SimInf (version 9.8.1)

trajectory,SimInf_model-method: Extract data from a simulated trajectory

Description

Extract the number of individuals in each compartment in every node after generating a single stochastic trajectory with run.

Usage

# S4 method for SimInf_model
trajectory(model, compartments, index, format = c("data.frame", "matrix"))

Value

A data.frame if format = "data.frame", else a matrix.

Arguments

model

the SimInf_model object to extract the result from.

compartments

specify the names of the compartments to extract data from. The compartments can be specified as a character vector e.g. compartments = c('S', 'I', 'R'), or as a formula e.g. compartments = ~S+I+R (see ‘Examples’). Default (compartments=NULL) is to extract the number of individuals in each compartment i.e. the data from all discrete state compartments in the model. In models that also have continuous state variables e.g. the SISe model, they are also included.

index

indices specifying the subset of nodes to include when extracting data. Default (index = NULL) is to extract data from all nodes.

format

the default (format = "data.frame") is to generate a data.frame with one row per node and time-step with the number of individuals in each compartment. Using format = "matrix" returns the result as a matrix, which is the internal format (see ‘Details’).

Internal format of the discrete state variables

Description of the layout of the internal matrix (U) that is returned if format = "matrix". U[, j] contains the number of individuals in each compartment at tspan[j]. U[1:Nc, j] contains the number of individuals in node 1 at tspan[j]. U[(Nc + 1):(2 * Nc), j] contains the number of individuals in node 2 at tspan[j] etc, where Nc is the number of compartments in the model. The dimension of the matrix is \(N_n N_c \times\) length(tspan) where \(N_n\) is the number of nodes.

Internal format of the continuous state variables

Description of the layout of the matrix that is returned if format = "matrix". The result matrix for the real-valued continuous state. V[, j] contains the real-valued state of the system at tspan[j]. The dimension of the matrix is \(N_n\)dim(ldata)[1] \(\times\) length(tspan).

Examples

## Create an 'SIR' model with 6 nodes and initialize
## it to run over 10 days.
u0 <- data.frame(S = 100:105, I = 1:6, R = rep(0, 6))
model <- SIR(u0 = u0, tspan = 1:10, beta = 0.16, gamma = 0.077)

## Run the model to generate a single stochastic trajectory.
result <- run(model)

## Extract the number of individuals in each compartment at the
## time-points in 'tspan'.
trajectory(result)

## Extract the number of recovered individuals in the first node
## at the time-points in 'tspan'.
trajectory(result, compartments = "R", index = 1)

## Extract the number of recovered individuals in the first and
## third node at the time-points in 'tspan'.
trajectory(result, compartments = "R", index = c(1, 3))

## Create an 'SISe' model with 6 nodes and initialize
## it to run over 10 days.
u0 <- data.frame(S = 100:105, I = 1:6)
model <- SISe(u0 = u0, tspan = 1:10, phi = rep(0, 6),
    upsilon = 0.02, gamma = 0.1, alpha = 1, epsilon = 1.1e-5,
    beta_t1 = 0.15, beta_t2 = 0.15, beta_t3 = 0.15, beta_t4 = 0.15,
    end_t1 = 91, end_t2 = 182, end_t3 = 273, end_t4 = 365)

## Run the model
result <- run(model)

## Extract the continuous state variable 'phi' which represents
## the environmental infectious pressure.
trajectory(result, "phi")