int omxExpectation::numSummaryStats()
{
omxMatrix *cov = getComponent("cov");
if (!cov) {
Rf_error("%s::numSummaryStats is not implemented (for object '%s')", expType, name);
}
omxMatrix *mean = getComponent("means");
int count = 0;
omxMatrix *slope = getComponent("slope");
if (slope) count += slope->rows * slope->cols;
auto &ti = getThresholdInfo();
if (ti.size() == 0) {
// all continuous
count += triangleLoc1(cov->rows);
if (mean) count += cov->rows;
return count;
}
count += triangleLoc1(cov->rows - 1); // covariances
for (auto &th : ti) {
// mean + variance
count += th.numThresholds? th.numThresholds : 2;
}
return count;
}
void QsfpModule::getTransceiverInfo(TransceiverInfo &info) {
lock_guard<std::mutex> g(qsfpModuleMutex_);
info.present = present_;
info.transceiver = type();
info.port = qsfpImpl_->getNum();
if (!cacheIsValid()) {
return;
}
if (getSensorInfo(info.sensor)) {
info.__isset.sensor = true;
}
if (getVendorInfo(info.vendor)) {
info.__isset.vendor = true;
}
if (getCableInfo(info.cable)) {
info.__isset.cable = true;
}
if (getThresholdInfo(info.thresholds)) {
info.__isset.thresholds = true;
}
for (int i = 0; i < CHANNEL_COUNT; i++) {
Channel chan;
chan.channel = i;
info.channels.push_back(chan);
}
if (getSensorsPerChanInfo(info.channels)) {
info.__isset.channels = true;
} else {
info.channels.clear();
}
}
void omxExpectation::asVector1(FitContext *fc, int row, Eigen::Ref<Eigen::VectorXd> out)
{
loadDefVars(row);
omxExpectationCompute(fc, this, 0);
omxMatrix *cov = getComponent("cov");
if (!cov) {
Rf_error("%s::asVector is not implemented (for object '%s')", expType, name);
}
normalToStdVector(cov, getComponent("means"), getComponent("slope"), thresholdsMat,
numOrdinal, getThresholdInfo(), out);
}
