dormancy_scout: Scout for Dormant Pattern Regions in Data

In dormancy: Detection and Analysis of Dormant Patterns in Data

Scout for Dormant Pattern Regions in Data

Description

Systematically scans the data space to identify regions where dormant patterns might emerge. Unlike dormancy_detect which identifies specific patterns, dormancy_scout maps the "terrain" of dormancy potential.

Usage

dormancy_scout(
  data,
  grid_resolution = 20,
  scout_method = "density",
  return_map = TRUE,
  verbose = FALSE
)

Arguments

data	A numeric matrix or data frame.
grid_resolution	Integer. Resolution of the scanning grid. Higher values give finer resolution but slower computation. Default is 20.
scout_method	Character. Scanning method: "density" - Identifies low-density regions where patterns might hide "variance" - Identifies high-variance regions with pattern potential "correlation" - Maps local correlation landscapes "entropy" - Identifies high-entropy regions with dormancy potential Default is "density".
return_map	Logical. Whether to return the full dormancy map. Default is TRUE.
verbose	Logical. Whether to print progress messages. Default is FALSE.

Details

Scout analysis is useful for:

• Identifying regions to monitor for future pattern emergence

• Understanding the "geography" of your data's pattern space

• Finding data regions that are underexplored or anomalous

• Planning targeted data collection in high-potential regions

The scout creates a map of "dormancy potential" - not actual patterns, but locations where patterns are more likely to exist or emerge.

Value

A list containing:

• scout_results - Data frame with coordinates and dormancy potential

• hotspots - Regions with highest dormancy potential

• dormancy_map - If return_map = TRUE, a matrix representing the dormancy landscape

• summary - Summary statistics of the scan

Examples

set.seed(42)
n <- 500
x <- rnorm(n)
y <- rnorm(n)
# Create a region with hidden pattern
z <- ifelse(x > 1 & y > 1, 0.9 * x + rnorm(sum(x > 1 & y > 1), 0, 0.1), y)
data <- data.frame(x = x, y = z)

scout <- dormancy_scout(data, grid_resolution = 15)
print(scout)

dormancy documentation built on March 16, 2026, 5:09 p.m.