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      Caption         =   "0.5"
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      Caption         =   "0.6"
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      Caption         =   "0.7"
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      TabIndex        =   3
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   End
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      Caption         =   "0.8"
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      TabIndex        =   2
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      Caption         =   "0.9"
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      Caption         =   "1"
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End
Attribute VB_Name = "main"
Attribute VB_GlobalNameSpace = False
Attribute VB_Creatable = False
Attribute VB_PredeclaredId = True
Attribute VB_Exposed = False
Option Explicit
Option Base 1

Const tempSize = 5
Const END_QUEUE = -10000


Dim cArr() As Double     '存放模糊等價(jià)矩陣
Dim copyCArr() As Double
Dim cBoolArr() As Double '聚類過程中的0-1矩陣
Dim dataArr() As Double

Dim cArrSize As Integer, dataArrRow As Integer, dataArrCol As Integer

'data val for cluster
Dim limitLine As Double, limitStep As Double, expectedLimit As Double
Dim comArr() As Double
Dim groupIndentifyArr() As Double, delegateQueue() As Double, preGroupIndentifyArr() As Double
Dim groupDelegateArr() As Double
Dim groupNum As Integer, delegateIndex As Integer
Dim totalClusterTime As Integer
Dim groupEleNum() As Integer, tmpSum As Integer, preI As Integer
Dim groupIdArr() As Integer
Dim innerIterCount As Integer
'Dim belongGroup() As Integer

'ulti datas for drawing cluster pics
Dim seqSet() As Integer, seqSet2() As Integer  'place the position in sequence of the elements
Dim seqArr() As Integer
Dim queueArr() As Integer
Dim queueIndex As Integer
Dim eachClusterNum() As Integer
Dim bucketArr() As Bucket
Dim tempBucketArr() As Bucket
Dim checkArr() As Boolean
Dim preEleNum() As Integer, curEleNum() As Integer
Dim preGroupNum As Integer

'ulti data for drawing the clustering pic
Dim setPointArr() As setPoint, setPointArr2() As setPoint
Dim x0 As Integer
Dim y0 As Integer
Dim stepX As Double
Dim stepY As Double
Dim descI As Integer
Dim Index As Integer


'other aided values
Dim tmpDotSum As Double, tmpLen As Double, tmpLen1 As Double, tmpLen2 As Double
    
Dim unchanged As Integer
Dim mergeVal As Double
    
Dim iterCount As Integer
Dim tempIndex As Integer
Dim tempVal As Double, tempInt As Integer
    

Private Sub cmdCluster_Click()
    Dim i As Integer, j As Integer, m As Integer, k As Integer, flag As Integer, count As Integer
    'Dim storeI As Integer
    Dim s As Double, sum As Double, avg As Double, minVal As Double, maxVal As Double
    
    pic.Cls
    reset_form
    'read in data size
    readInOriginalData dataTxt.Text   'dataArr,colArrNum,rowArrNum
    cArrSize = dataArrRow
    
    ReDim cArr(cArrSize, cArrSize)
    ReDim copyCArr(cArrSize, cArrSize)
    ReDim cBoolArr(cArrSize, cArrSize)
    
    'ReDim dataArr(dataArrRow, dataArrCol)
    
    '%--normalize the read in data--%
    For j = 1 To dataArrCol
        sum = 0
        minVal = dataArr(1, j)
        maxVal = dataArr(1, j)
        
        For i = 1 To dataArrRow
            sum = sum + dataArr(i, j)
            If minVal > dataArr(i, j) Then
                minVal = dataArr(i, j)
            ElseIf maxVal < dataArr(i, j) Then
                maxVal = dataArr(i, j)
            End If
        Next i
        avg = sum / dataArrRow
                
        s = 0
        For i = 1 To dataArrRow
           s = s + (dataArr(i, j) - avg) ^ 2
        Next i
        s = Sqr(s / dataArrRow)
        
        For i = 1 To dataArrRow
            dataArr(i, j) = (dataArr(i, j) - avg) / s
        Next i
        
        minVal = dataArr(1, j)
        maxVal = dataArr(1, j)
        
        For i = 1 To dataArrRow
            If minVal > dataArr(i, j) Then
                minVal = dataArr(i, j)
            ElseIf maxVal < dataArr(i, j) Then
                maxVal = dataArr(i, j)
            End If
        Next i
        
        For i = 1 To dataArrRow
            dataArr(i, j) = (dataArr(i, j) - minVal) / (maxVal - minVal)
        Next i
        
    Next j
    
    
    '%--cal dis between arr(i,j)--%
    '%-----using cos method-----%
    'cal with cos len method
    Select Case Combo1.ListIndex
        Case 0: 'cos dis
            cosDis dataArrRow, dataArrCol, dataArr, cArr
        Case 1: 'Euclid Dis
            EuclidDis dataArrRow, dataArrCol, dataArr, cArr
        Case 2: 'max-min dis
            MaxminDis dataArrRow, dataArrCol, dataArr, cArr
    End Select

    
    
'%--make the full c arr --%
For i = 1 To dataArrRow Step 1
    For j = 1 To i - 1 Step 1
        cArr(i, j) = cArr(j, i)
    Next j
    cArr(i, i) = 1
Next i

'%--washall enclosure algorithm--%
unchanged = 0
While unchanged = 0
    unchanged = 1
    '%--sigma:i=1:n(combine(conj(cArr(i,k),cArr(k,j))))
    For i = 1 To cArrSize Step 1
        For j = 1 To cArrSize Step 1
            mergeVal = 0
            For k = 1 To cArrSize Step 1
                If (cArr(i, k) <= cArr(k, j) And cArr(i, k) > mergeVal) Then
                        mergeVal = cArr(i, k)
                ElseIf (cArr(i, k) > cArr(k, j) And cArr(k, j) > mergeVal) Then
                        mergeVal = cArr(k, j)
                End If
            Next k
            
            If (mergeVal > cArr(i, j)) Then
                copyCArr(i, j) = mergeVal
                unchanged = 0
            Else
                copyCArr(i, j) = cArr(i, j)
            End If
        Next j
    Next i
    '%--copy back--%
    For i = 1 To cArrSize Step 1
        For j = 1 To cArrSize Step 1
            cArr(i, j) = copyCArr(i, j)
        Next j
    Next i
Wend


'%--cluster--%
'---init part---
limitLine = 1
limitStep = 0.01
expectedLimit = 0.1

ReDim comArr(cArrSize)
ReDim groupIndentifyArr(cArrSize)
ReDim groupDelegateArr(cArrSize)

groupNum = 1
preGroupNum = cArrSize
queueIndex = 1
iterCount = 0
totalClusterTime = 0
'---end of init part of cluster--

'prepare datas fro drawing the cluster pics
ReDim seqSet(cArrSize)
ReDim eachClusterNum(cArrSize)
ReDim queueArr(100 * (cArrSize + 1)) 'consider the worst condition
ReDim groupEleNum(100 * (cArrSize + 1))
ReDim seqArr(100 * cArrSize)
ReDim preGroupIndentifyArr(cArrSize)
ReDim groupIdArr(100 * cArrSize)
ReDim checkArr(cArrSize)


For i = 1 To cArrSize
    checkArr(i) = False
    preGroupIndentifyArr(i) = i
    groupEleNum(i) = 1
    seqArr(i) = i
    groupIdArr(i) = i
Next i
'---end of preparing the datas for drawing cluster pics

'---main part of clustering--
While (limitLine >= expectedLimit)
        iterCount = iterCount + 1
        totalClusterTime = totalClusterTime + 1
        
        For i = 1 To cArrSize Step 1
            For j = 1 To cArrSize Step 1
                If (cArr(i, j) < limitLine) Then
                    cBoolArr(i, j) = 0
                Else
                    cBoolArr(i, j) = 1
                End If
            Next j
        Next i

        '%--make the comparation arr--%
        For j = 1 To cArrSize Step 1
            tempVal = 0
            For i = 1 To cArrSize Step 1
                tempVal = tempVal + cBoolArr(i, j) * 2 ^ (i - 1)
            Next i
            comArr(j) = tempVal
        Next j
        
        '%--core part: pation the equivalence class--%
        'add these lines of code to elimate the previous iteration notes
        For i = 1 To cArrSize
            groupIndentifyArr(i) = -1
            groupDelegateArr(i) = -1
        Next i
        
        '%--initialize part--%
        groupIndentifyArr(1) = 1
        groupDelegateArr(1) = 1
        groupNum = 1
        
        '%--main part of the algorithm--%
        
        For i = 2 To cArrSize Step 1
            flag = 0
            For count = 1 To groupNum Step 1
                If (comArr(groupDelegateArr(count)) = comArr(i)) Then
                        groupIndentifyArr(i) = count
                        flag = 1
                        Exit For
                End If
            Next count
              
            If (flag = 0) Then
                groupNum = groupNum + 1
                groupDelegateArr(groupNum) = i
                groupIndentifyArr(i) = groupNum
            End If
        Next i
        
        ReDim eachClusterNum(groupNum)
        For i = 1 To groupNum Step 1
            eachClusterNum(i) = 0
        Next i
        
        'note the group id.
        For i = 1 To cArrSize