Merge pull request #36 from mathesong/cran_requirements

Add time-based functionality for start end and t*, and fix notes on devtools::check

Author: mathesong

DESCRIPTION

@@ -1,9 +1,9 @@
 Package: kinfitr
 Title: Kinetic Modelling of PET Time Activity Curves
-Date: 2024-08-14
-Version: 0.8.0
+Date: 2025-10-14
+Version: 0.9.0
 Authors@R: person("Granville", "Matheson", email = "[email protected]", role = c("aut", "cre"))
-Description: This package calculates outcome parameters for PET data using time activity curves (TACs). The will allow for more reproducible PET modelling research.
+Description: This package calculates outcome parameters for PET data using time activity curves (TACs). This will allow for more reproducible PET modelling research.
 Depends:
     R (>= 3.4.0)
 License: MIT + file LICENSE
@@ -15,7 +15,6 @@ Imports:
     minpack.lm,
     forcats,
     RColorBrewer,
-    plyr,
     tidyr,
     magrittr,
     scales,

NAMESPACE

@@ -146,4 +146,27 @@ export(weights_create)
 export(weights_create_bids)
 import(ggplot2)
 importFrom(dplyr,"%>%")
+importFrom(grDevices,dev.off)
+importFrom(grDevices,jpeg)
+importFrom(graphics,lines)
 importFrom(magrittr,"%>%")
+importFrom(rlang,":=")
+importFrom(stats,AIC)
+importFrom(stats,as.formula)
+importFrom(stats,coef)
+importFrom(stats,fitted)
+importFrom(stats,lag)
+importFrom(stats,lm)
+importFrom(stats,median)
+importFrom(stats,na.omit)
+importFrom(stats,pgamma)
+importFrom(stats,predict)
+importFrom(stats,residuals)
+importFrom(stats,start)
+importFrom(stats,time)
+importFrom(stats,weights)
+importFrom(utils,data)
+importFrom(utils,head)
+importFrom(utils,modifyList)
+importFrom(utils,read.delim)
+importFrom(utils,tail)

R/kinfitr_SUV.R

@@ -27,7 +27,8 @@
 #' fit1 <- SUV(tac, t_tac, injRad = 150, bodymass = 85)
 #' fit2 <- SUV(tac, dur_tac = dur_tac, injRad = 150, bodymass = 85)
 #' fit3 <- SUV(tac, t_tac = t_tac, dur_tac = dur_tac, injRad = 150, bodymass = 85)
-#' fit4 <- SUV(tac, t_tac = t_tac, dur_tac = dur_tac, injRad = 150, bodymass = 85, frameStartEnd = c(1,5))
+#' fit4 <- SUV(tac, t_tac = t_tac, dur_tac = dur_tac, injRad = 150, bodymass = 85,
+#'    frameStartEnd = c(1,5))
 #' @author Granville J Matheson, \email{mathesong@@gmail.com}
 #'
 #' @export

R/kinfitr_blooddata.R

@@ -584,7 +584,7 @@ bd_tidy_times <- function(blooddata,
                               interpPoints = 6000) {
 
   # Check that it actually is a blooddata object, even if old
-  if( class(blooddata) != "blooddata" ) {
+  if( !inherits(blooddata, "blooddata") ) {
     stop("The input data does not appear to be a blooddata object. Please make
            sure that the input data is correct.")
   }

R/kinfitr_bloodfuncs.R

@@ -118,14 +118,14 @@ blood_interp <- function(t_blood, blood,
 
   interptime <- pracma::linspace(0, maxtime, interpPoints)
 
-  interpcurves <- plyr::dlply(
-    input, "Measure",
-    function(x) pracma::interp1(x$Time,
-        x$Value,
+  interpcurves <- input %>%
+    dplyr::group_split(Measure) %>%
+    purrr::map(~ pracma::interp1(.x$Time,
+        .x$Value,
         interptime,
         method = "linear"
-      )
-  )
+      )) %>%
+    purrr::set_names(unique(input$Measure))
 
   if(is.null(aif)) {
 

R/kinfitr_frtm.R

@@ -285,12 +285,12 @@ plot_frtmfit <- function(frtmout, roiname = NULL, refname = NULL) {
     refname <- "Reference"
   }
 
-  measured <- plyr::rename(measured, c(
-    "ROI.measured" = paste0(roiname, ".measured"),
-    "Reference" = refname
-  ))
+  measured <- dplyr::rename(measured, 
+    !!paste0(roiname, ".measured") := ROI.measured,
+    !!refname := Reference
+  )
 
-  fitted <- plyr::rename(fitted, c("ROI.fitted" = paste0(roiname, ".fitted")))
+  fitted <- dplyr::rename(fitted, !!paste0(roiname, ".fitted") := ROI.fitted)
 
   tidymeasured <- tidyr::gather(
     measured,

R/kinfitr_lin2tcm.R

@@ -24,8 +24,13 @@
 #'   not included, the integrals will be calculated using trapezoidal
 #'   integration.
 #' @param frameStartEnd Optional: This allows one to specify the beginning and
-#'   final frame to use for modelling, e.g. c(1,20). This can be used to assess time stability for example.
-#' @param timeStartEnd Optional. This allows one to specify the beginning and end time point instead of defining the frame numbers using frameStartEnd. This function will restrict the model to all time frames whose t_tac is between the values, i.e. c(0,5) will select all frames with midtimes during the first 5 minutes.
+#'   final frame to use for modelling, e.g. c(1,20). This can be used to assess
+#'   time stability for example.
+#' @param timeStartEnd Optional. This allows one to specify the beginning and
+#'   end time point instead of defining the frame numbers using frameStartEnd.
+#'   This function will restrict the model to all time frames whose t_tac is
+#'   between the values, i.e. c(0,5) will select all frames with midtimes during
+#'   the first 5 minutes.
 #'
 #' @return A list with a data frame of the fitted parameters \code{out$par}, the
 #'   model fit object \code{out$fit}, a dataframe containing the TACs of the
@@ -55,10 +60,10 @@
 #' @author Granville J Matheson, \email{mathesong@@gmail.com}
 #'
 #' @references Oikonen, V (2003). Multilinear solution for 4-compartment model:
-#' I. Tissue compartments in series. Gjedde A, Wong DF 1990. Modeling
-#' neuroreceptor binding of radioligands in vivo. In: Quantitative imaging:
-#' neuroreceptors, neurotransmitters, and enzymes. (Eds. Frost JJ, Wagner HM
-#' Jr). Raven Press, 51-79.
+#'   I. Tissue compartments in series. Gjedde A, Wong DF 1990. Modeling
+#'   neuroreceptor binding of radioligands in vivo. In: Quantitative imaging:
+#'   neuroreceptors, neurotransmitters, and enzymes. (Eds. Frost JJ, Wagner HM
+#'   Jr). Raven Press, 51-79.
 #'
 #' @export
 lin2tcm <- function(t_tac, tac, input, weights = NULL, inpshift = 0,
@@ -67,7 +72,7 @@ lin2tcm <- function(t_tac, tac, input, weights = NULL, inpshift = 0,
 
   # Convert timeStartEnd to frameStartEnd if needed
   if (is.null(frameStartEnd) && !is.null(timeStartEnd)) {
-    frameStartEnd <- c(which(t_tac >= timeStartEnd[1])[1], 
+    frameStartEnd <- c(which(t_tac >= timeStartEnd[1])[1],
                        tail(which(t_tac <= timeStartEnd[2]), 1))
   }
 
@@ -347,8 +352,13 @@ plot_lin2tcmfit <- function(lin2tcmout, roiname = NULL) {
 #'   not included, the integrals will be calculated using trapezoidal
 #'   integration.
 #' @param frameStartEnd Optional: This allows one to specify the beginning and
-#'   final frame to use for modelling, e.g. c(1,20). This can be used to assess time stability for example.
-#' @param timeStartEnd Optional. This allows one to specify the beginning and end time point instead of defining the frame numbers using frameStartEnd. This function will restrict the model to all time frames whose t_tac is between the values, i.e. c(0,5) will select all frames with midtimes during the first 5 minutes.
+#'   final frame to use for modelling, e.g. c(1,20). This can be used to assess
+#'   time stability for example.
+#' @param timeStartEnd Optional. This allows one to specify the beginning and
+#'   end time point instead of defining the frame numbers using frameStartEnd.
+#'   This function will restrict the model to all time frames whose t_tac is
+#'   between the values, i.e. c(0,5) will select all frames with midtimes during
+#'   the first 5 minutes.
 #' @param inpshift_vals Optional. The values of the inpshift to assess with the
 #'   grid. By default, a grid between -1 and 1 with spacing of 0.01 will be
 #'   used.
@@ -379,10 +389,10 @@ plot_lin2tcmfit <- function(lin2tcmout, roiname = NULL) {
 #' @author Granville J Matheson, \email{mathesong@@gmail.com}
 #'
 #' @references Oikonen, V (2003). Multilinear solution for 4-compartment model:
-#' I. Tissue compartments in series. Gjedde A, Wong DF 1990. Modeling
-#' neuroreceptor binding of radioligands in vivo. In: Quantitative imaging:
-#' neuroreceptors, neurotransmitters, and enzymes. (Eds. Frost JJ, Wagner HM
-#' Jr). Raven Press, 51-79.
+#'   I. Tissue compartments in series. Gjedde A, Wong DF 1990. Modeling
+#'   neuroreceptor binding of radioligands in vivo. In: Quantitative imaging:
+#'   neuroreceptors, neurotransmitters, and enzymes. (Eds. Frost JJ, Wagner HM
+#'   Jr). Raven Press, 51-79.
 #'
 #' @export
 lin2tcm_inpshiftProfile <- function(t_tac, tac, input, weights = NULL, vB = NULL,
@@ -391,7 +401,7 @@ lin2tcm_inpshiftProfile <- function(t_tac, tac, input, weights = NULL, vB = NULL
 
   # Convert timeStartEnd to frameStartEnd if needed
   if (is.null(frameStartEnd) && !is.null(timeStartEnd)) {
-    frameStartEnd <- c(which(t_tac >= timeStartEnd[1])[1], 
+    frameStartEnd <- c(which(t_tac >= timeStartEnd[1])[1],
                        tail(which(t_tac <= timeStartEnd[2]), 1))
   }
 

R/kinfitr_loganplot.R

@@ -11,11 +11,12 @@
 #' @param input Data frame containing the blood, plasma, and parent fraction
 #'   concentrations over time.  This can be generated using the
 #'   \code{blood_interp} function.
-#' @param tstarIncludedFrames The number of frames to be used in the regression
-#'   model, i.e. the number of frames for which the function is linear after
-#'   pseudo-equilibrium is reached. This is a count from the end of the
-#'   measurement, so a value of 10 means that last 10 frames will be used. This
-#'   value can be estimated using \code{Logan_tstar}.
+#' @param tstar The t* specification for regression. If tstar_type="frames", 
+#'   this is the number of frames from the end to include (e.g., 10 means last 10 frames).
+#'   If tstar_type="time", this is the time point (in minutes) after which all frames 
+#'   with midpoints later than this time are included. This value can be estimated using \code{Logan_tstar}.
+#' @param tstar_type Either "frames" (default) or "time", specifying how to interpret tstar.
+#' @param tstarIncludedFrames Deprecated. Use 'tstar' with 'tstar_type="frames"' instead.
 #' @param weights Optional. Numeric vector of the weights assigned to each frame
 #'   in the fitting. We include zero at time zero: if not included, it is added.
 #'   If not specified, uniform weights will be used.
@@ -70,15 +71,44 @@
 #'
 #' @export
 
-Loganplot <- function(t_tac, tac, input, tstarIncludedFrames, weights = NULL,
-                      inpshift = 0, vB = 0, dur = NULL, frameStartEnd = NULL, timeStartEnd = NULL) {
+Loganplot <- function(t_tac, tac, input, tstar, weights = NULL,
+                      inpshift = 0, vB = 0, dur = NULL, frameStartEnd = NULL, timeStartEnd = NULL,
+                      tstar_type = "frames", tstarIncludedFrames = NULL) {
 
   # Convert timeStartEnd to frameStartEnd if needed
   if (is.null(frameStartEnd) && !is.null(timeStartEnd)) {
     frameStartEnd <- c(which(t_tac >= timeStartEnd[1])[1], 
                        tail(which(t_tac <= timeStartEnd[2]), 1))
   }
 
+  # Handle deprecated parameter
+  if (!is.null(tstarIncludedFrames)) {
+    warning("tstarIncludedFrames is deprecated and will be removed in a future version. Use 'tstar' with 'tstar_type=\"frames\"' instead", call. = FALSE)
+    if (!missing(tstar)) {
+      stop("Cannot specify both 'tstar' and 'tstarIncludedFrames'")
+    }
+    tstar <- tstarIncludedFrames
+    tstar_type <- "frames"
+  }
+
+  # Validate tstar_type
+  tstar_type <- match.arg(tstar_type, c("frames", "time"))
+
+  # Handle missing tstar
+  if (missing(tstar)) {
+    tstar <- length(t_tac)
+    tstar_type <- "frames"
+    warning("No value specified for tstar: defaulting to including all frames. This may produce biased outcomes.", call. = FALSE)
+  }
+
+  # Convert tstar based on type
+  if (tstar_type == "time") {
+    frames_after_tstar <- which(t_tac >= tstar)
+    tstarIncludedFrames <- length(frames_after_tstar)
+  } else {
+    tstarIncludedFrames <- tstar
+  }
+
   # Tidying
 
   tidyinput <- tidyinput_art(t_tac, tac, weights, frameStartEnd)

R/kinfitr_ma1.R

@@ -8,9 +8,12 @@
 #' zero: if not included, it is added.
 #' @param input Data frame containing the blood, plasma, and parent fraction concentrations over time.  This can be generated
 #' using the \code{blood_interp} function.
-#' @param tstarIncludedFrames The number of frames to be used in the regression model, i.e. the number of frames for which
-#' the function is linear after pseudo-equilibrium is reached. This is a count from the end of the measurement, so a value of
-#' 10 means that last 10 frames will be used. This value can be estimated using \code{ma1_tstar}.
+#' @param tstar The t* specification for regression. If tstar_type="frames", 
+#' this is the number of frames from the end to include (e.g., 10 means last 10 frames).
+#' If tstar_type="time", this is the time point (in minutes) after which all frames 
+#' with midpoints later than this time are included. This value can be estimated using \code{ma1_tstar}.
+#' @param tstar_type Either "frames" (default) or "time", specifying how to interpret tstar.
+#' @param tstarIncludedFrames Deprecated. Use 'tstar' with 'tstar_type="frames"' instead.
 #' @param weights Optional. Numeric vector of the weights assigned to each frame in the fitting. We include zero at time zero:
 #' if not included, it is added. If not specified, uniform weights will be used.
 #' @param inpshift Optional. The number of minutes by which to shift the timing of the input data frame forwards or backwards.
@@ -53,8 +56,9 @@
 #'
 #' @export
 
-ma1 <- function(t_tac, tac, input, tstarIncludedFrames, weights = NULL,
-                inpshift = 0, vB = 0, dur = NULL, frameStartEnd = NULL, timeStartEnd = NULL) {
+ma1 <- function(t_tac, tac, input, tstar, weights = NULL,
+                inpshift = 0, vB = 0, dur = NULL, frameStartEnd = NULL, timeStartEnd = NULL,
+                tstar_type = "frames", tstarIncludedFrames = NULL) {
 
 
   # Convert timeStartEnd to frameStartEnd if needed
@@ -63,6 +67,34 @@ ma1 <- function(t_tac, tac, input, tstarIncludedFrames, weights = NULL,
                        tail(which(t_tac <= timeStartEnd[2]), 1))
   }
 
+  # Handle deprecated parameter
+  if (!is.null(tstarIncludedFrames)) {
+    warning("tstarIncludedFrames is deprecated and will be removed in a future version. Use 'tstar' with 'tstar_type=\"frames\"' instead", call. = FALSE)
+    if (!missing(tstar)) {
+      stop("Cannot specify both 'tstar' and 'tstarIncludedFrames'")
+    }
+    tstar <- tstarIncludedFrames
+    tstar_type <- "frames"
+  }
+
+  # Validate tstar_type
+  tstar_type <- match.arg(tstar_type, c("frames", "time"))
+
+  # Handle missing tstar
+  if (missing(tstar)) {
+    tstar <- length(t_tac)
+    tstar_type <- "frames"
+    warning("No value specified for tstar: defaulting to including all frames. This may produce biased outcomes.", call. = FALSE)
+  }
+
+  # Convert tstar based on type
+  if (tstar_type == "time") {
+    frames_after_tstar <- which(t_tac >= tstar)
+    tstarIncludedFrames <- length(frames_after_tstar)
+  } else {
+    tstarIncludedFrames <- tstar
+  }
+
   # Tidying
 
   tidyinput <- tidyinput_art(t_tac, tac, weights, frameStartEnd)
@@ -210,9 +242,9 @@ plot_ma1fit <- function(ma1out, roiname = NULL) {
     roiname <- "ROI"
   }
 
-  measured <- plyr::rename(measured, c("Target.measured" = paste0(roiname, ".measured")))
+  measured <- dplyr::rename(measured, !!paste0(roiname, ".measured") := Target.measured)
 
-  fitted <- plyr::rename(fitted, c("Target.fitted" = paste0(roiname, ".fitted")))
+  fitted <- dplyr::rename(fitted, !!paste0(roiname, ".fitted") := Target.fitted)
 
   tidymeasured <- tidyr::gather(
     measured,

R/kinfitr_miscfuncs.R

@@ -397,7 +397,7 @@ fix_multstartpars <- function(start, lower, upper, multstart_iter, multstart_low
 
     ### Adding multstart boundaries
     if (!is.null(multstart_lower)) {
-      if (class(multstart_lower) != "list" ||
+      if (!inherits(multstart_lower, "list") ||
         sum(!(names(multstart_lower) %in% parnames)) > 0) { # Are there any names not in start?
         stop("multstart_lower should be a named list whose names match the parameters to be fitted")
       }
@@ -408,7 +408,7 @@ fix_multstartpars <- function(start, lower, upper, multstart_iter, multstart_low
     }
 
     if (!is.null(multstart_upper)) {
-      if (class(multstart_upper) != "list" ||
+      if (!inherits(multstart_upper, "list") ||
         sum(!(names(multstart_upper) %in% parnames)) > 0) { # Are there any names not in start?
         stop("multstart_upper should be a named list whose names match the parameters to be fitted")
       }