inst/extdata/real/script.R

In shaliulab/idocr: Analyze traces created in the Individual Drosophila Optogenetics Conditioner (IDOC)

test_that("idocr deals with tibble error", {
  
  experiment_folder <- system.file(
#    "extdata/2021-04-11_17-59-00", package = pkg_name,
    "extdata/real", package = pkg_name,
    mustWork = TRUE
  )
  
  treatment_A <- "OCT"
  treatment_B <- "MCH+ES"
  
  # leave this empty or fill something relevant for the experiment
  # it will appear in the subtitle of the plot
  # (below the big title)
  description <- "Enter a description here"
  
  # Minimal number of exits required to consider the data
  # of one animal significant and then compute a index from it
  min_exits_required <- 3
  
  # Apply a time offset to the treatment time series
  # to account for the time it takes for odour to
  # arrive to the chambers
  # Units in seconds
  delay <- 5
  
  
  #### Probably you dont want to change this
  #### Please change these numbers only if you know what you are doing
  
  # Define a distance from the center of the chamber
  # to the decision zone
  # Units in mm
  border_mm <- 5
  
  # Behavioral masking
  # Ignore exits happening this amount of seconds
  # after the previous exit
  # to avoid counting the same exit 
  # as two exits happening within ridiculously little time  
  mask_duration <- 1
  
  # Analysis mask
  # This is a list of numeric vectors of length 2
  # The name of the vector should represent some block or interval of your experiment
  # i.e. pre conditioning, post conditioning, etc
  # The vector should delimit the start and end time of the block in seconds
  # Passing this argument to idocr() will cause R to generate a subfolder
  # in the experiment data folder, for each element in the list
  # The folder will have the name of the element in the list
  # e.g. this list will create a subfolder called EVENT1 and another called EVENT2
  # Each of them will contain a pdf and png version of the plot but only the interval
  # when the mask is active is analyzed. It is marked accordingly on the plot
  # Moreover, you get SUMMARY and PI .csv files
  analysis_mask <- list(
    PRE_1 = c(60, 120),
    PRE_2 = c(180, 240)
  )                    
  
  
  ##################################################
  # CAUTION!! DONT CHANGE ANY CODE BELOW THIS LINE
  ##################################################
  
  treatments <- c(
    TREATMENT_A = treatment_A,
    TREATMENT_B = treatment_B
  )
  
  
  src_file <- rstudioapi::getActiveDocumentContext()$path
  
  p1 <- idocr(experiment_folder = experiment_folder,
              treatments = treatments,
              border_mm = border_mm,
              min_exits_required = min_exits_required,
              src_file = src_file,
              subtitle = description,
              delay = delay,
              # analysis_mask = analysis_mask,
              mask_duration = mask_duration
  )
  
  export_summary(experiment_folder = experiment_folder)
  
})