amica
amica copied to clipboard
sccn
Issue with mpich
Dear Dr. Jason Palmer,
I am having some issues with amica and would really appreciate if you could help me with this.
I've installed mpich using mpich2-1.4-win-x86-64.msi as an administrator and am trying to run some codes by Makoto.
I keep encountering the following errors as well as a pop up asking me to install mpich.
Errors:
Error: num_samples entries is less than num_files in paramfile
No gm present, setting num_models to 1
No W present, exiting
Reference to non-existent field 'W'.
Error in runamica15 (line 892)
weights = mods.W(:,:,1);
Screenshot of pop up:
I am using EEGLAB v14.1.1, MATLAB R2016a on a 64bit machine and I open MATLAB as an administrator.
The codes I am trying to run are:
if isfield(EEG.etc, 'clean_channel_mask')
dataRank = min([rank(double(EEG.data')) sum(EEG.etc.clean_channel_mask)]);
else
dataRank = rank(double(EEG.data'));
end
runamica15(EEG.data, 'num_chans', EEG.nbchan,...
'outdir', 'C:\amicaResults\' ,...
'pcakeep', dataRank, 'num_models', 1,...
'do_reject', 1, 'numrej', 15, 'rejsig', 3, 'rejint', 1);
EEG.etc.amica = loadmodout15('C:\amicaResults\' );
EEG.etc.amica.S = EEG.etc.amica.S(1:EEG.etc.amica.num_pcs, :); % Weirdly, I saw size(S,1) be larger than rank. This process does not hurt anyway.
EEG.icaweights = EEG.etc.amica.W;
EEG.icasphere = EEG.etc.amica.S;
EEG = eeg_checkset(EEG, 'ica');
Thank you in advance for your help.
Hi Jazelle, Could you send the complete text output (on Matlab command line), which shows all the parameter settings? Thanks, Jason
On Wed, Feb 13, 2019, 8:45 PM Jazelle759 <[email protected] wrote:
Dear Dr. Jason Palmer,
I am having some issues with amica and would really appreciate if you could help me with this.
I've installed mpich using mpich2-1.4-win-x86-64.msi as an administrator and am trying to run some codes by Makoto.
I keep encountering the following errors as well as a pop up asking me to install mpich.
Errors:
Error: num_samples entries is less than num_files in paramfile No gm present, setting num_models to 1 No W present, exiting Reference to non-existent field 'W'.
Error in runamica15 (line 892) weights = mods.W(:,:,1);
Screenshot of pop up: [image: image] https://user-images.githubusercontent.com/35135298/52704630-df301f80-2fe5-11e9-850f-e8f0a1143f0b.png
I am using EEGLAB v14.1.1, MATLAB R2016a on a 64bit machine and I open MATLAB as an administrator.
The codes I am trying to run are:
if isfield(EEG.etc, 'clean_channel_mask') dataRank = min([rank(double(EEG.data')) sum(EEG.etc.clean_channel_mask)]); else dataRank = rank(double(EEG.data')); end runamica15(EEG.data, 'num_chans', EEG.nbchan,... 'outdir', 'C:\amicaResults' ,... 'pcakeep', dataRank, 'num_models', 1,... 'do_reject', 1, 'numrej', 15, 'rejsig', 3, 'rejint', 1); EEG.etc.amica = loadmodout15('C:\amicaResults' ); EEG.etc.amica.S = EEG.etc.amica.S(1:EEG.etc.amica.num_pcs, :); % Weirdly, I saw size(S,1) be larger than rank. This process does not hurt anyway. EEG.icaweights = EEG.etc.amica.W; EEG.icasphere = EEG.etc.amica.S; EEG = eeg_checkset(EEG, 'ica');
Thank you in advance for your help.
— You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub https://github.com/japalmer29/amica/issues/10, or mute the thread https://github.com/notifications/unsubscribe-auth/AKISSt78GKN4fGpSrpiHZV4-PNOhv4WAks5vM_rLgaJpZM4a5Obu .
Hi Dr Palmer,
Thanks for the quick reply. Please see below the complete text output on MATLAB command window.
Writing data file: C:\Analysis\tmpdata81472.fdt
A subdirectory or file C:\amicaResults\ already exists.
1 processor name = LAPTOP-RNS6O05B
1 host_num = 1682198720
This is MPI process 1 of 1 ; I am process 1 of
1 on node: LAPTOP-RNS6O05B
1 : node root process 1 of 1
Processing arguments ...
num_files = 4
FILES:
C:\Analysis\tmpdata81472.fdt
num_dir_files = 1 1 1 1
initial matrix block_size = 128
do_opt_block = 0
blk_min = 256
blk_step = 256
blk_max = 1024
number of models = 1
max_thrds = 2
use_min_dll = 1
min dll = 1.000000000000000E-009
use_grad_norm = 1
min grad norm = 1.000000000000000E-007
number of density mixture components = 3
pdf type = 0
max_iter = 2000
Error: num_samples entries is less than num_files in paramfile
No gm present, setting num_models to 1
No W present, exiting
Reference to non-existent field 'W'.
Error in runamica15 (line 892)
weights = mods.W(:,:,1);
Hi Jazelle,
For some reason Amica thinks there are 4 files of input data, instead of 1 as it should be. I’m not sure how this is happening, since the FILES argument should be the same that is output as “C:\Analysis\tempdata…fdt”. Maybe you could put a breakpoint in the file runamica15.m where it says “file = “, and then step past that line and check the value of the “file” variable in the matlab debugger command line. Somehow this seems to be getting 4 text tokens separated by white space.
But I also think you could simplify the process and probably avoid this error. Make sure you have the matlab code from http://sccn.ucsd.edu/~jason/amica_web.html or the amica plugin in eeglab. Then you can just use these commands (the rank and pcakeep and loading commands are not necessary):
% save the data and fill datfile field in EEG
EEG = pop_saveset(EEG,[pwd '/mydata.set']);
% run amica with blocksize optimization and rejection
runamica15(EEG,'outdir',[pwd '/amicaout'],'do_opt_block',1, 'num_models', 1, ...
'do_reject',1,'rejstart',1,'rejint',1,'numrej',15,'rejsig',3, ...
'max_iter',2500,'writestep',50);
% load the amica results into EEG
EEG = eeg_loadamica(EEG,'./amicaout');
Best,
Jason
From: Jazelle759 [mailto:[email protected]] Sent: Thursday, February 14, 2019 7:38 AM To: japalmer29/amic Cc: Jason Palmer; Comment Subject: Re: [japalmer29/amica] Issue with mpich (#10)
Hi Dr Palmer,
Thanks for the quick reply. Please see below the complete text output on MATLAB command window.
Writing data file: C:\Analysis\tmpdata81472.fdt
A subdirectory or file C:\amicaResults\ already exists.
1 processor name = LAPTOP-RNS6O05B
1 host_num = 1682198720
This is MPI process 1 of 1 ; I am process 1 of
1 on node: LAPTOP-RNS6O05B
1 : node root process 1 of 1
Processing arguments ...
num_files = 4
FILES:
C:\Analysis\tmpdata81472.fdt
num_dir_files = 1 1 1 1
initial matrix block_size = 128
do_opt_block = 0
blk_min = 256
blk_step = 256
blk_max = 1024
number of models = 1
max_thrds = 2
use_min_dll = 1
min dll = 1.000000000000000E-009
use_grad_norm = 1
min grad norm = 1.000000000000000E-007
number of density mixture components = 3
pdf type = 0
max_iter = 2000
Error: num_samples entries is less than num_files in paramfile
No gm present, setting num_models to 1
No W present, exiting
Reference to non-existent field 'W'.
Error in runamica15 (line 892) weights = mods.W(:,:,1);
— You are receiving this because you commented. Reply to this email directly, view it on GitHub https://github.com/japalmer29/amica/issues/10#issuecomment-463404470 , or mute the thread https://github.com/notifications/unsubscribe-auth/AKISSlKUedObR-CNHvep4OeTMQEHvFXfks5vNJPTgaJpZM4a5Obu . https://github.com/notifications/beacon/AKISShJaXahpOIXKJBpKDb0YVD368ykaks5vNJPTgaJpZM4a5Obu.gif
Hi Dr Palmer,
At first, I changed my codes to:
runamica15(EEG.data,'outdir',participantAmicaFolder,'do_opt_block',1, 'num_models', 1, ...
'do_reject',1,'rejstart',1,'rejint',1,'numrej',15,'rejsig',3, ...
'max_iter',2500,'writestep',50);
% load the amica results into EEG
EEG.data = eeg_loadamica(EEG.data,participantAmicaFolder);
then I realized eeg_loadamica 1st input variable needs to be EEG not EEG.data, so I changed it to
runamica15(EEG.data,'outdir',participantAmicaFolder,'do_opt_block',1, 'num_models', 1, ...
'do_reject',1,'rejstart',1,'rejint',1,'numrej',15,'rejsig',3, ...
'max_iter',2500,'writestep',50);
% load the amica results into EEG
EEG = eeg_loadamica(EEG,participantAmicaFolder);
then it seems to work so I tried to reload eeglab, reload the file before I ran AMICA to retry running the whole script, and I encountered error again. I retried again after restarting eeglab and I keep coming up with this same error again.
Reference to non-existent field 'W'.
Error in runamica15 (line 892)
weights = mods.W(:,:,1);
You can see the whole process in the attached txt file. log.txt
What is pcakeep and why is it optional?
Thank you so much for your help so far! I very much appreciate it!
Hi Jazelle,
The Files problem is gone, but now it seems there is problem with the data. The mean has NaNs. Could you check the data with any(isnan(EEG.data(:))). Also, the first argument to runamica15 should just be EEG, not EEG.data.
Jason
On Sun, Feb 17, 2019, 10:30 AM Jazelle759 <[email protected] wrote:
Hi Dr Palmer,
At first, I changed my codes to:
runamica15(EEG.data,'outdir',participantAmicaFolder,'do_opt_block',1, 'num_models', 1, ... 'do_reject',1,'rejstart',1,'rejint',1,'numrej',15,'rejsig',3, ... 'max_iter',2500,'writestep',50); % load the amica results into EEG EEG.data = eeg_loadamica(EEG.data,participantAmicaFolder);
then I realized eeg_loadamica 1st input variable needs to be EEG not EEG.data, so I changed it to
runamica15(EEG.data,'outdir',participantAmicaFolder,'do_opt_block',1, 'num_models', 1, ... 'do_reject',1,'rejstart',1,'rejint',1,'numrej',15,'rejsig',3, ... 'max_iter',2500,'writestep',50); % load the amica results into EEG EEG = eeg_loadamica(EEG,participantAmicaFolder);
then it seems to work so I tried to reload eeglab, reload the file before I ran AMICA to retry running the whole script, and I encountered error again. I retried again after restarting eeglab and I keep coming up with this same error again.
Reference to non-existent field 'W'.
Error in runamica15 (line 892) weights = mods.W(:,:,1);
You can see the whole process in the attached txt file. log.txt https://github.com/japalmer29/amica/files/2872575/log.txt
What is pcakeep and why is it optional?
Thank you so much for your help so far! I very much appreciate it!
— You are receiving this because you commented. Reply to this email directly, view it on GitHub https://github.com/japalmer29/amica/issues/10#issuecomment-464405991, or mute the thread https://github.com/notifications/unsubscribe-auth/AKISStfzeJJPBmcp1tUsW3gr6HgUbInVks5vOLDCgaJpZM4a5Obu .
Hey Dr Palmer,
>> any(isnan(EEG.data(:)))
ans =
0
When I use EEG, I get the mean = NaN , while there are values when I use EEG.data instead.
>> runamica15(EEG,'outdir',participantAmicaFolder,'do_opt_block',1, 'num_models', 1, ...
'do_reject',1,'rejstart',1,'rejint',1,'numrej',15,'rejsig',3, ...
'max_iter',2500,'writestep',50);
% load the amica results into EEG
EEG = eeg_loadamica(EEG,participantAmicaFolder);
A subdirectory or file C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaResults\Participant01\ already exists.
1 processor name = LAPTOP-RNS6O05B
1 host_num = 1682198720
This is MPI process 1 of 1 ; I am process 1 of
1 on node: LAPTOP-RNS6O05B
1 : node root process 1 of 1
Processing arguments ...
num_files = 1
FILES:
C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAveRef
\\Participant01_AveRef.set
num_dir_files = 1
initial matrix block_size = 128
do_opt_block = 1
blk_min = 256
blk_step = 256
blk_max = 1024
number of models = 1
max_thrds = 2
use_min_dll = 1
min dll = 1.000000000000000E-009
use_grad_norm = 1
min grad norm = 1.000000000000000E-007
number of density mixture components = 3
pdf type = 0
max_iter = 2500
num_samples = 1
data_dim = 128
field_dim = 826525
do_history = 0
histstep = 10
share_comps = 0
share_start = 100
comp_thresh = 0.990000000000000
share_int = 100
initial lrate = 5.000000000000000E-002
minimum lrate = 1.000000000000000E-008
minimum data covariance eigenvalue = 1.000000000000000E-012
lrate factor = 0.500000000000000
initial rholrate = 5.000000000000000E-002
rho0 = 1.50000000000000
min rho = 1.00000000000000
max rho = 2.00000000000000
rho lrate factor = 0.500000000000000
kurt_start = 3
num kurt = 5
kurt interval = 1
do_newton = 1
newt_start = 50
newt_ramp = 10
initial newton lrate = 1.00000000000000
do_reject = 1
num reject = 15
reject sigma = 3.00000000000000
reject start = 1
reject interval = 1
write step = 50
write_nd = 0
write_LLt = 1
dec window = 1
max_decs = 3
fix_init = 0
update_A = 1
update_c = 1
update_gm = 1
update_alpha = 1
update_mu = 1
update_beta = 1
invsigmax = 100.000000000000
invsigmin = 0.000000000000000E+000
do_rho = 1
load_rej = 0
load_c = 0
load_gm = 0
load_alpha = 0
load_mu = 0
load_beta = 0
load_rho = 0
load_comp_list = 0
do_mean = 1
do_sphere = 1
pcakeep = 128
pcadb = 30.0000000000000
byte_size = 4
doscaling = 1
scalestep = 1
A subdirectory or file C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaResults\Participant01\ already exists.
output directory =
C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaR
esults\Participant01\
1 : setting num_thrds to 2 ...
1 : using 2 threads.
1 : node_thrds = 2
bytes in real = 1
1 : REAL nbyte = 1
getting segment list ...
blocks in sample = 826525
total blocks = 826525
node blocks = 826525
node 1 start: file 1 sample 1 index
1
node 1 stop : file 1 sample 1 index
826525
1 : data = 55641396.0000000 9.552169103699271E-006
getting the mean ...
mean = NaN NaN
NaN
subtracting the mean ...
getting the covariance matrix ...
cnt = 826525
doing eig nx = 128 lwork = 163840
Error doing eigenvalue decomposition!!!
num eigs kept = 0
getting the sphering matrix ...
Error doing eigenvalue decomposition!!!
num eigs kept = 0
MKL ERROR: Parameter 13 was incorrect on entry to DGEMM
MKL ERROR: Parameter 8 was incorrect on entry to DGEMM
sphering the data ...
numeigs = 0
MKL ERROR: Parameter 9 was incorrect on entry to DGESVD
MKL ERROR: Parameter 8 was incorrect on entry to DGEMM
1 : Allocating variables ...
1 : Initializing variables ...
MKL ERROR: Parameter 4 was incorrect on entry to DGETRF
forrtl: severe (157): Program Exception - access violation
Image PC Routine Line Source
amica15mkl.exe 00007FF7C5BB65EF Unknown Unknown Unknown
amica15mkl.exe 00007FF7C5B8E75B Unknown Unknown Unknown
amica15mkl.exe 00007FF7C5B5D859 Unknown Unknown Unknown
amica15mkl.exe 00007FF7C5FDC18C Unknown Unknown Unknown
amica15mkl.exe 00007FF7C5C3B24F Unknown Unknown Unknown
KERNEL32.DLL 00007FFA44113DC4 Unknown Unknown Unknown
ntdll.dll 00007FFA44273691 Unknown Unknown Unknown
No gm present, setting num_models to 1
No W present, exiting
Reference to non-existent field 'W'.
Error in runamica15 (line 892)
weights = mods.W(:,:,1);
>> runamica15(EEG.data,'outdir',participantAmicaFolder,'do_opt_block',1, 'num_models', 1, ...
'do_reject',1,'rejstart',1,'rejint',1,'numrej',15,'rejsig',3, ...
'max_iter',2500,'writestep',50);
% load the amica results into EEG
EEG = eeg_loadamica(EEG,participantAmicaFolder);
Writing data file: C:\Users\Jazelle\Desktop\Experiment\ExperimentAnalysis\tmpdata63236.fdt
A subdirectory or file C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaResults\Participant01\ already exists.
1 processor name = LAPTOP-RNS6O05B
1 host_num = 1682198720
This is MPI process 1 of 1 ; I am process 1 of
1 on node: LAPTOP-RNS6O05B
1 : node root process 1 of 1
Processing arguments ...
num_files = 1
FILES:
C:\Users\Jazelle\Desktop\Experiment\ExperimentAnalysis\tmpdata63236.fdt
num_dir_files = 1
initial matrix block_size = 128
do_opt_block = 1
blk_min = 256
blk_step = 256
blk_max = 1024
number of models = 1
max_thrds = 2
use_min_dll = 1
min dll = 1.000000000000000E-009
use_grad_norm = 1
min grad norm = 1.000000000000000E-007
number of density mixture components = 3
pdf type = 0
max_iter = 2500
num_samples = 1
data_dim = 128
field_dim = 826525
do_history = 0
histstep = 10
share_comps = 0
share_start = 100
comp_thresh = 0.990000000000000
share_int = 100
initial lrate = 5.000000000000000E-002
minimum lrate = 1.000000000000000E-008
minimum data covariance eigenvalue = 1.000000000000000E-012
lrate factor = 0.500000000000000
initial rholrate = 5.000000000000000E-002
rho0 = 1.50000000000000
min rho = 1.00000000000000
max rho = 2.00000000000000
rho lrate factor = 0.500000000000000
kurt_start = 3
num kurt = 5
kurt interval = 1
do_newton = 1
newt_start = 50
newt_ramp = 10
initial newton lrate = 1.00000000000000
do_reject = 1
num reject = 15
reject sigma = 3.00000000000000
reject start = 1
reject interval = 1
write step = 50
write_nd = 0
write_LLt = 1
dec window = 1
max_decs = 3
fix_init = 0
update_A = 1
update_c = 1
update_gm = 1
update_alpha = 1
update_mu = 1
update_beta = 1
invsigmax = 100.000000000000
invsigmin = 0.000000000000000E+000
do_rho = 1
load_rej = 0
load_c = 0
load_gm = 0
load_alpha = 0
load_mu = 0
load_beta = 0
load_rho = 0
load_comp_list = 0
do_mean = 1
do_sphere = 1
pcakeep = 128
pcadb = 30.0000000000000
byte_size = 4
doscaling = 1
scalestep = 1
A subdirectory or file C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaResults\Participant01\ already exists.
output directory =
C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaR
esults\Participant01\
1 : setting num_thrds to 2 ...
1 : using 2 threads.
1 : node_thrds = 2
bytes in real = 1
1 : REAL nbyte = 1
getting segment list ...
blocks in sample = 826525
total blocks = 826525
node blocks = 826525
node 1 start: file 1 sample 1 index
1
node 1 stop : file 1 sample 1 index
826525
1 : data = 5.66509771347046 0.897219359874725
getting the mean ...
mean = -2.465582641069445E-002 -6.649327648029919E-002
-8.313021872202728E-002
subtracting the mean ...
getting the covariance matrix ...
cnt = 826525
doing eig nx = 128 lwork = 163840
minimum eigenvalues = -6.844702957777817E-013 -2.003152265693854E-013
2.477480847177622E-013
maximum eigenvalues = 3040.04644502642 842.308374713901
684.480322075794
num eigs kept = 124
getting the sphering matrix ...
minimum eigenvalues = -6.844702957777817E-013 -2.003152265693854E-013
2.477480847177622E-013
maximum eigenvalues = 3040.04644502642 842.308374713901
684.480322075794
num eigs kept = 124
sphering the data ...
numeigs = 124
1 : Allocating variables ...
1 : Initializing variables ...
1 : Determining optimal block size ....
No gm present, setting num_models to 1
No W present, exiting
Reference to non-existent field 'W'.
Error in runamica15 (line 892)
weights = mods.W(:,:,1);
When I tried running on the school's PC, I keep getting amica15mkl.exe has stopped working instead.
It seems to be using the .set file instead if the .fdt. Do you have the eeglab option set to save datasets in two files, .set and .fdt? Could you make sure that is on, then use the pop_saveset command, and paste the output of >>EEG showing the field values?
On Sun, Feb 17, 2019, 2:40 PM Jazelle759 <[email protected] wrote:
Hey Dr Palmer,
any(isnan(EEG.data(:)))
ans =
0When I use EEG, I get the mean = NaN , while there are values when I use EEG.data instead.
runamica15(EEG,'outdir',participantAmicaFolder,'do_opt_block',1, 'num_models', 1, ... 'do_reject',1,'rejstart',1,'rejint',1,'numrej',15,'rejsig',3, ... 'max_iter',2500,'writestep',50); % load the amica results into EEG EEG = eeg_loadamica(EEG,participantAmicaFolder);
A subdirectory or file C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaResults\Participant01\ already exists. 1 processor name = LAPTOP-RNS6O05B 1 host_num = 1682198720 This is MPI process 1 of 1 ; I am process 1 of 1 on node: LAPTOP-RNS6O05B 1 : node root process 1 of 1 Processing arguments ... num_files = 1 FILES: C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAveRef \Participant01_AveRef.set num_dir_files = 1 initial matrix block_size = 128 do_opt_block = 1 blk_min = 256 blk_step = 256 blk_max = 1024 number of models = 1 max_thrds = 2 use_min_dll = 1 min dll = 1.000000000000000E-009 use_grad_norm = 1 min grad norm = 1.000000000000000E-007 number of density mixture components = 3 pdf type = 0 max_iter = 2500 num_samples = 1 data_dim = 128 field_dim = 826525 do_history = 0 histstep = 10 share_comps = 0 share_start = 100 comp_thresh = 0.990000000000000 share_int = 100 initial lrate = 5.000000000000000E-002 minimum lrate = 1.000000000000000E-008 minimum data covariance eigenvalue = 1.000000000000000E-012 lrate factor = 0.500000000000000 initial rholrate = 5.000000000000000E-002 rho0 = 1.50000000000000 min rho = 1.00000000000000 max rho = 2.00000000000000 rho lrate factor = 0.500000000000000 kurt_start = 3 num kurt = 5 kurt interval = 1 do_newton = 1 newt_start = 50 newt_ramp = 10 initial newton lrate = 1.00000000000000 do_reject = 1 num reject = 15 reject sigma = 3.00000000000000 reject start = 1 reject interval = 1 write step = 50 write_nd = 0 write_LLt = 1 dec window = 1 max_decs = 3 fix_init = 0 update_A = 1 update_c = 1 update_gm = 1 update_alpha = 1 update_mu = 1 update_beta = 1 invsigmax = 100.000000000000 invsigmin = 0.000000000000000E+000 do_rho = 1 load_rej = 0 load_c = 0 load_gm = 0 load_alpha = 0 load_mu = 0 load_beta = 0 load_rho = 0 load_comp_list = 0 do_mean = 1 do_sphere = 1 pcakeep = 128 pcadb = 30.0000000000000 byte_size = 4 doscaling = 1 scalestep = 1 A subdirectory or file C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaResults\Participant01\ already exists. output directory = C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaR esults\Participant01
1 : setting num_thrds to 2 ... 1 : using 2 threads. 1 : node_thrds = 2 bytes in real = 1 1 : REAL nbyte = 1 getting segment list ... blocks in sample = 826525 total blocks = 826525 node blocks = 826525 node 1 start: file 1 sample 1 index 1 node 1 stop : file 1 sample 1 index 826525 1 : data = 55641396.0000000 9.552169103699271E-006 getting the mean ... mean = NaN NaN NaN subtracting the mean ... getting the covariance matrix ... cnt = 826525 doing eig nx = 128 lwork = 163840 Error doing eigenvalue decomposition!!! num eigs kept = 0 getting the sphering matrix ... Error doing eigenvalue decomposition!!! num eigs kept = 0MKL ERROR: Parameter 13 was incorrect on entry to DGEMM
MKL ERROR: Parameter 8 was incorrect on entry to DGEMM sphering the data ... numeigs = 0
MKL ERROR: Parameter 9 was incorrect on entry to DGESVD
MKL ERROR: Parameter 8 was incorrect on entry to DGEMM 1 : Allocating variables ... 1 : Initializing variables ...
MKL ERROR: Parameter 4 was incorrect on entry to DGETRF forrtl: severe (157): Program Exception - access violation Image PC Routine Line Source amica15mkl.exe 00007FF7C5BB65EF Unknown Unknown Unknown amica15mkl.exe 00007FF7C5B8E75B Unknown Unknown Unknown amica15mkl.exe 00007FF7C5B5D859 Unknown Unknown Unknown amica15mkl.exe 00007FF7C5FDC18C Unknown Unknown Unknown amica15mkl.exe 00007FF7C5C3B24F Unknown Unknown Unknown KERNEL32.DLL 00007FFA44113DC4 Unknown Unknown Unknown ntdll.dll 00007FFA44273691 Unknown Unknown Unknown No gm present, setting num_models to 1 No W present, exiting Reference to non-existent field 'W'.
Error in runamica15 (line 892) weights = mods.W(:,:,1);
runamica15(EEG.data,'outdir',participantAmicaFolder,'do_opt_block',1, 'num_models', 1, ... 'do_reject',1,'rejstart',1,'rejint',1,'numrej',15,'rejsig',3, ... 'max_iter',2500,'writestep',50); % load the amica results into EEG EEG = eeg_loadamica(EEG,participantAmicaFolder); Writing data file: C:\Users\Jazelle\Desktop\Experiment\ExperimentAnalysis\tmpdata63236.fdt A subdirectory or file C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaResults\Participant01\ already exists. 1 processor name = LAPTOP-RNS6O05B 1 host_num = 1682198720 This is MPI process 1 of 1 ; I am process 1 of 1 on node: LAPTOP-RNS6O05B 1 : node root process 1 of 1 Processing arguments ... num_files = 1 FILES: C:\Users\Jazelle\Desktop\Experiment\SimpleERPAnalysisPipeline\TargetDistractorAnal ysis\tmpdata63236.fdt num_dir_files = 1 initial matrix block_size = 128 do_opt_block = 1 blk_min = 256 blk_step = 256 blk_max = 1024 number of models = 1 max_thrds = 2 use_min_dll = 1 min dll = 1.000000000000000E-009 use_grad_norm = 1 min grad norm = 1.000000000000000E-007 number of density mixture components = 3 pdf type = 0 max_iter = 2500 num_samples = 1 data_dim = 128 field_dim = 826525 do_history = 0 histstep = 10 share_comps = 0 share_start = 100 comp_thresh = 0.990000000000000 share_int = 100 initial lrate = 5.000000000000000E-002 minimum lrate = 1.000000000000000E-008 minimum data covariance eigenvalue = 1.000000000000000E-012 lrate factor = 0.500000000000000 initial rholrate = 5.000000000000000E-002 rho0 = 1.50000000000000 min rho = 1.00000000000000 max rho = 2.00000000000000 rho lrate factor = 0.500000000000000 kurt_start = 3 num kurt = 5 kurt interval = 1 do_newton = 1 newt_start = 50 newt_ramp = 10 initial newton lrate = 1.00000000000000 do_reject = 1 num reject = 15 reject sigma = 3.00000000000000 reject start = 1 reject interval = 1 write step = 50 write_nd = 0 write_LLt = 1 dec window = 1 max_decs = 3 fix_init = 0 update_A = 1 update_c = 1 update_gm = 1 update_alpha = 1 update_mu = 1 update_beta = 1 invsigmax = 100.000000000000 invsigmin = 0.000000000000000E+000 do_rho = 1 load_rej = 0 load_c = 0 load_gm = 0 load_alpha = 0 load_mu = 0 load_beta = 0 load_rho = 0 load_comp_list = 0 do_mean = 1 do_sphere = 1 pcakeep = 128 pcadb = 30.0000000000000 byte_size = 4 doscaling = 1 scalestep = 1 A subdirectory or file C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaResults\Participant01\ already exists. output directory = C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaR esults\Participant01
1 : setting num_thrds to 2 ... 1 : using 2 threads. 1 : node_thrds = 2 bytes in real = 1 1 : REAL nbyte = 1 getting segment list ... blocks in sample = 826525 total blocks = 826525 node blocks = 826525 node 1 start: file 1 sample 1 index 1 node 1 stop : file 1 sample 1 index 826525 1 : data = 5.66509771347046 0.897219359874725 getting the mean ... mean = -2.465582641069445E-002 -6.649327648029919E-002 -8.313021872202728E-002 subtracting the mean ... getting the covariance matrix ... cnt = 826525 doing eig nx = 128 lwork = 163840 minimum eigenvalues = -6.844702957777817E-013 -2.003152265693854E-013 2.477480847177622E-013 maximum eigenvalues = 3040.04644502642 842.308374713901 684.480322075794 num eigs kept = 124 getting the sphering matrix ... minimum eigenvalues = -6.844702957777817E-013 -2.003152265693854E-013 2.477480847177622E-013 maximum eigenvalues = 3040.04644502642 842.308374713901 684.480322075794 num eigs kept = 124 sphering the data ... numeigs = 124 1 : Allocating variables ... 1 : Initializing variables ... 1 : Determining optimal block size .... No gm present, setting num_models to 1 No W present, exiting Reference to non-existent field 'W'.Error in runamica15 (line 892) weights = mods.W(:,:,1);
When I tried running on the school's PC, I keep getting amica15mkl.exe has stopped working instead.
— You are receiving this because you commented. Reply to this email directly, view it on GitHub https://github.com/japalmer29/amica/issues/10#issuecomment-464419720, or mute the thread https://github.com/notifications/unsubscribe-auth/AKISSvwagGJqbRe0qXpw0GqqfmFMYO42ks5vOOtSgaJpZM4a5Obu .
Sorry for bothering you so much.
>> EEG
EEG =
setname: 'Participant01 resampled'
filename: 'Participant01_AveRef.set'
filepath: 'C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAveRef'
subject: ''
group: ''
condition: ''
session: []
comments: 'Original files: C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentData\Participant 1\P…'
nbchan: 128
trials: 1
pnts: 826775
srate: 250
xmin: 0
xmax: 3.3071e+03
times: [1x826775 double]
data: [128x826775 single]
icaact: []
icawinv: []
icasphere: []
icaweights: []
icachansind: []
chanlocs: [1x128 struct]
urchanlocs: [1x128 struct]
chaninfo: [1x1 struct]
ref: 'averef'
event: [1x1156 struct]
urevent: [1x1868 struct]
eventdescription: {'' '' '' ''}
epoch: []
epochdescription: {}
reject: [1x1 struct]
stats: [1x1 struct]
specdata: []
specicaact: []
splinefile: ''
icasplinefile: ''
dipfit: []
history: '…'
saved: 'justloaded'
etc: [1x1 struct]
datfile: 'Participant01_AveRef.fdt'
>> runamica15(EEG,'outdir',participantAmicaFolder,'do_opt_block',1, 'num_models', 1, ...
'do_reject',1,'rejstart',1,'rejint',1,'numrej',15,'rejsig',3, ...
'max_iter',2500,'writestep',50);
% load the amica results into EEG
EEG = eeg_loadamica(EEG,participantAmicaFolder);
A subdirectory or file C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaResults\Participant01\ already exists.
1 processor name = LAPTOP-RNS6O05B
1 host_num = 1682198720
This is MPI process 1 of 1 ; I am process 1 of
1 on node: LAPTOP-RNS6O05B
1 : node root process 1 of 1
Processing arguments ...
num_files = 1
FILES:
C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAveRef
\Participant01_AveRef.fdt
num_dir_files = 1
initial matrix block_size = 128
do_opt_block = 1
blk_min = 256
blk_step = 256
blk_max = 1024
number of models = 1
max_thrds = 2
use_min_dll = 1
min dll = 1.000000000000000E-009
use_grad_norm = 1
min grad norm = 1.000000000000000E-007
number of density mixture components = 3
pdf type = 0
max_iter = 2500
num_samples = 1
data_dim = 128
field_dim = 826775
do_history = 0
histstep = 10
share_comps = 0
share_start = 100
comp_thresh = 0.990000000000000
share_int = 100
initial lrate = 5.000000000000000E-002
minimum lrate = 1.000000000000000E-008
minimum data covariance eigenvalue = 1.000000000000000E-012
lrate factor = 0.500000000000000
initial rholrate = 5.000000000000000E-002
rho0 = 1.50000000000000
min rho = 1.00000000000000
max rho = 2.00000000000000
rho lrate factor = 0.500000000000000
kurt_start = 3
num kurt = 5
kurt interval = 1
do_newton = 1
newt_start = 50
newt_ramp = 10
initial newton lrate = 1.00000000000000
do_reject = 1
num reject = 15
reject sigma = 3.00000000000000
reject start = 1
reject interval = 1
write step = 50
write_nd = 0
write_LLt = 1
dec window = 1
max_decs = 3
fix_init = 0
update_A = 1
update_c = 1
update_gm = 1
update_alpha = 1
update_mu = 1
update_beta = 1
invsigmax = 100.000000000000
invsigmin = 0.000000000000000E+000
do_rho = 1
load_rej = 0
load_c = 0
load_gm = 0
load_alpha = 0
load_mu = 0
load_beta = 0
load_rho = 0
load_comp_list = 0
do_mean = 1
do_sphere = 1
pcakeep = 128
pcadb = 30.0000000000000
byte_size = 4
doscaling = 1
scalestep = 1
A subdirectory or file C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaResults\Participant01\ already exists.
output directory =
C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaR
esults\Participant01\
1 : setting num_thrds to 2 ...
1 : using 2 threads.
1 : node_thrds = 2
bytes in real = 1
1 : REAL nbyte = 1
getting segment list ...
blocks in sample = 826775
total blocks = 826775
node blocks = 826775
node 1 start: file 1 sample 1 index
1
node 1 stop : file 1 sample 1 index
826775
1 : data = 5.66509771347046 0.897219359874725
getting the mean ...
mean = -2.080518629688183E-002 -5.178608981631395E-002
-6.193587986477959E-002
subtracting the mean ...
getting the covariance matrix ...
cnt = 826775
doing eig nx = 128 lwork = 163840
minimum eigenvalues = -1.640216754986347E-013 9.411566154889960E-014
2.738278491293088E-013
maximum eigenvalues = 3184.94883024488 844.467229287250
689.519255671804
num eigs kept = 125
getting the sphering matrix ...
minimum eigenvalues = -1.640216754986347E-013 9.411566154889960E-014
2.738278491293088E-013
maximum eigenvalues = 3184.94883024488 844.467229287250
689.519255671804
num eigs kept = 125
sphering the data ...
numeigs = 125
1 : Allocating variables ...
1 : Initializing variables ...
1 : Determining optimal block size ....
No gm present, setting num_models to 1
No W present, exiting
Reference to non-existent field 'W'.
Error in runamica15 (line 892)
weights = mods.W(:,:,1);
Ok, now it's running, but the data low rank is causing problems. Are you interpolating channels before ica? The best approach is to run ica on the data without interpolating removed channels, and do average reference. This should make the data rank one less than nchans, but Amica should detect it and reduce dimsionality of data. If it does not automatically work, you can use 'pcakeep', EEG.nbchans-1 ...
Then after loading the ICA ouput, then do interpolation on the maps, EEG.icawinv. then backprojecting will fill missing channels.
On Sun, Feb 17, 2019, 5:01 PM Jazelle759 <[email protected] wrote:
Sorry for bothering you so much.
EEG
EEG =
setname: 'Participant01 resampled' filename: 'Participant01_AveRef.set' filepath: 'C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAveRef' subject: '' group: '' condition: '' session: [] comments: 'Original files: C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentData\Participant 1\P…' nbchan: 128 trials: 1 pnts: 826775 srate: 250 xmin: 0 xmax: 3.3071e+03 times: [1x826775 double] data: [128x826775 single] icaact: [] icawinv: [] icasphere: [] icaweights: [] icachansind: [] chanlocs: [1x128 struct] urchanlocs: [1x128 struct] chaninfo: [1x1 struct] ref: 'averef' event: [1x1156 struct] urevent: [1x1868 struct] eventdescription: {'' '' '' ''} epoch: [] epochdescription: {} reject: [1x1 struct] stats: [1x1 struct] specdata: [] specicaact: [] splinefile: '' icasplinefile: '' dipfit: [] history: '…' saved: 'justloaded' etc: [1x1 struct] datfile: 'Participant01_AveRef.fdt'runamica15(EEG,'outdir',participantAmicaFolder,'do_opt_block',1, 'num_models', 1, ...
'do_reject',1,'rejstart',1,'rejint',1,'numrej',15,'rejsig',3, ... 'max_iter',2500,'writestep',50);% load the amica results into EEG
EEG = eeg_loadamica(EEG,participantAmicaFolder);
A subdirectory or file C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaResults\Participant01\ already exists.
1 processor name = LAPTOP-RNS6O05B 1 host_num = 1682198720This is MPI process 1 of 1 ; I am process 1 of
1 on node: LAPTOP-RNS6O05B 1 : node root process 1 of 1Processing arguments ...
num_files = 1
FILES:
C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAveRef
\Participant01_AveRef.fdt
num_dir_files = 1
initial matrix block_size = 128
do_opt_block = 1
blk_min = 256
blk_step = 256
blk_max = 1024
number of models = 1
max_thrds = 2
use_min_dll = 1
min dll = 1.000000000000000E-009
use_grad_norm = 1
min grad norm = 1.000000000000000E-007
number of density mixture components = 3
pdf type = 0
max_iter = 2500
num_samples = 1
data_dim = 128
field_dim = 826775
do_history = 0
histstep = 10
share_comps = 0
share_start = 100
comp_thresh = 0.990000000000000
share_int = 100
initial lrate = 5.000000000000000E-002
minimum lrate = 1.000000000000000E-008
minimum data covariance eigenvalue = 1.000000000000000E-012
lrate factor = 0.500000000000000
initial rholrate = 5.000000000000000E-002
rho0 = 1.50000000000000
min rho = 1.00000000000000
max rho = 2.00000000000000
rho lrate factor = 0.500000000000000
kurt_start = 3
num kurt = 5
kurt interval = 1
do_newton = 1
newt_start = 50
newt_ramp = 10
initial newton lrate = 1.00000000000000
do_reject = 1
num reject = 15
reject sigma = 3.00000000000000
reject start = 1
reject interval = 1
write step = 50
write_nd = 0
write_LLt = 1
dec window = 1
max_decs = 3
fix_init = 0
update_A = 1
update_c = 1
update_gm = 1
update_alpha = 1
update_mu = 1
update_beta = 1
invsigmax = 100.000000000000
invsigmin = 0.000000000000000E+000
do_rho = 1
load_rej = 0
load_c = 0
load_gm = 0
load_alpha = 0
load_mu = 0
load_beta = 0
load_rho = 0
load_comp_list = 0
do_mean = 1
do_sphere = 1
pcakeep = 128
pcadb = 30.0000000000000
byte_size = 4
doscaling = 1
scalestep = 1
A subdirectory or file C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaResults\Participant01\ already exists.
output directory =
C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaR
esults\Participant01\
1 : setting num_thrds to 2 ... 1 : using 2 threads. 1 : node_thrds = 2bytes in real = 1
1 : REAL nbyte = 1getting segment list ...
blocks in sample = 826775
total blocks = 826775
node blocks = 826775
node 1 start: file 1 sample 1 index
1node 1 stop : file 1 sample 1 index
826775 1 : data = 5.66509771347046 0.897219359874725getting the mean ...
mean = -2.080518629688183E-002 -5.178608981631395E-002
-6.193587986477959E-002
subtracting the mean ...
getting the covariance matrix ...
cnt = 826775
doing eig nx = 128 lwork = 163840
minimum eigenvalues = -1.640216754986347E-013 9.411566154889960E-014
2.738278491293088E-013
maximum eigenvalues = 3184.94883024488 844.467229287250
689.519255671804
num eigs kept = 125
getting the sphering matrix ...
minimum eigenvalues = -1.640216754986347E-013 9.411566154889960E-014
2.738278491293088E-013
maximum eigenvalues = 3184.94883024488 844.467229287250
689.519255671804
num eigs kept = 125
sphering the data ...
numeigs = 125
1 : Allocating variables ... 1 : Initializing variables ... 1 : Determining optimal block size ....No gm present, setting num_models to 1
No W present, exiting
Reference to non-existent field 'W'.
Error in runamica15 (line 892)
weights = mods.W(:,:,1);— You are receiving this because you commented. Reply to this email directly, view it on GitHub https://github.com/japalmer29/amica/issues/10#issuecomment-464426937, or mute the thread https://github.com/notifications/unsubscribe-auth/AKISStEF9R4NoLyKW1Ge5C8eTxklklD7ks5vOQxPgaJpZM4a5Obu .
I tried running AMICA on the school PC and got this,
Not sure how that happened X<, but anyways, yes, I interpolated channels before ICA. I've basically been following the codes found here until the AMICA step which I've hit a roadblock.
I tried doing average reference without interpolating removed channels then running AMICA oth with and withot pcakeep. Results are as below.
>> % Save dataset (ParticipantNumber_AveRef)
EEG = pop_saveset( EEG, 'filename',strcat(name,'_AveRef.set'),'filepath',fullfile(processingFolderPath,'ExperimentAveRef'));
EEG = eeg_checkset( EEG );
Saving dataset...
>> runamica15(EEG,'outdir',participantAmicaFolder,'do_opt_block',1, 'num_models', 1, ...
'do_reject',1,'rejstart',1,'rejint',1,'numrej',15,'rejsig',3, ...
'max_iter',2500,'writestep',50);
% load the amica results into EEG
EEG = eeg_loadamica(EEG,participantAmicaFolder);
A subdirectory or file C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaResults\Participant01\ already exists.
1 processor name = LAPTOP-RNS6O05B
1 host_num = 1682198720
This is MPI process 1 of 1 ; I am process 1 of
1 on node: LAPTOP-RNS6O05B
1 : node root process 1 of 1
Processing arguments ...
num_files = 1
FILES:
C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAveRef
\Participant01_AveRef.fdt
num_dir_files = 1
initial matrix block_size = 128
do_opt_block = 1
blk_min = 256
blk_step = 256
blk_max = 1024
number of models = 1
max_thrds = 2
use_min_dll = 1
min dll = 1.000000000000000E-009
use_grad_norm = 1
min grad norm = 1.000000000000000E-007
number of density mixture components = 3
pdf type = 0
max_iter = 2500
num_samples = 1
data_dim = 124
field_dim = 826775
do_history = 0
histstep = 10
share_comps = 0
share_start = 100
comp_thresh = 0.990000000000000
share_int = 100
initial lrate = 5.000000000000000E-002
minimum lrate = 1.000000000000000E-008
minimum data covariance eigenvalue = 1.000000000000000E-012
lrate factor = 0.500000000000000
initial rholrate = 5.000000000000000E-002
rho0 = 1.50000000000000
min rho = 1.00000000000000
max rho = 2.00000000000000
rho lrate factor = 0.500000000000000
kurt_start = 3
num kurt = 5
kurt interval = 1
do_newton = 1
newt_start = 50
newt_ramp = 10
initial newton lrate = 1.00000000000000
do_reject = 1
num reject = 15
reject sigma = 3.00000000000000
reject start = 1
reject interval = 1
write step = 50
write_nd = 0
write_LLt = 1
dec window = 1
max_decs = 3
fix_init = 0
update_A = 1
update_c = 1
update_gm = 1
update_alpha = 1
update_mu = 1
update_beta = 1
invsigmax = 100.000000000000
invsigmin = 0.000000000000000E+000
do_rho = 1
load_rej = 0
load_c = 0
load_gm = 0
load_alpha = 0
load_mu = 0
load_beta = 0
load_rho = 0
load_comp_list = 0
do_mean = 1
do_sphere = 1
pcakeep = 124
pcadb = 30.0000000000000
byte_size = 4
doscaling = 1
scalestep = 1
A subdirectory or file C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaResults\Participant01\ already exists.
output directory =
C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaR
esults\Participant01\
1 : setting num_thrds to 2 ...
1 : using 2 threads.
1 : node_thrds = 2
bytes in real = 1
1 : REAL nbyte = 1
getting segment list ...
blocks in sample = 826775
total blocks = 826775
node blocks = 826775
node 1 start: file 1 sample 1 index
1
node 1 stop : file 1 sample 1 index
826775
1 : data = 5.70339298248291 0.935514807701111
getting the mean ...
mean = -1.447811822502307E-002 -4.881408335376367E-002
-5.660737602811115E-002
subtracting the mean ...
getting the covariance matrix ...
cnt = 826775
doing eig nx = 124 lwork = 153760
minimum eigenvalues = 2.377305388009759E-002 0.309337363531774
0.365926693662255
maximum eigenvalues = 3152.12089022707 825.109463263389
674.766848308228
num eigs kept = 124
getting the sphering matrix ...
minimum eigenvalues = 2.377305388009759E-002 0.309337363531774
0.365926693662255
maximum eigenvalues = 3152.12089022707 825.109463263389
674.766848308228
num eigs kept = 124
sphering the data ...
numeigs = 124
1 : Allocating variables ...
1 : Initializing variables ...
1 : Determining optimal block size ....
No gm present, setting num_models to 1
No W present, exiting
Reference to non-existent field 'W'.
Error in runamica15 (line 892)
weights = mods.W(:,:,1);
>> eeglab
eeglab: options file is C:\Users\Jazelle\eeg_options.m
EEGLAB: adding "MARA" v1.2 (see >> help eegplugin_MARA)
EEGLAB: adding "amica" v1.5.1 (see >> help eegplugin_amica)
EEGLAB: adding "clean_rawdata" v0.34 (see >> help eegplugin_clean_rawdata)
EEGLAB: adding "dipfit" v2.3 (see >> help eegplugin_dipfit)
EEGLAB: adding "erplab" v6.1.4 (see >> help eegplugin_erplab)
EEGLAB: adding "firfilt" v1.6.2 (see >> help eegplugin_firfilt)
EEGLAB: adding "postAmicaUtility" v2.01 (see >> help eegplugin_postAmicaUtility)
EEGLAB: adding "tmullen-cleanline-696a7181b7d" v0 (see >> help eegplugin_cleanline)
Warning:
A newer version of EEGLAB (14.1.2) is available here
This version fixes issues with Matlab 2018a. See Release notes for more informations.
You may disable this message in the Option menu but will miss critical updates.
pop_loadset(): loading file C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAveRef\Participant01_AveRef.set ...
Reading float file 'C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAveRef\Participant01_AveRef.fdt'...
Creating a new ALLEEG dataset 1
Done.
>> % Run AMICA using calculated data rank with 'pcakeep' option
if isfield(EEG.etc, 'clean_channel_mask')
dataRank = min([rank(double(EEG.data')) sum(EEG.etc.clean_channel_mask)]);
else
dataRank = rank(double(EEG.data'));
end
runamica15(EEG.data, 'num_chans', EEG.nbchan,...
'outdir', participantAmicaFolder ,...
'pcakeep', dataRank, 'num_models', 1,...
'do_reject', 1, 'numrej', 15, 'rejsig', 3, 'rejint', 1);
EEG.etc.amica = loadmodout15(participantAmicaFolder );
EEG.etc.amica.S = EEG.etc.amica.S(1:EEG.etc.amica.num_pcs, :); % Weirdly, I saw size(S,1) be larger than rank. This process does not hurt anyway.
EEG.icaweights = EEG.etc.amica.W;
EEG.icasphere = EEG.etc.amica.S;
EEG = eeg_checkset(EEG, 'ica');
Writing data file: C:\Users\Jazelle\Desktop\Experiment\DataAnalysis\tmpdata95751.fdt
A subdirectory or file C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaResults\Participant01\ already exists.
1 processor name = LAPTOP-RNS6O05B
1 host_num = 1682198720
This is MPI process 1 of 1 ; I am process 1 of
1 on node: LAPTOP-RNS6O05B
1 : node root process 1 of 1
Processing arguments ...
num_files = 1
FILES:
C:\Users\Jazelle\Desktop\Experiment\DataAnalysis\tmpdata95751.fdt
num_dir_files = 1
initial matrix block_size = 128
do_opt_block = 0
blk_min = 256
blk_step = 256
blk_max = 1024
number of models = 1
max_thrds = 2
use_min_dll = 1
min dll = 1.000000000000000E-009
use_grad_norm = 1
min grad norm = 1.000000000000000E-007
number of density mixture components = 3
pdf type = 0
max_iter = 2000
num_samples = 1
data_dim = 124
field_dim = 826775
do_history = 0
histstep = 10
share_comps = 0
share_start = 100
comp_thresh = 0.990000000000000
share_int = 100
initial lrate = 5.000000000000000E-002
minimum lrate = 1.000000000000000E-008
minimum data covariance eigenvalue = 1.000000000000000E-012
lrate factor = 0.500000000000000
initial rholrate = 5.000000000000000E-002
rho0 = 1.50000000000000
min rho = 1.00000000000000
max rho = 2.00000000000000
rho lrate factor = 0.500000000000000
kurt_start = 3
num kurt = 5
kurt interval = 1
do_newton = 1
newt_start = 50
newt_ramp = 10
initial newton lrate = 1.00000000000000
do_reject = 1
num reject = 15
reject sigma = 3.00000000000000
reject start = 2
reject interval = 1
write step = 20
write_nd = 0
write_LLt = 1
dec window = 1
max_decs = 3
fix_init = 0
update_A = 1
update_c = 1
update_gm = 1
update_alpha = 1
update_mu = 1
update_beta = 1
invsigmax = 100.000000000000
invsigmin = 0.000000000000000E+000
do_rho = 1
load_rej = 0
load_c = 0
load_gm = 0
load_alpha = 0
load_mu = 0
load_beta = 0
load_rho = 0
load_comp_list = 0
do_mean = 1
do_sphere = 1
pcakeep = 124
pcadb = 30.0000000000000
byte_size = 4
doscaling = 1
scalestep = 1
A subdirectory or file C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaResults\Participant01\ already exists.
output directory =
C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaR
esults\Participant01\
1 : setting num_thrds to 2 ...
1 : using 2 threads.
1 : node_thrds = 2
bytes in real = 1
1 : REAL nbyte = 1
getting segment list ...
blocks in sample = 826775
total blocks = 826775
node blocks = 826775
node 1 start: file 1 sample 1 index
1
node 1 stop : file 1 sample 1 index
826775
1 : data = 5.70339298248291 0.935514807701111
getting the mean ...
mean = -1.447811822502307E-002 -4.881408335376367E-002
-5.660737602811115E-002
subtracting the mean ...
getting the covariance matrix ...
cnt = 826775
doing eig nx = 124 lwork = 153760
minimum eigenvalues = 2.377305388009759E-002 0.309337363531774
0.365926693662255
maximum eigenvalues = 3152.12089022707 825.109463263389
674.766848308228
num eigs kept = 124
getting the sphering matrix ...
minimum eigenvalues = 2.377305388009759E-002 0.309337363531774
0.365926693662255
maximum eigenvalues = 3152.12089022707 825.109463263389
674.766848308228
num eigs kept = 124
sphering the data ...
numeigs = 124
1 : Allocating variables ...
1 : Initializing variables ...
1 : block size = 128
1 : entering the main loop ...
iter 1 lrate = 0.0500000000 LL = -2.1879400453 nd = 0.0316209328, D = 0.63086E-01 0.63086E-01 ( 15.34 s, 8.5 h)
Doing rejection ....
maximum likelihood value = -1.94530531277019
minimum likelihood value = -12.8424480341366
average likelihood value = -2.18794004532239
standard deviation = 0.249405579766357
rejecting data with likelihood less than -2.93615678462146
rejected 11729 data points so far. Will perform rejection 14
more times at intervals of 1 iterations.
iter 2 lrate = 0.0500000000 LL = -2.0951590716 nd = 0.0172690336, D = 0.55033E-01 0.55033E-01 ( 15.65 s, 8.7 h)
Doing rejection ....
maximum likelihood value = -1.74648645162986
minimum likelihood value = -3.03062210659308
average likelihood value = -2.09515907155584
standard deviation = 0.154974182576645
rejecting data with likelihood less than -2.56008161928578
rejected 23811 data points so far. Will perform rejection 13
more times at intervals of 1 iterations.
iter 3 lrate = 0.0500000000 LL = -2.0700441090 nd = 0.0122252001, D = 0.47893E-01 0.47893E-01 ( 13.34 s, 7.4 h)
Doing rejection ....
maximum likelihood value = -1.66660347014341
minimum likelihood value = -2.66387051151617
average likelihood value = -2.07004410898280
standard deviation = 0.154976084710437
rejecting data with likelihood less than -2.53497236311411
rejected 28270 data points so far. Will perform rejection 12
more times at intervals of 1 iterations.
iter 4 lrate = 0.0500000000 LL = -2.0631597399 nd = 0.0112155711, D = 0.48270E-01 0.48270E-01 ( 13.60 s, 7.5 h)
Doing rejection ....
maximum likelihood value = -1.63570475536690
minimum likelihood value = -2.59663802391389
average likelihood value = -2.06315973985731
standard deviation = 0.158387401110060
rejecting data with likelihood less than -2.53832194318749
rejected 29533 data points so far. Will perform rejection 11
more times at intervals of 1 iterations.
iter 5 lrate = 0.0500000000 LL = -2.0606809694 nd = 0.0105759165, D = 0.57496E-01 0.57496E-01 ( 13.40 s, 7.4 h)
Doing rejection ....
maximum likelihood value = -1.62309489244165
minimum likelihood value = -2.56312046661083
average likelihood value = -2.06068096939705
standard deviation = 0.159893620368294
rejecting data with likelihood less than -2.54036183050194
rejected 29947 data points so far. Will perform rejection 10
more times at intervals of 1 iterations.
iter 6 lrate = 0.0500000000 LL = -2.0593191199 nd = 0.0098341258, D = 0.73951E-01 0.73951E-01 ( 13.39 s, 7.4 h)
Doing rejection ....
maximum likelihood value = -1.61730196403345
minimum likelihood value = -2.55388876873334
average likelihood value = -2.05931911993658
standard deviation = 0.160469212582739
rejecting data with likelihood less than -2.54072675768480
rejected 30138 data points so far. Will perform rejection 9
more times at intervals of 1 iterations.
iter 7 lrate = 0.0500000000 LL = -2.0583445560 nd = 0.0090861193, D = 0.95516E-01 0.95516E-01 ( 13.68 s, 7.6 h)
Doing rejection ....
maximum likelihood value = -1.61419717964216
minimum likelihood value = -2.54868565651634
average likelihood value = -2.05834455599736
standard deviation = 0.160729968755536
rejecting data with likelihood less than -2.54053446226397
rejected 30241 data points so far. Will perform rejection 8
more times at intervals of 1 iterations.
iter 8 lrate = 0.0500000000 LL = -2.0575761156 nd = 0.0083848950, D = 0.12040E+00 0.12040E+00 ( 13.90 s, 7.7 h)
Doing rejection ....
maximum likelihood value = -1.61227278528098
minimum likelihood value = -2.54745500857799
average likelihood value = -2.05757611564512
standard deviation = 0.160900836724358
rejecting data with likelihood less than -2.54027862581819
rejected 30346 data points so far. Will perform rejection 7
more times at intervals of 1 iterations.
iter 9 lrate = 0.0500000000 LL = -2.0569184537 nd = 0.0077475771, D = 0.14722E+00 0.14722E+00 ( 14.84 s, 8.2 h)
Doing rejection ....
maximum likelihood value = -1.61097240302034
minimum likelihood value = -2.54581067854753
average likelihood value = -2.05691845365445
standard deviation = 0.160998105953585
rejecting data with likelihood less than -2.53991277151520
rejected 30445 data points so far. Will perform rejection 6
more times at intervals of 1 iterations.
iter 10 lrate = 0.0500000000 LL = -2.0563526199 nd = 0.0071754584, D = 0.17491E+00 0.17491E+00 ( 14.75 s, 8.2 h)
Doing rejection ....
maximum likelihood value = -1.61002422084216
minimum likelihood value = -2.54565539665346
average likelihood value = -2.05635261993232
standard deviation = 0.161067879008281
rejecting data with likelihood less than -2.53955625695716
rejected 30511 data points so far. Will perform rejection 5
more times at intervals of 1 iterations.
iter 11 lrate = 0.0500000000 LL = -2.0558783264 nd = 0.0066639133, D = 0.20269E+00 0.20269E+00 ( 15.21 s, 8.4 h)
Doing rejection ....
maximum likelihood value = -1.60929435618993
minimum likelihood value = -2.54302315300348
average likelihood value = -2.05587832635617
standard deviation = 0.161142445762817
rejecting data with likelihood less than -2.53930566364462
rejected 30571 data points so far. Will perform rejection 4
more times at intervals of 1 iterations.
iter 12 lrate = 0.0500000000 LL = -2.0554660517 nd = 0.0062113138, D = 0.22996E+00 0.22996E+00 ( 14.12 s, 7.8 h)
Doing rejection ....
maximum likelihood value = -1.60872588030599
minimum likelihood value = -2.54260357882775
average likelihood value = -2.05546605169460
standard deviation = 0.161200182465468
rejecting data with likelihood less than -2.53906659909100
rejected 30634 data points so far. Will perform rejection 3
more times at intervals of 1 iterations.
No gm present, setting num_models to 1
No W present, exiting
Reference to non-existent field 'W'.
Error in runamica15 (line 892)
weights = mods.W(:,:,1);
Thanks again so much!!
Sorry you're having so many problems with amica. The covariance eigenvalues seem right though for avg ref. It should work if you use 'pcakeep', 123. The problem seems to be that the minimum covariance eigenvalue is above the minimum threshold mineig. Hopefully it will work finally with the pcakeep arg. Then interpolate the maps in icawinv as though they were time points and overwrite EEG.icawinv with the result and set EEG.nbchan to the full num channels.
On Sun, Feb 17, 2019, 9:23 PM Jazelle759 <[email protected] wrote:
I tried running AMICA on the school PC and got this, [image: image] https://user-images.githubusercontent.com/47597128/52912425-40bdfa00-3316-11e9-86cd-4189151b22ac.png
Not sure how that happened X<, but anyways, yes, I interpolated channels before ICA. I've basically been following the codes found here https://sccn.ucsd.edu/wiki/Makoto%27s_useful_EEGLAB_code#Example_of_batch_code_to_preprocess_multiple_subjects_.2801.2F27.2F2017_updated.29 until the AMICA step which I've hit a roadblock.
I tried doing average reference without interpolating removed channels then running AMICA oth with and withot pcakeep. Results are as below.
% Save dataset (ParticipantNumber_AveRef) EEG = pop_saveset( EEG, 'filename',strcat(name,'_AveRef.set'),'filepath',fullfile(processingFolderPath,'ExperimentAveRef')); EEG = eeg_checkset( EEG ); Saving dataset... runamica15(EEG,'outdir',participantAmicaFolder,'do_opt_block',1, 'num_models', 1, ... 'do_reject',1,'rejstart',1,'rejint',1,'numrej',15,'rejsig',3, ... 'max_iter',2500,'writestep',50); % load the amica results into EEG EEG = eeg_loadamica(EEG,participantAmicaFolder); A subdirectory or file C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaResults\Participant01\ already exists. 1 processor name = LAPTOP-RNS6O05B 1 host_num = 1682198720 This is MPI process 1 of 1 ; I am process 1 of 1 on node: LAPTOP-RNS6O05B 1 : node root process 1 of 1 Processing arguments ... num_files = 1 FILES: C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAveRef \Participant01_AveRef.fdt num_dir_files = 1 initial matrix block_size = 128 do_opt_block = 1 blk_min = 256 blk_step = 256 blk_max = 1024 number of models = 1 max_thrds = 2 use_min_dll = 1 min dll = 1.000000000000000E-009 use_grad_norm = 1 min grad norm = 1.000000000000000E-007 number of density mixture components = 3 pdf type = 0 max_iter = 2500 num_samples = 1 data_dim = 124 field_dim = 826775 do_history = 0 histstep = 10 share_comps = 0 share_start = 100 comp_thresh = 0.990000000000000 share_int = 100 initial lrate = 5.000000000000000E-002 minimum lrate = 1.000000000000000E-008 minimum data covariance eigenvalue = 1.000000000000000E-012 lrate factor = 0.500000000000000 initial rholrate = 5.000000000000000E-002 rho0 = 1.50000000000000 min rho = 1.00000000000000 max rho = 2.00000000000000 rho lrate factor = 0.500000000000000 kurt_start = 3 num kurt = 5 kurt interval = 1 do_newton = 1 newt_start = 50 newt_ramp = 10 initial newton lrate = 1.00000000000000 do_reject = 1 num reject = 15 reject sigma = 3.00000000000000 reject start = 1 reject interval = 1 write step = 50 write_nd = 0 write_LLt = 1 dec window = 1 max_decs = 3 fix_init = 0 update_A = 1 update_c = 1 update_gm = 1 update_alpha = 1 update_mu = 1 update_beta = 1 invsigmax = 100.000000000000 invsigmin = 0.000000000000000E+000 do_rho = 1 load_rej = 0 load_c = 0 load_gm = 0 load_alpha = 0 load_mu = 0 load_beta = 0 load_rho = 0 load_comp_list = 0 do_mean = 1 do_sphere = 1 pcakeep = 124 pcadb = 30.0000000000000 byte_size = 4 doscaling = 1 scalestep = 1 A subdirectory or file C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaResults\Participant01\ already exists. output directory = C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaR esults\Participant01
1 : setting num_thrds to 2 ... 1 : using 2 threads. 1 : node_thrds = 2 bytes in real = 1 1 : REAL nbyte = 1 getting segment list ... blocks in sample = 826775 total blocks = 826775 node blocks = 826775 node 1 start: file 1 sample 1 index 1 node 1 stop : file 1 sample 1 index 826775 1 : data = 5.70339298248291 0.935514807701111 getting the mean ... mean = -1.447811822502307E-002 -4.881408335376367E-002 -5.660737602811115E-002 subtracting the mean ... getting the covariance matrix ... cnt = 826775 doing eig nx = 124 lwork = 153760 minimum eigenvalues = 2.377305388009759E-002 0.309337363531774 0.365926693662255 maximum eigenvalues = 3152.12089022707 825.109463263389 674.766848308228 num eigs kept = 124 getting the sphering matrix ... minimum eigenvalues = 2.377305388009759E-002 0.309337363531774 0.365926693662255 maximum eigenvalues = 3152.12089022707 825.109463263389 674.766848308228 num eigs kept = 124 sphering the data ... numeigs = 124 1 : Allocating variables ... 1 : Initializing variables ... 1 : Determining optimal block size .... No gm present, setting num_models to 1 No W present, exiting Reference to non-existent field 'W'.Error in runamica15 (line 892) weights = mods.W(:,:,1);
eeglab eeglab: options file is C:\Users\Jazelle\eeg_options.m EEGLAB: adding "MARA" v1.2 (see >> help eegplugin_MARA) EEGLAB: adding "amica" v1.5.1 (see >> help eegplugin_amica) EEGLAB: adding "clean_rawdata" v0.34 (see >> help eegplugin_clean_rawdata) EEGLAB: adding "dipfit" v2.3 (see >> help eegplugin_dipfit) EEGLAB: adding "erplab" v6.1.4 (see >> help eegplugin_erplab) EEGLAB: adding "firfilt" v1.6.2 (see >> help eegplugin_firfilt) EEGLAB: adding "postAmicaUtility" v2.01 (see >> help eegplugin_postAmicaUtility) EEGLAB: adding "tmullen-cleanline-696a7181b7d" v0 (see >> help eegplugin_cleanline) Warning: A newer version of EEGLAB (14.1.2) is available here This version fixes issues with Matlab 2018a. See Release notes for more informations. You may disable this message in the Option menu but will miss critical updates.
pop_loadset(): loading file C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAveRef\Participant01_AveRef.set ... Reading float file 'C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAveRef\Participant01_AveRef.fdt'... Creating a new ALLEEG dataset 1 Done.
% Run AMICA using calculated data rank with 'pcakeep' option if isfield(EEG.etc, 'clean_channel_mask') dataRank = min([rank(double(EEG.data')) sum(EEG.etc.clean_channel_mask)]); else dataRank = rank(double(EEG.data')); end runamica15(EEG.data, 'num_chans', EEG.nbchan,... 'outdir', participantAmicaFolder ,... 'pcakeep', dataRank, 'num_models', 1,... 'do_reject', 1, 'numrej', 15, 'rejsig', 3, 'rejint', 1); EEG.etc.amica = loadmodout15(participantAmicaFolder ); EEG.etc.amica.S = EEG.etc.amica.S(1:EEG.etc.amica.num_pcs, :); % Weirdly, I saw size(S,1) be larger than rank. This process does not hurt anyway. EEG.icaweights = EEG.etc.amica.W; EEG.icasphere = EEG.etc.amica.S; EEG = eeg_checkset(EEG, 'ica'); Writing data file: C:\Users\Jazelle\Desktop\Experiment\DataAnalysis\tmpdata95751.fdt A subdirectory or file C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaResults\Participant01\ already exists. 1 processor name = LAPTOP-RNS6O05B 1 host_num = 1682198720 This is MPI process 1 of 1 ; I am process 1 of 1 on node: LAPTOP-RNS6O05B 1 : node root process 1 of 1 Processing arguments ... num_files = 1 FILES: C:\Users\Jazelle\Desktop\Experiment\DataAnalysis\tmpdata95751.fdt num_dir_files = 1 initial matrix block_size = 128 do_opt_block = 0 blk_min = 256 blk_step = 256 blk_max = 1024 number of models = 1 max_thrds = 2 use_min_dll = 1 min dll = 1.000000000000000E-009 use_grad_norm = 1 min grad norm = 1.000000000000000E-007 number of density mixture components = 3 pdf type = 0 max_iter = 2000 num_samples = 1 data_dim = 124 field_dim = 826775 do_history = 0 histstep = 10 share_comps = 0 share_start = 100 comp_thresh = 0.990000000000000 share_int = 100 initial lrate = 5.000000000000000E-002 minimum lrate = 1.000000000000000E-008 minimum data covariance eigenvalue = 1.000000000000000E-012 lrate factor = 0.500000000000000 initial rholrate = 5.000000000000000E-002 rho0 = 1.50000000000000 min rho = 1.00000000000000 max rho = 2.00000000000000 rho lrate factor = 0.500000000000000 kurt_start = 3 num kurt = 5 kurt interval = 1 do_newton = 1 newt_start = 50 newt_ramp = 10 initial newton lrate = 1.00000000000000 do_reject = 1 num reject = 15 reject sigma = 3.00000000000000 reject start = 2 reject interval = 1 write step = 20 write_nd = 0 write_LLt = 1 dec window = 1 max_decs = 3 fix_init = 0 update_A = 1 update_c = 1 update_gm = 1 update_alpha = 1 update_mu = 1 update_beta = 1 invsigmax = 100.000000000000 invsigmin = 0.000000000000000E+000 do_rho = 1 load_rej = 0 load_c = 0 load_gm = 0 load_alpha = 0 load_mu = 0 load_beta = 0 load_rho = 0 load_comp_list = 0 do_mean = 1 do_sphere = 1 pcakeep = 124 pcadb = 30.0000000000000 byte_size = 4 doscaling = 1 scalestep = 1 A subdirectory or file C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaResults\Participant01\ already exists. output directory = C:\Users\Jazelle\Desktop\Experiment\DataProcessing\ExperimentAmicaR esults\Participant01
1 : setting num_thrds to 2 ... 1 : using 2 threads. 1 : node_thrds = 2 bytes in real = 1 1 : REAL nbyte = 1 getting segment list ... blocks in sample = 826775 total blocks = 826775 node blocks = 826775 node 1 start: file 1 sample 1 index 1 node 1 stop : file 1 sample 1 index 826775 1 : data = 5.70339298248291 0.935514807701111 getting the mean ... mean = -1.447811822502307E-002 -4.881408335376367E-002 -5.660737602811115E-002 subtracting the mean ... getting the covariance matrix ... cnt = 826775 doing eig nx = 124 lwork = 153760 minimum eigenvalues = 2.377305388009759E-002 0.309337363531774 0.365926693662255 maximum eigenvalues = 3152.12089022707 825.109463263389 674.766848308228 num eigs kept = 124 getting the sphering matrix ... minimum eigenvalues = 2.377305388009759E-002 0.309337363531774 0.365926693662255 maximum eigenvalues = 3152.12089022707 825.109463263389 674.766848308228 num eigs kept = 124 sphering the data ... numeigs = 124 1 : Allocating variables ... 1 : Initializing variables ... 1 : block size = 128 1 : entering the main loop ... iter 1 lrate = 0.0500000000 LL = -2.1879400453 nd = 0.0316209328, D = 0.63086E-01 0.63086E-01 ( 15.34 s, 8.5 h) Doing rejection .... maximum likelihood value = -1.94530531277019 minimum likelihood value = -12.8424480341366 average likelihood value = -2.18794004532239 standard deviation = 0.249405579766357 rejecting data with likelihood less than -2.93615678462146 rejected 11729 data points so far. Will perform rejection 14 more times at intervals of 1 iterations. iter 2 lrate = 0.0500000000 LL = -2.0951590716 nd = 0.0172690336, D = 0.55033E-01 0.55033E-01 ( 15.65 s, 8.7 h) Doing rejection .... maximum likelihood value = -1.74648645162986 minimum likelihood value = -3.03062210659308 average likelihood value = -2.09515907155584 standard deviation = 0.154974182576645 rejecting data with likelihood less than -2.56008161928578 rejected 23811 data points so far. Will perform rejection 13 more times at intervals of 1 iterations. iter 3 lrate = 0.0500000000 LL = -2.0700441090 nd = 0.0122252001, D = 0.47893E-01 0.47893E-01 ( 13.34 s, 7.4 h) Doing rejection .... maximum likelihood value = -1.66660347014341 minimum likelihood value = -2.66387051151617 average likelihood value = -2.07004410898280 standard deviation = 0.154976084710437 rejecting data with likelihood less than -2.53497236311411 rejected 28270 data points so far. Will perform rejection 12 more times at intervals of 1 iterations. iter 4 lrate = 0.0500000000 LL = -2.0631597399 nd = 0.0112155711, D = 0.48270E-01 0.48270E-01 ( 13.60 s, 7.5 h) Doing rejection .... maximum likelihood value = -1.63570475536690 minimum likelihood value = -2.59663802391389 average likelihood value = -2.06315973985731 standard deviation = 0.158387401110060 rejecting data with likelihood less than -2.53832194318749 rejected 29533 data points so far. Will perform rejection 11 more times at intervals of 1 iterations. iter 5 lrate = 0.0500000000 LL = -2.0606809694 nd = 0.0105759165, D = 0.57496E-01 0.57496E-01 ( 13.40 s, 7.4 h) Doing rejection .... maximum likelihood value = -1.62309489244165 minimum likelihood value = -2.56312046661083 average likelihood value = -2.06068096939705 standard deviation = 0.159893620368294 rejecting data with likelihood less than -2.54036183050194 rejected 29947 data points so far. Will perform rejection 10 more times at intervals of 1 iterations. iter 6 lrate = 0.0500000000 LL = -2.0593191199 nd = 0.0098341258, D = 0.73951E-01 0.73951E-01 ( 13.39 s, 7.4 h) Doing rejection .... maximum likelihood value = -1.61730196403345 minimum likelihood value = -2.55388876873334 average likelihood value = -2.05931911993658 standard deviation = 0.160469212582739 rejecting data with likelihood less than -2.54072675768480 rejected 30138 data points so far. Will perform rejection 9 more times at intervals of 1 iterations. iter 7 lrate = 0.0500000000 LL = -2.0583445560 nd = 0.0090861193, D = 0.95516E-01 0.95516E-01 ( 13.68 s, 7.6 h) Doing rejection .... maximum likelihood value = -1.61419717964216 minimum likelihood value = -2.54868565651634 average likelihood value = -2.05834455599736 standard deviation = 0.160729968755536 rejecting data with likelihood less than -2.54053446226397 rejected 30241 data points so far. Will perform rejection 8 more times at intervals of 1 iterations. iter 8 lrate = 0.0500000000 LL = -2.0575761156 nd = 0.0083848950, D = 0.12040E+00 0.12040E+00 ( 13.90 s, 7.7 h) Doing rejection .... maximum likelihood value = -1.61227278528098 minimum likelihood value = -2.54745500857799 average likelihood value = -2.05757611564512 standard deviation = 0.160900836724358 rejecting data with likelihood less than -2.54027862581819 rejected 30346 data points so far. Will perform rejection 7 more times at intervals of 1 iterations. iter 9 lrate = 0.0500000000 LL = -2.0569184537 nd = 0.0077475771, D = 0.14722E+00 0.14722E+00 ( 14.84 s, 8.2 h) Doing rejection .... maximum likelihood value = -1.61097240302034 minimum likelihood value = -2.54581067854753 average likelihood value = -2.05691845365445 standard deviation = 0.160998105953585 rejecting data with likelihood less than -2.53991277151520 rejected 30445 data points so far. Will perform rejection 6 more times at intervals of 1 iterations. iter 10 lrate = 0.0500000000 LL = -2.0563526199 nd = 0.0071754584, D = 0.17491E+00 0.17491E+00 ( 14.75 s, 8.2 h) Doing rejection .... maximum likelihood value = -1.61002422084216 minimum likelihood value = -2.54565539665346 average likelihood value = -2.05635261993232 standard deviation = 0.161067879008281 rejecting data with likelihood less than -2.53955625695716 rejected 30511 data points so far. Will perform rejection 5 more times at intervals of 1 iterations. iter 11 lrate = 0.0500000000 LL = -2.0558783264 nd = 0.0066639133, D = 0.20269E+00 0.20269E+00 ( 15.21 s, 8.4 h) Doing rejection .... maximum likelihood value = -1.60929435618993 minimum likelihood value = -2.54302315300348 average likelihood value = -2.05587832635617 standard deviation = 0.161142445762817 rejecting data with likelihood less than -2.53930566364462 rejected 30571 data points so far. Will perform rejection 4 more times at intervals of 1 iterations. iter 12 lrate = 0.0500000000 LL = -2.0554660517 nd = 0.0062113138, D = 0.22996E+00 0.22996E+00 ( 14.12 s, 7.8 h) Doing rejection .... maximum likelihood value = -1.60872588030599 minimum likelihood value = -2.54260357882775 average likelihood value = -2.05546605169460 standard deviation = 0.161200182465468 rejecting data with likelihood less than -2.53906659909100 rejected 30634 data points so far. Will perform rejection 3 more times at intervals of 1 iterations. No gm present, setting num_models to 1 No W present, exiting Reference to non-existent field 'W'.Error in runamica15 (line 892) weights = mods.W(:,:,1);
— You are receiving this because you commented. Reply to this email directly, view it on GitHub https://github.com/japalmer29/amica/issues/10#issuecomment-464450512, or mute the thread https://github.com/notifications/unsubscribe-auth/AKISSkFhhwTYfYxHvJbWybJFxdwaexthks5vOUnagaJpZM4a5Obu .
No, I'm sorry for repeatedly asking for help. Unfortunately, I am still having problems, I have tried on 1 laptop, 1 PC and 1 VM, the application keeps crashing. Seemingly randomly, with the same data input, once in every unknown number of tries, it will manage to run til the end. I decided to check windows event viewer and here's the screenshot.
I believe the application errors are from amica15mkl.exe crashing, and they all have a similar message. Attached a text file with the details from event viewer. eventviewer.txt
Any ideas?
Could you try setting ‘max_threads’, 1 (instead of default 2) and see if it still sometimes dies?
From: Jazelle759 [mailto:[email protected]] Sent: Wednesday, February 27, 2019 7:09 PM To: japalmer29/amica Cc: Jason Palmer; Comment Subject: Re: [japalmer29/amica] Issue with mpich (#10)
No, I'm sorry for repeatedly asking for help. Unfortunately, I am still having problems, I have tried on 1 laptop, 1 PC and 1 VM, the application keeps crashing. Seemingly randomly, with the same data input, once in every unknown number of tries, it will manage to run til the end. I decided to check windows event viewer and here's the screenshot.
https://user-images.githubusercontent.com/47597128/53482358-e70eba00-3ae3-11e9-9554-872d8ddc9792.JPG eventviewer
I believe the application errors are from amica15mkl.exe crashing, and they all have a similar message. Attached a text file with the details from event viewer. eventviewer.txt https://github.com/japalmer29/amica/files/2909624/eventviewer.txt
Any ideas?
— You are receiving this because you commented. Reply to this email directly, view it on GitHub https://github.com/japalmer29/amica/issues/10#issuecomment-467802854 , or mute the thread https://github.com/notifications/unsubscribe-auth/AKISSligCP9GtL8YTwSUw_mDSvWWdYqkks5vRlkigaJpZM4a5Obu . https://github.com/notifications/beacon/AKISSmU1WMT91AsVhKjDfKkb_KuDK-ZJks5vRlkigaJpZM4a5Obu.gif
Ok. I just tried running 1 data set and it seems to work but it is predicting more than 12 hours to complete each data set. Is there anyway I can speed it up without the application dying? It is utilizing less than 15% of the CPU power.
Maybe use fixed 'block_size' of 64, 128, or 256, with 'max_threads', 2. Maybe small enough block size won't crash and will be faster.
On Wed, Feb 27, 2019, 9:36 PM Jazelle759 [email protected] wrote:
Ok. I just tried running 1 data set and it seems to work but it is predicting more than 12 hours to complete each data set. Is there anyway I can speed it up without the application dying? It is utilizing less than 15% of the CPU power.
— You are receiving this because you commented. Reply to this email directly, view it on GitHub https://github.com/japalmer29/amica/issues/10#issuecomment-467846173, or mute the thread https://github.com/notifications/unsubscribe-auth/AKISShvOPXaJlYFt-8kYLF12WZ2W2d-1ks5vRnvogaJpZM4a5Obu .
Also use 'do_opt_block', 0, (or leave that keyword arg out).
On Wed, Feb 27, 2019, 10:25 PM Jason Palmer [email protected] wrote:
Maybe use fixed 'block_size' of 64, 128, or 256, with 'max_threads', 2. Maybe small enough block size won't crash and will be faster.
On Wed, Feb 27, 2019, 9:36 PM Jazelle759 [email protected] wrote:
Ok. I just tried running 1 data set and it seems to work but it is predicting more than 12 hours to complete each data set. Is there anyway I can speed it up without the application dying? It is utilizing less than 15% of the CPU power.
— You are receiving this because you commented. Reply to this email directly, view it on GitHub https://github.com/japalmer29/amica/issues/10#issuecomment-467846173, or mute the thread https://github.com/notifications/unsubscribe-auth/AKISShvOPXaJlYFt-8kYLF12WZ2W2d-1ks5vRnvogaJpZM4a5Obu .
hello Would you please help me I have the same issue and I really do not understand how to solve it since I am a beginner Reference to non-existent field 'W'.
Error in runamica15 (line 892) weights = mods.W(:,:,1);
Error in pop_runamica (line 239) [W,S,mods] = runamica15(datfile,arglist{:});
Error while evaluating Menu Callback.
Matlab is asking me to download mpich2-1.4-win-x86-64 which is downloaded and installed
