update readme

NAMESPACE

@@ -9,6 +9,7 @@ export(ecological_detector)
 export(factor_detector)
 export(gd)
 export(gd_bestunidisc)
+export(gd_rpart)
 export(gd_sesu)
 export(gozh)
 export(interaction_detector)

R/gozh.R

@@ -14,7 +14,7 @@
 #' @param cores positive integer(default is 1). If cores > 1, a 'parallel' package
 #' cluster with that many cores is created and used. You can also supply a cluster
 #' object.
-#' @param ... (optional) Other arguments passed to `rpart::rpart`.
+#' @param ... (optional) Other arguments passed to `rpart::rpart()`.
 #'
 #' @return A list of the GOZH model result.
 #' @export
@@ -69,11 +69,17 @@ gozh = \(formula,data,cores = 1,...){
   return(res)
 }
 
-
 #' @title Q-statistics of geographical detector based on Recursive Partitioning
+#' @author Wenbo Lv \email{[email protected]}
+#'
+#' @param formula A formula.
+#' @param data A data.frame or tibble of observation data.
+#' @param ... (optional) Other arguments passed to `rpart::rpart()`.
+#'
 #' @importFrom rpart rpart
 #' @importFrom tibble as_tibble_row
-#' @noRd
+#' @return A tibble contains the Q-statistic and the p-value.
+#' @export
 gd_rpart = \(formula,data,...){
   formula = stats::as.formula(formula)
   formula.vars = all.vars(formula)

README.Rmd

@@ -64,17 +64,28 @@ tictoc::toc()
 fvc_opgd
 ```
 
+### GOZH model
+
+```{r}
+tictoc::tic()
+g = gozh(fvc ~ ., data = fvc, cores = 6)
+tictoc::tic()
+g
+```
+
 ### RGD model
 
 To run `RGD`,remember to set up your python dependence, see `RGD` vignette to get more details.
 
 ```{r}
 reticulate::use_condaenv('geocompy')
 tictoc::tic()
-fvc_rgd = rgd(fvc ~ ., data = fvc, discnum = 15, 
+fvc_rgd = rgd(fvc ~ ., data = fvc, discnum = 10, 
               discvar = names(select(fvc,-c(fvc,lulc))),
-              cores = 8, type = 'factor')
+              cores = 6, type = 'factor')
 tictoc::toc()
 fvc_rgd
 ```
 
+
+

README.md

@@ -60,7 +60,7 @@ fvc_opgd = opgd(fvc ~ ., data = fvc, discnum = 3:15,
                 discvar = names(select(fvc,-c(fvc,lulc))),
                 cores = 6, type = 'factor')
 tictoc::toc()
-## 2.92 sec elapsed
+## 3.11 sec elapsed
 ```
 
 ``` r
@@ -74,16 +74,44 @@ fvc_opgd
 |:--------:|:-----------:|:---------:|
 |  presum  |   0.6626    | 9.145e-10 |
 |   lulc   |   0.6597    | 8.782e-10 |
-|  premin  |   0.4638    | 8.103e-10 |
-|  tmpmin  |   0.4278    | 5.541e-10 |
-|  tmpmax  |   0.2536    | 7.849e-10 |
-|  slope   |    0.233    | 8.055e-10 |
-|   elev   |   0.2318    | 8.79e-10  |
-|  tmpavg  |   0.2116    | 7.357e-10 |
-|   pop    |   0.1896    | 7.855e-10 |
-|  premax  |   0.1417    | 7.869e-10 |
+|  premin  |   0.4654    | 4.831e-10 |
+|  tmpmin  |   0.4323    | 4.367e-10 |
+|  tmpmax  |   0.2543    | 4.168e-10 |
+|   elev   |   0.2353    | 2.885e-10 |
+|  slope   |   0.2338    | 7.849e-10 |
+|  tmpavg  |   0.2214    | 7.616e-10 |
+|   pop    |   0.1953    | 2.428e-10 |
+|  premax  |   0.1442    | 1.682e-10 |
 |   ntl    |   0.02272   |  0.0301   |
-|  aspect  |   0.0118    |  0.1859   |
+|  aspect  |   0.0186    |  0.7491   |
+
+### GOZH model
+
+``` r
+tictoc::tic()
+g = gozh(fvc ~ ., data = fvc, cores = 6)
+tictoc::tic()
+g
+## Spatial Stratified Heterogeneity Test 
+##  
+##           Factor detector
+```
+
+|             variable              | Q-statistic |  P-value  |
+|:---------------------------------:|:-----------:|:---------:|
+| Explanatory Variables Association |   0.8052    | 7.146e-10 |
+|              presum               |   0.6372    | 9.492e-11 |
+|               lulc                |   0.6106    | 4.797e-10 |
+|              premin               |   0.4658    | 5.484e-10 |
+|              tmpmin               |   0.4112    | 2.948e-10 |
+|              tmpmax               |   0.2478    | 7.308e-10 |
+|               slope               |   0.2286    | 6.05e-10  |
+|                pop                |   0.2238    | 3.753e-10 |
+|               elev                |   0.2237    | 4.671e-10 |
+|              tmpavg               |   0.2188    | 6.543e-10 |
+|              premax               |   0.1259    | 1.436e-10 |
+|                ntl                |   0.02365   | 1.832e-10 |
+|              aspect               |   0.01413   | 8.938e-09 |
 
 ### RGD model
 
@@ -93,11 +121,11 @@ vignette to get more details.
 ``` r
 reticulate::use_condaenv('geocompy')
 tictoc::tic()
-fvc_rgd = rgd(fvc ~ ., data = fvc, discnum = 15, 
+fvc_rgd = rgd(fvc ~ ., data = fvc, discnum = 10, 
               discvar = names(select(fvc,-c(fvc,lulc))),
-              cores = 8, type = 'factor')
+              cores = 6, type = 'factor')
 tictoc::toc()
-## 2980.2 sec elapsed
+## 1886.14 sec elapsed
 ```
 
 ``` r
@@ -109,15 +137,15 @@ fvc_rgd
 
 | variable | Q-statistic |  P-value  |
 |:--------:|:-----------:|:---------:|
-|  presum  |   0.6745    | 6.166e-10 |
+|  presum  |   0.6678    | 4.284e-10 |
 |   lulc   |   0.6597    | 8.782e-10 |
-|  premin  |   0.4855    | 5.461e-10 |
-|  tmpmin  |   0.4575    | 6.232e-10 |
-|  tmpmax  |   0.2816    | 5.853e-10 |
-|   elev   |   0.2576    | 5.407e-10 |
-|   pop    |   0.2566    | 4.386e-10 |
-|  slope   |   0.2525    | 9.439e-10 |
-|  tmpavg  |   0.2502    |  4.2e-10  |
-|  premax  |   0.1668    | 9.434e-10 |
-|  aspect  |   0.03427   |  0.06239  |
+|  premin  |   0.4781    | 7.04e-10  |
+|  tmpmin  |    0.448    | 5.718e-10 |
+|  tmpmax  |   0.2692    | 3.296e-10 |
+|   elev   |    0.248    | 4.734e-10 |
+|  slope   |   0.2464    | 8.852e-10 |
+|   pop    |   0.2446    | 9.414e-10 |
+|  tmpavg  |   0.2405    | 5.228e-10 |
+|  premax  |   0.1572    | 5.383e-10 |
+|  aspect  |   0.02759   | 0.003456  |
 |   ntl    |   0.02334   | 4.623e-10 |