remove some remaining uses of Stan's old array syntax

paul-buerkner · Nov 13, 2023 · 3625d91 · 3625d91
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -2,8 +2,8 @@ Package: brms
 Encoding: UTF-8
 Type: Package
 Title: Bayesian Regression Models using 'Stan'
-Version: 2.20.5
-Date: 2023-09-25
+Version: 2.20.6
+Date: 2023-11-13
 Authors@R:
     c(person("Paul-Christian", "Bürkner", email = "[email protected]",
              role = c("aut", "cre")),

diff --git a/NEWS.md b/NEWS.md
@@ -5,6 +5,10 @@
 * No longer automatically canonicalize the Stan code if cmdstanr is used
 as backend. (#1544)
 
+### Bug Fixes
+
+* Remove some remaining uses of Stan's old array syntax.
+
 
 # brms 2.20.3
 

diff --git a/R/families.R b/R/families.R
@@ -1122,7 +1122,7 @@ mixture <- function(..., flist = NULL, nmix = 1, order = NULL) {
 #'
 #' # define the corresponding Stan density function
 #' stan_density_vec <- "
-#'   real beta_binomial2_lpmf(int[] y, vector mu, real phi, int[] N) {
+#'   real beta_binomial2_lpmf(array[] int y, vector mu, real phi, array[] int N) {
 #'     return beta_binomial_lpmf(y | N, mu * phi, (1 - mu) * phi);
 #'   }
 #' "

diff --git a/R/stan-response.R b/R/stan-response.R
@@ -36,7 +36,7 @@ stan_response <- function(bterms, data, normalize) {
       str_add(out$data) <- glue(
         "  array[N{resp}, ncat{resp}] int Y{resp};  // response array\n"
       )
-      str_add(out$pll_args) <- glue(", data int[,] Y{resp}")
+      str_add(out$pll_args) <- glue(", data array[,] int Y{resp}")
     }
   } else {
     if (rtype == "real") {

diff --git a/R/stanvars.R b/R/stanvars.R
@@ -123,7 +123,7 @@ stanvar <- function(x = NULL, name = NULL, scode = NULL,
         if (length(x) == 1L) {
           pll_type <- paste0(pll_type, "int")
         } else {
-          pll_type <- paste0(pll_type, "int[]")
+          pll_type <- paste0(pll_type, "array[] int")
         }
       } else if (is.vector(x)) {
         if (length(x) == 1L) {

diff --git a/inst/chunks/fun_is_equal.stan b/inst/chunks/fun_is_equal.stan
@@ -1,5 +1,5 @@
   // are two 1D integer arrays equal?
-  int is_equal(int[] a, int[] b) {
+  int is_equal(array[] int a, array[] int b) {
     int n_a = size(a);
     int n_b = size(b);
     if (n_a != n_b) {

diff --git a/inst/chunks/fun_multinomial_logit.stan b/inst/chunks/fun_multinomial_logit.stan
@@ -5,6 +5,6 @@
    * Returns:
    *   a scalar to be added to the log posterior
    */
-   real multinomial_logit2_lpmf(int[] y, vector mu) {
+   real multinomial_logit2_lpmf(array[] int y, vector mu) {
      return multinomial_lpmf(y | softmax(mu));
    }
diff --git a/inst/chunks/fun_normal_time.stan b/inst/chunks/fun_normal_time.stan
@@ -12,7 +12,7 @@
    *   sum of the log-PDF values of all observations
    */
   real normal_time_hom_lpdf(vector y, vector mu, real sigma, matrix chol_cor,
-                            int[] nobs, int[] begin, int[] end) {
+                            array[] int nobs, array[] int begin, array[] int end) {
     int I = size(nobs);
     vector[I] lp;
     matrix[rows(chol_cor), cols(chol_cor)] L = sigma * chol_cor;
@@ -32,7 +32,7 @@
    *   sum of the log-PDF values of all observations
    */
   real normal_time_het_lpdf(vector y, vector mu, vector sigma, matrix chol_cor,
-                            int[] nobs, int[] begin, int[] end) {
+                            array[] int nobs, array[] int begin, array[] int end) {
     int I = size(nobs);
     vector[I] lp;
     for (i in 1:I) {
@@ -53,7 +53,8 @@
    *   sum of the log-PDF values of all observations
    */
   real normal_time_hom_flex_lpdf(vector y, vector mu, real sigma, matrix chol_cor,
-                                 int[] nobs, int[] begin, int[] end, int[,] Jtime) {
+                                 array[] int nobs, array[] int begin, array[] int end,
+                                 array[,] int Jtime) {
     real lp = 0.0;
     int I = size(nobs);
     array[I] int has_lp = rep_array(0, I);
@@ -103,7 +104,8 @@
    *   sum of the log-PDF values of all observations
    */
   real normal_time_het_flex_lpdf(vector y, vector mu, vector sigma, matrix chol_cor,
-                                 int[] nobs, int[] begin, int[] end, int[,] Jtime) {
+                                 array[] int nobs, array[] int begin, array[] int end,
+                                 array[,] int Jtime) {
     int I = size(nobs);
     vector[I] lp;
     array[I] int has_lp = rep_array(0, I);

diff --git a/inst/chunks/fun_normal_time_se.stan b/inst/chunks/fun_normal_time_se.stan
@@ -14,7 +14,7 @@
    *   sum of the log-PDF values of all observations
    */
   real normal_time_hom_se_lpdf(vector y, vector mu, real sigma, data vector se2,
-                               matrix chol_cor, int[] nobs, int[] begin, int[] end) {
+                               matrix chol_cor, array[] int nobs, array[] int begin, array[] int end) {
     int I = size(nobs);
     vector[I] lp;
     matrix[rows(chol_cor), cols(chol_cor)] Cov;
@@ -36,7 +36,7 @@
    *   sum of the log-PDF values of all observations
    */
   real normal_time_het_se_lpdf(vector y, vector mu, vector sigma, data vector se2,
-                               matrix chol_cor, int[] nobs, int[] begin, int[] end) {
+                               matrix chol_cor, array[] int nobs, array[] int begin, array[] int end) {
     int I = size(nobs);
     vector[I] lp;
     for (i in 1:I) {
@@ -59,8 +59,8 @@
    *   sum of the log-PDF values of all observations
    */
   real normal_time_hom_se_flex_lpdf(vector y, vector mu, real sigma, data vector se2,
-                                    matrix chol_cor, int[] nobs, int[] begin,
-                                    int[] end, int[,] Jtime) {
+                                    matrix chol_cor, array[] int nobs, array[] int begin,
+                                    array[] int end, array[,] int Jtime) {
     int I = size(nobs);
     vector[I] lp;
     matrix[rows(chol_cor), cols(chol_cor)] Cov;
@@ -84,8 +84,8 @@
    *   sum of the log-PDF values of all observations
    */
   real normal_time_het_se_flex_lpdf(vector y, vector mu, vector sigma, data vector se2,
-                                    matrix chol_cor, int[] nobs, int[] begin,
-                                    int[] end, int[,] Jtime) {
+                                    matrix chol_cor, array[] int nobs, array[] int begin,
+                                    array[] int end, array[,] int Jtime) {
     int I = size(nobs);
     vector[I] lp;
     matrix[rows(chol_cor), cols(chol_cor)] Cor;

diff --git a/inst/chunks/fun_scale_r_cor_by.stan b/inst/chunks/fun_scale_r_cor_by.stan
@@ -7,7 +7,7 @@
   * Returns:
   *   matrix of scaled group-level effects
   */
-  matrix scale_r_cor_by(matrix z, matrix SD, matrix[] L, int[] Jby) {
+  matrix scale_r_cor_by(matrix z, matrix SD, array[] matrix L, array[] int Jby) {
     // r is stored in another dimension order than z
     matrix[cols(z), rows(z)] r;
     array[size(L)] matrix[rows(L[1]), cols(L[1])] LC;

diff --git a/inst/chunks/fun_scale_r_cor_by_cov.stan b/inst/chunks/fun_scale_r_cor_by_cov.stan
@@ -9,8 +9,8 @@
   * Returns:
   *   matrix of scaled group-level effects
   */
-  matrix scale_r_cor_by_cov(matrix z, matrix SD, matrix[] L,
-                            int[] Jby, matrix Lcov) {
+  matrix scale_r_cor_by_cov(matrix z, matrix SD, array[] matrix L,
+                            array[] int Jby, matrix Lcov) {
     vector[num_elements(z)] z_flat = to_vector(z);
     vector[num_elements(z)] r = rep_vector(0, num_elements(z));
     array[size(L)] matrix[rows(L[1]), cols(L[1])] LC;

diff --git a/inst/chunks/fun_scale_time_err.stan b/inst/chunks/fun_scale_time_err.stan
@@ -11,7 +11,7 @@
    *   vector of scaled and correlated residuals
    */
    vector scale_time_err(vector zerr, real sderr, matrix chol_cor,
-                         int[] nobs, int[] begin, int[] end) {
+                         array[] int nobs, array[] int begin, array[] int end) {
      vector[rows(zerr)] err;
      for (i in 1:size(nobs)) {
        matrix[nobs[i], nobs[i]] L_i;
@@ -28,7 +28,7 @@
    *   vector of scaled and correlated residuals
    */
    vector scale_time_err_flex(vector zerr, real sderr, matrix chol_cor,
-                              int[] nobs, int[] begin, int[] end, int[,] Jtime) {
+                              array[] int nobs, array[] int begin, array[] int end, array[,] int Jtime) {
      vector[rows(zerr)] err;
      int I = size(nobs);
      array[I] int has_err = rep_array(0, I);

diff --git a/inst/chunks/fun_sequence.stan b/inst/chunks/fun_sequence.stan
@@ -5,7 +5,7 @@
    * Returns:
    *   an integer sequence from start to end
    */
-  int[] sequence(int start, int end) {
+  array[] int sequence(int start, int end) {
     array[end - start + 1] int seq;
     for (n in 1:num_elements(seq)) {
       seq[n] = n + start - 1;

diff --git a/inst/chunks/fun_sparse_car_lpdf.stan b/inst/chunks/fun_sparse_car_lpdf.stan
@@ -17,7 +17,7 @@
   */
   real sparse_car_lpdf(vector phi, real car, real sdcar, int Nloc,
                        int Nedges, data vector Nneigh, data vector eigenW,
-                       int[] edges1, int[] edges2) {
+                       array[] int edges1, array[] int edges2) {
     real tau;  // precision parameter
     row_vector[Nloc] phit_D;  // phi' * D
     row_vector[Nloc] phit_W;  // phi' * W

diff --git a/inst/chunks/fun_sparse_icar_lpdf.stan b/inst/chunks/fun_sparse_icar_lpdf.stan
@@ -16,7 +16,7 @@
   */
   real sparse_icar_lpdf(vector phi, real sdcar, int Nloc,
                         int Nedges, data vector Nneigh, data vector eigenW,
-                        int[] edges1, int[] edges2) {
+                        array[] int edges1, array[] int edges2) {
     real tau;  // precision parameter
     row_vector[Nloc] phit_D;  // phi' * D
     row_vector[Nloc] phit_W;  // phi' * W

diff --git a/inst/chunks/fun_stack_vectors.stan b/inst/chunks/fun_stack_vectors.stan
@@ -1,8 +1,8 @@
   /* grouped data stored linearly in "data" as indexed by begin and end
    * is repacked to be stacked into an array of vectors.
    */
-  vector[] stack_vectors(vector long_data, int n, int[] stack,
-                         int[] begin, int[] end) {
+  vector[] stack_vectors(vector long_data, int n, array[] int stack,
+                         array[] int begin, array[] int end) {
     int S = sum(stack);
     int G = size(stack);
     array[S] vector[n] stacked;

diff --git a/inst/chunks/fun_student_t_time.stan b/inst/chunks/fun_student_t_time.stan
@@ -13,8 +13,8 @@
    *   sum of the log-PDF values of all observations
    */
   real student_t_time_hom_lpdf(vector y, real nu, vector mu, real sigma,
-                               matrix chol_cor, int[] nobs, int[] begin,
-                               int[] end) {
+                               matrix chol_cor, array[] int nobs, array[] int begin,
+                               array[] int end) {
     int I = size(nobs);
     vector[I] lp;
     for (i in 1:I) {
@@ -35,8 +35,8 @@
    *   sum of the log-PDF values of all observations
    */
   real student_t_time_het_lpdf(vector y, real nu, vector mu, vector sigma,
-                               matrix chol_cor, int[] nobs, int[] begin,
-                               int[] end) {
+                               matrix chol_cor, array[] int nobs, array[] int begin,
+                               array[] int end) {
     int I = size(nobs);
     vector[I] lp;
     for (i in 1:I) {
@@ -58,8 +58,8 @@
    *   sum of the log-PDF values of all observations
    */
   real student_t_time_hom_flex_lpdf(vector y, real nu, vector mu, real sigma,
-                                    matrix chol_cor, int[] nobs, int[] begin,
-                                    int[] end, int[,] Jtime) {
+                                    matrix chol_cor, array[] int nobs, array[] int begin,
+                                    array[] int end, array[,] int Jtime) {
     int I = size(nobs);
     vector[I] lp;
     matrix[rows(chol_cor), cols(chol_cor)] Cov;
@@ -83,8 +83,8 @@
    *   sum of the log-PDF values of all observations
    */
   real student_t_time_het_flex_lpdf(vector y, real nu, vector mu, vector sigma,
-                                    matrix chol_cor, int[] nobs, int[] begin,
-                                    int[] end, int[,] Jtime) {
+                                    matrix chol_cor, array[] int nobs, array[] int begin,
+                                    array[] int end, array[,] int Jtime) {
     int I = size(nobs);
     vector[I] lp;
     matrix[rows(chol_cor), cols(chol_cor)] Cor;

diff --git a/inst/chunks/fun_student_t_time_se.stan b/inst/chunks/fun_student_t_time_se.stan
@@ -15,8 +15,8 @@
    *   sum of the log-PDF values of all observations
    */
   real student_t_time_hom_se_lpdf(vector y, real nu, vector mu, real sigma,
-                                  data vector se2, matrix chol_cor, int[] nobs,
-                                  int[] begin, int[] end) {
+                                  data vector se2, matrix chol_cor, array[] int nobs,
+                                  array[] int begin, array[] int end) {
     int I = size(nobs);
     vector[I] lp;
     matrix[rows(chol_cor), cols(chol_cor)] Cov;
@@ -38,8 +38,8 @@
    *   sum of the log-PDF values of all observations
    */
   real student_t_time_het_se_lpdf(vector y, real nu, vector mu, vector sigma,
-                                  data vector se2, matrix chol_cor, int[] nobs,
-                                  int[] begin, int[] end) {
+                                  data vector se2, matrix chol_cor, array[] int nobs,
+                                  array[] int begin, array[] int end) {
     int I = size(nobs);
     vector[I] lp;
     for (i in 1:I) {
@@ -61,8 +61,8 @@
    *   sum of the log-PDF values of all observations
    */
   real student_t_time_hom_se_flex_lpdf(vector y, real nu, vector mu, real sigma,
-                                       data vector se2, matrix chol_cor, int[] nobs,
-                                       int[] begin, int[] end, int[,] Jtime) {
+                                       data vector se2, matrix chol_cor, array[] int nobs,
+                                       array[] int begin, array[] int end, array[,] int Jtime) {
     int I = size(nobs);
     vector[I] lp;
     matrix[rows(chol_cor), cols(chol_cor)] Cov;
@@ -86,8 +86,8 @@
    *   sum of the log-PDF values of all observations
    */
   real student_t_time_het_se_flex_lpdf(vector y, real nu, vector mu, vector sigma,
-                                       data vector se2, matrix chol_cor, int[] nobs,
-                                       int[] begin, int[] end, int[,] Jtime) {
+                                       data vector se2, matrix chol_cor, array[] int nobs,
+                                       array[] int begin, array[] int end, array[,] int Jtime) {
     int I = size(nobs);
     vector[I] lp;
     matrix[rows(chol_cor), cols(chol_cor)] Cor;

diff --git a/inst/chunks/fun_which_range.stan b/inst/chunks/fun_which_range.stan
@@ -6,7 +6,7 @@
    * Returns:
    *   a scalar integer
    */
-  int size_range(int[] x, int start, int end) {
+  int size_range(array[] int x, int start, int end) {
     int out = 0;
     for (i in 1:size(x)) {
       out += (x[i] >= start && x[i] <= end);
@@ -21,7 +21,7 @@
    * Returns:
    *   an integer array
    */
-  int[] which_range(int[] x, int start, int end) {
+  array[] int which_range(array[] int x, int start, int end) {
     array[size_range(x, start, end)] int out;
     int j = 1;
     for (i in 1:size(x)) {
@@ -39,7 +39,7 @@
    * Returns:
    *   an integer array
    */
-  int[] start_at_one(int[] x, int start) {
+  array[] int start_at_one(array[] int x, int start) {
     array[size(x)] int out;
     for (i in 1:size(x)) {
       out[i] = x[i] - start + 1;

diff --git a/man/custom_family.Rd b/man/custom_family.Rd
diff --git a/tests/local/tests.models-2.R b/tests/local/tests.models-2.R
@@ -238,7 +238,7 @@ test_that("Nested non-linear models work correctly", {
 test_that("Non-linear non-looped model predictions work correctly in blocked order", {
   loss_alt <- transform(loss, row=as.integer(1:nrow(loss)), nr=nrow(loss), test=as.integer(0))
   scode_growth <- "
-    vector growth_test(vector ult, int[] dev, vector theta, vector omega, int[] row, int[] test) {
+    vector growth_test(vector ult, array[] int dev, vector theta, vector omega, array[] int row, array[] int test) {
       int N = rows(ult);
       vector[N] mu;
       int rows_sorted = 1;