igft: Inverse Graph Fourier Transform

In BioGSP: Biological Graph Signal Processing for Spatial Data Analysis

Inverse Graph Fourier Transform

Description

Compute the Inverse Graph Fourier Transform (IGFT) of spectral coefficients using Laplacian eigenvectors.

Usage

igft(fourier_coeffs, U)

Arguments

fourier_coeffs	Input Fourier coefficients (vector or matrix)
U	Matrix of eigenvectors (dense matrix preferred)

Value

Reconstructed signal in the vertex domain (vector or matrix)

Examples

# Create example data
data <- data.frame(x = runif(50), y = runif(50), signal = rnorm(50))
SG <- initSGWT(data, signals = "signal")
SG <- runSpecGraph(SG, k = 10)
eigenvectors <- SG$Graph$eigenvectors

# Single signal - use GFT to get Fourier coefficients
fourier_coeffs <- gft(data$signal, eigenvectors)
signal_reconstructed <- igft(fourier_coeffs, eigenvectors)

# Multiple signals (batch processing)
signals_matrix <- cbind(data$signal, data$signal * 2)
fourier_coeffs_matrix <- gft(signals_matrix, eigenvectors)
signals_reconstructed <- igft(fourier_coeffs_matrix, eigenvectors)

BioGSP documentation built on Feb. 2, 2026, 5:06 p.m.