Generate classification image noise pattern based on set of stimuli (matrix: trials, parameters), responses (vector), and sinusoid

Generate classification image noise pattern based on set of stimuli (matrix: trials, parameters), responses (vector), and sinusoid

Usage

generateCINoise(stimuli, responses, p)

Arguments

stimuli

Matrix with one row per trial, each row containing the 4092 parameters for the original stimulus.

responses

Vector containing the response to each trial (1 if participant selected original, -1 if participant selected inverted; this can be changed into a scale).

p

3D patch matrix (generated using generateNoisePattern()).

Value

The classification image as pixel matrix.

Examples

p <- generateNoisePattern(img_size = 32, nscales = 1)
nparams <- max(p$patchIdx)

# two trials, one chosen original (1) and one inverted (-1)
stimuli <- matrix(runif(2 * nparams, -1, 1), nrow = 2)
responses <- c(1, -1)

ci <- generateCINoise(stimuli, responses, p)