R/get_sweep_pair_counts.R
get_sweep_pair_counts.RdRetrieves the pairwise connection propensity counts from latest MCMC sweep on an sbm_network object. Needs to have
mcmc_sweep(track_pairs = TRUE) run on the object before.
get_sweep_pair_counts(sbm, isolate_type = NULL)
| sbm | Object of class |
|---|---|
| isolate_type | Node type to be isolated for visualization. If left empty all types are included. |
pairwise connection propensity counts from latest MCMC sweep
Other helpers:
build_score_fn(),
combination_indices(),
get_sweep_results(),
print.sbm_network(),
rolling_mean(),
verify_model()
# Start with a small random network net <- sim_basic_block_network(n_blocks = 3, n_nodes_per_block = 15) %>% initialize_blocks(n_blocks = 4) %>% mcmc_sweep(num_sweeps = 4, variable_n_blocks = FALSE) # Retrieve the sweep results from network get_sweep_results(net)#> $nodes_moved #> [1] "g3_1" "g1_4" "g2_4" "g2_12" "g2_7" "g1_15" "g1_11" "g3_10" "g3_5" #> [10] "g1_3" "g1_5" "g1_9" "g1_1" "g2_6" "g2_2" "g3_7" "g2_10" "g2_15" #> [19] "g2_11" "g3_13" "g3_12" "g2_1" "g3_3" "g1_8" "g3_14" "g2_6" "g2_7" #> [28] "g1_5" "g1_2" "g1_9" "g3_2" "g1_6" "g2_14" "g1_1" "g1_10" "g3_3" #> [37] "g3_5" "g2_2" "g2_9" "g2_10" "g1_13" "g3_8" "g1_12" "g2_7" "g1_13" #> [46] "g2_15" "g2_8" "g3_4" "g2_4" "g2_2" "g3_13" "g3_7" "g1_8" "g1_11" #> [55] "g2_11" "g1_12" "g3_12" "g3_3" "g1_14" "g1_3" "g2_9" "g3_11" "g1_2" #> [64] "g2_14" "g3_2" "g1_15" "g2_5" "g2_3" "g1_6" "g3_4" "g2_10" "g1_5" #> [73] "g1_2" "g3_2" "g1_12" "g3_10" "g2_4" "g1_9" "g2_13" "g2_11" "g3_14" #> [82] "g2_3" "g1_13" "g3_5" "g1_15" "g3_8" "g3_6" "g1_7" "g2_5" #> #> $sweep_info #> entropy_delta n_nodes_moved #> 1 -2.0507433 23 #> 2 0.9396352 20 #> 3 -1.0845948 26 #> 4 1.6959935 20 #>