bml_sync_neuroomega_event

 BML_SYNC_NEUROOMEGA_EVENT synchronizes neuroomega files based on events

 Use as 
    sync_roi = bml_sync_neuroomega_event(cfg)

   cfg.master_events - events to align to in annot table in master time
   cfg.roi - roi table for neuroomega files to be synchronized
   cfg.timewarp - logical: Should slave time be warped? defaults to 
            true.
   cfg.scan - double: number of seconds to scan for optimal alignment 
             (defaults to 100)
   cfg.scan_step - double: step size of initial scan for alignment
             (defaults to 0.1)
   cfg.diagnostic_plot - logical
   cfg.timetol - numeric, time tolerance in seconds. Defaults to 1e-6
   cfg.min_events - integer. Minimum number of events required to attemp
             alingment, defaults to 10. 
   cfg.strict - logical. Issue errors if timetol is violated instead of errors. 
             Defaults to false. 

 returns a roi table

0001 function sync_roi = bml_sync_neuroomega_event(cfg)
0002 
0003 % BML_SYNC_NEUROOMEGA_EVENT synchronizes neuroomega files based on events
0004 %
0005 % Use as
0006 %    sync_roi = bml_sync_neuroomega_event(cfg)
0007 %
0008 %   cfg.master_events - events to align to in annot table in master time
0009 %   cfg.roi - roi table for neuroomega files to be synchronized
0010 %   cfg.timewarp - logical: Should slave time be warped? defaults to
0011 %            true.
0012 %   cfg.scan - double: number of seconds to scan for optimal alignment
0013 %             (defaults to 100)
0014 %   cfg.scan_step - double: step size of initial scan for alignment
0015 %             (defaults to 0.1)
0016 %   cfg.diagnostic_plot - logical
0017 %   cfg.timetol - numeric, time tolerance in seconds. Defaults to 1e-6
0018 %   cfg.min_events - integer. Minimum number of events required to attemp
0019 %             alingment, defaults to 10.
0020 %   cfg.strict - logical. Issue errors if timetol is violated instead of errors.
0021 %             Defaults to false.
0022 %
0023 % returns a roi table
0024 
0025 scan_step         = bml_getopt(cfg,'scan_step',0.1);
0026 scan              = bml_getopt(cfg,'scan',100);
0027 timewarp          = bml_getopt(cfg,'timewarp',false);
0028 master_events     = bml_getopt(cfg,'master_events');
0029 roi               = bml_getopt(cfg,'roi');
0030 diagnostic_plot   = bml_getopt(cfg,'diagnostic_plot',false);
0031 timetol           = bml_getopt(cfg,'timetol',1e-6);
0032 min_events        = bml_getopt(cfg,'min_events',10);
0033 strict            = bml_getopt(cfg,'strict',false);
0034 
0035 assert(~isempty(roi),'roi required');
0036 assert(~isempty(master_events),'master_events required');
0037 
0038 all_slave_dt = zeros(height(roi),1);
0039 all_warpfactor = ones(height(roi),1);
0040 all_meanerror = zeros(height(roi),1);
0041 for i=1:height(roi)
0042   
0043   %getting events
0044     i_slave_events = bml_read_event(roi(i,:));
0045   if isempty(i_slave_events) || length(i_slave_events) < min_events
0046     all_slave_dt(i) = nan;
0047     all_warpfactor(i) = nan;
0048   else
0049     cfg=[]; cfg.Fs = 1; %already in seconds
0050     cfg.starts = roi.starts(i);
0051     i_slave_events = bml_event2annot(cfg,i_slave_events);
0052     i_slave_events = bml_annot_table(i_slave_events);
0053     
0054     %doing time alingment
0055     cfg=[]; 
0056     cfg.scan=scan; 
0057     cfg.scan_step=scan_step; 
0058     cfg.timewarp = timewarp; 
0059     [slave_dt, min_cost, warpfactor]=bml_timealign_annot(cfg,master_events,i_slave_events);
0060     all_slave_dt(i) = slave_dt;
0061     all_warpfactor(i) = warpfactor;
0062 
0063     if diagnostic_plot
0064       tbar = mean(i_slave_events.starts);
0065       i_slave_events_starts = (i_slave_events.starts - tbar) .* warpfactor + tbar + slave_dt;
0066       figure;
0067       plot(master_events.starts,ones(1,height(master_events)),'bo');
0068       hold on;
0069       plot(i_slave_events_starts,ones(1,length(i_slave_events_starts)),'r*');
0070     end
0071 
0072     all_meanerror(i) = min_cost/height(i_slave_events);
0073     if all_meanerror(i) > timetol
0074       if strict
0075         error('could not time align within timetol. Mean error %f > %f. File %s',all_meanerror(i),timetol,roi.name{i});
0076       else
0077         warning('could not time align within timetol. Mean error %f > %f. File %s. Ignoring this file during consolidation.',all_meanerror(i),timetol,roi.name{i});
0078         all_slave_dt(i) = nan;
0079         all_warpfactor(i) = nan;
0080       end
0081     end
0082   end
0083 end
0084 
0085 if ~timewarp
0086   all_slave_dt = repmat(nanmean(all_slave_dt),length(all_slave_dt),1);
0087 end
0088 
0089 %consolidating results
0090 roi.slave_dt = all_slave_dt;
0091 roi.warpfactor = all_warpfactor;
0092 roi.alignment_error = all_meanerror;
0093 
0094 cfg=[];
0095 cfg.criterion = @(x) (abs((max(x.ends)-min(x.starts))-sum(x.duration))<10e-3);
0096 cont_roi = bml_annot_consolidate(cfg,roi);
0097 
0098 consolidated_roi = table();
0099 for i=1:height(cont_roi)
0100   i_roi = roi(roi.id >= cont_roi.id_starts(i) & roi.id <= cont_roi.id_ends(i),:);
0101   i_roi.slave_dt(:) = nanmean(i_roi.slave_dt);
0102   i_roi.warpfactor(:) = nanmean(i_roi.warpfactor);
0103   consolidated_roi = [consolidated_roi; i_roi];
0104 end
0105 roi = consolidated_roi;
0106 
0107 if any(ismissing(roi.slave_dt))
0108   warning('Using mean dt for some files');
0109   roi.slave_dt(ismissing(roi.slave_dt)) = nanmean(roi.slave_dt);
0110 end
0111 if any(ismissing(roi.warpfactor))
0112   warning('Using mean warpfactor for some files');
0113   roi.warpfactor(ismissing(roi.warpfactor)) = nanmean(roi.warpfactor);
0114 end
0115 
0116 midpoint_a = (roi.ends + roi.ends) ./ 2;
0117 midpoint_t = (roi.t1 + roi.t2) ./ 2;
0118 roi.starts = (roi.starts - midpoint_a) .* roi.warpfactor + midpoint_a + roi.slave_dt;
0119 roi.ends = (roi.ends - midpoint_a) .* roi.warpfactor + midpoint_a + roi.slave_dt;
0120 roi.t1 = (roi.t1 - midpoint_t) .* roi.warpfactor + midpoint_t + roi.slave_dt;
0121 roi.t2 = (roi.t2 - midpoint_t) .* roi.warpfactor + midpoint_t + roi.slave_dt;
0122 
0123 roi.chunk_id = (1:height(roi))';
0124 roi.sync_channel = repmat({'digital'},height(roi),1);
0125 roi.sync_type = repmat({'slave'},height(roi),1);
0126 
0127 sync_roi = bml_roi_table(roi);
0128 
0129 sync_roi(:,{'id','starts','ends','duration','name','warpfactor'})
0130