tests/testthat/test-0_plot_ice_b.R

In familiar: End-to-End Automated Machine Learning and Model Evaluation

# Don't perform any further tests on CRAN due to time of running the complete
# test.
testthat::skip_on_cran()
testthat::skip_on_ci()

debug_flag <- FALSE

# Test alignment of different plots, with missing data.
familiar:::test_plot_ordering(
  plot_function = familiar:::plot_ice,
  data_element = "ice_data",
  outcome_type_available = "survival",
  features = c("adhere"),
  sample_limit = 20L,
  n_sample_points = 10L,
  debug = debug_flag
)

# 1D plot without novelty, and with anchored values.
familiar:::test_plot_ordering(
  plot_function = familiar:::plot_ice,
  data_element = "ice_data",
  outcome_type_available = "survival",
  features = c("nodes"),
  plot_args = list(
    "anchor_values" = list("nodes" = 2.5),
    "value_scales" = "figure"),
  sample_limit = 20L,
  n_sample_points = 10L,
  debug = debug_flag
)

# 1D plot with novelty, and with anchored values.
familiar:::test_plot_ordering(
  plot_function = familiar:::plot_ice,
  data_element = "ice_data",
  outcome_type_available = "survival",
  features = c("nodes"),
  plot_args = list(
    "anchor_values" = list("nodes" = 2.5),
    "value_scales" = "figure"),
  sample_limit = 20L,
  n_sample_points = 10L,
  create_novelty_detector = TRUE,
  debug = debug_flag
)

# 1D plot with novelty, but no ICE
familiar:::test_plot_ordering(
  plot_function = familiar:::plot_ice,
  data_element = "ice_data",
  outcome_type_available = "survival",
  features = c("nodes"),
  plot_args = list("show_ice" = FALSE),
  sample_limit = 20L,
  n_sample_points = 10L,
  create_novelty_detector = TRUE,
  debug = debug_flag
)

# 1D plot with novelty, but no PD
familiar:::test_plot_ordering(
  plot_function = familiar:::plot_ice,
  data_element = "ice_data",
  outcome_type_available = "survival",
  features = c("nodes"),
  plot_args = list("show_pd" = FALSE),
  sample_limit = 20L,
  n_sample_points = 10L,
  create_novelty_detector = TRUE,
  debug = debug_flag
)


# 1D plot with novelty and colouring, and with anchored values.
familiar:::test_plot_ordering(
  plot_function = familiar:::plot_ice,
  data_element = "ice_data",
  outcome_type_available = "multinomial",
  features = c("Sepal_Length"),
  plot_args = list(
    "anchor_values" = list("Sepal_Length" = 5.05),
    "value_scales" = "figure",
    "color_by" = "positive_class",
    "facet_by" = c("data_set", "fs_method", "learner")),
  sample_limit = 20L,
  n_sample_points = 10L,
  create_novelty_detector = TRUE,
  debug = debug_flag
)


# 1D plot with novelty and colouring, with anchored values and scaling per
# facet.
familiar:::test_plot_ordering(
  plot_function = familiar:::plot_ice,
  data_element = "ice_data",
  outcome_type_available = "multinomial",
  features = c("Sepal_Length"),
  plot_args = list(
    "anchor_values" = list("Sepal_Length" = 5.05),
    "value_scales" = "facet",
    "color_by" = "positive_class",
    "facet_by" = c("data_set", "fs_method", "learner")),
  sample_limit = 20L,
  n_sample_points = 10L,
  create_novelty_detector = TRUE,
  debug = debug_flag
)


# 1D plot with novelty and colouring, and with anchored values.
familiar:::test_plot_ordering(
  plot_function = familiar:::plot_ice,
  data_element = "ice_data",
  outcome_type_available = "multinomial",
  features = c("Sepal_Length"),
  plot_args = list(
    "anchor_values" = list("Sepal_Length" = 5.05),
    "value_scales" = "figure",
    "split_by" = c("fs_method", "learner"),
    "color_by" = "positive_class",
    "facet_by" = "data_set"),
  sample_limit = 20L,
  n_sample_points = 10L,
  create_novelty_detector = TRUE,
  debug = debug_flag
)

# 2D plot without novelty, and with anchored values.
familiar:::test_plot_ordering(
  plot_function = familiar:::plot_ice,
  data_element = "ice_data",
  outcome_type_available = "survival",
  features = c("rx", "nodes"),
  plot_args = list(
    "anchor_values" = list(
      "rx" = "Obs",
      "nodes" = 2.5),
    "value_scales" = "figure"),
  sample_limit = 20L,
  n_sample_points = 10L,
  debug = debug_flag
)

# 2D plot with novelty, and with anchored values.
familiar:::test_plot_ordering(
  plot_function = familiar:::plot_ice,
  data_element = "ice_data",
  outcome_type_available = "survival",
  features = c("rx", "nodes"),
  plot_args = list(
    "anchor_values" = list(
      "rx" = "Obs",
      "nodes" = 2.5),
    "value_scales" = "figure"),
  sample_limit = 20L,
  n_sample_points = 10L,
  create_novelty_detector = TRUE,
  debug = debug_flag
)

# 2D plot with novelty, and with anchored values.
familiar:::test_plot_ordering(
  plot_function = familiar:::plot_ice,
  data_element = "ice_data",
  outcome_type_available = "multinomial",
  features = c("Sepal_Length", "Petal_Width"),
  plot_args = list(
    "anchor_values" = list(
      "Sepal_Length" = 5.05,
      "Petal_Width" = 1.05),
    "value_scales" = "figure"),
  sample_limit = 20L,
  n_sample_points = 10L,
  debug = debug_flag
)