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/* hc.f -- translated by f2c (version 20020208).
You must link the resulting object file with the libraries:
-lf2c -lm (in that order)
*/
#include "f2c.h"
/* ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++C */
/* C */
/* HIERARCHICAL CLUSTERING using (user-specified) criterion. C */
/* C */
/* Parameters: C */
/* C */
/* DISS(LEN) dissimilarities in lower half diagonal C */
/* storage; LEN = N.N-1/2, C */
/* IOPT clustering criterion to be used, C */
/* IA, IB, CRIT history of agglomerations; dimensions C */
/* N, first N-1 locations only used, C */
/* MEMBR, NN, DISNN vectors of length N, used to store C */
/* cluster cardinalities, current nearest C */
/* neighbour, and the dissimilarity assoc. C */
/* with the latter. C */
/* FLAG boolean indicator of agglomerable obj./ C */
/* clusters. C */
/* C */
/* F. Murtagh, ESA/ESO/STECF, Garching, February 1986. C */
/* C */
/* ------------------------------------------------------------C */
/* Subroutine */ int hc_(n, len, iopt, ia, ib, crit, membr, nn, disnn, flag__,
diss)
integer *n, *len, *iopt, *ia, *ib;
doublereal *crit, *membr;
integer *nn;
doublereal *disnn;
logical *flag__;
doublereal *diss;
{
/* Initialized data */
static doublereal inf = 1e20;
/* System generated locals */
integer i__1, i__2;
doublereal d__1, d__2;
/* Local variables */
static doublereal dmin__;
static integer i__, j, k;
static doublereal x;
static integer i2, j2, jj, im, jm;
static doublereal xx;
static integer ind, ncl;
extern integer ioffset_();
static integer ind1, ind2, ind3;
/* Parameter adjustments */
--flag__;
--disnn;
--nn;
--membr;
--crit;
--ib;
--ia;
--diss;
/* Function Body */
/* Initializations */
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
membr[i__] = (float)1.;
flag__[i__] = TRUE_;
}
ncl = *n;
if (*iopt == 1) {
i__1 = *n * (*n - 1) / 2;
for (ind = 1; ind <= i__1; ++ind) {
diss[ind] /= (float)2.;
}
}
/* (Above is done for the case of the min. var. method */
/* where merging criteria are defined in terms of variances */
/* rather than distances.) */
/* Carry out an agglomeration - first create list of NNs */
i__1 = *n - 1;
for (i__ = 1; i__ <= i__1; ++i__) {
dmin__ = inf;
i__2 = *n;
for (j = i__ + 1; j <= i__2; ++j) {
ind = ioffset_(n, &i__, &j);
if (diss[ind] >= dmin__) {
goto L500;
}
dmin__ = diss[ind];
jm = j;
L500:
;
}
nn[i__] = jm;
disnn[i__] = dmin__;
}
L400:
/* Next, determine least diss. using list of NNs */
dmin__ = inf;
i__1 = *n - 1;
for (i__ = 1; i__ <= i__1; ++i__) {
if (! flag__[i__]) {
goto L600;
}
if (disnn[i__] >= dmin__) {
goto L600;
}
dmin__ = disnn[i__];
im = i__;
jm = nn[i__];
L600:
;
}
--ncl;
/* This allows an agglomeration to be carried out. */
i2 = min(im,jm);
j2 = max(im,jm);
ia[*n - ncl] = i2;
ib[*n - ncl] = j2;
crit[*n - ncl] = dmin__;
ind1 = ioffset_(n, &i2, &j2);
/* write(6,*) "agglom: ",i2,j2,dmin,diss(ind1) */
/* Update dissimilarities from new cluster. */
flag__[j2] = FALSE_;
dmin__ = inf;
i__1 = *n;
for (k = 1; k <= i__1; ++k) {
if (! flag__[k]) {
goto L800;
}
if (k == i2) {
goto L800;
}
x = membr[i2] + membr[j2] + membr[k];
if (i2 < k) {
ind1 = ioffset_(n, &i2, &k);
} else {
ind1 = ioffset_(n, &k, &i2);
}
if (j2 < k) {
ind2 = ioffset_(n, &j2, &k);
} else {
ind2 = ioffset_(n, &k, &j2);
}
ind3 = ioffset_(n, &i2, &j2);
xx = diss[ind3];
/* WARD'S MINIMUM VARIANCE METHOD - IOPT=1. */
if (*iopt == 1) {
diss[ind1] = (membr[i2] + membr[k]) * diss[ind1] + (membr[j2] +
membr[k]) * diss[ind2] - membr[k] * xx;
diss[ind1] /= x;
}
/* SINGLE LINK METHOD - IOPT=2. */
if (*iopt == 2) {
/* Computing MIN */
d__1 = diss[ind1], d__2 = diss[ind2];
diss[ind1] = min(d__1,d__2);
}
/* COMPLETE LINK METHOD - IOPT=3. */
if (*iopt == 3) {
/* Computing MAX */
d__1 = diss[ind1], d__2 = diss[ind2];
diss[ind1] = max(d__1,d__2);
}
/* AVERAGE LINK (OR GROUP AVERAGE) METHOD - IOPT=4. */
if (*iopt == 4) {
diss[ind1] = (membr[i2] * diss[ind1] + membr[j2] * diss[ind2]) / (
membr[i2] + membr[j2]);
}
/* MCQUITTY'S METHOD - IOPT=5. */
if (*iopt == 5) {
diss[ind1] = diss[ind1] * (float).5 + diss[ind2] * (float).5;
}
/* MEDIAN (GOWER'S) METHOD - IOPT=6. */
if (*iopt == 6) {
diss[ind1] = diss[ind1] * (float).5 + diss[ind2] * (float).5 - xx
* (float).25;
}
/* CENTROID METHOD - IOPT=7. */
if (*iopt == 7) {
diss[ind1] = (membr[i2] * diss[ind1] + membr[j2] * diss[ind2] -
membr[i2] * membr[j2] * xx / (membr[i2] + membr[j2])) / (
membr[i2] + membr[j2]);
}
if (i2 > k) {
goto L800;
}
if (diss[ind1] >= dmin__) {
goto L800;
}
dmin__ = diss[ind1];
jj = k;
L800:
;
}
membr[i2] += membr[j2];
disnn[i2] = dmin__;
nn[i2] = jj;
/* Update list of NNs insofar as this is required. */
i__1 = *n - 1;
for (i__ = 1; i__ <= i__1; ++i__) {
if (! flag__[i__]) {
goto L900;
}
if (nn[i__] == i2) {
goto L850;
}
if (nn[i__] == j2) {
goto L850;
}
goto L900;
L850:
/* (Redetermine NN of I:) */
dmin__ = inf;
i__2 = *n;
for (j = i__ + 1; j <= i__2; ++j) {
ind = ioffset_(n, &i__, &j);
if (! flag__[j]) {
goto L870;
}
if (i__ == j) {
goto L870;
}
if (diss[ind] >= dmin__) {
goto L870;
}
dmin__ = diss[ind];
jj = j;
L870:
;
}
nn[i__] = jj;
disnn[i__] = dmin__;
L900:
;
}
/* Repeat previous steps until N-1 agglomerations carried out. */
if (ncl > 1) {
goto L400;
}
return 0;
} /* hc_ */
integer ioffset_(n, i__, j)
integer *n, *i__, *j;
{
/* System generated locals */
integer ret_val;
/* Map row I and column J of upper half diagonal symmetric matrix */
/* onto vector. */
/*ret_val = *j + (*i__ - 1) * *n - *i__ * (*i__ + 1) / 2;*/
if(*j > *i__) ret_val = (*j-1)*(*j-2)/2+*i__;
else ret_val = (*i__-1)*(*i__-2)/2+*j;
return ret_val;
} /* ioffset_ */
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