#' Copyright(c) 2017-2024 R. Mark Sharp
#' This file is part of nprcgenekeepr
context("calcFG")
library(testthat)
ped <- data.frame(
  id = c("A", "B", "C", "D", "E", "F", "G"),
  sire = c(NA, NA, "A", "A", NA, "D", "D"),
  dam = c(NA, NA, "B", "B", NA, "E", "E"),
  stringsAsFactors = FALSE
)
ped["gen"] <- findGeneration(ped$id, ped$sire, ped$dam)
ped$population <- getGVPopulation(ped, NULL)
pedFactors <- data.frame(
  id = c("A", "B", "C", "D", "E", "F", "G"),
  sire = c(NA, NA, "A", "A", NA, "D", "D"),
  dam = c(NA, NA, "B", "B", NA, "E", "E"),
  stringsAsFactors = TRUE
)
pedFactors["gen"] <- findGeneration(pedFactors$id, pedFactors$sire,
                                    pedFactors$dam)
pedFactors$population <- getGVPopulation(pedFactors, NULL)
alleles <- geneDrop(ped$id, ped$sire, ped$dam, ped$gen, genotype = NULL,
                    n = 5000, updateProgress = NULL)
allelesFactors <- geneDrop(pedFactors$id, pedFactors$sire, pedFactors$dam,
                           pedFactors$gen, genotype = NULL, n = 5000,
                           updateProgress = NULL)
fg <- calcFG(ped, alleles)
fgFactors <- calcFG(pedFactors, allelesFactors)

## Prior to forcing the pedigree to have id, sire, and dam as character vectors
## inside calcFG, the two calculations above with ped (characters) and
## feFactors (factors) resulted 2.189855 and 1.857998 respectively.
##
## Used example from Analysis of Founder Representation in Pedigrees: Founder
## Equivalents and Founder Genome Equivalents.
## Zoo Biology 8:111-123, (1989) by Robert C. Lacy
## He presented 2.18 as the answer, which was truncated and not precise enough
## for this specific comparison.
test_that("calcFG correctly calculates the number of founder genetic
equivalents in the pedigree", {
            expect_true(abs(fg - fgFactors) < 0.2)
            expect_true(abs(fg - 2.18) < 0.2)
})