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Enhanced Version of create.hop.nbhd.extrema.df with Improved Spurious Classification

Source: R/gflow_cx.R
create.hop.nbhd.extrema.df2.Rd

Creates a data frame containing information about local extrema with multiple options for classifying spurious extrema.

Usage

create.hop.nbhd.extrema.df2(
  result,
  include_spurious = TRUE,
  spurious_method = "threshold",
  threshold = NULL,
  quantile_level = 0.25,
  sort_by_value = FALSE,
  vertex_column_name = "vertex",
  verbose = FALSE
)

Arguments

result

An object from compute.extrema.hop.nbhds() or create.gflow.cx()

include_spurious

Logical; whether to include spurious extrema (default TRUE)

spurious_method

Method for determining spurious extrema (see classify.spurious.extrema)

threshold

Threshold for hop_idx (default 2, or from result object)

quantile_level

Quantile level for quantile-based spurious detection (default 0.25)

sort_by_value

Logical; if TRUE, orders extrema by function value (default FALSE)

vertex_column_name

Character; name of the vertex column (default "vertex")

verbose

Logical; print diagnostic information (default FALSE)

Value

A data frame with columns:

  • vertex: Vertex index

  • hop_idx: Hop index of the extremum

  • is_max: 0 for minima, 1 for maxima

  • label: Label for the extremum

  • spurious: Logical; whether the extremum is considered spurious

  • value: Function value at the extremum (if available)

Examples

result <- list(
  lmin_hop_nbhds = list(
    list(vertex = 1, hop_idx = 1, value = 0.2),
    list(vertex = 3, hop_idx = 4, value = 0.1)
  ),
  lmax_hop_nbhds = list(
    list(vertex = 2, hop_idx = 2, value = 0.9),
    list(vertex = 4, hop_idx = Inf, value = 1.2)
  )
)
create.hop.nbhd.extrema.df2(result)
create.hop.nbhd.extrema.df2(result, spurious_method = "quantile", quantile_level = 0.33)