## ----setup--------------------------------------------------------------------
library(netOP)

## ----network------------------------------------------------------------------
A <- generate_sbm(
  n = 200,
  K = 3,
  alpha = 0.5,
  beta = 0.08,
  seed = 2026,
  ncores = 1
)
truth <- get_generator_parameters(A)
table(truth$g_true)

## ----block-selection, eval=FALSE----------------------------------------------
# netcrop_fit <- netcrop_blockmodel(
#   A, K_candidates = 1:5,
#   nrep = 1, ncores = 1, seed = 1, verbose = FALSE
# )
# 
# ecv_fit <- ecv_stability_blockmodel(
#   A, max_K = 5,
#   nrep = 1, ncores = 1, seed = 1, verbose = FALSE
# )
# 
# ncv_fit <- ncv_stability_blockmodel(
#   A, max_K = 5,
#   nrep = 1L, ncores = 1, seed = 1, verbose = FALSE
# )

## ----dimension-selection, eval=FALSE------------------------------------------
# rdpg_fit <- netcrop_rdpg(
#   A, d_candidates = 1:5,
#   nrep = 1, ncores = 1, seed = 2, verbose = FALSE
# )
# 
# ecv_rdpg_fit <- ecv_stability_rdpg(
#   A, max_d = 5,
#   nrep = 1, ncores = 1, seed = 2, verbose = FALSE
# )
# 
# lsm_fit <- netcrop_lsm(
#   A, d_candidates = 1:5,
#   nrep = 1, ncores = 1, seed = 2, verbose = FALSE
# )