<div dir="ltr">Hi Mads,<div><br></div><div><div class="gmail_extra">Which version of sklearn are you using?</div><div class="gmail_extra">Do you use the decim parameter for ICA?</div><div class="gmail_extra">How do axactly do you use ICA?</div><div class="gmail_extra">50GB of memory is unexpected, it would mean that you make up to 10 copies of your data.</div><div class="gmail_extra"><br></div><div class="gmail_extra"><br></div><div class="gmail_extra"><div class="gmail_quote">On Wed, Nov 25, 2015 at 3:24 PM, Mads Jensen <span dir="ltr"><<a href="mailto:mje.mads@gmail.com" target="_blank">mje.mads@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">Hi all,<br>
<br>
I would like to hear what people do to filter and run ICA and if there<br>
is any advise.<br>
<br>
We usually have around an hour of recording which gives ~4.5 to 5GB of<br>
raw fiff files. First filtering and then running ICA in MNE-python<br>
requires a lot of memory, sometimes as much as 50GB. So, I fairly often<br>
get a memory error.<br>
<br>
I would prefer not to downsample at this stage in the process. So, I<br>
kindly ask if anybody has any thoughts and/or practises to avoid very<br>
heavy memory use.<br>
<br>
best wishes,<br>
mads<br>
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