Generates multiple classification images by participant or condition

Generate classification image for any reverse correlation task that displays independently generated alternatives.

Usage

batchGenerateCI(
  data,
  by,
  stimuli,
  responses,
  baseimage,
  rdata,
  save_as_png = TRUE,
  targetpath,
  label = "",
  antiCI = FALSE,
  scaling = "autoscale",
  constant = 0.1
)

Arguments

data

Data frame

by

String specifying column name that specifies the smallest unit (participant, condition) to subset the data on and calculate CIs for.

stimuli

String specifying column name in data frame that contains the stimulus numbers of the presented stimuli.

responses

String specifying column name in data frame that contains the responses coded 1 for original stimulus selected and -1 for inverted stimulus selected.

baseimage

String specifying which base image was used. Not the file name, but the key used in the list of base images at time of generating the stimuli.

rdata

String pointing to .RData file that was created when stimuli were generated. This file contains the contrast parameters of all generated stimuli.

save_as_png

Boolean stating whether to additionally save the CI as PNG image.

targetpath

String specifying the directory to save PNGs to. Required when save_as_png = TRUE; there is no default path. It is created if it does not exist. Use tempdir() if you only want to try the function out.

label

Optional string to insert in file names of PNGs to make them easier to identify.

antiCI

Optional boolean specifying whether antiCI instead of CI should be computed.

scaling

Optional string specifying scaling method: none, constant, independent or autoscale (default).

constant

Optional number specifying the value used as constant scaling factor for the noise (only works for scaling='constant').

Value

List of classification image data structures (which are themselves lists of pixel matrix of classification noise only, scaled classification noise only, base image only and combined).

Details

This function saves the classification images by participant or condition as PNG to a folder and returns the CIs.

Examples

# a synthetic square grayscale image stands in for a real base face photo
base_face <- tempfile(fileext = ".png")
png::writePNG(matrix(runif(32 * 32), 32, 32), base_face)

stimulus_path <- tempdir()
generateStimuli2IFC(
  base_face_files = list(face = base_face),
  n_trials = 6,
  img_size = 32,
  stimulus_path = stimulus_path,
  seed = 1,
  ncores = 1,
  nscales = 1,
  save_as_png = FALSE
)
#> 
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rdata_file <- list.files(stimulus_path, pattern = "\\.Rdata$", full.names = TRUE)[1]

# two "participants", three trials each
data <- data.frame(
  participant = rep(c("p1", "p2"), each = 3),
  stimulus = 1:6,
  response = sample(c(1, -1), 6, replace = TRUE)
)

cis <- suppressWarnings(batchGenerateCI(
  data = data, by = "participant", stimuli = "stimulus", responses = "response",
  baseimage = "face", rdata = rdata_file, save_as_png = FALSE
))
#> 
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  |======================================================================| 100%Using scaling factor constant:0.182416456662573
#>