scripts/stim_df_dead_space_avg2.R

In pnojai/rwalk: Random Walk Model of Neurotransmitter Release and Uptake

# library(dplyr)
# library(ggplot2)
# library(data.table)
# 
# # Global variables
# pipeline_dir <- "/media/sf_OneDrive_-_cumc.columbia.edu/rwalk/pipeline"
# input_dir <- paste(pipeline_dir, "06_Library", sep = "/")# WT - Pre-AMPH
# output_dir <- paste(pipeline_dir, "output", "plots", sep = "/")
# dat_fil <- "stim_df.csv"
# params_fil <- "dead_space_avg_params2.csv"
# dead_space_fil <- "dead_space_avg_by_animal_params.csv"
# 
# # Plotting variables
# pulses <- 30
# pulse_freq <- 50
# bin_size <- 2.0
# electrode_distance <- 1000
# diffusion_coefficient <- 2.7 * 10^-6
# convert_current <- FALSE
# fit_region = "fall"
# 
# # Read data and plot parameters
# stim_df <- fread(paste(input_dir, dat_fil, sep = "/"))
params <- fread(paste(input_dir, params_fil, sep = "/"))
dead_space <- fread(paste(input_dir, dead_space_fil, sep ="/"))

# Pick off the complete parameters for plotting.
complete_params <- complete.cases(params) & params$include == "TRUE"
plot_params <- params[complete_params, ]

for (i in 1:nrow(plot_params)) {
#for (i in 20:20) {
        # Variables
        an_animal <- plot_params$animal[i]
        stim_low <- plot_params$stim_low[i]
        stim_high <- plot_params$stim_high[i]
        release <-plot_params$release[i] 
        vmax <- plot_params$vmax[i]
        km <- plot_params$km[i]
        dead_space_distance <- dead_space[animal == an_animal, "dead_space_distance"]
        base_tolerance <- plot_params$base_tolerance[i]
        plot_duration_sec <- plot_params$plot_duration_sec[i]        
        
        dat_fit <- select(stim_df, animal, stim_time_sec, electrode_concentration, genotype, stimulus, include) %>%
                filter(animal == an_animal & stimulus >= stim_low & stimulus <= stim_high & include == TRUE & stim_time_sec <= 120) %>%
                group_by(stim_time_sec) %>%
                summarize(mean(electrode_concentration))
        dat_fit <- rename(dat_fit, time_sec = stim_time_sec, "electrode" = `mean(electrode_concentration)`)
        
        compare_pulse(dat = dat_fit, fil = paste0(an_animal, " ", plot_params$genotype[i],
                                                  " Stim range = ", stim_low, ":", stim_high),
                      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,
                      dead_space = dead_space_distance)
        
        # Copy the plot from the screen device to the file device.
        fil_name <- paste0(output_dir, "/", an_animal, "_",
                           plot_params$genotype[i], "_stim_",
                           stim_low, "_", stim_high, ".jpg")
        # dev.copy(jpeg, file = fil_name)
        # dev.off() # Don't forget!        
}

# Review stimuli
# animal_review <- an_animal
# dat_review <- stim_df %>%
#         filter(animal == animal_review & stimulus >= 1 & stimulus <= 3 & include == TRUE)
# qplot(data = dat_review, x = time_sec, y = electrode_concentration, geom = "line")
# stim_review <- 2
# dat_review_stim <- dat_review[dat_review$stimulus == stim_review & dat_review$stim_time_sec < 30, ]
# qplot(data = dat_review_stim, x = stim_time_sec, y = electrode_concentration, geom = "line")