Nothing
R/Graphics.R
Defines functions Graphics
Documented in Graphics
#' Plots the time series
#
#'@param especie Matrix that contains at row i the bacterial taxa of bacteria i at all time points.
#'@param esperanza Matrix that contains at row i the expected value of the bacterial taxa i at all time points. The bacteria must be placed in the same order than in \code{especie}
#'@param names.especie Vector with the names of the bacteria in the same order that are placed in the \code{especie} matrix.
#'@param Variance Matrix that contains at row i the variance of the bacterial taxa i at all time points. The bacteria must be placed in the same order than in \code{especie}
#'@param Plot.Tipe Character. If \code{Plot.Tipe==Data} the function displays a graphic of the dataset, if \code{Plot.Tipe==DataExpected} the function displays a graphic of the data and the expected values, if \code{Plot.Tipe==All} the function displais a graphic woth the data, the expected values and the variance.If \code{Plot.Tipe==Var} the function returns the boxplot of the variance at each time point and the variance of each bacteria. If \code{Plot.Tipe==OnlyVar} the function returns the boxplots of the variance at each time points.
#'@param Detail Character. If \code{Detail==no} the graphic obtained when \code{Plot.Tipe==DataExpected} and \code{Plot.Tipe==All} will have the same y axis for all the taxa. If \code{Detail==yes} these functions will have different y axis.
#'
#'@return Returns the indicated plots.
#'
#'
#' @examples
#'
#'
#'names.especie=c("Bact1", "Bact2", "Bact3")
#'especie=cbind(c(0.5,0.3,0.2), c(0.6,0.3,0.1),c(0.4,0.1,0.5),c(0.4,0.1,0.5))
#'esperanza=especie[,c(1:3)]+0.1
#'Variance=matrix(c(runif(9,0.001,0.004)), 3,3)
#'
#'Graphics(especie, names.especie, esperanza, Variance,"Data","no")
#'Graphics(especie, names.especie, esperanza, Variance,"DataExpected","no")
#'Graphics(especie, names.especie, esperanza, Variance,"All","no")
#' @export
#'
#'
#'
# CoDaLoMic. Compositional Models to Longitudinal Microbiome Data.
# Copyright (C) 2024 Irene Creus MartÃ
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License version 3 as
# published by the Free Software Foundation.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
Graphics<-function(especie, names.especie, esperanza, Variance,Plot.Tipe,Detail){
if(Plot.Tipe=="Data"){
time=c(1:dim(especie)[2])
time.prep<-as.vector(sapply(time, function (x) rep(x,dim(especie)[1])))
Names<-rep(names.especie, length(time))
especie.prep<-as.vector(especie)
df.graphic1<-data.frame(cbind(especie.prep,time.prep, Names))
df.graphic1$especie.prep=as.numeric(df.graphic1$especie.prep)
df.graphic1$time.prep=as.numeric(df.graphic1$time.prep)
graphic1<-ggplot2::ggplot(df.graphic1, ggplot2::aes(x=time.prep, y=especie.prep, colour=Names)) +
ggplot2::geom_line()+
ggplot2::labs(x = "Time",
y = "Relative Abundance")
return(graphic1)
}
time=c(1:(dim(especie)[2]-1))
time.prep<-as.vector(sapply(time, function (x) rep(x,dim(especie)[1])))
Names<-rep(names.especie, length(time))
especie.prep<-as.vector(especie)
esperanza.prep<-as.vector(esperanza)
especiemodi<-especie[,-1]
especiemodi.prep<-as.vector(especiemodi)
if(Plot.Tipe=="DataExpected"){
if(Detail=="no"){
df.graphic2<-data.frame(cbind(especiemodi.prep,esperanza.prep,time.prep, Names))
df.graphic2$especiemodi.prep=as.numeric(df.graphic2$especiemodi.prep)
df.graphic2$esperanza.prep=as.numeric(df.graphic2$esperanza.prep)
df.graphic2$time.prep=as.numeric(df.graphic2$time.prep)
df2=reshape2::melt(df.graphic2, id=c("time.prep","Names"))
value=df2$value #Not necessary
variable=df2$variable #Not necessary
graphic2<-ggplot2::ggplot(df2, ggplot2::aes(x=time.prep, y=value, group=variable)) +
ggplot2::geom_line(data=subset(df2, variable %in% "esperanza.prep"),ggplot2::aes(linetype=variable))+
ggplot2::geom_point(data=subset(df2,variable %in% "especiemodi.prep"), ggplot2::aes(size=variable))+
ggplot2::theme(legend.position="bottom")+
ggplot2::facet_grid(Names~ .)+
ggplot2::labs(x = "Time",
y = "Relative Abundance")+
ggplot2::scale_linetype_discrete(name ="",
breaks=c("esperanza.prep"),
labels=c("ExpectedValue"))+
ggplot2::scale_size_discrete(name ="",
breaks=c("especiemodi.prep"),
labels=c("Data"))
return(graphic2)
}
if(Detail=="yes"){
df.graphic2<-data.frame(cbind(especiemodi.prep,esperanza.prep,time.prep, Names))
df.graphic2$especiemodi.prep=as.numeric(df.graphic2$especiemodi.prep)
df.graphic2$esperanza.prep=as.numeric(df.graphic2$esperanza.prep)
df.graphic2$time.prep=as.numeric(df.graphic2$time.prep)
df2=reshape2::melt(df.graphic2, id=c("time.prep","Names"))
value=df2$value #Not necessary
variable=df2$variable #Not necessary
graphic2<-ggplot2::ggplot(df2, ggplot2::aes(x=time.prep, y=value, group=variable)) +
ggplot2::geom_line(data=subset(df2, variable %in% "esperanza.prep"),ggplot2::aes(linetype=variable))+
ggplot2::geom_point(data=subset(df2, variable %in% "especiemodi.prep"), ggplot2::aes(size=variable))+
ggplot2::theme(legend.position="bottom")+
ggplot2::facet_grid(Names~ .,scales="free_y")+
ggplot2::labs(x = "Time",
y = "Relative Abundance")+
ggplot2::scale_linetype_discrete(name ="",
breaks=c("esperanza.prep"),
labels=c("ExpectedValue"))+
ggplot2::scale_size_discrete(name ="",
breaks=c("especiemodi.prep"),
labels=c("Data"))
return(graphic2)
}
}
if(Plot.Tipe=="All"){
if(Detail=="no"){
Varmas=esperanza+2*sqrt(Variance)
Varmenos=esperanza-2*sqrt(Variance)
Varmas.prep<-as.vector(Varmas)
Varmenos.prep<-as.vector(Varmenos)
df.graphic3<-data.frame(cbind(especiemodi.prep,esperanza.prep,Varmas.prep,Varmenos.prep,time.prep, Names))
df.graphic3$especiemodi.prep=as.numeric(df.graphic3$especiemodi.prep)
df.graphic3$esperanza.prep=as.numeric(df.graphic3$esperanza.prep)
df.graphic3$Varmas.prep=as.numeric(df.graphic3$Varmas.prep)
df.graphic3$Varmenos.prep=as.numeric(df.graphic3$Varmenos.prep)
df.graphic3$time.prep=as.numeric(df.graphic3$time.prep)
df3=reshape2::melt(df.graphic3, id=c("time.prep","Names"))
value=df3$value #Not necessary
variable=df3$variable #Not necessary
graphic3<-ggplot2::ggplot(df3, ggplot2::aes(x=time.prep, y=value, group=variable)) +
ggplot2::geom_line(data=subset(df3,variable %in% c("esperanza.prep","Varmas.prep","Varmenos.prep")),ggplot2::aes(linetype=variable))+
ggplot2::geom_point(data=subset(df3, variable %in% "especiemodi.prep"), ggplot2::aes(size=variable))+
ggplot2::theme(legend.position="bottom")+
ggplot2::facet_grid(Names~ .)+
ggplot2::labs(x = "Time",
y = "Relative Abundance")+
ggplot2::scale_linetype_discrete(name ="",
breaks=c("esperanza.prep","Varmas.prep","Varmenos.prep"),
labels=c("ExpectedValue (e)",expression(e + 2*sqrt(Variance)),expression(e - 2*sqrt(Variance))))+
ggplot2::scale_size_discrete(name ="",
breaks=c("especiemodi.prep"),
labels=c("Data"))
return(graphic3)
}
if(Detail=="yes"){
Varmas=esperanza+2*sqrt(Variance)
Varmenos=esperanza-2*sqrt(Variance)
Varmas.prep<-as.vector(Varmas)
Varmenos.prep<-as.vector(Varmenos)
df.graphic3<-data.frame(cbind(especiemodi.prep,esperanza.prep,Varmas.prep,Varmenos.prep,time.prep, Names))
df.graphic3$especiemodi.prep=as.numeric(df.graphic3$especiemodi.prep)
df.graphic3$esperanza.prep=as.numeric(df.graphic3$esperanza.prep)
df.graphic3$Varmas.prep=as.numeric(df.graphic3$Varmas.prep)
df.graphic3$Varmenos.prep=as.numeric(df.graphic3$Varmenos.prep)
df.graphic3$time.prep=as.numeric(df.graphic3$time.prep)
df3=reshape2::melt(df.graphic3, id=c("time.prep","Names"))
value=df3$value #Not necessary
variable=df3$variable #Not necessary
graphic3<-ggplot2::ggplot(df3, ggplot2::aes(x=time.prep, y=value, group=variable)) +
ggplot2::geom_line(data=subset(df3, variable %in% c("esperanza.prep","Varmas.prep","Varmenos.prep")),ggplot2::aes(linetype=variable))+
ggplot2::geom_point(data=subset(df3,variable %in% "especiemodi.prep"), ggplot2::aes(size=variable))+
ggplot2::theme(legend.position="bottom")+
ggplot2::facet_grid(Names~ .,scales="free_y")+
ggplot2::labs(x = "Time",
y = "Relative Abundance")+
ggplot2::scale_linetype_discrete(name ="",
breaks=c("esperanza.prep","Varmas.prep","Varmenos.prep"),
labels=c("ExpectedValue (e)",expression(e + 2*sqrt(Variance)),expression(e - 2*sqrt(Variance))))+
ggplot2::scale_size_discrete(name ="",
breaks=c("especiemodi.prep"),
labels=c("Data"))
return(graphic3)
}
}
if(Plot.Tipe=="Var"){
variance.prep<-as.vector(Variance)
df.graphic4<-data.frame(cbind(time.prep, Names,variance.prep))
df.graphic4$time.prep=as.numeric(df.graphic4$time.prep)
df.graphic4$variance.prep=as.numeric(df.graphic4$variance.prep)
graphic4 <- ggplot2::ggplot(df.graphic4, ggplot2::aes(x=time.prep, y=variance.prep)) +
ggplot2::geom_boxplot(ggplot2::aes(group=time.prep))+
ggplot2::geom_line( data = df.graphic4,ggplot2::aes(x = time.prep, y = variance.prep, color=Names))+
ggplot2::labs(x = "Time",
y = "Variance")+
ggplot2:: theme(legend.position="bottom")+
ggplot2:: theme(legend.title=ggplot2::element_blank())
return(graphic4)
}
if(Plot.Tipe=="OnlyVar"){
variance.prep<-as.vector(Variance)
df.graphic5<-data.frame(cbind(time.prep, Names,variance.prep))
df.graphic5$time.prep=as.numeric(df.graphic5$time.prep)
df.graphic5$variance.prep=as.numeric(df.graphic5$variance.prep)
graphic5 <- ggplot2::ggplot(df.graphic5, ggplot2::aes(x=time.prep, y=variance.prep)) +
ggplot2:: geom_boxplot(ggplot2::aes(group=time.prep))+
ggplot2::labs(x = "Time",
y = "Variance")
return(graphic5)
}
}
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