generateCINoise: Generate classification image noise pattern based on set of...

In rcicr: Reverse-Correlation Image-Classification Toolbox

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

Description

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 parameter row per response. A parameter vector is also accepted for a single trial with exactly one response.
responses	Vector with the response to each trial: 1 where the participant chose the original, -1 where they chose the inverted image. Other values, such as ratings on a scale, weight the trials accordingly.
p	Noise basis, as returned by 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)

rcicr documentation built on Sept. 27, 2026, 5:07 p.m.