minor improvements

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: LearnNonparam
 Title: 'R6'-Based Flexible Framework for Permutation Tests
-Version: 1.2.5
+Version: 1.2.6
 Authors@R: 
     person(given = "Yan", family = "Du", role = c("aut", "cre"), email = "[email protected]", comment = c(ORCID = "0009-0009-1169-921X"))
 Description: Implements non-parametric tests from Higgins (2004, ISBN:0534387756), including tests for one sample, two samples, k samples, paired comparisons, blocked designs, trends and association. Built with 'Rcpp' for efficiency and 'R6' for flexible, object-oriented design, the package provides a unified framework for performing or creating custom permutation tests.

NEWS.md

@@ -1,3 +1,17 @@
+# LearnNonparam 1.2.6
+
+- R side
+  - Added more documentation
+  - Switched to version 3 serialization format
+  - Fixed the issue with parameter passing to `ggplot2::stat_bin` in `plot()`
+  - Added detection for missing values and zero-length data in `test()`
+
+- C++ side
+  - Improved the efficiency of calling R from C++
+  - Enhanced the permuting efficiency in `rcbd.*`, `association.*`, and `table.*`
+  - Replaced `R_len_t` with `R_xlen_t` to support long vectors
+  - Replaced `Rcpp.h` with `Rcpp/Lightest` to reduce compilation time
+
 # LearnNonparam 1.2.5
 
 - Added support for `scoring` as an active binding in `define_pmt`
@@ -7,39 +21,39 @@
 # LearnNonparam 1.2.4
 
 - R side
-    - Added support for custom scoring systems in `define_pmt`
-    - Enabled compatibility with C++ standard versions beyond C++14 in `define_pmt`
-    - Improved the performance of `KruskalWallis`, `OneWay`, and `Studentized`
-    - Replaced certain `warning()` calls with `stop()`
-    - Refined some text
+  - Added support for custom scoring systems in `define_pmt`
+  - Enabled compatibility with C++ standard versions beyond C++14 in `define_pmt`
+  - Improved the performance of `KruskalWallis`, `OneWay`, and `Studentized`
+  - Replaced certain `warning()` calls with `stop()`
+  - Refined some text
 
 - C++ side
-    - Enhanced permuting efficiency in `twosample_pmt`
+  - Enhanced the permuting efficiency in `twosample.*`
 
 # LearnNonparam 1.2.3
 
-- Improved `twosample_pmt`
+- Improved `twosample.*`
 - Added examples
 - Fixed `SiegelTukey` and `ContingencyTableTest`
 
 # LearnNonparam 1.2.2
 
 - R side
-    - Changed the default value of `n_permu` to `1e4`
-    - Added support for test statistics defined using Rcpp in `define_pmt`
-    - Added support for `null_value` other than zero in two-sample location tests
-    - Added support for `scoring` in `TwoSampleAssociationTest`
-    - Added a confidence interval for p-value in `print()`
-    - Added the `LearnNonparam.pmt_progress` option
-    - Added `attr(t$n_permu, "n_used")`
-    - Replaced `multicomp.*` with `multcomp.*`
-    - Replaced `KSampleF` and `RCBDF` with `OneWay` and `RCBDOneWay`
-    - Stopped exporting abstract classes (`TwoSampleTest`, `KSampleTest`, etc.)
-    - Improved the efficiency of `ChiSquare`, `Difference`, `JonckheereTerpstra`, `KruskalWallis`, `RatioMeanDeviance` and `Studentized`
-    - Fixed many bugs
+  - Changed the default value of `n_permu` to `1e4`
+  - Added support for test statistics defined using Rcpp in `define_pmt`
+  - Added support for `null_value` other than zero in two-sample location tests
+  - Added support for `scoring` in `TwoSampleAssociationTest`
+  - Added a confidence interval for p-value in `print()`
+  - Added the `LearnNonparam.pmt_progress` option
+  - Added `attr(t$n_permu, "n_used")`
+  - Replaced `multicomp.*` with `multcomp.*`
+  - Replaced `KSampleF` and `RCBDF` with `OneWay` and `RCBDOneWay`
+  - Stopped exporting abstract classes (`TwoSampleTest`, `KSampleTest`, etc.)
+  - Improved the efficiency of `ChiSquare`, `Difference`, `JonckheereTerpstra`, `KruskalWallis`, `RatioMeanDeviance` and `Studentized`
+  - Fixed many bugs
 
 - C++ side
-    - Introduced a new progress bar, which is built at compile time to minimize runtime overhead
+  - Introduced a new progress bar, which is built at compile time to minimize runtime overhead
 
 # LearnNonparam 1.2.1
 

R/AnsariBradley.R

@@ -89,4 +89,4 @@ AnsariBradley <- R6Class(
             private$.p_value <- get_p_continous(z, "norm", private$.side)
         }
     )
-)
+)

R/Friedman.R

@@ -65,4 +65,4 @@ Friedman <- R6Class(
             )
         }
     )
-)
+)

R/KolmogorovSmirnov.R

@@ -48,4 +48,4 @@ KolmogorovSmirnov <- R6Class(
             private$.side <- "r"
         }
     )
-)
+)

R/Page.R

@@ -64,4 +64,4 @@ Page <- R6Class(
             private$.p_value <- get_p_continous(z, "norm", private$.side)
         }
     )
-)
+)

R/RCBDOneWay.R

@@ -69,5 +69,4 @@ RCBDOneWay <- R6Class(
             )
         }
     )
-)
-
+)

R/do_call.R

@@ -27,4 +27,4 @@ do_call <- function(func, default = list(), fixed = list(), ...) {
     # All arguments will be evaluated within the `args` environment.
     # https://stackoverflow.com/a/25371509/23137996
     eval(as.call(c(func, lapply(`names<-`(...args, ...args), as.name))), args)
-}
+}

R/pmt.R

@@ -164,8 +164,8 @@ pmts <- function(
 #' rcpp <- define_pmt(
 #'     inherit = "twosample", n_permu = 1e5,
 #'     statistic = "[](const auto& x, const auto& y) {
-#'         auto m = x.size();
-#'         auto n = y.size();
+#'         auto m = x.length();
+#'         auto n = y.length();
 #'         return [=](const auto& x, const auto& y) {
 #'             return sum(x) / m - sum(y) / n;
 #'         };
@@ -176,9 +176,9 @@ pmts <- function(
 #' # rcpp <- define_pmt(
 #' #     inherit = "twosample", n_permu = 1e5,
 #' #     statistic = "[](const NumericVector& x, const NumericVector& y) {
-#' #         R_xlen_t m = x.size();
-#' #         R_xlen_t n = y.size();
-#' #         return [=](const NumericVector& x, const NumericVector& y) -> double {
+#' #         R_xlen_t m = x.length();
+#' #         R_xlen_t n = y.length();
+#' #         return [m, n](const NumericVector& x, const NumericVector& y) -> double {
 #' #             return sum(x) / m - sum(y) / n;
 #' #         };
 #' #     }"

inst/include/pmt/permutation.hpp

@@ -3,6 +3,9 @@
 #include <algorithm>
 #include <iterator>
 
+template <typename T>
+using diff_t = typename std::iterator_traits<T>::difference_type;
+
 template <typename T>
 T rand_int(T n)
 {
@@ -12,12 +15,10 @@ T rand_int(T n)
 template <typename T>
 void random_shuffle(T first, T last)
 {
-    using diff_t = typename std::iterator_traits<T>::difference_type;
-
-    diff_t n = std::distance(first, last);
+    diff_t<T> n = std::distance(first, last);
 
-    for (diff_t i = 0; i < n - 1; i++) {
-        diff_t j = i + rand_int(n - i);
+    for (diff_t<T> i = 0; i < n - 1; i++) {
+        diff_t<T> j = i + rand_int(n - i);
         std::iter_swap(first + i, first + j);
     }
 }
@@ -33,10 +34,10 @@ double n_permutation(T first, T last)
 {
     double A = 1.0;
 
-    typename std::iterator_traits<T>::difference_type rep = 0;
+    diff_t<T> rep = 0;
 
     auto val = *first;
-    for (auto it = first; it != last; it++) {
+    for (T it = first; it != last; it++) {
         A *= std::distance(first, it) + 1;
         if (*it == val) {
             A /= ++rep;
@@ -50,19 +51,19 @@ double n_permutation(T first, T last)
 }
 
 template <typename T>
-auto random_shuffle(T& v)
+auto random_shuffle(T&& v)
 {
     return random_shuffle(v.begin(), v.end());
 }
 
 template <typename T>
-auto next_permutation(T& v)
+auto next_permutation(T&& v)
 {
     return next_permutation(v.begin(), v.end());
 }
 
 template <typename T>
-auto n_permutation(const T& v)
+auto n_permutation(T&& v)
 {
     return n_permutation(v.begin(), v.end());
 }