void CRUDupElimLogScanner::Fetch()
{
// Start the cyclic shift ...
pPrevRec_ = pCurrentRec_;
if (TRUE == pResultSet_->Next())
{
// End the cyclic shift ...
pCurrentRec_ = inputBuf_[inputBufIndex_];
// ... and retrieve the new data
pCurrentRec_->Build(*pResultSet_, ckStartColumn_);
// Move the pointer inside the buffer
inputBufIndex_ = (inputBufIndex_+1) % IB_SIZE;
if (NULL == pPrevRec_
||
pCurrentRec_->GetCKTuple() != pPrevRec_->GetCKTuple())
{
// A new distinct CK value has been encountered
ckTag_++;
}
pCurrentRec_->SetCKTag(ckTag_);
UpdateStatistics();
}
else
{
// End of input reached !
isEntireDeltaScanned_ = TRUE;
pCurrentStmt_->Close();
}
}
void CChangedDlg::OnBnClickedShowUnmodified()
{
UpdateData();
m_FileListCtrl.Show(UpdateShowFlags());
m_regAddBeforeCommit = m_bShowUnversioned;
UpdateStatistics();
}
void Game::Run()
{
sf::Clock clock;
sf::Time timeSinceLastUpdate = sf::Time::Zero;
while (m_window.isOpen())
{
sf::Time elapsedTime = clock.restart();
timeSinceLastUpdate += elapsedTime;
while (timeSinceLastUpdate > TimePerFrame)
{
timeSinceLastUpdate -= TimePerFrame;
ProcessInput();
Update(TimePerFrame);
// Check inside this loop, because stack might be empty before Update() call.
if (m_stateStack.IsEmpty())
{
std::cout << "In Game: Stack empty, closing window.\n";
m_window.close();
}
}
UpdateStatistics(elapsedTime);
Render();
}
}
int CBaseParser::ReadAmrData(ONDEMANDPARAM *pOndemand, BYTE *szBuffer, int nRetryState, int nSuccState)
{
int readLen=0, nError;
pOndemand->stat.nCount ++;
pOndemand->stat.nSendCount ++;
pOndemand->stat.nSend += sizeof(ENDI_AMRREAD_PAYLOAD) + sizeof(CODI_HEADER) + sizeof(EUI64) + sizeof(CODI_TAIL);
gettimeofday((struct timeval *)&pOndemand->tmSend, NULL);
nError = endiReadAmr(pOndemand->endi, (BYTE *)szBuffer, &readLen, GetReplyTimeout());
if (nError != CODIERR_NOERROR)
{
pOndemand->stat.nError ++;
if (pOndemand->nRetry < GetRetryCount()) // 3회 이상 연속 실패시 종료
{
pOndemand->nRetry++;
return nRetryState;
}else {
pOndemand->nRetry = 0;
return STATE_ERROR;
}
}
pOndemand->nRetry = 0;
UpdateStatistics(pOndemand, (BYTE *)szBuffer, readLen);
pOndemand->stat.nCount ++;
pOndemand->stat.nRecvCount ++;
return nSuccState;
}
void Frame::RunQuery(const wxString& query, bool empty_results)
{
wxStopWatch sw;
const wxString query_lower = query.Lower();
// Query functions supported by ODBC
// $SQLTables, $SQLColumns, etc.
// $SQLTables $1:'%'
// allow you to get database schema.
if (query_lower.StartsWith("select") ||
query_lower.StartsWith("describe") ||
query_lower.StartsWith("show") ||
query_lower.StartsWith("explain") ||
query_lower.StartsWith("$sql"))
{
long rpc;
if (m_Results->IsShown())
{
rpc = m_otl.Query(query, m_Results, m_Stopped, empty_results);
}
else
{
rpc = m_otl.Query(query, m_Shell, m_Stopped);
}
sw.Pause();
UpdateStatistics(sw.Time(), rpc);
}
else
{
const auto rpc = m_otl.Query(query);
sw.Pause();
UpdateStatistics(sw.Time(), rpc);
}
m_Shell->DocumentEnd();
}
UINT CChangedDlg::ChangedStatusThread()
{
InterlockedExchange(&m_bBlock, TRUE);
g_Git.RefreshGitIndex();
m_bCanceled = false;
SetDlgItemText(IDOK, CString(MAKEINTRESOURCE(IDS_MSGBOX_CANCEL)));
DialogEnableWindow(IDC_REFRESH, FALSE);
DialogEnableWindow(IDC_SHOWUNVERSIONED, FALSE);
DialogEnableWindow(IDC_SHOWUNMODIFIED, FALSE);
DialogEnableWindow(IDC_SHOWIGNORED, FALSE);
DialogEnableWindow(IDC_SHOWUSERPROPS, FALSE);
CString temp;
m_FileListCtrl.Clear();
if (!m_FileListCtrl.GetStatus(&m_pathList, m_bRemote, m_bShowIgnored != FALSE, m_bShowUnversioned != FALSE))
{
if (!m_FileListCtrl.GetLastErrorMessage().IsEmpty())
m_FileListCtrl.SetEmptyString(m_FileListCtrl.GetLastErrorMessage());
}
unsigned int dwShow = GITSLC_SHOWVERSIONEDBUTNORMALANDEXTERNALS | GITSLC_SHOWLOCKS | GITSLC_SHOWSWITCHED | GITSLC_SHOWINCHANGELIST;
dwShow |= m_bShowUnversioned ? GITSLC_SHOWUNVERSIONED : 0;
dwShow |= m_iShowUnmodified ? GITSLC_SHOWNORMAL : 0;
dwShow |= m_bShowIgnored ? GITSLC_SHOWIGNORED : 0;
dwShow |= m_bShowExternals ? GITSLC_SHOWEXTERNAL | GITSLC_SHOWINEXTERNALS | GITSLC_SHOWEXTERNALFROMDIFFERENTREPO : 0;
m_FileListCtrl.Show(dwShow);
UpdateStatistics();
bool bIsDirectory = false;
CTGitPath commonDir = m_FileListCtrl.GetCommonDirectory(false);
if (m_pathList.GetCount() == 1)
{
if (m_pathList[0].IsEmpty())
CAppUtils::SetWindowTitle(m_hWnd, g_Git.m_CurrentDir, m_sTitle);
else
CAppUtils::SetWindowTitle(m_hWnd, (g_Git.m_CurrentDir + _T("\\") + m_pathList[0].GetWinPathString()).TrimRight('\\'), m_sTitle);
bIsDirectory = m_pathList[0].IsDirectory() || m_pathList[0].IsEmpty(); // if it is empty it is g_Git.m_CurrentDir which is a directory
}
else
CAppUtils::SetWindowTitle(m_hWnd, commonDir.GetWinPathString(), m_sTitle);
SetDlgItemText(IDOK, CString(MAKEINTRESOURCE(IDS_MSGBOX_OK)));
DialogEnableWindow(IDC_REFRESH, TRUE);
DialogEnableWindow(IDC_SHOWUNVERSIONED, bIsDirectory);
//DialogEnableWindow(IDC_SHOWUNMODIFIED, bIsDirectory);
DialogEnableWindow(IDC_SHOWIGNORED, bIsDirectory);
DialogEnableWindow(IDC_SHOWUSERPROPS, TRUE);
InterlockedExchange(&m_bBlock, FALSE);
// revert the remote flag back to the default
m_bRemote = !!(DWORD)CRegDWORD(_T("Software\\TortoiseGit\\CheckRepo"), FALSE);
RefreshCursor();
return 0;
}
void CChangedDlg::OnBnClickedShowlocalchangesignored()
{
UpdateData();
if (m_FileListCtrl.m_FileLoaded & CGitStatusListCtrl::FILELIST_LOCALCHANGESIGNORED)
m_FileListCtrl.Show(UpdateShowFlags());
else if (m_bShowLocalChangesIgnored)
{
if (!AfxBeginThread(ChangedStatusThreadEntry, this))
CMessageBox::Show(GetSafeHwnd(), IDS_ERR_THREADSTARTFAILED, IDS_APPNAME, MB_OK | MB_ICONERROR);
}
UpdateStatistics();
}
void CChangedDlg::OnBnClickedShowignored()
{
UpdateData();
if (m_FileListCtrl.m_FileLoaded & CGitStatusListCtrl::FILELIST_IGNORE)
m_FileListCtrl.Show(UpdateShowFlags());
else if (m_bShowIgnored)
{
if (AfxBeginThread(ChangedStatusThreadEntry, this) == nullptr)
CMessageBox::Show(NULL, IDS_ERR_THREADSTARTFAILED, IDS_APPNAME, MB_OK | MB_ICONERROR);
}
UpdateStatistics();
}
bool StatisticalProfiler::IsDone() const
{
if (mSamples.size() >= mLastCalculationSize + mSamplesPerCalculation)
UpdateStatistics();
if (mSamples.size() >= mMaxSamples)
return true;
if (mSamples.size() < mMinSamples)
return false;
return mStdDev <= mTargetStdDev * mMean;
}
UINT CChangedDlg::ChangedStatusThread()
{
InterlockedExchange(&m_bBlock, TRUE);
m_bCanceled = false;
SetDlgItemText(IDOK, CString(MAKEINTRESOURCE(IDS_MSGBOX_CANCEL)));
DialogEnableWindow(IDC_REFRESH, FALSE);
DialogEnableWindow(IDC_CHECKREPO, FALSE);
DialogEnableWindow(IDC_SHOWUNVERSIONED, FALSE);
DialogEnableWindow(IDC_SHOWUNMODIFIED, FALSE);
DialogEnableWindow(IDC_SHOWIGNORED, FALSE);
DialogEnableWindow(IDC_SHOWUSERPROPS, FALSE);
CString temp;
if (!m_FileListCtrl.GetStatus(&m_pathList, m_bRemote, m_bShowIgnored != FALSE, m_bShowUnversioned,m_bShowUserProps != FALSE))
{
if (!m_FileListCtrl.GetLastErrorMessage().IsEmpty())
m_FileListCtrl.SetEmptyString(m_FileListCtrl.GetLastErrorMessage());
}
DWORD dwShow = SVNSLC_SHOWVERSIONEDBUTNORMALANDEXTERNALS | SVNSLC_SHOWLOCKS | SVNSLC_SHOWSWITCHED | SVNSLC_SHOWINCHANGELIST;
dwShow |= m_bShowUnversioned ? SVNSLC_SHOWUNVERSIONED : 0;
dwShow |= m_iShowUnmodified ? SVNSLC_SHOWNORMAL : 0;
dwShow |= m_bShowIgnored ? SVNSLC_SHOWIGNORED : 0;
dwShow |= m_bShowExternals ? SVNSLC_SHOWEXTERNAL | SVNSLC_SHOWINEXTERNALS | SVNSLC_SHOWEXTERNALFROMDIFFERENTREPO : 0;
m_FileListCtrl.Show(dwShow);
UpdateStatistics();
CTGitPath commonDir = m_FileListCtrl.GetCommonDirectory(false);
bool bSingleFile = ((m_pathList.GetCount()==1)&&(!m_pathList[0].IsDirectory()));
if (bSingleFile)
SetWindowText(m_sTitle + _T(" - ") + m_pathList[0].GetWinPathString());
else
SetWindowText(m_sTitle + _T(" - ") + commonDir.GetWinPathString());
SetDlgItemText(IDOK, CString(MAKEINTRESOURCE(IDS_MSGBOX_OK)));
DialogEnableWindow(IDC_REFRESH, TRUE);
DialogEnableWindow(IDC_CHECKREPO, TRUE);
DialogEnableWindow(IDC_SHOWUNVERSIONED, !bSingleFile);
DialogEnableWindow(IDC_SHOWUNMODIFIED, !bSingleFile);
DialogEnableWindow(IDC_SHOWIGNORED, !bSingleFile);
DialogEnableWindow(IDC_SHOWUSERPROPS, TRUE);
InterlockedExchange(&m_bBlock, FALSE);
// revert the remote flag back to the default
m_bRemote = !!(DWORD)CRegDWORD(_T("Software\\TortoiseGit\\CheckRepo"), FALSE);
RefreshCursor();
return 0;
}
UINT CChangedDlg::ChangedStatusThread()
{
InterlockedExchange(&m_bBlock, TRUE);
g_Git.RefreshGitIndex();
m_bCanceled = false;
SetDlgItemText(IDOK, CString(MAKEINTRESOURCE(IDS_MSGBOX_CANCEL)));
DialogEnableWindow(IDC_REFRESH, FALSE);
DialogEnableWindow(IDC_SHOWUNVERSIONED, FALSE);
DialogEnableWindow(IDC_SHOWUNMODIFIED, FALSE);
DialogEnableWindow(IDC_SHOWIGNORED, FALSE);
DialogEnableWindow(IDC_SHOWLOCALCHANGESIGNORED, FALSE);
CString temp;
m_FileListCtrl.Clear();
if (!m_FileListCtrl.GetStatus(m_bWholeProject ? nullptr : &m_pathList, m_bRemote, m_bShowIgnored != FALSE, m_bShowUnversioned != FALSE, m_bShowLocalChangesIgnored != FALSE))
{
if (!m_FileListCtrl.GetLastErrorMessage().IsEmpty())
m_FileListCtrl.SetEmptyString(m_FileListCtrl.GetLastErrorMessage());
}
unsigned int dwShow = GITSLC_SHOWVERSIONEDBUTNORMALANDEXTERNALS | GITSLC_SHOWLOCKS | GITSLC_SHOWSWITCHED | GITSLC_SHOWINCHANGELIST;
dwShow |= m_bShowUnversioned ? GITSLC_SHOWUNVERSIONED : 0;
dwShow |= m_iShowUnmodified ? GITSLC_SHOWNORMAL : 0;
dwShow |= m_bShowIgnored ? GITSLC_SHOWIGNORED : 0;
dwShow |= m_bShowLocalChangesIgnored ? GITSLC_SHOWASSUMEVALID | GITSLC_SHOWSKIPWORKTREE : 0;
m_FileListCtrl.Show(dwShow);
UpdateStatistics();
SetDlgTitle();
bool bIsDirectory = false;
if (m_pathList.GetCount() == 1)
bIsDirectory = m_pathList[0].IsDirectory() || m_pathList[0].IsEmpty(); // if it is empty it is g_Git.m_CurrentDir which is a directory
SetDlgItemText(IDOK, CString(MAKEINTRESOURCE(IDS_MSGBOX_OK)));
DialogEnableWindow(IDC_REFRESH, TRUE);
DialogEnableWindow(IDC_SHOWUNVERSIONED, bIsDirectory);
//DialogEnableWindow(IDC_SHOWUNMODIFIED, bIsDirectory);
DialogEnableWindow(IDC_SHOWIGNORED, bIsDirectory);
DialogEnableWindow(IDC_SHOWLOCALCHANGESIGNORED, TRUE);
InterlockedExchange(&m_bBlock, FALSE);
// revert the remote flag back to the default
m_bRemote = !!(DWORD)CRegDWORD(_T("Software\\TortoiseGit\\CheckRepo"), FALSE);
RefreshCursor();
return 0;
}
void CChangedDlg::OnBnClickedShowunversioned()
{
UpdateData();
m_regAddBeforeCommit = m_bShowUnversioned;
if(m_FileListCtrl.m_FileLoaded & CGitStatusListCtrl::FILELIST_UNVER)
{
m_FileListCtrl.Show(UpdateShowFlags());
}
else
{
if(m_bShowUnversioned)
{
if (!AfxBeginThread(ChangedStatusThreadEntry, this))
{
CMessageBox::Show(GetSafeHwnd(), IDS_ERR_THREADSTARTFAILED, IDS_APPNAME, MB_OK | MB_ICONERROR);
}
}
}
UpdateStatistics();
}
void Game::Run()
{
sf::Clock clock;
sf::Time timeSinceLastUpdate = sf::Time::Zero;
while (mWindow.isOpen())
{
sf::Time elapsedTime = clock.restart();
timeSinceLastUpdate += elapsedTime;
while (timeSinceLastUpdate > TimePerFrame)
{
timeSinceLastUpdate -= TimePerFrame;
ProcessEvents();
Update(TimePerFrame);
}
UpdateStatistics(elapsedTime);
Render();
}
}
int CBaseParser::ReadRomMap(WORD addr, int len, ONDEMANDPARAM *pOndemand, BYTE *szBuffer,
int nRetryState, int nSuccState)
{
int readLen=0, nError;
pOndemand->stat.nCount ++;
pOndemand->stat.nSendCount ++;
pOndemand->stat.nSend += sizeof(ENDI_ROMREAD_PAYLOAD) + sizeof(CODI_HEADER) + sizeof(EUI64) + sizeof(CODI_TAIL);
gettimeofday((struct timeval *)&pOndemand->tmSend, NULL);
nError = endiReadRom(pOndemand->endi, addr, len, (BYTE *)szBuffer, &readLen, GetReplyTimeout());
if (nError != CODIERR_NOERROR)
{
pOndemand->stat.nError ++;
if (pOndemand->nRetry < GetRetryCount()) // 3회 이상 연속 실패시 종료
{
pOndemand->nRetry++;
return nRetryState;
}else {
pOndemand->nRetry = 0;
return STATE_ERROR;
}
}
if (readLen != len)
{
XDEBUG(ANSI_COLOR_RED " ****** PARSER: Invalid ROM DATA Length ******\r\n" ANSI_NORMAL);
XDEBUG(ANSI_COLOR_RED " Request Size = %d, Read Size = %d\r\n" ANSI_NORMAL, len, readLen);
pOndemand->nRetry++;
return nRetryState;
}
pOndemand->nRetry = 0;
UpdateStatistics(pOndemand, (BYTE *)szBuffer, readLen);
pOndemand->stat.nCount ++;
pOndemand->stat.nRecvCount ++;
return nSuccState;
}
double StatisticalProfiler::GetMedian() const
{
UpdateStatistics();
return mMedian;
}
double StatisticalProfiler::GetMax() const
{
UpdateStatistics();
return mMax;
}
float32 b2ParticleGroup::GetMass() const
{
UpdateStatistics();
return m_mass;
}
int
SolveSubproblem(int CurrentSubproblem, int Subproblems,
GainType * GlobalBestCost)
{
Node *FirstNodeSaved = FirstNode, *N, *Next, *Last = 0;
GainType OptimumSaved = Optimum, Cost, Improvement, GlobalCost;
double LastTime, Time, ExcessSaved = Excess;
int NewDimension = 0, OldDimension = 0, Number, i, InitialTourEdges = 0,
AscentCandidatesSaved = AscentCandidates,
InitialPeriodSaved = InitialPeriod, MaxTrialsSaved = MaxTrials;
BestCost = PLUS_INFINITY;
FirstNode = 0;
N = FirstNodeSaved;
do {
if (N->Subproblem == CurrentSubproblem) {
if (SubproblemsCompressed &&
(((N->SubproblemPred == N->SubBestPred ||
FixedOrCommon(N, N->SubproblemPred) ||
(N->SubBestPred &&
(N->FixedTo1Saved == N->SubBestPred ||
N->FixedTo2Saved == N->SubBestPred))) &&
(N->SubproblemSuc == N->SubBestSuc ||
FixedOrCommon(N, N->SubproblemSuc) ||
(N->SubBestSuc &&
(N->FixedTo1Saved == N->SubBestSuc ||
N->FixedTo2Saved == N->SubBestSuc)))) ||
((N->SubproblemPred == N->SubBestSuc ||
FixedOrCommon(N, N->SubproblemPred) ||
(N->SubBestSuc &&
(N->FixedTo1Saved == N->SubBestSuc ||
N->FixedTo2Saved == N->SubBestSuc))) &&
(N->SubproblemSuc == N->SubBestPred ||
FixedOrCommon(N, N->SubproblemSuc) ||
(N->SubBestPred &&
(N->FixedTo1Saved == N->SubBestPred ||
N->FixedTo2Saved == N->SubBestPred))))))
N->Subproblem = -CurrentSubproblem;
else {
if (!FirstNode)
FirstNode = N;
NewDimension++;
}
N->Head = N->Tail = 0;
if (N->SubBestSuc)
OldDimension++;
}
N->SubBestPred = N->SubBestSuc = 0;
N->FixedTo1Saved = N->FixedTo1;
N->FixedTo2Saved = N->FixedTo2;
} while ((N = N->SubproblemSuc) != FirstNodeSaved);
if ((Number = CurrentSubproblem % Subproblems) == 0)
Number = Subproblems;
if (NewDimension <= 3 || NewDimension == OldDimension) {
if (TraceLevel >= 1 && NewDimension <= 3)
printff
("\nSubproblem %d of %d: Dimension = %d (too small)\n",
Number, Subproblems, NewDimension);
FirstNode = FirstNodeSaved;
return 0;
}
if (AscentCandidates > NewDimension - 1)
AscentCandidates = NewDimension - 1;
if (InitialPeriod < 0) {
InitialPeriod = NewDimension / 2;
if (InitialPeriod < 100)
InitialPeriod = 100;
}
if (Excess < 0)
Excess = 1.0 / NewDimension;
if (MaxTrials == -1)
MaxTrials = NewDimension;
N = FirstNode;
do {
Next = N->SubproblemSuc;
if (N->Subproblem == CurrentSubproblem) {
N->Pred = N->Suc = N;
if (N != FirstNode)
Follow(N, Last);
Last = N;
} else if (Next->Subproblem == CurrentSubproblem
&& !Fixed(Last, Next)) {
if (!Last->FixedTo1
|| Last->FixedTo1->Subproblem != CurrentSubproblem)
Last->FixedTo1 = Next;
else
Last->FixedTo2 = Next;
if (!Next->FixedTo1
|| Next->FixedTo1->Subproblem != CurrentSubproblem)
Next->FixedTo1 = Last;
else
Next->FixedTo2 = Last;
if (C == C_EXPLICIT) {
if (Last->Id > Next->Id)
Last->C[Next->Id] = 0;
else
Next->C[Last->Id] = 0;
}
}
}
while ((N = Next) != FirstNode);
Dimension = NewDimension;
AllocateSegments();
InitializeStatistics();
if (CacheSig)
for (i = 0; i <= CacheMask; i++)
CacheSig[i] = 0;
OptimumSaved = Optimum;
Optimum = 0;
N = FirstNode;
do {
if (N->SubproblemSuc == N->InitialSuc ||
N->SubproblemPred == N->InitialSuc)
InitialTourEdges++;
if (!Fixed(N, N->Suc))
Optimum += Distance(N, N->Suc);
if (N->FixedTo1 && N->Subproblem != N->FixedTo1->Subproblem)
eprintf("Illegal fixed edge (%d,%d)", N->Id, N->FixedTo1->Id);
if (N->FixedTo2 && N->Subproblem != N->FixedTo2->Subproblem)
eprintf("Illegal fixed edge (%d,%d)", N->Id, N->FixedTo2->Id);
}
while ((N = N->Suc) != FirstNode);
if (TraceLevel >= 1)
printff
("\nSubproblem %d of %d: Dimension = %d, Upper bound = "
GainFormat "\n", Number, Subproblems, Dimension, Optimum);
FreeCandidateSets();
CreateCandidateSet();
for (Run = 1; Run <= Runs; Run++) {
LastTime = GetTime();
Cost = Norm != 0 ? FindTour() : Optimum;
/* Merge with subproblem tour */
Last = 0;
N = FirstNode;
do {
if (N->Subproblem == CurrentSubproblem) {
if (Last)
Last->Next = N;
Last = N;
}
}
while ((N = N->SubproblemSuc) != FirstNode);
Last->Next = FirstNode;
Cost = MergeWithTour();
if (MaxPopulationSize > 1) {
/* Genetic algorithm */
for (i = 0; i < PopulationSize; i++)
Cost = MergeTourWithIndividual(i);
if (!HasFitness(Cost)) {
if (PopulationSize < MaxPopulationSize) {
AddToPopulation(Cost);
if (TraceLevel >= 1)
PrintPopulation();
} else if (Cost < Fitness[PopulationSize - 1]) {
ReplaceIndividualWithTour(PopulationSize - 1, Cost);
if (TraceLevel >= 1)
PrintPopulation();
}
}
}
if (Cost < BestCost) {
N = FirstNode;
do {
N->SubBestPred = N->Pred;
N->SubBestSuc = N->Suc;
} while ((N = N->Suc) != FirstNode);
BestCost = Cost;
}
if (Cost < Optimum || (Cost != Optimum && OutputTourFileName)) {
Improvement = Optimum - Cost;
if (Improvement > 0) {
BestCost = GlobalCost = *GlobalBestCost -= Improvement;
Optimum = Cost;
} else
GlobalCost = *GlobalBestCost - Improvement;
N = FirstNode;
do
N->Mark = 0;
while ((N = N->SubproblemSuc) != FirstNode);
do {
N->Mark = N;
if (!N->SubproblemSuc->Mark &&
(N->Subproblem != CurrentSubproblem ||
N->SubproblemSuc->Subproblem != CurrentSubproblem))
N->BestSuc = N->SubproblemSuc;
else if (!N->SubproblemPred->Mark &&
(N->Subproblem != CurrentSubproblem ||
N->SubproblemPred->Subproblem !=
CurrentSubproblem))
N->BestSuc = N->SubproblemPred;
else if (!N->Suc->Mark)
N->BestSuc = N->Suc;
else if (!N->Pred->Mark)
N->BestSuc = N->Pred;
else
N->BestSuc = FirstNode;
}
while ((N = N->BestSuc) != FirstNode);
Dimension = DimensionSaved;
i = 0;
do {
if (ProblemType != ATSP)
BetterTour[++i] = N->Id;
else if (N->Id <= Dimension / 2) {
i++;
if (N->BestSuc->Id != N->Id + Dimension / 2)
BetterTour[i] = N->Id;
else
BetterTour[Dimension / 2 - i + 1] = N->Id;
}
}
while ((N = N->BestSuc) != FirstNode);
BetterTour[0] =
BetterTour[ProblemType !=
ATSP ? Dimension : Dimension / 2];
WriteTour(OutputTourFileName, BetterTour, GlobalCost);
if (Improvement > 0) {
do
if (N->Subproblem != CurrentSubproblem)
break;
while ((N = N->SubproblemPred) != FirstNode);
if (N->SubproblemSuc == N->BestSuc) {
N = FirstNode;
do {
N->BestSuc->SubproblemPred = N;
N = N->SubproblemSuc = N->BestSuc;
}
while (N != FirstNode);
} else {
N = FirstNode;
do
(N->SubproblemPred = N->BestSuc)->SubproblemSuc =
N;
while ((N = N->BestSuc) != FirstNode);
}
RecordBestTour();
WriteTour(TourFileName, BestTour, GlobalCost);
}
Dimension = NewDimension;
if (TraceLevel >= 1) {
printff("*** %d: Cost = " GainFormat, Number, GlobalCost);
if (OptimumSaved != MINUS_INFINITY && OptimumSaved != 0)
printff(", Gap = %04f%%",
100.0 * (GlobalCost -
OptimumSaved) / OptimumSaved);
printff(", Time = %0.2f sec. %s\n",
fabs(GetTime() - LastTime),
GlobalCost < OptimumSaved ? "<" : GlobalCost ==
OptimumSaved ? "=" : "");
}
}
Time = fabs(GetTime() - LastTime);
UpdateStatistics(Cost, Time);
if (TraceLevel >= 1 && Cost != PLUS_INFINITY)
printff("Run %d: Cost = " GainFormat ", Time = %0.2f sec.\n\n",
Run, Cost, Time);
if (PopulationSize >= 2 &&
(PopulationSize == MaxPopulationSize
|| Run >= 2 * MaxPopulationSize) && Run < Runs) {
Node *N;
int Parent1, Parent2;
Parent1 = LinearSelection(PopulationSize, 1.25);
do
Parent2 = LinearSelection(PopulationSize, 1.25);
while (Parent1 == Parent2);
ApplyCrossover(Parent1, Parent2);
N = FirstNode;
do {
int d = C(N, N->Suc);
AddCandidate(N, N->Suc, d, INT_MAX);
AddCandidate(N->Suc, N, d, INT_MAX);
N = N->InitialSuc = N->Suc;
}
while (N != FirstNode);
}
SRandom(++Seed);
if (Norm == 0)
break;
}
if (TraceLevel >= 1)
PrintStatistics();
if (C == C_EXPLICIT) {
N = FirstNode;
do {
for (i = 1; i < N->Id; i++) {
N->C[i] -= N->Pi + NodeSet[i].Pi;
N->C[i] /= Precision;
}
if (N->FixedTo1 && N->FixedTo1 != N->FixedTo1Saved) {
if (N->Id > N->FixedTo1->Id)
N->C[N->FixedTo1->Id] = Distance(N, N->FixedTo1);
else
N->FixedTo1->C[N->Id] = Distance(N, N->FixedTo1);
}
if (N->FixedTo2 && N->FixedTo2 != N->FixedTo2Saved) {
if (N->Id > N->FixedTo2->Id)
N->C[N->FixedTo2->Id] = Distance(N, N->FixedTo2);
else
N->FixedTo2->C[N->Id] = Distance(N, N->FixedTo2);
}
}
while ((N = N->Suc) != FirstNode);
}
FreeSegments();
FreeCandidateSets();
FreePopulation();
if (InitialTourEdges == Dimension) {
do
N->InitialSuc = N->SubproblemSuc;
while ((N = N->SubproblemSuc) != FirstNode);
} else {
do
N->InitialSuc = 0;
while ((N = N->SubproblemSuc) != FirstNode);
}
Dimension = ProblemType != ATSP ? DimensionSaved : 2 * DimensionSaved;
N = FirstNode = FirstNodeSaved;
do {
N->Suc = N->BestSuc = N->SubproblemSuc;
N->Suc->Pred = N;
Next = N->FixedTo1;
N->FixedTo1 = N->FixedTo1Saved;
N->FixedTo1Saved = Next;
Next = N->FixedTo2;
N->FixedTo2 = N->FixedTo2Saved;
N->FixedTo2Saved = Next;
}
while ((N = N->Suc) != FirstNode);
Optimum = OptimumSaved;
Excess = ExcessSaved;
AscentCandidates = AscentCandidatesSaved;
InitialPeriod = InitialPeriodSaved;
MaxTrials = MaxTrialsSaved;
return 1;
}
float32 b2ParticleGroup::GetInertia() const
{
UpdateStatistics();
return m_inertia;
}
b2Vec2 b2ParticleGroup::GetCenter() const
{
UpdateStatistics();
return m_center;
}
QgsMssqlProvider::QgsMssqlProvider( QString uri )
: QgsVectorDataProvider( uri )
, mCrs()
, mWkbType( QGis::WKBUnknown )
{
QgsDataSourceURI anUri = QgsDataSourceURI( uri );
if ( !anUri.srid().isEmpty() )
mSRId = anUri.srid().toInt();
else
mSRId = -1;
mWkbType = anUri.wkbType();
mValid = true;
mUseWkb = false;
mSkipFailures = false;
mUseEstimatedMetadata = anUri.useEstimatedMetadata();
mSqlWhereClause = anUri.sql();
mDatabase = GetDatabase( anUri.service(), anUri.host(), anUri.database(), anUri.username(), anUri.password() );
if ( !OpenDatabase( mDatabase ) )
{
setLastError( mDatabase.lastError( ).text( ) );
mValid = false;
return;
}
// Create a query for default connection
mQuery = QSqlQuery( mDatabase );
// Database successfully opened; we can now issue SQL commands.
if ( !anUri.schema().isEmpty() )
mSchemaName = anUri.schema();
else
mSchemaName = "dbo";
if ( !anUri.table().isEmpty() )
{
// the layer name has been specified
mTableName = anUri.table();
QStringList sl = mTableName.split( '.' );
if ( sl.length() == 2 )
{
mSchemaName = sl[0];
mTableName = sl[1];
}
mTables = QStringList( mTableName );
}
else
{
// Get a list of table
mTables = mDatabase.tables( QSql::Tables );
if ( mTables.count() > 0 )
mTableName = mTables[0];
else
mValid = false;
}
if ( mValid )
{
if ( !anUri.keyColumn().isEmpty() )
mFidColName = anUri.keyColumn();
if ( !anUri.geometryColumn().isEmpty() )
mGeometryColName = anUri.geometryColumn();
if ( mSRId < 0 || mWkbType == QGis::WKBUnknown || mGeometryColName.isEmpty() )
loadMetadata();
loadFields();
UpdateStatistics( mUseEstimatedMetadata );
if ( mGeometryColName.isEmpty() )
{
// table contains no geometries
mWkbType = QGis::WKBNoGeometry;
mSRId = 0;
}
}
//fill type names into sets
mNativeTypes
// integer types
<< QgsVectorDataProvider::NativeType( tr( "8 Bytes integer" ), "bigint", QVariant::Int )
<< QgsVectorDataProvider::NativeType( tr( "4 Bytes integer" ), "int", QVariant::Int )
<< QgsVectorDataProvider::NativeType( tr( "2 Bytes integer" ), "smallint", QVariant::Int )
<< QgsVectorDataProvider::NativeType( tr( "1 Bytes integer" ), "tinyint", QVariant::Int )
<< QgsVectorDataProvider::NativeType( tr( "Decimal number (numeric)" ), "numeric", QVariant::Double, 1, 20, 0, 20 )
<< QgsVectorDataProvider::NativeType( tr( "Decimal number (decimal)" ), "decimal", QVariant::Double, 1, 20, 0, 20 )
// floating point
<< QgsVectorDataProvider::NativeType( tr( "Decimal number (real)" ), "real", QVariant::Double )
<< QgsVectorDataProvider::NativeType( tr( "Decimal number (double)" ), "float", QVariant::Double )
// string types
<< QgsVectorDataProvider::NativeType( tr( "Text, fixed length (char)" ), "char", QVariant::String, 1, 255 )
<< QgsVectorDataProvider::NativeType( tr( "Text, limited variable length (varchar)" ), "varchar", QVariant::String, 1, 255 )
<< QgsVectorDataProvider::NativeType( tr( "Text, fixed length unicode (nchar)" ), "nchar", QVariant::String, 1, 255 )
<< QgsVectorDataProvider::NativeType( tr( "Text, limited variable length unicode (nvarchar)" ), "nvarchar", QVariant::String, 1, 255 )
<< QgsVectorDataProvider::NativeType( tr( "Text, unlimited length (text)" ), "text", QVariant::String )
<< QgsVectorDataProvider::NativeType( tr( "Text, unlimited length unicode (ntext)" ), "text", QVariant::String )
;
}
LRESULT CChangedDlg::OnSVNStatusListCtrlItemCountChanged(WPARAM, LPARAM)
{
UpdateStatistics();
return 0;
}
void QmitkImageStatisticsView::IgnoreZerosCheckboxClicked( )
{
UpdateStatistics();
}
b2Vec2 b2ParticleGroup::GetLinearVelocity() const
{
UpdateStatistics();
return m_linearVelocity;
}
float32 b2ParticleGroup::GetAngularVelocity() const
{
UpdateStatistics();
return m_angularVelocity;
}
ReturnFlag LKH::LKHAlg::run_()
{
GainType Cost, OldOptimum;
double Time, LastTime = GetTime();
if (SubproblemSize > 0) {
if (DelaunayPartitioning)
SolveDelaunaySubproblems();
else if (KarpPartitioning)
SolveKarpSubproblems();
else if (KCenterPartitioning)
SolveKCenterSubproblems();
else if (KMeansPartitioning)
SolveKMeansSubproblems();
else if (RohePartitioning)
SolveRoheSubproblems();
else if (MoorePartitioning || SierpinskiPartitioning)
SolveSFCSubproblems();
else
SolveTourSegmentSubproblems();
}
AllocateStructures();
CreateCandidateSet();
InitializeStatistics();
if (Norm != 0)
BestCost = PLUS_INFINITY;
else {
/* The ascent has solved the problem! */
Optimum = BestCost = (GainType) LowerBound;
UpdateStatistics(Optimum, GetTime() - LastTime);
RecordBetterTour();
RecordBestTour();
WriteTour(OutputTourFileName, BestTour, BestCost);
WriteTour(TourFileName, BestTour, BestCost);
Runs = 0;
}
/* Find a specified number (Runs) of local optima */
for (Run = 1; Run <= Runs; Run++) {
LastTime = GetTime();
Cost = FindTour(); /* using the Lin-Kernighan heuristic */
if (*MaxPopulationSize > 1) {
/* Genetic algorithm */
int i;
for (i = 0; i < *PopulationSize; i++) {
GainType OldCost = Cost;
Cost = MergeTourWithIndividual(i,this);
if (TraceLevel >= 1 && Cost < OldCost) {
printff(" Merged with %d: Cost = " GainFormat, i + 1,
Cost);
if (Optimum != MINUS_INFINITY && Optimum != 0)
printff(", Gap = %0.4f%%",
100.0 * (Cost - Optimum) / Optimum);
printff("\n");
}
}
if (!HasFitness(Cost)) {
if (*PopulationSize < *MaxPopulationSize) {
AddToPopulation(Cost,this);
if (TraceLevel >= 1)
PrintPopulation(this);
} else if (Cost < Fitness.get()[*PopulationSize - 1]) {
i = ReplacementIndividual(Cost,this);
ReplaceIndividualWithTour(i, Cost,this);
if (TraceLevel >= 1)
PrintPopulation(this);
}
}
} else if (Run > 1)
Cost = MergeBetterTourWithBestTour();
if (Cost < BestCost) {
BestCost = Cost;
RecordBetterTour();
RecordBestTour();
WriteTour(OutputTourFileName, BestTour, BestCost);
WriteTour(TourFileName, BestTour, BestCost);
}
OldOptimum = Optimum;
if (Cost < Optimum) {
if (FirstNode->InputSuc) {
Node *N = FirstNode;
while ((N = N->InputSuc = N->Suc) != FirstNode);
}
Optimum = Cost;
printff("*** New optimum = " GainFormat " ***\n\n", Optimum);
}
Time = fabs(GetTime() - LastTime);
UpdateStatistics(Cost, Time);
if (TraceLevel >= 1 && Cost != PLUS_INFINITY) {
printff("Run %d: Cost = " GainFormat, Global::msp_global->m_runId, Cost);
if (Optimum != MINUS_INFINITY && Optimum != 0)
printff(", Gap = %0.4f%%",
100.0 * (Cost - Optimum) / Optimum);
// printff(", Time = %0.2f sec. %s\n\n", Time,
// Cost < Optimum ? "<" : Cost == Optimum ? "=" : "");
printff(", Time = %0.2f sec. \n", Time);
}
if (StopAtOptimum && Cost == OldOptimum && *MaxPopulationSize >= 1) {
Runs = Run;
break;
}
if (*PopulationSize >= 2 &&
(*PopulationSize == *MaxPopulationSize ||
Run >= 2 * *MaxPopulationSize) && Run < Runs) {
Node *N;
int Parent1, Parent2;
Parent1 = LinearSelection(*PopulationSize, 1.25,this);
do
Parent2 = LinearSelection(*PopulationSize, 1.25,this);
while (Parent2 == Parent1);
ApplyCrossover(Parent1, Parent2,this);
N = FirstNode;
do {
int d = (this->*C)(N, N->Suc);
AddCandidate(N, N->Suc, d, INT_MAX);
AddCandidate(N->Suc, N, d, INT_MAX);
N = N->InitialSuc = N->Suc;
}
while (N != FirstNode);
}
mv_cost[Global::msp_global->m_runId]=Cost;
SRandom(++Seed);
}
// PrintStatistics();
freeAll();
FreeStructures();
return Return_Terminate;
}
double StatisticalProfiler::GetRawMean() const
{
UpdateStatistics();
return mRawMean;
}
int main(int argc, char *argv[])
{
GainType Cost;
double Time, LastTime = GetTime();
/* Read the specification of the problem */
if (argc >= 2)
ParameterFileName = argv[1];
ReadParameters();
MaxMatrixDimension = 10000;
ReadProblem();
if (SubproblemSize > 0) {
if (DelaunayPartitioning)
SolveDelaunaySubproblems();
else if (KarpPartitioning)
SolveKarpSubproblems();
else if (KCenterPartitioning)
SolveKCenterSubproblems();
else if (KMeansPartitioning)
SolveKMeansSubproblems();
else if (RohePartitioning)
SolveRoheSubproblems();
else if (MoorePartitioning || SierpinskiPartitioning)
SolveSFCSubproblems();
else
SolveTourSegmentSubproblems();
return EXIT_SUCCESS;
}
AllocateStructures();
CreateCandidateSet();
InitializeStatistics();
if (Norm != 0)
BestCost = PLUS_INFINITY;
else {
/* The ascent has solved the problem! */
Optimum = BestCost = (GainType) LowerBound;
UpdateStatistics(Optimum, GetTime() - LastTime);
RecordBetterTour();
RecordBestTour();
WriteTour(OutputTourFileName, BestTour, BestCost);
WriteTour(TourFileName, BestTour, BestCost);
Runs = 0;
}
/* Find a specified number (Runs) of local optima */
for (Run = 1; Run <= Runs; Run++) {
LastTime = GetTime();
Cost = FindTour(); /* using the Lin-Kernighan heuristic */
if (MaxPopulationSize > 1) {
/* Genetic algorithm */
int i;
for (i = 0; i < PopulationSize; i++) {
GainType OldCost = Cost;
Cost = MergeTourWithIndividual(i);
if (TraceLevel >= 1 && Cost < OldCost) {
printff(" Merged with %d: Cost = " GainFormat, i + 1,
Cost);
if (Optimum != MINUS_INFINITY && Optimum != 0)
printff(", Gap = %0.4f%%",
100.0 * (Cost - Optimum) / Optimum);
printff("\n");
}
}
if (!HasFitness(Cost)) {
if (PopulationSize < MaxPopulationSize) {
AddToPopulation(Cost);
if (TraceLevel >= 1)
PrintPopulation();
} else if (Cost < Fitness[PopulationSize - 1]) {
i = ReplacementIndividual(Cost);
ReplaceIndividualWithTour(i, Cost);
if (TraceLevel >= 1)
PrintPopulation();
}
}
} else if (Run > 1)
Cost = MergeBetterTourWithBestTour();
if (Cost < BestCost) {
BestCost = Cost;
RecordBetterTour();
RecordBestTour();
WriteTour(OutputTourFileName, BestTour, BestCost);
WriteTour(TourFileName, BestTour, BestCost);
}
if (Cost < Optimum) {
if (FirstNode->InputSuc) {
Node *N = FirstNode;
while ((N = N->InputSuc = N->Suc) != FirstNode);
}
Optimum = Cost;
printff("*** New optimum = " GainFormat " ***\n\n", Optimum);
}
Time = fabs(GetTime() - LastTime);
UpdateStatistics(Cost, Time);
if (TraceLevel >= 1 && Cost != PLUS_INFINITY) {
printff("Run %d: Cost = " GainFormat, Run, Cost);
if (Optimum != MINUS_INFINITY && Optimum != 0)
printff(", Gap = %0.4f%%",
100.0 * (Cost - Optimum) / Optimum);
printff(", Time = %0.2f sec. %s\n\n", Time,
Cost < Optimum ? "<" : Cost == Optimum ? "=" : "");
}
if (PopulationSize >= 2 &&
(PopulationSize == MaxPopulationSize ||
Run >= 2 * MaxPopulationSize) && Run < Runs) {
Node *N;
int Parent1, Parent2;
Parent1 = LinearSelection(PopulationSize, 1.25);
do
Parent2 = LinearSelection(PopulationSize, 1.25);
while (Parent2 == Parent1);
ApplyCrossover(Parent1, Parent2);
N = FirstNode;
do {
int d = C(N, N->Suc);
AddCandidate(N, N->Suc, d, INT_MAX);
AddCandidate(N->Suc, N, d, INT_MAX);
N = N->InitialSuc = N->Suc;
}
while (N != FirstNode);
}
SRandom(++Seed);
}
PrintStatistics();
return EXIT_SUCCESS;
}
double StatisticalProfiler::GetRawStdDev() const
{
UpdateStatistics();
return mRawStdDev;
}
int tsp_lkh()
{
GainType Cost, OldOptimum;
double Time, LastTime = GetTime();
/* Read the specification of the problem */
ReadParameters();
MaxMatrixDimension = 10000;
init();
AllocateStructures();
CreateCandidateSet();
InitializeStatistics();
BestCost = PLUS_INFINITY;
for (Run = 1; Run <= Runs; Run++) {
LastTime = GetTime();
Cost = FindTour(); /* using the Lin-Kernighan heuristic */
if (MaxPopulationSize > 1) {
/* Genetic algorithm */
int i;
for (i = 0; i < PopulationSize; i++) {
GainType OldCost = Cost;
Cost = MergeTourWithIndividual(i);
if (TraceLevel >= 1 && Cost < OldCost) {
// printff(" Merged with %d: Cost = " GainFormat, i + 1,
/// Cost);
// if (Optimum != MINUS_INFINITY && Optimum != 0)
// printff(", Gap = %0.4f%%",
// 100.0 * (Cost - Optimum) / Optimum);
//printff("\n");
}
}
if (!HasFitness(Cost)) {
if (PopulationSize < MaxPopulationSize) {
AddToPopulation(Cost);
if (TraceLevel >= 1)
PrintPopulation();
}
else if (Cost < Fitness[PopulationSize - 1]) {
i = ReplacementIndividual(Cost);
ReplaceIndividualWithTour(i, Cost);
if (TraceLevel >= 1)
PrintPopulation();
}
}
}
else if (Run > 1)
Cost = MergeTourWithBestTour();
if (Cost < BestCost) {
BestCost = Cost;
RecordBetterTour();
RecordBestTour();
}
OldOptimum = Optimum;
if (Cost < Optimum) {
if (FirstNode->InputSuc) {
Node *N = FirstNode;
while ((N = N->InputSuc = N->Suc) != FirstNode);
}
Optimum = Cost;
//printff("*** New optimum = " GainFormat " ***\n\n", Optimum);
}
Time = fabs(GetTime() - LastTime);
UpdateStatistics(Cost, Time);
/*
if (TraceLevel >= 1 && Cost != PLUS_INFINITY) {
printff("Run %d: Cost = " GainFormat, Run, Cost);
if (Optimum != MINUS_INFINITY && Optimum != 0)
printff(", Gap = %0.4f%%",
100.0 * (Cost - Optimum) / Optimum);
printff(", Time = %0.2f sec. %s\n\n", Time,
Cost < Optimum ? "<" : Cost == Optimum ? "=" : "");
}*/
if (StopAtOptimum && Cost == OldOptimum && MaxPopulationSize >= 1) {
Runs = Run;
break;
}
if (PopulationSize >= 2 &&
(PopulationSize == MaxPopulationSize ||
Run >= 2 * MaxPopulationSize) && Run < Runs) {
Node *N;
int Parent1, Parent2;
Parent1 = LinearSelection(PopulationSize, 1.25);
do
Parent2 = LinearSelection(PopulationSize, 1.25);
while (Parent2 == Parent1);
ApplyCrossover(Parent1, Parent2);
N = FirstNode;
do {
if (ProblemType != HCP && ProblemType != HPP) {
int d = C(N, N->Suc);
AddCandidate(N, N->Suc, d, INT_MAX);
AddCandidate(N->Suc, N, d, INT_MAX);
}
N = N->InitialSuc = N->Suc;
} while (N != FirstNode);
}
SRandom(++Seed);
}
// PrintStatistics();
for (int i = 0; i < TSP_N; i++)
{
TSP_RESULT[i] = BestTour[i] - 1;
}
// printf("%d -¡·",BestTour[i]-1);
return BestCost;
}