CV_IMPL void
cvMerge( const void* srcarr0, const void* srcarr1, const void* srcarr2,
const void* srcarr3, void* dstarr )
{
const void* sptrs[] = { srcarr0, srcarr1, srcarr2, srcarr3 };
cv::Mat dst = cv::cvarrToMat(dstarr);
int i, j, nz = 0;
for( i = 0; i < 4; i++ )
nz += sptrs[i] != 0;
CV_Assert( nz > 0 );
std::vector<cv::Mat> svec(nz);
std::vector<int> pairs(nz*2);
for( i = j = 0; i < 4; i++ )
{
if( sptrs[i] != 0 )
{
svec[j] = cv::cvarrToMat(sptrs[i]);
CV_Assert( svec[j].size == dst.size &&
svec[j].depth() == dst.depth() &&
svec[j].channels() == 1 && i < dst.channels() );
pairs[j*2] = j;
pairs[j*2+1] = i;
j++;
}
}
if( nz == dst.channels() )
cv::merge( svec, dst );
else
{
cv::mixChannels( &svec[0], nz, &dst, 1, &pairs[0], nz );
}
}
void ToolTip::SetTool(Tool * tool, LPRECT rect)
{
TOOLINFO ti;
LRESULT update;
ti.cbSize = sizeof(TOOLINFO);
ti.hwnd = m_hOwnerWnd;
ti.uId = (UINT_PTR)tool;
ti.lpszText = NULL;
update = SendMessage(m_hWnd, TTM_GETTOOLINFO, 0, (LPARAM) (LPTOOLINFO) &ti);
ti.uFlags = TTF_SUBCLASS;
ti.hinst = vdWindow;
std::vector<TCHAR> svec(
tool->GetText(),
tool->GetText() + _tcslen(tool->GetText()) + 1);
ti.lpszText = &(svec[0]);
if (rect)
ti.rect = *rect;
else
tool->GetRect(&ti.rect);
if (update)
SendMessage(m_hWnd, TTM_SETTOOLINFO, 0, (LPARAM) (LPTOOLINFO) &ti);
else
SendMessage(m_hWnd, TTM_ADDTOOL, 0, (LPARAM) (LPTOOLINFO) &ti);
}
int main(int argc, char **argv) {
// Load the model from the file given as first non-option argument.
// Normalization constant Z, will be calculated (takes long) if not provided.
double Z = 0;
int opt;
while((opt = getopt(argc, argv, "z:")) != -1) {
switch(opt) {
case 'z': Z = atof(optarg); break;
default: die("%s", usage);
}
}
if (optind == argc) die("%s", usage);
msg("Loading model from %s.", argv[optind]);
if (Z > 0) msg("Will use fixed Z of %g.", Z);
else msg("Will calculate Z, this may take some time...");
model_t m = load_model(argv[optind], Z);
// Read data from stdin and calculate logL
char **toks = _d_calloc(m->ntok, sizeof(char *));
svec_t *x = _d_calloc(m->ntok, sizeof(svec_t));
double *logZ = _d_calloc(m->ntok, sizeof(double));
for (size_t i = 1; i < m->ntok; i++) {
logZ[i] = log(m->z[i]);
}
double logL = 0;
size_t nline = 0;
msg("Reading data from stdin (each dot = 1M lines)...");
forline (line, NULL) {
if ((++nline & ((1<<20)-1)) == 0) fputc('.', stderr);
line[strlen(line)-1] = 0; // chop newline
size_t ntok = split(line, "\t", toks, m->ntok);
if (ntok != m->ntok) die("Wrong number of columns.");
for (size_t i = 0; i < m->ntok; i++) {
if (*toks[i] == '\0') {
x[i] = NULL;
} else {
x[i] = svec(m->v[i], toks[i]);
assert(x[i]->vec != NULL && x[i]->cnt > 0);
}
}
assert(x[0] != NULL);
double logx = log(((double) x[0]->cnt) / m->n[0]);
for (size_t i = 1; i < m->ntok; i++) {
if (x[i] == NULL) continue;
double logy = log(((double) x[i]->cnt) / m->n[i]);
logL += logx + logy - logZ[i] - d2(x[0]->vec, x[i]->vec, m->ndim);
}
}
fputc('\n', stderr);
logL /= nline;
_d_free(toks); _d_free(x); _d_free(logZ);
free_model(m);
msg("nlines=%zu avg-logL=%g", nline, logL);
}
int main(int argc, char const *argv[])
{
std::vector<int> ivec(9, 8);
std::vector<double> dvec(8, 9.9);
std::vector<char> cvec(7, 'h');
std::cout << count(ivec, 8) << std::endl;
std::cout << count(dvec, 9.9) << std::endl;
std::cout << count(cvec, 'h') << std::endl;
std::vector<std::string> svec(6, "hey");
std::cout << count(svec, std::string("hey")) << std::endl;
return 0;
}
model_t load_model(char *modelfile, double Z) {
model_t m = _d_calloc(1, sizeof(struct model_s));
char **toks = NULL; // array to tokenize each line
size_t len1 = 0; // length of the first line (used as upper bound on number of toks)
// msg("Reading %s...", modelfile);
forline (line, modelfile) {
line[strlen(line)-1] = 0; // chop newline
if (len1 == 0) {
len1 = strlen(line);
toks = _d_calloc(len1, sizeof(char *));
}
size_t n = split(line, "\t", toks, len1);
if (m->ndim == 0) {
m->ndim = n - 2;
}
assert(n == m->ndim + 2);
char *ptr = NULL;
long int index = strtol(toks[0], &ptr, 10);
assert(ptr > toks[0] && *ptr == ':' && index >= 0);
if (index >= m->ntok) {
size_t oldn = m->ntok;
m->ntok = index + 1;
m->v = _d_realloc(m->v, m->ntok * sizeof(darr_t));
m->n = _d_realloc(m->n, m->ntok * sizeof(size_t));
m->z = _d_realloc(m->z, m->ntok * sizeof(double));
for (int i = oldn; i < m->ntok; i++) {
m->v[i] = darr(0, svec_t);
m->n[i] = 0;
m->z[i] = 0;
}
}
char *token = ptr+1;
svec_t s = svec(m->v[index], token);
assert(!strcmp(s->key, token));
long int count = strtol(toks[1], &ptr, 10);
assert(ptr > toks[1] && *ptr == 0 && count > 0);
assert(s->cnt == 0);
s->cnt = count;
m->n[index] += count;
assert(s->vec == NULL);
s->vec = _d_calloc(m->ndim, sizeof(float));
for (size_t i = 0; i < m->ndim; i++) {
s->vec[i] = strtof(toks[i+2], &ptr);
assert(ptr > toks[i+2] && *ptr == 0);
}
}
void benchmark_convert_type ()
{
const size_t size = 10000000;
const S testval(1.0);
std::vector<S> svec (size, testval);
std::vector<D> dvec (size);
std::cout << Strutil::format("Benchmark conversion of %6s -> %6s : ",
TypeDesc(BaseTypeFromC<S>::value),
TypeDesc(BaseTypeFromC<D>::value));
float time = time_trial (bind (do_convert_type<S,D>, OIIO::cref(svec), OIIO::ref(dvec)),
ntrials, iterations) / iterations;
std::cout << Strutil::format ("%7.1f Mvals/sec", (size/1.0e6)/time) << std::endl;
D r = convert_type<S,D>(testval);
OIIO_CHECK_EQUAL (dvec[size-1], r);
}
void TrayIcon::OnContextMenu()
{
HMENU hMenu, hmenuTrackPopup;
POINT pt;
HRESULT res;
int i;
Desktop * desk;
//Get the "base" menu
hMenu = Locale::GetInstance().LoadMenu(IDC_VIRTUALDIMENSION);
if (hMenu == NULL)
return;
hmenuTrackPopup = GetSubMenu(hMenu, 0);
//Append the list of desktops
InsertMenu(hmenuTrackPopup, 0, MF_BYPOSITION | MF_SEPARATOR, 0, 0);
i = 0;
for( desk = deskMan->GetFirstDesktop();
desk != NULL;
desk = deskMan->GetNextDesktop())
{
MENUITEMINFO mii;
mii.cbSize = sizeof(mii);
mii.fMask = MIIM_STATE | MIIM_STRING | MIIM_ID | MIIM_DATA;
if (desk->IsActive())
mii.fState = MFS_CHECKED;
else
mii.fState = MFS_UNCHECKED;
mii.dwItemData = (DWORD)desk;
std::vector<TCHAR> svec(
desk->GetText(),
desk->GetText() + _tcslen(desk->GetText()) + 1);
mii.dwTypeData = &(svec[0]);
mii.cch = (UINT)_tcslen(mii.dwTypeData);
mii.wID = WM_USER + i++;
InsertMenuItem(hmenuTrackPopup, 0, TRUE, &mii);
}
//And show the menu
GetCursorPos(&pt);
SetForegroundWindow(m_hWnd);
res = TrackPopupMenu(hmenuTrackPopup, TPM_RIGHTBUTTON | TPM_RETURNCMD, pt.x, pt.y, 0, m_hWnd, NULL);
//Process the resulting message
if (res >= WM_USER)
{
Desktop * desk;
MENUITEMINFO mii;
mii.cbSize = sizeof(mii);
mii.fMask = MIIM_DATA;
GetMenuItemInfo(hmenuTrackPopup, res, FALSE, &mii);
desk = (Desktop*)mii.dwItemData;
deskMan->SwitchToDesktop(desk);
InvalidateRect(m_hWnd, NULL, TRUE);
}
else
PostMessage(m_hWnd, WM_COMMAND, res, 0);
//Do not forget to destroy the menu
DestroyMenu(hMenu);
}
/** Read examples into memory
*/
void CSeqFeature::LoadFeatures()
{
unsigned int tmpFidx = 0;
Scalar tmpFval = 0;
unsigned int featureCnt = 0;
unsigned int seqNum = 0;
unsigned int phiNum = 0;
unsigned int posNum1 = 0, posNum2 = 0;
std::string line = "";
std::string token = "";
std::ifstream featureFp;
featureFp.open(featureFile.c_str());
if(!featureFp.good())
{
string msg = "Cannot open feature file <" + featureFile + ">!";
throw CBMRMException(msg, "CSeqFeature::ScanFeatureFile()");
}
// read header information
int headerInfoCnt = 3; // min duration, max duration, feature dimension
do {
getline(featureFp, line);
trim(line);
if(IsBlankLine(line)) continue; // blank line
if(line[0] == '#') continue; // comment line
if(sscanf(line.c_str(),"maxDuration:%d",&maxDuration)==1) headerInfoCnt--;
if(sscanf(line.c_str(),"minDuration:%d",&minDuration)==1) headerInfoCnt--;
if(sscanf(line.c_str(),"globalFeatureDim:%d",&featureDimension)==1) headerInfoCnt--;
} while(!featureFp.eof() && (headerInfoCnt != 0));
assert(maxDuration >= minDuration);
assert(featureDimension < (1<<30)); // featureDimension is normally less then 1 billion
if(featureFp.eof())
throw CBMRMException("Feature file does not contain valid examples","CSeqFeature::LoadFeatures()");
// read sequences
nnz = 0;
while(!featureFp.eof())
{
// read sequence number
do {
getline(featureFp, line);
trim(line);
if(IsBlankLine(line)) continue; // blank line
if(line[0] == '#') continue; // comment line
if(sscanf(line.c_str(),"sequence:%d",&seqNum)==1) break;
} while(!featureFp.eof());
if(featureFp.eof())
throw CBMRMException("Feature file does not contain valid phi:*","CSeqFeature::LoadFeatures()");
// read phi:1 tag
phiNum = 0;
do {
getline(featureFp, line);
trim(line);
if(IsBlankLine(line)) continue; // blank line
if(line[0] == '#') continue; // comment line
if(sscanf(line.c_str(),"phi:%d",&phiNum)==1) break;
} while(!featureFp.eof());
if(featureFp.eof() || (phiNum != 1))
throw CBMRMException("Feature file does not contain valid phi:1","CSeqFeature::LoadFeatures()");
// read phi:1 sparse vectors
do {
getline(featureFp, line);
trim(line);
if(IsBlankLine(line)) continue; // blank line
if(line[0] == '#') continue; // comment line
if(sscanf(line.c_str(),"phi:%d",&phiNum) == 1)
break;
istringstream iss(line);
iss >> token;
if((sscanf(token.c_str(),"pos:%d",&posNum1) != 1))
throw CBMRMException("Feature file does not contain valid pos tag in phi:1","CSeqFeature::LoadFeatures()");
TheMatrix svec(1,featureDimension,SML::SPARSE);
featureCnt = 0;
while(!iss.eof())
{
iss >> token;
if(sscanf(token.c_str(),svec_feature_index_and_value_format.c_str(),&tmpFidx, &tmpFval) != 2)
{
ostringstream msg;
msg << "Invalid #" << featureCnt + 1 << " sparse vector element in phi:"<< phiNum << " seq:" << seqNum << " pos:" << posNum1;
throw CBMRMException(msg.str(),"CSeqFeature::LoadFeatures()");
}
svec.Set(0,tmpFidx,tmpFval);
nnz++;
}
if(featureCnt == 0)
throw CBMRMException("Feature file does not contain valid phi:2 sparse vector","CSeqFeature::LoadFeatures()");
phi_1.push_back(svec);
} while(!featureFp.eof());
if(phi_1.size() < 1)
throw CBMRMException("Feature file does not contain valid phi:1","CSeqFeature::LoadFeatures()");
numOfSeq = phi_1.size();
if(featureFp.eof() || (phiNum != 2))
throw CBMRMException("Feature file does not contain valid phi:2","CSeqFeature::LoadFeatures()");
// read phi:2 sparse vectors
unsigned int prevPosNum1 = 0, prevPosNum2 = 0;
vector<TheMatrix> tmp_phi_2_svecs;
featureCnt = 0;
do {
getline(featureFp, line);
trim(line);
if(IsBlankLine(line)) continue; // blank line
if(line[0] == '#') continue; // comment line
if((sscanf(line.c_str(),"phi:%d",&phiNum) == 1))
break;
istringstream iss(line);
iss >> token;
if((sscanf(token.c_str(),"pos:%d,%d",&posNum1,&posNum2) != 2))
throw CBMRMException("Feature file does not containt valid pos tag in phi:2","CSeqFeature::LoadFeatures()");
if(prevPosNum2 >= posNum2)
{
ostringstream msg;
msg << "previous posNum2 must be > current posNum2 in phi:2 (phi:2 pos:" << posNum1 << "," << posNum2;
throw CBMRMException(msg.str(),"CSeqFeature::LoadFeatures()");
}
if(prevPosNum1 >= posNum1)
{
ostringstream msg;
msg << "previous posNum1 must be > current posNum1 in phi:2 (phi:2 pos:" << posNum1 << "," << posNum2;
throw CBMRMException(msg.str(),"CSeqFeature::LoadFeatures()");
}
if(posNum1 != prevPosNum1)
{
phi_2.push_back(tmp_phi_2_svecs);
tmp_phi_2_svecs.clear();
}
TheMatrix svec(1,featureDimension,SML::SPARSE);
featureCnt = 0;
while(!iss.eof())
{
iss >> token;
if(sscanf(token.c_str(),svec_feature_index_and_value_format.c_str(),&tmpFidx, &tmpFval) != 2)
{
ostringstream msg;
msg << "Invalid #" << featureCnt + 1 << " sparse vector element in phi:"<< phiNum << " seq:" << seqNum << " pos:" << posNum1;
throw CBMRMException(msg.str(),"CSeqFeature::LoadFeatures()");
}
svec.Set(0,tmpFidx,tmpFval);
nnz++;
}
if(featureCnt == 0)
throw CBMRMException("Feature file does not containt valid phi:2 sparse vector","CSeqFeature::LoadFeatures()");
tmp_phi_2_svecs.push_back(svec);
} while(!featureFp.eof());
if(phi_2.size() < 1)
throw CBMRMException("Feature file does not contain phi:2","CSeqFeature::LoadFeatures()");
}
// data matrix density
density = ((double)nnz/featureDimension)/numOfSeq;
featureFp.close();
}
