<html><body><div style="font-family: arial, helvetica, sans-serif; font-size: 12pt; color: #000000"><div> apparently there seems to be a way of using in-house pymvpa tools to do representational similarity of spatio-temporal events</div><div>  <br>(i) segment my timeseries data  <span style="font-size: 12pt;" data-mce-style="font-size: 12pt;">into the relevant spatio-temporal events with  'extract_boxcar_event_samples'</span></div><div><span style="font-size: 12pt;" data-mce-style="font-size: 12pt;"><br data-mce-bogus="1"></span></div><div><div>(ii)  flat the space-time matrices to plain vectors (as reccomended before in this post)<br></div></div><div><br data-mce-bogus="1"></div><div>(iii) set these to 'chunks' for the subsequent RSA analyis<br><br>(iii) run 'rsa.PDist' on those vectors</div><div><br>this approach would tell me the extent to which  my ROI is modulated by spatio-temporal features of my stimulus<br><br></div><div>does this sonds right?</div><div><br data-mce-bogus="1"></div><div>thanks!</div><div><br data-mce-bogus="1"></div><div>david</div><hr id="zwchr" data-marker="__DIVIDER__"><div data-marker="__HEADERS__"><b>From: </b>"David Soto" <d.soto@bcbl.eu><br><b>To: </b>"Development and support of PyMVPA" <pkg-exppsy-pymvpa@lists.alioth.debian.org><br><b>Sent: </b>Friday, October 28, 2016 11:24:07 PM<br><b>Subject: </b>Re: [pymvpa] correlation between 2 matrices<br></div><div><br></div><div data-marker="__QUOTED_TEXT__"><div style="font-family: arial, helvetica, sans-serif; font-size: 12pt; color: #000000;" data-mce-style="font-family: arial, helvetica, sans-serif; font-size: 12pt; color: #000000;"><div>thanks that is useful, however to clarify I meant it to be in the context of a representational similarity analyses</div><div>so would this solution be similar option 7  in here ? http://www.pymvpa.org/generated/mvpa2.measures.rsa.pdist.html</div><div>how about if I wanted to use a euclidean distance? not sure it could handle 2 spatio-temporal matrices </div><div>best</div><div>david</div><br><hr id="zwchr"><div><b>From: </b>"Brian Murphy" <brian.murphy@qub.ac.uk><br><b>To: </b>"Development and support of PyMVPA" <pkg-exppsy-pymvpa@lists.alioth.debian.org><br><b>Sent: </b>Friday, October 28, 2016 9:58:45 PM<br><b>Subject: </b>Re: [pymvpa] correlation between 2 matrices<br></div><br><div><p>If I understand your query correctly, I think numpy could do it,
      first by flattening the matrices to simple vectors, and then
      calculating the correlation between those, e.g.</p>
    <p>np.corrcoef(np.array(matrix1).flatten(),
      np.array(matrix2).flatten())</p>
    <p>... assuming you're using the matrix datatype. If they are
      vanilla 2D arrays, then you shouldn't need to recast:<br>
    </p>
    <p>np.corrcoef(matrix1.flatten(), matrix2.flatten())</p>
    <p>best,</p>
    <p>Brian</p>
    <p><br>
    </p>
    <div class="moz-cite-prefix">On 28/10/16 20:44, David Soto wrote:<br>
    </div>
    <blockquote cite="mid:CAPeRSSW8gGwdwkyZfbq2S2MCzfN2+=V5aWBSVZc7yR012FVVEQ@mail.gmail.com">
      
      <div dir="ltr">
        <div class="gmail_default" style="font-family: garamond,serif; font-size: large; color: #000000;" data-mce-style="font-family: garamond,serif; font-size: large; color: #000000;">hi, </div>
        <div class="gmail_default" style="font-family: garamond,serif; font-size: large; color: #000000;" data-mce-style="font-family: garamond,serif; font-size: large; color: #000000;"><br>
        </div>
        <div class="gmail_default" style="font-family: garamond,serif; font-size: large; color: #000000;" data-mce-style="font-family: garamond,serif; font-size: large; color: #000000;">I
          wonder whether PyMVPA can compute a similarity index
          (correlation) between two 2D matrices, each comprised of 12
          seconds & 300 voxels?</div>
        <div class="gmail_default" style="font-family: garamond,serif; font-size: large; color: #000000;" data-mce-style="font-family: garamond,serif; font-size: large; color: #000000;"><br>
        </div>
        <div class="gmail_default" style="font-family: garamond,serif; font-size: large; color: #000000;" data-mce-style="font-family: garamond,serif; font-size: large; color: #000000;">thanks!</div>
        <div class="gmail_default" style="font-family: garamond,serif; font-size: large; color: #000000;" data-mce-style="font-family: garamond,serif; font-size: large; color: #000000;">david</div>
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    </blockquote>
    <br>
  

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