I, isV=FALSE, is=FALSE, var.diff=FALSE, p.df="p", .vcov=NULL, .coef=NULL, prev.trend=FALSE,
smoos=NULL, hide.zeros=TRUE,col=cols[j],
lty=ltys[j],pch=pchs[j],lwd=lwds[j],cex=cexs[j])
Term<- if(is.numeric(term[j])) x$nameUV$Z[term[j]] else term[j]
int.all[j]<-interc.gr<- strsplit(Term, ":")[[1]][2]
points.segmented(x, term[j], col=cols[j], const = estcoef[interc.gr], v=psi.lines, pch=20, link=link)
}
if(!is.na(leg)) {
legend(leg, int.all, col=cols, lty=1, lwd=1.5, bty="n")
}
} else {
if(is.null(const)){
interc.gr<- strsplit(term, ":")[[1]][2]
const<- estcoef[interc.gr]
if(is.na(const)) const<-0
}
if(!is.numeric(const)) stop(" 'const' should be NULL (default) or numeric")
opz <- list(...)
col.shade<-if(!is.null(opz$col.shade)) adjustcolor(opz$col.shade, .15) else adjustcolor("grey", .4)
cols<- if("col"%in% names(opz)) opz$col else 2
lwds<- if("lwd"%in% names(opz)) opz$lwd else 2
ltys<- if("lty"%in% names(opz)) opz$lty else 1
cexs<- if("cex"%in% names(opz)) opz$cex else .75
pchs<- if("pch"%in% names(opz)) opz$pch else 19
ylabs<- if("ylab"%in% names(opz)) opz$ylab else paste("Effect of ", term, sep = " ")
xlabs<- if("xlab"%in% names(opz)) opz$xlab else term
a <- intercept(x, term, digits=20, .vcov=covv, .coef=estcoef)[[1]][, "Est."]
#Poiche' intercept() restituisce quantita' che includono sempre l'intercetta del modello, questa va eliminata se interc=FALSE
idInterc<-grep("ntercept",names(estcoef))
if(!interc && length(idInterc)==1) a<- a-estcoef[idInterc]
b <- slope(x, term, digits=20, .coef=estcoef, .vcov=covv)[[1]][, "Est."]
#browser()
id <- f.U(rownames(x$psi), term)
est.psi <- x$indexU[[term]]
val <- sort(c(est.psi, x$rangeZ[, term]))
#vettorializza i cols, lwds, ltys
cols<-rep(cols, l=length(est.psi)+1)
lwds<-rep(lwds, l=length(est.psi)+1)
ltys<-rep(ltys, l=length(est.psi)+1)
#---------aggiunta per gli IC
rangeCI<-NULL
vall<-sort(c(seq(min(val), max(val), l=100), est.psi, est.psi+1e-5))
#ciValues<-predict.segmented(x, newdata=vall, se.fit=TRUE, type=tipo, level=conf.level)
vall.list<-list(vall)
names(vall.list)<-term
if(conf.level>0) {
k.alpha<- if(all(c("segmented","lm") %in% class(x))) abs(qt((1-conf.level)/2, x$df.residual)) else abs(qnorm((1-conf.level)/2))
ciValues<-broken.line(x, vall.list, link=link, interc=interc, se.fit=TRUE, isV=isV, is=is, var.diff=var.diff,
p.df=p.df, .vcov=covv, .coef=estcoef) #se gli passi covv, gli argomenti is e var.diff NON servono perche li ignora..
ciValues<-cbind(ciValues$fit, ciValues$fit- k.alpha*ciValues$se.fit, ciValues$fit + k.alpha*ciValues$se.fit) + const
#---> transf...
ciValues<-apply(ciValues, 2, transf)
rangeCI<-range(ciValues)
#ciValues e' una matrice di length(val)x3. Le 3 colonne: stime, inf, sup
#polygon(c(vall, rev(vall)), c(ciValues[,2],rev(ciValues[,3])), col = "gray", border=NA)
}
#---------
a.ok <- c(a[1], a)
b.ok <- c(b[1], b)
y.val <- a.ok + b.ok * val + const
a.ok1 <- c(a, a[length(a)])
b.ok1 <- c(b, b[length(b)])
y.val <- y.val1 <- a.ok1 + b.ok1 * val + const
s <- 1:(length(val) - 1)
if(rev.sgn) val <- -val
m <- cbind(val[s], y.val1[s], val[s + 1], y.val[s + 1])
#xvalues <- if(all(c("segmented", "Arima") %in% class(x))) x$Z[,1] else model.matrix(x)[,term] #x$model[, term]
#browser()
if(res || dens.rug || rug){
if(inherits(x,"Arima")){
xvalues <-x$Z[,1]
} else {
M <- model.matrix.segmented(x)
#il 18/4/24 mi sono accorto che con ogg ottenuti da segmented.* con leftmost pendenza nulla non funzionava
#perche' model.matrix.segmented non restituiva la variabile (non inserita nel modello (g)lm di partenza..)
if(!term %in% colnames(M) && term%in%names(x$model)) M<-cbind(M, x$model[,term,drop=FALSE] )
if(term %in% colnames(M)) {
xvalues <- M[,term]
} else {
id.segTerm<-which(sapply(names(x$nameUV$formulaSeg), function(.x) startsWith(term,.x)))
xvalues <- model.matrix(x$nameUV$formulaSeg[[id.segTerm]], data=x$model)[,term]
}
}
if(rev.sgn) xvalues <- -xvalues
}
#browser()
if(res){
new.d<-data.frame(ifelse(rep(rev.sgn, length(xvalues)),-xvalues, xvalues))
names(new.d)<-term
fit0 <- broken.line(x, new.d, link = link, interc=interc, se.fit=FALSE, .vcov=covv, .coef=estcoef)$fit
}
#-------------------------------------------------------------------------------
if (inherits(x, what = "glm", which = FALSE) && linkinv) { #se GLM con link=FALSE (ovvero linkinv=TRUE)
fit <- if (res)
#predict.segmented(x, ifelse(rep(rev.sgn, length(xvalues)),-xvalues,xvalues), type=tipo) + resid(x, "response") + const
#broken.line(x, term, gap = show.gap, link = link) + resid(x, "response") + const
fit0 + resid(x, "response") + const
else x$family$linkinv(c(y.val, y.val1))
xout <- sort(c(seq(val[1], val[length(val)], l = 50), val[-c(1, length(val))],
pmax(val[-c(1, length(val))]*1.0001, val[-c(1, length(val))]*.9999)))
l <- suppressWarnings(approx(as.vector(m[, c(1, 3)]), as.vector(m[, c(2, 4)]), xout = xout))
val[length(val)]<- if(rev.sgn) min(l$x) else max(l$x) #aggiunto 11/09/17.. if else il 9/3/21
id.group <- cut(l$x, val, labels=FALSE, include.lowest =TRUE, right=TRUE)
#xout <- sort(c(seq(val[1], val[length(val)], l = 150), val[-c(1, length(val))],val[-c(1, length(val))]*1.0001))
#l <- suppressWarnings(approx(as.vector(m[, c(1, 3)]), as.vector(m[, c(2, 4)]), xout = xout))
#val[length(val)]<-max(l$x) #aggiunto 11/09/17
#id.group <- cut(l$x, val, FALSE, TRUE)
yhat <- l$y
xhat <- l$x
m[, c(2, 4)] <- x$family$linkinv(m[, c(2, 4)])
if (!add) {
plot(as.vector(m[, c(1, 3)]), as.vector(m[, c(2, 4)]),
type = "n", xlab = xlabs, ylab = ylabs,
main = opz$main, sub = opz$sub,
cex.axis = opz$cex.axis,
cex.lab = opz$cex.lab,
xlim = opz$xlim,
ylim = if(is.null(opz$ylim)) enl.range(fit, rangeCI, enlarge=dens.rug) else opz$ylim
)
if(dens.rug){
density <- density(xvalues)
# the height of the densityity curve
max.density <- max(density$y)
# Get the boundaries of the plot to
# put the density polygon at the x-line
plot_coordinates <- par("usr")
# get the "length" and range of the y-axis
y.scale <- plot_coordinates[4] - plot_coordinates[3]
# transform the y-coordinates of the density
# to the lower 10% of the plotting panel
density$y <- (0.1 * y.scale / max.density) * density$y + plot_coordinates[3]
## plot the polygon
polygon( density$x , density$y , border = FALSE , col = dens.col)
box()
}
if(rug) {
#usare rug()?
segments(xvalues, rep(par()$usr[3],length(xvalues)), xvalues,
rep(par()$usr[3],length(xvalues))+ abs(diff(par()$usr[3:4]))/80)
}
}
if (res) {
if(hide.zeros) {
fit <- fit[abs(xvalues)>1e-8]
xvalues <- xvalues[abs(xvalues)>1e-8]
}
if(is.null(smoos)) { smoos <- if(length(xvalues)>10000) TRUE else FALSE }
if(smoos){
smoothScatter(xvalues, fit, add=TRUE, nrpoints = 0, colramp= colorRampPalette(c("white", res.col)))
} else {
points(xvalues, fit, cex = cexs, pch = pchs, col = res.col)
}
}
if(conf.level>0){
if(rev.sgn) vall<- -vall
if(shade) {
polygon(c(vall, rev(vall)), c(ciValues[,2],rev(ciValues[,3])),
col = col.shade, border=NA)
} else {
#browser()
id.group1 <- cut(vall, val, labels=FALSE, include.lowest =TRUE, right=TRUE) #serve per gli IC..
for (i in 1:max(id.group1)) matlines(vall[id.group1 == i], ciValues[id.group1 == i,-1], type="l", lty=2, col=cols[i])
#matlines(vall, ciValues[,-1], type="l", lty=2, col=cols)
}
}
yhat <- x$family$linkinv(yhat)
if (length(cols) == 1) cols <- rep(cols, max(id.group))
if (length(lwds) == 1) lwds <- rep(lwds, max(id.group))
if (length(ltys) == 1) ltys <- rep(ltys, max(id.group))
for (i in 1:max(id.group)) {
lines(xhat[id.group == i], yhat[id.group == i], col = cols[i],
lwd = lwds[i], lty = ltys[i])
if(prev.trend) lines(xhat[xhat>est.psi[i]], x$family$linkinv((a[i]+b[i]*xhat)[xhat>est.psi[i]]), col=cols[i], lwd = lwds[i]*.65, lty = 2)
}
#-------------------------------------------------------------------------------
} else { #se LM o "GLM con link=TRUE (ovvero linkinv=FALSE)"
##---> transf!!!
y.val<- do.call(transf, list(y.val))
y.val1<-do.call(transf, list(y.val1))
r <- cbind(val, y.val)
r1 <- cbind(val, y.val1)
rr <- rbind(r, r1)
fit <- c(y.val, y.val1)
if (res) {
ress <- if (inherits(x, what = "glm", which = FALSE))
residuals(x, "working") #* sqrt(x$weights) mgcv::gam() usa " ..*sqrt(x$weights)/mean(sqrt(x$weights))"
else resid(x)
#if(!is.null(x$offset)) ress<- ress - x$offset
#fit <- broken.line(x, term, gap = show.gap, link = link, interc = TRUE) + ress + const
#fit <- predict.segmented(x, ifelse(rep(rev.sgn, length(xvalues)),-xvalues,xvalues), type=tipo) + ress + const
fit <- fit0 + ress + const
}
if (!add)
plot(rr, type = "n", xlab = xlabs, ylab = ylabs,
main = opz$main, sub = opz$sub,
xlim = opz$xlim,
cex.axis = opz$cex.axis,
cex.lab = opz$cex.lab,
#ylim = if(is.null(opz$ylim)) enl.range(fit, rangeCI, enlarge=dens.rug) else opz$ylim)
ylim = if(is.null(opz$ylim)) enl.range(fit, rangeCI, do.call(transf, list(m[, c(2,4)])), enlarge=dens.rug) else opz$ylim)
if(dens.rug){
density <- density(xvalues)
# the height of the densityity curve
max.density <- max(density$y)
# Get the boundaries of the plot to
# put the density polygon at the x-line
plot_coordinates <- par("usr")
# get the "length" and range of the y-axis
y.scale <- plot_coordinates[4] - plot_coordinates[3]
# transform the y-coordinates of the density
# to the lower 10% of the plotting panel
density$y <- (0.1 * y.scale / max.density) * density$y + plot_coordinates[3]
## plot the polygon
polygon(density$x , density$y , border = F , col = dens.col)
box()
}
if(rug) {segments(xvalues, rep(par()$usr[3],length(xvalues)), xvalues,
rep(par()$usr[3],length(xvalues))+ abs(diff(par()$usr[3:4]))/80)}
if (res) {
if(hide.zeros) {
fit <- fit[abs(xvalues)>1e-8]
xvalues <- xvalues[abs(xvalues)>1e-8]
}
if(is.null(smoos)) { smoos <- if(length(xvalues)>10000) TRUE else FALSE }
if(smoos){
smoothScatter(xvalues, fit, add=TRUE, nrpoints = 0, colramp= colorRampPalette(c("white", res.col)))
} else {
#browser()
points(xvalues, fit, cex = cexs, pch = pchs, col = res.col)
}
}
if(rev.sgn) vall<- -vall
if(conf.level>0) {
if(shade) {
polygon(c(vall, rev(vall)), c(ciValues[,2],rev(ciValues[,3])), col = col.shade, border=NA)
} else {
#infittire vall, soprattutto in prossimita' dei psi?
id.group1 <- cut(vall, val, labels=FALSE, include.lowest =TRUE, right=TRUE) #serve per gli IC..
for (i in 1:max(id.group1)) matlines(vall[id.group1 == i], ciValues[id.group1 == i,-1], type="l", lty=2, col=cols[i])
#VECCHIO: matlines(vall, ciValues[,-1], type="l", lty=2, col=cols)
}
}
#aggiunto 06/2019 perche' sotto disegnava linee (e non curve)
# segments(m[, 1], do.call(transf, list(m[, 2])), m[, 3], do.call(transf, list(m[, 4])),
# col = cols, lwd = lwds, lty = ltys)
#---
# modificato 8/2/21.. adesso le linee si uniscono sempre.
#.. con valori tipo 2010 (date), non si uniscono..
#comunque vall ha piu' valori di xout, quindi e' sufficiente assegnare xout<-vall (01/10/2021)
#xout <- sort(c(seq(val[1], val[length(val)], l = 50), val[-c(1, length(val))],
# pmax(val[-c(1, length(val))]*1.0001, val[-c(1, length(val))]*.9999)))
#if(rev.sgn) vall<- -vall
xout <- vall
l <- suppressWarnings(approx(as.vector(m[, c(1, 3)]), as.vector(m[, c(2, 4)]), xout = xout))
val[length(val)]<- if(rev.sgn) min(l$x) else max(l$x) #aggiunto 11/09/17; messo il if .. else 9/3/21
#id.group <- cut(l$x, val, labels=FALSE, include.lowest =TRUE, right=TRUE)
id.group <- cut(vall, val, labels=FALSE, include.lowest =TRUE, right=TRUE) #e' come id.group1
#---
xhat <- l$x
yhat <- l$y
yhat <- do.call(transf, list(yhat)) #transf(yhat)
if (length(cols) == 1) cols <- rep(cols, max(id.group))
if (length(lwds) == 1) lwds <- rep(lwds, max(id.group))
if (length(ltys) == 1) ltys <- rep(ltys, max(id.group))
for (i in 1:max(id.group)) {
lines(xhat[id.group == i], yhat[id.group == i], col = cols[i], lwd = lwds[i], lty = ltys[i])
#if(conf.level>0 && !shade) matlines(vall[id.group1 == i], ciValues[id.group1 == i,-1], type="l", lty=2, col=cols[i])
if(prev.trend) lines(xhat[xhat>est.psi[i]], (a[i]+b[i]*xhat)[xhat>est.psi[i]], col=cols[i], lwd = lwds[i]*.65, lty = 2)
}
# if(prev.trend){
# for(i in 1:(length(est.psi)+1)) lines(xhat[xhat>est.psi[i]], a[i]+b[i]*xhat)[xhat>est.psi[i]], col=cols[i], lwd = lwds[i]*.7, lty = 2)
# }
}
invisible(NULL)
}
}
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