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Run Parameter Sweep Experiment

Source: R/run_param_sweep.R
run_param_sweep.Rd

Orchestrates a comprehensive parameter sweep experiment to evaluate the performance of MFA, MPCA, and baseline methods using the v2 dynamic synergy simulator with three orthogonal control axes.

Usage

run_param_sweep(
  test = FALSE,
  cores = 4,
  output_dir = NULL,
  param_grid = NULL,
  verbose = TRUE
)

Arguments

test

Logical. If TRUE, uses a smaller test grid for quick validation. Default is FALSE (full parameter grid).

cores

Integer. Number of CPU cores to use for parallel processing. Default is 4. Set to 1 for sequential processing.

output_dir

Character. Directory to save results. Default is "inst/paper/results_sweep" if it exists (repo use), otherwise "results_sweep" in the current working directory.

param_grid

Optional. Custom parameter grid data frame. If NULL, uses the built-in full or test grid based on the test parameter.

verbose

Logical. If TRUE, prints progress information. Default is TRUE.

Value

Invisibly returns a list containing:

  • raw_results: Data frame with raw results from all runs

  • aggregated_results: Data frame with results aggregated across seeds

  • summary_file: Path to the summary CSV file

  • win_rates_file: Path to the win rates CSV file

  • output_dir: Directory where results were saved

Details

The parameter sweep evaluates:

  • 6 methods: SingleFA, SinglePCA, TwoStep_FA, TwoStep_PCA, MixtureFA, MixturePCA

  • 2 model types: Mixture (static) vs Dynamic_v2 (with 3 orthogonal axes)

  • Metrics: ARI (clustering accuracy), VAF (reconstruction quality), BIC, SSE

  • Variable parameters: N, K, r, cluster_sep_spatial, cluster_sep_temporal, cluster_sep_stability

For parallel processing (cores > 1), the function uses parLapplyLB for load balancing. If the pbapply package is installed, a progress bar will be displayed.

Examples

if (FALSE) { # \dontrun{
# Run test mode with 2 cores
results <- run_param_sweep(test = TRUE, cores = 2)

# Run full sweep with 8 cores
results <- run_param_sweep(test = FALSE, cores = 8)

# Run with custom output directory
results <- run_param_sweep(test = TRUE, cores = 2, output_dir = "my_results")

# Run with custom parameter grid
library(dplyr)
custom_grid <- expand.grid(
  N = c(20, 50),
  K = c(2, 3),
  r = 2,
  M = 8,
  T_each = 200,
  cluster_sep_spatial = c(0.3, 0.6),
  cluster_sep_temporal = 0.6,
  cluster_sep_stability = 1.0,
  seed = 1:3,
  stringsAsFactors = FALSE
)
custom_grid$run_id <- seq_len(nrow(custom_grid))

results <- run_param_sweep(
  param_grid = custom_grid,
  cores = 8,
  output_dir = "inst/paper/results_custom"
)

# Access results directly
head(results$raw_results)
head(results$aggregated_results)
} # }