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Commit02b88e1

Browse files
committed
Preparing for CRAN submission
1 parentcf16688 commit02b88e1

21 files changed

+179
-138
lines changed

‎.Rbuildignore‎

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^_pkgdown\.yml$
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^docs$
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^pkgdown$
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^CRAN-SUBMISSION$

‎CRAN-SUBMISSION‎

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Version: 1.0.0
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Date: 2024-07-14 16:18:21 UTC
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SHA: cf16688021606b21a9f4ec274e2dd4ebd51210dc

‎LICENSE‎

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YEAR:2020
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YEAR:2024
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COPYRIGHT HOLDER: Pablo Paccioretti

‎LICENSE.md‎

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#MIT License
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Copyright (c)2020 Pablo Paccioretti
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Copyright (c)2024 Pablo Paccioretti
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal

R/compare_zones.R renamed to R/compare_zone.R

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#' @param grid_dim \code{numeric} grid dimentins to estimate spatial variance
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#'
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#' @return \code{list} with differences and descriptive_stat
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#' @references
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#' Paccioretti, P., Córdoba, M., & Balzarini, M. (2020).
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#' FastMapping: Software to create field maps and identify management zones
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#' in precision agriculture. Computers and Electronics in Agriculture, 175,
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#' 105556 https://doi.org/10.1016/j.compag.2020.105556.
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#' @export
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#'
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#' @examples
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#' @example inst/examples/compare_zone.R
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#'
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#' library(sf)
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#' data(wheat, package = "paar")
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#'
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#' ##Convert to an sf object
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#' wheat <- sf::st_as_sf(wheat,
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#' coords = c("x", "y"),
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#' crs = 32720)
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#' clusters <- paar::kmspc(
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#' wheat,
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#' variables = c('CE30', 'CE90', 'Elev', 'Pe', 'Tg'),
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#' number_cluster = 3:4
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#' )
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#' data_clusters <- cbind(wheat, clusters$cluster)
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#' compare_zone(data_clusters,
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#' "Elev",
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#' "Cluster_3")
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compare_zone<-function(data,
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variable,
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if (chequeo>n)
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break
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for (iinj:n) {
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# browser()
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stest<-Qm[q[i],q[j]]>alpha
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if (stest) {
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if (lastC(M[i])!=letras[k]) {
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cambio1<-0
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ja<-j
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for (jjincambio:n)
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M[jj]<- paste(M[jj],"",sep="")# El espacio
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M[jj]<- paste(M[jj],"",sep="")
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M[cambio]<- paste(M[cambio],letras[k],sep="")
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for (vinja:cambio) {
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if (Qm[q[v],q[cambio]]<=alpha) {
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if (cambio1==0)
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j<-j+1
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}
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#-----------
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# browser()
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w<-data.frame(w,stat=M)
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if (k>81
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)
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cat(
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"\n",
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k,
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"groups are estimated.The number of groups exceeded the maximum of 81 labels.change to group=FALSE.\n"
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"groups are estimated.The number of groups exceeded the maximum of 81 labels.Change to group=FALSE.\n"
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)
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invisible(w)
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}

‎R/depurate.R‎

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#' outliers and spatial outliers or local defective observations. Default
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#' values are optimized for precision agricultural data.
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#'
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#' @inheritParams remove_border
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#' @inheritParams remove_outlier
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#'@inheritParams remove_inlier
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#' @param x an \code{sf} points object
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#' @param y \code{character} with the name of the variable to use for
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#' depuration/filtering process
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#' @param toremove \code{character} vector specifying the procedure to
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#' implement for errors removal. Default 'edges', 'outlier', 'inlier'.
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#' See Details.
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#' @param crs coordinate reference system: integer with the EPSG code,
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#' or character with proj4string to convert coordinates if \code{x} has
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#' longitude/latitude data
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#' @param buffer \code{numeric} distance in meters to be removed. Negative
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#' values are recommended
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#' @param ylimitmax \code{numeric} of length 1 indicating the maximum limit
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#' for the \code{y} variable. If \code{NA} \code{Inf} is assumed
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#' @param ylimitmin \code{numeric} of length 1 indicating the minimum limit
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#' for the \code{y} variable. If \code{NA} \code{-Inf} is assumed
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#' @param sdout \code{numeric} values outside the interval
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#' \eqn{mean ± sdout × sdout} values will be removed
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#' @param ldist \code{numeric} lower distance bound to identify neighbors
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#' @param udist \code{numeric} upper distance bound to identify neighbors
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#' @param criteria \code{character} with "LM" and/or "MP" for methods to
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#' identify spatial outliers
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#' @param zero.policy default NULL, use global option value;
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#' if FALSE stop with error for any empty neighbors sets,
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#' if TRUE permit the weights list to be formed with zero-length
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#' weights vectors
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#' @param poly_border \code{sf} object with one polygon or NULL. Can be
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#' the result of \code{concaveman::concaveman}
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#'
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#' @details
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#' Possible values for \code{toremove} are one or more elements of:
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#' automating error removal from yield maps. Precision Agric 20, 1030–1044
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#' (2019). https://doi.org/10.1007/s11119-018-09632-8
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#'
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#' @return an object of class \code{paar}
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#' @return an object of class \code{paar} with two elements:
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#' \describe{
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#' \item{depurated_data}{\code{sf} object with the data after the removal
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#' process}
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#' \item{condition}{\code{character} vector with the condition of each
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#' observation}
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#' }
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#' @export
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#' @example inst/examples/depurate.R
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#' values are recommended
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#' @param poly_border \code{sf} object with one polygon or NULL. Can be
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#' the result of \code{concaveman::concaveman}
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#'
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#' @noRd
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#' @keywords internal
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remove_border<-function(x,
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crs=NULL,
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buffer,
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#' for the \code{y} variable. If \code{NA} \code{-Inf} is assumed
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#' @param sdout \code{numeric} values outside the interval
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#' \eqn{mean ± sdout × sdout} values will be removed
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#'
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#'
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#' @noRd
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#' @keywords internal
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remove_outlier<-function(x,
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y,
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ylimitmax=NA,
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#' if FALSE stop with error for any empty neighbors sets,
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#' if TRUE permit the weights list to be formed with zero-length
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#' weights vectors
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#'
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#' @noRd
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#' @keywords internal
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remove_inlier<-function(x,
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y,
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ldist=0,
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#' @param is_error internal object
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#' @param remove_result internal results from remove_* functions
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#' @noRd
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#' @keywords internal
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is_error_update<-function(is_error,remove_result) {
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# Keeps NA, others are conditions
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is_error_no_na<-is_error[is.na(is_error$because),]

‎R/fuzzy_k_means.R‎

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#' @return a list with classification results and indices to select best number of
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#' clusters.
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#' @export
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#' @example inst/examples/fuzzy_k_means.R
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#'
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fuzzy_k_means<-function(data,
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variables,

‎R/kmspc.R‎

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#' MULTISPATI-PCA clustering
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#'
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#'
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#' @inheritParamsremove_inlier
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#' @inheritParamsdepurate
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#' @param data sf object
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#' @param variables variables to use for clustering, if missing, all numeric
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#' variables will be used

‎R/spatial_t_test.R‎

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#' columns \code{matrix} or \code{data.frame} specifying coordinates.
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#'
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#' @param variables \code{character} vector with column names to perform ttest
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#'
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#' @return a data.frame with the correlation and p-value for each pair
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#' of variables
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#' @export
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spatial_t_test<-function(data,variables) {
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if (!requireNamespace("SpatialPack",quietly=TRUE)) {
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stop(paste0("SpatialPack package is needed to perform spatial_t_test","\n",
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"Install it with 'install.packages(SpatialPack)'"),
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"Install it with 'install.packages(\'SpatialPack\')'"),
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.call=FALSE)
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}
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‎README.Rmd‎

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##Installation
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<!--You can install the released version of paar from [CRAN](https://CRAN.R-project.org) with:-->
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You can install the released version of paar from[CRAN](https://CRAN.R-project.org) with (not-yet):
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<!--``` r-->
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<!-- install.packages("paar")-->
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<!--```-->
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```r
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# install.packages("paar")
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```
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You can install the development version from[GitHub](https://github.com/PPaccioretti/paar) with:
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```r

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