Comparative_MEA_dataset/Codes/meaRtools/.Rhistory

source('D:/gin-cli-latest-windows64/attempt2/Codes/meaRtools/MEA_analysis_Axion.R')
library(svDialogs)
Filesdirectory<-paste0(choose.dir(default = "", caption = "SELECT THE FOLDER WITH THE FILES"),"\\")
#my.files2 <- as.list(choose.files(default = "", caption = "SELECT YOUR SPIKE FILES", multi = TRUE))#,
my.files2=as.list(list.files(Filesdirectory, full.names=TRUE))
WorF <- (dlgInput("Enter your experiment type:  (w) for weekly and (p) for pharma")$res)#, Sys.info()["user"])$res
View(my.files2)
my.files2[[1]]
my.files2[[2]]
my.files2[[3]]
if (WorF == 'w') {
pattern="week\\s\\d{1}"
string=Filesdirectory
DIV=regmatches(string, regexpr(pattern, string))
DIV=paste0('DIV',gsub(" ", "", DIV, fixed = TRUE))
ExpName='beforePFF'
} else if (WorF == 'p') {
dday=regmatches(Filesdirectory, regexpr('\\+\\d+', Filesdirectory))
ExpName=paste0('PFFday',gsub("+", "", dday, fixed = TRUE))
} else {
stop("Please, enter the appropriate experiment type: (w) for weekly and (p) for pharma!")
}
library(svDialogs)
Filesdirectory<-paste0(choose.dir(default = "", caption = "SELECT THE FOLDER WITH THE FILES"),"\\")
#my.files2 <- as.list(choose.files(default = "", caption = "SELECT YOUR SPIKE FILES", multi = TRUE))#,
my.files2=as.list(list.files(Filesdirectory, full.names=TRUE))
WorF <- (dlgInput("Enter your experiment type:  (w) for weekly and (p) for pharma")$res)#, Sys.info()["user"])$res
if (WorF == 'w') {
pattern="week\\s\\d{1}"
string=Filesdirectory
DIV=regmatches(string, regexpr(pattern, string))
DIV=paste0('DIV',gsub(" ", "", DIV, fixed = TRUE))
ExpName='beforePFF'
} else if (WorF == 'p') {
dday=regmatches(Filesdirectory, regexpr('\\+\\d+', Filesdirectory))
ExpName=paste0('PFFday',gsub("+", "", dday, fixed = TRUE))
} else {
stop("Please, enter the appropriate experiment type: (w) for weekly and (p) for pharma!")
}
my.channels2=my.explog <- choose.files(default = "", caption = "SELECT YOUR POSITION FILE (e.g. 1well_8x8.csv or so)", multi = FALSE)
my.input2 <- choose.dir(default = "", caption = "SELECT YOUR OUTPUT FOLDER")
#my.channel_text_file <- '1well_8x8.csv' # name of your positions file - add .csv to end !!
# note that channel_text_file determines the well information you wish to use
# inform the number of wells - this will be added to the exported file name
my.well_number <- '6w' # e.g. '6w' or '1w'
# extracting data
my.spike_data <- list()
for (i in 1:length(my.files2)) {
my.spike_data[[i]] <- read.csv(my.files2[[i]])
}
my.channel_data <- read.csv(my.channels2, stringsAsFactors = FALSE)
# creating new spike data with well indo added to the electrode name
new.channels <- my.channel_data$Channel
new.ch <- list()
for (i in 1:length(my.spike_data)) {
new.ch[[i]] <- rep(0, times = length(my.spike_data[[i]]$Channel))
for (k in 1:length(new.channels)) {
new.ch[[i]][which(my.spike_data[[i]]$Channel == strsplit(new.channels[k], split = '_')[[1]][2])] <- new.channels[k]
}
}
new.times <- list()
for (i in 1:length(my.spike_data)) {
new.times[[i]] <- my.spike_data[[i]]$Time
}
# creating and exporting data frames as csv
for (i in 1:length(my.spike_data)) {
new.df <- data.frame()
new.df <- data.frame('Channel' = new.ch[[i]], 'Time' = new.times[[i]])
#new.basename <- c()
#new.basename <- strsplit(basename(my.files2[[i]]), split = '.csv')[[1]][1]
if (WorF == 'p') {
pattern3="baseline1|baseline2|AMPA|CNQX|NMDA|DAP5"
DIV=regmatches(basename(my.files2[[i]]), regexpr(pattern3, basename(my.files2[[i]])))
DIV=paste0('DIV',DIV)
}
pattern2="N\\d{3,}"
plateN=regmatches(basename(my.files2[[i]]), regexpr(pattern2,basename(my.files2[[i]])))
CHECKTHIS THING!!!ExpDate="210226"
#=regmatches(basename(my.files2[[i]]), regexpr('\\d{5,}', basename(my.files2[[i]])))
export_name <- paste0(my.input2, '/',plateN, '_', ExpDate, '_', ExpName,'_', DIV, '_', 'spikes', '_', my.well_number, '.csv')
#export_name <- paste0(my.input2, '/',new.basename, '_', my.well_number, '.csv')
write.csv(new.df, file = export_name, row.names = FALSE, quote = FALSE)
}
# creating and exporting data frames as csv
for (i in 1:length(my.spike_data)) {
new.df <- data.frame()
new.df <- data.frame('Channel' = new.ch[[i]], 'Time' = new.times[[i]])
#new.basename <- c()
#new.basename <- strsplit(basename(my.files2[[i]]), split = '.csv')[[1]][1]
if (WorF == 'p') {
pattern3="baseline1|baseline2|AMPA|CNQX|NMDA|DAP5"
DIV=regmatches(basename(my.files2[[i]]), regexpr(pattern3, basename(my.files2[[i]])))
DIV=paste0('DIV',DIV)
}
pattern2="N\\d{3,}"
plateN=regmatches(basename(my.files2[[i]]), regexpr(pattern2,basename(my.files2[[i]])))
CHECKTHIS THING!!!ExpDate="210226"
#=regmatches(basename(my.files2[[i]]), regexpr('\\d{5,}', basename(my.files2[[i]])))
export_name <- paste0(my.input2, '/',plateN, '_', ExpDate, '_', ExpName,'_', DIV, '_', 'spikes', '_', my.well_number, '.csv')
#export_name <- paste0(my.input2, '/',new.basename, '_', my.well_number, '.csv')
write.csv(new.df, file = export_name, row.names = FALSE, quote = FALSE)
}
View(my.files2)
my.files2[[1]]
pattern2="N\\d{3,}"
plateN=regmatches(basename(my.files2[[1]]), regexpr(pattern2,basename(my.files2[[1]])))
regmatches(basename(my.files2[[1]]), regexpr('\\d{5,}', basename(my.files2[[1]])))
ExpDate=regmatches(basename(my.files2[[1]]), regexpr('\\d{5,}', basename(my.files2[[1]])))
# creating and exporting data frames as csv
for (i in 1:length(my.spike_data)) {
new.df <- data.frame()
new.df <- data.frame('Channel' = new.ch[[i]], 'Time' = new.times[[i]])
#new.basename <- c()
#new.basename <- strsplit(basename(my.files2[[i]]), split = '.csv')[[1]][1]
if (WorF == 'p') {
pattern3="baseline1|baseline2|AMPA|CNQX|NMDA|DAP5"
DIV=regmatches(basename(my.files2[[i]]), regexpr(pattern3, basename(my.files2[[i]])))
DIV=paste0('DIV',DIV)
}
pattern2="N\\d{3,}"
plateN=regmatches(basename(my.files2[[i]]), regexpr(pattern2,basename(my.files2[[i]])))
# CHECKTHIS THING!!!ExpDate="210226"
#=regmatches(basename(my.files2[[i]]), regexpr('\\d{5,}', basename(my.files2[[i]])))
export_name <- paste0(my.input2, '/',plateN, '_', ExpDate, '_', ExpName,'_', DIV, '_', 'spikes', '_', my.well_number, '.csv')
#export_name <- paste0(my.input2, '/',new.basename, '_', my.well_number, '.csv')
write.csv(new.df, file = export_name, row.names = FALSE, quote = FALSE)
}