Updates for Octave

exampleRunScripts/run_megapressproc_auto.m

@@ -50,8 +50,14 @@
 
 %Ensure that filestring is an absolute path, otherwise you can get yourself
 %in a tangle later inserting figures at the report stage.
-if ~java.io.File(filestring).isAbsolute
-    filestring = cd(cd(filestring));    
+if exist('OCTAVE_VERSION', 'builtin') ~= 0 %Option for Octave (doesn't have java library) - **PT**2025
+    if ~is_absolute_filename(filestring)
+        filestring = canonicalize_file_name(filestring);
+    end
+else
+    if ~java.io.File(filestring).isAbsolute
+        filestring = cd(cd(filestring));
+    end
 end
 
 %make a new directory for the output report and figures:

exampleRunScripts/run_megaspecialproc_auto.m

@@ -52,8 +52,14 @@
 
 %Ensure that filestring is an absolute path, otherwise you can get yourself
 %in a tangle later inserting figures at the report stage.
-if ~java.io.File(filestring).isAbsolute
-    filestring = cd(cd(filestring));    
+if exist('OCTAVE_VERSION', 'builtin') ~= 0 %Option for Octave (doesn't have java library) - **PT**2025
+    if ~is_absolute_filename(filestring)
+        filestring = canonicalize_file_name(filestring);
+    end
+else
+    if ~java.io.File(filestring).isAbsolute
+        filestring = cd(cd(filestring));
+    end
 end
 
 %make a new directory for the output report and figures:

exampleRunScripts/run_specialproc_auto.m

@@ -45,8 +45,14 @@
 
 %Ensure that filestring is an absolute path, otherwise you can get yourself
 %in a tangle later inserting figures at the report stage.
-if ~java.io.File(filestring).isAbsolute
-    filestring = cd(cd(filestring)); 
+if exist('OCTAVE_VERSION', 'builtin') ~= 0 %Option for Octave (doesn't have java library) - **PT**2025
+    if ~is_absolute_filename(filestring)
+        filestring = canonicalize_file_name(filestring);
+    end
+else
+    if ~java.io.File(filestring).isAbsolute
+        filestring = cd(cd(filestring));
+    end
 end
 
 %make a new directory for the output report and figures:

inputOutput/mapVBVD/read_twix_hdr.m

@@ -156,7 +156,7 @@
         breaked = false;
         for k=1:numel(v)
             if isOctave
-                vk = v{k};
+                vk = v(k); %Originally with {} brackets, but octave doesn't use this. Fixed in official map_VBVD - **PT**2025
                 if iscell(vk.name)
                     % lazy fix that throws some info away
                     vk.name = vk.name{1};

processingTools/distinguishable_colors/distinguishable_colors.m

@@ -90,9 +90,15 @@
     lab = func(rgb);
     bglab = func(bg);
   else
-    C = makecform('srgb2lab');
-    lab = applycform(rgb,C);
-    bglab = applycform(bg,C);
+      %Octave doesn't has makecform,applycform libraries - **PT**2025
+      if exist('OCTAVE_VERSION','builtin')~=0 % Running in Octave
+          lab = rgb2lab_oct(rgb);
+          bglab = rgb2lab_oct(bg);
+      else % Running in MATLAB
+          C = makecform('srgb2lab');
+          lab = applycform(rgb,C);
+          bglab = applycform(bg,C);
+      end
   end
 
   % If the user specified multiple background colors, compute distances
@@ -150,3 +156,59 @@
     end
   end
 end
+
+%Adding in function for Octave, as it doesn't support makecform&applycform - **PT**2025
+function lab = rgb2lab_oct(rgb)
+  % RGB2LAB_OCT: Convert sRGB values in [0,1] to CIELAB (Lab) color space.
+  % Input:  Nx3 matrix of RGB values, range [0,1]
+  % Output: Nx3 matrix of Lab values [L*, a*, b*]
+
+  % --- Step 1: Linearize sRGB (remove gamma correction) ---
+  % sRGB is gamma-compressed; we need to convert it to linear light values.
+  % Reference: IEC 61966-2-1 (sRGB standard)
+  mask = rgb <= 0.04045;
+  rgb(mask) = rgb(mask)/12.92;                  % linear for dark values
+  rgb(~mask) = ((rgb(~mask)+0.055)/1.055).^2.4; % power law for bright values
+  rgb = rgb * 100; % scale to [0,100] (matches XYZ reference scale)
+
+  % --- Step 2: sRGB → CIE XYZ ---
+  % This is a linear transformation using the sRGB-to-XYZ matrix
+  % under D65 illuminant (standard daylight white point).
+  % Numbers come from the official sRGB specification.
+  M = [0.4124564 0.3575761 0.1804375;  % X coefficients
+       0.2126729 0.7151522 0.0721750;  % Y coefficients
+       0.0193339 0.1191920 0.9503041]; % Z coefficients
+  XYZ = rgb * M';
+
+  % --- Step 3: Normalize by reference white (D65) ---
+  % CIELAB requires normalization relative to a "reference white".
+  % D65 white point in CIE XYZ is:
+  refX = 95.047;
+  refY = 100.000;
+  refZ = 108.883;
+  X = XYZ(:,1)/refX;
+  Y = XYZ(:,2)/refY;
+  Z = XYZ(:,3)/refZ;
+
+  % --- Step 4: XYZ → Lab nonlinear transform ---
+  % CIELAB uses a cube root transform, but with a linear fallback for very
+  % small values to avoid instability. Threshold = 0.008856.
+  f = @(t) (t > 0.008856) .* (t.^(1/3)) + ...
+           (t <= 0.008856) .* (7.787.*t + 16/116);
+
+  fX = f(X);
+  fY = f(Y);
+  fZ = f(Z);
+
+  % --- Step 5: Compute L*, a*, b* ---
+  % Standard CIELAB equations:
+  % L* = 116*f(Y) - 16      (0 = black, 100 = white)
+  % a* = 500*(f(X) - f(Y))  (green ↔ red axis)
+  % b* = 200*(f(Y) - f(Z))  (blue ↔ yellow axis)
+  L = 116*fY - 16;
+  a = 500*(fX - fY);
+  b = 200*(fY - fZ);
+
+  % --- Output ---
+  lab = [L a b];
+end

processingTools/op_alignMPSubspecs.m

@@ -92,15 +92,32 @@
 %DO FITTING
 n=1;
 %disp(['fitting subspec number ' num2str(m) ' and average number ' num2str(n)]);
-parsFit=nlinfit(in.fids(:,2),base,@op_freqPhaseShiftComplexNest,parsGuess,...
-                'weights', [ppmWeights ppmWeights]');
-A=op_freqPhaseShiftNest(parsFit,in.fids(:,2),phShift);
-size(A);
-size(fids);
-fids(:,1)=in.fids(:,1);
-fids(:,2)=A;
-fs=parsFit(1);
-phs=parsFit(2)+phShift;
+if exist('OCTAVE_VERSION', 'builtin') ~= 0 %If using Octave, nlinfit doesn't have 'weights' option - **PT**2025
+    % Combine weights for real + imaginary parts
+    combinedWeights = [ppmWeights ppmWeights]';  % column
+
+    % Scale y and create a model that returns scaled predictions
+    yWeighted = sqrt(combinedWeights) .* base;
+    weightedModel = @(pars, input) sqrt(combinedWeights) .* op_freqPhaseShiftComplexNest(pars, input);
+
+    % Fit using Octave's nlinfit
+    parsFit = nlinfit(in.fids(:,2), yWeighted, weightedModel, parsGuess);
+    A = op_freqPhaseShiftNest(parsFit, in.fids(:,2), phShift);
+    fids(:,1) = in.fids(:,1);
+    fids(:,2) = A;
+    fs = parsFit(1);
+    phs = parsFit(2) + phShift;
+else
+    parsFit=nlinfit(in.fids(:,2),base,@op_freqPhaseShiftComplexNest,parsGuess,...
+        'weights', [ppmWeights ppmWeights]');
+    A=op_freqPhaseShiftNest(parsFit,in.fids(:,2),phShift);
+    size(A);
+    size(fids);
+    fids(:,1)=in.fids(:,1);
+    fids(:,2)=A;
+    fs=parsFit(1);
+    phs=parsFit(2)+phShift;
+end
 %plot(in.ppm,fftshift(ifft(fids(:,1,m))),in.ppm,fftshift(ifft(fids(:,n,m))));
 
 %re-calculate Specs using fft

processingTools/op_lorentz.m

@@ -26,6 +26,11 @@
 
 function [y]=op_lorentz(pars,ppm)
 
+% For Octave, force pars to be a row vector - **PT**2025
+if exist('OCTAVE_VERSION','builtin')~=0
+    pars = pars(:).';
+end
+
 A=pars(:,1);     %Amplitude  (Use only positive Numbers)
 w=pars(:,2);     %full width at half max
 ppm0=pars(:,3);  %centre frequency of peak