UInt_t GetListOfJobs( TFile* file, TList& jobdirs)
{
// get a list of all jobs in all method directories
// based on ideas by Peter and Joerg found in macro deviations.C
TIter next(file->GetListOfKeys());
TKey *key(0);
while ((key = (TKey*)next())) {
if (TString(key->GetName()).BeginsWith("Method_")) {
if (gROOT->GetClass(key->GetClassName())->InheritsFrom("TDirectory")) {
TDirectory* mDir = (TDirectory*)key->ReadObj();
TIter keyIt(mDir->GetListOfKeys());
TKey *jobkey;
while ((jobkey = (TKey*)keyIt())) {
if (!gROOT->GetClass(jobkey->GetClassName())->InheritsFrom("TDirectory")) continue;
TDirectory *jobDir = (TDirectory *)jobkey->ReadObj();
cout << "jobdir name " << jobDir->GetName() << endl;
jobdirs.Add(jobDir);
}
}
}
}
return jobdirs.GetSize();
}
void TextStage::filterAndScore(BSONObj key, DiskLoc loc) {
// Locate score within possibly compound key: {prefix,term,score,suffix}.
BSONObjIterator keyIt(key);
for (unsigned i = 0; i < _params.spec.numExtraBefore(); i++) {
keyIt.next();
}
keyIt.next(); // Skip past 'term'.
BSONElement scoreElement = keyIt.next();
double documentTermScore = scoreElement.number();
double& documentAggregateScore = _scores[loc];
// Handle filtering.
if (documentAggregateScore < 0) {
// We have already rejected this document.
return;
}
if (documentAggregateScore == 0 && _filter) {
// We have not seen this document before and need to apply a filter.
Record* rec_p = loc.rec();
BSONObj doc = BSONObj::make(rec_p);
// TODO: Covered index matching logic here.
if (!_filter->matchesBSON(doc)) {
documentAggregateScore = -1;
return;
}
}
// Aggregate relevance score, term keys.
documentAggregateScore += documentTermScore;
}
inline bool operator()(TUInt key,int x,int y){
TFRG_map<TUInt,int>::const_iterator keyIt(m_nodeKeysSet.find(key));
if (keyIt==m_nodeKeysSet.end())
return false;
if (((TUInt32)x%kFrg_ClipWidth==0)&&((TUInt32)y%kFrg_ClipHeight==0)&&(keyIt->second==1)){//self node
return false;
}
m_matchMap.insert(TColorMatch::TMatchMap::value_type((TUInt32)key,packMatchXY(x, y)));
return false;
}
void DrawNetworkMovie( TFile* file, const TString& methodType, const TString& methodTitle )
{
TString dirname = methodType + "/" + methodTitle + "/" + "EpochMonitoring";
TDirectory *epochDir = (TDirectory*)file->Get( dirname );
if (!epochDir) {
cout << "Big troubles: could not find directory \"" << dirname << "\"" << endl;
exit(1);
}
epochDir->cd();
// loop over all epoch-wise monitoring histograms
TIter keyIt(epochDir->GetListOfKeys());
TKey *key;
vector<TString> epochList;
Int_t ic = 0;
while ((key = (TKey*)keyIt())) {
if (!gROOT->GetClass(key->GetClassName())->InheritsFrom("TH2F")) continue;
TString name = key->GetName();
if (!name.BeginsWith("epochmonitoring___")) continue;
// extract epoch
TObjArray* tokens = name.Tokenize("_");
TString es = ((TObjString*)tokens->At(2))->GetString();
// check if done already
Bool_t isOld = kFALSE;
for (vector<TString>::const_iterator it = epochList.begin(); it < epochList.end(); it++) {
if (*it == es) isOld = kTRUE;
}
if (isOld) continue;
epochList.push_back( es );
// create bulk file name
TString bulkname = Form( "epochmonitoring___epoch_%s_weights_hist", es.Data() );
// draw the network
if (ic <= 60) draw_network( file, epochDir, bulkname, kTRUE, es );
ic++;
}
}
void TextStage::addTerm(const BSONObj& key, const DiskLoc& loc, ScoreMap* curMap) {
double *documentAggregateScore = &(*curMap)[loc];
if (curMap != &_negativeScores)
++_specificStats.keysExamined;
// Locate score within possibly compound key: {prefix,term,score,suffix}.
BSONObjIterator keyIt(key);
for (unsigned i = 0; i < _params.spec.numExtraBefore(); i++) {
keyIt.next();
}
keyIt.next(); // Skip past 'term'.
BSONElement scoreElement = keyIt.next();
double documentTermScore = scoreElement.number();
// Handle filtering.
if (*documentAggregateScore < 0) {
// We have already rejected this document.
return;
}
if (*documentAggregateScore == 0) {
if (_filter) {
// We have not seen this document before and need to apply a filter.
bool fetched = false;
TextMatchableDocument tdoc(_params.index->keyPattern(),
key,
loc,
_params.index->getCollection(),
&fetched);
if (!_filter->matches(&tdoc)) {
// We had to fetch but we're not going to return it.
if (fetched && curMap != &_negativeScores) {
++_specificStats.fetches;
}
*documentAggregateScore = -1;
return;
}
}
else {
// If we're here, we're going to return the doc, and we do a fetch later.
if (curMap != &_negativeScores)
++_specificStats.fetches;
}
}
// Aggregate relevance score, term keys.
*documentAggregateScore += documentTermScore;
}
bool KPrDeclarations::saveOdf(KoPASavingContext &paContext) const
{
/*
<presentation:header-decl presentation:name="hdr1">header</presentation:header-decl>
<presentation:footer-decl presentation:name="ftr1">Footer for the slide</presentation:footer-decl>
<presentation:footer-decl presentation:name="ftr2">footer</presentation:footer-decl>
<presentation:date-time-decl presentation:name="dtd1" presentation:source="current-date" style:data-style-name="D3"/>
*/
KoXmlWriter &writer(paContext.xmlWriter());
QHash<Type, QHash<QString, QVariant> >::const_iterator typeIt(m_declarations.constBegin());
for (; typeIt != m_declarations.constEnd(); ++typeIt) {
QHash<QString, QVariant>::const_iterator keyIt(typeIt.value().begin());
for (; keyIt != typeIt.value().constEnd(); ++keyIt) {
switch (typeIt.key()) {
case Footer:
writer.startElement("presentation:footer-decl");
break;
case Header:
writer.startElement("presentation:header-decl");
break;
case DateTime:
writer.startElement("presentation:date-time-decl");
break;
}
writer.addAttribute("presentation:name", keyIt.key());
if (typeIt.key() == DateTime) {
//TODO
}
else {
writer.addTextNode(keyIt.value().value<QString>());
}
writer.endElement();
}
}
return true;
}
// input: - Input file (result from TMVA)
// - use of TMVA plotting TStyle
void mvas( TString fin = "TMVA.root", HistType htype = MVAType, Bool_t useTMVAStyle = kTRUE )
{
// set style and remove existing canvas'
TMVAGlob::Initialize( useTMVAStyle );
// switches
const Bool_t Save_Images = kTRUE;
// checks if file with name "fin" is already open, and if not opens one
TFile* file = TMVAGlob::OpenFile( fin );
// define Canvas layout here!
Int_t xPad = 1; // no of plots in x
Int_t yPad = 1; // no of plots in y
Int_t noPad = xPad * yPad ;
const Int_t width = 600; // size of canvas
// this defines how many canvases we need
TCanvas *c = 0;
// counter variables
Int_t countCanvas = 0;
// search for the right histograms in full list of keys
TIter next(file->GetListOfKeys());
TKey *key(0);
while ((key = (TKey*)next())) {
if (!TString(key->GetName()).BeginsWith("Method_")) continue;
if( ! gROOT->GetClass(key->GetClassName())->InheritsFrom("TDirectory") ) continue;
TString methodName;
TMVAGlob::GetMethodName(methodName,key);
TDirectory* mDir = (TDirectory*)key->ReadObj();
TIter keyIt(mDir->GetListOfKeys());
TKey *titkey;
while ((titkey = (TKey*)keyIt())) {
if (!gROOT->GetClass(titkey->GetClassName())->InheritsFrom("TDirectory")) continue;
TDirectory *titDir = (TDirectory *)titkey->ReadObj();
TString methodTitle;
TMVAGlob::GetMethodTitle(methodTitle,titDir);
cout << "--- Found directory for method: " << methodName << "::" << methodTitle << flush;
TString hname = "MVA_" + methodTitle;
if (htype == ProbaType ) hname += "_Proba";
else if (htype == RarityType ) hname += "_Rarity";
TH1* sig = dynamic_cast<TH1*>(titDir->Get( hname + "_S" ));
TH1* bgd = dynamic_cast<TH1*>(titDir->Get( hname + "_B" ));
if (sig==0 || bgd==0) {
if (htype == MVAType)
cout << "mva distribution not available (this is normal for Cut classifier)" << endl;
else if(htype == ProbaType)
cout << "probability distribution not available (this is normal for Cut classifier)" << endl;
else if(htype == RarityType)
cout << "rarity distribution not available (this is normal for Cut classifier)" << endl;
else if(htype == CompareType)
cout << "overtraining check not available (this is normal for Cut classifier)" << endl;
else cout << endl;
}
else {
cout << endl;
// chop off useless stuff
sig->SetTitle( Form("TMVA response for classifier: %s", methodTitle.Data()) );
if (htype == ProbaType)
sig->SetTitle( Form("TMVA probability for classifier: %s", methodTitle.Data()) );
else if (htype == RarityType)
sig->SetTitle( Form("TMVA Rarity for classifier: %s", methodTitle.Data()) );
else if (htype == CompareType)
sig->SetTitle( Form("TMVA overtraining check for classifier: %s", methodTitle.Data()) );
// create new canvas
TString ctitle = ((htype == MVAType) ?
Form("TMVA response %s",methodTitle.Data()) :
(htype == ProbaType) ?
Form("TMVA probability %s",methodTitle.Data()) :
(htype == CompareType) ?
Form("TMVA comparison %s",methodTitle.Data()) :
Form("TMVA Rarity %s",methodTitle.Data()));
TString cname = ((htype == MVAType) ?
Form("output_%s",methodTitle.Data()) :
(htype == ProbaType) ?
Form("probability_%s",methodTitle.Data()) :
(htype == CompareType) ?
Form("comparison_%s",methodTitle.Data()) :
Form("rarity_%s",methodTitle.Data()));
c = new TCanvas( Form("canvas%d", countCanvas+1), ctitle,
countCanvas*50+200, countCanvas*20, width, (Int_t)width*0.78 );
// set the histogram style
TMVAGlob::SetSignalAndBackgroundStyle( sig, bgd );
// normalise both signal and background
TMVAGlob::NormalizeHists( sig, bgd );
// frame limits (choose judicuous x range)
Float_t nrms = 4;
cout << "--- Mean and RMS (S): " << sig->GetMean() << ", " << sig->GetRMS() << endl;
cout << "--- Mean and RMS (B): " << bgd->GetMean() << ", " << bgd->GetRMS() << endl;
Float_t xmin = TMath::Max( TMath::Min(sig->GetMean() - nrms*sig->GetRMS(),
bgd->GetMean() - nrms*bgd->GetRMS() ),
sig->GetXaxis()->GetXmin() );
Float_t xmax = TMath::Min( TMath::Max(sig->GetMean() + nrms*sig->GetRMS(),
bgd->GetMean() + nrms*bgd->GetRMS() ),
sig->GetXaxis()->GetXmax() );
Float_t ymin = 0;
Float_t maxMult = (htype == CompareType) ? 1.3 : 1.2;
Float_t ymax = TMath::Max( sig->GetMaximum(), bgd->GetMaximum() )*maxMult;
// build a frame
Int_t nb = 500;
TString hFrameName(TString("frame") + methodTitle);
TObject *o = gROOT->FindObject(hFrameName);
if(o) delete o;
TH2F* frame = new TH2F( hFrameName, sig->GetTitle(),
nb, xmin, xmax, nb, ymin, ymax );
frame->GetXaxis()->SetTitle( methodTitle + ((htype == MVAType || htype == CompareType) ? " response" : "") );
if (htype == ProbaType ) frame->GetXaxis()->SetTitle( "Signal probability" );
else if (htype == RarityType ) frame->GetXaxis()->SetTitle( "Signal rarity" );
frame->GetYaxis()->SetTitle("Normalized");
TMVAGlob::SetFrameStyle( frame );
// eventually: draw the frame
frame->Draw();
c->GetPad(0)->SetLeftMargin( 0.105 );
frame->GetYaxis()->SetTitleOffset( 1.2 );
// Draw legend
TLegend *legend= new TLegend( c->GetLeftMargin(), 1 - c->GetTopMargin() - 0.12,
c->GetLeftMargin() + (htype == CompareType ? 0.40 : 0.3), 1 - c->GetTopMargin() );
legend->SetFillStyle( 1 );
legend->AddEntry(sig,TString("Signal") + ((htype == CompareType) ? " (test sample)" : ""), "F");
legend->AddEntry(bgd,TString("Background") + ((htype == CompareType) ? " (test sample)" : ""), "F");
legend->SetBorderSize(1);
legend->SetMargin( (htype == CompareType ? 0.2 : 0.3) );
legend->Draw("same");
// overlay signal and background histograms
sig->Draw("samehist");
bgd->Draw("samehist");
if (htype == CompareType) {
// if overtraining check, load additional histograms
TH1* sigOv = 0;
TH1* bgdOv = 0;
TString ovname = hname += "_Train";
sigOv = dynamic_cast<TH1*>(titDir->Get( ovname + "_S" ));
bgdOv = dynamic_cast<TH1*>(titDir->Get( ovname + "_B" ));
if (sigOv == 0 || bgdOv == 0) {
cout << "+++ Problem in \"mvas.C\": overtraining check histograms do not exist" << endl;
}
else {
cout << "--- Found comparison histograms for overtraining check" << endl;
TLegend *legend2= new TLegend( 1 - c->GetRightMargin() - 0.42, 1 - c->GetTopMargin() - 0.12,
1 - c->GetRightMargin(), 1 - c->GetTopMargin() );
legend2->SetFillStyle( 1 );
legend2->SetBorderSize(1);
legend2->AddEntry(sigOv,"Signal (training sample)","P");
legend2->AddEntry(bgdOv,"Background (training sample)","P");
legend2->SetMargin( 0.1 );
legend2->Draw("same");
}
Int_t col = sig->GetLineColor();
sigOv->SetMarkerColor( col );
sigOv->SetMarkerSize( 0.7 );
sigOv->SetMarkerStyle( 20 );
sigOv->SetLineWidth( 1 );
sigOv->SetLineColor( col );
sigOv->Draw("e1same");
col = bgd->GetLineColor();
bgdOv->SetMarkerColor( col );
bgdOv->SetMarkerSize( 0.7 );
bgdOv->SetMarkerStyle( 20 );
bgdOv->SetLineWidth( 1 );
bgdOv->SetLineColor( col );
bgdOv->Draw("e1same");
ymax = TMath::Max( ymax, TMath::Max( sigOv->GetMaximum(), bgdOv->GetMaximum() )*maxMult );
frame->GetYaxis()->SetLimits( 0, ymax );
// for better visibility, plot thinner lines
sig->SetLineWidth( 1 );
bgd->SetLineWidth( 1 );
// perform K-S test
cout << "--- Perform Kolmogorov-Smirnov tests" << endl;
Double_t kolS = sig->KolmogorovTest( sigOv );
Double_t kolB = bgd->KolmogorovTest( bgdOv );
cout << "--- Goodness of signal (background) consistency: " << kolS << " (" << kolB << ")" << endl;
TString probatext = Form( "Kolmogorov-Smirnov test: signal (background) probability = %5.3g (%5.3g)", kolS, kolB );
TText* tt = new TText( 0.12, 0.74, probatext );
tt->SetNDC(); tt->SetTextSize( 0.032 ); tt->AppendPad();
}
// redraw axes
frame->Draw("sameaxis");
// text for overflows
Int_t nbin = sig->GetNbinsX();
Double_t dxu = sig->GetBinWidth(0);
Double_t dxo = sig->GetBinWidth(nbin+1);
TString uoflow = Form( "U/O-flow (S,B): (%.1f, %.1f)%% / (%.1f, %.1f)%%",
sig->GetBinContent(0)*dxu*100, bgd->GetBinContent(0)*dxu*100,
sig->GetBinContent(nbin+1)*dxo*100, bgd->GetBinContent(nbin+1)*dxo*100 );
TText* t = new TText( 0.975, 0.115, uoflow );
t->SetNDC();
t->SetTextSize( 0.030 );
t->SetTextAngle( 90 );
t->AppendPad();
// update canvas
c->Update();
// save canvas to file
TMVAGlob::plot_logo(1.058);
if (Save_Images) {
if (htype == MVAType) TMVAGlob::imgconv( c, Form("plots/mva_%s", methodTitle.Data()) );
else if (htype == ProbaType) TMVAGlob::imgconv( c, Form("plots/proba_%s", methodTitle.Data()) );
else if (htype == CompareType) TMVAGlob::imgconv( c, Form("plots/overtrain_%s", methodTitle.Data()) );
else TMVAGlob::imgconv( c, Form("plots/rarity_%s", methodTitle.Data()) );
}
countCanvas++;
}
}
}
}
IndexBoundsChecker::KeyState IndexBoundsChecker::checkKey(const BSONObj& key,
int* keyEltsToUse,
bool* movePastKeyElts,
vector<const BSONElement*>* out,
vector<bool>* incOut) {
verify(_curInterval.size() > 0);
verify(out->size() == _curInterval.size());
verify(incOut->size() == _curInterval.size());
// It's useful later to go from a field number to the value for that field. Store these.
// TODO: on optimization pass, populate the vector as-needed and keep the vector around as a
// member variable
vector<BSONElement> keyValues;
BSONObjIterator keyIt(key);
while (keyIt.more()) {
keyValues.push_back(keyIt.next());
}
verify(keyValues.size() == _curInterval.size());
size_t firstNonContainedField;
Location orientation;
if (!findLeftmostProblem(keyValues, &firstNonContainedField, &orientation)) {
// All fields in the index are within the current interval. Caller can use the key.
return VALID;
}
// Field number 'firstNonContainedField' of the index key is before its current interval.
// Tell the caller to move forward to the start of the current interval.
if (BEHIND == orientation) {
*keyEltsToUse = firstNonContainedField;
*movePastKeyElts = false;
for (size_t j = firstNonContainedField; j < _curInterval.size(); ++j) {
const OrderedIntervalList& oil = _bounds->fields[j];
(*out)[j] = &oil.intervals[_curInterval[j]].start;
(*incOut)[j] = oil.intervals[_curInterval[j]].startInclusive;
}
return MUST_ADVANCE;
}
verify(AHEAD == orientation);
// Field number 'firstNonContainedField' of the index key is after interval we think it's
// in. Fields 0 through 'firstNonContained-1' are within their current intervals and we can
// ignore them.
while (firstNonContainedField < _curInterval.size()) {
// Find the interval that contains our field.
size_t newIntervalForField;
Location where = findIntervalForField(keyValues[firstNonContainedField],
_bounds->fields[firstNonContainedField],
_expectedDirection[firstNonContainedField],
&newIntervalForField);
if (WITHIN == where) {
// Found a new interval for field firstNonContainedField. Move our internal choice
// of interval to that.
_curInterval[firstNonContainedField] = newIntervalForField;
// Let's find valid intervals for fields to the right.
++firstNonContainedField;
}
else if (BEHIND == where) {
// firstNonContained field is between the intervals (newIntervalForField-1) and
// newIntervalForField. We have to tell the caller to move forward until he at
// least hits our new current interval.
_curInterval[firstNonContainedField] = newIntervalForField;
// All other fields to the right start at their first interval.
for (size_t i = firstNonContainedField + 1; i < _curInterval.size(); ++i) {
_curInterval[i] = 0;
}
*keyEltsToUse = firstNonContainedField;
*movePastKeyElts = false;
for (size_t i = firstNonContainedField; i < _curInterval.size(); ++i) {
const OrderedIntervalList& oil = _bounds->fields[i];
(*out)[i] = &oil.intervals[_curInterval[i]].start;
(*incOut)[i] = oil.intervals[_curInterval[i]].startInclusive;
}
return MUST_ADVANCE;
}
else {
verify (AHEAD == where);
// Field number 'firstNonContainedField' cannot possibly be placed into an interval,
// as it is already past its last possible interval. The caller must move forward
// to a key with a greater value for the previous field.
// If all fields to the left have hit the end of their intervals, we can't ask them
// to move forward and we should stop iterating.
if (!spaceLeftToAdvance(firstNonContainedField, keyValues)) {
return DONE;
}
*keyEltsToUse = firstNonContainedField;
*movePastKeyElts = true;
for (size_t i = firstNonContainedField; i < _curInterval.size(); ++i) {
_curInterval[i] = 0;
}
// If movePastKeyElts is true, we don't examine any fields after the keyEltsToUse
// fields of the key. As such we don't populate the out/incOut.
return MUST_ADVANCE;
}
}
verify(firstNonContainedField == _curInterval.size());
return VALID;
}
Status S2IndexCursor::seek(const BSONObj &position) {
vector<GeoQuery> regions;
bool isNearQuery = false;
NearQuery nearQuery;
// Go through the fields that we index, and for each geo one, make
// a GeoQuery object for the S2*Cursor class to do intersection
// testing/cover generating with.
BSONObjIterator keyIt(_descriptor->keyPattern());
while (keyIt.more()) {
BSONElement keyElt = keyIt.next();
if (keyElt.type() != String || IndexNames::GEO_2DSPHERE != keyElt.valuestr()) {
continue;
}
BSONElement e = position.getFieldDotted(keyElt.fieldName());
if (e.eoo()) { continue; }
if (!e.isABSONObj()) { continue; }
BSONObj obj = e.Obj();
if (nearQuery.parseFrom(obj, _params.radius)) {
if (isNearQuery) {
return Status(ErrorCodes::BadValue, "Only one $near clause allowed: " +
position.toString(), 16685);
}
isNearQuery = true;
nearQuery.field = keyElt.fieldName();
continue;
}
GeoQuery geoQueryField(keyElt.fieldName());
if (!geoQueryField.parseFrom(obj)) {
return Status(ErrorCodes::BadValue, "can't parse query (2dsphere): "
+ obj.toString(), 16535);
}
if (!geoQueryField.hasS2Region()) {
return Status(ErrorCodes::BadValue, "Geometry unsupported: " + obj.toString(),
16684);
}
regions.push_back(geoQueryField);
}
// Remove all the indexed geo regions from the query. The s2*cursor will
// instead create a covering for that key to speed up the search.
//
// One thing to note is that we create coverings for indexed geo keys during
// a near search to speed it up further.
BSONObjBuilder geoFieldsToNuke;
if (isNearQuery) {
geoFieldsToNuke.append(nearQuery.field, "");
}
for (size_t i = 0; i < regions.size(); ++i) {
geoFieldsToNuke.append(regions[i].getField(), "");
}
// false means we want to filter OUT geoFieldsToNuke, not filter to include only that.
BSONObj filteredQuery = position.filterFieldsUndotted(geoFieldsToNuke.obj(), false);
if (isNearQuery) {
S2NearIndexCursor* nearCursor = new S2NearIndexCursor(_descriptor, _params);
_underlyingCursor.reset(nearCursor);
nearCursor->seek(filteredQuery, nearQuery, regions);
} else {
S2SimpleCursor* simpleCursor = new S2SimpleCursor(_descriptor, _params);
_underlyingCursor.reset(simpleCursor);
simpleCursor->seek(filteredQuery, regions);
}
return Status::OK();
}
void plPageOptimizer::Optimize()
{
fResMgr->AddSinglePage(fPagePath);
// Get the location of the page we're optimizing
IFindLoc();
bool loaded = true;
// Get the key for the scene node, we'll load it to force a load on all the objects
plKey snKey = plKeyFinder::Instance().FindSceneNodeKey(fLoc);
if (snKey)
{
// Load all the keys
fPageNode = fResMgr->FindPage(fLoc);
fResMgr->LoadPageKeys(fPageNode);
// Put all the keys in a vector, so they won't get unreffed
class plVecKeyCollector : public plRegistryKeyIterator
{
public:
KeyVec& fKeys;
plVecKeyCollector(KeyVec& keys) : fKeys(keys) {}
virtual bool EatKey(const plKey& key) { fKeys.push_back(key); return true; }
};
plVecKeyCollector keyIt(fAllKeys);
fResMgr->IterateKeys(&keyIt);
// Set our load proc, which will track the order that objects are loaded
fResMgr->SetProgressBarProc(KeyedObjectProc);
// Load the page
snKey->VerifyLoaded();
// Unload everything
snKey->RefObject();
snKey->UnRefObject();
snKey = nil;
}
else
{
loaded = false;
}
if (loaded)
IRewritePage();
uint64_t oldSize = plFileInfo(fPagePath).FileSize();
uint64_t newSize = plFileInfo(fTempPagePath).FileSize();
if (!loaded)
{
puts("no scene node.");
}
else if (fOptimized)
{
plFileSystem::Unlink(fTempPagePath);
puts("already optimized.");
}
else if (oldSize == newSize)
{
plFileSystem::Unlink(fPagePath);
plFileSystem::Move(fTempPagePath, fPagePath);
puts("complete");
}
else
{
plFileSystem::Unlink(fTempPagePath);
puts("failed. File sizes different");
}
}
// input: - Input file (result from TMVA)
// - use of TMVA plotting TStyle
void deviations( TString fin = "TMVAReg.root",
HistType htype = MVAType, Bool_t showTarget, Bool_t useTMVAStyle = kTRUE )
{
// set style and remove existing canvas'
TMVAGlob::Initialize( useTMVAStyle );
gStyle->SetNumberContours(999);
// switches
const Bool_t Save_Images = kTRUE;
// checks if file with name "fin" is already open, and if not opens one
TFile* file = TMVAGlob::OpenFile( fin );
// define Canvas layout here!
Int_t xPad = 1; // no of plots in x
Int_t yPad = 1; // no of plots in y
Int_t noPad = xPad * yPad ;
const Int_t width = 650; // size of canvas
// this defines how many canvases we need
TCanvas* c[100];
// counter variables
Int_t countCanvas = 0;
// search for the right histograms in full list of keys
// TList* methods = new TMap();
TIter next(file->GetListOfKeys());
TKey *key(0);
while ((key = (TKey*)next())) {
if (!TString(key->GetName()).BeginsWith("Method_")) continue;
if (!gROOT->GetClass(key->GetClassName())->InheritsFrom("TDirectory")) continue;
TString methodName;
TMVAGlob::GetMethodName(methodName,key);
cout << "--- Plotting deviation for method: " << methodName << endl;
TObjString *mN = new TObjString( methodName );
TDirectory* mDir = (TDirectory*)key->ReadObj();
TList* jobNames = new TList();
TIter keyIt(mDir->GetListOfKeys());
TKey *titkey;
while ((titkey = (TKey*)keyIt())) {
if (!gROOT->GetClass(titkey->GetClassName())->InheritsFrom("TDirectory")) continue;
TDirectory *titDir = (TDirectory *)titkey->ReadObj();
TObjString *jN = new TObjString( titDir->GetName() );
if (!jobNames->Contains( jN )) jobNames->Add( jN );
else delete jN;
TString methodTitle;
TMVAGlob::GetMethodTitle(methodTitle,titDir);
TString hname = "MVA_" + methodTitle;
TIter dirKeyIt( titDir->GetListOfKeys() );
TKey* dirKey;
Int_t countPlots = 0;
while ((dirKey = (TKey*)dirKeyIt())){
if (dirKey->ReadObj()->InheritsFrom("TH2F")) {
TString s(dirKey->ReadObj()->GetName());
if (s.Contains("_reg_") &&
( (showTarget && s.Contains("_tgt")) || (!showTarget && !s.Contains("_tgt")) ) &&
s.Contains( (htype == CompareType ? "train" : "test" ))) {
c[countCanvas] = new TCanvas( Form("canvas%d", countCanvas+1),
Form( "Regression output deviation versus %s for method: %s",
(showTarget ? "target" : "input variables"), methodName.Data() ),
countCanvas*50+100, (countCanvas+1)*20, width, (Int_t)width*0.72 );
c[countCanvas]->SetRightMargin(0.10); // leave space for border
TH1* h = (TH1*)dirKey->ReadObj();
h->SetTitle( Form("Output deviation for method: %s (%s sample)",
hname.Data(), (htype == CompareType ? "training" : "test" )) );
// methodName.Data(), (htype == CompareType ? "training" : "test" )) );
h->Draw("colz");
TLine* l = new TLine( h->GetXaxis()->GetXmin(), 0, h->GetXaxis()->GetXmax(), 0 );
l->SetLineStyle(2);
l->Draw();
// update and print
cout << "plotting logo" << endl;
TMVAGlob::plot_logo(1.058);
c[countCanvas]->Update();
TString fname = Form( "plots/deviation_%s_%s_%s_c%i",
methodName.Data(),
(showTarget ? "target" : "vars"),
(htype == CompareType ? "training" : "test" ), countPlots );
TMVAGlob::imgconv( c[countCanvas], fname );
countPlots++;
countCanvas++;
}
}
}
}
}
}
void ctkQtMobilityServiceRuntime::processPlugin(QSharedPointer<ctkPlugin> plugin)
{
QHash<QString, QString> headers = plugin->getHeaders();
QHash<QString, QString>::const_iterator it = headers.find(ctkQtMobilityServiceConstants::SERVICE_DESCRIPTOR);
ctkLogService* log = ctkQtMobilityServiceActivator::getLogService();
CTK_DEBUG(log)
<< "Process header " << ctkQtMobilityServiceConstants::SERVICE_DESCRIPTOR
<< " for plugin #" << plugin->getPluginId() << ": " << (it != headers.end() ? it.value() : "[missing]");
if (it != headers.end())
{
QString sd = it.value();
if (sd.isEmpty())
{
QString msg = QString("Header ") + ctkQtMobilityServiceConstants::SERVICE_DESCRIPTOR + " empty.";
ctkQtMobilityServiceActivator::logError(plugin->getPluginContext(), msg);
return;
}
QByteArray serviceDescription = plugin->getResource(sd);
QBuffer serviceBuffer(&serviceDescription);
qServiceManager.addService(&serviceBuffer);
QServiceManager::Error error = qServiceManager.error();
if (!(error == QServiceManager::NoError || error == QServiceManager::ServiceAlreadyExists))
{
QString msg = QString("Registering the QtMobility service descriptor failed: ") +
getQServiceManagerErrorString(error);
ctkQtMobilityServiceActivator::logError(plugin->getPluginContext(), msg);
return;
}
QString serviceName = plugin->getSymbolicName() + "_" + plugin->getVersion().toString();
QList<QServiceInterfaceDescriptor> descriptors = qServiceManager.findInterfaces(serviceName);
if (descriptors.isEmpty())
{
QString msg = QString("No interfaces found for service name ") + serviceName;
ctkQtMobilityServiceActivator::logWarning(plugin->getPluginContext(), msg);
return;
}
QListIterator<QServiceInterfaceDescriptor> it(descriptors);
while (it.hasNext())
{
QServiceInterfaceDescriptor descr = it.next();
CTK_DEBUG(ctkQtMobilityServiceActivator::getLogService()) << "Registering:" << descr.interfaceName();
QStringList classes;
ctkDictionary props;
QStringList customKeys = descr.customAttributes();
QStringListIterator keyIt(customKeys);
bool classAttrFound = false;
while (keyIt.hasNext())
{
QString key = keyIt.next();
if (key == ctkPluginConstants::OBJECTCLASS)
{
classAttrFound = true;
classes << descr.customAttribute(key);
}
else
{
props.insert(key, descr.customAttribute(key));
}
}
if (!classAttrFound)
{
QString msg = QString("The custom attribute \"") + ctkPluginConstants::OBJECTCLASS
+ "\" is missing in the interface description of \"" + descr.interfaceName();
ctkQtMobilityServiceActivator::logError(plugin->getPluginContext(), msg);
continue;
}
ctkQtMobilityServiceFactory* serviceObject = new ctkQtMobilityServiceFactory(descr, this, plugin);
ctkServiceRegistration serviceReg = plugin->getPluginContext()->registerService(classes, serviceObject, props);
if (serviceReg)
{
mapPluginToServiceFactory.insert(plugin, serviceObject);
mapPluginToServiceRegistration.insert(plugin, serviceReg);
}
else
{
QString msg = QString("Could not register QtMobility service ") + descr.serviceName() + " "
+ descr.interfaceName();
ctkQtMobilityServiceActivator::logError(plugin->getPluginContext(), msg);
continue;
}
}
}
}
