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oo_timeseries_wbextract_manualscans.R
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oo_timeseries_wbextract_manualscans.R
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# plots all spectral scans in the folder
setwd("//Volumes/Extended/OO/")
scans = list.files(pattern = "*.txt") # create list of text files
tot.scans=length(scans) # number of *.txt files in the directory
#scan_a = scans[c(TRUE,TRUE,TRUE,FALSE,FALSE,FALSE)]
#scan_b = scans[c(FALSE,FALSE,FALSE,TRUE,TRUE,TRUE)]
sun = read.table("Subt1_14-03-44-401_sun2500ms_good.txt", skip=14, header=F, sep = "\t", col.names = c("wavelength", "intensity"))
attach(sun)
plant = read.table("Subt1_14-05-09-394_plant2500ms_good.txt", skip=14, header=F, sep = "\t", col.names = c("wavelength", "intensity"))
attach(plant)
dim(plant)
dim(sun)
# L = plant
# E = solar
o2b_sun = subset(sun, wavelength > 675)
o2b_sun = subset(sun, wavelength < 697)
o2a_sun = subset(sun, wavelength > 750)
o2b_plant = subset(plant, plant$wavelength > 675)
o2b_plant = subset(plant, plant$wavelength < 697)
o2a_plant = subset(plant, plant$wavelength > 750)
dim(o2b_sun)
dim(o2b_plant)
o2a = merge(o2a_sun, o2a_plant, by = "wavelength")
names(o2a)[2] = "o2a_sun"
names(o2a)[3] = "o2a_plant"
o2a["plnt_pi"] = NA
o2a[4] = o2a[3]*pi
o2a["upwelling"] = NA
o2a[5] = o2a[4]/o2a[2]
o2b = merge(o2b_sun, o2b_plant, by = "wavelength")
names(o2b)[2] = "o2b_sun"
names(o2b)[3] = "o2b_plant"
o2b["plnt_pi"] = NA
o2b[4] = o2b[3]*pi
o2b["upwelling"] = NA
o2b[5] = o2b[4]/o2b[2]
plot(o2a$wavelength, o2a$o2a_sun, type="l")
lines(o2a$wavelength, o2a$o2a_plant, type="l")
lines(o2a$wavelength, o2a$upwelling, type="l")
plot(o2b[,2], type="l")
lines(o2b[,3], type="l")
graphics.off()
par(mar = c(5,5,2,5))
with(o2a, plot(o2a$wavelength, o2a$o2a_sun, type="l", col="red3", ylab="wavelength"))
par(new = T)
with(o2a, plot(o2a$wavelength, o2a$upwelling, type="l", col="blue", ylab="wavelength"), ylim = c(-4,2))
axis(side = 4)
# https://www.r-bloggers.com/r-single-plot-with-two-different-y-axes/
with(d, plot(x, n, pch=16, axes=F, xlab=NA, ylab=NA, cex=1.2))
axis(side = 4)
mtext(side = 4, line = 3, 'Number genes selected')
legend("topleft",
legend=c(expression(-log[10](italic(p))), "N genes"),
lty=c(1,0), pch=c(NA, 16), col=c("red3", "black"))
layout(matrix(c(1,2,3,4),2,2, byrow = TRUE))
graphics.off()
summary(o2a)
data_frame = data.frame(o2a_sun)
data_frame[2] = "O2a_sun"
plot(((o2a_plant[,2]*pi)/o2a_sun[,2]), col="black", type="l")
plot(o2a[,1], o2a[,5], type="l", xlab = "Wavelength (nm)", ylab = "Intensity (counts)", main = "O2A", cex.main=0.8)
lines(o2a[,5])
text(7500, 1.6, "O2A", cex=0.9, col="blue") #, adj = 0)
pi_l = (o2a_plant$intensity*pi)
ba = ((o2a_plant$intensity*pi)/o2a_sun$intensity))
dim(pi_l)
o2b.mod = lm(o2b$wavelength ~ o2b$intensity)
o2b.mod$coefficients[2] -> o2bslope
o2a = subset(data_frame, wavelength > 759.3)
o2a = subset(o2a, wavelength < 762.0)
o2a.mod = lm(o2a$wavelength ~ o2a$intensity)
o2a.mod$coefficients[2] -> o2aslope
####################
#n=4
for (n in 1:length(scans)){
file_n = scans[n] # change this to the list of files = list.files(pattern = "*.txt")[n]
data_frame2 = readLines(as.character(file_n))[3]
data_frame3 = substr(as.character(data_frame2), 18, nchar(as.character(data_frame2))-9) # truncate string
data_frame = read.table(as.character(file_n), skip=14, header=F, sep = "\t", col.names = c("wavelength", "intensity"))
attach(data_frame)
# o2b = data_frame[5,2] # extracts single waveband
# o2b = lapply(o2b[2], mean)
o2b = subset(data_frame, wavelength > 686.7)
o2b = subset(o2b, wavelength < 688.3)
o2b.mod = lm(o2b$wavelength ~ o2b$intensity)
o2b.mod$coefficients[2] -> o2bslope
o2a = subset(data_frame, wavelength > 759.3)
o2a = subset(o2a, wavelength < 762.0)
o2a.mod = lm(o2a$wavelength ~ o2a$intensity)
o2a.mod$coefficients[2] -> o2aslope
df = data.frame(data_frame3, o2bslope, o2aslope)
write.table(df, file="scan1.csv", eol = "\r", na = "NA", row.names = FALSE, append = TRUE, sep=",", col.names = !file.exists("scan1.csv"))
}