[Rcicr-users] Obtaining Noise Image

[Rodrigo Cardenas]

Thank you Ron and sorry for the confusion. The goal was to produce the
noise image that can be used with the stat4CI toolbox (although you
mentioned that I should not use that method). So, first I tried generating
the noise image with the code posted by Dan (image A):

data <- read.csv("rcicrData1.csv")

rdata <- 'rcicrdata.Rdata'

#### specific to image A #######
s <- generateNoisePattern(img_size = 512, pre_0.3.0 = TRUE)

noise <- generateCINoise(data$Face, data$correct, s)
image(noise)

#output grey scale image#
jpeg("Noise_imgA.jpg",
     width = 512, height = 512, units = "px")
par(mar = rep(0,4))
image(noise, axes=FALSE, col = grey(seq(0,1, length = 512)))
dev.off()


After reading your reply to Dan, I tried code with $ci

###### specific to image B #######
ci1 <- generateCI2IFC(data$Face, data$correct, baseimage1, rdata,
targetpath='./cis')
noise <- ci1$ci
jpeg("Noise_imgB.jpg",
     width = 512, height = 512, units = "px")
par(mar = rep(0,4))
image(noise, axes=FALSE, col = grey(seq(0,1, length = 512)))
dev.off()

Images A and B are not identical. Since I am not familiar with the
mechanics of the code, I was wandering which method is recommended for
generating the noise CI. Thank you for the reference, I will look further
into it.

All the best,

Rodrigo


On Mon, Aug 31, 2015 at 2:13 PM, Dotsch, R. (Ron) <R.Dotsch at uu.nl> wrote:

> Dear Rodrigo,
>
> I need more information to help you out. What is the code you use to
> generate the images? And which two images do you mean?
>
> With respect to using the stat4CI toolbox on sinusoid noise like I did in
> the SPPS paper: I would recommend not following the method I used as it is
> very unclear how to compute the z-scores with these noise patterns. A
> different approach to compute z-scores is given by
> http://dx.doi.org/10.3389/fpsyg.2013.00592, which I would recommend
> following.
>
> Best,
>
> Ron
>
> _____________________
> Ron Dotsch
> Associate Professor
> Department of Psychology
> Utrecht University
> http://ron.dotsch.org/
>
>
>
>
>
> On 31 Aug 2015, at 17:50, Rodrigo Cardenas <rodrigo.a.cardenas at gmail.com>
> wrote:
>
> Dear Ron,
>
> Thank you for your reply. I read your post and tried the code posted by
> Daniel as well as yours (someCI$ci), using my data. However, both images
> are not identical, so now I am wondering which one I should use. My goal is
> to generate a noise image that I can use for the analysis done with the
> matlab toolbox stat4CI, as described in Dotsch, R., & Todorov, A. (2012).
> Reverse correlating social face perception. Social Psychological and
> Personality Science, 3 (5), 562-571. Any help/guidance with this will be
> much appreciated.
>
> Best,
>
> Rodrigo
>
> On Sat, Aug 22, 2015 at 8:29 AM, Dotsch, R. (Ron) <R.Dotsch at uu.nl> wrote:
>
>> Hi Dan,
>>
>> This looks fine to me. If you have a ci object, for instance the output
>> of:
>>
>> someCI <- generateCI2IFC(…)
>>
>> you can get the raw noise in a 512x512 pixel matrix without base image
>> using:
>>
>> someCI$ci
>>
>> This is not well-documented yet, but you can rely on it (so does rcicr).
>>
>> Best,
>>
>> Ron
>>
>>
>> _____________________
>> Ron Dotsch
>> Associate Professor
>> Department of Psychology
>> Utrecht University
>> http://ron.dotsch.org/
>>
>>
>>
>> On 21 Aug 2015, at 17:48, Daniel Albohn <d.albohn at gmail.com> wrote:
>>
>> Hello,
>>
>> I am writing the listserv to get some feedback on how to obtain just a
>> noise image from a reverse correlation task (i.e., without the base image).
>> Through looking at the documentation, I believe this is possible, although
>> there are not many examples or supporting documents to confirm my
>> suspicious. As such, I wanted to make sure my code was actually giving me
>> what I want it to give me.
>>
>> ----R code----
>>
>> data <- read.csv("rcicrData1.csv")
>>
>> ##Apparently this is unneeded for creating just a noise image?##
>> n <- 'rcicrdata.Rdata'
>>
>> responses <- as.vector(data$correct)
>>
>> s <- generateNoisePattern(img_size = 512, pre_0.3.0 = TRUE)
>>
>> noise <- generateCINoise(data$Face, data$correct, s)
>> image(noise) #it's in color?
>>
>> ##output grey scale image##
>> jpeg("Noise_img.jpg",
>>      width = 512, height = 512, units = "px")
>> par(mar = rep(0,4))
>> image(noise, axes=FALSE, col = grey(seq(0,1, length = 512)))
>> dev.off()
>>
>> ---End Code---
>>
>> Any thoughts, suggestions, or critiques would be appreciated! Again, I am
>> looking to output a noise image from RC data, much like generating a CI,
>> but without the base image underneath.
>>
>> Thanks,
>> Dan
>>
>> --
>>
>> Daniel Albohn
>> Website <http://www.sites.psu.edu/albohn> | 484-332-7688
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