我需要从csv文件中检索数据并对其进行图形化。数据如下所示：
S096-A91 11525 11492 11526 11514 11570 11563 11570 11562 11575 11594 11586 11592 11597 11596 11603 11608 11592 11605 11607 11599 11610 11601 11598 11610 11602 11611 11607 11608 11621 11614 11609 11616 11602 11610 11623
Raw Data for Probe FAM-MGB
Chamber ID 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35
S235-A01 4210 4260 4273 4274 4290 4310 4324 4331 4357 4367 4371 4381 4396 4393 4409 4416 4424 4430 4443 4457 4490 4538 4604 4669 4719 4779 4812 4853 4908 4938 4986 5019 5039 5073 5110
S235-A02 4166 4224 4250 4253 4252 4275 4266 4272 4290 4294 4295 4300 4300 4301 4308 4310 4309 4320 4325 4346 4368 4435 4545 4688 4887 5107 5329 5541 5754 5944 6123 6282 6418 6541 6651
我需要来自（探测器FAM-MGB的原始数据）的数据，并且ID会继续保持大约40k以上的数据。我不能包括最左边的列S235-A01，因为我必须绘制点图。到目前为止，我几乎所有的工作都在工作，下面是代码：
#------DATA---------------------------
#|Raw Data for Probe FAM-MGB |
#|Raw Data for Passive Reference ROX |
#|Bkgd Data for Passive Reference ROX|
#|Bkgd Data for Probe FAM-MGB |
#-------------------------------------
#---- BEGIN file operations ------
getData <- function(file,name) {
#lines <- readLines("Baseline Poly Raw.csv") #get each full row
for(i in 1:length(file)) {
lines <- readLines(file[i])
indx <- grep(name, lines) #row number for anything with search term in it
counter <- 3
dat <- read.table(text=lines[(indx+2)],
sep="", header=FALSE, stringsAsFactors=FALSE, check.names=FALSE)
return(dat) #only getting 1 row for now for testing
while(dat != " ") {#get all the data up to the whitespace
print(dat)
dat <- read.table(text=lines[(indx+counter)], #read only one line per loop
sep=",", header=FALSE, stringsAsFactors=FALSE, check.names=FALSE)
counter <- counter + 1
}
}
}
readFiles <- function() { #gets all the files in directory ending in .csv, returns them as temp[x]
temp = list.files(pattern="*.csv")
#for (i in 1:length(temp)) print(temp[i])
return(temp)
}
onStart <- function() { #function to get everything moving
temp <- readFiles() #gets all the files in directory ending in .csv, returns them as temp[x]
getData(temp,"Raw Data for Probe FAM-MGB") #gets all data for this section form all the .csv files in directory
}
#------END file operations
#------BEGIN Plotting functions
quickPlot <- function(xs,ys) { #quickly plot any points with a regression line
plot(xs,ys, xlab="x", ylab="y")
abline(lm(ys~xs))
title("Test graph")
}
polyFit <- function(xs,ys,degree) { #polynomial fitting a data set degree 3
fit3 <- lm(ys~poly(xs,degree,raw=TRUE))
xx <- seq(0,160, length=50)
plot(xs,ys,pch='@')
lines(xx, predict(fit3, data.frame(xs=xx)), col="green")
}
logFit <- function(xs,ys) { #graph the data set with log(x), y
logEstimate = lm(ys ~ log(xs))
plot(xs,ys,pch='@')
lines(xs,predict(logEstimate),col='green')
}
eFit <- function(xs,ys) {
expEstimate = lm(log(ys) ~ xs)
plot(xs, ys,pch='@')
lines(xs, exp(predict(expEstimate)),col='green')
}
sigmoidalFit <- function(xs,ys) {
}
#------END plotting functions
getNormalization <- function(data) {
}
askYesNo <- function() {
n <- readline("Would you like to save the image? (Y/N):")
if(n == 'Y' | n == 'y' | n == 'yes' | n == 'Yes') {
print("Image saved")
return(1)
} else {
print("Image not saved")
return(0)
}
}
# x <- c(32,64,96,118,126,144,152.5,158)
# y <- c(99.5,104.8,108.5,100,86,64,35.3,15)
#
# polyFit(x,y,3)
x <- onStart() #only get 1 data row for now, just for testing
print(x)
print（x）yield：
V1
1 S235-A01,4210,4260,4273,4274,4290,4310,4324,4331,4357,4367,4371,4381,4396,4393,4409,4416,4424,4430,4443,4457,4490,4538,4604,4669,4719,4779,4812,4853,4908,4938,4986,5019,5039,5073,5110,
我无法绘制，因为它包含S235-A01。我不知道如何摆脱它。任何帮助都会被贬低，谢谢。 -SAM