ham_distance {CommKern} | R Documentation |

## Hamiltonian distance matrix creation

### Description

Description of the Hamiltonian distance matrix creation function.

### Usage

```
ham_distance(hamil_df)
```

### Arguments

`hamil_df` |
a data frame containing two columns, one for network ID and another containing Hamiltonian values |

### Details

This function creates a distance matrix using the Hamiltonian output values from a community detection algorithm that implements a Hamiltonian value, such as the hierarchical multimodal spinglass algorithm. To ensure a positive, semi-definite matrix (as required for the kernel function), the absolute difference between Hamiltonian values is calculated.

The function returns an m x m matrix (where m is the number of networks) to be used as input for the kernel function.

### Value

the Hamiltonian distance matrix to be used as input for the kernel function

### See Also

### Examples

```
hamil_df <- data.frame(id = seq(1:8),
ham = c(-160.5375, -167.8426, -121.7128, -155.7245,
-113.9834, -112.5262, -117.9724, -171.374))
ham_distance(hamil_df)
```

[Package

*CommKern*version 1.0.1 Index]