Interface/python

IO_stf.m

@@ -0,0 +1,23 @@
+function status = IO_stf(path)
+
+stf_init = load(strcat(path,'stf_with_separate_rays.mat'), 'stf');
+ray_init = load(strcat(path,'stf_with_separate_rays.mat'), 'rays');
+
+%%
+stf = [stf_init.stf{:}];
+ray = cell(size(ray_init.rays, 2), 1);
+
+for i=1:size(ray_init.rays, 2)
+    ray{i} = [ray_init.rays{i}{:}];
+end
+
+for i=1:size(ray_init.rays, 2)
+    stf(i).ray = ray{i};
+end
+
+%%
+save(strcat(path,'stf.mat'), 'stf')
+
+status = 'STF written';
+
+end

examples/matRad_example2_photons.m

@@ -146,7 +146,7 @@
 % Let's generate dosimetric information by pre-computing dose influence 
 % matrices for unit beamlet intensities. Having dose influences available 
 % allows subsequent inverse optimization.
-dij = matRad_calcPhotonDose(ct,stf,pln,cst);
+dij = matRad_calcPhotonDoseMC(ct,stf,pln,cst,1000);
 
 %% Inverse Optimization for IMRT
 % The goal of the fluence optimization is to find a set of beamlet/pencil 
@@ -155,7 +155,7 @@
 % treatment. Once the optimization has finished, trigger once the GUI to 
 % visualize the optimized dose cubes.
 resultGUI = matRad_fluenceOptimization(dij,cst,pln);
-matRadGUI;
+%matRadGUI;
 
 %% Plot the Resulting Dose Slice
 % Let's plot the transversal iso-center dose slice

matRad_callFromPython.m

@@ -1,10 +1,14 @@
-function matRad_callFromPython(functionName, outputName, varargin)
+function matRad_callFromPython(functionName, outputName, inputPath, outputPath, varargin)
 %matRad_callFromPython Function that uses temporary mat file to call any function from within python
 
 for i=1:length(varargin)
-    load(varargin{i});
-    var=varargin{i}(1:end-4);
-    functionVars{i}=var;
+    if contains(string(varargin{i}), string('.mat'))
+        load(strcat(inputPath, varargin{i}));
+        [path, var, ext]=fileparts(varargin{i});
+        functionVars{i}=var;
+    else
+        functionVars{i} = num2str(varargin{i});
+    end
 end
 
 execFunc = sprintf('%s = %s(%s);', outputName, functionName, strjoin(functionVars,','));
@@ -14,6 +18,6 @@ function matRad_callFromPython(functionName, outputName, varargin)
 %end
 
 eval(execFunc);
-save(strcat(outputName,'.mat'), outputName);
+save(strcat(outputPath, outputName,'.mat'), outputName);
 
 end

matRad_generateStf.m

@@ -53,6 +53,8 @@
     end
 end
 
+disp(length(V));
+
 % Remove double voxels
 V = unique(V);
 % generate voi cube for targets
@@ -115,6 +117,10 @@
 % Define steering file like struct. Prellocating for speed.
 stf = struct;
 
+save('coordsX_vox', 'coordsX_vox');
+save('coordsY_vox', 'coordsY_vox');
+save('coordsZ_vox', 'coordsZ_vox');
+
 % loop over all angles
 for i = 1:length(pln.propStf.gantryAngles)
 
@@ -123,6 +129,8 @@
     coordsX = coordsX_vox*ct.resolution.x - pln.propStf.isoCenter(i,1);
     coordsY = coordsY_vox*ct.resolution.y - pln.propStf.isoCenter(i,2);
     coordsZ = coordsZ_vox*ct.resolution.z - pln.propStf.isoCenter(i,3);
+
+    save('coordsX', 'coordsX');
 
     % Save meta information for treatment plan
     stf(i).gantryAngle   = pln.propStf.gantryAngles(i);
@@ -182,7 +190,7 @@
 
          rayPos = [x,y,z];
      end
-
+     
     % remove double rays
     rayPos = unique(rayPos,'rows');
 

matRad_saveStructs.m

@@ -1,4 +1,4 @@
-function status = matRad_saveStructs(path)
+function status = matRad_saveStructs(load_path, save_path, engine)
 % matRad_saveStructs Mat file transfer for python interface
 %
 % input
@@ -18,10 +18,17 @@
 %
 % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
-load(path);
+load(load_path);
 
-save('ct.mat', 'ct');
-save('cst.mat', 'cst');
+if engine=='matlab'
+    save(append(save_path, 'ct.mat'), 'ct');
+    save(append(save_path, 'cst.mat'), 'cst');
+else
+    save(append(save_path, 'ct.mat'), '-mat7-binary', 'ct');
+    save(append(save_path, 'ct.mat'), '-mat7-binary', 'cst');
+end
+
+%Choosing the engine is necessary because Octave has trouble reading .mat files. Doesn't recognize them as binary.
 
 status = 'Files written';