<div dir="ltr">To simply trim out all +/-150 uV, for sample, from all channel all dataponts, use trimOutlier.<div><a href="http://sccn.ucsd.edu/wiki/Plugin_list_process">http://sccn.ucsd.edu/wiki/Plugin_list_process</a><br>
</div><div><br></div><div>Makoto</div></div><div class="gmail_extra"><br><br><div class="gmail_quote">2014-04-09 13:10 GMT-07:00 Jason Palmer <span dir="ltr"><<a href="mailto:japalmer29@gmail.com" target="_blank">japalmer29@gmail.com</a>></span>:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">Dear Tatu,<br>
<br>
Apparently that data is causing a "stack overflow", which can occur with<br>
large datasets using the Windows version (which forces a maximum stack<br>
size). It may be just small enough with the block of data removed. However,<br>
since it also contains large artifacts, this probably contributes to the<br>
need for addition stack resources. The Mac and Linux versions should not<br>
have this issue.<br>
<br>
I typically remove large artifacts before running ICA by simply detecting<br>
timepoints where the potential magnitude is greater than say  150uV, and use<br>
pop_select.m to remove them. Or if the boundary events are always at the<br>
beginning/end, or known locations, you can use pop_select to remove them as<br>
well. Or you could search for boundary events and remove continuous section<br>
around the boundaries.<br>
<br>
FYI, I usually remove bad channels with simple heuristics, do average<br>
reference, Â and high-pass filter above 1 Hz as the remaining pre-processing.<br>
<br>
Best,<br>
Jason<br>
<div class="HOEnZb"><div class="h5"><br>
-----Original Message-----<br>
From: <a href="mailto:eeglablist-bounces@sccn.ucsd.edu">eeglablist-bounces@sccn.ucsd.edu</a><br>
[mailto:<a href="mailto:eeglablist-bounces@sccn.ucsd.edu">eeglablist-bounces@sccn.ucsd.edu</a>] On Behalf Of Tatu Huovilainen<br>
Sent: Wednesday, April 09, 2014 1:47 AM<br>
To: <a href="mailto:eeglablist@sccn.ucsd.edu">eeglablist@sccn.ucsd.edu</a><br>
Subject: [Eeglablist] AMICA on semicontinuous data<br>
<br>
Hello EEGlab community,<br>
<br>
I'm still somewhat new to EEGlab, but the features and their documentation<br>
have made it really easy to hop on. Still, I've run into a problem I don't<br>
have the knowhow to solve and the documentation on it is pretty scarce.<br>
<br>
I'm using AMICA for cleaning the data, which works unbelievably well by the<br>
way, but I've learned that if there's even one boundary event in the data<br>
the program crashes. This is problematic as some of the blocks I'm trying to<br>
run ICA on have some ~10 second windows with huge artefacts that have to be<br>
removed. Below is an output of the AMICA command. It's from a block that<br>
without a removed part would run through perfectly well.<br>
<br>
Has anyone encountered this before, and is there maybe some simple<br>
workaround I don't see?<br>
<br>
Any advice would be appreciated. Thank you in advance!<br>
<br>
-Tatu<br>
<br>
(Using Matlab R2012a & EEGlab 13.1.1<br>
[ EEG.icaweights, EEG.icasphere, mods ] = runamica12(<br>
EEG.data(chanInd('EEG'),:) ); Â %%% The chanInd('EEG') just returns a list of<br>
channels of the type.<br>
The system cannot find the path specified.<br>
The system cannot find the path specified.<br>
The system cannot find the path specified.<br>
No recognized parallel environment found. Run qconf -spl to get a list of<br>
available environments and use keyword use_pe.<br>
Running locally with maximum of 4 threads.<br>
Writing data file: D:\Tatu\AMICATMP\tmpdata61471.fdt<br>
      1 processor name = XXXXXX<br>
      1 host_num =  1376903278<br>
 This is MPI process      1 of      1 ; I am process      1<br>
of<br>
      1 on node: XXXXXX %Post removed, probably no need..<br>
      1  : node root process      1 of      1<br>
Processing arguments ...<br>
 num_files =       1<br>
 FILES:<br>
 D:\Tatu\AMICATMP\tmpdata61471.fdt<br>
 num_dir_files =       1<br>
 initial matrix block_size =      256<br>
 do_opt_block =       0<br>
 number of models =       1<br>
 number of density mixture components =       3<br>
 pdf type =       0<br>
 max_iter =     2000<br>
 num_samples =       1<br>
 data_dim =      134<br>
 field_dim =    382975<br>
 do_history =       0<br>
 histstep =      10<br>
 share_comps =       0<br>
 share_start =      100<br>
 comp_thresh =  0.990000000000000<br>
 share_int =      100<br>
 initial lrate =  5.000000000000000E-002<br>
 minimum lrate =  1.000000000000000E-008<br>
 lrate factor =  0.500000000000000<br>
 initial rholrate =  5.000000000000000E-002<br>
 rho0 =   1.50000000000000<br>
 min rho =   1.00000000000000<br>
 max rho =   2.00000000000000<br>
 rho lrate factor =  0.500000000000000<br>
 kurt_start =       3<br>
 num kurt =       5<br>
 kurt interval =       1<br>
 do_newton =       1<br>
 newt_start =      50<br>
 newt_ramp =      10<br>
 initial newton lrate =   1.00000000000000<br>
 do_reject =       0<br>
 num reject =       3<br>
 reject sigma =   3.00000000000000<br>
 reject start =       2<br>
 reject interval =       3<br>
 max_thrds =       2<br>
 write step =      10<br>
 write_nd =       0<br>
 write_LLt =       1<br>
 dec window =       1<br>
 max_decs =       3<br>
 fix_init =       0<br>
 update_A =       1<br>
 update_c =       1<br>
 update_gm =       1<br>
 update_alpha =       1<br>
 update_mu =       1<br>
 update_beta =       1<br>
 invsigmax =   100.000000000000<br>
 invsigmin =  0.000000000000000E+000<br>
 do_rho =       1<br>
 load_rej =       0<br>
 load_c =       0<br>
 load_gm =       0<br>
 load_alpha =       0<br>
 load_mu =       0<br>
 load_beta =       0<br>
 load_rho =       0<br>
 load_comp_list =       0<br>
 do_mean =       1<br>
 do_sphere =       1<br>
 doPCA =       1<br>
 pcakeep =      134<br>
 pcadb =   30.0000000000000<br>
 byte_size =       4<br>
 doscaling =       1<br>
 scalestep =       1<br>
A subdirectory or file D:\Tatu\AMICATMP\amicaouttmp\ already exists.<br>
 output directory = D:\Tatu\AMICATMP\amicaouttmp\<br>
      1 : setting num_thrds to       2  ...<br>
      1 : using      2 threads.<br>
      1 : node_thrds =       2<br>
 bytes in real =       1<br>
      1 : REAL nbyte =       1<br>
 getting segment list ...<br>
 blocks in sample =    382975<br>
 total blocks =    382975<br>
 node blocks =    382975<br>
 node       1  start: file       1  sample       1  index<br>
      1<br>
 node       1  stop : file       1  sample       1  index<br>
    382975<br>
      1 : data =   19.4008998870850     8.51673507690430<br>
 getting the mean ...<br>
  mean =  -1.38158794941323    9.108994773376549E-003<br>
 -9.745015379274158E-003<br>
 subtracting the mean ...<br>
 getting the sphering matrix ...<br>
 cnt =    382975<br>
 doing eig nx =      134  lwork =    179560<br>
 minimum eigenvalues =   1.32521304789175     1.60365130875427<br>
  1.83976537562973<br>
 maximum eigenvalues =   287079.512877785     8402.99938147310<br>
  4669.66292334350<br>
 num eigs kept =      134<br>
 numeigs =      134<br>
 sphering the data ...<br>
      1 Allocating variables ...<br>
      1 : Initializing variables ...<br>
      1 : block size =      256<br>
      1 : entering the main loop ...<br>
forrtl: severe (170): Program Exception - stack overflow<br>
Image        PC         Routine       Line     Source<br>
amica12win64.exe  000000013FCEE047  Unknown        Unknown  Unknown<br>
amica12win64.exe  000000013FC55847  Unknown        Unknown  Unknown<br>
libiomp5md.dll   000000001007BC0C  Unknown        Unknown  Unknown<br>
libiomp5md.dll   000000001005C428  Unknown        Unknown  Unknown<br>
libiomp5md.dll   0000000010053BC8  Unknown        Unknown  Unknown<br>
libiomp5md.dll   000000001003591C  Unknown        Unknown  Unknown<br>
amica12win64.exe  000000013FC41A35  Unknown        Unknown  Unknown<br>
amica12win64.exe  000000013FC1447C  Unknown        Unknown  Unknown<br>
amica12win64.exe  000000014008F42C  Unknown        Unknown  Unknown<br>
amica12win64.exe  000000013FCEE56F  Unknown        Unknown  Unknown<br>
kernel32.dll    0000000076CA652D  Unknown        Unknown  Unknown<br>
ntdll.dll      0000000076DDC541  Unknown        Unknown  Unknown<br>
No gm present, setting num_models to 1<br>
No W present, exiting<br>
Reference to non-existent field 'W'.<br>
<br>
Error in runamica12 (line 851)<br>
   weights = mods.W(:,:,1);<br>
<br>
--------------------------------<br>
Tatu Huovilainen<br>
Research Assistant<br>
CBRU - Helsinki University<br>
<br>
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</div></div></blockquote></div><br><br clear="all"><div><br></div>-- <br><div dir="ltr">Makoto Miyakoshi<br>Swartz Center for Computational Neuroscience<br>Institute for Neural Computation, University of California San Diego<br>
</div>
</div>