Mitokic 02202026 unit tests

AGENTS.md

@@ -48,6 +48,7 @@ When adding or changing user-facing behavior:
    - happy path
    - 1–2 edge cases
    - regression test for the bug/feature request (if applicable)
+   - avoid using finnts::: or finnts:: to call internal/exported functions; instead, call them directly (e.g. use `my_function()` instead of `finnts:::my_function()`).
 4. **Docs**:
    - update roxygen comments (`@param`, `@return`, `@examples`)
    - run `devtools::document()` so `man/*.Rd` stays in sync

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: finnts
 Title: Microsoft Finance Time Series Forecasting Framework
-Version: 0.6.0.9022
+Version: 0.6.0.9023
 Authors@R: 
     c(person(given = "Mike",
            family = "Tokic",
@@ -43,6 +43,7 @@ Imports:
     glue, 
     glmnet,
     gtools,
+    hardhat,
     hts,
     kernlab,
     lubridate,

NEWS.md

@@ -1,4 +1,4 @@
-# finnts 0.6.0.9022 (development version)
+# finnts 0.6.0.9023 (development version)
 
 ## Improvements
 - TimeGPT Integration

R/ensemble_models.R

@@ -293,7 +293,7 @@ ensemble_models <- function(run_info,
 
         set.seed(seed)
 
-        grid <- dials::grid_latin_hypercube(parameters, size = num_hyperparameters)
+        grid <- dials::grid_space_filling(parameters, size = num_hyperparameters)
 
         hyperparameters_temp <- grid %>%
           dplyr::group_split(dplyr::row_number(), .keep = FALSE) %>%

R/models.R

@@ -481,15 +481,15 @@ get_kfold_tune_grid <- function(train_data,
     )
 }
 
-#' Get grid_latin_hypercube
+#' Get space-filling grid
 #'
 #' @param model_spec Model Spec Obj
 #'
-#' @return gives the latin hypercube grid
+#' @return gives a space-filling parameter grid
 #' @noRd
-get_latin_hypercube_grid <- function(model_spec) {
-  dials::grid_latin_hypercube(
-    dials::parameters(model_spec),
+get_space_filling_grid <- function(model_spec) {
+  dials::grid_space_filling(
+    hardhat::extract_parameter_set_dials(model_spec),
     size = 10
   )
 }

R/parallel_util.R

@@ -54,8 +54,8 @@ par_start <- function(run_info,
     add_packages <- c(add_packages, "arrow")
   }
 
-  if (run_info$object_output == "qs") {
-    add_packages <- c(add_packages, "qs")
+  if (run_info$object_output == "qs2") {
+    add_packages <- c(add_packages, "qs2")
   }
 
   # register cluster

R/timegpt_model.R

@@ -320,16 +320,22 @@ pad_time_series_data <- function(train_df, date_type, min_size = NULL) {
   }
 
   # For each combo, calculate how far back we need to go to add required rows
-  combos_to_pad <- combos_to_pad %>%
-    dplyr::mutate(
-      start_date = dplyr::case_when(
-        date_type == "day" ~ earliest_date - lubridate::days(rows_to_add),
-        date_type == "week" ~ earliest_date - lubridate::weeks(rows_to_add),
-        date_type == "month" ~ earliest_date - months(rows_to_add),
-        date_type == "quarter" ~ earliest_date - months(rows_to_add * 3),
-        date_type == "year" ~ earliest_date - lubridate::years(rows_to_add)
-      )
-    )
+  if (date_type == "day") {
+    combos_to_pad <- combos_to_pad %>%
+      dplyr::mutate(start_date = earliest_date - lubridate::days(rows_to_add))
+  } else if (date_type == "week") {
+    combos_to_pad <- combos_to_pad %>%
+      dplyr::mutate(start_date = earliest_date - lubridate::weeks(rows_to_add))
+  } else if (date_type == "month") {
+    combos_to_pad <- combos_to_pad %>%
+      dplyr::mutate(start_date = earliest_date - months(rows_to_add))
+  } else if (date_type == "quarter") {
+    combos_to_pad <- combos_to_pad %>%
+      dplyr::mutate(start_date = earliest_date - months(rows_to_add * 3))
+  } else if (date_type == "year") {
+    combos_to_pad <- combos_to_pad %>%
+      dplyr::mutate(start_date = earliest_date - lubridate::years(rows_to_add))
+  }
 
   # Create complete date sequences for each combo
   create_date_sequence <- function(start, end, by_type) {

R/utility.R

@@ -28,7 +28,7 @@ utils::globalVariables(c(
   "to", "total_rows", "weighted_mape", "Analysis_Type", "Metric", "Value_Numeric",
   "is_stationary", "outlier_pct", "model_class", "section", "value", "Hierarchy_Level",
   "Sort_Order", "run_id", "date_type", "file_path", "models_to_run", "underscore_count",
-  "max_iterations", "run_complete"
+  "max_iterations", "run_complete", "earliest_date", "rows_to_add"
 ))
 
 #' @importFrom magrittr %>%