Add set_nd_nq previously in pfm

pfm depends on mkin anyways, so reexporting set_nd_nq and
set_nd_nq_focus in pfm should provide reasonable continuity.

7 files changed, 405 insertions, 18 deletions

diff --git a/NAMESPACE b/NAMESPACE
index 388a16fd..f6c5ebf9 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -129,6 +129,8 @@ export(plot_sep)
 export(saem)
 export(saemix_data)
 export(saemix_model)
+export(set_nd_nq)
+export(set_nd_nq_focus)
 export(sigma_twocomp)
 export(transform_odeparms)
 import(deSolve)
diff --git a/R/set_nd_nq.R b/R/set_nd_nq.R
new file mode 100644
index 00000000..37b9a894
--- /dev/null
+++ b/R/set_nd_nq.R
@@ -0,0 +1,164 @@
+#' Set non-detects and unquantified values in residue series without replicates
+#'
+#' This function automates replacing unquantified values in residue time and
+#' depth series. For time series, the function performs part of the residue
+#' processing proposed in the FOCUS kinetics guidance for parent compounds
+#' and metabolites. For two-dimensional residue series over time and depth,
+#' it automates the proposal of Boesten et al (2015).
+#'
+#' @param res_raw Character vector of a residue time series, or matrix of
+#' residue values with rows representing depth profiles for a specific sampling
+#' time, and columns representing time series of residues at the same depth.
+#' Values below the limit of detection (lod) have to be coded as "nd", values
+#' between the limit of detection and the limit of quantification, if any, have
+#' to be coded as "nq". Samples not analysed have to be coded as "na". All
+#' values that are not "na", "nd" or "nq" have to be coercible to numeric
+#' @param lod Limit of detection (numeric)
+#' @param loq Limit of quantification(numeric). Must be specified if the FOCUS rule to
+#' stop after the first non-detection is to be applied
+#' @param time_zero_presence Do we assume that residues occur at time zero?
+#' This only affects samples from the first sampling time that have been
+#' reported as "nd" (not detected).
+#' @references Boesten, J. J. T. I., van der Linden, A. M. A., Beltman, W. H.
+#' J. and Pol, J. W. (2015). Leaching of plant protection products and their
+#' transformation products; Proposals for improving the assessment of leaching
+#' to groundwater in the Netherlands — Version 2. Alterra report 2630, Alterra
+#' Wageningen UR (University & Research centre)
+#' @references FOCUS (2014) Generic Guidance for Estimating Persistence and Degradation
+#'   Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Version 1.1,
+#'   18 December 2014, p. 251
+#' @return A numeric vector, if a vector was supplied, or a numeric matrix otherwise
+#' @export
+#' @examples
+#' # FOCUS (2014) p. 75/76 and 131/132
+#' parent_1 <- c(.12, .09, .05, .03, "nd", "nd", "nd", "nd", "nd", "nd")
+#' set_nd_nq(parent_1, 0.02)
+#' parent_2 <- c(.12, .09, .05, .03, "nd", "nd", .03, "nd", "nd", "nd")
+#' set_nd_nq(parent_2, 0.02)
+#' set_nd_nq_focus(parent_2, 0.02, loq = 0.05)
+#' parent_3 <- c(.12, .09, .05, .03, "nd", "nd", .06, "nd", "nd", "nd")
+#' set_nd_nq(parent_3, 0.02)
+#' set_nd_nq_focus(parent_3, 0.02, loq = 0.05)
+#' metabolite <- c("nd", "nd", "nd", 0.03, 0.06, 0.10, 0.11, 0.10, 0.09, 0.05, 0.03, "nd", "nd")
+#' set_nd_nq(metabolite, 0.02)
+#' set_nd_nq_focus(metabolite, 0.02, 0.05)
+#' #
+#' # Boesten et al. (2015), p. 57/58
+#' table_8 <- matrix(
+#'   c(10, 10, rep("nd", 4),
+#'     10, 10, rep("nq", 2), rep("nd", 2),
+#'     10, 10, 10, "nq", "nd", "nd",
+#'     "nq", 10, "nq", rep("nd", 3),
+#'     "nd", "nq", "nq", rep("nd", 3),
+#'     rep("nd", 6), rep("nd", 6)),
+#'   ncol = 6, byrow = TRUE)
+#' set_nd_nq(table_8, 0.5, 1.5, time_zero_presence = TRUE)
+#' table_10 <- matrix(
+#'   c(10, 10, rep("nd", 4),
+#'     10, 10, rep("nd", 4),
+#'     10, 10, 10, rep("nd", 3),
+#'     "nd", 10, rep("nd", 4),
+#'     rep("nd", 18)),
+#'   ncol = 6, byrow = TRUE)
+#' set_nd_nq(table_10, 0.5, time_zero_presence = TRUE)
+set_nd_nq <- function(res_raw, lod, loq = NA, time_zero_presence = FALSE) {
+  if (!is.character(res_raw)) {
+    stop("Please supply a vector or a matrix of character values")
+  }
+  if (is.vector(res_raw)) {
+    was_vector <- TRUE
+    res_raw <- as.matrix(res_raw)
+  } else {
+    was_vector <- FALSE
+    if (!is.matrix(res_raw)) {
+      stop("Please supply a vector or a matrix of character values")
+    }
+  }
+  nq <- 0.5 * (loq + lod)
+  nda <- 0.5 * lod # not detected but adjacent to detection
+  res_raw[res_raw == "nq"] <- nq
+
+  if (!time_zero_presence) {
+    for (j in 1:ncol(res_raw)) {
+      if (res_raw[1, j] == "nd") res_raw[1, j] <- "na"
+    }
+  }
+  res_raw[res_raw == "na"] <- NA
+
+  not_nd_na <- function(value) !(grepl("nd", value) | is.na(value))
+
+  for (i in 1:nrow(res_raw)) {
+    for (j in 1:ncol(res_raw)) {
+      if (!is.na(res_raw[i, j]) && res_raw[i, j] == "nd") {
+        if (i > 1) { # check earlier sample in same layer
+          if (not_nd_na(res_raw[i - 1, j])) res_raw[i, j] <- "nda"
+        }
+        if (i < nrow(res_raw)) { # check later sample
+          if (not_nd_na(res_raw[i + 1, j])) res_raw[i, j] <- "nda"
+        }
+        if (j > 1) { # check above sample at the same time
+          if (not_nd_na(res_raw[i, j - 1])) res_raw[i, j] <- "nda"
+        }
+        if (j < ncol(res_raw)) { # check sample below at the same time
+          if (not_nd_na(res_raw[i, j + 1])) res_raw[i, j] <- "nda"
+        }
+      }
+    }
+  }
+  res_raw[res_raw == "nda"] <- nda
+  res_raw[res_raw == "nd"] <- NA
+
+  result <- as.numeric(res_raw)
+  dim(result) <- dim(res_raw)
+  dimnames(result) <- dimnames(res_raw)
+  if (was_vector) result <- as.vector(result)
+  return(result)
+}
+
+#' @describeIn set_nd_nq Set non-detects in residue time series according to FOCUS rules
+#' @param set_first_sample_nd Should the first sample be set to "first_sample_nd_value"
+#' in case it is a non-detection?
+#' @param first_sample_nd_value Value to be used for the first sample if it is a non-detection
+#' @param ignore_below_loq_after_first_nd Should we ignore values below the LOQ after the first
+#' non-detection that occurs after the quantified values?
+#' @export
+set_nd_nq_focus <- function(res_raw, lod, loq = NA,
+  set_first_sample_nd = TRUE, first_sample_nd_value = 0,
+  ignore_below_loq_after_first_nd = TRUE)
+{
+
+  if (!is.vector(res_raw)) stop("FOCUS rules are only specified for one-dimensional time series")
+
+  if (ignore_below_loq_after_first_nd & is.na(loq)) {
+    stop("You need to specify an LOQ")
+  }
+
+  n <- length(res_raw)
+  if (ignore_below_loq_after_first_nd) {
+    for (i in 3:n) {
+      if (!res_raw[i - 2] %in% c("na", "nd")) {
+        if (res_raw[i - 1] == "nd") {
+          res_remaining <- res_raw[i:n]
+          res_remaining_unquantified <- ifelse(res_remaining == "na", TRUE,
+            ifelse(res_remaining == "nd", TRUE,
+              ifelse(res_remaining == "nq", TRUE,
+                ifelse(suppressWarnings(as.numeric(res_remaining)) < loq, TRUE, FALSE))))
+          res_remaining_numeric <- suppressWarnings(as.numeric(res_remaining))
+          res_remaining_below_loq <- ifelse(res_remaining == "nq", TRUE,
+                ifelse(!is.na(res_remaining_numeric) & res_remaining_numeric < loq, TRUE, FALSE))
+          if (all(res_remaining_unquantified)) {
+            res_raw[i:n] <- ifelse(res_remaining_below_loq, "nd", res_remaining)
+          }
+        }
+      }
+    }
+  }
+
+  result <- set_nd_nq(res_raw, lod = lod, loq = loq)
+
+  if (set_first_sample_nd) {
+    if (res_raw[1] == "nd") result[1] <- first_sample_nd_value
+  }
+
+  return(result)
+}
diff --git a/log/test.log b/log/test.log
index efa30d17..73fbfcf2 100644
--- a/log/test.log
+++ b/log/test.log
@@ -1,24 +1,55 @@
 ℹ Testing mkin
 ✔ | F W S  OK | Context
 ✔ |         5 | AIC calculation
-✔ |         5 | Analytical solutions for coupled models [3.4s]
+✔ |         5 | Analytical solutions for coupled models [3.3s]
 ✔ |         5 | Calculation of Akaike weights
 ✔ |         3 | Export dataset for reading into CAKE
 ✔ |        12 | Confidence intervals and p-values [1.0s]
-✔ |     1  12 | Dimethenamid data from 2018 [31.9s]
+✔ |     1  12 | Dimethenamid data from 2018 [32.2s]
 ────────────────────────────────────────────────────────────────────────────────
 Skip (test_dmta.R:98:3): Different backends get consistent results for SFO-SFO3+, dimethenamid data
 Reason: Fitting this ODE model with saemix takes about 15 minutes on my system
 ────────────────────────────────────────────────────────────────────────────────
-✔ |        14 | Error model fitting [4.9s]
+✔ |        14 | Error model fitting [5.1s]
 ✔ |         5 | Time step normalisation
 ✔ |         4 | Calculation of FOCUS chi2 error levels [0.6s]
 ✔ |        14 | Results for FOCUS D established in expertise for UBA (Ranke 2014) [0.8s]
 ✔ |         4 | Test fitting the decline of metabolites from their maximum [0.4s]
 ✔ |         1 | Fitting the logistic model [0.2s]
-✔ |         7 | Batch fitting and diagnosing hierarchical kinetic models [14.5s]
-✔ |     1  12 | Nonlinear mixed-effects models [0.3s]
+✖ | 1       6 | Batch fitting and diagnosing hierarchical kinetic models [14.5s]
 ────────────────────────────────────────────────────────────────────────────────
+Failure (test_mhmkin.R:41:3): Multiple hierarchical kinetic models can be fitted and diagnosed
+Results have changed from known value recorded in 'summary_hfit_sfo_tc.txt'.
+
+     old                           | new                               
+[45] ""                            | ""                            [45]
+[46] "Variance model:"             | "Variance model:"             [46]
+[47] "    est. lower upper"        | "    est. lower upper"        [47]
+[48] "a.1 0.91  0.64  1.17"        - "a.1 0.90  0.64  1.17"        [48]
+[49] "b.1 0.05  0.04  0.06"        | "b.1 0.05  0.04  0.06"        [49]
+[50] ""                            | ""                            [50]
+[51] "Backtransformed parameters:" | "Backtransformed parameters:" [51]
+────────────────────────────────────────────────────────────────────────────────
+✖ | 1   1  11 | Nonlinear mixed-effects models [0.3s]
+────────────────────────────────────────────────────────────────────────────────
+Failure (test_mixed.R:8:3): Print methods work
+Results have changed from known value recorded in 'print_sfo_saem_1.txt'.
+
+old[7:19] vs new[7:19]
+  ""
+  "Likelihood computed by importance sampling"
+  "   AIC  BIC logLik"
+- "  1311 1315   -649"
++ "  1312 1316   -650"
+  ""
+  "Fitted parameters:"
+  "            estimate lower upper"
+- "parent_0       1e+02 99.13 1e+02"
++ "parent_0       1e+02 99.28 1e+02"
+  "k_parent       4e-02  0.03 4e-02"
+  "a.1            9e-01  0.75 1e+00"
+and 3 more ...
+
 Skip (test_mixed.R:68:3): saemix results are reproducible for biphasic fits
 Reason: Fitting with saemix takes around 10 minutes when using deSolve
 ────────────────────────────────────────────────────────────────────────────────
@@ -26,25 +57,26 @@ Reason: Fitting with saemix takes around 10 minutes when using deSolve
 ✔ |        10 | Special cases of mkinfit calls [0.4s]
 ✔ |         3 | mkinfit features [0.7s]
 ✔ |         8 | mkinmod model generation and printing [0.2s]
-✔ |         3 | Model predictions with mkinpredict [0.3s]
-✔ |        16 | Evaluations according to 2015 NAFTA guidance [1.8s]
-✔ |         9 | Nonlinear mixed-effects models with nlme [8.3s]
-✔ |        16 | Plotting [10.0s]
+✔ |         3 | Model predictions with mkinpredict [0.4s]
+✔ |        16 | Evaluations according to 2015 NAFTA guidance [1.9s]
+✔ |         9 | Nonlinear mixed-effects models with nlme [8.6s]
+✔ |        16 | Plotting [10.2s]
 ✔ |         4 | Residuals extracted from mkinfit models
-✔ |        28 | saemix parent models [180.2s]
+✔ |        28 | saemix parent models [181.5s]
 ✔ |         2 | Complex test case from Schaefer et al. (2007) Piacenza paper [1.4s]
-✔ |         7 | Fitting the SFORB model [3.6s]
+✔ |        11 | Processing of residue series
+✔ |         7 | Fitting the SFORB model [3.7s]
 ✔ |         1 | Summaries of old mkinfit objects
 ✔ |         5 | Summary [0.2s]
 ✔ |         4 | Results for synthetic data established in expertise for UBA (Ranke 2014) [2.1s]
-✔ |         9 | Hypothesis tests [7.8s]
+✔ |         9 | Hypothesis tests [8.3s]
 ✔ |         4 | Calculation of maximum time weighted average concentrations (TWAs) [2.2s]
 
 ══ Results ═════════════════════════════════════════════════════════════════════
-Duration: 277.4 s
+Duration: 280.7 s
 
 ── Skipped tests  ──────────────────────────────────────────────────────────────
 • Fitting this ODE model with saemix takes about 15 minutes on my system (1)
 • Fitting with saemix takes around 10 minutes when using deSolve (1)
 
-[ FAIL 0 | WARN 0 | SKIP 2 | PASS 235 ]
+[ FAIL 2 | WARN 0 | SKIP 2 | PASS 244 ]
diff --git a/man/set_nd_nq.Rd b/man/set_nd_nq.Rd
new file mode 100644
index 00000000..87a3fae1
--- /dev/null
+++ b/man/set_nd_nq.Rd
@@ -0,0 +1,103 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/set_nd_nq.R
+\name{set_nd_nq}
+\alias{set_nd_nq}
+\alias{set_nd_nq_focus}
+\title{Set non-detects and unquantified values in residue series without replicates}
+\usage{
+set_nd_nq(res_raw, lod, loq = NA, time_zero_presence = FALSE)
+
+set_nd_nq_focus(
+  res_raw,
+  lod,
+  loq = NA,
+  set_first_sample_nd = TRUE,
+  first_sample_nd_value = 0,
+  ignore_below_loq_after_first_nd = TRUE
+)
+}
+\arguments{
+\item{res_raw}{Character vector of a residue time series, or matrix of
+residue values with rows representing depth profiles for a specific sampling
+time, and columns representing time series of residues at the same depth.
+Values below the limit of detection (lod) have to be coded as "nd", values
+between the limit of detection and the limit of quantification, if any, have
+to be coded as "nq". Samples not analysed have to be coded as "na". All
+values that are not "na", "nd" or "nq" have to be coercible to numeric}
+
+\item{lod}{Limit of detection (numeric)}
+
+\item{loq}{Limit of quantification(numeric). Must be specified if the FOCUS rule to
+stop after the first non-detection is to be applied}
+
+\item{time_zero_presence}{Do we assume that residues occur at time zero?
+This only affects samples from the first sampling time that have been
+reported as "nd" (not detected).}
+
+\item{set_first_sample_nd}{Should the first sample be set to "first_sample_nd_value"
+in case it is a non-detection?}
+
+\item{first_sample_nd_value}{Value to be used for the first sample if it is a non-detection}
+
+\item{ignore_below_loq_after_first_nd}{Should we ignore values below the LOQ after the first
+non-detection that occurs after the quantified values?}
+}
+\value{
+A numeric vector, if a vector was supplied, or a numeric matrix otherwise
+}
+\description{
+This function automates replacing unquantified values in residue time and
+depth series. For time series, the function performs part of the residue
+processing proposed in the FOCUS kinetics guidance for parent compounds
+and metabolites. For two-dimensional residue series over time and depth,
+it automates the proposal of Boesten et al (2015).
+}
+\section{Functions}{
+\itemize{
+\item \code{set_nd_nq_focus()}: Set non-detects in residue time series according to FOCUS rules
+
+}}
+\examples{
+# FOCUS (2014) p. 75/76 and 131/132
+parent_1 <- c(.12, .09, .05, .03, "nd", "nd", "nd", "nd", "nd", "nd")
+set_nd_nq(parent_1, 0.02)
+parent_2 <- c(.12, .09, .05, .03, "nd", "nd", .03, "nd", "nd", "nd")
+set_nd_nq(parent_2, 0.02)
+set_nd_nq_focus(parent_2, 0.02, loq = 0.05)
+parent_3 <- c(.12, .09, .05, .03, "nd", "nd", .06, "nd", "nd", "nd")
+set_nd_nq(parent_3, 0.02)
+set_nd_nq_focus(parent_3, 0.02, loq = 0.05)
+metabolite <- c("nd", "nd", "nd", 0.03, 0.06, 0.10, 0.11, 0.10, 0.09, 0.05, 0.03, "nd", "nd")
+set_nd_nq(metabolite, 0.02)
+set_nd_nq_focus(metabolite, 0.02, 0.05)
+#
+# Boesten et al. (2015), p. 57/58
+table_8 <- matrix(
+  c(10, 10, rep("nd", 4),
+    10, 10, rep("nq", 2), rep("nd", 2),
+    10, 10, 10, "nq", "nd", "nd",
+    "nq", 10, "nq", rep("nd", 3),
+    "nd", "nq", "nq", rep("nd", 3),
+    rep("nd", 6), rep("nd", 6)),
+  ncol = 6, byrow = TRUE)
+set_nd_nq(table_8, 0.5, 1.5, time_zero_presence = TRUE)
+table_10 <- matrix(
+  c(10, 10, rep("nd", 4),
+    10, 10, rep("nd", 4),
+    10, 10, 10, rep("nd", 3),
+    "nd", 10, rep("nd", 4),
+    rep("nd", 18)),
+  ncol = 6, byrow = TRUE)
+set_nd_nq(table_10, 0.5, time_zero_presence = TRUE)
+}
+\references{
+Boesten, J. J. T. I., van der Linden, A. M. A., Beltman, W. H.
+J. and Pol, J. W. (2015). Leaching of plant protection products and their
+transformation products; Proposals for improving the assessment of leaching
+to groundwater in the Netherlands — Version 2. Alterra report 2630, Alterra
+Wageningen UR (University & Research centre)
+
+FOCUS (2014) Generic Guidance for Estimating Persistence and Degradation
+Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Version 1.1,
+18 December 2014, p. 251
+}
diff --git a/tests/testthat/print_sfo_saem_1.txt b/tests/testthat/print_sfo_saem_1.txt
index a11e1e96..34eea058 100644
--- a/tests/testthat/print_sfo_saem_1.txt
+++ b/tests/testthat/print_sfo_saem_1.txt
@@ -7,13 +7,13 @@ Data:
 
 Likelihood computed by importance sampling
    AIC  BIC logLik
-  1311 1315   -649
+  1312 1316   -650
 
 Fitted parameters:
             estimate lower upper
-parent_0       1e+02 99.13 1e+02
+parent_0       1e+02 99.28 1e+02
 k_parent       4e-02  0.03 4e-02
 a.1            9e-01  0.75 1e+00
 b.1            5e-02  0.04 5e-02
-SD.parent_0    7e-01 -1.09 3e+00
+SD.parent_0    2e-01 -6.33 7e+00
 SD.k_parent    3e-01  0.20 4e-01
diff --git a/tests/testthat/summary_hfit_sfo_tc.txt b/tests/testthat/summary_hfit_sfo_tc.txt
index ad701cee..e3e2f7e4 100644
--- a/tests/testthat/summary_hfit_sfo_tc.txt
+++ b/tests/testthat/summary_hfit_sfo_tc.txt
@@ -45,7 +45,7 @@ SD.log_k_parent  0.3   0.1   0.4
 
 Variance model:
     est. lower upper
-a.1 0.91  0.64  1.17
+a.1 0.90  0.64  1.17
 b.1 0.05  0.04  0.06
 
 Backtransformed parameters:
diff --git a/tests/testthat/test_set_nd.R b/tests/testthat/test_set_nd.R
new file mode 100644
index 00000000..232e7c62
--- /dev/null
+++ b/tests/testthat/test_set_nd.R
@@ -0,0 +1,86 @@
+context("Processing of residue series")
+
+# FOCUS (2014) page 76 (parent) and page 132 (metabolite)
+
+parent_1 <- c(.12, .09, .05, .03, "nd", "nd", "nd", "nd", "nd", "nd")
+parent_2 <- c(.12, .09, .05, .03, "nd", "nd", .03, "nd", "nd", "nd")
+parent_3 <- c(.12, .09, .05, .03, "nd", "nd", .06, "nd", "nd", "nd")
+metabolite <- c("nd", "nd", "nd", 0.03, 0.06, 0.10, 0.11, 0.10, 0.09, 0.05, 0.03, "nd", "nd")
+
+test_that("Simple residue series are processed as intended", {
+
+  expect_equal(set_nd_nq(parent_1, 0.02),
+    c(.12, .09, .05, .03, .01, rep(NA, 5)))
+
+  expect_equal(set_nd_nq(parent_2, 0.02, loq = 0.05),
+    c(.12, .09, .05, .03, .01, .01, .03, .01, NA, NA))
+
+  expect_equal(set_nd_nq(metabolite, 0.02, loq = 0.05),
+    c(NA, NA, .01, .03, .06, .1, .11, .1, .09, .05, .03, .01, NA))
+
+  expect_equal(set_nd_nq(c("nd", 1, 0.2, "nd"), 0.1),
+    c(NA, 1, 0.2, 0.05))
+
+})
+
+test_that("Simple residue series are processed as in the FOCUS guidance", {
+
+  # Parent 1
+  expect_error(set_nd_nq_focus(parent_1, 0.02),
+    "You need to specify an LOQ")
+  expect_equal(set_nd_nq_focus(parent_1, 0.02, 0.05),
+    c(.12, .09, .05, .03, .01, rep(NA, 5)))
+
+  # Parent 2
+  expect_equal(set_nd_nq_focus(parent_2, 0.02, loq = 0.05),
+    c(.12, .09, .05, .03, .01, rep(NA, 5)))
+
+  # Parent 3
+  expect_equal(set_nd_nq_focus(parent_3, 0.02, loq = 0.05),
+    c(.12, .09, .05, .03, .01, .01, .06, .01, NA, NA))
+
+  # Metabolite
+  expect_equal(set_nd_nq_focus(metabolite, 0.02, loq = 0.05),
+    c(0, NA, .01, .03, .06, .1, .11, .1, .09, .05, .03, .01, NA))
+
+})
+
+test_that("Examples Boesten et al. (2015, p. 57/58) are correctly processed", {
+  table_8 <- matrix(
+    c(10, 10, rep("nd", 4),
+      10, 10, rep("nq", 2), rep("nd", 2),
+      10, 10, 10, "nq", "nd", "nd",
+      "nq", 10, "nq", rep("nd", 3),
+      "nd", "nq", "nq", rep("nd", 3),
+      rep("nd", 6), rep("nd", 6)),
+    ncol = 6, byrow = TRUE)
+  table_8_processed <- set_nd_nq(table_8, 0.5, 1.5, time_zero_presence = TRUE)
+  table_9 <- matrix(
+    c(10, 10, 0.25, 0.25, NA, NA,
+      10, 10, 1, 1, 0.25, NA,
+      10, 10, 10, 1, 0.25, NA,
+      1, 10, 1, 0.25, NA, NA,
+      0.25, 1, 1, 0.25, NA, NA,
+      NA, 0.25, 0.25, NA, NA, NA,
+      rep(NA, 6)),
+    ncol = 6, byrow = TRUE)
+  expect_equal(table_8_processed, table_9)
+
+  table_10 <- matrix(
+    c(10, 10, rep("nd", 4),
+      10, 10, rep("nd", 4),
+      10, 10, 10, rep("nd", 3),
+      "nd", 10, rep("nd", 4),
+      rep("nd", 18)),
+    ncol = 6, byrow = TRUE)
+  table_10_processed <- set_nd_nq(table_10, 0.5, time_zero_presence = TRUE)
+  table_11 <- matrix(
+    c(10, 10, 0.25, rep(NA, 3),
+      10, 10, 0.25, rep(NA, 3),
+      10, 10, 10, 0.25, NA, NA,
+      0.25, 10, 0.25, rep(NA, 3),
+      NA, 0.25, rep(NA, 4),
+      rep(NA, 12)),
+    ncol = 6, byrow = TRUE)
+  expect_equal(table_10_processed, table_11)
+})