This function takes a spotoroo object to produce a summary of the
clustering results. It can be called by summary.spotoroo().
Arguments
- result
spotorooobject. A result of a call tohotspot_cluster().- cluster
Character/Integer. If "all", summarize all clusters. If an integer vector is given, summarize corresponding clusters.
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
#>
#> ────────────────────────────────────────────────────────────────────────────────
# Make a summary of all clusters
summary_spotoroo(result)
#>
#> ──────────────────────────────── SPOTOROO 0.1.4 ────────────────────────────────
#>
#> ── Calling Core Function : `summary_spotoroo()` ──
#>
#> CLUSTERS: ALL
#> OBSERVATIONS: 1070
#> FROM: 2019-12-29 13:10:00
#> TO: 2020-02-07 22:50:00
#>
#>
#> ── Clusters
#> ℹ Number of clusters: 6
#>
#> Observations in cluster
#> Min. 1st Qu. Mean 3rd Qu. Max.
#> 111.0 131.0 176.7 233.2 256.0
#> Duration of cluster (hours)
#> Min. 1st Qu. Mean 3rd Qu. Max.
#> 111.2 118.2 131.9 146.1 148.3
#>
#> ── Hot spots (excluding noise)
#> ℹ Number of hot spots: 1060
#>
#> Distance to ignition points (m)
#> Min. 1st Qu. Mean 3rd Qu. Max.
#> 0.0 2840.3 5058.2 6981.6 13452.7
#> Time from ignition (hours)
#> Min. 1st Qu. Mean 3rd Qu. Max.
#> 0.0 25.2 62.5 98.2 148.3
#>
#> ── Noise
#> ℹ Number of noise points: 10 (0.93 %)
#>
#>
#> ────────────────────────────────────────────────────────────────────────────────
# Make a summary of cluster 1 to 3
summary_spotoroo(result, 1:3)
#>
#> ──────────────────────────────── SPOTOROO 0.1.4 ────────────────────────────────
#>
#> ── Calling Core Function : `summary_spotoroo()` ──
#>
#> CLUSTERS: 1 2 3
#> OBSERVATIONS: 447
#> FROM: 2019-12-29 13:10:00
#> TO: 2020-02-01 05:20:00
#>
#>
#> ── Clusters
#> ℹ Number of clusters: 3
#>
#> Observations in cluster
#> Min. 1st Qu. Mean 3rd Qu. Max.
#> 126.0 136.0 145.7 155.5 165.0
#> Duration of cluster (hours)
#> Min. 1st Qu. Mean 3rd Qu. Max.
#> 116.2 131.2 136.9 147.3 148.3
#>
#> ── Hot spots (excluding noise)
#> ℹ Number of hot spots: 437
#>
#> Distance to ignition points (m)
#> Min. 1st Qu. Mean 3rd Qu. Max.
#> 0.0 2222.7 4788.2 6944.3 13452.7
#> Time from ignition (hours)
#> Min. 1st Qu. Mean 3rd Qu. Max.
#> 0.0 14.0 61.3 97.5 148.3
#>
#> ────────────────────────────────────────────────────────────────────────────────
# }