From 698a02879311e01802ff473bd97cd3bcf831f8bc Mon Sep 17 00:00:00 2001
From: SpatLyu <lyu.geosocial@gmail.com>
Date: Tue, 24 Sep 2024 21:18:48 +0800
Subject: [PATCH] update rgd to fix #2

---
 R/rgd.R    | 47 +++++++++++++++++++++--------------------------
 man/rgd.Rd | 29 +++++++----------------------
 2 files changed, 28 insertions(+), 48 deletions(-)

diff --git a/R/rgd.R b/R/rgd.R
index 466ca7b4..9426ce8e 100644
--- a/R/rgd.R
+++ b/R/rgd.R
@@ -23,6 +23,7 @@
 #' @return A list of the RGD model result.
 #' \describe{
 #' \item{\code{factor}}{the result of RGD model}
+#' \item{\code{disc}}{robust discrete results}
 #' }
 #' @export
 #'
@@ -32,9 +33,9 @@
 #' data('ndvi')
 #' g = rgd(NDVIchange ~ ., data = ndvi,
 #'         discvar = names(ndvi)[-1:-3],
-#'         cores = 6)
+#'         discnum = 3:8, cores = 6)
 #' }
-rgd = \(formula, data, discvar = 3:22, discnum = 10, minsize = 1, cores = 1){
+rgd = \(formula, data, discvar = NULL, discnum = 3:22, minsize = 1, cores = 1){
   formula = stats::as.formula(formula)
   formula.vars = all.vars(formula)
   if (inherits(data,'sf')) {data = sf::st_drop_geometry(data)}
@@ -46,24 +47,22 @@ rgd = \(formula, data, discvar = 3:22, discnum = 10, minsize = 1, cores = 1){
     discvar = colnames(data)[-which(colnames(data) == yname)]
   }
   discdf =  dplyr::select(data,dplyr::all_of(c(yname,discvar)))
-  if (length(discnum)==1) {discnum = rep(discnum,length(discvar))}
-  g = robust_disc(paste0(yname,'~',paste0(discvar,collapse = '+')),
-                  discdf, discnum, minsize, cores = cores)
   discedvar = colnames(data[,-which(colnames(data) %in% discvar)])
-  newdata = data %>%
-    dplyr::select(dplyr::all_of(discedvar)) %>%
-    dplyr::bind_cols(g)
-  if (length(type) == 1){
-    res = gd(paste0(yname,' ~ .'),data = newdata,
-             type = type,alpha = alpha)
-  } else {
-    res = vector("list", length(type))
-    for (i in seq_along(type)){
-      res[[i]] = gd(paste0(yname,' ~ .'),data = newdata,
-                    type = type[i],alpha = alpha)[[1]]
-    }
-    names(res) = type
+
+  resqv = vector("list", length(discnum))
+  resdisc = vector("list", length(discnum))
+  for (i in seq_along(discnum)) {
+    g = robust_disc(paste0(yname,'~',paste0(discvar,collapse = '+')),
+                    discdf, discnum[i], minsize, cores = cores)
+    resdisc[[i]] = g
+    newdata = data %>%
+      dplyr::select(dplyr::all_of(discedvar)) %>%
+      dplyr::bind_cols(g)
+    resqv[[i]] = gd(paste0(yname,' ~ .'),data = newdata,type = "factor")[[1]]
   }
+  names(resqv) = paste0("discnum_",discnum)
+  names(resdisc) = paste0("discnum_",discnum)
+  res = c("factor" = resqv, "disc" = resdisc)
   class(res) = "rgd_result"
   return(res)
 }
@@ -80,14 +79,10 @@ rgd = \(formula, data, discvar = 3:22, discnum = 10, minsize = 1, cores = 1){
 #' @method print rgd_result
 #' @export
 print.rgd_result = \(x, ...) {
-  cat("                 RGD Model                  \n")
-  nx = names(x)
-  for (i in seq_along(x)){
-    res = x[i]
-    class(res) = paste0(nx[i],"_detector")
-    print(res)
-    cat("\n")
-  }
+  cat("***                  Robust Geographical Detector       ")
+  qv = x[[1]]
+  print(knitr::kable(qv[[length(qv)]],format = "markdown",digits = 12,align = 'c',...))
+  cat("#### Only display the results corresponding to the maximum number of discretizations.")
 }
 
 #' @title plot RGD result
diff --git a/man/rgd.Rd b/man/rgd.Rd
index fc43527a..56f95fe8 100644
--- a/man/rgd.Rd
+++ b/man/rgd.Rd
@@ -4,16 +4,7 @@
 \alias{rgd}
 \title{robust geographical detector(RGD) model}
 \usage{
-rgd(
-  formula,
-  data,
-  discvar = NULL,
-  discnum = 10,
-  minsize = 1,
-  cores = 1,
-  type = "factor",
-  alpha = 0.95
-)
+rgd(formula, data, discvar = NULL, discnum = 3:22, minsize = 1, cores = 1)
 }
 \arguments{
 \item{formula}{A formula of RGD model.}
@@ -25,25 +16,18 @@ when \code{formula} has \code{discvar}, \code{data} must have these columns. By
 variables are used as \code{discvar}.}
 
 \item{discnum}{A numeric vector of discretized classes of columns that need to be discretized.
-Default all \code{discvar} use \code{10}.}
+Default all \code{discvar} use \code{3:22}.}
 
 \item{minsize}{(optional) The min size of each discretization group. Default all use \code{1}.}
 
 \item{cores}{(optional) Positive integer(default is 1). If cores > 1, use \code{python} \code{joblib} package to
 parallel computation.}
-
-\item{type}{(optional) The type of geographical detector, which must be \code{factor}(default),
-\code{interaction}, \code{risk}, \code{ecological}.You can run one or more types at one time.}
-
-\item{alpha}{(optional) Specifies the size of confidence level. Default is \code{0.95}.}
 }
 \value{
 A list of the RGD model result.
 \describe{
-\item{\code{factor}}{the result of factor detector}
-\item{\code{interaction}}{the result of interaction detector}
-\item{\code{risk}}{the result of risk detector}
-\item{\code{ecological}}{the result of ecological detector}
+\item{\code{factor}}{the result of RGD model}
+\item{\code{disc}}{robust discrete results}
 }
 }
 \description{
@@ -57,8 +41,9 @@ See \code{vignette('rgdrid',package = 'gdverse')} for more details.
 \dontrun{
 ## The following code needs to configure the Python environment to run:
 data('ndvi')
-g = rgd(NDVIchange ~ ., data = ndvi, discvar = names(ndvi)[-1:-3],
-        cores = 6, type =c('factor','interaction'))
+g = rgd(NDVIchange ~ ., data = ndvi,
+        discvar = names(ndvi)[-1:-3],
+        discnum = 3:8, cores = 6)
 }
 }
 \references{