R/plots.load.R

In cugliari/enercast: Electrical energy forecast tools

plot.load.global <- function(yt, dataux = NULL, ...){
    if(is.null(dataux)){
        plot(yt, type = 'l',ylab='Load',xlab='Time',...)

    }
    if(!is.null(dataux)){
        names(dataux)[1] <- 'year'
        aux1 <- by(dataux, dataux$year, nrow)
        aux2 <- cumsum(aux1)-(aux1/2)
        
        plot(yt,type='l',ylab='Load',xlab='Time',axes=FALSE,...);box()

        axis(1,at=aux2,labels=names(aux1),tick=FALSE)
        axis(1,at=c(0,cumsum(aux1)),labels=FALSE,tick=TRUE)
        axis(2)      
    }

}

plot.load.wday <- function(data,...){
    auxwday <- factor(data$wday,levels=c('Mon','Tue','Wed','Thu','Fri','Sat','Sun'),labels=c('Mon','Tue','Wed','Thu','Fri','Sat','Sun'),ordered=TRUE)
    auxsday <- factor(data$spec.day,labels=c('regular','special'),ordered=TRUE)
    days <- unique(auxwday)
    mean.d <- NULL
    for (d in days){
        DAT <- subset(data[(auxsday=='regular' & auxwday==d),])
        mean.d <- rbind(mean.d,as.vector(by(DAT$load,DAT$hour,mean, na.rm=TRUE)))
    }
    row.names(mean.d) <- days
    plot(data$load,type='n',xlim=c(1,ncol(mean.d)),ylim=c(min(mean.d),max(mean.d)),ylab='Load',xlab='Time',main='Mean Daily Load')
    aux <- seq(1,ncol(mean.d),by=ncol(mean.d)/length(days))
    for (d in 1:length(days)){
        lines(mean.d[d,],col=d,lwd=2)
        mtext(row.names(mean.d)[d],col=d,cex=0.7, side=3, line=0.5, at=aux[d])
    }
}



plot.load.month <- function(data,...){
    auxmonth <- factor(data$month,labels=c('Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'),ordered=TRUE)
    auxsday <- factor(data$spec.day,labels=c('regular','special'),ordered=TRUE)
    months <- unique(auxmonth)
    mean.m <- NULL
    for (m in months){
        DAT <- subset(data[(auxsday=='regular' & auxmonth==m),])
        mean.m <- rbind(mean.m,as.vector(by(DAT$load,DAT$hour,mean, na.rm=TRUE)))
    }

    row.names(mean.m) <- months
    
    plot(data$load,type='n',xlim=c(1,ncol(mean.m)),ylim=c(min(mean.m),max(mean.m)),ylab='Load',xlab='Time',main='Mean Monthly Load')
    aux <- seq(min(mean.m),max(mean.m),by=(max(mean.m)-min(mean.m))/length(months))
    aux <- seq(1,ncol(mean.m),by=ncol(mean.m)/length(months))
    for (m in 1:length(months)){
        lines(mean.m[m,],col=m,lwd=2)
        mtext(row.names(mean.m)[m],col=m,cex=0.7, side=3, line=0.5, at=aux[m])
    }
}



plot.load.corr <- function(yt,data=NULL,nw=3,...){
  if(is.null(data)){
    s1=24
    s2=168
  } else{
    frec<-apply(data[,c('wday','hour')],2,function(x)length(unique(x)))
    s1<-frec[names(frec)=='hour']
    s2<-prod(frec)
  }
  lag.max=s2*nw
  par(las=1)
  
  layout(1:3)

  # ACF11
  acf(yt,lag.max=s2*nw,axes=FALSE);box()
  axis(2,seq(-1,1,0.2))
  axis(1,seq(0,by=s2,length=nw+1),labels=c(NA,paste('week',seq(3))))
#  par(ask=TRUE,las=1)

  # ACF 2
  acf(diff(yt,1),lag.max=s2*nw,axes=FALSE);box()
  axis(2,seq(-1,1,0.2))
  axis(1,seq(0,by=s2,length=nw+1),labels=c(NA,paste('week',seq(3))))
#  par(ask=TRUE,las=1)

  # ACF 3
  acf(diff(diff(yt),s1),lag.max=s2*nw,axes=FALSE);box()
  axis(2,seq(-1,1,0.2))
  axis(1,seq(0,by=s2,length=nw+1),labels=c(NA,paste('week',seq(3))))
}


plot.temp <- function(data, group, ...){
  if (missing(group)) group <- 1
  rf <- colorRampPalette(rev(RColorBrewer::brewer.pal(11,'Spectral')))
  hexbin::hexbinplot(data$load ~ data$temp | group, 
                     colramp = rf, xlab = "temperature", ylab = "load",
                     colorkey = FALSE) #, aspect=1)
}