inst/doc/network-objects.R

In EpiModel: Mathematical Modeling of Infectious Disease Dynamics

## ----echo = FALSE, include = FALSE--------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## ----setup, echo = FALSE, include = FALSE-------------------------------------
library(EpiModel)

## ----eval = FALSE-------------------------------------------------------------
# # Get the network for layer 1
# nw <- get_network(dat, network = 1)
# 
# # After modifying a network, set it back
# dat <- set_network(dat, network = 1, nw = nw)

## ----eval = FALSE-------------------------------------------------------------
# sim <- netsim(est, param, init, control)
# 
# # Extract the network from simulation 1, network layer 1
# nw <- get_network(sim, sim = 1, network = 1)
# 
# # Collapse to a static cross-section at time step 50 (full mode only)
# nw_at_50 <- get_network(sim, sim = 1, collapse = TRUE, at = 50)

## ----eval = FALSE-------------------------------------------------------------
# transmat <- get_transmat(sim, sim = 1)

## ----eval = FALSE-------------------------------------------------------------
# el <- get_edgelist(dat, network = 1)

## ----eval = FALSE-------------------------------------------------------------
# # All networks
# el_all <- get_edgelists_df(dat, networks = NULL)
# 
# # Specific networks
# el_12 <- get_edgelists_df(dat, networks = c(1, 2))

## ----eval = FALSE-------------------------------------------------------------
# disc_el <- get_discordant_edgelist(
#   dat,
#   status.attr = "status",
#   head.status = "i",
#   tail.status = "s"
# )

## ----eval = FALSE-------------------------------------------------------------
# control <- control.net(
#   type = "SI",
#   nsims = 1,
#   nsteps = 100,
#   cumulative.edgelist = TRUE,       # Enable tracking during simulation
#   save.cumulative.edgelist = TRUE,  # Save in output after simulation
#   verbose = FALSE
# )

## ----eval = FALSE-------------------------------------------------------------
# dat <- update_cumulative_edgelist(dat, network = 1, truncate = Inf)

## ----eval = FALSE-------------------------------------------------------------
# for (n_network in seq_len(dat$num.nw)) {
#   dat <- update_cumulative_edgelist(dat, n_network, truncate = 100)
# }

## ----eval = FALSE-------------------------------------------------------------
# el_cuml <- get_cumulative_edgelist(dat, network = 1)

## ----eval = FALSE-------------------------------------------------------------
# el_cumls <- get_cumulative_edgelists_df(dat, networks = NULL)

## ----eval = FALSE-------------------------------------------------------------
# partner_list <- get_partners(
#     dat,
#     index_posit_ids,
#     networks = NULL,
#     truncate = Inf,
#     only.active.nodes = FALSE
# )

## ----eval = FALSE-------------------------------------------------------------
# cum_degree <- get_cumulative_degree(
#     dat,
#     index_posit_ids = 1:50,
#     networks = NULL,
#     truncate = Inf,
#     only.active.nodes = FALSE
# )

## ----eval = FALSE-------------------------------------------------------------
# el_cuml <- get_cumulative_edgelist(dat, network = 1)
# 
# fwd <- get_forward_reachable(
#   el_cuml,
#   from_step = 1,
#   to_step = 52,
#   nodes = c(10, 25, 42),  # NULL for all nodes with edges
#   dense_optim = "auto"
# )

## ----eval = FALSE-------------------------------------------------------------
# bkwd <- get_backward_reachable(
#   el_cuml,
#   from_step = 1,
#   to_step = 52,
#   nodes = c(10, 25, 42)
# )

## ----eval = FALSE-------------------------------------------------------------
# progressr::with_progress({
#   fwd <- get_forward_reachable(el_cuml, from_step = 1, to_step = 260)
# })