tests/testthat/test-10-makeModelMatrix.R

In vdorie/dbarts: Discrete Bayesian Additive Regression Trees Sampler

context("make model matrix from data frame")

getTestDataFrame <- function() {
  set.seed(42)
  df <- data.frame(iv = seq.int(10L), rv = runif(10),
                   f = factor(sample(3L, 10L, TRUE), labels = c("a", "b", "c")))
  df[[4]] <- matrix(rbinom(20, 3, 0.5), 10, dimnames = list(NULL, c("a", "b")))
  df[[5]] <- matrix(rnorm(20), 10, dimnames = list(NULL, c("a", "b")))
  names(df) <- c(names(df)[1:3], "im", "rm")
  df
}

test_that("make model matrix works on default", {
  df <- getTestDataFrame()
  mm <- dbarts::makeModelMatrixFromDataFrame(df)
  
  expect_equal(ncol(mm), 9)
  expect_equal(colnames(mm), c("iv", "rv", "f.a", "f.b", "f.c", "im.a", "im.b", "rm.a", "rm.b"))
  expect_equal(mm[,"iv"], df$iv)
  expect_equal(mm[,"rv"], df$rv)
  expect_equal(mm[,"f.a"], ifelse(df$f == "a", 1L, 0L))
  expect_equal(mm[,"f.b"], ifelse(df$f == "b", 1L, 0L))
  expect_equal(mm[,"f.c"], ifelse(df$f == "c", 1L, 0L))
  expect_equal(mm[,"im.a"], df$im[,"a"])
  expect_equal(mm[,"im.b"], df$im[,"b"])
  expect_equal(mm[,"rm.a"], df$rm[,"a"])
  expect_equal(mm[,"rm.b"], df$rm[,"b"])
})

test_that("make model matrix handles empty names", {  
  df <- getTestDataFrame()
  names(df) <- NULL
  mm <- dbarts::makeModelMatrixFromDataFrame(df)
  expect_equal(colnames(mm), c("", "", "a", "b", "c", "a", "b", "a", "b"))
  
  df <- getTestDataFrame()
  df$f <- as.factor(as.integer(df$f))
  mm <- dbarts::makeModelMatrixFromDataFrame(df)
  expect_equal(colnames(mm), c("iv", "rv", "f.1", "f.2", "f.3", "im.a", "im.b", "rm.a", "rm.b"))
  
  df <- getTestDataFrame()
  colnames(df$im) <- NULL
  mm <- dbarts::makeModelMatrixFromDataFrame(df)
  expect_equal(colnames(mm), c("iv", "rv", "f.a", "f.b", "f.c", "im.1", "im.2", "rm.a", "rm.b"))
  
  df <- getTestDataFrame()
  colnames(df$rm) <- NULL
  mm <- dbarts::makeModelMatrixFromDataFrame(df)
  expect_equal(colnames(mm), c("iv", "rv", "f.a", "f.b", "f.c", "im.a", "im.b", "rm.1", "rm.2"))
})

test_that("make model matrix drops useless columns",  {
  df <- getTestDataFrame()
  df$iv <- rep(1L, 10)
  mm <- dbarts::makeModelMatrixFromDataFrame(df)
  expect_equal(ncol(mm), 8)
  expect_equal(attr(mm, "drop")$iv, TRUE)
  expect_equal(colnames(mm), c("rv", "f.a", "f.b", "f.c", "im.a", "im.b", "rm.a", "rm.b"))
  
  df <- getTestDataFrame()
  df$rv <- rep(pi, 10)
  mm <- dbarts::makeModelMatrixFromDataFrame(df)
  expect_equal(ncol(mm), 8)
  expect_equal(attr(mm, "drop")$rv, TRUE)
  expect_equal(colnames(mm), c("iv", "f.a", "f.b", "f.c", "im.a", "im.b", "rm.a", "rm.b"))
  
  df <- getTestDataFrame()
  ## creates a factor with one unused level
  df$f <- factor(rep(seq.int(3), c(5, 5, 1)), labels = c("a", "b", "c"))[1:10]
  mm <- dbarts::makeModelMatrixFromDataFrame(df)
  expect_equal(ncol(mm), 7)
  expect_equal(attr(mm, "drop")$f, c(5, 5, 0))
  expect_equal(colnames(mm), c("iv", "rv", "f.b", "im.a", "im.b", "rm.a", "rm.b"))
  
  df <- getTestDataFrame()
  df$im[,1] <- rep(1L, 10)
  mm <- dbarts::makeModelMatrixFromDataFrame(df)
  expect_equal(ncol(mm), 8)
  expect_equal(attr(mm, "drop")$im, c(TRUE, FALSE))
  expect_equal(colnames(mm), c("iv", "rv", "f.a", "f.b", "f.c", "im.b", "rm.a", "rm.b"))
  expect_equal(as.double(mm[,7:8]), as.double(df$rm))
  
  df <- getTestDataFrame()
  df$im[,1] <- rep(1L, 10); df$im[,2] <- rep(2L, 10)
  mm <- dbarts::makeModelMatrixFromDataFrame(df)
  expect_equal(ncol(mm), 7)
  expect_equal(attr(mm, "drop")$im, c(TRUE, TRUE))
  expect_equal(colnames(mm), c("iv", "rv", "f.a", "f.b", "f.c", "rm.a", "rm.b"))

  df <- getTestDataFrame()
  df$rm[,2] <- rep(pi, 10)
  mm <- dbarts::makeModelMatrixFromDataFrame(df)
  expect_equal(ncol(mm), 8)
  expect_equal(attr(mm, "drop")$rm, c(FALSE, TRUE))
  expect_equal(colnames(mm), c("iv", "rv", "f.a", "f.b", "f.c", "im.a", "im.b", "rm.a"))
  expect_equal(as.integer(mm[,6:7]), as.integer(df$im))
})

test_that("make model matrix doesn't drop useless columns when drop = FALSE", {
  df <- getTestDataFrame()
  df$iv <- rep(1L, 10)
  mm <- dbarts::makeModelMatrixFromDataFrame(df, FALSE)
  expect_equal(ncol(mm), 9)
  expect_equal(mm[,"iv"], df$iv)
  
  df <- getTestDataFrame()
  df$rv <- rep(pi, 10)
  mm <- dbarts::makeModelMatrixFromDataFrame(df, FALSE)
  expect_equal(mm[,"rv"], df$rv)
  
  df <- getTestDataFrame()
  df$f <- factor(rep(seq.int(3), c(5, 5, 1)), labels = c("a", "b", "c"))[1:10]
  mm <- dbarts::makeModelMatrixFromDataFrame(df, FALSE)
  expect_equal(mm[,"f.a"], c(rep(1L, 5), rep(0L, 5)))
  expect_equal(mm[,"f.b"], c(rep(0L, 5), rep(1L, 5)))
  expect_equal(mm[,"f.c"], rep(0L, 10))
  
  df <- getTestDataFrame()
  df$im[,1] <- rep(1L, 10)
  mm <- dbarts::makeModelMatrixFromDataFrame(df, FALSE)
  expect_equal(as.integer(mm[,6:7]), as.integer(df$im))
  
  df <- getTestDataFrame()
  df$rm[,2] <- rep(pi, 10)
  mm <- dbarts::makeModelMatrixFromDataFrame(df, FALSE)
  expect_equal(as.double(mm[,8:9]), as.double(df$rm))
})

test_that("make model matrix respects drop argument when a list", {
  df <- getTestDataFrame()
  drop <- list(TRUE, FALSE, as.integer(table(df$f)), c(FALSE, FALSE), c(FALSE, FALSE))
  names(drop) <- names(df)
  
  mm <- dbarts::makeModelMatrixFromDataFrame(df, drop)
  expect_equal(ncol(mm), 8)
  expect_equal(colnames(mm), c("rv", "f.a", "f.b", "f.c", "im.a", "im.b", "rm.a", "rm.b"))
  
  drop$iv <- FALSE; drop$rv <- TRUE
  mm <- dbarts::makeModelMatrixFromDataFrame(df, drop)
  expect_equal(ncol(mm), 8)
  expect_equal(colnames(mm), c("iv", "f.a", "f.b", "f.c", "im.a", "im.b", "rm.a", "rm.b"))
  
  drop$rv <- FALSE; drop$f <- c(1L, 0L, 1L)
  mm <- dbarts::makeModelMatrixFromDataFrame(df, drop)
  expect_equal(ncol(mm), 7)
  expect_equal(colnames(mm), c("iv", "rv", "f.c", "im.a", "im.b", "rm.a", "rm.b"))
  expect_equal(mm[,"f.c"], ifelse(df$f == "c", 1L, 0L))
  
  drop$f <- as.integer(table(df$f)); drop$im <- c(FALSE, TRUE)
  mm <- dbarts::makeModelMatrixFromDataFrame(df, drop)
  expect_equal(ncol(mm), 8)
  expect_equal(colnames(mm), c("iv", "rv", "f.a", "f.b", "f.c", "im.a", "rm.a", "rm.b"))
  expect_equal(as.integer(mm[,"im.a"]), as.integer(df$im[,"a"]))
  
  drop$im <- c(FALSE, FALSE); drop$rm <- c(TRUE, TRUE)
  mm <- dbarts::makeModelMatrixFromDataFrame(df, drop)
  expect_equal(ncol(mm), 7)
  expect_equal(colnames(mm), c("iv", "rv", "f.a", "f.b", "f.c", "im.a", "im.b"))
})

rm(getTestDataFrame)

test_that("make model matrix handles character vectors correctly", {
  n <- 1000L
  if (getRversion() >= "3.6.0")
    suppressWarnings(set.seed(0, kind = "Mersenne-Twister", normal.kind = "Inversion", sample.kind = "Rounding"))
  else
    set.seed(0, kind = "Mersenne-Twister", normal.kind = "Inversion")
  mf <- data.frame(x1 = runif(n),
                   x2 = c(rep.int(0L, n - 1L), 1L),
                   x3 = factor(sample(letters[1:5], n, TRUE)),
                   x4 = sample(letters[1:5], n, TRUE),
                   x5 = c("a", rep("b", n - 1L)),
                   x6 = c("a", rep("b", n - 2L), "c"))
  
  mm <- dbarts::makeModelMatrixFromDataFrame(mf)
  
  
  drop <- attr(mm, "drop")
  
  expect_true(all(!is.null(drop)))
  expect_true(all(sapply(drop[sapply(drop, is.numeric)], sum) == n))
  
  factorCols <- which(sapply(mf, function(col) is.factor(col) || is.character(col)))
  
  for (col in factorCols) {
    col.table <- table(mf[,col])
    col.name  <- colnames(mf)[col]
    col.nvals <- length(col.table)
    
    expect_true(sum(grepl(paste0("^", col.name, "\\."), colnames(mm))) == (if (col.nvals > 2L) col.nvals else col.nvals - 1L))
    expect_true(all(drop[[col.name]] == col.table))
  }
})