sgwt_get_kernels

Returns a pair of functions implementing the scaling (low-pass)
and wavelet (band-pass) kernels for a given kernel family. This enforces
consistency: a single kernel_type defines both filters.

Implementation of Graph Signal Processing (GSP) methods including Spectral
Graph Wavelet Transform (SGWT) for analyzing spatial patterns in biological data.
Based on Hammond, Vandergheynst, and Gribonval (2011) <doi:10.1016/j.acha.2010.04.005>. Provides tools for multi-scale analysis of biology spatial signals, including forward and inverse transforms, energy analysis, and visualization functions tailored for biological applications. Biological application example is on Stephanie, Yao, Yuzhou (2024) <doi:10.1101/2024.12.20.629650>.

Yuzhou Chang

BioGSP

Biological Graph Signal Processing for Spatial Data Analysis

sgwt_get_kernels function

<dl><dt>kernel_type</dt>
<dd>Kernel family name ("mexican_hat", "meyer", or "heat")</dd></dl>

Arguments

Get a unified kernel family (low-pass and band-pass) by kernel_type — sgwt_get_kernels

<dl>

<dt>kernel_type</dt>
<dd>Kernel family name ("mexican_hat", "meyer", or "heat")</dd>

</dl>

sgwt_get_kernels: Get a unified kernel family (low-pass and band-pass) by kernel_type

Description

Usage

Value

Arguments