snapshots: The network sliced into snapshots

In Dynet: Tidy Temporal Network Analysis

The network sliced into snapshots

Description

The edges alive in each time bin, as one tidy table. Useful for exporting a slice, for feeding a layout routine, or for checking by eye what the metric verbs are seeing.

Usage

snapshots(
  dn,
  at = NULL,
  sessions = c("bounded", "collapse", "separate"),
  sample = NULL,
  start = NULL,
  end = NULL,
  step = NULL,
  window = NULL,
  plot = FALSE
)

Arguments

dn	A temporal network from dynet().
at	Optional single time, narrowing the result to the bins that cover it. A network built from dates may be addressed with a date. With the default disjoint tiling that is one bin; with an overlapping window every bin containing the time is returned. A time outside every bin falls back to the nearest bin rather than failing, but that bin may itself hold no active tie, in which case the result is a zero-row frame with the documented columns.
sessions	How to treat sessions, as in centrality_series(): "bounded" (the default), "collapse" or "separate". "separate" needs a network built with a session column and raises dynet_no_sessions otherwise.
sample	Deprecated. "instant" is equivalent to window = 0; "window" uses the current positive/default window.
start, end	First and last time at which to measure. Default to the observed range. A network built from dates may be addressed with dates.
step	How often to measure. Defaults to the interval the network was built with.
window	How much time each measurement covers. Defaults to step, which tiles the period into disjoint bins. A larger value slides an overlapping window; 0 samples the network at each point in time. "all" measures the whole observed period as one window, closed on the right so an event at the final instant is inside it; it cannot be combined with step, and under sessions = "separate" or discontinuous observation it gives one window per session or observed component.
plot	Whether to draw the result as well as return it. Drawing is a side effect in the manner of graphics::hist(): the verb still returns its tidy table, invisibly when it has drawn, so plot = TRUE saves the wrapping plot() call without changing what comes back. Use plot() on the result when the figure needs arguments of its own.

Value

A dynet_snapshot data frame with one row per active edge per bin: session (when the network has sessions), observation (when observation is discontinuous, naming the observed component the bin falls in), time, from, to, weight and n_spells. print() shows a header and the first rows, summary() collapses to one row per bin, plot() draws how many ties each bin holds, and as.data.frame() returns the plain table. A pair joined by more than one spell in the same bin is one edge, with n_spells recording how many spells were collapsed – so the edge counts here agree with those from metrics(). weight is the sum of those spells' full weights: a spell counts its whole weight in every bin it touches, as networkDynamic::network.collapse() does. Snapshot "strength" in centrality_series() instead splits a spell's weight by the share of its duration inside the bin. Eligible isolates have no synthetic edge row; use centrality_series() or metrics() when the eligible population itself is required.

Conditions

Errors: dynet_no_sessions (sessions = "separate" without a session column), dynet_outside_observation (the requested range misses observed support; it also carries dynet_bad_input), and dynet_bad_input for every other broken contract – dn not a dynet, an at, start or end that is not a single finite time, and an out-of-range step or window.

Warning: dynet_deprecated for the retired sample argument.

Examples

dn <- dynet(school_contacts)
snapshots(dn, at = 3)

Dynet documentation built on Oct. 7, 2026, 5:08 p.m.