Critical fixes

spike_sorting.m

@@ -14,11 +14,10 @@
 datasetMedians(8) = 0;
 datasetFactors(8) = 0;
 
-thresholdFactorInitValue = 3; % k starting value
+thresholdFactorInitValue = 1; % k starting value
-thresholdFactorEndValue = 12; % k ending value
+thresholdFactorEndValue = 7; % k ending value
 thresholdFactorStep = 0.01; % k jumping step
 numberOfFactors = length(thresholdFactorInitValue:thresholdFactorStep:thresholdFactorEndValue);
-numberOfSpikesPerFactor(numberOfFactors) = 0;
 
 for fileIndex=1:8
     fprintf('Loading test dataset no. %d\n', fileIndex);
@@ -38,6 +37,7 @@ for fileIndex=1:8
     %% Q.1.2
     dataMedian = median(abs(data)/0.6745);
     datasetMedians(fileIndex) = dataMedian;
+    numberOfSpikesPerFactor(numberOfFactors) = 0;
     
     for factorIteration=1:numberOfFactors % runs for each k
         % builds threshold
@@ -84,6 +84,7 @@ for fileIndex=1:8
     
     clear Dataset
     clear data
+    clear numberOfSpikesPerFactor
 end
 fprintf('\n');
 
@@ -95,7 +96,7 @@ xlabel('Dataset median');
 ylabel('Threshold factor');
 hold on;
 
-empiricalRule = polyfit(datasetMedians, datasetFactors, 8);
+empiricalRule = polyfit(datasetMedians, datasetFactors, 1);
 visualizationX = linspace(0, 0.5, 50);
 visualizationY = polyval(empiricalRule, visualizationX);
 plot(visualizationX, visualizationY);
@@ -118,8 +119,8 @@ for fileIndex=1:4
     %% Q.2.1 and Q.2.2
     dataMedian = median(abs(data)/0.6745);
     
-    %factorEstimation = polyval(empiricalRule, dataMedian);
+    factorEstimation = polyval(empiricalRule, dataMedian);
-    factorEstimation = 4;
+    %factorEstimation = 4;
     threshold = factorEstimation * dataMedian;
     numberOfSpikes = 0;
     spikesTimesEst(2500) = 0;
@@ -144,7 +145,9 @@ for fileIndex=1:4
             % spike found
             numberOfSpikes = numberOfSpikes + 1;
             spikeStartIndex = sample;
-            
+            % Q.2.1
+            spikesTimesEst(numberOfSpikes) = spikeStartIndex;
+                    
             % skips cheking until values are below threshold again
             while sample <= length(data)
                 sample = sample + 1;
@@ -163,8 +166,6 @@ for fileIndex=1:4
                     % occurs first
                     firstIndex = min([absoluteMaxIndex absoluteMinIndex]);
                     
-                    % Q.2.1
-                    spikesTimesEst(numberOfSpikes) = firstIndex;
                     % Q.2.2
                     spikesEst(numberOfSpikes, :) = data(firstIndex-34:firstIndex+29);
                     break;