unlucky

inst/include/vinecopulib/vinecop/implementation/class.ipp

@@ -1166,13 +1166,12 @@ Vinecop::rosenblatt_discrete(const Eigen::MatrixXd& u,
     // fill first row of hfunc2 matrix with evaluation points;
     // points have to be reordered to correspond to natural order
     for (size_t j = 0; j < d_; ++j) {
-      hfunc2.col(j) = u.block(b.begin, order[j] - 1, b.size, 1);
+      hfunc2.col(j) = uu.block(b.begin, order[j] - 1, b.size, 1);
       if (var_types_[order[j] - 1] == "d") {
         hfunc2_sub.col(j) =
-          u.block(b.begin, d_ + disc_cols[order[j] - 1], b.size, 1);
+          uu.block(b.begin, d_ + disc_cols[order[j] - 1], b.size, 1);
       }
     }
-    hfunc1_sub = Eigen::MatrixXd::Zero(b.size, d);
 
     for (size_t tree = 0; tree < trunc_lvl; ++tree) {
       tools_interface::check_user_interrupt(

tests/testthat/test_rosenblatt.R

@@ -26,22 +26,25 @@ test_that("rosenblatt works with vine copulas", {
 
 test_that("rosenblatt_discrete works with vine copulas", {
   u <- rvinecop(2000, vc)
-  uu <- cbind(u, u)
+  uu <- cbind(u, u[, 2])
 
   thresh <- 0.05
-  uu[, 1:3][u < thresh] <- 1e-10
-  uu[, -(1:3)][u < thresh] <- thresh
+  uu[u[, 2] < thresh, 2] <- 1e-10
+  uu[u[, 2] < thresh, 4] <- thresh
 
-  vc_c <- vc <- vinecop(uu, var_types = rep("d", 3), structure = mat, family = "clay")
+  vc_c <- vc <- vinecop(uu, var_types = c("c", "d", "c"),
+                        structure = mat, family = "clay")
   vc_c$var_types = rep("c", 3)
 
   v <- inverse_rosenblatt(rosenblatt_discrete(uu, vc), vc_c)
   expect_eql(v, u, tol = 2 * thresh)
-  pairs(cbind(v, u))
 
-  for (i in 1:50) {
-    rosenblatt_discrete(uu, vc)
-  }
+  # other format
+  uu <- cbind(u, u)
+  uu[u[, 2] < thresh, 2] <- 1e-10
+  uu[u[, 2] < thresh, 5] <- thresh
+  v <- inverse_rosenblatt(rosenblatt_discrete(uu, vc), vc_c)
+  expect_eql(v, u, tol = 2 * thresh)
 })
 
 test_that("rosenblatt works with vine distribution", {