classifyModel: Classify clouds in a model

In montesmariana/semcloud: Post-processing of token-level clouds

Classify clouds in a model

Description

Classify clouds in a model

Usage

classifyModel(mdata, mname, ttmx_dir, suffix = ".ttmx.dist.pac", k = 8)

Arguments

mdata	Data of a model, as given by summarizeHDBSCAN.
mname	Name of a model; the name of mdata.
ttmx_dir	Directory where the token-level distance matrices are stored.
suffix	Suffix of the file names for the token-level distance matrices; the function assumes that the name of the file is the name of the medoid plus the suffix.
k	Number of nearest neighbors for clusterDistance and clusterSeparation.

Value

A table with one row per cluster in the model, the columns created by clusterSeparation, clusterHDBSCAN and clusterDistance and the classification of each cluster based on the Nephological Shapes from \insertCitemontes_2021;textualsemcloud (see Chapter 5 for a full description and examples).

References

\insertAllCited

Examples

## Not run: 
purrr::imap_dfr(models$medoidCoords, classifyModel, ttmx_dir = 'path/to/dir')

## End(Not run)

montesmariana/semcloud documentation built on April 15, 2022, 6:57 a.m.