From fa0559a8476104a87ee508ee081eb7ca1054ab1c Mon Sep 17 00:00:00 2001
From: wendycwong <wendy.wong@h2o.ai>
Date: Tue, 22 Oct 2024 19:38:23 -0700
Subject: [PATCH] remove functions that are deleted.

---
 .../hglm/runit_GH_8487_HGLM_testAgainstR1.R   | 57 -------------------
 .../hglm/runit_GH_8487_coefs_check.R          |  4 --
 2 files changed, 61 deletions(-)
 delete mode 100644 h2o-r/tests/testdir_algos/hglm/runit_GH_8487_HGLM_testAgainstR1.R

diff --git a/h2o-r/tests/testdir_algos/hglm/runit_GH_8487_HGLM_testAgainstR1.R b/h2o-r/tests/testdir_algos/hglm/runit_GH_8487_HGLM_testAgainstR1.R
deleted file mode 100644
index 3bba2d1d5dce..000000000000
--- a/h2o-r/tests/testdir_algos/hglm/runit_GH_8487_HGLM_testAgainstR1.R
+++ /dev/null
@@ -1,57 +0,0 @@
-setwd(normalizePath(dirname(R.utils::commandArgs(asValues=TRUE)$"f")))
-source("../../../scripts/h2o-r-test-setup.R")
-##
-# Copy example from HGLM package and compare results from our implementation.  This test should be 
-# enabled after we implemented the version using hlikelihood.
-##
-
-test.HGLMData1 <- function() {
-  tol = 2e-2
-  h2odata <- h2o.importFile(locate("smalldata/hglm_test/semiconductor.csv"))
-  h2odata$Device <- h2o.asfactor(h2odata$Device)
-  yresp <- "y"
-  xlist <- c("x1", "x3", "x5", "x6")
-  z <- c(1)
-  hglm_model <- h2o.hglm(x=xlist, y=yresp, training_frame=h2odata, random_columns=xlist, group_column="Device")
-
-  print(hglm_model)
-  summary(hglm_model)
-  modelMetrics = h2o.HGLMMetrics(hglm_model) # grab HGLM model metrics
-  
-  # correct R outputs
-  # rModelMetrics <- list(hlik = 363.6833,
-  # pvh = 272.1705,
-  # pbvh =  241.1754,
-  # caic= -550.9321,
-  # fixef = c(0.001929687,0.002817188,-0.001707813,-0.003889063, 0.010685938),
-  # ranef = c( 0.0033338907,0.0004762701,-0.0029608332,-0.0018242513,-0.0003195859,0.0015680851,
-  #            0.0002648708,0.0038885029,0.0010084988,-0.0027494339,0.0022346145,0.0004812442,
-  #            -0.0018938887,-0.0031647713,-0.0016675671,0.0013243542),
-  # varfix = 0.00000862277,
-  # varranef = 0.000008353105,
-  # sefe = c(0.0008120345,0.0008120345,0.0008120345,0.0008120345,0.0008120345),
-  # sere = c(0.001949972,0.001949972,0.001949972,0.001949972,0.001949972,0.001949972,0.001949972, 0.001949972,
-  #          0.001949972,0.001949972,0.001949972,0.001949972,0.001949972,0.001949972,0.001949972,0.001949972),
-  # dfrefe = 50,
-  # summvc1 = c(-11.6611042,0.1995106),
-  # summvc2 = c(-11.6928772,0.4779708))
-
-  # compare H2O output with R outputs
-#  expect_true(abs(rModelMetrics$hlik-modelMetrics$hlik)<tol, "R hlik and H2O-3 hlik differ too much.")
- # expect_true(abs(rModelMetrics$pvh-modelMetrics$pvh)<tol, "R pvh and H2O-3 pvh differ too much.")
-#  expect_true(abs(rModelMetrics$pbvh-modelMetrics$pbvh)<tol, "R pbvh and H2O-3 pbvh differ too much.")
-#  expect_true(abs(rModelMetrics$caic-modelMetrics$caic)<tol, "R caic and H2O-3 caic differ too much.")
-#  compare_arrays(rModelMetrics$fixef, modelMetrics$fixef, tol)
-#  compare_arrays(rModelMetrics$ranef, modelMetrics$ranef, tol)
-#  expect_true(abs(rModelMetrics$varfix-modelMetrics$varfix)<tol, "R varfix and H2O-3 varfix differ too much.")
-#  expect_true(abs(rModelMetrics$varranef-modelMetrics$varranef)<tol, "R varranef and H2O-3 varranef differ too much.")
-#  compare_arrays(rModelMetrics$sefe, modelMetrics$sefe, tol)
- # compare_arrays(rModelMetrics$sere, modelMetrics$sere, tol)
-#  expect_true(abs(rModelMetrics$dfrefe-modelMetrics$dfrefe)<tol, "R dfrefe and H2O-3 dfrefe differ too much.")
- # compare_arrays(rModelMetrics$summvc1, modelMetrics$summvc1, tol)
-#  compare_arrays(rModelMetrics$summvc2, modelMetrics$summvc2, tol)
- }
-
-doTest("Comparison of H2O to R with HGLM 1", test.HGLMData1)
-
-
diff --git a/h2o-r/tests/testdir_algos/hglm/runit_GH_8487_coefs_check.R b/h2o-r/tests/testdir_algos/hglm/runit_GH_8487_coefs_check.R
index 7742f29fdf8a..8ff49221adec 100644
--- a/h2o-r/tests/testdir_algos/hglm/runit_GH_8487_coefs_check.R
+++ b/h2o-r/tests/testdir_algos/hglm/runit_GH_8487_coefs_check.R
@@ -15,10 +15,8 @@ test.HGLMData1 <- function() {
                          seed=12345, max_iterations=10, em_epsilon=0.0000001, random_intercept=TRUE)
   coeff <- h2o.coef(hglm_model)
   coeff_random_effects <- h2o.coef_random(hglm_model)
-  coeff_random_effects_norm <- h2o.coef_random_norm(hglm_model)
   level_2_names <- h2o.level_2_names(hglm_model)
   coefs_random_names <- h2o.coefs_random_names(hglm_model)
-  coefs_random_names_norm <- h2o.coefs_random_names_norm(hglm_model)
   scoring_history <- h2o.scoring_history(hglm_model)
   t_mat <- h2o.matrix_T(hglm_model)
   residual_var <- h2o.residual_variance(hglm_model)
@@ -29,9 +27,7 @@ test.HGLMData1 <- function() {
   expect_true(mse < mean_res_fixed)
   expect_true(length(icc)==length(coeff))
   expect_true(length(level_2_names)*length(coefs_random_names) == length(coeff_random_effects))
-  expect_true(length(coeff_random_effects) == length(coeff_random_effects_norm))
   expect_true(residual_var < mean_res_fixed)
-  expect_true(length(t_mat) == length(coefs_random_names)*length(coefs_random_names_norm))
   expect_true(length(scoring_history[[1]]) <= 10)
   print(hglm_model)
  }