differences for PR #51

files/plans/plan_10.R

@@ -16,27 +16,26 @@ tar_plan(
     path_to_file("penguins_raw.csv"),
     read_csv(!!.x, show_col_types = FALSE)
   ),
-  # Clean data
-  penguins_data = clean_penguin_data(penguins_data_raw),
-  # Build models
-  models = list(
-    combined_model = lm(
-      bill_depth_mm ~ bill_length_mm, data = penguins_data),
-    species_model = lm(
-      bill_depth_mm ~ bill_length_mm + species, data = penguins_data),
-    interaction_model = lm(
-      bill_depth_mm ~ bill_length_mm * species, data = penguins_data)
+  # Clean and group data
+  tar_group_by(
+    penguins_data,
+    clean_penguin_data(penguins_data_raw),
+    species
   ),
-  # Get model summaries
+  # Get summary of combined model with all species together
+  combined_summary = model_glance_slow(penguins_data),
+  # Get summary of one model per species
   tar_target(
-    model_summaries,
-    glance_with_mod_name_slow(models),
-    pattern = map(models)
+    species_summary,
+    model_glance_slow(penguins_data),
+    pattern = map(penguins_data)
   ),
-  # Get model predictions
+  # Get predictions of combined model with all species together
+  combined_predictions = model_augment_slow(penguins_data),
+  # Get predictions of one model per species
   tar_target(
-    model_predictions,
-    augment_with_mod_name_slow(models),
-    pattern = map(models)
+    species_predictions,
+    model_augment_slow(penguins_data),
+    pattern = map(penguins_data)
   )
 )

files/plans/plan_11.R

@@ -9,34 +9,32 @@ tar_plan(
     path_to_file("penguins_raw.csv"),
     read_csv(!!.x, show_col_types = FALSE)
   ),
-  # Clean data
-  penguins_data = clean_penguin_data(penguins_data_raw),
-  # Build models
-  models = list(
-    combined_model = lm(
-      bill_depth_mm ~ bill_length_mm, data = penguins_data),
-    species_model = lm(
-      bill_depth_mm ~ bill_length_mm + species, data = penguins_data),
-    interaction_model = lm(
-      bill_depth_mm ~ bill_length_mm * species, data = penguins_data)
+  # Clean and group data
+  tar_group_by(
+    penguins_data,
+    clean_penguin_data(penguins_data_raw),
+    species
   ),
-  # Get model summaries
+  # Get summary of combined model with all species together
+  combined_summary = model_glance(penguins_data),
+  # Get summary of one model per species
   tar_target(
-    model_summaries,
-    glance_with_mod_name(models),
-    pattern = map(models)
+    species_summary,
+    model_glance(penguins_data),
+    pattern = map(penguins_data)
   ),
-  # Get model predictions
+  # Get predictions of combined model with all species together
+  combined_predictions = model_augment(penguins_data),
+  # Get predictions of one model per species
   tar_target(
-    model_predictions,
-    augment_with_mod_name(models),
-    pattern = map(models)
+    species_predictions,
+    model_augment(penguins_data),
+    pattern = map(penguins_data)
   ),
   # Generate report
   tar_quarto(
     penguin_report,
     path = "penguin_report.qmd",
-    quiet = FALSE,
-    packages = c("targets", "tidyverse")
+    quiet = FALSE
   )
 )

files/plans/plan_5.R

@@ -16,16 +16,21 @@ tar_plan(
     bill_depth_mm ~ bill_length_mm,
     data = penguins_data
   ),
-  species_model = lm(
-    bill_depth_mm ~ bill_length_mm + species,
-    data = penguins_data
+  adelie_model = lm(
+    bill_depth_mm ~ bill_length_mm,
+    data = filter(penguins_data, species == "Adelie")
   ),
-  interaction_model = lm(
-    bill_depth_mm ~ bill_length_mm * species,
-    data = penguins_data
+  chinstrap_model = lm(
+    bill_depth_mm ~ bill_length_mm,
+    data = filter(penguins_data, species == "Chinstrap")
+  ),
+  gentoo_model = lm(
+    bill_depth_mm ~ bill_length_mm,
+    data = filter(penguins_data, species == "Gentoo")
   ),
   # Get model summaries
   combined_summary = glance(combined_model),
-  species_summary = glance(species_model),
-  interaction_summary = glance(interaction_model)
+  adelie_summary = glance(adelie_model),
+  chinstrap_summary = glance(chinstrap_model),
+  gentoo_summary = glance(gentoo_model)
 )

files/plans/plan_6.R

@@ -11,19 +11,18 @@ tar_plan(
   ),
   # Clean data
   penguins_data = clean_penguin_data(penguins_data_raw),
-  # Build models
-  models = list(
-    combined_model = lm(
-      bill_depth_mm ~ bill_length_mm, data = penguins_data),
-    species_model = lm(
-      bill_depth_mm ~ bill_length_mm + species, data = penguins_data),
-    interaction_model = lm(
-      bill_depth_mm ~ bill_length_mm * species, data = penguins_data)
+  # Group data
+  tar_group_by(
+    penguins_data_grouped,
+    penguins_data,
+    species
   ),
-  # Get model summaries
+  # Build combined model with all species together
+  combined_summary = model_glance(penguins_data),
+  # Build one model per species
   tar_target(
-    model_summaries,
-    glance(models[[1]]),
-    pattern = map(models)
+    species_summary,
+    model_glance(penguins_data_grouped),
+    pattern = map(penguins_data_grouped)
   )
 )

files/plans/plan_6b.R

@@ -0,0 +1,28 @@
+options(tidyverse.quiet = TRUE)
+source("R/packages.R")
+source("R/functions.R")
+
+tar_plan(
+  # Load raw data
+  tar_file_read(
+    penguins_data_raw,
+    path_to_file("penguins_raw.csv"),
+    read_csv(!!.x, show_col_types = FALSE)
+  ),
+  # Clean data
+  penguins_data = clean_penguin_data(penguins_data_raw),
+  # Group data
+  tar_group_by(
+    penguins_data_grouped,
+    penguins_data,
+    species
+  ),
+  # Build combined model with all species together
+  combined_summary = model_glance_orig(penguins_data),
+  # Build one model per species
+  tar_target(
+    species_summary,
+    model_glance_orig(penguins_data_grouped),
+    pattern = map(penguins_data_grouped)
+  )
+)

files/plans/plan_7.R

@@ -11,19 +11,26 @@ tar_plan(
   ),
   # Clean data
   penguins_data = clean_penguin_data(penguins_data_raw),
-  # Build models
-  models = list(
-    combined_model = lm(
-      bill_depth_mm ~ bill_length_mm, data = penguins_data),
-    species_model = lm(
-      bill_depth_mm ~ bill_length_mm + species, data = penguins_data),
-    interaction_model = lm(
-      bill_depth_mm ~ bill_length_mm * species, data = penguins_data)
+  # Group data
+  tar_group_by(
+    penguins_data_grouped,
+    penguins_data,
+    species
   ),
-  # Get model summaries
+  # Get summary of combined model with all species together
+  combined_summary = model_glance(penguins_data),
+  # Get summary of one model per species
   tar_target(
-    model_summaries,
-    glance_with_mod_name(models),
-    pattern = map(models)
+    species_summary,
+    model_glance(penguins_data_grouped),
+    pattern = map(penguins_data_grouped)
+  ),
+  # Get predictions of combined model with all species together
+  combined_predictions = model_augment(penguins_data_grouped),
+  # Get predictions of one model per species
+  tar_target(
+    species_predictions,
+    model_augment(penguins_data_grouped),
+    pattern = map(penguins_data_grouped)
   )
 )

files/plans/plan_8.R

@@ -9,27 +9,26 @@ tar_plan(
     path_to_file("penguins_raw.csv"),
     read_csv(!!.x, show_col_types = FALSE)
   ),
-  # Clean data
-  penguins_data = clean_penguin_data(penguins_data_raw),
-  # Build models
-  models = list(
-    combined_model = lm(
-      bill_depth_mm ~ bill_length_mm, data = penguins_data),
-    species_model = lm(
-      bill_depth_mm ~ bill_length_mm + species, data = penguins_data),
-    interaction_model = lm(
-      bill_depth_mm ~ bill_length_mm * species, data = penguins_data)
+  # Clean and group data
+  tar_group_by(
+    penguins_data,
+    clean_penguin_data(penguins_data_raw),
+    species
   ),
-  # Get model summaries
+  # Get summary of combined model with all species together
+  combined_summary = model_glance(penguins_data),
+  # Get summary of one model per species
   tar_target(
-    model_summaries,
-    glance_with_mod_name(models),
-    pattern = map(models)
+    species_summary,
+    model_glance(penguins_data),
+    pattern = map(penguins_data)
   ),
-  # Get model predictions
+  # Get predictions of combined model with all species together
+  combined_predictions = model_augment(penguins_data),
+  # Get predictions of one model per species
   tar_target(
-    model_predictions,
-    augment_with_mod_name(models),
-    pattern = map(models)
+    species_predictions,
+    model_augment(penguins_data),
+    pattern = map(penguins_data)
   )
 )

files/plans/plan_9.R

@@ -16,27 +16,26 @@ tar_plan(
     path_to_file("penguins_raw.csv"),
     read_csv(!!.x, show_col_types = FALSE)
   ),
-  # Clean data
-  penguins_data = clean_penguin_data(penguins_data_raw),
-  # Build models
-  models = list(
-    combined_model = lm(
-      bill_depth_mm ~ bill_length_mm, data = penguins_data),
-    species_model = lm(
-      bill_depth_mm ~ bill_length_mm + species, data = penguins_data),
-    interaction_model = lm(
-      bill_depth_mm ~ bill_length_mm * species, data = penguins_data)
+  # Clean and group data
+  tar_group_by(
+    penguins_data,
+    clean_penguin_data(penguins_data_raw),
+    species
   ),
-  # Get model summaries
+  # Get summary of combined model with all species together
+  combined_summary = model_glance(penguins_data),
+  # Get summary of one model per species
   tar_target(
-    model_summaries,
-    glance_with_mod_name(models),
-    pattern = map(models)
+    species_summary,
+    model_glance(penguins_data),
+    pattern = map(penguins_data)
   ),
-  # Get model predictions
+  # Get predictions of combined model with all species together
+  combined_predictions = model_augment(penguins_data),
+  # Get predictions of one model per species
   tar_target(
-    model_predictions,
-    augment_with_mod_name(models),
-    pattern = map(models)
+    species_predictions,
+    model_augment(penguins_data),
+    pattern = map(penguins_data)
   )
 )

files/tar_functions/model_augment.R

@@ -0,0 +1,16 @@
+model_augment <- function(penguins_data) {
+  # Make model
+  model <- lm(
+    bill_depth_mm ~ bill_length_mm,
+    data = penguins_data)
+  # Get species name
+  species_name <- unique(penguins_data$species)
+  # If this is the combined dataset with multiple
+  # species, changed name to 'combined'
+  if (length(species_name) > 1) {
+    species_name <- "combined"
+  }
+  # Get model summary and add species name
+  augment(model) |>
+    mutate(species = species_name, .before = 1)
+}

files/tar_functions/model_augment_slow.R

@@ -0,0 +1,17 @@
+model_augment_slow <- function(penguins_data) {
+  Sys.sleep(4)
+  # Make model
+  model <- lm(
+    bill_depth_mm ~ bill_length_mm,
+    data = penguins_data)
+  # Get species name
+  species_name <- unique(penguins_data$species)
+  # If this is the combined dataset with multiple
+  # species, changed name to 'combined'
+  if (length(species_name) > 1) {
+    species_name <- "combined"
+  }
+  # Get model summary and add species name
+  augment(model) |>
+    mutate(species = species_name, .before = 1)
+}

files/tar_functions/model_glance.R

@@ -0,0 +1,16 @@
+model_glance <- function(penguins_data) {
+  # Make model
+  model <- lm(
+    bill_depth_mm ~ bill_length_mm,
+    data = penguins_data)
+  # Get species name
+  species_name <- unique(penguins_data$species)
+  # If this is the combined dataset with multiple
+  # species, changed name to 'combined'
+  if (length(species_name) > 1) {
+    species_name <- "combined"
+  }
+  # Get model summary and add species name
+  glance(model) |>
+    mutate(species = species_name, .before = 1)
+}

files/tar_functions/model_glance_orig.R

@@ -0,0 +1,6 @@
+model_glance_orig <- function(penguins_data) {
+  model <- lm(
+    bill_depth_mm ~ bill_length_mm,
+    data = penguins_data)
+  broom::glance(model)
+}

files/tar_functions/model_glance_slow.R

@@ -0,0 +1,17 @@
+model_glance_slow <- function(penguins_data) {
+  Sys.sleep(4)
+  # Make model
+  model <- lm(
+    bill_depth_mm ~ bill_length_mm,
+    data = penguins_data)
+  # Get species name
+  species_name <- unique(penguins_data$species)
+  # If this is the combined dataset with multiple
+  # species, changed name to 'combined'
+  if (length(species_name) > 1) {
+    species_name <- "combined"
+  }
+  # Get model summary and add species name
+  glance(model) |>
+    mutate(species = species_name, .before = 1)
+}