Calculate AUC Metrics — calculate

Calculates AUROC and AUPRC metrics with optional visualization

Usage

calculate_auc(
  network_table,
  ground_truth,
  return_plot = FALSE,
  line_color = "#1563cc",
  line_width = 1,
  tag_levels = "A"
)

Arguments

network_table: A data frame of predicted network structure
ground_truth: A data frame of ground truth network
return_plot: Logical value indicating whether to generate plots
line_color: Color for plot lines
line_width: Width for plot lines
tag_levels: Tag levels for plot annotations

Value

A list containing metrics and optional plots

Examples

data(example_matrix)
data("example_ground_truth")
network_table <- inferCSN(example_matrix)
#> ℹ [2025-10-30 09:48:56] Running for <dense matrix>.
#> ◌ [2025-10-30 09:48:56] Checking input parameters...
#> ℹ [2025-10-30 09:48:56] Using `L0` sparse regression model
#> ℹ [2025-10-30 09:48:56] Using 1 core
#> ⠙ [2025-10-30 09:48:56] Running [1/18] ETA:  0s
#> ✔ [2025-10-30 09:48:56] Completed 18 tasks in 227ms
#> 
#> ℹ [2025-10-30 09:48:56] Building results
#> ✔ [2025-10-30 09:48:56] Run done.
calculate_auc(
  network_table,
  example_ground_truth,
  return_plot = TRUE
)
#> $metrics
#>   Metric Value
#> 1  AUROC 0.952
#> 2  AUPRC 0.437
#> 
#> $plot

#>