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

library(knitr)
library(ggplot2)
library(openxlsx)
library(dplyr)
library(rwalk)

opts_knit$set(root.dir = "/media/sf_Computing/RProg/Columbia/rwalk")
input_dir <- "./input"           # Input directory, on GitHub
par_dir <- "./scripts"           # File params need a trackable directory

Read parameters

# File parameters, on GitHub
fil_params_all <- read.xlsx(paste(par_dir, "file_params.xlsx", sep = "/"))
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")])
fil_not_exists <- sum(!file.exists(paste(input_dir, fils$filename, sep = "/")))
if (fil_not_exists) {stop("Input file not found")}

Files

print(fils$filename)

Merge data

```r stim_df <- data.frame(animal = character(), stimulus = integer(), stim_time_sec = double(), genotype = character(), include = logical(), time_sec = double(), electrode = integer())

for (i in 1:(nrow(fils) - 0)) { print(fils[i, "filename"])

    dat <- read_experiment_csv(paste(input_dir, fils[i, "filename"], sep = "/"),
                               sr = fils[i, "sample_rate"])

    if (fils[i, "convert_current"] == TRUE) {
            dat <- current_to_concentration(dat, calibration_current = fils[i, "calibration_current"],
                                            calibration_concentration = fils[i, "calibration_concentration"])
    }

    fil_params_cur <- fil_params_all[fil_params_all$filename == fils[i, "filename"], ]
    # dat_list <- list()
    max_stim <- max(fil_params_cur$stimulus)

    for (j in seq_along(fil_params_cur$stimulus)) {
            start_idx <- fil_params_cur$start[j] # start_idx <- fil_params_cur[fil_params_cur$stimulus == stim, "start"]
            if (start_idx > nrow(dat)) {
                    stop("Stimulus start overflows data")

            } else if (fil_params_cur$stimulus[j] == max_stim) {
                    top_row_idx <- nrow(dat)
            } else {
                    top_row_idx <- fil_params_cur$start[(j + 1)] -1 # , "start"] - 1 # fil_params_cur[fil_params_cur$stimulus == (stim + 1), "start"] - 1
            }

            #dat_list[[stim]] <- dat[start_idx:top_row_idx, ] # Don't really need the list

            sr_s <- fil_params_cur$sample_rate * 10^-3

            stim_time_sec <- seq(from = 0, by = sr_s,
                                 length.out = nrow(dat[start_idx:top_row_idx, ]))

            one_stim_df <- cbind(animal = fils[i, "animal"], stimulus = fil_params_cur$stimulus[j],
                                 stim_time_sec = stim_time_sec, genotype = fils[i, "genotype"],
                                 include = fil_params_cur$include[j], #fil_params_cur[fil_params_cur$stimulus == stim, "include"],
                                 dat[start_idx:top_row_idx, ])

            stim_df <- rbind(stim_df, one_stim_df)
    }