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Hi Rodrigo,
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<div class="">If you used a 2-images forced choice (2IFC) version, and you coded data$correct to be 1 for selecting the original and -1 for selecting the negative image, you should use generateCI2IFC(). </div>
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<div class="">Method A makes some assumptions; for instance the pre_0.3.0 parameter is set to True by Dan because he probably generated his stimuli with an earlier version of rcicr that had a bug in it. If you generated your stimuli with version 0.3.0 or later,
this will lead to different results. The generateCI2IFC() function automatically selects the right analysis by looking at the .RData file containing the stimulus information, so that method (method B) is indeed highly recommended.</div>
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<div class="">Best,</div>
<div class=""><br class="">
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<div class="">Ron</div>
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_____________________</div>
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Ron Dotsch<br class="">
Associate Professor<br class="">
Department of Psychology<br class="">
Utrecht University<br class="">
<a href="http://ron.dotsch.org/" class="">http://ron.dotsch.org/</a></div>
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<div class="">On 01 Sep 2015, at 22:40, Rodrigo Cardenas <<a href="mailto:rodrigo.a.cardenas@gmail.com" class="">rodrigo.a.cardenas@gmail.com</a>> wrote:</div>
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<div dir="ltr" class="">Thank you Ron and sorry for the confusion. The goal was to produce the noise image that can be used with the <span style="font-size: 12.8000001907349px;" class="">stat4CI toolbox</span><span style="font-size: 12.8000001907349px;" class=""> (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):</span>
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<div class="">data <- read.csv("rcicrData1.csv")</div>
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<div class="">rdata <- 'rcicrdata.Rdata'</div>
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<div class="">#### specific to image A #######</div>
<div class="">s <- generateNoisePattern(img_size = 512, pre_0.3.0 = TRUE)</div>
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<div class="">noise <- generateCINoise(data$Face, data$correct, s)</div>
<div class="">image(noise)</div>
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<div class="">#output grey scale image#</div>
<div class="">jpeg("Noise_imgA.jpg",</div>
<div class=""> width = 512, height = 512, units = "px")</div>
<div class="">par(mar = rep(0,4))</div>
<div class="">image(noise, axes=FALSE, col = grey(seq(0,1, length = 512)))</div>
<div class="">dev.off()</div>
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<div class="">After reading your reply to Dan, I tried code with $ci</div>
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<div class="">###### specific to image B #######</div>
<div class="">ci1 <- generateCI2IFC(data$Face, data$correct, baseimage1, rdata, targetpath='./cis')</div>
<div class="">noise <- ci1$ci</div>
<div class="">jpeg("Noise_imgB.jpg",</div>
<div class=""> width = 512, height = 512, units = "px")</div>
<div class="">par(mar = rep(0,4))</div>
<div class="">image(noise, axes=FALSE, col = grey(seq(0,1, length = 512)))</div>
<div class="">dev.off()</div>
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<div class="">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.<br class="">
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<div class="">All the best,</div>
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<div class="">Rodrigo</div>
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<div class="gmail_quote">On Mon, Aug 31, 2015 at 2:13 PM, Dotsch, R. (Ron) <span dir="ltr" class="">
<<a href="mailto:R.Dotsch@uu.nl" target="_blank" class="">R.Dotsch@uu.nl</a>></span> wrote:<br class="">
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<div style="word-wrap:break-word" class="">Dear Rodrigo,
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</div>
<div class="">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?</div>
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<div class="">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 <a href="http://dx.doi.org/10.3389/fpsyg.2013.00592" target="_blank" class="">http://dx.doi.org/10.3389/fpsyg.2013.00592</a>, which I would recommend following.</div>
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<div class="">Best,</div>
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<div class="">Ron</div>
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<div style="word-wrap:break-word" class="">_____________________</div>
<div style="word-wrap:break-word" class="">Ron Dotsch<br class="">
Associate Professor<br class="">
Department of Psychology<br class="">
Utrecht University<br class="">
<a href="http://ron.dotsch.org/" target="_blank" class="">http://ron.dotsch.org/</a></div>
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<div class="">On 31 Aug 2015, at 17:50, Rodrigo Cardenas <<a href="mailto:rodrigo.a.cardenas@gmail.com" target="_blank" class="">rodrigo.a.cardenas@gmail.com</a>> wrote:<br class="">
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<div dir="ltr" class="">Dear Ron,
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<div class="">Thank you for your reply. I read your post and tried the code posted by Daniel as well as yours (<span style="font-size:12.8000001907349px" class="">someCI$ci</span>), using my data. However, both images are not identical, so now I am wondering
which one I should use. My goal is to generate a noise image that I can use for the analysis done with<span style="font-size:12.8000001907349px" class=""> the matlab toolbox stat4CI, as described in Dotsch, R., & Todorov, A. (2012). Reverse correlating social
face perception. Social Psychological and Personality Science, 3 (5), 562-571. Any help/guidance with this will be much appreciated.</span></div>
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</span></div>
<div class=""><span style="font-size:12.8000001907349px" class="">Best,</span></div>
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<div class=""><span style="font-size:12.8000001907349px" class="">Rodrigo</span></div>
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<div class="gmail_extra"><br class="">
<div class="gmail_quote">On Sat, Aug 22, 2015 at 8:29 AM, Dotsch, R. (Ron) <span dir="ltr" class="">
<<a href="mailto:R.Dotsch@uu.nl" target="_blank" class="">R.Dotsch@uu.nl</a>></span> wrote:<br class="">
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<div style="word-wrap:break-word" class="">Hi Dan,
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<div class="">This looks fine to me. If you have a ci object, for instance the output of:</div>
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<div class="">someCI <- generateCI2IFC(…) </div>
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<div class="">you can get the raw noise in a 512x512 pixel matrix without base image using:</div>
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<div class="">someCI$ci</div>
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</div>
<div class="">This is not well-documented yet, but you can rely on it (so does rcicr).</div>
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<div class="">Best,</div>
<div class=""><br class="">
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<div class="">Ron</div>
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_____________________</div>
<div style="letter-spacing:normal;text-align:start;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;word-wrap:break-word" class="">
Ron Dotsch<br class="">
Associate Professor<br class="">
Department of Psychology<br class="">
Utrecht University<br class="">
<a href="http://ron.dotsch.org/" target="_blank" class="">http://ron.dotsch.org/</a></div>
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<div class="">On 21 Aug 2015, at 17:48, Daniel Albohn <<a href="mailto:d.albohn@gmail.com" target="_blank" class="">d.albohn@gmail.com</a>> wrote:</div>
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<div class="">Hello,<br class="">
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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.<br class="">
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----R code----<br class="">
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data <- read.csv("rcicrData1.csv")<br class="">
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<div class="">##Apparently this is unneeded for creating just a noise image?##<br class="">
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<div class="">n <- 'rcicrdata.Rdata'<br class="">
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responses <- as.vector(data$correct)<br class="">
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s <- generateNoisePattern(img_size = 512, pre_0.3.0 = TRUE)<br class="">
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noise <- generateCINoise(data$Face, data$correct, s)<br class="">
image(noise) #it's in color?<br class="">
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<div class="">##output grey scale image##<br class="">
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<div class="">jpeg("Noise_img.jpg",<br class="">
width = 512, height = 512, units = "px")<br class="">
par(mar = rep(0,4))<br class="">
image(noise, axes=FALSE, col = grey(seq(0,1, length = 512)))<br class="">
dev.off()<br class="">
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---End Code---<br class="">
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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.<br class="">
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Thanks,<br class="">
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Dan<br clear="all" class="">
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Daniel Albohn<br class="">
<div class=""><a href="http://www.sites.psu.edu/albohn" target="_blank" class="">Website</a> |
<a href="tel:484-332-7688" value="+14843327688" target="_blank" class="">484-332-7688</a></div>
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