1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223
|
C++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++C
C C
C HIERARCHICAL CLUSTERING using (user-specified) criterion. C
C C
C Parameters: C
C C
C DISS(LEN) dissimilarities in lower half diagonal C
C storage; LEN = N.N-1/2, C
C IOPT clustering criterion to be used, C
C IA, IB, CRIT history of agglomerations; dimensions C
C N, first N-1 locations only used, C
C MEMBR, NN, DISNN vectors of length N, used to store C
C cluster cardinalities, current nearest C
C neighbour, and the dissimilarity assoc. C
C with the latter. C
C FLAG boolean indicator of agglomerable obj./ C
C clusters. C
C C
C F. Murtagh, ESA/ESO/STECF, Garching, February 1986. C
C C
C------------------------------------------------------------C
SUBROUTINE HC(N,LEN,IOPT,IA,IB,CRIT,MEMBR,NN,DISNN,
X FLAG,DISS)
implicit none
integer n,m,len,iopt
REAL*8 MEMBR(N),DISS(LEN)
INTEGER IA(N),IB(N)
REAL*8 CRIT(N)
integer nn
real*8 disnn
DIMENSION NN(N),DISNN(N)
LOGICAL FLAG(N)
REAL*8 INF
integer i,j,ncl,ind,ioffset,jm,im,i2,j2,k
integer ind1,ind2,ind3,jj
real*8 dmin,x,xx
DATA INF/1.E+20/
C
C Initializations
C
DO I=1,N
MEMBR(I)=1.
FLAG(I)=.TRUE.
ENDDO
NCL=N
if (IOPT.EQ.1) then
do IND=1,n*(n-1)/2
DISS(IND)=DISS(IND)/2.
enddo
endif
C (Above is done for the case of the min. var. method
C where merging criteria are defined in terms of variances
C rather than distances.)
C
C Carry out an agglomeration - first create list of NNs
C
DO I=1,N-1
DMIN=INF
DO J=I+1,N
IND=IOFFSET(N,I,J)
IF (DISS(IND).GE.DMIN) GOTO 500
DMIN=DISS(IND)
JM=J
500 CONTINUE
ENDDO
NN(I)=JM
DISNN(I)=DMIN
ENDDO
C
400 CONTINUE
C Next, determine least diss. using list of NNs
DMIN=INF
DO I=1,N-1
IF (.NOT.FLAG(I)) GOTO 600
IF (DISNN(I).GE.DMIN) GOTO 600
DMIN=DISNN(I)
IM=I
JM=NN(I)
600 CONTINUE
ENDDO
NCL=NCL-1
C
C This allows an agglomeration to be carried out.
C
I2=MIN0(IM,JM)
J2=MAX0(IM,JM)
IA(N-NCL)=I2
IB(N-NCL)=J2
CRIT(N-NCL)=DMIN
ind1 = ioffset(n,i2,j2)
c write(6,*) "agglom: ",i2,j2,dmin,diss(ind1)
C
C Update dissimilarities from new cluster.
C
FLAG(J2)=.FALSE.
DMIN=INF
DO K=1,N
IF (.NOT.FLAG(K)) GOTO 800
IF (K.EQ.I2) GOTO 800
X=MEMBR(I2)+MEMBR(J2)+MEMBR(K)
IF (I2.LT.K) THEN
IND1=IOFFSET(N,I2,K)
ELSE
IND1=IOFFSET(N,K,I2)
ENDIF
IF (J2.LT.K) THEN
IND2=IOFFSET(N,J2,K)
ELSE
IND2=IOFFSET(N,K,J2)
ENDIF
IND3=IOFFSET(N,I2,J2)
XX=DISS(IND3)
C
C WARD'S MINIMUM VARIANCE METHOD - IOPT=1.
C
IF (IOPT.EQ.1) THEN
DISS(IND1)=(MEMBR(I2)+MEMBR(K))*DISS(IND1)+
X (MEMBR(J2)+MEMBR(K))*DISS(IND2)-
X MEMBR(K)*XX
DISS(IND1)=DISS(IND1)/X
ENDIF
C
C SINGLE LINK METHOD - IOPT=2.
C
IF (IOPT.EQ.2) THEN
DISS(IND1)=MIN(DISS(IND1),DISS(IND2))
ENDIF
C
C COMPLETE LINK METHOD - IOPT=3.
C
IF (IOPT.EQ.3) THEN
DISS(IND1)=MAX(DISS(IND1),DISS(IND2))
ENDIF
C
C AVERAGE LINK (OR GROUP AVERAGE) METHOD - IOPT=4.
C
IF (IOPT.EQ.4) THEN
DISS(IND1)=(MEMBR(I2)*DISS(IND1)+MEMBR(J2)*DISS(IND2))/
X (MEMBR(I2)+MEMBR(J2))
ENDIF
C
C MCQUITTY'S METHOD - IOPT=5.
C
IF (IOPT.EQ.5) THEN
DISS(IND1)=0.5*DISS(IND1)+0.5*DISS(IND2)
ENDIF
C
C MEDIAN (GOWER'S) METHOD - IOPT=6.
C
IF (IOPT.EQ.6) THEN
DISS(IND1)=0.5*DISS(IND1)+0.5*DISS(IND2)-0.25*XX
ENDIF
C
C CENTROID METHOD - IOPT=7.
C
IF (IOPT.EQ.7) THEN
DISS(IND1)=(MEMBR(I2)*DISS(IND1)+MEMBR(J2)*DISS(IND2)-
X MEMBR(I2)*MEMBR(J2)*XX/(MEMBR(I2)+MEMBR(J2)))/
X (MEMBR(I2)+MEMBR(J2))
ENDIF
C
IF (I2.GT.K) GOTO 800
IF (DISS(IND1).GE.DMIN) GOTO 800
DMIN=DISS(IND1)
JJ=K
800 CONTINUE
ENDDO
MEMBR(I2)=MEMBR(I2)+MEMBR(J2)
DISNN(I2)=DMIN
NN(I2)=JJ
C
C Update list of NNs insofar as this is required.
C
DO I=1,N-1
IF (.NOT.FLAG(I)) GOTO 900
IF (NN(I).EQ.I2) GOTO 850
IF (NN(I).EQ.J2) GOTO 850
GOTO 900
850 CONTINUE
C (Redetermine NN of I:)
DMIN=INF
DO J=I+1,N
IND=IOFFSET(N,I,J)
IF (.NOT.FLAG(J)) GOTO 870
IF (I.EQ.J) GOTO 870
IF (DISS(IND).GE.DMIN) GOTO 870
DMIN=DISS(IND)
JJ=J
870 CONTINUE
ENDDO
NN(I)=JJ
DISNN(I)=DMIN
900 CONTINUE
ENDDO
C
C Repeat previous steps until N-1 agglomerations carried out.
C
IF (NCL.GT.1) GOTO 400
C
C
RETURN
END
C
C
FUNCTION IOFFSET(N,I,J)
C Map row I and column J of upper half diagonal symmetric matrix
C onto vector.
c IOFFSET=J+(I-1)*N-(I*(I+1))/2
if ( j > i) then
ioffset= (j-1)*(j-2)/2+i
else
ioffset= (i-1)*(i-2)/2+j
endif
RETURN
END
|