trying to optimize the more precise mat mult

ropensci · Oct 8, 2023 · 870c741 · 870c741
1 parent fc9c909
commit 870c741
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Showing 2 changed files with 37 additions and 14 deletions.
diff --git a/src/Tree.cpp b/src/Tree.cpp
@@ -1095,21 +1095,13 @@
 
     if(obs_in_node.size() > 0){
 
-     // lincomb = prediction_data->x_submat(obs_in_node, coef_indices[i]) * coef_values[i];
-
      x_node = prediction_data->x_submat(obs_in_node, coef_indices[i]);
-     lincomb.set_size(x_node.n_rows);
-
-     for(uword k = 0; k < lincomb.size(); k++){
-      vec new_lincomb_value = (x_node.row(k) * coef_values[i]);
-      lincomb[k] = new_lincomb_value(0);
-     }
 
      it = obs_in_node.begin();
 
-     for(uword j = 0; j < lincomb.size(); ++j, ++it){
+     for(uword j = 0; j < obs_in_node.size(); ++j, ++it){
 
-      if(lincomb[j] <= cutpoint[i]) {
+      if(dot(x_node.row(j), coef_values[i]) <= cutpoint[i]) {
 
        pred_leaf[*it] = child_left[i];
 

diff --git a/tests/testthat/test-performance.R b/tests/testthat/test-performance.R
@@ -1,7 +1,7 @@
-
-
-
-# flc %>% dim()
+#
+#
+#
+# # grow ----
 #
 # microbenchmark::microbenchmark(
 #  aorsf = orsf(flc, time + status ~ .,
@@ -31,3 +31,34 @@
 #                          min.node.size = 10),
 #  times = 10
 # )
+#
+# # predict ----
+# source("tests/testthat/setup.R")
+#
+# fit_orsf <- orsf(pbc, time + status ~ ., n_thread = 0, leaf_min_obs = 10)
+#
+# fit_rfsrc <- randomForestSRC::rfsrc(Surv(time, status) ~ .,
+#                                     data = pbc,
+#                                     nodesize = 10,
+#                                     samptype = 'swr')
+#
+#
+# microbenchmark::microbenchmark(
+#  orsf = predict(fit_orsf, new_data = pbc),
+#  rfsrc = predict(fit_rfsrc, newdata = pbc),
+#  times = 50
+# )
+#
+# fit_orsf <- orsf(flc, time + status ~ ., n_thread = 0, leaf_min_obs = 10)
+#
+# fit_rfsrc <- randomForestSRC::rfsrc(Surv(time, status) ~ .,
+#                                     data = flc,
+#                                     nodesize = 10,
+#                                     samptype = 'swr')
+#
+#
+# microbenchmark::microbenchmark(
+#  orsf = predict(fit_orsf, new_data = flc),
+#  rfsrc = predict(fit_rfsrc, newdata = flc),
+#  times = 3
+# )