library(knitr) opts_chunk$set(fig.width=11, fig.height=7, base64_images=F, fig.align="center", message=F, warning=F, fig.path='figure_wave/')
library(centWaveP) library(ggplot2)
eic = readRDS("eic.rds") eic.n = estimateBaselineNoise(eic, peakwidth = c(15,70), minslope.peak = 10000, plot.tf = T) eic.n$inroi=T ggplot(eic) + geom_line(aes(x = rt, y = i)) ggplot(subset(eic.n,abs(rt - 1300) < 200)) + geom_line(aes(x = rt, y = i)) + geom_line(aes(x = rt, y =noise.local.sd), colour = "red") + geom_line(aes(x = rt, y =baseline), colour = "orchid") + geom_line(aes(x = rt, y =noise.baseline.sd), colour = "green") peaks = wave(eic.n, peakwidth = c(5,70), valleywidth.min = 10) peaks = subset(peaks, descent.fold.above.descentbaseline > 0.95) for (i in seq_along(peaks[,1])) { plotWavePeak(i, eic.n, peaks) %>% print #cat ("Press [enter] to continue") #line <- readline() #if (line == "x") {break;} }
eic = { dnorm(seq(-6, 6, by =0.1)) + dnorm(seq(-6, 6, by =0.1), mean = 3) } %>% { ./max(.) } eic = data.frame( i = eic, rt = seq(eic), scan = seq(eic)) eic$inroi = T ggplot(eic) + geom_line(aes(x = rt, y = i)) eic.n = estimateBaselineNoise(eic, peakwidth = c(15, 70), minslope.peak = .005, plot.tf = T) ggplot(eic.n) + geom_line(aes(x = rt, y = i)) + geom_line(aes(x = rt, y =noise.local.sd), colour = "red") + geom_line(aes(x = rt, y =baseline), colour = "orchid") + geom_line(aes(x = rt, y =noise.baseline.sd), colour = "green") peaks = wave(eic.n, peakwidth = c(5,70), valleywidth.min = 10) for (i in seq_along(peaks[,1])) { plotWavePeak(i, eic.n, peaks) %>% print }
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