scripts/merge_igor_files.R
In pnojai/rwalk: Random Walk Model of Neurotransmitter Release and Uptake
library(ggplot2)
library(openxlsx)
library(dplyr)
library(data.table)
# Global variables
pipeline_dir <- "/media/sf_OneDrive_-_cumc.columbia.edu/rwalk/pipeline"
input_dir <- paste(pipeline_dir, "06_Library", sep = "/")
coordinate_file_tag <- "PD"
data_file_tag <- "DAT"
fil_extension <- "csv"
sample_rate <- 100
stim_period <- 120 # seconds
input_queue <- dir(input_dir)
# Filter for coordinate files
pat <- paste0(coordinate_file_tag, "\\.", fil_extension, "$")
input_queue <- input_queue[grep(pattern = pat, x = input_queue, ignore.case = TRUE)]
# fils <- unique(fil_params_all[ , c("filename", "sample_rate", "animal", "genotype",
# "pulses", "pulse_freq", "bin_size", "electrode_distance",
# "dead_space_distance", "diffusion_coefficient", "convert_current",
# "calibration_current", "calibration_concentration")])
# Files for merging.
print(input_queue)
# Initialize data frame for merge.
stim_df <- data.frame(animal = integer(),
stimulus = integer(),
stim_time_sec = double(),
genotype = character(),
include = logical(),
time_sec = double(),
electrode_current = double(),
electrode_concentration = double())
animal_id_last_file <- 0
max_stim_last_file <- 0
# Read data
for (i in 1:(length(input_queue) - 0)) {
# Coordinate file drives processing.
coord_fil <- input_queue[i]
print(coord_fil)
coord_fil_path <- paste(input_dir, coord_fil, sep = "/")
# Derive data file name.
dat_fil <- sub(pattern = paste0(coordinate_file_tag, "\\.", fil_extension, "$"),
replacement = paste0(data_file_tag, "\\.", fil_extension),
x = coord_fil,
ignore.case = TRUE)
dat_fil_path <- paste(input_dir, dat_fil, sep = "/")
#Parse file name
file_tags <- parse_file_name(dat_fil)
animal_id <- file_tags[[1]]
# skip file_tags[[2]]. It is the file_type.
genotype <- file_tags[[3]]
drug_concentration <- file_tags[[4]]
# drug_name <- UNSUPPORTED
drug_position <- file_tags[[5]]
calibration_current <- file_tags[[6]]
calibration_concentration <- file_tags[[7]]
# Read the coordinate file
coord <- fread(coord_fil_path)
# coord$T_Bkg1 <- coord$T_Bkg1 * 10 # Convert Igor start times.
# coord$T_Bkg2 <- coord$T_Bkg2 * 10 # Convert Igor start times.
# Read data. Electrode as current.
dat_current <- read_experiment_csv(dat_fil_path, sr = sample_rate)
# Read data. Electrode as concentration.
dat_concentration <- read_experiment_csv(dat_fil_path, sr = sample_rate)
dat_concentration <- current_to_concentration(dat_concentration,
calibration_current = calibration_current,
calibration_concentration = calibration_concentration)
# If new animal, reset stim counting, otherwise continue series.
if (animal_id != animal_id_last_file) {
max_stim_last_file <- 0
}
max_stim <- nrow(coord) + max_stim_last_file
dat_current_list <- list()
dat_concentration_list <- list()
# j points to the coordinate row
# j + max_stim_last_file equals the current stimulus
for (j in 1:nrow(coord)) {
stim <- max_stim_last_file + j
stim_start_time <- coord$T_Bkg1[j]
dat_start_idx <- which(round(dat_current$time_sec, 1) == round(coord$T_Bkg1[j], 1))
if (dat_start_idx > nrow(dat_current)) {
stop(paste0("Stimulus start overflows data: ", coord_fil,
" #", stim))
} else if (stim == max_stim) {
top_row_idx <- nrow(dat_current)
} else {
top_row_idx <- which(round(dat_current$time_sec, 1) == round(coord$T_Bkg1[(j + 1)], 1)) - 1
}
sr_s <- sample_rate * 10^-3
stim_time_sec <- seq(from = 0, by = sr_s,
length.out = nrow(dat_current[dat_start_idx:top_row_idx, ]))
one_stim_df <- as.data.frame(cbind(animal = animal_id, stimulus = stim,
stim_time_sec = stim_time_sec, genotype = genotype,
include = coord$include[j],
time_sec = dat_current[dat_start_idx:top_row_idx, 1],
electrode_current = dat_current[dat_start_idx:top_row_idx, 2],
electrode_concentration = dat_concentration[dat_start_idx:top_row_idx, 2]),
stringsAsFactors = FALSE)
one_stim_df$animal <- as.integer(one_stim_df$animal)
one_stim_df$stimulus <- as.integer(one_stim_df$stimulus)
one_stim_df$stim_time_sec <- as.double(one_stim_df$stim_time_sec)
one_stim_df$include <- as.logical(one_stim_df$include)
one_stim_df$time_sec <- as.double(one_stim_df$time_sec)
one_stim_df$electrode_current <- as.double(one_stim_df$electrode_current)
one_stim_df$electrode_concentration <- as.double(one_stim_df$electrode_concentration)
stim_df <- rbind(stim_df, one_stim_df)
}
# Before leaving file loop, remember which animal we just processed.
animal_id_last_file <- animal_id
max_stim_last_file <- max_stim
}
# # Analysis of NA
ok <- complete.cases(stim_df)
sum(!ok)
fwrite(x = stim_df, file = paste(input_dir, "stim_df.csv", sep = "/"))
# # WT - Pre-AMPH
# dat_merge_wt_pre <- select(stim_df, animal, stim_time_sec, electrode_concentration, genotype, stimulus, include) %>%
# filter(genotype == "wt" & stimulus >= 1 & stimulus <= 3 & include == TRUE & stim_time_sec <= 120) %>%
# group_by(stim_time_sec) %>%
# summarize(mean(electrode_concentration))
# dat_merge_wt_pre <- rename(dat_merge_wt_pre, time_sec = stim_time_sec, "electrode_concentration" = "mean(electrode_concentration)")
# qplot(dat_merge_wt_pre$time_sec, dat_merge_wt_pre$electrode_concentration, geom = "line")
# # WT - AMPH_06_10
# dat_merge_wt_amph_0610 <- select(stim_df, animal, stim_time_sec, electrode, genotype, stimulus, include) %>%
# filter(genotype == "wt" & stimulus >= 6 & stimulus <= 10 & include == TRUE & stim_time_sec <= 120) %>%
# group_by(stim_time_sec) %>%
# summarize(mean(electrode))
# dat_merge_wt_amph_0610 <- rename(dat_merge_wt_amph_0610, time_sec = stim_time_sec, "electrode" = "mean(electrode)")
# qplot(dat_merge_wt_amph_0610$time_sec, dat_merge_wt_amph_0610$electrode, geom = "line")
#
# # WT - AMPH_16_20
# dat_merge_wt_amph_1620 <- select(stim_df, animal, stim_time_sec, electrode, genotype, stimulus, include) %>%
# filter(genotype == "wt" & stimulus >= 16 & stimulus <= 20 & include == TRUE & stim_time_sec <= 120) %>%
# group_by(stim_time_sec) %>%
# summarize(mean(electrode))
# dat_merge_wt_amph_1620 <- rename(dat_merge_wt_amph_1620, time_sec = stim_time_sec, "electrode" = "mean(electrode)")
# qplot(dat_merge_wt_amph_1620$time_sec, dat_merge_wt_amph_1620$electrode, geom = "line")
#
# # KO - Pre-AMPH
# dat_merge_ko_pre <- select(stim_df, animal, stim_time_sec, electrode_concentration, genotype, stimulus, include) %>%
# filter(genotype == "ko" & stimulus >= 1 & stimulus <= 3 & include == TRUE & stim_time_sec <= 120) %>%
# group_by(stim_time_sec) %>%
# summarize(mean(electrode_concentration))
# dat_merge_ko_pre <- rename(dat_merge_ko_pre, time_sec = stim_time_sec, "electrode_concentration" = "mean(electrode_concentration)")
# qplot(dat_merge_ko_pre$time_sec, dat_merge_ko_pre$electrode_concentration, geom = "line")
#
# dat_merge_ko_pre <- select(stim_df, animal, stim_time_sec, electrode, genotype, stimulus, include) %>%
# filter(genotype == "ko" & stimulus >= 1 & stimulus <= 3 & include == TRUE & stim_time_sec <= 120) %>%
# group_by(stim_time_sec) %>%
# summarize(mean(electrode))
# dat_merge_ko_pre <- rename(dat_merge_ko_pre, time_sec = stim_time_sec, "electrode" = "mean(electrode)")
# qplot(dat_merge_ko_pre$time_sec, dat_merge_ko_pre$electrode, geom = "line")
#
# # KO - AMPH_06_10
# dat_merge_ko_amph_0610 <- select(stim_df, animal, stim_time_sec, electrode, genotype, stimulus, include) %>%
# filter(genotype == "ko" & stimulus >= 6 & stimulus <= 10 & include == TRUE & stim_time_sec <= 120) %>%
# group_by(stim_time_sec) %>%
# summarize(mean(electrode))
# dat_merge_ko_amph_0610 <- rename(dat_merge_ko_amph_0610, time_sec = stim_time_sec, "electrode" = "mean(electrode)")
# qplot(dat_merge_ko_amph_0610$time_sec, dat_merge_ko_amph_0610$electrode, geom = "line")
#
# # KO - AMPH_16_20
# dat_merge_ko_amph_1620 <- select(stim_df, animal, stim_time_sec, electrode, genotype, stimulus, include) %>%
# filter(genotype == "wt" & stimulus >= 16 & stimulus <= 20 & include == TRUE & stim_time_sec <= 120) %>%
# group_by(stim_time_sec) %>%
# summarize(mean(electrode))
# dat_merge_ko_amph_1620 <- rename(dat_merge_ko_amph_1620, time_sec = stim_time_sec, "electrode" = "mean(electrode)")
# qplot(dat_merge_ko_amph_1620$time_sec, dat_merge_ko_amph_1620$electrode, geom = "line")
#
# # Plot and compile results.
# results <- data.frame(genotype = character(),
# amphetamine = character(),
# release = double(),
# vmax = double(),
# km = double(),
# stringsAsFactors = FALSE)
#
# # Constants
# pulses <- 30
# pulse_freq <- 50
# bin_size <- 2.0
# electrode_distance <- 1000
# dead_space_distance <- 4
# diffusion_coefficient <- 2.7 * 10^-6
# convert_current <- FALSE
# fit_region = "fall"
#
# # WT - Pre-AMPH
#
# # Variables
# genotype <- "WT"
# amphetamine <- "PRE"
# release <- 2.25
# vmax <- 4.8
# km <- 5
# base_tolerance <- 0.05
# plot_duration_sec = 18
#
# if (nrow(results[results$genotype == genotype & results$amphetamine == amphetamine, ]) == 0) {
# results[(nrow(results)+1), ] <- c(genotype, amphetamine, release, vmax, km)
# } else {
# results[results$genotype == genotype &
# results$amphetamine == amphetamine, ] <- cbind(genotype, amphetamine, release, vmax, km)
# }
#
# compare_pulse(dat = dat_merge_wt_pre, fil = "Wild Type - Pre-AMPH",
# vmax = vmax, km = km,
# pulses = pulses,
# pulse_freq = pulse_freq,
# release = release,
# bin_size = bin_size,
# electrode_distance = electrode_distance,
# dead_space_distance = dead_space_distance,
# diffusion_coefficient = diffusion_coefficient,
# convert_current = convert_current,
# fit_region = fit_region,
# base_tolerance = base_tolerance,
# plot_duration_sec = plot_duration_sec)
#
# # WT - Post-AMPH 6-10
#
# # Variables
# genotype <- "WT"
# amphetamine <- "POST_06-10"
# release <- 5.5
# vmax <- 4.8
# km <- 24
# base_tolerance <- 0.05
# plot_duration_sec = 50
#
# if (nrow(results[results$genotype == genotype & results$amphetamine == amphetamine, ]) == 0) {
# results[(nrow(results)+1), ] <- c(genotype, amphetamine, release, vmax, km)
# } else {
# results[results$genotype == genotype &
# results$amphetamine == amphetamine, ] <- cbind(genotype, amphetamine, release, vmax, km)
# }
#
# compare_pulse(dat = dat_merge_wt_amph_0610, fil = "Wild Type - Post-AMPH 06-10",
# vmax = vmax, km = km,
# pulses = pulses,
# pulse_freq = pulse_freq,
# release = release,
# bin_size = bin_size,
# electrode_distance = electrode_distance,
# dead_space_distance = dead_space_distance,
# diffusion_coefficient = diffusion_coefficient,
# convert_current = convert_current,
# fit_region = fit_region,
# base_tolerance = base_tolerance,
# plot_duration_sec = plot_duration_sec)
#
# # WT - Post-AMPH 16-20
#
# # Variables
# genotype <- "WT"
# amphetamine <- "POST_16-20"
# release <- 4.3
# vmax <- 4.8
# km <- 24
# base_tolerance <- 0.05
# plot_duration_sec = 50
#
# if (nrow(results[results$genotype == genotype & results$amphetamine == amphetamine, ]) == 0) {
# results[(nrow(results)+1), ] <- c(genotype, amphetamine, release, vmax, km)
# } else {
# results[results$genotype == genotype &
# results$amphetamine == amphetamine, ] <- cbind(genotype, amphetamine, release, vmax, km)
# }
#
# compare_pulse(dat = dat_merge_wt_amph_1620, fil = "Wild Type - Post-AMPH 16-20",
# vmax = vmax, km = km,
# pulses = pulses,
# pulse_freq = pulse_freq,
# release = release,
# bin_size = bin_size,
# electrode_distance = electrode_distance,
# dead_space_distance = dead_space_distance,
# diffusion_coefficient = diffusion_coefficient,
# convert_current = convert_current,
# fit_region = fit_region,
# base_tolerance = base_tolerance,
# plot_duration_sec = plot_duration_sec)
#
# # ----------------- END OF WILD TYPE -----------------#
#
# # ----------------- BEGIN KNOCKOUT -----------------#
#
# # KO - Pre-AMPH
#
# # Variables
# genotype <- "KO"
# amphetamine <- "PRE"
# release <- 1.77
# vmax <- 4.8
# km <- 5
# base_tolerance <- 0.05
# plot_duration_sec = 10
#
# if (nrow(results[results$genotype == genotype & results$amphetamine == amphetamine, ]) == 0) {
# results[(nrow(results)+1), ] <- c(genotype, amphetamine, release, vmax, km)
# } else {
# results[results$genotype == genotype &
# results$amphetamine == amphetamine, ] <- cbind(genotype, amphetamine, release, vmax, km)
# }
#
# compare_pulse(dat = dat_merge_ko_pre, fil = "Knockout - Pre-AMPH",
# vmax = vmax, km = km,
# pulses = pulses,
# pulse_freq = pulse_freq,
# release = release,
# bin_size = bin_size,
# electrode_distance = electrode_distance,
# dead_space_distance = dead_space_distance,
# diffusion_coefficient = diffusion_coefficient,
# convert_current = convert_current,
# fit_region = fit_region,
# base_tolerance = base_tolerance,
# plot_duration_sec = plot_duration_sec)
#
# # KO - Post-AMPH 6-10
#
# # Variables
# genotype <- "KO"
# amphetamine <- "POST_06-10"
# release <- 3.8
# vmax <- 4.8
# km <- 24
# base_tolerance <- 0.05
# plot_duration_sec = 30
#
# if (nrow(results[results$genotype == genotype & results$amphetamine == amphetamine, ]) == 0) {
# results[(nrow(results)+1), ] <- c(genotype, amphetamine, release, vmax, km)
# } else {
# results[results$genotype == genotype &
# results$amphetamine == amphetamine, ] <- cbind(genotype, amphetamine, release, vmax, km)
# }
#
# compare_pulse(dat = dat_merge_ko_amph_0610, fil = "Knockout - Post-AMPH 06-10",
# vmax = vmax, km = km,
# pulses = pulses,
# pulse_freq = pulse_freq,
# release = release,
# bin_size = bin_size,
# electrode_distance = electrode_distance,
# dead_space_distance = dead_space_distance,
# diffusion_coefficient = diffusion_coefficient,
# convert_current = convert_current,
# fit_region = fit_region,
# base_tolerance = base_tolerance,
# plot_duration_sec = plot_duration_sec)
#
# # KO - Post-AMPH 16-20
#
# # Variables
# genotype <- "KO"
# amphetamine <- "POST_16-20"
# release <- 4.3
# vmax <- 4.8
# km <- 24
# base_tolerance <- 0.05
# plot_duration_sec = 50
#
# if (nrow(results[results$genotype == genotype & results$amphetamine == amphetamine, ]) == 0) {
# results[(nrow(results)+1), ] <- c(genotype, amphetamine, release, vmax, km)
# } else {
# results[results$genotype == genotype &
# results$amphetamine == amphetamine, ] <- cbind(genotype, amphetamine, release, vmax, km)
# }
#
# compare_pulse(dat = dat_merge_ko_amph_1620, fil = "Knockout - Post-AMPH 16-20",
# vmax = vmax, km = km,
# pulses = pulses,
# pulse_freq = pulse_freq,
# release = release,
# bin_size = bin_size,
# electrode_distance = electrode_distance,
# dead_space_distance = dead_space_distance,
# diffusion_coefficient = diffusion_coefficient,
# convert_current = convert_current,
# fit_region = fit_region,
# base_tolerance = base_tolerance,
# plot_duration_sec = plot_duration_sec)
#
# results
#
# dat <- select(stim_df, animal, stim_time_sec, time_sec, electrode_concentration, electrode_current, genotype, stimulus, include) %>%
# filter(animal == 1902051)
# # group_by(stim_time_sec) %>%
# # summarize(mean(electrode_concentration))
# dat_merge_ko_pre <- rename(dat_merge_ko_pre, time_sec = stim_time_sec, "electrode_concentration" = "mean(electrode_concentration)")
# qplot(dat_merge_ko_pre$time_sec, dat_merge_ko_pre$electrode_concentration, geom = "line")
#
pnojai/rwalk documentation built on Nov. 12, 2019, 7:42 a.m.
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library(ggplot2)
library(openxlsx)
library(dplyr)
library(data.table)
# Global variables
pipeline_dir <- "/media/sf_OneDrive_-_cumc.columbia.edu/rwalk/pipeline"
input_dir <- paste(pipeline_dir, "06_Library", sep = "/")
coordinate_file_tag <- "PD"
data_file_tag <- "DAT"
fil_extension <- "csv"
sample_rate <- 100
stim_period <- 120 # seconds
input_queue <- dir(input_dir)
# Filter for coordinate files
pat <- paste0(coordinate_file_tag, "\\.", fil_extension, "$")
input_queue <- input_queue[grep(pattern = pat, x = input_queue, ignore.case = TRUE)]
# fils <- unique(fil_params_all[ , c("filename", "sample_rate", "animal", "genotype",
# "pulses", "pulse_freq", "bin_size", "electrode_distance",
# "dead_space_distance", "diffusion_coefficient", "convert_current",
# "calibration_current", "calibration_concentration")])
# Files for merging.
print(input_queue)
# Initialize data frame for merge.
stim_df <- data.frame(animal = integer(),
stimulus = integer(),
stim_time_sec = double(),
genotype = character(),
include = logical(),
time_sec = double(),
electrode_current = double(),
electrode_concentration = double())
animal_id_last_file <- 0
max_stim_last_file <- 0
# Read data
for (i in 1:(length(input_queue) - 0)) {
# Coordinate file drives processing.
coord_fil <- input_queue[i]
print(coord_fil)
coord_fil_path <- paste(input_dir, coord_fil, sep = "/")
# Derive data file name.
dat_fil <- sub(pattern = paste0(coordinate_file_tag, "\\.", fil_extension, "$"),
replacement = paste0(data_file_tag, "\\.", fil_extension),
x = coord_fil,
ignore.case = TRUE)
dat_fil_path <- paste(input_dir, dat_fil, sep = "/")
#Parse file name
file_tags <- parse_file_name(dat_fil)
animal_id <- file_tags[[1]]
# skip file_tags[[2]]. It is the file_type.
genotype <- file_tags[[3]]
drug_concentration <- file_tags[[4]]
# drug_name <- UNSUPPORTED
drug_position <- file_tags[[5]]
calibration_current <- file_tags[[6]]
calibration_concentration <- file_tags[[7]]
# Read the coordinate file
coord <- fread(coord_fil_path)
# coord$T_Bkg1 <- coord$T_Bkg1 * 10 # Convert Igor start times.
# coord$T_Bkg2 <- coord$T_Bkg2 * 10 # Convert Igor start times.
# Read data. Electrode as current.
dat_current <- read_experiment_csv(dat_fil_path, sr = sample_rate)
# Read data. Electrode as concentration.
dat_concentration <- read_experiment_csv(dat_fil_path, sr = sample_rate)
dat_concentration <- current_to_concentration(dat_concentration,
calibration_current = calibration_current,
calibration_concentration = calibration_concentration)
# If new animal, reset stim counting, otherwise continue series.
if (animal_id != animal_id_last_file) {
max_stim_last_file <- 0
}
max_stim <- nrow(coord) + max_stim_last_file
dat_current_list <- list()
dat_concentration_list <- list()
# j points to the coordinate row
# j + max_stim_last_file equals the current stimulus
for (j in 1:nrow(coord)) {
stim <- max_stim_last_file + j
stim_start_time <- coord$T_Bkg1[j]
dat_start_idx <- which(round(dat_current$time_sec, 1) == round(coord$T_Bkg1[j], 1))
if (dat_start_idx > nrow(dat_current)) {
stop(paste0("Stimulus start overflows data: ", coord_fil,
" #", stim))
} else if (stim == max_stim) {
top_row_idx <- nrow(dat_current)
} else {
top_row_idx <- which(round(dat_current$time_sec, 1) == round(coord$T_Bkg1[(j + 1)], 1)) - 1
}
sr_s <- sample_rate * 10^-3
stim_time_sec <- seq(from = 0, by = sr_s,
length.out = nrow(dat_current[dat_start_idx:top_row_idx, ]))
one_stim_df <- as.data.frame(cbind(animal = animal_id, stimulus = stim,
stim_time_sec = stim_time_sec, genotype = genotype,
include = coord$include[j],
time_sec = dat_current[dat_start_idx:top_row_idx, 1],
electrode_current = dat_current[dat_start_idx:top_row_idx, 2],
electrode_concentration = dat_concentration[dat_start_idx:top_row_idx, 2]),
stringsAsFactors = FALSE)
one_stim_df$animal <- as.integer(one_stim_df$animal)
one_stim_df$stimulus <- as.integer(one_stim_df$stimulus)
one_stim_df$stim_time_sec <- as.double(one_stim_df$stim_time_sec)
one_stim_df$include <- as.logical(one_stim_df$include)
one_stim_df$time_sec <- as.double(one_stim_df$time_sec)
one_stim_df$electrode_current <- as.double(one_stim_df$electrode_current)
one_stim_df$electrode_concentration <- as.double(one_stim_df$electrode_concentration)
stim_df <- rbind(stim_df, one_stim_df)
}
# Before leaving file loop, remember which animal we just processed.
animal_id_last_file <- animal_id
max_stim_last_file <- max_stim
}
# # Analysis of NA
ok <- complete.cases(stim_df)
sum(!ok)
fwrite(x = stim_df, file = paste(input_dir, "stim_df.csv", sep = "/"))
# # WT - Pre-AMPH
# dat_merge_wt_pre <- select(stim_df, animal, stim_time_sec, electrode_concentration, genotype, stimulus, include) %>%
# filter(genotype == "wt" & stimulus >= 1 & stimulus <= 3 & include == TRUE & stim_time_sec <= 120) %>%
# group_by(stim_time_sec) %>%
# summarize(mean(electrode_concentration))
# dat_merge_wt_pre <- rename(dat_merge_wt_pre, time_sec = stim_time_sec, "electrode_concentration" = "mean(electrode_concentration)")
# qplot(dat_merge_wt_pre$time_sec, dat_merge_wt_pre$electrode_concentration, geom = "line")
# # WT - AMPH_06_10
# dat_merge_wt_amph_0610 <- select(stim_df, animal, stim_time_sec, electrode, genotype, stimulus, include) %>%
# filter(genotype == "wt" & stimulus >= 6 & stimulus <= 10 & include == TRUE & stim_time_sec <= 120) %>%
# group_by(stim_time_sec) %>%
# summarize(mean(electrode))
# dat_merge_wt_amph_0610 <- rename(dat_merge_wt_amph_0610, time_sec = stim_time_sec, "electrode" = "mean(electrode)")
# qplot(dat_merge_wt_amph_0610$time_sec, dat_merge_wt_amph_0610$electrode, geom = "line")
#
# # WT - AMPH_16_20
# dat_merge_wt_amph_1620 <- select(stim_df, animal, stim_time_sec, electrode, genotype, stimulus, include) %>%
# filter(genotype == "wt" & stimulus >= 16 & stimulus <= 20 & include == TRUE & stim_time_sec <= 120) %>%
# group_by(stim_time_sec) %>%
# summarize(mean(electrode))
# dat_merge_wt_amph_1620 <- rename(dat_merge_wt_amph_1620, time_sec = stim_time_sec, "electrode" = "mean(electrode)")
# qplot(dat_merge_wt_amph_1620$time_sec, dat_merge_wt_amph_1620$electrode, geom = "line")
#
# # KO - Pre-AMPH
# dat_merge_ko_pre <- select(stim_df, animal, stim_time_sec, electrode_concentration, genotype, stimulus, include) %>%
# filter(genotype == "ko" & stimulus >= 1 & stimulus <= 3 & include == TRUE & stim_time_sec <= 120) %>%
# group_by(stim_time_sec) %>%
# summarize(mean(electrode_concentration))
# dat_merge_ko_pre <- rename(dat_merge_ko_pre, time_sec = stim_time_sec, "electrode_concentration" = "mean(electrode_concentration)")
# qplot(dat_merge_ko_pre$time_sec, dat_merge_ko_pre$electrode_concentration, geom = "line")
#
# dat_merge_ko_pre <- select(stim_df, animal, stim_time_sec, electrode, genotype, stimulus, include) %>%
# filter(genotype == "ko" & stimulus >= 1 & stimulus <= 3 & include == TRUE & stim_time_sec <= 120) %>%
# group_by(stim_time_sec) %>%
# summarize(mean(electrode))
# dat_merge_ko_pre <- rename(dat_merge_ko_pre, time_sec = stim_time_sec, "electrode" = "mean(electrode)")
# qplot(dat_merge_ko_pre$time_sec, dat_merge_ko_pre$electrode, geom = "line")
#
# # KO - AMPH_06_10
# dat_merge_ko_amph_0610 <- select(stim_df, animal, stim_time_sec, electrode, genotype, stimulus, include) %>%
# filter(genotype == "ko" & stimulus >= 6 & stimulus <= 10 & include == TRUE & stim_time_sec <= 120) %>%
# group_by(stim_time_sec) %>%
# summarize(mean(electrode))
# dat_merge_ko_amph_0610 <- rename(dat_merge_ko_amph_0610, time_sec = stim_time_sec, "electrode" = "mean(electrode)")
# qplot(dat_merge_ko_amph_0610$time_sec, dat_merge_ko_amph_0610$electrode, geom = "line")
#
# # KO - AMPH_16_20
# dat_merge_ko_amph_1620 <- select(stim_df, animal, stim_time_sec, electrode, genotype, stimulus, include) %>%
# filter(genotype == "wt" & stimulus >= 16 & stimulus <= 20 & include == TRUE & stim_time_sec <= 120) %>%
# group_by(stim_time_sec) %>%
# summarize(mean(electrode))
# dat_merge_ko_amph_1620 <- rename(dat_merge_ko_amph_1620, time_sec = stim_time_sec, "electrode" = "mean(electrode)")
# qplot(dat_merge_ko_amph_1620$time_sec, dat_merge_ko_amph_1620$electrode, geom = "line")
#
# # Plot and compile results.
# results <- data.frame(genotype = character(),
# amphetamine = character(),
# release = double(),
# vmax = double(),
# km = double(),
# stringsAsFactors = FALSE)
#
# # Constants
# pulses <- 30
# pulse_freq <- 50
# bin_size <- 2.0
# electrode_distance <- 1000
# dead_space_distance <- 4
# diffusion_coefficient <- 2.7 * 10^-6
# convert_current <- FALSE
# fit_region = "fall"
#
# # WT - Pre-AMPH
#
# # Variables
# genotype <- "WT"
# amphetamine <- "PRE"
# release <- 2.25
# vmax <- 4.8
# km <- 5
# base_tolerance <- 0.05
# plot_duration_sec = 18
#
# if (nrow(results[results$genotype == genotype & results$amphetamine == amphetamine, ]) == 0) {
# results[(nrow(results)+1), ] <- c(genotype, amphetamine, release, vmax, km)
# } else {
# results[results$genotype == genotype &
# results$amphetamine == amphetamine, ] <- cbind(genotype, amphetamine, release, vmax, km)
# }
#
# compare_pulse(dat = dat_merge_wt_pre, fil = "Wild Type - Pre-AMPH",
# vmax = vmax, km = km,
# pulses = pulses,
# pulse_freq = pulse_freq,
# release = release,
# bin_size = bin_size,
# electrode_distance = electrode_distance,
# dead_space_distance = dead_space_distance,
# diffusion_coefficient = diffusion_coefficient,
# convert_current = convert_current,
# fit_region = fit_region,
# base_tolerance = base_tolerance,
# plot_duration_sec = plot_duration_sec)
#
# # WT - Post-AMPH 6-10
#
# # Variables
# genotype <- "WT"
# amphetamine <- "POST_06-10"
# release <- 5.5
# vmax <- 4.8
# km <- 24
# base_tolerance <- 0.05
# plot_duration_sec = 50
#
# if (nrow(results[results$genotype == genotype & results$amphetamine == amphetamine, ]) == 0) {
# results[(nrow(results)+1), ] <- c(genotype, amphetamine, release, vmax, km)
# } else {
# results[results$genotype == genotype &
# results$amphetamine == amphetamine, ] <- cbind(genotype, amphetamine, release, vmax, km)
# }
#
# compare_pulse(dat = dat_merge_wt_amph_0610, fil = "Wild Type - Post-AMPH 06-10",
# vmax = vmax, km = km,
# pulses = pulses,
# pulse_freq = pulse_freq,
# release = release,
# bin_size = bin_size,
# electrode_distance = electrode_distance,
# dead_space_distance = dead_space_distance,
# diffusion_coefficient = diffusion_coefficient,
# convert_current = convert_current,
# fit_region = fit_region,
# base_tolerance = base_tolerance,
# plot_duration_sec = plot_duration_sec)
#
# # WT - Post-AMPH 16-20
#
# # Variables
# genotype <- "WT"
# amphetamine <- "POST_16-20"
# release <- 4.3
# vmax <- 4.8
# km <- 24
# base_tolerance <- 0.05
# plot_duration_sec = 50
#
# if (nrow(results[results$genotype == genotype & results$amphetamine == amphetamine, ]) == 0) {
# results[(nrow(results)+1), ] <- c(genotype, amphetamine, release, vmax, km)
# } else {
# results[results$genotype == genotype &
# results$amphetamine == amphetamine, ] <- cbind(genotype, amphetamine, release, vmax, km)
# }
#
# compare_pulse(dat = dat_merge_wt_amph_1620, fil = "Wild Type - Post-AMPH 16-20",
# vmax = vmax, km = km,
# pulses = pulses,
# pulse_freq = pulse_freq,
# release = release,
# bin_size = bin_size,
# electrode_distance = electrode_distance,
# dead_space_distance = dead_space_distance,
# diffusion_coefficient = diffusion_coefficient,
# convert_current = convert_current,
# fit_region = fit_region,
# base_tolerance = base_tolerance,
# plot_duration_sec = plot_duration_sec)
#
# # ----------------- END OF WILD TYPE -----------------#
#
# # ----------------- BEGIN KNOCKOUT -----------------#
#
# # KO - Pre-AMPH
#
# # Variables
# genotype <- "KO"
# amphetamine <- "PRE"
# release <- 1.77
# vmax <- 4.8
# km <- 5
# base_tolerance <- 0.05
# plot_duration_sec = 10
#
# if (nrow(results[results$genotype == genotype & results$amphetamine == amphetamine, ]) == 0) {
# results[(nrow(results)+1), ] <- c(genotype, amphetamine, release, vmax, km)
# } else {
# results[results$genotype == genotype &
# results$amphetamine == amphetamine, ] <- cbind(genotype, amphetamine, release, vmax, km)
# }
#
# compare_pulse(dat = dat_merge_ko_pre, fil = "Knockout - Pre-AMPH",
# vmax = vmax, km = km,
# pulses = pulses,
# pulse_freq = pulse_freq,
# release = release,
# bin_size = bin_size,
# electrode_distance = electrode_distance,
# dead_space_distance = dead_space_distance,
# diffusion_coefficient = diffusion_coefficient,
# convert_current = convert_current,
# fit_region = fit_region,
# base_tolerance = base_tolerance,
# plot_duration_sec = plot_duration_sec)
#
# # KO - Post-AMPH 6-10
#
# # Variables
# genotype <- "KO"
# amphetamine <- "POST_06-10"
# release <- 3.8
# vmax <- 4.8
# km <- 24
# base_tolerance <- 0.05
# plot_duration_sec = 30
#
# if (nrow(results[results$genotype == genotype & results$amphetamine == amphetamine, ]) == 0) {
# results[(nrow(results)+1), ] <- c(genotype, amphetamine, release, vmax, km)
# } else {
# results[results$genotype == genotype &
# results$amphetamine == amphetamine, ] <- cbind(genotype, amphetamine, release, vmax, km)
# }
#
# compare_pulse(dat = dat_merge_ko_amph_0610, fil = "Knockout - Post-AMPH 06-10",
# vmax = vmax, km = km,
# pulses = pulses,
# pulse_freq = pulse_freq,
# release = release,
# bin_size = bin_size,
# electrode_distance = electrode_distance,
# dead_space_distance = dead_space_distance,
# diffusion_coefficient = diffusion_coefficient,
# convert_current = convert_current,
# fit_region = fit_region,
# base_tolerance = base_tolerance,
# plot_duration_sec = plot_duration_sec)
#
# # KO - Post-AMPH 16-20
#
# # Variables
# genotype <- "KO"
# amphetamine <- "POST_16-20"
# release <- 4.3
# vmax <- 4.8
# km <- 24
# base_tolerance <- 0.05
# plot_duration_sec = 50
#
# if (nrow(results[results$genotype == genotype & results$amphetamine == amphetamine, ]) == 0) {
# results[(nrow(results)+1), ] <- c(genotype, amphetamine, release, vmax, km)
# } else {
# results[results$genotype == genotype &
# results$amphetamine == amphetamine, ] <- cbind(genotype, amphetamine, release, vmax, km)
# }
#
# compare_pulse(dat = dat_merge_ko_amph_1620, fil = "Knockout - Post-AMPH 16-20",
# vmax = vmax, km = km,
# pulses = pulses,
# pulse_freq = pulse_freq,
# release = release,
# bin_size = bin_size,
# electrode_distance = electrode_distance,
# dead_space_distance = dead_space_distance,
# diffusion_coefficient = diffusion_coefficient,
# convert_current = convert_current,
# fit_region = fit_region,
# base_tolerance = base_tolerance,
# plot_duration_sec = plot_duration_sec)
#
# results
#
# dat <- select(stim_df, animal, stim_time_sec, time_sec, electrode_concentration, electrode_current, genotype, stimulus, include) %>%
# filter(animal == 1902051)
# # group_by(stim_time_sec) %>%
# # summarize(mean(electrode_concentration))
# dat_merge_ko_pre <- rename(dat_merge_ko_pre, time_sec = stim_time_sec, "electrode_concentration" = "mean(electrode_concentration)")
# qplot(dat_merge_ko_pre$time_sec, dat_merge_ko_pre$electrode_concentration, geom = "line")
#
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