allow removing nonnegativity constraint by removing the deconvolution…

… step

ca_source_extraction/@Sources2D/update_temporal_parallel.m

@@ -280,7 +280,10 @@ function update_temporal_parallel(obj, use_parallel, use_c_hat)
 obj.C_raw = bsxfun(@times, C_new, 1./aa);
 fprintf('Deconvolve and denoise all temporal traces again...\n');
 if deconv_flag
-    C_new = obj.deconvTemporal();
+    obj.C = obj.deconvTemporal();
+else
+    obj.C_raw = bsxfun(@minus, obj.C_raw, min(obj.C_raw,[],2)); 
+    obj.C = obj.C_raw; 
 end
 fprintf('Done!\n');
 

ca_source_extraction/utilities/HALS_temporal.m

@@ -63,13 +63,9 @@
 
         if ~deconv_flag
             % no deconvolution, just thresholding
-%             C_raw(k, :) = ck_raw;
             ck_raw = ck_raw -min(ck_raw); 
+            C(k, :) = ck_raw; 
             C_raw(k, :) = ck_raw; 
-%             C(k, :) = max(0, ck_raw);
-%             if miter==maxIter
-%                 C_raw(k, :) = ck_raw;
-%             end
         else
             %remove baseline and estimate noise level. estiamte the noise
             %using two methods: psd and histogram. choose the one with
@@ -79,7 +75,7 @@
             %             catch
             %                 sn_hist = inf;
             %             end
-            %             b = mean(ck_raw(ck_raw<median(ck_raw)));
+            b = mean(ck_raw(ck_raw<median(ck_raw)));
             sn_psd = GetSn(ck_raw);
             %             if sn_psd<sn_hist
             %                 tmp_sn = sn_psd;
@@ -89,7 +85,7 @@
             %             end
 
             % subtract the baseline
-            %             ck_raw = ck_raw -b;
+            ck_raw = ck_raw -b;
             sn(k) = sn_psd;
 
             % deconvolution

demos/demo_large_data_1p.m

@@ -16,7 +16,7 @@
 gSig = 3;           % pixel, gaussian width of a gaussian kernel for filtering the data. 0 means no filtering
 gSiz = 13;          % pixel, neuron diameter
 ssub = 1;           % spatial downsampling factor
-with_dendrites = true;   % with dendrites or not
+with_dendrites = false;   % with dendrites or not
 if with_dendrites
     % determine the search locations by dilating the current neuron shapes
     updateA_search_method = 'dilate';  %#ok<UNRCH>
@@ -34,6 +34,7 @@
 % -------------------------      TEMPORAL     -------------------------  %
 Fs = 10;             % frame rate
 tsub = 1;           % temporal downsampling factor
+deconv_flag = true;     % run deconvolution or not 
 deconv_options = struct('type', 'ar1', ... % model of the calcium traces. {'ar1', 'ar2'}
     'method', 'foopsi', ... % method for running deconvolution {'foopsi', 'constrained', 'thresholded'}
     'smin', -5, ...         % minimum spike size. When the value is negative, the actual threshold is abs(smin)*noise level
@@ -99,6 +100,7 @@
     'spatial_constraints', spatial_constraints, ...
     'spatial_algorithm', spatial_algorithm, ...
     'tsub', tsub, ...                       % -------- temporal --------
+    'deconv_flag', deconv_flag, ...
     'deconv_options', deconv_options, ...
     'nk', nk, ...
     'detrend_method', detrend_method, ...