BioGSP (version 1.0.0)

visualize_sgwt_kernels: Visualize SGWT kernels and scaling functions

Description

Visualize the scaling function and wavelet kernels used in SGWT based on the eigenvalue spectrum and selected parameters

Usage

visualize_sgwt_kernels(
  eigenvalues,
  scales = NULL,
  J = 4,
  scaling_factor = 2,
  kernel_type = "heat",
  lmax = NULL,
  eigenvalue_range = NULL,
  resolution = 1000
)

Value

List containing the filter visualization plot and filter values

Arguments

eigenvalues

Vector of eigenvalues from graph Laplacian

scales

Vector of scales for the wavelets (if NULL, auto-generated)

J

Number of scales to generate if scales is NULL (default: 4)

scaling_factor

Scaling factor between consecutive scales (default: 2)

kernel_type

Type of wavelet kernel ("mexican_hat" or "meyer", default: "mexican_hat")

lmax

Maximum eigenvalue (optional, computed if NULL)

eigenvalue_range

Range of eigenvalues to plot (default: full range)

resolution

Number of points for smooth curve plotting (default: 1000)

Examples

# \donttest{
# Generate some example eigenvalues
eigenvals <- seq(0, 2, length.out = 100)

# Visualize kernels with specific parameters
viz_result <- visualize_sgwt_kernels(
  eigenvalues = eigenvals,
  J = 4,
  scaling_factor = 2,
  kernel_type = "heat"
)
print(viz_result$plot)
# }