74 const Eigen::Index n = this->
epoch.cols();
75 const double step = n > 1 ? (
static_cast<double>(this->
tmax) - this->
tmin) /
static_cast<double>(n - 1) : 1.0;
76 const double first = std::round(this->
tmin / step);
78 for (Eigen::Index i = 0; i < n; ++i)
79 times(i) =
static_cast<float>((first +
static_cast<double>(i)) * step);
87 if (sel.cols() == 0) {
88 qWarning(
"MNEEpochData::pick_channels - Warning : No channels were provided.\n");
93 MatrixXd selBlock(1, 1);
95 if (selBlock.rows() != sel.cols() || selBlock.cols() !=
epoch.cols()) {
96 selBlock.resize(sel.cols(),
epoch.cols());
99 for (qint32 l = 0; l < sel.cols(); ++l) {
100 if (sel(l) <=
epoch.rows()) {
101 selBlock.row(l) =
epoch.row(sel(0, l));
103 qWarning(
"FiffEvoked::pick_channels - Warning : Selected channel index out of bound.\n");
General numerical helpers: GCD, log2, histogram binning, baseline rescaling, sparsity tests.
Single epoch (one trial slice of preprocessed sensor data) with timing and rejection metadata.
Core MNE data structures (source spaces, source estimates, hemispheres).
Shared utilities (I/O helpers, spectral analysis, layout management, warp algorithms).
static Eigen::MatrixXd rescale(const Eigen::MatrixXd &data, const Eigen::RowVectorXf ×, const QPair< float, float > &baseline, QString mode)
void pick_channels(const Eigen::RowVectorXi &sel)
void applyBaselineCorrection(const QPair< float, float > &baseline)
FIFFLIB::fiff_int_t eventSample
FIFFLIB::fiff_int_t event