Merge pull request #413 from muschellij2/docfix

fixing docs and some suggests

.Rbuildignore

@@ -29,3 +29,4 @@ R/connectedThresholdImage.R
 Dockerfile
 code_of_conduct.md
 ^data-raw$
+^Makefile$

.github/workflows/R-CMD-check.yaml

@@ -53,7 +53,17 @@ jobs:
             ${{ runner.os }}-${{ hashFiles('.github/R-version') }}-1
             ${{ runner.os }}-${{ hashFiles('.github/R-version') }}
             ${{ runner.os }}-
+
+      - name: Build HDF5 - OSX
+        if: runner.os == 'macOS'
+        run: |
+          brew install hdf5
           
+      - name: Build HDF5 - LINUX
+        if: runner.os == 'Linux'
+        run: |
+          sudo apt-get install -y libhdf5-dev
+
       - name: Install dependencies
         run: |
           remotes::install_deps(dependencies = TRUE)

DESCRIPTION

@@ -43,7 +43,6 @@ Suggests:
     caret,
     cluster,
     corpcor,
-    dplyr,
     e1071,
     fastICA,
     fpc,
@@ -79,7 +78,11 @@ Suggests:
     tsne,
     viridis,
     xgboost,
-    FNN
+    FNN,
+    gridExtra,
+    hdf5r,
+    salad,
+    reshape2
 LazyData: TRUE
 Remotes: ANTsX/ANTsRCore
 VignetteBuilder: knitr

R/antsApplyTransforms.R

@@ -14,7 +14,7 @@
 #' @param transformlist character vector of transforms generated by antsRegistration where
 #' each transform is a filename.
 #' @param interpolator Choice of interpolator.  Supports partial matching.
-#' \itemize{
+#' \describe{
 #' \item{linear}{}
 #' \item{nearestNeighbor}{}
 #' \item{multiLabel}{ for label images but genericlabel is preferred}

R/antsImageHeaderInfo.R

@@ -10,7 +10,7 @@
 #' antsImageHeaderInfo(getANTsRData("r16"))
 #'
 #' @return outputs a list containing:
-#' \itemize{
+#' \describe{
 #'   \item{pixelclass: }{Type of pixel (scalar, vector, etc).}
 #'   \item{pixeltype: }{Type of pixel values (int, float, etc).}
 #'   \item{nDimensions: }{Number of image dimensions.}

R/antsMotionCalculation.R

@@ -27,7 +27,7 @@
 #' @param ... additional argument to \code{\link{.motion_correction}}
 #'
 #' @return List containing:
-#' \itemize{
+#' \describe{
 #'  \item{moco_img}{ Motion corrected time-series image.}
 #'  \item{moco_params}{ Data frame of translation parameters.}
 #'  \item{moco_avg_img}{ Average motion-corrected image.}

R/antsRegistration.R

@@ -53,7 +53,7 @@
 #' @param ... additional options see antsRegistration in ANTs
 #' @details
 #' typeofTransform can be one of:
-#' \itemize{
+#' \describe{
 #'   \item{"Translation": }{Translation transformation.}
 #'   \item{"Rigid": }{Rigid transformation: Only rotation and translation.}
 #'   \item{"Similarity": }{Similarity transformation: scaling, rotation and
@@ -111,7 +111,7 @@
 #'   \item{"antsRegistrationSyNQuickRepro[x]":}{quick reproducible registration.  x options as above.}
 #' }
 #' @return outputs a list containing:
-#' \itemize{
+#' \describe{
 #'   \item{warpedmovout: }{Moving image warped to space of fixed image.}
 #'   \item{warpedfixout: }{Fixed image warped to space of moving image.}
 #'   \item{fwdtransforms: }{Transforms to move from moving to fixed image.}

R/antsrMetric_class.R

@@ -59,7 +59,7 @@ setMethod(f = "initialize", signature(.Object = "antsrMetric"), definition = fun
 #' @param fixed the fixed antsImage
 #' @param moving the moving antsImage
 #' @param type image metric to calculate
-#' \itemize{
+#' \describe{
 #'   \item{MeanSquares}{}
 #'   \item{Correlation}{}
 #'   \item{ANTSNeighborhoodCorrelation}{}
@@ -72,7 +72,7 @@ setMethod(f = "initialize", signature(.Object = "antsrMetric"), definition = fun
 #' @param fixed.mask mask for the fixed image
 #' @param moving.mask mask for the moving image
 #' @param sampling.strategy sampling strategy, default if full sampling
-#' \itemize{
+#' \describe{
 #'   \item{none}{Full sampling}
 #'   \item{random}{}
 #'   \item{regular}{}
@@ -283,7 +283,7 @@ antsrMetricSetRadius <- function(metric, radius) {
 #' @description set image sampling strategy and rate
 #' @param metric an 'antsrMetric'
 #' @param sampling.strategy sampling strategy, default if full sampling
-#' \itemize{
+#' \describe{
 #'   \item{none}{Full sampling}
 #'   \item{random}{}
 #'   \item{regular}{}

R/antsrMotionCalculation.R

@@ -22,7 +22,7 @@
 #' for discussion.  If \code{NULL}, will not set anything.
 #' @param ... extra parameters passed to antsRegistration
 #' @return List containing:
-#' \itemize{
+#' \describe{
 #'  \item{moco_img}{ Motion corrected time-series image.}
 #'  \item{moco_params}{ Data frame of translation parameters.}
 #'  \item{moco_avg_img}{ Average motion-corrected image.}

R/antsrTransform_class.R

@@ -59,7 +59,7 @@ setMethod(f = "initialize", signature(.Object = "antsrTransform"), definition =
 #' @title createAntsrTransform
 #' @description Create and initialize an antsrTransform
 #' @param type type of transform
-#' \itemize{
+#' \describe{
 #'   \item{AffineTransform}{}
 #'   \item{CenteredAffineTransform}{}
 #'   \item{Euler2DTransform}{}

R/aslAveraging.R

@@ -15,7 +15,7 @@
 #'
 #' @details
 #' Two major types of methods are available for ASL signal averaging:
-#' \itemize{
+#' \describe{
 #'    \item{Subtraction}{: All the subtraction methods are based on subtracting
 #'     the tag from control images and averaging the result.  \code{simple}
 #'     subtracts adjacent tag and control images.  The other methods use
@@ -29,7 +29,7 @@
 #'    similar perfusion values.}
 #'  }
 #' For \code{bayesian}, two more arguments are required:
-#' \itemize{
+#' \describe{
 #'   \item{segmentation}{: a segmentation image}
 #'   \item{tissuelist}{: a list of tissue probability images}
 #' }

R/aslCensoring.R

@@ -10,12 +10,12 @@
 #' @param ... Additional arguments to pass to censoring method.  See \code{Details.}
 #' @details \code{aslCensoring} is an interface to ASL timepoint censoring algorithms.
 #' Three options are currently provided, with different additional arguments:
-#' \enumerate{
+#' \describe{
 #'  \item{\code{outlier}}{ Outlier rejection from Tan et al.  This method rejects
 #'    volumes that are either far from the mean of the time-series or whose
 #'    standard deviation is far from the standard deviations of the individual volumes.
 #'    Accepts two additional arguments:
-#'      \itemize{
+#'      \describe{
 #'         \item{\code{sigma.mean}: }{how many standard
 #'         deviations the mean of the volume can be from the
 #'         mean of all the volumes before
@@ -27,7 +27,7 @@
 #' }
 #'  \item{\code{robust}}{ Uses a robust regression approach to estimate volumes
 #'    with high leverage.  Accepts three arguments:
-#'    \itemize{
+#'    \describe{
 #'      \item{\code{nuis}:}{ Nuisance regressors to use as covariates.}
 #'      \item{\code{robthresh}:}{ Threshold for weights on leverage estimates.  Points
 #'         with weights under this value will be thrown out; defaults to 0.95.}

R/euler.R

@@ -6,11 +6,11 @@
 #' @param u statistical value (typically the maxima of a cluster or statistical field)
 #' @param df degrees of freedom expressed as df = c(degrees of interest, degrees of error)
 #' @param fieldType
-#' \itemize{
-#' \item{T: } {T-field}
-#' \item{F: } {F-field}
-#' \item{X: } {Chi-square field'}
-#' \item{Z: } {Gaussian field}
+#' \describe{
+#' \item{T: }{T-field}
+#' \item{F: }{F-field}
+#' \item{X: }{Chi-square field'}
+#' \item{Z: }{Gaussian field}
 #' }
 #' @return A vector of estimated euler characteristics for dimensions 0:D
 #'

R/fitBsplineObjectToScatteredData.R

@@ -4,7 +4,7 @@
 #' 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{
+#' \describe{
 #'     \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}

R/getMask.R

@@ -3,8 +3,11 @@
 #' Get a binary mask image from the given image after thresholding.
 #'
 #' If \code{cleanup} is \code{>0}, the following steps are applied
-#' \enumerate{ \item Erosion with radius 2 voxels \item Retain largest
-#' component \item Dilation with radius 1 voxel \item Morphological closing }
+#' \enumerate{ 
+#' \item Erosion with radius 2 voxels 
+#' \item Retain largest component 
+#' \item Dilation with radius 1 voxel \item Morphological closing 
+#' }
 #'
 #' These functions are available in \link{iMath}, see the operations
 #' \dQuote{ME}, \dQuote{GetLargestComponent}, \dQuote{MD}, \dQuote{FillHoles}.

R/getNeighborhood.R

@@ -8,7 +8,7 @@
 #' @param physical.coordinates a logical indicating if voxel indices and
 #' offsets should be in voxel or physical coordinates
 #' @return a list
-#' \itemize{
+#' \describe{
 #'   \item{values}{numeric vector of values}
 #'   \item{indices}{matrix providing the coordinates for each value}
 #' }
@@ -88,7 +88,7 @@ getNeighborhoodAtVoxel <- function(image, center, kernel, physical.coordinates =
 #' center voxel) should be returned in addition to the value matrix (WIP)
 #' @details
 #' \code{boundary.condition} should be one of:
-#' \itemize{
+#' \describe{
 #'   \item{\code{NA}: }{Fill values with \code{NA}.}
 #'   \item{\code{image}: }{Use image value, even if not in mask.}
 #'   \item{\code{mean}: }{Use man of all non-\code{NA} values for that neighborhood.}
@@ -99,7 +99,7 @@ getNeighborhoodAtVoxel <- function(image, center, kernel, physical.coordinates =
 #' is the size of the neighborhood and there is a column for each voxel
 #'
 #' if \code{spatial.info} is true, a list containing three matrices:
-#' \itemize{
+#' \describe{
 #'  \item{values: }{matrix of pixel values where the number of rows
 #'  is the size of the neighborhood and there is a column for each voxel.}
 #'  \item{indices: }{matrix providing the center coordinates for each neighborhood}

R/imageSimilarity.R

@@ -3,7 +3,7 @@
 #' @param fixed the fixed antsImage
 #' @param moving the moving antsImage
 #' @param type image metric to calculate
-#' \itemize{
+#' \describe{
 #'   \item{MeanSquares}{}
 #'   \item{Correlation}{}
 #'   \item{ANTSNeighborhoodCorrelation}{}
@@ -14,7 +14,7 @@
 #' @param fixed.mask mask for the fixed image
 #' @param moving.mask mask for the moving image
 #' @param sampling.strategy sampling strategy, default if full sampling
-#' \itemize{
+#' \describe{
 #'   \item{none}{Full sampling}
 #'   \item{random}{}
 #'   \item{regular}{}

R/labelImageRegistration.R

@@ -35,7 +35,7 @@
 #' @param randomSeed Definition for deformable registration.
 #' @param verbose Print progress to the screen.
 #' @return outputs a list containing:
-#' \itemize{
+#' \describe{
 #'   \item{fwdtransforms: }{Transforms to move from moving to fixed image.}
 #'   \item{invtransforms: }{Transforms to move from fixed to moving image.}
 #' }
@@ -415,4 +415,4 @@ labelImageRegistration <- function( fixedLabelImages, movingLabelImages,
 
   return( list( fwdtransforms = fwdtransforms,
                 invtransforms = invtransforms ) )
-}
+}

R/morphology.R

@@ -5,21 +5,21 @@
 #'
 #' @param input input image
 #' @param operation operation to apply
-#'  \itemize{
+#'  \describe{
 #'  \item{"close"}{ Morpholgical closing}
 #'  \item{"dilate"}{ Morpholgical dilation}
 #'  \item{"erode"}{ Morpholgical erosion}
 #'  \item{"open"}{ Morpholgical opening}
 #'  }
 #' @param type type of morphology
-#'  \itemize{
+#'  \describe{
 #'  \item{"binary"}{ Binary operation on a single value}
 #'  \item{"grayscale"}{ Grayscale operations}
 #'  }
 #' @param radius radius of structuring element
 #' @param value value to operation on (type='binary' only)
 #' @param shape shape of the structuring element ( type='binary' only )
-#'  \itemize{
+#'  \describe{
 #'  \item{"ball"}{ spherical structuring element}
 #'  \item{"box"}{ box shaped structuring element}
 #'  \item{"cross"}{ cross shaped structuring element}