Merge branch 'master' of https://github.com/canlab/CanlabCore

CanlabCore/@atlas/select_atlas_subset.m

@@ -20,6 +20,9 @@
 % 'labels_2' : If you enter any field name in the object, e.g., labels_2,
 % the function will search for keyword matches here instead of in obj.labels.
 %
+% 'exact' : If you enter 'exact', function will not look for overlaps in
+% names, and only look for exact string matches.
+%
 % Examples:
 % 
 % atlasfile = which('Morel_thalamus_atlas_object.mat');
@@ -59,6 +62,9 @@
 % Edited by tor, 12/2019, to use any field to select labels; and update
 % auxiliary label fields too.
 %
+% Edited by Michael Sun, 09/04/2023, added an 'exact' flag, so that users
+% can select to match string labels exactly and not capture regions with
+% overlapping labels e.g., Cblm_Vermis_VI and Cblm_Vermis_VII.
 
 % -------------------------------------------------------------------------
 % DEFAULTS AND INPUTS
@@ -67,6 +73,7 @@
 strings_to_find = [];
 integers_to_find = [];
 doflatten = false;
+doexact=false;
 
 % for entry of optional field to search for keywords
 myfields = fieldnames(obj);
@@ -87,6 +94,7 @@
              case 'flatten', doflatten = true;
 
                  %             case 'xxx', xxx = varargin{i+1}; varargin{i+1} = [];
+            case 'exact', doexact = true;
 
             otherwise
 
@@ -117,14 +125,22 @@
 for i = 1:length(strings_to_find)
 
     % Find which names match
-    wh = ~cellfun(@isempty, strfind(obj.(mylabelsfield), strings_to_find{i}));
-    if strmatch(mylabelsfield, 'label_descriptions')
-        wh=wh';
+    if doexact == false
+        wh = ~cellfun(@isempty, strfind(obj.(mylabelsfield), strings_to_find{i}));
+        if strmatch(mylabelsfield, 'label_descriptions')
+            wh=wh'; 
+        end
+
+        to_extract = to_extract | wh;
+    % Addition by Michael Sun 09/04/2023: Match strings exactly
+    else
+        wh = strcmp(obj.(mylabelsfield), strings_to_find{i});
+        if strmatch(mylabelsfield, 'label_descriptions')
+            wh=wh'; 
+        end
+
+        to_extract = to_extract | wh;
     end
-
-
-    to_extract = to_extract | wh;
-
 end
 
 % -------------------------------------------------------------------------

CanlabCore/Data_processing_tools/downsample_scnlab.m

@@ -15,6 +15,17 @@
 %   **new_samprate:**
 %        desired sampling rate in Hz
 %
+%   **doplot:**
+%        visualize the plot. Default: off
+% 
+%   **method:**
+%        Interpolation method. Default: linear
+%        'linear' (default) | 'nearest' | 'next' | 'previous' | 'pchip' | 
+%        'cubic' | 'v5cubic' | 'makima' | 'spline'
+% 
+%   **extrap:**
+%        Extrapolation strategy, specified as 'extrap' or a real scalar value.
+% 
 % ..
 %    I prefer this to matlab's downsample.m because linear interpolation is
 %    robust and does fewer weird things to the data.
@@ -30,10 +41,30 @@
 %    % every 100 / TR = 100/.5 = 200 samples
 %
 %    [yi, xi] = downsample_scnlab(y, 100, .5)
+%    [yi, xi] = downsample_scnlab(y, 100, .5, 'doplot', 'method', 'spline')
 %
+% Programmers notes:
+% 8/25/2023 - Byeol
+% Add more method options for interp1 function.
+
 
 doplot = 0;
-if length(varargin) > 0, doplot = varargin{1}; end
+method = 'linear';
+extrapolation = 'extrap';
+
+for i = 1:length(varargin)
+    if ischar(varargin{i})
+        switch varargin{i}
+            % functional commands
+            case {'doplot'}
+                doplot = 1;
+            case {'method'}
+                method = varargin{i+1};
+            case {'extrap'}
+                extrapolation = varargin{i+1};
+        end
+    end
+end
 
 downsamplerate = orig_samprate ./ new_samprate;
 
@@ -49,7 +80,7 @@
 xi = linspace(0, nobs, nobs_out);
 
 
-yi = interp1(x, y, xi, 'linear', 'extrap');
+yi = interp1(x, y, xi, method, extrapolation);
 
 if doplot
 

CanlabCore/HRF_Est_Toolbox2/Example2.m

@@ -20,11 +20,13 @@
 if isempty(mypath), error('Cannot find directory with ilogit.m and other functions. Not on path?'); end
 [mydir] = fileparts(mypath);
 
-% load(fullfile(mydir,'timecourse'))
-% 
-% tc = (tc- mean(tc))/std(tc);
-% len = length(tc);
+load(fullfile(mydir,'timecourse'))
+
+tc = (tc- mean(tc))/std(tc);
+len = length(tc);
 
+
+%%
 % Create HRFs
 
 [xBF] = spm_get_bf(struct('dt', .5, 'name', 'hrf (with time and dispersion derivatives)', 'length', 32));
@@ -35,7 +37,7 @@
 for i = 2:3, xx = conv(xBF.bf(:,i), [1 1]');
     Xtrue1(:, i) = xx(1:66);
 end
-hrf1 = Xtrue * [1 .5 .3]';
+hrf1 = Xtrue1 * [1 .5 .3]';
 
 
 clear Xtrue2
@@ -312,21 +314,56 @@
 
 figure; hold on;
 
-plot(xsecs, beta1*hrf1, 'k', 'LineWidth', 2)
-plot(xsecs, beta2*hrf2, 'k', 'LineWidth', 2)
+% plot(xsecs, beta1*hrf1, 'k--', 'LineWidth', 2)
+% plot(xsecs, beta2*hrf2, 'k--', 'LineWidth', 2)
+% 
+% xsecs1 = xsecs(1:length(h1));
+% han2 = plot(xsecs1, h1,'r', 'LineWidth', 2);
+% xsecs2 = xsecs(1:length(h2));
+% han2(3:4) = plot(xsecs2, h2,'g', 'LineWidth', 2);
+% xsecs3 = xsecs(1:length(h3));
+% han2(5:6) = plot(xsecs3, h3,'m', 'LineWidth', 2);
+% xsecs4 = xsecs(1:length(h4));
+% han2(7:8) = plot(xsecs4, h4,'b', 'LineWidth', 2);
+% xsecs5 = xsecs(1:length(h5));
+% han2(9:10) = plot(xsecs5, h5,'y', 'LineWidth', 2);
+% 
+% legend(han2,{'IL1' 'IL2' 'sFIR1' 'sFIR2' 'DD1' 'DD2' 'Spline1' 'Spline2' 'NL1' 'NL2'})
+% title('Estimated HRF');
+
+subplot 121
+hold
+plot(xsecs, beta1*hrf1, 'k--', 'LineWidth', 2)
 
 xsecs1 = xsecs(1:length(h1));
-han2 = plot(xsecs1, h1,'r', 'LineWidth', 2);
+han2 = plot(xsecs1, h1(:,1),'r', 'LineWidth', 2);
 xsecs2 = xsecs(1:length(h2));
-han2(3:4) = plot(xsecs2, h2,'g', 'LineWidth', 2);
+han2(2) = plot(xsecs2, h2(:,1),'g', 'LineWidth', 2);
 xsecs3 = xsecs(1:length(h3));
-han2(5:6) = plot(xsecs3, h3,'m', 'LineWidth', 2);
+han2(3) = plot(xsecs3, h3(:,1),'m', 'LineWidth', 2);
 xsecs4 = xsecs(1:length(h4));
-han2(7:8) = plot(xsecs4, h4,'b', 'LineWidth', 2);
+han2(4) = plot(xsecs4, h4(:,1),'b', 'LineWidth', 2);
 xsecs5 = xsecs(1:length(h5));
-han2(9:10) = plot(xsecs5, h5,'y', 'LineWidth', 2);
+han2(5) = plot(xsecs5, h5(:,1),'y', 'LineWidth', 2);
 
-legend(han2,{'IL1' 'IL2' 'sFIR1' 'sFIR2' 'DD1' 'DD2' 'Spline1' 'Spline2' 'NL1' 'NL2'})
+legend(han2,{'IL1' 'sFIR1' 'DD1' 'Spline1' 'NL1'})
 title('Estimated HRF');
 
+subplot 122
+hold
+plot(xsecs, beta2*hrf2, 'k--', 'LineWidth', 2)
+
+xsecs1 = xsecs(1:length(h1));
+han2 = plot(xsecs1, h1(:,2),'r', 'LineWidth', 2);
+xsecs2 = xsecs(1:length(h2));
+han2(2) = plot(xsecs2, h2(:,2),'g', 'LineWidth', 2);
+xsecs3 = xsecs(1:length(h3));
+han2(3) = plot(xsecs3, h3(:,2),'m', 'LineWidth', 2);
+xsecs4 = xsecs(1:length(h4));
+han2(4) = plot(xsecs4, h4(:,2),'b', 'LineWidth', 2);
+xsecs5 = xsecs(1:length(h5));
+han2(5) = plot(xsecs5, h5(:,2),'y', 'LineWidth', 2);
+
+legend(han2,{'IL2' 'sFIR2' 'DD2' 'Spline2' 'NL2'})
+title('Estimated HRF');