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Truncated dominant community state types with configurable low-support handling

Source: R/linf.R
linf.csts.Rd

Forms provisional depth-1 dominance sample sets from the dominant feature of each sample and then applies the minimum support threshold n0. Sets with fewer than n0 samples are handled according to low.freq.policy:

  • "pure": retain only sets with support >= n0 as named dCSTs and collapse all low-support sets into rare.label.

  • "absorb": reassign each low-support sample to the retained state with the largest value among the retained features (ties handled by tie.method).

Usage

linf.csts(
  S,
  feature.ids = NULL,
  feature.labels = NULL,
  n0 = 50,
  low.freq.policy = c("pure", "absorb"),
  rare.label = "RARE_DOMINANT",
  tie.method = c("first", "random", "error"),
  return.diagnostics = FALSE,
  return.landmarks = FALSE,
  landmark.types = c("endpoint.max", "endpoint.min"),
  landmark.view = c("active", "pure", "absorb"),
  backend = c("auto", "dense", "sparse")
)

Arguments

S

Numeric matrix (samples x features), typically L-infinity relatives.

feature.ids

Optional character vector of stable feature identifiers, length ncol(S).

feature.labels

Optional character vector of display labels, length ncol(S).

n0

Integer >= 1. Minimum support required to retain a dominance sample set.

low.freq.policy

Character. One of "pure" or "absorb". Default: "pure".

rare.label

Character scalar used when low.freq.policy = "pure". Default: "RARE_DOMINANT".

tie.method

Character. Tie handling passed to linf.dominant.features() and used during absorb reassignment ("first", "random", "error"). Positive ties use original matrix column order for "first" on both backends. If all retained values are zero, absorption uses the retained state with greatest reference support (then lexical label order), regardless of tie.method.

return.diagnostics

Logical. If TRUE, return reassignment diagnostics.

return.landmarks

Logical. If TRUE, attach a depth-1 landmark summary computed by linf.landmarks.

landmark.types

Character vector of landmark types passed to linf.landmarks when return.landmarks = TRUE.

landmark.view

Character. Landmark view passed to linf.landmarks when return.landmarks = TRUE.

backend

Character. Matrix backend to use: "auto", "dense", or "sparse". The default "auto" preserves sparse input and otherwise uses the dense path.

Value

List with:

  • depth1.feature.index, depth1.feature.id, depth1.feature.label: active depth-1 assignment

  • lineage.id, lineage.label: active leaf-lineage assignment

  • policy-specific variants of the depth-1 and leaf-lineage fields, ending in .pure or .absorb

  • lineage.ids, lineage.labels: active hierarchy, plus policy-specific .pure and .absorb hierarchies

  • depth: current hierarchy depth

  • retained.feature.indices, retained.feature.ids, retained.feature.labels

  • provisional.feature.index, provisional.feature.id, provisional.feature.label

  • feature.ids, feature.labels

  • size.table, size.table.id

  • n0, low.freq.policy, rare.label

  • diagnostics (if return.diagnostics = TRUE)

  • landmarks (if return.landmarks = TRUE)

Examples

X <- rbind(
  s1 = c(A = 10, B = 2, C = 1),
  s2 = c(A = 9, B = 3, C = 1),
  s3 = c(A = 1, B = 10, C = 2),
  s4 = c(A = 1, B = 9, C = 3),
  s5 = c(A = 1, B = 2, C = 10)
)
fit <- linf.csts(normalize.linf(X), n0 = 2, low.freq.policy = "pure")
table(fit$lineage.label)
#> 
#>             A             B RARE_DOMINANT 
#>             2             2             1 
fit$retained.feature.ids
#> [1] "A" "B"