mclVector* mcxAttractivityScale
( const mclMatrix* M
)
{ dim n_cols = N_COLS(M)
;
dim d
;
mclVector* vec_values = mclvResize(NULL, n_cols)
;
for (d=0; d<n_cols; d++)
{ mclVector* vec = M->cols+d
;
double selfval = mclvIdxVal(vec, d, NULL)
;
double maxval = mclvMaxValue(vec)
;
if (maxval <= 0.0)
{ mcxErr
( "mcxAttractivityScale"
, "encountered nonpositive maximum value"
)
;
maxval = 1.0
;
}
(vec_values->ivps+d)->idx = d
;
(vec_values->ivps+d)->val = selfval / maxval
;
}
return vec_values
;
}
mclMatrix* mclDag
( const mclMatrix* A
, const mclInterpretParam* ipp
)
{ dim d
;
double w_selfval= ipp ? ipp->w_selfval: 0.999
;
double w_maxval = ipp ? ipp->w_maxval : 0.001
;
double delta = ipp ? ipp->delta : 0.01
;
mclMatrix* M = mclxAllocZero
( mclvCopy(NULL, A->dom_cols)
, mclvCopy(NULL, A->dom_rows)
)
;
for (d=0; d<N_COLS(A); d++) /* thorough clean-up */
{ mclVector* vec = A->cols+d
;
mclVector* dst = M->cols+d
;
double selfval = mclvIdxVal(vec, vec->vid, NULL)
;
double maxval = mclvMaxValue(vec)
;
double bar = selfval < maxval
? ( (w_selfval * selfval)
+ (w_maxval * maxval)
)
: delta
? selfval / (1 + delta)
: selfval
;
int n_bar = mclvCountGiven(vec, mclpGivenValGQ, &bar)
;
mclvCopyGiven(dst, vec, mclpGivenValGQ, &bar, n_bar)
;
}
if (0)
{ dim ne = mclxNrofEntries(M)
;
fprintf(stderr, "nroff entries %u\n", (unsigned) ne)
;
}
return M
;
}
static dim clm_clm_adjust
( mclx* mx
, mclx* cl
, dim cls_size_max
, mclx** cl_adjustedpp
, mclv** cid_affectedpp
, mclv** nid_affectedpp
)
{ dim i, j, n_adjusted = 0
; mclx* cl_adj = mclxCopy(cl)
; mclv* cid_affected = mclvClone(cl->dom_cols)
; mclv* nid_affected = mclvClone(mx->dom_cols)
; double bar_affected = 1.5
; const char* e1 = getenv("MCL_ADJ_FMAX")
; const char* e2 = getenv("MCL_ADJ_EMASS")
; double f1 = e1 ? atof(e1) : 2
; double f2 = e2 ? atof(e2) : 3
; mcxbool loggit = mcxLogGet( MCX_LOG_CELL | MCX_LOG_INFO )
; clmVScore sc
; mclx *el_to_cl = NULL
; mclx *el_on_cl = NULL
; mclx *cl_on_cl = NULL
; mclx *cl_on_el = NULL
; *cl_adjustedpp = NULL
; *cid_affectedpp = NULL
; *nid_affectedpp = NULL
; clmCastActors
(&mx, &cl, &el_to_cl, &el_on_cl, &cl_on_cl, &cl_on_el, 0.95)
; mclxFree(&cl_on_cl)
; mclxFree(&cl_on_el)
; mclvMakeConstant(cid_affected, 1.0)
; mclvMakeConstant(nid_affected, 1.0)
; for (i=0;i<N_COLS(cl_adj);i++)
cl_adj->cols[i].val = 0.5
/* Proceed with smallest clusters first.
* Caller has to take care of mclxColumnsRealign
*/
; for (i=0;i<N_COLS(cl);i++)
{ mclv* clself = cl->cols+i
/* Only consider nodes in clusters of
* size <= cls_size_max
*/
; if (cls_size_max && clself->n_ivps > cls_size_max)
break
/* Clusters that have been marked for inclusion
* cannot play.
*/
; if (cl_adj->cols[i].val > 1)
continue
; for (j=0;j<clself->n_ivps;j++)
{ long nid = clself->ivps[j].idx
; long nos = mclvGetIvpOffset(mx->dom_cols, nid, -1)
; mclv* clidvec = mclxGetVector(el_on_cl, nid, RETURN_ON_FAIL, NULL)
; double eff_alien_bsf = 0.0, eff_alien_max_bsf = 0.0 /* best so far*/
; double eff_self = 0.0, eff_self_max = 0.0
; long cid_alien = -1, cid_self = -1
; clmVScore sc_self = { 0 }, sc_alien = { 0 }
; dim f
; if (nos < 0 || !clidvec)
{ mcxErr
("clmDumpNodeScores panic", "node <%ld> does not belong", nid)
; continue
; }
clmVScanDomain(mx->cols+nos, clself, &sc)
; clmVScoreCoverage(&sc, &eff_self, &eff_self_max)
; cid_self = clself->vid
; sc_self = sc
; if (loggit)
mcxLog2
( us
, "node %ld in cluster %ld eff %.3f,%.3f sum %.3f"
, nid
, cid_self
, eff_self
, eff_self_max
, sc.sum_i
)
; for (f=0;f<clidvec->n_ivps;f++)
{ long cid = clidvec->ivps[f].idx
; mclv* clvec = mclxGetVector(cl, cid, RETURN_ON_FAIL, NULL)
/* ^ overdoing: cid == clvec->vid */
; double eff, eff_max
; if (!clvec)
{ mcxErr
( "clmAdjust panic"
, "cluster <%ld> node <%ld> mishap"
, cid
, nid
)
; continue
; }
/* fixme: document or remove first condition
*
*/
if ((0 && clvec->n_ivps <= clself->n_ivps) || clvec->vid == cid_self)
continue
; clmVScanDomain(mx->cols+nos, clvec, &sc)
; clmVScoreCoverage(&sc, &eff, &eff_max)
#if 0
# define PIVOT eff > eff_alien_bsf
#else
# define PIVOT eff_max > eff_alien_max_bsf
#endif
; if
( PIVOT
|| sc.sum_i >= 0.5
)
eff_alien_bsf = eff
, eff_alien_max_bsf = eff_max
, cid_alien = clvec->vid
, sc_alien = sc
; if (sc.sum_i >= 0.5)
break
; }
if (loggit)
mcxLog2
( us
, " -> best alien %ld eff %.3f,%.3f sum %.3f"
, cid_alien
, eff_alien_bsf
, eff_alien_max_bsf
, sc_alien.sum_i
)
/* below: use sum_i as mass fraction
* (clmAdjust framework uses stochastic * matrix)
*/
; if
( cid_alien >= 0
&& cid_self >= 0
&& f1 * sc_alien.max_i >= sc_self.max_i
&& ( ( eff_alien_bsf > eff_self
&& sc_alien.sum_i > sc_self.sum_i
)
|| ( pow(sc_alien.sum_i, f2) >= sc_self.sum_i
&& pow(eff_self, f2) <= eff_alien_bsf
)
)
/* So, if max is reasonable
* and efficiency is better and mass is better
* or if mass is ridiculously better -> move
* Somewhat intricate and contrived, yes.
*/
)
{ mclv* acceptor
= mclxGetVector(cl_adj, cid_alien, RETURN_ON_FAIL, NULL)
; mclv* donor
= mclxGetVector(cl_adj, cid_self, RETURN_ON_FAIL, NULL)
; if (!donor || !acceptor || acceptor == donor)
continue
; mclvInsertIdx(donor, nid, 0.0)
; mclvInsertIdx(acceptor, nid, 1.0)
; acceptor->val = 1.5
; if (mcxLogGet(MCX_LOG_LIST))
{ mclv* nb = mx->cols+nos
; double mxv = mclvMaxValue(nb)
; double avg = nb->n_ivps ? mclvSum(nb) / nb->n_ivps : -1.0
; mcxLog
( MCX_LOG_LIST
, us
, "mov %ld (%ld %.2f %.2f)"
" %ld (cv=%.2f cm=%.2f s=%.2f m=%.2f #=%lu)"
" to %ld (cv=%.2f cm=%.2f s=%.2f m=%.2f #=%lu)"
, nid
, (long) nb->n_ivps, mxv, avg
, cid_self
, eff_self, eff_self_max, sc_self.sum_i, sc_self.max_i
, (ulong) (sc_self.n_meet + sc_self.n_ddif)
, cid_alien
, eff_alien_bsf, eff_alien_max_bsf, sc_alien.sum_i, sc_alien.max_i
, (ulong) (sc_alien.n_meet + sc_alien.n_ddif)
)
; }
n_adjusted++
; mclvInsertIdx(cid_affected, cid_alien, 2.0)
; mclvInsertIdx(cid_affected, cid_self, 2.0)
; mclvInsertIdx(nid_affected, nid, 2.0)
; }
}
}
mclxFree(&el_on_cl)
; mclxFree(&el_to_cl)
; for (i=0;i<N_COLS(cl_adj);i++)
cl_adj->cols[i].val = 0.0
; mclxMakeCharacteristic(cl)
; if (!n_adjusted)
{ mclxFree(&cl_adj)
; mclvFree(&cid_affected)
; mclvFree(&nid_affected)
; return 0
; }
mclxUnary(cl_adj, fltxCopy, NULL)
; mclxMakeCharacteristic(cl_adj)
/* FIRST REMOVE ENTRIES set to zero (sssst now .. */
/* ...) and THEN make it characteristic again */
; mclvUnary(cid_affected, fltxGT, &bar_affected)
; mclvUnary(nid_affected, fltxGT, &bar_affected)
; *cl_adjustedpp = cl_adj
; *cid_affectedpp = cid_affected
; *nid_affectedpp = nid_affected
; return n_adjusted
; }
