<html><head><meta http-equiv="Content-Type" content="text/html charset=utf-8"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class="">Hi Laura,<div class=""><br class=""></div><div class="">We’re actually working on this issue right now. You can follow the pull request: <a href="https://github.com/mne-tools/mne-python/pull/1931" class="">https://github.com/mne-tools/mne-python/pull/1931</a>. Essentially, you will be able to load headshape points, and other digitization points, compute a device-to-head transformation, and apply it to existing raw files.</div><div class=""><br class=""></div><div class="">HTH,</div><div class="">Teon </div><div class=""><br class=""><div><blockquote type="cite" class=""><div class="">On Apr 20, 2015, at 6:46 AM, Laura Elizabeth Gwilliams <<a href="mailto:laura.gwilliams@nyu.edu" class="">laura.gwilliams@nyu.edu</a>> wrote:</div><br class="Apple-interchange-newline"><div class=""><div dir="ltr" class="">Dear All,<div class=""><br class=""></div><div class="">I am trying to use MNE-Python to preprocess MEG data from a CTF scanner. Using MNE binaries I have been able to use ctf2fiff to convert the raw data file into a .fif file; however, this method does not support loading the headshape information alongside the raw data (as with kit2fiff, for example).</div><div class=""><br class=""></div><div class="">My question is whether I can somehow load the headshape.txt and add this to the information dict of the raw data .fif? The ultimate goal is to allow me to co-register and continue with source analysis.</div><div class=""><br class=""></div><div class="">Thank you for your help,</div><div class="">Laura.<br clear="all" class=""><div class=""><br class=""></div>-- <br class=""><div class="gmail_signature"><div dir="ltr" class=""><div dir="ltr" class=""><div dir="ltr" class=""><div dir="ltr" class=""><div class="">Neuroscience of Language Lab<br class=""></div><div class="">New York University Abu Dhabi</div><div class="">Computational Research Building (A2 - 008)</div><div class="">PO BOX: 129188</div><div class="">Office Tel.: +971 262 85345</div><div class=""><a href="http://lauragwilliams.github.io/index.html" target="_blank" class="">http://lauragwilliams.github.io/index.html</a></div></div></div></div></div></div>
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