Assigns a distance measure to the `MapperRef`

instance to use in the clustering algorithm.

$use_distance_measure(measure, ...)

`measure`

The distance measure to use (string).

`...`

Extra parameters passed to the distance function. See details.

Unless the `clustering_algorithm`

has been replaced by the user,
by default, Mapper requires a notion of distance between objects to be defined in creating the vertices of the construction.

The distance function is determined based on the supplied `measure`

. `measure`

must be one of:

["euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski"]

or, if the proxy and `parallelDist`

packages are installed, any name in `proxy::pr_DB$get_entry_names()`

.

Additional parameters passed via `...`

are passed to either `dist`

(or
`parallelDist`

if installed).

The mapper instance, with the measure field assigned.

data(noisy_circle) m <- MapperRef$new(noisy_circle) m$use_filter(noisy_circle[,1]) m$use_cover("fixed interval", number_intervals = 5, percent_overlap = 25) ## Constructs clusters with euclidean metric (default) m$use_distance_measure("euclidean") m$construct_pullback() ## Constructs clusters with p-norm (p = 1) m$use_distance_measure("Minkowski", p = 1L) m$construct_pullback()# NOT RUN { ## To see list of available measures, use: proxy::pr_DB$get_entry_names() # }