map_clusters: Map Clusters

In gsClusterDetect: Utilities for Geo-Spatial Cluster Detection and Significance Classification

Map Clusters

Description

Utility for mapping clusters. The function ingest an object 'cl' as returned by find_clusters() and a shape file provisioned by the caller, along with a string name of a column in the shape file that uniquely defines the locations. Note that this column will be used to merge with the clusters and therefore must aligned with the labels in 'cl' cluster locations. The function returns a basic plotly map object that can be further modified by the user

Usage

map_clusters(
  cl,
  s,
  s_id,
  label_id = NULL,
  label = c("none", "cluster_centers", "cluster_locations", "all"),
  engine = c("plotly", "ggplot"),
  point_crs = NULL
)

Arguments

cl	an object of class "clusters" as returned by find_clusters()
s	shape file; must be of class sf
s_id	string unique identifier of 's'
label_id	string column of 's' that indicates display label for the row in 's' (default is NULL)
label	for engine = "ggplot", indicates which locations should receive visible text labels. Valid choices are "none", "cluster_centers", "cluster_locations", and "all". The default is "none". This argument is ignored when engine = "plotly" because plotly maps always include hover labels for all locations.
engine	string label to indicate plotting engine; either "plotly" (default) or "ggplot"
point_crs	optional coordinate reference system used to compute representative points when 's' is in longitude/latitude coordinates. If 'NULL', EPSG:3857 is used as a general-purpose fallback. The resulting points are transformed back to the CRS of 's' before plotting

Examples

if (
  requireNamespace("tigris", quietly = TRUE) &&
    requireNamespace("ggplot2", quietly = TRUE)
) {
  # get some data
  dd <- example_count_data[, max(date)]
  # get a distance matrix
  dm <- create_dist_list("county", 50, st = "OH")
  # find the clusters
  cl <- find_clusters(
    cases = example_count_data,
    detect_date = dd,
    distance_matrix = dm
  )
  # get shape file
  ohio_shape <- tigris::counties("OH", cb = TRUE, class = "sf")

  # prepare map data
  md <- map_clusters(cl, ohio_shape, "GEOID")
}

gsClusterDetect documentation built on July 27, 2026, 5:09 p.m.