use R_xlen_t everywhere

R/pmt.R

@@ -159,8 +159,8 @@ pmts <- function(
 #'     inherit = "twosample",
 #'     n_permu = 1e5,
 #'     statistic = "[](const NumericVector& x, const NumericVector& y) {
-#'         R_len_t m = x.size();
-#'         R_len_t n = y.size();
+#'         R_xlen_t m = x.size();
+#'         R_xlen_t n = y.size();
 #'         return [=](const NumericVector& x, const NumericVector& y) -> double {
 #'             return sum(x) / m - sum(y) / n;
 #'         };

inst/include/pmt/impl_multcomp_pmt.hpp

@@ -7,16 +7,16 @@ RObject impl_multcomp_pmt(
     const T& statistic_func,
     const double n_permu)
 {
-    R_len_t n_group = group[group.size() - 1];
-    R_len_t n_pair = n_group * (n_group - 1) / 2;
+    R_xlen_t n_group = group[group.size() - 1];
+    R_xlen_t n_pair = n_group * (n_group - 1) / 2;
 
     Stat<progress> statistic_container(n_pair);
 
     auto multcomp_update = [group_i, group_j, data, group, n_pair, &statistic_func, &statistic_container]() {
         auto statistic_closure = statistic_func(data, group);
 
         bool flag = false;
-        for (R_len_t k = 0; k < n_pair; k++) {
+        for (R_xlen_t k = 0; k < n_pair; k++) {
             flag = statistic_container << statistic_closure(group_i[k], group_j[k]);
         };
 

inst/include/pmt/impl_paired_pmt.hpp

@@ -15,13 +15,15 @@ RObject impl_paired_pmt(
     statistic_container.init_statistic(paired_update);
 
     if (!std::isnan(n_permu)) {
-        R_len_t i = 0;
-        R_len_t n = x.size();
+        R_xlen_t n = x.size();
 
+        R_xlen_t i;
         if (n_permu == 0) {
             statistic_container.init_statistic_permu(1 << n);
 
             IntegerVector swapped(n, 0);
+
+            i = 0;
             while (i < n) {
                 if (i == 0) {
                     paired_update();

inst/include/pmt/impl_rcbd_pmt.hpp

@@ -14,7 +14,7 @@ RObject impl_rcbd_pmt(
     statistic_container.init_statistic(rcbd_update);
 
     if (!std::isnan(n_permu)) {
-        R_len_t k = data.nrow();
+        R_xlen_t k = data.nrow();
 
         auto begin = data.begin();
         auto end = data.end() - k;

inst/include/pmt/impl_table_pmt.hpp

@@ -7,13 +7,13 @@ RObject impl_table_pmt(
 {
     Stat<progress> statistic_container;
 
-    R_len_t n = row.size();
+    R_xlen_t n = row.size();
 
     IntegerMatrix data(no_init(row[n - 1] + 1, col[n - 1] + 1));
 
     auto data_filled = [data, row, col, n]() mutable {
         data.fill(0);
-        for (R_len_t i = 0; i < n; i++) {
+        for (R_xlen_t i = 0; i < n; i++) {
             data(row[i], col[i])++;
         }
         return data;

inst/include/pmt/impl_twosample_pmt.hpp

@@ -18,10 +18,10 @@ RObject impl_twosample_pmt(
         NumericVector x_ = x.size() < y.size() ? x : y;
         NumericVector y_ = x.size() < y.size() ? y : x;
 
-        R_len_t m = x_.size();
-        R_len_t n = x_.size() + y_.size();
+        R_xlen_t m = x_.size();
+        R_xlen_t n = x_.size() + y_.size();
 
-        R_len_t i, j;
+        R_xlen_t i, j;
         if (n_permu == 0) {
             IntegerVector p(n, 0);
 
@@ -33,7 +33,7 @@ RObject impl_twosample_pmt(
             for (i = 0; i < n; i++) {
                 p[i] = i;
             }
-            auto swap_update = [x_, y_, p, m, &twosample_update](const R_len_t out, const R_len_t in) mutable {
+            auto swap_update = [x_, y_, p, m, &twosample_update](const R_xlen_t out, const R_xlen_t in) mutable {
                 std::swap(x_[p[out]], y_[p[in] - m]);
                 std::swap(p[out], p[in]);
                 twosample_update();

inst/include/pmt/progress.hpp

@@ -35,7 +35,7 @@ constexpr auto generated_bars = generate_bars(std::make_integer_sequence<unsigne
 template <bool progress>
 class Stat {
 public:
-    Stat(R_len_t statistic_size = 1) :
+    Stat(R_xlen_t statistic_size = 1) :
         _progress_i(0),
         _progress_every(2),
         _statistic_size(statistic_size) { }
@@ -87,9 +87,9 @@ class Stat {
     R_xlen_t _progress_i;
     R_xlen_t _progress_every;
 
-    R_len_t _statistic_size;
+    R_xlen_t _statistic_size;
 
-    void _init_statistic_buffer(double n, R_len_t size)
+    void _init_statistic_buffer(double n, R_xlen_t size)
     {
         double total = n * size;
         if (total <= 0 || total > R_XLEN_T_MAX) {