Improve doc here and there + NEWS

NEWS

@@ -7,13 +7,14 @@ This release has received external contributions from K. Siteur
 Improvements: 
 
   * The type of neighborhood can now be specified in all patch-related functions, 
-      including high-level functions (e.g. patchdistr_sews)
+      including high-level functions (e.g. patchdistr_sews). Neighborhood can also be 
+      specified using "von_neumann" or "moore", on top of a 3x3 matrix
 
 New indicators: 
 
   * Clustering of pairs (e.g. Schneider et al. 2016)
 
-  * Indicators based on the LSW distribution (Siteur et al. 2023)
+  * Indicators related to the LSW distribution (Siteur et al. 2023)
 
 Bug fixes: 
 

R/extra_doc.R

@@ -39,46 +39,46 @@
 #' 
 #' A \code{simple_sews_single} object is a list with the following components
 #'   \itemize{
-#'     \item{value: }{the indicator values. A vector of length one if there is 
+#'     \code{itemvalue}: the indicator values. A vector of length one if there is 
 #'       only one numeric value returned by the indicator function (e.g.
-#'       \code{\link{flowlength_sews}}, or with a length above one otherwise}
-#'     \item{orig_data: }{the original matrix on which the indicator was computed} 
-#'     \item{fun.args: }{the argument used in the call to the indicator function 
+#'       \code{\link{flowlength_sews}}, or with a length above one otherwise
+#'     \item \code{orig_data}: the original matrix on which the indicator was computed
+#'     \item \code{fun.args}: the argument used in the call to the indicator function 
 #'       (the function that given a matrix, returns the spatial metrics of
-#'       interest)}
-#'     \item{taskname: }{a character string describing the current indicator(s) 
-#'       being computed}
-#'     \item{indicf: }{the indicator function, which given the matrix, returns the
-#'       spatial metric(s) of interest}
+#'       interest)
+#'     \item \code{taskname}: a character string describing the current indicator(s) 
+#'       being computed
+#'     \item \©ode{indicf}: the indicator function, which given the matrix, returns the
+#'       spatial metric(s) of interest
 #'   }
 #' 
 #'   \code{simple_sews_test_single} have all of the above components, plus 
 #' the following: 
 #' 
 #' \itemize{ 
-#'   \item{nulldistr: }{the null distribution of values, with nulln rows and 
+#'   \item \code{nulldistr}: the null distribution of values, with nulln rows and 
 #'     as many columns as the number of values returned by the indicator 
-#'     function}
-#'   \item{null_mean: }{the mean indicator values in the null distribution}
-#'   \item{null_sd: }{the standard deviation of the null distribution}
-#'   \item{null_qsup: }{the upper quantile of the null distribution, by default 
+#'     function
+#'   \item \code{null_mean}: the mean indicator values in the null distribution
+#'   \item \code{null_sd}: the standard deviation of the null distribution
+#'   \item \code{null_qsup}: the upper quantile of the null distribution, by default 
 #'     the 95% upper quantile, but see \code{\link{indictest}} for a way to 
-#'     adjust this}
-#'   \item{null_qinf: }{the upper quantile of the null distribution, by default 
+#'     adjust this
+#'   \item \code{null_qinf}: the upper quantile of the null distribution, by default 
 #'     the 05% upper quantile, but see \code{\link{indictest}} for a way to 
-#'     adjust this}
-#'   \item{z_score: }{the z_score of the observed value relative to the null 
-#'     distribution, i.e. (value - null_mean) / null_sd}
-#'   \item{pval: }{the p-value of the indicator, i.e. the proporation of values 
-#'     of the null distribution that fall below the observed indicator value}
-#'   \item{null_method: }{the method used to produce the null matrices. See 
-#'     \code{\link{indictest}} for details}
-#'   \item{nulln: }{the number of null matrices used}
-#'   \item{get_nullmat: }{a function that can be called to obtain a randomized 
-#'     matrix}
-#'   \item{matrixn: }{the number of the matrix, can be above one if the
+#'     adjust this
+#'   \item \code{z_score}: the z_score of the observed value relative to the null 
+#'     distribution, i.e. (value - null_mean) / null_sd
+#'   \item \code{pval}: the p-value of the indicator, i.e. the proporation of values 
+#'     of the null distribution that fall below the observed indicator value
+#'   \item \code{null_method}: the method used to produce the null matrices. See 
+#'     \code{\link{indictest}} for details
+#'   \item \code{nulln}: the number of null matrices used
+#'   \item \code{get_nullmat}: a function that can be called to obtain a randomized 
+#'     matrix
+#'   \item \code{matrixn}: the number of the matrix, can be above one if the
 #'     computations have been run on a list of matrices, or non-existent if 
-#'     only one matrix was used}
+#'     only one matrix was used
 #' }
 #' 
 #' @seealso \code{\link{custom_indicator}} 

R/fitpsd.R

@@ -213,22 +213,21 @@ pl_ll <- function(dat, expo, xmin) {
 #' @return A list containing at list the following components: 
 #'
 #' \itemize{ 
-#'    \item{type: }{The type of distribution fitted (as a character string)}
-#'    \item{method: }{The method used for the fit - here, maximum likelihood,
-#'                  'll'}
-#'    \item{ll: }{The log likelihood at the estimated parameter values}
-#'    \item{xmin: }{The value of xmin used for the fit}
-#'    \item{npars: }{The number of parameters of the distribution}
+#'    \item \code{type}: The type of distribution fitted (as a character string)
+#'    \item \code{method}: The method used for the fit - here, maximum likelihood, 'll'
+#'    \item \code{ll}: The log likelihood at the estimated parameter values
+#'    \item \code{xmin}: The value of xmin used for the fit
+#'    \item \code{npars}: The number of parameters of the distribution
 #'  }
 #' 
-#' Additionnaly, this list may have one or more of the following parameters 
-#'   depending on the type of distribution that has been fitted: 
+#' Additionally, this list may have one or more of the following elements depending on 
+#'   the type of distribution that has been fitted: 
 #'   \itemize{ 
-#'     \item{plexpo: }{The exponent of the power-law}
-#'     \item{cutoff: }{The rate of truncation, for truncated power law and 
-#'                 exponential fits}
-#'     \item{meanlog: }{The mean of the lognormal distribution}
-#'     \item{sdlog: }{The s.d. of the lognormal distribution}
+#'     \item \code{plexpo}: The exponent of the power-law
+#'     \item \code{cutoff}: The rate of truncation, for truncated power law and 
+#'                 exponential fits
+#'     \item \code{meanlog}: The mean of the lognormal distribution
+#'     \item \code{sdlog}: The s.d. of the lognormal distribution
 #'   }
 #' 
 #' @details These functions will fit distributions to a set of values using 

R/indicator_psdtype.R

@@ -33,10 +33,9 @@
 #'  matrix when reaching the side 
 #' 
 #' @param nbmask Either "moore" for 8-way neighborhood, "von_neumann" for four-way 
-#'   neighborhood (default), or a square matrix with an odd number of lines and columns 
-#'   that describes which neighbors are to be considered around a cell. Default 
-#'   is 4-way or Von Neumann neighborhood (the neighborhood of a cell comprises the cell 
-#'   above, below, on the right and on the left of the target cell). 
+#'   neighborhood (default), or a 3x3 matrix describing which neighbors to 
+#'   consider around a cell. See \code{\link{patchsizes}} for details on how to specify 
+#'   such neighborhoods.
 #' 
 #' @return A data.frame (or a list of these if x is a list) with the 
 #'   following columns:

R/label.R

@@ -5,10 +5,9 @@
 #' @param mat A binary matrix
 #' 
 #' @param nbmask Either "moore" for 8-way neighborhood, "von_neumann" for four-way 
-#'   neighborhood, or a square matrix with an odd number of lines and columns that 
-#'   describes which neighbors are to be considered around a cell. Default 
-#'   is 4-way or Von Neumann neighborhood (the neighborhood of a cell comprises the cell 
-#'   above, below, on the right and on the left of the target cell). 
+#'   neighborhood (default), or a 3x3 matrix describing which neighbors to 
+#'   consider around a cell. See \code{\link{patchsizes}} for details on how to specify 
+#'   such neighborhoods.
 #' 
 #' @param wrap Whether to wrap around lattice boundaries (`TRUE`/`FALSE`), 
 #'   effectively using periodic boundaries.
@@ -122,10 +121,9 @@ percolation <- function(mat, nbmask = "von_neumann") {
 #'   be pooled together if \code{mat} is a list of matrices. 
 #' 
 #' @param nbmask Either "moore" for 8-way neighborhood, "von_neumann" for four-way 
-#'   neighborhood, or a square matrix with an odd number of lines and columns that 
-#'   describes which neighbors are to be considered around a cell. Default 
-#'   is 4-way or Von Neumann neighborhood (the neighborhood of a cell comprises the cell 
-#'   above, below, on the right and on the left of the target cell). 
+#'   neighborhood (default), or a 3x3 matrix describing which neighbors to 
+#'   consider around a cell. See \code{\link{patchsizes}} for details on how to specify 
+#'   such neighborhoods.
 #' 
 #' @param wrap Whether to wrap around lattice boundaries (`TRUE`/`FALSE`), 
 #'   effectively using periodic boundaries.

R/task_patch_indic.R

@@ -28,9 +28,9 @@
 #'  matrix when reaching the side 
 #' 
 #' @param nbmask Either "moore" for 8-way neighborhood, "von_neumann" for four-way 
-#'   neighborhood (default), or a square matrix with an odd number of lines and columns 
-#'   that describes which neighbors are to be considered around a cell. See
-#'   \code{\link{patchsizes}} for details on how to specify more advanced neighborhoods.
+#'   neighborhood (default), or a 3x3 matrix describing which neighbors to 
+#'   consider around a cell. See \code{\link{patchsizes}} for details on how to specify 
+#'   such neighborhoods.
 #' 
 #' @return A list object of class 'psdfit' containing among other things 
 #'   - the observed patch size distribution data