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Formally Check Resistance Profile Probability Constraints

Source: R/daly_resistance_profiles.R
check_profile_constraints.Rd

Validates that the profile probability distributions returned by compute_resistance_profiles() satisfy all mathematical requirements: non-negativity, sum-to-one, and reconstruction of the input marginal and pairwise resistance rates within a specified tolerance.

Usage

check_profile_constraints(
  profiles_output,
  marginals = NULL,
  pairwise = NULL,
  tolerance = 1e-06,
  pathogen_col = "pathogen",
  class_col = "antibiotic_class",
  rate_col = "marginal_resistance",
  class1_col = "antibiotic_class_1",
  class2_col = "antibiotic_class_2",
  pairwise_rate_col = "pairwise_resistance_prevalence"
)

Arguments

profiles_output

Named list returned by compute_resistance_profiles(). Each element must contain $profiles (data frame with probability and binary class columns) and optionally $constraint_residuals.

marginals

Data frame or NULL. Original marginal resistance rates used as QP constraints. When provided, reconstructed marginals are compared against these values. Must have columns pathogen_col, class_col, and rate_col. Default NULL.

pairwise

Data frame or NULL. Original pairwise co-resistance rates. When provided, reconstructed pairwise values are also checked. Must have columns pathogen_col, class1_col, class2_col, and pairwise_rate_col. Default NULL.

tolerance

Numeric. Maximum absolute residual considered a pass. Default 1e-6.

pathogen_col

Character. Pathogen column in marginals / pairwise. Default "pathogen".

class_col

Character. Class column in marginals. Default "antibiotic_class".

rate_col

Character. Marginal rate column in marginals. Default "marginal_resistance".

class1_col

Character. First class column in pairwise. Default "antibiotic_class_1".

class2_col

Character. Second class column in pairwise. Default "antibiotic_class_2".

pairwise_rate_col

Character. Pairwise rate column. Default "pairwise_resistance_prevalence".

Value

A tibble with one row per constraint per pathogen:

pathogen

Pathogen name.

constraint_type

One of "nonneg", "sum_to_one", "marginal", "pairwise".

constraint_name

Specific label (e.g. "marg_3GC", "pair_3GC_Carbapenems").

target

The constraint target value (NA for nonneg).

reconstructed

The value implied by \(\hat{p}\).

abs_residual

Absolute difference between target and reconstructed.

pass

Logical. TRUE if abs_residual < tolerance or the structural check passed.

source

Either "stored_residuals" (from solve-time values) or "recomputed" (from direct reconstruction).

Also prints a per-pathogen summary of passed and failed checks.

Details

The function uses two complementary sources of evidence:

  1. Constraint residuals already stored in profiles_output[[pathogen]]$constraint_residuals – these are \(M \hat{p} - v\) computed at solve time and are available without re-supplying the original rates.

  2. Direct reconstruction from the binary class-indicator columns in the profiles data frame when marginals and/or pairwise are supplied – independently verifies the residuals and catches any post-solve modifications to the probability vector.

Examples

if (FALSE) { # \dontrun{
marg    <- compute_marginal_resistance(amr_clean)
co_res  <- compute_pairwise_coresistance(marg)
rp      <- compute_resistance_profiles(marg, co_res)

# Using stored constraint residuals only
checks  <- check_profile_constraints(rp)

# Full re-verification with original rates
checks  <- check_profile_constraints(
  rp,
  marginals = marg$marginal,
  pairwise  = NULL,
  tolerance = 1e-5
)

# Inspect failures
checks[!checks$pass, ]
} # }