Momocs：用R进行表型变化分析

for (i in 1:fn) {

j <- 2*i - 1

k <- 2*i

erUD[[j]] <- dataAllCorr[[i]][dataAllCorr[[i]]$dat.corr.y > 0,]

erUD[[k]] <- dataAllCorr[[i]][dataAllCorr[[i]]$dat.corr.y < 0,]

}

plot(x = erUD[[1]]$ dat.corr.x, y = abs(erUD[[1]]$ dat.corr.y), col="blue", type= "l", xlim = c(0, 1.4), main="Corrected by Leaf Area (er 001-014)")

for (i in 1:length(erUD) ) {

points(x = erUD[[i]]$ dat.corr.x, y = abs(erUD[[i]]$ dat.corr.y), col="blue", type= "l")

}

require(Momocs)

pnt_num <- 500

files <- read.csv("er_BinaryImageFileList.csv")

dataNames.txt <- files$txt.files

dataNames.jpg <- files$jpg.files

fn <- dim(files)[1]

dataAll <- list(0)

for (i in 1:fn) {

in_f <- as.character(dataNames.txt[i])

dat.imgj <- read.delim(in_f)

dat.imgj <- which(dat.imgj < 127, arr.ind = T)

image.ori <- import_jpg1(as.character(dataNames.jpg[i]))

cimage <- Out(image.ori)

files $Area.pixels[i] <- coo_area(cimage)

image1 <- coo_sample(cimage[1], pnt_num)

image1 <- as.data.frame(image1)

pet.pos <- min(image1[,2])

image.coo <- image1[image1$V2 > pet.pos + 1, ]

lm2 <- lm(dat.imgj[,1] ~ 1 + dat.imgj[,2] + I(dat.imgj[,2]^2))

k1 <- as.numeric(lm2$coefficients[1])

k2 <- as.numeric(lm2$coefficients[2])

k3 <- as.numeric(lm2$coefficients[3])

dat.corr.x <- image.coo[,2] - min(image.coo[,2])

dat.corr.y <- k1 + k2 * image.coo[,2] + k3 * image.coo[,2]^2 - image.coo[,1]

datXY <- as.data.frame(cbind(dat.corr.x, dat.corr.y))

dataAll[[i]] <- datXY

}

names(dataAll) <- dataNames.txt

plot(x = dataAll[[1]][,1], y = abs(dataAll[[1]][,2]), type="l")

for (i in 2:fn) {

points(x = dataAll[[i]][,1], y = abs(dataAll[[i]][,2]), col="gray", type="l")

}

size <- sqrt(files $Area.pixels)

dataAllCorr <- list(0)

for (i in 1:fn) {

dataAllCorr[[i]] <- dataAll[[i]]/size[i]

}

plot(x = dataAllCorr[[1]][,1], y = abs(dataAllCorr[[1]][,2]), xlim= c(0, 1.4), type="l")

for (i in 2:fn) {

points(x = dataAllCorr[[i]][,1], y = abs(dataAllCorr[[i]][,2]), col="gray", type="l")

}

erUD <- list(0)

for (i in 1:fn) {

j <- 2*i - 1

k <- 2*i

erUD[[j]] <- dataAllCorr[[i]][dataAllCorr[[i]]$dat.corr.y > 0,]

erUD[[k]] <- dataAllCorr[[i]][dataAllCorr[[i]]$dat.corr.y < 0,]

}

plot(x = erUD[[1]]$ dat.corr.x, y = abs(erUD[[1]]$ dat.corr.y), col="blue", type= "l", xlim = c(0, 1.4), main="Corrected by Leaf Area (er 001-014)")

for (i in 1:length(erUD) ) {

points(x = erUD[[i]]$ dat.corr.x, y = abs(erUD[[i]]$ dat.corr.y), col="blue", type= "l")

}