static void RenderStrip( GLUtesselator *tess, GLUhalfEdge *e, long size )
{
/* Render as many CCW triangles as possible in a strip starting from
* edge "e". The strip *should* contain exactly "size" triangles
* (otherwise we've goofed up somewhere).
*/
CALL_BEGIN_OR_BEGIN_DATA( GL_TRIANGLE_STRIP );
CALL_VERTEX_OR_VERTEX_DATA( e->Org->data );
CALL_VERTEX_OR_VERTEX_DATA( e->Dst->data );
while( ! Marked( e->Lface )) {
e->Lface->marked = TRUE;
--size;
e = e->Dprev;
CALL_VERTEX_OR_VERTEX_DATA( e->Org->data );
if( Marked( e->Lface )) break;
e->Lface->marked = TRUE;
--size;
e = e->Onext;
CALL_VERTEX_OR_VERTEX_DATA( e->Dst->data );
}
assert( size == 0 );
CALL_END_OR_END_DATA();
}
static struct FaceCount MaximumFan(GLUhalfEdge* eOrig)
{
/* eOrig->Lface is the face we want to render. We want to find the size
* of a maximal fan around eOrig->Org. To do this we just walk around
* the origin vertex as far as possible in both directions.
*/
struct FaceCount newFace={0, NULL, &RenderFan};
GLUface* trail=NULL;
GLUhalfEdge* e;
for (e=eOrig; !Marked(e->Lface); e=e->Onext)
{
AddToTrail(e->Lface, trail);
++newFace.size;
}
for (e=eOrig; !Marked(e->Rface); e=e->Oprev)
{
AddToTrail( e->Rface, trail);
++newFace.size;
}
newFace.eStart=e;
/*LINTED*/
FreeTrail(trail);
return newFace;
}
void scContUnit::scAssertValid( Bool recurse ) const
{
scTBObj::scAssertValid();
scAssert( !Marked( scRETABULATE ) );
scAssert( !Marked( scREBREAK ) );
if ( fFirstline ) {
fFirstline->scAssertValid( false );
scAssert( fFirstline->GetStartOffset() == 0 );
scAssert( fFirstline->GetEndOffset() <= fCharArray.GetContentSize() );
}
}
static struct FaceCount MaximumStrip( GLUhalfEdge *eOrig )
{
/* Here we are looking for a maximal strip that contains the vertices
* eOrig->Org, eOrig->Dst, eOrig->Lnext->Dst (in that order or the
* reverse, such that all triangles are oriented CCW).
*
* Again we walk forward and backward as far as possible. However for
* strips there is a twist: to get CCW orientations, there must be
* an *even* number of triangles in the strip on one side of eOrig.
* We walk the strip starting on a side with an even number of triangles;
* if both side have an odd number, we are forced to shorten one side.
*/
struct FaceCount newFace = { 0, NULL, &RenderStrip };
long headSize = 0, tailSize = 0;
GLUface *trail = NULL;
GLUhalfEdge *e, *eTail, *eHead;
for( e = eOrig; ! Marked( e->Lface ); ++tailSize, e = e->Onext ) {
AddToTrail( e->Lface, trail );
++tailSize;
e = e->Dprev;
if( Marked( e->Lface )) break;
AddToTrail( e->Lface, trail );
}
eTail = e;
for( e = eOrig; ! Marked( e->Rface ); ++headSize, e = e->Dnext ) {
AddToTrail( e->Rface, trail );
++headSize;
e = e->Oprev;
if( Marked( e->Rface )) break;
AddToTrail( e->Rface, trail );
}
eHead = e;
newFace.size = tailSize + headSize;
if( IsEven( tailSize )) {
newFace.eStart = eTail->Sym;
} else if( IsEven( headSize )) {
newFace.eStart = eHead;
} else {
/* Both sides have odd length, we must shorten one of them. In fact,
* we must start from eHead to guarantee inclusion of eOrig->Lface.
*/
--newFace.size;
newFace.eStart = eHead->Onext;
}
/*LINTED*/
FreeTrail( trail );
return newFace;
}
void scContUnit::RestorePointers( scSet* enumTable )
{
if ( !Marked( scPTRRESTORED ) ) {
scTBObj::RestorePointers( enumTable );
fSpecRun.RestorePointers( );
}
}
/* ==================================================================== */
BOOL scTextline::IsLastLinePara ( ) const
{
BOOL tf;
if ( Marked( scINVALID | scREPAINT ) )
return true;
scAssertValid( false );
tf = Marked( scLASTLINE );
if ( tf ) {
if ( !fPara->Marked( scREBREAK ) )
scAssert( GetEndOffset() == PARAChSize( fPara ) );
}
return tf;
}
void scTBObj::RestorePointers( scSet* enumTable )
{
if ( !Marked( scPTRRESTORED ) ) {
fNext = (scTBObj*)enumTable->Get( (long)fNext );
fPrev = (scTBObj*)enumTable->Get( (long)fPrev );
Mark( scPTRRESTORED );
}
}
/* draw the line */
void scTextline::Draw( APPDrwCtx appMat,
const scFlowDir& flowDir,
const scMuPoint& transpt )
{
if ( !fPara->Marked( scREBREAK | scRETABULATE ) ) {
if ( GetCharCount() || Marked( scLASTLINE ) ) {
scDrawLine ld( *this, flowDir, appMat, transpt );
ld.Draw();
}
Unmark( scREPAINT );
}
}
/* ==================================================================== */
void scTextline::scAssertValid( BOOL recurse ) const
{
scTBObj::scAssertValid();
scAssert( !Marked( scINVALID ) );
scAssert( fMaxLeadSpec != 0 );
if ( recurse ) {
fColumn->scAssertValid( false );
fPara->scAssertValid( false );
}
else {
scAssert( fColumn != 0 );
scAssert( fPara != 0 );
}
scAssert( fStartOffset >= 0 && fEndOffset <= fPara->GetContentSize() );
}
static count SamplesLookup(Samples *samples, int key,
ccount nwant, ccount nmax, count nmin)
{
count n;
if( key == 13 && ndim_ == 2 ) {
if( rule13_.first == NULL ) Rule13Alloc(&rule13_);
samples->rule = &rule13_;
samples->n = n = nmin = rule13_.n;
samples->sampler = SampleRule;
}
else if( key == 11 && ndim_ == 3 ) {
if( rule11_.first == NULL ) Rule11Alloc(&rule11_);
samples->rule = &rule11_;
samples->n = n = nmin = rule11_.n;
samples->sampler = SampleRule;
}
else if( key == 9 ) {
if( rule9_.first == NULL ) Rule9Alloc(&rule9_);
samples->rule = &rule9_;
samples->n = n = nmin = rule9_.n;
samples->sampler = SampleRule;
}
else if( key == 7 ) {
if( rule7_.first == NULL ) Rule7Alloc(&rule7_);
samples->rule = &rule7_;
samples->n = n = nmin = rule7_.n;
samples->sampler = SampleRule;
}
else {
n = Abs1(key);
if( n < 40 ) n *= nwant;
samples->sampler = (key < 0) ? SampleSobol :
(n = n/2 + 1, SampleKorobov);
samples->n = IMin(n, nmax);
}
samples->neff = samples->n;
return IDim(n - nmax) | Marked(nmax - nmin);
}
static count SamplesLookup(This *t, Samples *samples, cint key,
cnumber nwant, cnumber nmax, number nmin)
{
number n;
if( key == 13 && t->ndim == 2 ) {
samples->rule = &t->rule13;
samples->n = n = nmin = t->rule13.n;
samples->sampler = SampleRule;
}
else if( key == 11 && t->ndim == 3 ) {
samples->rule = &t->rule11;
samples->n = n = nmin = t->rule11.n;
samples->sampler = SampleRule;
}
else if( key == 9 ) {
samples->rule = &t->rule9;
samples->n = n = nmin = t->rule9.n;
samples->sampler = SampleRule;
}
else if( key == 7 ) {
samples->rule = &t->rule7;
samples->n = n = nmin = t->rule7.n;
samples->sampler = SampleRule;
}
else {
n = Abs1(key);
if( n < 40 ) n *= nwant;
samples->sampler = (key < 0) ? SampleSobol :
(n = n/2 + 1, SampleKorobov);
samples->n = IMin(n, nmax);
}
samples->neff = samples->n;
return IDim(n - nmax) | Marked(nmax - nmin);
}
static int Integrate(This *t, real *integral, real *error, real *prob)
{
TYPEDEFREGION;
Totals totals[NCOMP];
real nneed, weight;
count dim, comp, iter, pass = 0, err, iregion;
number nwant, nmin = INT_MAX;
int fail;
if( VERBOSE > 1 ) {
char s[512];
sprintf(s, "Divonne input parameters:\n"
" ndim " COUNT "\n ncomp " COUNT "\n"
" epsrel " REAL "\n epsabs " REAL "\n"
" flags %d\n seed %d\n"
" mineval " NUMBER "\n maxeval " NUMBER "\n"
" key1 %d\n key2 %d\n key3 %d\n maxpass " COUNT "\n"
" border " REAL "\n maxchisq " REAL "\n mindeviation " REAL "\n"
" ngiven " NUMBER "\n nextra " NUMBER,
t->ndim, t->ncomp,
t->epsrel, t->epsabs,
t->flags, t->seed,
t->mineval, t->maxeval,
t->key1, t->key2, t->key3, t->maxpass,
t->border.lower, t->maxchisq, t->mindeviation,
t->ngiven, t->nextra);
Print(s);
}
if( BadComponent(t) ) return -2;
if( BadDimension(t, t->key1) ||
BadDimension(t, t->key2) ||
((t->key3 & -2) && BadDimension(t, t->key3)) ) return -1;
t->neval_opt = t->neval_cut = 0;
t->size = CHUNKSIZE;
MemAlloc(t->voidregion, t->size*sizeof(Region));
for( dim = 0; dim < t->ndim; ++dim ) {
Bounds *b = &RegionPtr(0)->bounds[dim];
b->lower = 0;
b->upper = 1;
}
RuleIni(&t->rule7);
RuleIni(&t->rule9);
RuleIni(&t->rule11);
RuleIni(&t->rule13);
SamplesIni(&t->samples[0]);
SamplesIni(&t->samples[1]);
SamplesIni(&t->samples[2]);
if( (fail = setjmp(t->abort)) ) goto abort;
t->epsabs = Max(t->epsabs, NOTZERO);
/* Step 1: partition the integration region */
if( VERBOSE ) Print("Partitioning phase:");
if( IsSobol(t->key1) || IsSobol(t->key2) || IsSobol(t->key3) )
IniRandom(t);
SamplesLookup(t, &t->samples[0], t->key1,
(number)47, (number)INT_MAX, (number)0);
SamplesAlloc(t, &t->samples[0]);
t->totals = totals;
Zap(totals);
t->phase = 1;
Explore(t, 0, &t->samples[0], INIDEPTH, 1);
for( iter = 1; ; ++iter ) {
Totals *maxtot;
count valid;
for( comp = 0; comp < t->ncomp; ++comp ) {
Totals *tot = &totals[comp];
tot->avg = tot->spreadsq = 0;
tot->spread = tot->secondspread = -INFTY;
}
for( iregion = 0; iregion < t->nregions; ++iregion ) {
Region *region = RegionPtr(iregion);
for( comp = 0; comp < t->ncomp; ++comp ) {
cResult *r = ®ion->result[comp];
Totals *tot = &totals[comp];
tot->avg += r->avg;
tot->spreadsq += Sq(r->spread);
if( r->spread > tot->spread ) {
tot->secondspread = tot->spread;
tot->spread = r->spread;
tot->iregion = iregion;
}
else if( r->spread > tot->secondspread )
tot->secondspread = r->spread;
}
}
maxtot = totals;
valid = 0;
for( comp = 0; comp < t->ncomp; ++comp ) {
Totals *tot = &totals[comp];
integral[comp] = tot->avg;
valid += tot->avg == tot->avg;
if( tot->spreadsq > maxtot->spreadsq ) maxtot = tot;
tot->spread = sqrt(tot->spreadsq);
error[comp] = tot->spread*t->samples[0].weight;
}
if( VERBOSE ) {
char s[128 + 64*NCOMP], *p = s;
p += sprintf(p, "\n"
"Iteration " COUNT " (pass " COUNT "): " COUNT " regions\n"
NUMBER7 " integrand evaluations so far,\n"
NUMBER7 " in optimizing regions,\n"
NUMBER7 " in finding cuts",
iter, pass, t->nregions, t->neval, t->neval_opt, t->neval_cut);
for( comp = 0; comp < t->ncomp; ++comp )
p += sprintf(p, "\n[" COUNT "] "
REAL " +- " REAL,
comp + 1, integral[comp], error[comp]);
Print(s);
}
if( valid == 0 ) goto abort; /* all NaNs */
if( t->neval > t->maxeval ) break;
nneed = maxtot->spread/MaxErr(maxtot->avg);
if( nneed < MAXPRIME ) {
cnumber n = t->neval + t->nregions*(number)ceil(nneed);
if( n < nmin ) {
nmin = n;
pass = 0;
}
else if( ++pass > t->maxpass && n >= t->mineval ) break;
}
Split(t, maxtot->iregion, DEPTH);
}
/* Step 2: do a "full" integration on each region */
/* nneed = t->samples[0].neff + 1; */
nneed = 2*t->samples[0].neff;
for( comp = 0; comp < t->ncomp; ++comp ) {
Totals *tot = &totals[comp];
creal maxerr = MaxErr(tot->avg);
tot->nneed = tot->spread/maxerr;
nneed = Max(nneed, tot->nneed);
tot->maxerrsq = Sq(maxerr);
tot->mindevsq = tot->maxerrsq*Sq(t->mindeviation);
}
nwant = (number)Min(ceil(nneed), MARKMASK/40.);
err = SamplesLookup(t, &t->samples[1], t->key2, nwant,
(t->maxeval - t->neval)/t->nregions + 1, t->samples[0].n + 1);
/* the number of points needed to reach the desired accuracy */
fail = Unmark(err)*t->nregions;
if( Marked(err) ) {
if( VERBOSE ) Print("\nNot enough samples left for main integration.");
for( comp = 0; comp < t->ncomp; ++comp )
prob[comp] = -999;
weight = t->samples[0].weight;
}
else {
bool can_adjust = (t->key3 == 1 && t->samples[1].sampler != SampleRule &&
(t->key2 < 0 || t->samples[1].neff < MAXPRIME));
count df, nlimit;
SamplesAlloc(t, &t->samples[1]);
if( VERBOSE ) {
char s[128];
sprintf(s, "\nMain integration on " COUNT
" regions with " NUMBER " samples per region.",
t->nregions, t->samples[1].neff);
Print(s);
}
ResClear(integral);
ResClear(error);
ResClear(prob);
nlimit = t->maxeval - t->nregions*t->samples[1].n;
df = 0;
for( iregion = 0; iregion < t->nregions; ++iregion ) {
Region *region = RegionPtr(iregion);
char s[64*NDIM + 256*NCOMP], *p = s;
int todo;
refine:
t->phase = 2;
t->samples[1].sampler(t, &t->samples[1], region->bounds, region->vol);
if( can_adjust )
for( comp = 0; comp < t->ncomp; ++comp )
totals[comp].spreadsq -= Sq(region->result[comp].spread);
nlimit += t->samples[1].n;
todo = 0;
for( comp = 0; comp < t->ncomp; ++comp ) {
cResult *r = ®ion->result[comp];
Totals *tot = &totals[comp];
t->samples[0].avg[comp] = r->avg;
t->samples[0].err[comp] = r->err;
if( t->neval < nlimit ) {
creal avg2 = t->samples[1].avg[comp];
creal err2 = t->samples[1].err[comp];
creal diffsq = Sq(avg2 - r->avg);
#define Var(s) Sq((s.err[comp] == 0) ? r->spread*s.weight : s.err[comp])
if( err2*tot->nneed > r->spread ||
diffsq > Max(t->maxchisq*(Var(t->samples[0]) + Var(t->samples[1])),
EPS*Sq(avg2)) ) {
if( t->key3 && diffsq > tot->mindevsq ) {
if( t->key3 == 1 ) {
ccount xregion = t->nregions;
if( VERBOSE > 2 ) Print("\nSplit");
t->phase = 1;
Explore(t, iregion, &t->samples[1], POSTDEPTH, 2);
if( can_adjust ) {
number nnew;
count ireg, xreg;
for( ireg = iregion, xreg = xregion;
ireg < t->nregions; ireg = xreg++ ) {
cResult *result = RegionPtr(ireg)->result;
count c;
for( c = 0; c < t->ncomp; ++c )
totals[c].spreadsq += Sq(result[c].spread);
}
nnew = (tot->spreadsq/Sq(MARKMASK) > tot->maxerrsq) ?
MARKMASK :
(number)ceil(sqrt(tot->spreadsq/tot->maxerrsq));
if( nnew > nwant + nwant/64 ) {
ccount err = SamplesLookup(t, &t->samples[1], t->key2, nnew,
(t->maxeval - t->neval)/t->nregions + 1, t->samples[1].n);
fail += Unmark(err)*t->nregions;
nwant = nnew;
SamplesFree(&t->samples[1]);
SamplesAlloc(t, &t->samples[1]);
if( t->key2 > 0 && t->samples[1].neff >= MAXPRIME )
can_adjust = false;
if( VERBOSE > 2 ) {
char s[128];
sprintf(s, "Sampling remaining " COUNT
" regions with " NUMBER " points per region.",
t->nregions, t->samples[1].neff);
Print(s);
}
}
}
goto refine;
}
todo |= 3;
}
todo |= 1;
}
}
}
if( can_adjust ) {
for( comp = 0; comp < t->ncomp; ++comp )
totals[comp].maxerrsq -=
Sq(region->result[comp].spread*t->samples[1].weight);
}
switch( todo ) {
case 1: /* get spread right */
Explore(t, iregion, &t->samples[1], 0, 2);
break;
case 3: /* sample region again with more points */
if( SamplesIniQ(&t->samples[2]) ) {
SamplesLookup(t, &t->samples[2], t->key3,
nwant, (number)INT_MAX, (number)0);
SamplesAlloc(t, &t->samples[2]);
}
t->phase = 3;
t->samples[2].sampler(t, &t->samples[2], region->bounds, region->vol);
Explore(t, iregion, &t->samples[2], 0, 2);
++region->depth; /* misused for df here */
++df;
}
++region->depth; /* misused for df here */
if( VERBOSE > 2 ) {
for( dim = 0; dim < t->ndim; ++dim ) {
cBounds *b = ®ion->bounds[dim];
p += sprintf(p,
(dim == 0) ? "\nRegion (" REALF ") - (" REALF ")" :
"\n (" REALF ") - (" REALF ")",
b->lower, b->upper);
}
}
for( comp = 0; comp < t->ncomp; ++comp ) {
Result *r = ®ion->result[comp];
creal x1 = t->samples[0].avg[comp];
creal s1 = Var(t->samples[0]);
creal x2 = t->samples[1].avg[comp];
creal s2 = Var(t->samples[1]);
creal r2 = (s1 == 0) ? Sq(t->samples[1].neff*t->samples[0].weight) : s2/s1;
real norm = 1 + r2;
real avg = x2 + r2*x1;
real sigsq = s2;
real chisq = Sq(x2 - x1);
real chiden = s1 + s2;
if( todo == 3 ) {
creal x3 = t->samples[2].avg[comp];
creal s3 = Var(t->samples[2]);
creal r3 = (s2 == 0) ? Sq(t->samples[2].neff*t->samples[1].weight) : s3/s2;
norm = 1 + r3*norm;
avg = x3 + r3*avg;
sigsq = s3;
chisq = s1*Sq(x3 - x2) + s2*Sq(x3 - x1) + s3*chisq;
chiden = s1*s2 + s3*chiden;
}
avg = LAST ? r->avg : (sigsq *= norm = 1/norm, avg*norm);
if( chisq > EPS ) chisq /= Max(chiden, NOTZERO);
#define Out(s) s.avg[comp], r->spread*s.weight, s.err[comp]
if( VERBOSE > 2 ) {
p += sprintf(p, "\n[" COUNT "] "
REAL " +- " REAL "(" REAL ")\n "
REAL " +- " REAL "(" REAL ")",
comp + 1, Out(t->samples[0]), Out(t->samples[1]));
if( todo == 3 ) p += sprintf(p, "\n "
REAL " +- " REAL "(" REAL ")",
Out(t->samples[2]));
p += sprintf(p, " \tchisq " REAL, chisq);
}
integral[comp] += avg;
error[comp] += sigsq;
prob[comp] += chisq;
r->avg = avg;
r->spread = sqrt(sigsq);
r->chisq = chisq;
}
if( VERBOSE > 2 ) Print(s);
}
for( comp = 0; comp < t->ncomp; ++comp )
error[comp] = sqrt(error[comp]);
df += t->nregions;
if( VERBOSE > 2 ) {
char s[16 + 128*NCOMP], *p = s;
p += sprintf(p, "\nTotals:");
for( comp = 0; comp < t->ncomp; ++comp )
p += sprintf(p, "\n[" COUNT "] "
REAL " +- " REAL " \tchisq " REAL " (" COUNT " df)",
comp + 1, integral[comp], error[comp], prob[comp], df);
Print(s);
}
for( comp = 0; comp < t->ncomp; ++comp )
prob[comp] = ChiSquare(prob[comp], df);
weight = 1;
}
#ifdef MLVERSION
if( REGIONS ) {
MLPutFunction(stdlink, "List", 2);
MLPutFunction(stdlink, "List", t->nregions);
for( iregion = 0; iregion < t->nregions; ++iregion ) {
Region *region = RegionPtr(iregion);
cBounds *b = region->bounds;
real lower[NDIM], upper[NDIM];
for( dim = 0; dim < t->ndim; ++dim ) {
lower[dim] = b[dim].lower;
upper[dim] = b[dim].upper;
}
MLPutFunction(stdlink, "Cuba`Divonne`region", 4);
MLPutRealList(stdlink, lower, t->ndim);
MLPutRealList(stdlink, upper, t->ndim);
MLPutFunction(stdlink, "List", t->ncomp);
for( comp = 0; comp < t->ncomp; ++comp ) {
cResult *r = ®ion->result[comp];
real res[] = {r->avg, r->spread*weight, r->chisq};
MLPutRealList(stdlink, res, Elements(res));
}
MLPutInteger(stdlink, region->depth); /* misused for df */
}
}
#endif
abort:
SamplesFree(&t->samples[2]);
SamplesFree(&t->samples[1]);
SamplesFree(&t->samples[0]);
RuleFree(&t->rule13);
RuleFree(&t->rule11);
RuleFree(&t->rule9);
RuleFree(&t->rule7);
free(t->voidregion);
return fail;
}
/* reposition the line, this line is part of a flex column and it may
* need repositioning depending on the line rag
* returns the next line - thus optimizing loop in column a little
*/
void scTextline::Reposition( MicroPoint measure )
{
MicroPoint displacement;
CharRecordP chP;
scFlowDir flowDir;
scMuPoint transPt( fOrigin );
flowDir = fColumn->GetFlowdir( );
if ( flowDir.IsHorizontal() ) {
transPt.x = -transPt.x;
transPt.y = 0;
}
else {
transPt.x = 0;
transPt.y = -transPt.y;
}
switch ( GetFlexLineAdjustment() & eRagFlag ) {
case eRagLeft:
fOrigin.Translate( transPt );
fInkExtents.Translate( transPt );
displacement = measure - fLength;
if ( flowDir.IsHorizontal() ) {
fOrigin.Translate( displacement, 0 );
fInkExtents.Translate( displacement, 0 );
}
else {
fOrigin.Translate( 0, displacement );
fInkExtents.Translate( 0, displacement );
}
break;
case eRagCentered:
fOrigin.Translate( transPt );
fInkExtents.Translate( transPt );
displacement = ( measure - fLength ) / 2;
if ( flowDir.IsHorizontal() ) {
fOrigin.Translate( displacement, 0 );
fInkExtents.Translate( displacement, 0 );
}
else {
fOrigin.Translate( 0, displacement );
fInkExtents.Translate( 0, displacement );
}
break;
case eRagJustified:
if ( !Marked( scLASTLINE ) || GetFlexLineAdjustment() & eLastLineJust ) {
chP = (CharRecordP)GetPara()->GetCharArray().Lock();
if ( BRKJustify( chP, GetStartOffset(), GetEndOffset(), measure ) )
Mark( scREPAINT );
if ( flowDir.IsHorizontal() )
fInkExtents.x2 = fInkExtents.x1 + measure + fInkExtents.Depth() / 2;
else
fInkExtents.y2 = fInkExtents.y1 + measure + fInkExtents.Width() / 2;
fLength = measure;
GetPara()->GetCharArray().Unlock();
}
break;
case eRagRight:
break;
}
}
// update the lines instance variables, determining if there have
// been any changes in the line
void scTextline::Set( short lineCount,
eBreakType breakType,
scLINERefData& lineData )
{
BOOL changed;
scXRect exrect = lineData.fInkExtents;
scAssert( lineData.fInkExtents.Valid() );
TypeSpec ts = lineData.GetMaxLeadSpec();
scCachedStyle& cs = scCachedStyle::GetCachedStyle( ts );
if ( fOrigin == lineData.fOrg
&& fLength == lineData.fComputedLen
&& GetCharCount() == lineData.GetCharCount()
&& fLineCount == lineCount
&& fLspAdjustment == lineData.fLetterSpace
&& fInkExtents == lineData.fInkExtents
&& Marked( scLASTLINE ) && ( breakType == eEndStreamBreak )
&& fMaxLead == lineData.fEndLead.GetLead()
&& fMaxLeadSpec == lineData.GetMaxLeadSpec() ) {
changed = false;
}
else
changed = true;
if ( !changed ) {
if ( fColumn->GetFlowdir().IsVertical() ) {
changed = ( fCursorY1 == lineData.fOrg.x + cs.GetCursorX1() ) &&
( fCursorY2 == lineData.fOrg.x + cs.GetCursorX2() );
}
else {
changed = ( fCursorY1 == lineData.fOrg.y + cs.GetCursorY1() ) &&
( fCursorY2 == lineData.fOrg.y + cs.GetCursorY2() );
}
}
SetOffsets( lineData.GetStartCharOffset(), lineData.GetEndCharOffset() );
if ( changed ) {
fOrigin = lineData.fOrg;
fVJOffset = 0;
fLength = lineData.fComputedLen;
fLineCount = lineCount;
if ( breakType == eEndStreamBreak )
Mark( scLASTLINE );
else
Unmark( scLASTLINE );
fLspAdjustment = lineData.fLetterSpace;
fInkExtents = lineData.fInkExtents;
fMaxLead = lineData.fEndLead.GetLead();
fMaxLeadSpec = lineData.GetMaxLeadSpec(); // fMaxLeadSpec
if ( fColumn->GetFlowdir().IsVertical() ) {
fCursorY1 = lineData.fOrg.x + cs.GetCursorX1();
fCursorY2 = lineData.fOrg.x + cs.GetCursorX2();
lineData.fInkExtents.x1 = fCursorY1;
lineData.fInkExtents.x2 = fCursorY2;
if ( !lineData.GetStartCharOffset() && scCachedStyle::GetParaStyle().GetNumbered() )
lineData.fInkExtents.y1 -= scCachedStyle::GetParaStyle().GetBulletIndent();
}
else {
fCursorY1 = lineData.fOrg.y + cs.GetCursorY1();
fCursorY2 = lineData.fOrg.y + cs.GetCursorY2();
lineData.fInkExtents.y1 = fCursorY1;
lineData.fInkExtents.y2 = fCursorY2;
if ( !lineData.GetStartCharOffset() && scCachedStyle::GetParaStyle().GetNumbered() )
lineData.fInkExtents.x1 -= scCachedStyle::GetParaStyle().GetBulletIndent();
}
fInkExtents.Union( lineData.fInkExtents );
}
if ( fColumn->GetFlowdir().IsVertical() && lineData.fColShapeType & eVertFlex )
SetFlexLineAdjustment( lineData.fRagSetting );
else if ( lineData.fColShapeType & eHorzFlex )
SetFlexLineAdjustment( lineData.fRagSetting );
else
SetFlexLineAdjustment( eNoRag );
lineData.fLastLineLen = lineData.fComputedLen;
if ( changed )
fColumn->Mark( scREPAINT );
scAssertValid( false );
}
/* ==================================================================== */
BOOL scTextline::Compare( scTextline* orgTxl,
const scStreamChangeInfo& streamChange )
{
#if 1
if ( fPara != orgTxl->GetPara() )
return false;
if ( fOrigin != orgTxl->fOrigin )
return false;
if ( !TestOffsets( orgTxl, streamChange ) )
return false;
if ( fVJOffset != orgTxl->fVJOffset )
return false;
if ( fMaxLeadSpec != orgTxl->fMaxLeadSpec )
return false;
if ( fLength != orgTxl->fLength )
return false;
if ( fLineCount != orgTxl->fLineCount )
return false;
if ( fInkExtents != orgTxl->fInkExtents )
return false;
if ( Marked( scLASTLINE ) != orgTxl->Marked( scLASTLINE ) )
return false;
if ( fCursorY1 != orgTxl->fCursorY1 )
return false;
if ( fCursorY2 != orgTxl->fCursorY2 )
return false;
if ( fColumn != orgTxl->fColumn )
return false;
if ( fLspAdjustment != orgTxl->fLspAdjustment )
return false;
return true;
#else
BOOL notChanged;
if ( GetPara() == orgTxl->GetPara() &&
fOrigin == orgTxl->fOrigin &&
TestOffsets( orgTxl, p, offset, len ) &&
fVJOffset == orgTxl->fVJOffset &&
fMaxLeadSpec == orgTxl->fMaxLeadSpec &&
fLength == orgTxl->fLength &&
fLineCount == orgTxl->fLineCount &&
fInkExtents == orgTxl->fInkExtents &&
Marked( scLASTLINE ) == orgTxl->Marked( scLASTLINE ) &&
fCursorY1 == orgTxl->fCursorY1 &&
fCursorY2 == orgTxl->fCursorY2 &&
fColumn == orgTxl->fColumn &&
fLspAdjustment == orgTxl->fLspAdjustment )
notChanged = true;
else
notChanged = false;
return notChanged;
#endif
}
static int Integrate(creal epsrel, creal epsabs,
cint flags, cnumber mineval, cnumber maxeval,
int key1, int key2, int key3, ccount maxpass,
creal maxchisq, creal mindeviation,
real *integral, real *error, real *prob)
{
TYPEDEFREGION;
Region anchor, *region;
Totals totals[NCOMP];
real nneed, weight;
count dim, comp, iter, nregions, pass = 0, err;
number nwant, nmin = INT_MAX;
int fail = -1;
if( VERBOSE > 1 ) {
char s[512];
sprintf(s, "Divonne input parameters:\n"
" ndim " COUNT "\n ncomp " COUNT "\n"
" epsrel " REAL "\n epsabs " REAL "\n"
" flags %d\n mineval " NUMBER "\n maxeval " NUMBER "\n"
" key1 %d\n key2 %d\n key3 %d\n maxpass " COUNT "\n"
" border " REAL "\n maxchisq " REAL "\n mindeviation " REAL "\n"
" ngiven " NUMBER "\n nextra " NUMBER "\n",
ndim_, ncomp_,
epsrel, epsabs,
flags, mineval, maxeval,
key1, key2, key3, maxpass,
border_.lower, maxchisq, mindeviation,
ngiven_, nextra_);
Print(s);
}
anchor.next = NULL;
for( dim = 0; dim < ndim_; ++dim ) {
Bounds *b = &anchor.bounds[dim];
b->lower = 0;
b->upper = 1;
}
RuleIni(&rule7_);
RuleIni(&rule9_);
RuleIni(&rule11_);
RuleIni(&rule13_);
SamplesIni(&samples_[0]);
SamplesIni(&samples_[1]);
SamplesIni(&samples_[2]);
#ifdef MLVERSION
if( setjmp(abort_) ) goto abort;
#endif
/* Step 1: partition the integration region */
if( VERBOSE ) Print("Partitioning phase:");
if( IsSobol(key1) || IsSobol(key2) || IsSobol(key3) )
IniRandom(2*maxeval, flags);
SamplesLookup(&samples_[0], key1,
(number)47, (number)INT_MAX, (number)0);
SamplesAlloc(&samples_[0]);
totals_ = totals;
Zap(totals);
phase_ = 1;
Explore(&anchor, &samples_[0], INIDEPTH, 1);
for( iter = 1; ; ++iter ) {
Totals *maxtot;
for( comp = 0; comp < ncomp_; ++comp ) {
Totals *tot = &totals[comp];
tot->avg = tot->spreadsq = 0;
tot->spread = tot->secondspread = -INFTY;
}
nregions = 0;
for( region = anchor.next; region; region = region->next ) {
++nregions;
for( comp = 0; comp < ncomp_; ++comp ) {
cResult *r = ®ion->result[comp];
Totals *tot = &totals[comp];
tot->avg += r->avg;
tot->spreadsq += Sq(r->spread);
if( r->spread > tot->spread ) {
tot->secondspread = tot->spread;
tot->spread = r->spread;
tot->region = region;
}
else if( r->spread > tot->secondspread )
tot->secondspread = r->spread;
}
}
maxtot = totals;
for( comp = 0; comp < ncomp_; ++comp ) {
Totals *tot = &totals[comp];
integral[comp] = tot->avg;
if( tot->spreadsq > maxtot->spreadsq ) maxtot = tot;
tot->spread = sqrt(tot->spreadsq);
error[comp] = tot->spread*samples_[0].weight;
}
if( VERBOSE ) {
char s[128 + 64*NCOMP], *p = s;
p += sprintf(p, "\n"
"Iteration " COUNT " (pass " COUNT "): " COUNT " regions\n"
NUMBER7 " integrand evaluations so far,\n"
NUMBER7 " in optimizing regions,\n"
NUMBER7 " in finding cuts",
iter, pass, nregions, neval_, neval_opt_, neval_cut_);
for( comp = 0; comp < ncomp_; ++comp )
p += sprintf(p, "\n[" COUNT "] "
REAL " +- " REAL,
comp + 1, integral[comp], error[comp]);
Print(s);
}
if( neval_ > maxeval ) break;
nneed = maxtot->spread/MaxErr(maxtot->avg);
if( nneed < MAXPRIME ) {
cnumber n = neval_ + nregions*(number)ceil(nneed);
if( n < nmin ) {
nmin = n;
pass = 0;
}
else if( ++pass > maxpass && n >= mineval ) break;
}
Split(maxtot->region, DEPTH);
}
/* Step 2: do a "full" integration on each region */
/* nneed = samples_[0].neff + 1; */
nneed = 2*samples_[0].neff;
for( comp = 0; comp < ncomp_; ++comp ) {
Totals *tot = &totals[comp];
creal maxerr = MaxErr(tot->avg);
tot->nneed = tot->spread/maxerr;
nneed = Max(nneed, tot->nneed);
tot->maxerrsq = Sq(maxerr);
tot->mindevsq = tot->maxerrsq*Sq(mindeviation);
}
nwant = (number)Min(ceil(nneed), MARKMASK/40.);
err = SamplesLookup(&samples_[1], key2, nwant,
(maxeval - neval_)/nregions + 1, samples_[0].n + 1);
/* the number of points needed to reach the desired accuracy */
fail = Unmark(err)*nregions;
if( Marked(err) ) {
if( VERBOSE ) Print("\nNot enough samples left for main integration.");
for( comp = 0; comp < ncomp_; ++comp )
prob[comp] = -999;
weight = samples_[0].weight;
nregions_ = nregions;
}
else {
bool can_adjust = (key3 == 1 && samples_[1].sampler != SampleRule &&
(key2 < 0 || samples_[1].neff < MAXPRIME));
count df, nlimit;
SamplesAlloc(&samples_[1]);
if( VERBOSE ) {
char s[128];
sprintf(s, "\nMain integration on " COUNT
" regions with " NUMBER " samples per region.",
nregions, samples_[1].neff);
Print(s);
}
ResClear(integral);
ResClear(error);
ResClear(prob);
nlimit = maxeval - nregions*samples_[1].n;
df = nregions_ = 0;
for( region = anchor.next; region; region = region->next ) {
char s[64*NDIM + 256*NCOMP], *p = s;
int todo;
refine:
phase_ = 2;
samples_[1].sampler(&samples_[1], region->bounds, region->vol);
if( can_adjust ) {
--nregions;
for( comp = 0; comp < ncomp_; ++comp )
totals[comp].spreadsq -= Sq(region->result[comp].spread);
}
nlimit += samples_[1].n;
todo = 0;
for( comp = 0; comp < ncomp_; ++comp ) {
cResult *r = ®ion->result[comp];
Totals *tot = &totals[comp];
samples_[0].avg[comp] = r->avg;
samples_[0].err[comp] = r->err;
if( neval_ < nlimit ) {
creal avg2 = samples_[1].avg[comp];
creal err2 = samples_[1].err[comp];
creal diffsq = Sq(avg2 - r->avg);
#define Var(s) Sq((s.err[comp] == 0) ? r->spread*s.weight : s.err[comp])
if( err2*tot->nneed > r->spread ||
diffsq > Max(maxchisq*(Var(samples_[0]) + Var(samples_[1])),
EPS*Sq(avg2)) ) {
if( key3 && diffsq > tot->mindevsq ) {
if( key3 == 1 ) {
const Region *next = region->next;
if( VERBOSE > 2 ) Print("\nSplit");
phase_ = 1;
Explore(region, &samples_[1], POSTDEPTH, 2);
if( can_adjust ) {
number nnew;
Region *child;
for( child = region; child != next; child = child->next ) {
count c;
for( c = 0; c < ncomp_; ++c )
totals[c].spreadsq += Sq(child->result[c].spread);
++nregions;
}
nnew = (tot->spreadsq/Sq(MARKMASK) > tot->maxerrsq) ?
MARKMASK :
(number)ceil(sqrt(tot->spreadsq/tot->maxerrsq));
if( nnew > nwant + nwant/64 ) {
ccount err = SamplesLookup(&samples_[1], key2, nnew,
(maxeval - neval_)/nregions + 1, samples_[1].n);
fail += Unmark(err)*nregions;
nwant = nnew;
SamplesFree(&samples_[1]);
SamplesAlloc(&samples_[1]);
if( key2 > 0 && samples_[1].neff >= MAXPRIME )
can_adjust = false;
if( VERBOSE > 2 ) {
char s[128];
sprintf(s, "Sampling remaining " COUNT
" regions with " NUMBER " points per region.",
nregions, samples_[1].neff);
Print(s);
}
}
}
goto refine;
}
todo |= 3;
}
todo |= 1;
}
}
}
if( can_adjust ) {
for( comp = 0; comp < ncomp_; ++comp )
totals[comp].maxerrsq -=
Sq(region->result[comp].spread*samples_[1].weight);
}
switch( todo ) {
case 1: /* get spread right */
Explore(region, &samples_[1], 0, 2);
break;
case 3: /* sample region again with more points */
if( MEM(&samples_[2]) == NULL ) {
SamplesLookup(&samples_[2], key3,
nwant, (number)INT_MAX, (number)0);
SamplesAlloc(&samples_[2]);
}
phase_ = 3;
samples_[2].sampler(&samples_[2], region->bounds, region->vol);
Explore(region, &samples_[2], 0, 2);
++region->depth; /* misused for df here */
++df;
}
++region->depth; /* misused for df here */
++nregions_;
if( VERBOSE > 2 ) {
for( dim = 0; dim < ndim_; ++dim ) {
cBounds *b = ®ion->bounds[dim];
p += sprintf(p,
(dim == 0) ? "\nRegion (" REALF ") - (" REALF ")" :
"\n (" REALF ") - (" REALF ")",
b->lower, b->upper);
}
}
for( comp = 0; comp < ncomp_; ++comp ) {
Result *r = ®ion->result[comp];
creal x1 = samples_[0].avg[comp];
creal s1 = Var(samples_[0]);
creal x2 = samples_[1].avg[comp];
creal s2 = Var(samples_[1]);
creal r2 = (s1 == 0) ? Sq(samples_[1].neff*samples_[0].weight) : s2/s1;
real norm = 1 + r2;
real avg = x2 + r2*x1;
real sigsq = s2;
real chisq = Sq(x2 - x1);
real chiden = s1 + s2;
if( todo == 3 ) {
creal x3 = samples_[2].avg[comp];
creal s3 = Var(samples_[2]);
creal r3 = (s2 == 0) ? Sq(samples_[2].neff*samples_[1].weight) : s3/s2;
norm = 1 + r3*norm;
avg = x3 + r3*avg;
sigsq = s3;
chisq = s1*Sq(x3 - x2) + s2*Sq(x3 - x1) + s3*chisq;
chiden = s1*s2 + s3*chiden;
}
avg = LAST ? r->avg : (sigsq *= norm = 1/norm, avg*norm);
if( chisq > EPS ) chisq /= Max(chiden, NOTZERO);
#define Out(s) s.avg[comp], r->spread*s.weight, s.err[comp]
if( VERBOSE > 2 ) {
p += sprintf(p, "\n[" COUNT "] "
REAL " +- " REAL "(" REAL ")\n "
REAL " +- " REAL "(" REAL ")",
comp + 1, Out(samples_[0]), Out(samples_[1]));
if( todo == 3 ) p += sprintf(p, "\n "
REAL " +- " REAL "(" REAL ")",
Out(samples_[2]));
p += sprintf(p, " \tchisq " REAL, chisq);
}
integral[comp] += avg;
error[comp] += sigsq;
prob[comp] += chisq;
r->avg = avg;
r->spread = sqrt(sigsq);
r->chisq = chisq;
}
if( VERBOSE > 2 ) Print(s);
}
for( comp = 0; comp < ncomp_; ++comp )
error[comp] = sqrt(error[comp]);
df += nregions_;
if( VERBOSE > 2 ) {
char s[16 + 128*NCOMP], *p = s;
p += sprintf(p, "\nTotals:");
for( comp = 0; comp < ncomp_; ++comp )
p += sprintf(p, "\n[" COUNT "] "
REAL " +- " REAL " \tchisq " REAL " (" COUNT " df)",
comp + 1, integral[comp], error[comp], prob[comp], df);
Print(s);
}
for( comp = 0; comp < ncomp_; ++comp )
prob[comp] = ChiSquare(prob[comp], df);
weight = 1;
}
#ifdef MLVERSION
if( REGIONS ) {
MLPutFunction(stdlink, "List", 2);
MLPutFunction(stdlink, "List", nregions_);
for( region = anchor.next; region; region = region->next ) {
cBounds *b = region->bounds;
real lower[NDIM], upper[NDIM];
for( dim = 0; dim < ndim_; ++dim ) {
lower[dim] = b[dim].lower;
upper[dim] = b[dim].upper;
}
MLPutFunction(stdlink, "Cuba`Divonne`region", 4);
MLPutRealList(stdlink, lower, ndim_);
MLPutRealList(stdlink, upper, ndim_);
MLPutFunction(stdlink, "List", ncomp_);
for( comp = 0; comp < ncomp_; ++comp ) {
cResult *r = ®ion->result[comp];
real res[] = {r->avg, r->spread*weight, r->chisq};
MLPutRealList(stdlink, res, Elements(res));
}
MLPutInteger(stdlink, region->depth); /* misused for df */
}
}
#endif
#ifdef MLVERSION
abort:
#endif
SamplesFree(&samples_[2]);
SamplesFree(&samples_[1]);
SamplesFree(&samples_[0]);
RuleFree(&rule13_);
RuleFree(&rule11_);
RuleFree(&rule9_);
RuleFree(&rule7_);
for( region = anchor.next; region; ) {
Region *next = region->next;
free(region);
region = next;
}
return fail;
}
