R/fitBsplineObjectToScatteredData.R

In stnava/ANTsR: ANTs in R: Quantification Tools for Biomedical Images

#' fitBsplineObjectToScatteredData
#'
#' Fit a b-spline object to scattered data.  This is basically a wrapper
#' for the ITK filter \url{https://itk.org/Doxygen/html/classitk_1_1BSplineScatteredDataPointSetToImageFilter.html}.
#' This filter is flexible in the possible objects that can be approximated.
#' Possibilities include:
#' \itemize{
#'     \item{curve:}{1/2/3/4-D}
#'     \item{surface:}{2-D surface in 3-D space (not available/templated)}
#'     \item{scalar:}{2/3/4-D scalar field}
#'     \item{displacement:}{2/3-D displacement field}
#'     \item{displacement:}{2/3-D time-varying velocity field}
#' }
#' In order to understand the input parameters, it is important to understand
#' the difference between the parametric and data dimensions.  A curve as one
#' parametric dimension but the data dimension can be 1-D, 2-D, 3-D, or 4-D.
#' In contrast, a 3-D displacement field has a parametric and data dimension
#' of 3.  The scattered data is what's approximated by the B-spline object and
#' the parametric point is the location of scattered data within the domain of
#' the B-spline object.
#'
#' @param scatteredData matrix defining the scattered data input to be approximated.
#' Data is organized by row --> data v, column ---> data dimension.
#' @param parametricData matrix defining the parametric location of the scattered
#' data.  Data is organized by row --> parametric point, column --> parametric
#' dimension.  Note that each row corresponds to the same row in the
#' \code{scatteredData}.
#' @param dataWeights vector defining the individual weighting of the corresponding
#' scattered data value.  Default = NULL meaning all values are weighted the same.
#' @param parametricDomainOrigin vector defining the parametric origin of the B-spline
#' object.
#' @param parametricDomainSpacing vector defining the parametric spacing of the B-spline
#' object.  Defines the sampling rate in the parametric domain.
#' @param parametricDomainSize vector defining the size (length) of the
#' B-spline object.  Note that the length of the B-spline object in dimension \code{d}
#' is defined as \code{parametricDomainSpacing[d] * (parametricDomainSize[d]-1)}.
#' @param isParametricDimensionClosed vector of bools defining whether or not the
#' corresponding parametric dimension is closed (e.g., closed loop).  Default = FALSE.
#' @param numberOfFittingLevels integer specifying the number of fitting levels.
#' @param meshSize vector defining the mesh size at the initial fitting level.
#' @param splineOrder spline order of the B-spline object.  Default = 3.
#' @return Matrix for B-spline curve.  Otherwise, returns ANTsR image.
#'
#' @author NJ Tustison
#'
#' @examples
#'
#' # Perform 2-D curve example
#'
#' x <- seq(from = -4, to = 4, by = 0.1)
#' y <- exp(-(x * x)) + runif(length(x), min = -0.1, max = 0.1)
#' u <- seq(from = 0.0, to = 1.0, length.out = length(x))
#' scatteredData <- cbind(x, y)
#' parametricData <- as.matrix(u, ncol = 1)
#' numberOfSamplePoints <- 100
#' spacing <- 1 / (numberOfSamplePoints - 1) * 1.0
#' bsplineCurve <- fitBsplineObjectToScatteredData(scatteredData, parametricData,
#'   parametricDomainOrigin = c(0.0), parametricDomainSpacing = c(spacing),
#'   parametricDomainSize = c(numberOfSamplePoints), isParametricDimensionClosed = c(FALSE),
#'   numberOfFittingLevels = 5, meshSize = 1
#' )
#'
#' plot(x, y, "p", col = "red")
#' points(scatteredData[, 1], scatteredData[, 2], col = "green")
#' lines(bsplineCurve[, 1], bsplineCurve[, 2], col = "blue")
#'
#' # Perform 2-D scalar field (i.e., image) example
#'
#' numberOfRandomPoints <- 10000
#'
#' img <- antsImageRead(getANTsRData("r16"))
#' imgArray <- as.array(img)
#' rowIndices <- sample(2:(dim(imgArray)[1] - 1), numberOfRandomPoints, replace = TRUE)
#' colIndices <- sample(2:(dim(imgArray)[2] - 1), numberOfRandomPoints, replace = TRUE)
#'
#' scatteredData <- as.matrix(array(data = 0, dim = c(numberOfRandomPoints, 1)))
#' parametricData <- as.matrix(array(data = 0, dim = c(numberOfRandomPoints, 2)))
#' for (i in seq_len(numberOfRandomPoints))
#' {
#'   scatteredData[i, 1] <- imgArray[rowIndices[i], colIndices[i]]
#'   parametricData[i, 1] <- rowIndices[i]
#'   parametricData[i, 2] <- colIndices[i]
#' }
#'
#' bsplineImage <- fitBsplineObjectToScatteredData(scatteredData, parametricData,
#'   parametricDomainOrigin = c(0.0, 0.0), parametricDomainSpacing = c(1.0, 1.0),
#'   parametricDomainSize = dim(img),
#'   numberOfFittingLevels = 7, meshSize = c(1, 1)
#' )
#' plot(bsplineImage)
#'
#' @export fitBsplineObjectToScatteredData

fitBsplineObjectToScatteredData <- function(
    scatteredData,
    parametricData,
    parametricDomainOrigin,
    parametricDomainSpacing,
    parametricDomainSize,
    isParametricDimensionClosed = NULL,
    dataWeights = NULL,
    numberOfFittingLevels = 4,
    meshSize = 1,
    splineOrder = 3) {
  if (missing(scatteredData)) {
    stop("Error: missing scatteredData.")
  }

  if (missing(parametricData)) {
    stop("Error: missing parametricData.")
  }
  parametricDimension <- ncol(parametricData)

  if (is.null(isParametricDimensionClosed)) {
    isParametricDimensionClosed <- rep(FALSE, parametricDimension)
  }

  if (length(meshSize) != 1 && length(meshSize) != parametricDimension) {
    stop("Error:  incorrect specification for meshSize.")
  }
  if (length(parametricDomainOrigin) != parametricDimension) {
    stop("Error:  origin is not of length parametricDimension.")
  }
  if (length(parametricDomainSpacing) != parametricDimension) {
    stop("Error:  spacing is not of length parametricDimension.")
  }
  if (length(parametricDomainSize) != parametricDimension) {
    stop("Error:  size is not of length parametricDimension.")
  }
  if (length(isParametricDimensionClosed) != parametricDimension) {
    stop("Error:  closed is not of length parametricDimension.")
  }

  numberOfControlPoints <- meshSize + splineOrder

  if (length(numberOfControlPoints) == 1) {
    numberOfControlPoints <- rep(numberOfControlPoints, parametricDimension)
  }

  if (nrow(parametricData) != nrow(scatteredData)) {
    stop("Error:  the number of points is not equal to the number of scattered data values.")
  }

  if (is.null(dataWeights)) {
    dataWeights <- rep(1.0, nrow(parametricData))
  }
  if (length(dataWeights) != nrow(parametricData)) {
    stop("Error:  the number of weights is not the same as the number of points.")
  }

  bsplineObject <- ANTsRCore::fitBsplineObjectToScatteredData(
    scatteredData, parametricData, dataWeights,
    parametricDomainOrigin, parametricDomainSpacing,
    parametricDomainSize, isParametricDimensionClosed,
    numberOfFittingLevels, numberOfControlPoints,
    splineOrder
  )
  return(bsplineObject)
}