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Coerce a SimInf_events object to a data.frame

Source: R/SimInf_events.R
as.data.frame.SimInf_events.Rd

Convert the scheduled events stored in a SimInf_events object into a data.frame. This function extracts the event type, time, source node, destination node, number of individuals, proportion, and the specific columns from the select (E) and shift (N) matrices that define how each event modifies the compartment state. The resulting data.frame has one row per scheduled event.

Usage

# S3 method for class 'SimInf_events'
as.data.frame(x, ...)

Arguments

x

A SimInf_events object.

...

Additional arguments (currently ignored).

Value

A data.frame with columns:

  • event: Event type (integer or character, depending on input).

  • time: Time of the event (integer or Date, depending on input).

  • node: Source node identifier.

  • dest: Destination node identifier (may be NA).

  • n: Number of individuals affected.

  • proportion: Proportion of the population affected (if applicable).

  • select: The column vector from the select matrix (E) that defines how the event modifies the compartment state.

  • shift: The column vector from the shift matrix (N) that defines how the event modifies the compartment state.

See also

SimInf_events for the class definition and events for extracting events from a model.

Examples

## Create an 'SIR' model with 1600 cattle herds (nodes) and
## initialize it to run over 4*365 days. Define 'tspan' to record
## the state of the system at daily time-points. Load scheduled
## events for the population of nodes with births, deaths and
## between-node movements of individuals.
model <- SIR(
  u0     = u0_SIR(),
  tspan  = seq(from = 1, to = 4*365, by = 1),
  events = events_SIR(),
  beta   = 0.16,
  gamma  = 0.01
)

## Extract the events from the model and convert to a data frame.
head(as.data.frame(events(model)))
#>   event time node dest n proportion select shift
#> 1  exit    1    6    0 1          0      4     0
#> 2  exit    1   12    0 1          0      4     0
#> 3  exit    1   30    0 1          0      4     0
#> 4  exit    1   46    0 1          0      4     0
#> 5  exit    1   55    0 1          0      4     0
#> 6  exit    1   57    0 1          0      4     0