importFrom(utils, tail) to avoid R CMD
check NOTEs.is.symbol() before as.character()
in internal eco atlas extraction to prevent errors on non-symbol
inputs.hrf_bspline() support handling so values for
t > span (and t < 0) are zeroed instead
of wrapping to onset-like values.block_hrf() block integration to include
quadrature step-size scaling, making amplitudes stable across
precision.hrf_sine() and hrf_fourier() to
clamp support to [0, span] and return zero outside the
modeled window.normalise_hrf() to use fixed normalization
constants computed on the HRF support, avoiding data-dependent scaling
across evaluation grids.evaluate.HRF() block-duration summation to use
the same weighted integration scheme as block_hrf().evaluate.Reg(normalize = TRUE) to normalize
regressor outputs consistently across evaluation methods, including
single-trial regressors with different durations.block_hrf(summate = FALSE) to return normalized
block integration (for both single- and multi-basis HRFs) instead of the
legacy pointwise-maximum behavior.hrf_boxcar() function for simple boxcar (step
function) HRFs with optional normalization.hrf_weighted() function for arbitrary
weighted-window HRFs with constant or linear interpolation.regressor() now accepts a list of HRF objects for
trial-varying HRF designs.plot.Reg() method for visualizing regressor
objects.plot_regressors() for comparing multiple regressors
on one plot (ggplot2 or base R).plot_hrfs() for comparing multiple HRF shapes.print.HRF() method for concise HRF summaries.as_hrf() where parameters stored
in the params attribute were never used at evaluation time.
The fix creates a closure that properly captures and applies parameters
during evaluation.
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