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Normalize an HRF Object with a Fixed Scale

Source: R/hrf_decorators.R
normalize_hrf.Rd

Creates an HRF whose evaluations are divided by constants computed once on a fixed reference grid. The resulting scale therefore does not depend on the time points supplied in later calls.

Usage

normalize_hrf(hrf, mode)

Arguments

hrf

An object of class `HRF`.

mode

Normalization convention: `"spm"` divides by the sum of the canonical basis on the 1,600-point 0–32 second Nilearn reference grid; `"unit_peak"` divides every basis by the canonical basis peak; `"unit_integral"` divides every basis by the canonical basis trapezoidal integral; `"unit_peak_per_basis"` scales each basis independently; and `"none"` returns `hrf` unchanged.

Value

An `HRF` object with fixed normalization.

Details

For multi-basis HRFs, `"spm"`, `"unit_peak"`, and `"unit_integral"` use one scalar computed from the first (canonical) column and apply it uniformly. This preserves the relative scale of derivative bases. Only `"unit_peak_per_basis"` rescales columns independently.

See also

Other HRF_decorator_functions: block_hrf(), lag_hrf(), normalise_hrf()

Examples

spm_scaled <- normalize_hrf(HRF_SPMG1, "spm")
reference_grid <- seq(0, 32, length.out = 1600)
sum(spm_scaled(reference_grid))
#> [1] 1

peak_scaled <- normalize_hrf(HRF_SPMG2, "unit_peak")
max(abs(peak_scaled(seq(0, 24, by = 0.01))[, 1]))
#> [1] 1