small fixes and perfornamce updates

sc_loadmuadata.m

@@ -9,10 +9,22 @@
 switch muafile_ext
 
     case 'spikes' % open ephys data format
-        [data, timestamps, info] = load_open_ephys_data(muafile);
+        [data, timestamps, info] = load_open_ephys_data_faster(muafile);
+
+       % remove end of file? 
+       % cutoff_t=3.9100e+03;
+       % cutoff=min(find(timestamps>cutoff_t));
+       % data=data(1:cutoff,:,:);
+       % timestamps=timestamps(1:cutoff);
+
 
         features.chnumstr = info.header.electrode;
+
         features.sourcechannel= str2num(info.header.electrode(end-1:end));
+        if numel( features.sourcechannel)==0
+            features.sourcechannel= str2num(info.header.electrode(end));
+        end;
+
         sourcechannel=features.sourcechannel; % just so we dont overwrite it in  'features=sc_mua2features(mua,s_opt);'
 
 
@@ -474,6 +486,9 @@
 
     features.waveformscale=0.0001;
 
+    mua.waveforms( find(abs(mua.waveforms) > 10000) ) =0;
+ mua.waveforms( isnan(mua.waveforms) ) =0;
+
     % find appropriate scale for plotting waveforms
     features.waveformscale=0.1 ./ quantile(mua.waveforms(1:100:end)-mean(mua.waveforms(1:100:end)),.95);
 

sc_mua2features.m

@@ -136,6 +136,22 @@
 
     if n==1; features.name{c}=['time']; end;
 
+
+    %max peak
+    if 0
+        for d=1:mua.ncontacts %size(spike,1)
+            c=c+1;
+            %features.data(c,n)= nle(d,n);
+
+            x=spike(trodeboundaries(d):trodeboundaries(d+1)-1);
+
+            features.data(c,n)= -x(9);
+
+            if n==1; features.name{c}=['peak ',num2str(d)]; end;
+
+        end;
+    end;
+
     %peak height
     for d=1:mua.ncontacts %size(spike,1)
         x=spike(trodeboundaries(d):trodeboundaries(d+1)-1);
@@ -144,7 +160,7 @@
         c=c+1;
         features.data(c,n)= neo(d);
 
-        if n==1; features.name{c}=['peak ',num2str(d)]; end;
+        if n==1; features.name{c}=['max ',num2str(d)]; end;
 
     end;
 

sc_updateclusterimages.m

@@ -45,10 +45,11 @@
         sfact = features.imagesize/x;
         features.waveforms_hi=zeros(size(mua.waveforms,1),round(x*sfact));
 
+        ii_intp=round(L_im);
 
         for i=1:size( mua.waveforms,1)
 
-            if mod(i,4000)==0
+            if mod(i,10000)==0
                 clf; hold on;
                 fill([-2 -2 5 5],[-2 2 2 -2],'k','FaceColor',[.95 .95 .95]);
 
@@ -66,9 +67,8 @@
                 drawnow;
             end;
 
-
-
-            features.waveforms_hi(i,:) = interp1(1:x,mua.waveforms(i,:),L_im, 'linear'); % use 'linear' for speed or even 'nearest'
+            %features.waveforms_hi(i,:) = interp1(1:x,mua.waveforms(i,:),L_im, 'nearest'); % use 'linear' for speed or even 'nearest'
+            features.waveforms_hi(i,:) = mua.waveforms(i,ii_intp);
         end;
     end;
 end;

simple_clust.m

@@ -105,7 +105,7 @@
 % specify what features to compute:
 s_opt.features.pca=0;
 s_opt.features.wavelet=0;
-s_opt.features.nonlinear_energy=1;
+s_opt.features.nonlinear_energy=0;
 s_opt.features.max_derivative=1;
 
 %% init