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spDist_scoreEyeData.m
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spDist_scoreEyeData.m
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function spDist_scoreEyeData(subj,sess,WHICH_EXCL)
%
% adapted from wmPri_scoreEyeData
% TCS 8/30/2018
%
% preprocesses eye position data (EDF) files from spDist scanning experiment
%
% feedback = 7
% pre-targets = 1
%
% trial start/end = 1/10
%
% NOTE: to 'skip' WHICH_EXCL argument (and to not give a 'null' argument,
% which is a valid option here, use an empty CELL: {} - giving [] will not
% visually mark any trials for exclusion in QC images.
%
close all;
%root = spDist_loadRoot;
root = '/share/data/spDist/'
%root = sprintf('/d/DATA/data/spDist/')
%ifg_fn = '~/Documents/MATLAB/toolboxes_dev/iEye_ts/examples/p_500hz.ifg';
%ifg_fn = '/Volumes/home/grace/iEye/examples/p_500hz.ifg';
ifg_fn = '/share/home/grace/iEye/examples/p_500hz.ifg';
%ifg_fn = '/d/DATA/home/grace/iEye/examples/p_500hz.ifg';
task_dir = 'spDist';
if nargin < 1
%subj = {'AY','CC','KD','MR','XL'};
subj = {'CC','MR','AY'}
% subj = {'KD','CC','AY','MR','XL','EK','SF'};
end
if nargin < 2
sess = {{'spDistLong1','spDistLong2'},{'spDistLong1','spDistLong2'},{'spDistLong1','spDistLong2'}};
%sess = {{'spDist1','spDist2'},{'spDist1','spDist2'},{'spDist1','spDist2'},{'spDist1','spDist2'},{'spDist1','spDist2'},{'spDist1','spDist2'},{'spDist1','spDist2'}}; %two sessions removed
%sess = {{'spDist1','spDist2'},{'spDist1','spDist2'},{'spDist1','spDist2'}};
end
if nargin < 3 || iscell(WHICH_EXCL) && isempty(WHICH_EXCL)
WHICH_EXCL = [11 13 20 21 22]; % everything except calibration errors (for now)
end
excl_criteria.drift_fix_thresh = 5; % how far a fixation can be from center to drop a trial
QCdir = sprintf('%s/%s_iEye_scoreQC_61520',root,task_dir);
%QCdir = '/Volumes/data/wmPri/wmPri_iEye_score_QC';
fn_prefix = 'spDist_scanner'; % OR _ds_preCue
% set up iEye params
ii_params = ii_loadparams;
ii_params.trial_end_value = 10;
ii_params.drift_epoch = [1 2 3 4 5];
ii_params.calibrate_epoch = 7;
ii_params.calibrate_mode = 'run';
ii_params.calibrate_select_mode = 'nearest';
ii_params.blink_window = [200 200];
ii_params.plot_epoch = [3 4 5 6 7];
ii_params.calibrate_limits = 2.5; % original ecc b/w 9 and 16...
excl_criteria.micro_dur_thresh = 150;
excl_criteria.micro_amp_min = 0.5;
excl_criteria.micro_amp_max = 2.0;
ii_params.microsacc_amplitude_min =0.5;
ii_params.microsacc_amplitude_max= 2.0;
ii_params.ppd = 31.8578; % for scanner, 1280 x 1024
for ss = 1:length(subj)
for sessidx = 1:length(sess{ss})
%fns = sprintf('%s/raw/%s_%s_behav/%s_%s_r*_%s_multiDist_*.edf',root,subj{ss},sess{ss}{sessidx},subj{ss},sess{ss}{sessidx},fn_prefix);
fns = sprintf('%sraw/%s_%s_behav/%s_%s_r*_%s_*.edf',root,subj{ss},sess{ss}{sessidx},subj{ss},sess{ss}{sessidx},fn_prefix);
thisf = dir(fns);
clear fns;
run_labels = nan(length(thisf),1);
ii_trial = cell(length(thisf),1);
for ff = 1:length(thisf)
fprintf('Preprocessing %s\n',thisf(ff).name);
this_edf = sprintf('%s/raw/%s_%s_behav/%s',root,subj{ss},sess{ss}{sessidx},thisf(ff).name);
% look for matching mat file
%fns = sprintf('%s/data/%s_%s*block%02.f_*.mat',root,subj{ss},fn_prefix,block_num);
%matf = dir(fns);
matf = sprintf('%smat',this_edf(1:end-3));
thisbehav = load(matf);
% for convenience...
thisbehav = thisbehav.p;
% save:
% 1: distractor condition (1 = no, 2 = distractor)
% 2,3: target position X, Y (dva)
% 4,5: distractor position X,Y (or NaN; dva)
% 6: distractor bin (-3:3; NaN); Cartesian, so + is CCW
% 7: distractor direction (1 = CCW, 2 = CW, NaN = no dst)
% 8: correct? (0 or 1; NaN)
% 9: RT for mean dist 1
% 10: jitter amt
% NOTE: for spDistLong? files, only takes the first value of
% direction, RT
trialinfo = nan(thisbehav.ntrials,9);
trialinfo(:,1) = thisbehav.conditions(:,1);
trialinfo(:,[2 3]) = thisbehav.wm_coords;
trialinfo(:,[4 5]) = thisbehav.dist_coords;
trialinfo(:,6) = thisbehav.conditions(:,2);
trialinfo(:,7) = thisbehav.dist_dir(:,1);
trialinfo(trialinfo(:,1)==1,8) = thisbehav.correct(trialinfo(:,1)==1);
trialinfo(:,9) = nanmean([thisbehav.dist_RT(:,2) thisbehav.dist_RT(:,4)],2);
%trialinfo(:,9) = thisbehav.dist_RT(:,1);
trialinfo(:,10) = thisbehav.jitter_amt;
%following acc and coh added 06/15/20
trialinfo(:,11) = thisbehav.acc;
% trialinfo(:,12) = thisbehav.task_coh;
trialinfo(:,12) = thisbehav.task_coh(2); %will be same in both dists
%trialinfo(:,13) = thisbehav.dist_RT;
% custom for each expt
block_num = str2double(matf(strfind(matf,'_r')+[2 3]));
run_labels(ff) = block_num;
% set up trialinfo
% - to match w/ wmChoose, we'll store condition #, then xy for
% item 1 (cued) and item 2 (uncued)
% coords = cell(thisbehav.ntrials,1);
% for tt = 1:thisbehav.ntrials
% coords{tt} = {thisbehav.targ_coords{1}(tt,:), thisbehav.targ_coords{2}(tt,:)};
% end
% set up trialinfo
% trial_info = horzcat(thisbehav.conditions,thisbehav.targ_coords{:});
preproc_fn = sprintf('%s/%s_iEye_preproc_61520/%s_%s_r%02.f_preproc.mat',root,task_dir,subj{ss},sess{ss}{sessidx},block_num);
% preprocess raw data and extract saccades
[ii_data,ii_cfg,ii_sacc,ii_microsacc] = ii_preproc(this_edf,ifg_fn,preproc_fn,ii_params,trialinfo);
% define resp epoch, fix epoch, etc. note that default behavior
% of ii_scoreMGS will pick these up automatically
ii_trial{ff} = ii_scoreMGS(ii_data,ii_cfg,ii_sacc,{'TarX', 'TarY'},ii_params.calibrate_epoch-1,ii_params.drift_epoch,excl_criteria,[],'strict',[NaN 0],ii_microsacc);
%[ii_trial{ff},ii_cfg] = ii_scoreMGS(ii_data,ii_cfg,ii_sacc,{'TarX', 'TarY'},4,[1 2 3],excl_criteria,[],'lenient',[9 0],ii_microsacc); %added TargCoords, respEpoch
close all;
clear preproc_fn trial_info cond thisbehav matf fns block_num this_edf thisbehav;
end
ii_sess = ii_combineruns(ii_trial,run_labels);
save(sprintf('%s/%s_behav_61520/%s_%s_scored.mat',root,task_dir,subj{ss},sess{ss}{sessidx}),'ii_sess','WHICH_EXCL');
% exclusion report
fh_excl = ii_plotQC_exclusions(ii_sess,ii_cfg,WHICH_EXCL,0);
for ff = 1:length(fh_excl)-1
saveas(fh_excl(ff),sprintf('%s/%s_%s_excl_dot_%02.f.png',QCdir,subj{ss},sess{ss}{sessidx},ff));
end
saveas(fh_excl(end),sprintf('%s/%s_%s_excl_all.png',QCdir,subj{ss},sess{ss}{sessidx}),0);
close(fh_excl);
% all trials
fh_trials = ii_plotQC_alltrials(ii_sess,ii_cfg,WHICH_EXCL,0);
for ff = 1:length(fh_trials)
set(fh_trials(ff),'Renderer','painters'); % hack to make sure saving as png works...
saveas(fh_trials(ff),sprintf('%s/%s_%s_trials_r%02.f.png',QCdir,subj{ss},sess{ss}{sessidx},run_labels(ff)));
end
close(fh_trials);
close all hidden;
clear ii_sess;
end
end
end