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Default method of plotting the clustering results

Source: R/plot_def.R
plot_def.Rd

This function plots the clustering result spatially as a scatter plot.

Usage

plot_def(
  result,
  cluster = "all",
  hotspot = TRUE,
  noise = FALSE,
  ignition = TRUE,
  from = NULL,
  to = NULL,
  bg = NULL
)

Arguments

result

spotoroo object. A result of a call to hotspot_cluster().

cluster

Character/Integer. If "all", plot all clusters. If an integer vector is given, plot corresponding clusters.

hotspot

Logical. If TRUE, plot the hot spots.

noise

Logical. If TRUE, plot the noise points.

ignition

Logical. If TRUE, plot the ignition points.

from

OPTIONAL. Date/Datetime/Numeric. Start time. The data type needs to be the same as the provided observed time.

to

OPTIONAL. Date/Datetime/Numeric. End time. The data type needs to be the same as the provided observed time.

bg

OPTIONAL. ggplot object. If specified, plot onto this object.

Value

A ggplot object. The plot of the clustering results.

Examples

# \donttest{

  # Time consuming functions (>5 seconds)


  # Get clustering results
  result <- hotspot_cluster(hotspots,
                          lon = "lon",
                          lat = "lat",
                          obsTime = "obsTime",
                          activeTime = 24,
                          adjDist = 3000,
                          minPts = 4,
                          minTime = 3,
                          ignitionCenter = "mean",
                          timeUnit = "h",
                          timeStep = 1)
#> 
#> ──────────────────────────────── SPOTOROO 0.1.4 ────────────────────────────────
#> 
#> ── Calling Core Function : `hotspot_cluster()` ──
#> 
#> ── "1" time index = 1 hour 
#> ✔ Transform observed time → time indexes
#> ℹ 970 time indexes found
#> 
#> ── activeTime = 24 time indexes | adjDist = 3000 meters 
#> ✔ Cluster
#> ℹ 16 clusters found (including noise)
#> 
#> ── minPts = 4 hot spots | minTime = 3 time indexes 
#> ✔ Handle noise
#> ℹ 6 clusters left
#> ℹ noise proportion : 0.935 %
#> 
#> ── ignitionCenter = "mean" 
#> ✔ Compute ignition points for clusters
#> ℹ average hot spots : 176.7
#> ℹ average duration : 131.9 hours
#> 
#> ── Time taken = 0 mins 1 sec for 1070 hot spots 
#> ℹ 0.001 secs per hot spot
#> 
#> ────────────────────────────────────────────────────────────────────────────────

  # Plot a subset of clusters
  plot_def(result, cluster = 1:3)


  # Plot all clusters
  plot_def(result, cluster = "all")

# }