Please help, these are my example outputs:

Example for gradle run $-$q $--$args$="\text{'}$input$\_$files$/$correctfiles$.$txt$\text{'}\text{'}3\text{'}\text{'}1\text{'}"$:

$0\mathrm{.}857143$ or $0\mathrm{.}714286$

$\text{'}3\text{'}\text{'}2\text{'}"$:

$0\mathrm{.}857143$ or $0\mathrm{.}714286$

$\text{'}4\text{'}\text{'}3\text{'}"$

$1\mathrm{.}000000$

$\text{'}3\text{'}\text{'}4\text{'}"$

$0\mathrm{.}857143$ or $0\mathrm{.}714286$

The outputs I get are:

$\text{'}3\text{'}\text{'}1\text{'}$

$0\mathrm{.}428571$

$\text{'}3\text{'}\text{'}2\text{'}"$:

$0\mathrm{.}428571$

$\text{'}4\text{'}\text{'}3\text{'}"$:

$1\mathrm{.}000000$

$\text{'}3\text{'}\text{'}4\text{'}"$:

Exception in thread "main" java.lang.IndexOutOfBoundsException: Index $4$ out of bounds for length $4$

I think theres an issue with my clustering logic, Please help, I have no idea how to get my output calculations correct.

Here is my code that handles the histogram clustering

public List performClustering$()\{$

if $($clusters$.$isEmpty$())\{$

throw new IllegalArgumentException$("$Error: No files to cluster."$)$;

$\}$

while $($clusters$.$size$()>$ K$)\{$

int$[]$ closestClusters $=$ findClosestClusters$()$;

mergeClusters$($closestClusters$[0],$ closestClusters$[1])$;

$\}$

return clusters;

$\}$

private int$[]$ findClosestClusters$()\{$

double minDistance $=$ Double.MAX$\_$VALUE;

int$[]$ closestIndices $=\{-1,-1\}$;

for $($int i $=0$; i $<$ clusters.size$()$; i$++)\{$

for $($int j $=$ i $+1$; j $<$ clusters.size$()$; j$++)\{$

double distance $=$ calculateDistance$($clusters$.$get$($i$),$ clusters.get$($j$))$;

if $($distance $<$ minDistance$)\{$

minDistance $=$ distance;

closestIndices$[0]=$ i;

closestIndices$[1]=$ j;

$\}$

$\}$

$\}$

return closestIndices;

$\}$

public double calculateDistance$($ImageCluster cluster$1,$ ImageCluster cluster$2)\{$

if $($similarityMeasure $==1)\{$

return normHistDistance$($cluster$1,$ cluster$2)$; $//$ Use NormHist

$\}$

else if $($similarityMeasure $==2)\{$

return normHist$4$Distance$($cluster$1,$ cluster$2)$; $//$ Use NormHist$4$

$\}$

else if $($similarityMeasure $==3)\{$

return invSquareDiffDistance$($cluster$1,$ cluster$2)$; $//$ Use InvSquareDiff

$\}$

else if $($similarityMeasure $==4)\{$

return normHist$9$Distance$($cluster$1,$ cluster$2)$;

$\}$

else $\{$

throw new IllegalArgumentException$("$Invalid similarity measure: $"+$ similarityMeasure $+".$ Must be $1,2,$ or $3.")$;

$\}$

$\}$

private double normHistDistance$($ImageCluster cluster$1,$ ImageCluster cluster$2)\{$

return cluster$1.$getHistogram$().$similarity$($cluster$2.$getHistogram$())$; $//$ Histogram similarity

$\}$

private double normHist$4$Distance$($ImageCluster cluster$1,$ ImageCluster cluster$2)\{$

$//$ Divide images into $4$ parts and compare histograms

List hists$1=$ cluster$1.$getHistograms$()$;

List hists$2=$ cluster$2.$getHistograms$()$;

double totalSimilarity $=0\mathrm{.}0$;

for $($int i $=0$; i $<4$; i$++)\{$

totalSimilarity $+=$ hists$1.$get$($i$).$similarity$($hists$2.$get$($i$))$;

$\}$

return totalSimilarity $/4$; $//$ Average similarity

$\}$

private double invSquareDiffDistance$($ImageCluster cluster$1,$ ImageCluster cluster$2)\{$

double$[][]$ pixels$1=$ cluster$1.$getPixelData$()$;

double$[][]$ pixels$2=$ cluster$2.$getPixelData$()$;

double sumSquaredDiff $=0\mathrm{.}0$;

for $($int x $=0$; x $<128$; x$++)\{$

for $($int y $=0$; y $<128$; y$++)\{$

double diff $=$ pixels$1[$x$][$y$]-$ pixels$2[$x$][$y$]$;

sumSquaredDiff $+=$ diff $*$ diff;

$\}$

$\}$

$//$ Check if both images are identical

if $($sumSquaredDiff $==0\mathrm{.}0)\{$

return $0\mathrm{.}0$; $//$ Return $0$ for identical images

$\}$

return Math.sqrt$($sumSquaredDiff$)$; $//$ Return the square root of the summed squared differences

$\}$

private double normHist$9$Distance$($ImageCluster cluster$1,$ ImageCluster cluster$2)\{$

List hists$1=$ cluster$1.$getHistograms$()$;

List hists$2=$ cluster$2.$getHistograms$()$;

double totalSimilarity $=0\mathrm{.}0$;

for $($int i $=0$; i $<9$; i$++)\{$

totalSimilarity $+=$ hists$1.$get$($i$).$similarity$($hists$2.$get$($i$))$;

$\}$

return totalSimilarity $/9$;

$\}$

public void mergeClusters$($int index$1,$ int index$2)\{$

ImageCluster cluster$1=$ clusters.get$($index$1)$;

ImageCluster cluster$2=$ clusters.get$($index$2)$;

$///$ Merge images and their histograms

for $($int i $=0$; i $<$ cluster$2.$getImageNames$().$size$()$; i$++)\{$

String imageName $=$ cluster$2.$getImageNames$().$get$($i$)$;

$//$ If there are histograms available, add them; otherwise, just add the image

$$if $($i $<$ cluster$2.$getHistograms$().$size$())\{$

$$ Histogram histogramToAdd $=$ cluster$2.$getHistograms$().$get$($i$)$;

$$ cluster$1.$addImage$($imageName$,$ histogramToAdd$)$;

$\}$

$\}$

$$ cluster$1.$recalculateHistogram$()$;

clusters.remove$($index$2)$;

$\}$