# heat-diffusion-methods: Graph diffusion using a heat diffusion process on a Laplacian... In diffusr: Network Diffusion Algorithms

## Description

An amount of starting heat gets distribution using the Laplacian matrix of a graph. Every iteration (or time interval) `t` heat streams from the starting nodes into surrounding nodes.

## Usage

 ```1 2 3 4 5 6 7``` ```heat.diffusion(h0, graph, t = 0.5, ...) ## S4 method for signature 'numeric,matrix' heat.diffusion(h0, graph, t = 0.5, ...) ## S4 method for signature 'matrix,matrix' heat.diffusion(h0, graph, t = 0.5, ...) ```

## Arguments

 `h0` an `n x p`-dimensional numeric non-negative vector/matrix of starting temperatures `graph` an (`n x n`)-dimensional numeric non-negative adjacence matrix representing the graph `t` time point when heat is measured `...` additional parameters

## Value

returns the heat on every node as numeric vector

## Examples

 ```1 2 3 4 5 6 7 8``` ```# count of nodes n <- 5 # starting distribution (has to sum to one) h0 <- as.vector(rmultinom(1, 1, prob=rep(.2, n))) # adjacency matrix (either normalized or not) graph <- matrix(abs(rnorm(n*n)), n, n) # computation of stationary distribution ht <- heat.diffusion(h0, graph) ```

### Example output

```setting diag of graph to zero
```

diffusr documentation built on May 2, 2019, 3:42 a.m.