How can I add an event with matrix data in ode solver - r

Question

I have a differential equation model that is running on a network of interactions. Nodes connect to food and can take food at a rate dependent on the size of the food (see first chunk of code).
changes <- function(t, state_a, parameters){
with(as.list(c(state_a, parameters)),{
r <- rowSums(n_mat * food)
dN <- matrix(r * state_a,3,1)
list(c(dN))
})
}
food <- c(0,0.2,0.5)
n_vec <- c(0,0,1,1,0,0,0,1,0)
n_mat <- matrix(n_vec, 3 ,3)
times <- seq(0, 10, by = 1)
state_a <- runif(3, 0, 1000)
parameters <- c(n_mat, food)
out <- ode (y = state_a,
times = times,
func = changes, parms = parameters)
However, I'd like to be able to change the size of the food over time, whilst the differential equations are runnning. For example, if the food looks like the below code (where each row is a timepoint and each column is a food source). It looks like this is possible with using events in the ode solver, but I can't figure out how to do this when I have a matrix of parameters to change, rather than just a single parameter. Is there a good way to do this?
food <- rep(c(0,0.6,0.1,0.4,0.2,0.1,0.2), 6)
food <- matrix(food[1:30],10,3)
colnames(food) <- 1:3
rownames(food) <- 1:10
Below is a working example of ode events where only a single parameter is being changed:
derivs <- function(t, var, parms) {
list(dvar = rep(0, 2))
}
yini <- c(v1 = 1, v2 = 2)
times <- seq(0, 10, by = 0.1)
eventdat <- data.frame(var = c("v1", "v2", "v2", "v1"),
time = c(1, 1, 5, 9) ,
value = c(1, 2, 3, 4),
method = c("add", "mult", "rep", "add"))
eventdat
out <- vode(func = derivs, y = yini, times = times, parms = NULL,
events = list(data = eventdat))
New, but not working code:
calc_food_mat <- function(t, food_df){
return(food_df[which(food_df$time == floor(t)),2] + ((food_df[which(food_df$time == ceiling(t)),2] - food_df[which(food_df$time == floor(t)),2]) * (t - floor(t))))
}
changes <- function(t, state_a, parameters){
with(as.list(c(t, state_a, parameters)),{
food <- calc_food_mat(t, food_df)
r <- rowSums((n_mat * food)[drop = FALSE])
dN <- r * state_a
list(c(dN))
})
}
seasonl <- 40
foodsize <- 4000
foods <- 3
food_seq <- append(seq(foodsize/5, foodsize, foodsize/5), rev(seq(foodsize/5, foodsize, foodsize/5)))
start <- round(runif(foods, -0.5, seasonl - length(food_seq) + 0.5))
food_mat <- matrix(0, foods, seasonl)
for (i in 1:length(start)){
food_mat[i,(start[i]+1):(start[i]+length(food_seq))] <- food_seq
}
food_mat <- data.frame(food_mat)
colnames(food_mat) <- 1:seasonl
rownames(food_mat) <- 1:foods
food_df <- food_mat %>%
gather (key = time, value = resources)
n_vec <- c(0,0,1,1,0,0,0,1,0)
n_mat <- matrix(n_vec, 3 ,3)
times <- seq(0, 40, by = 1)
state_a <- runif(3, 0, 1000)
parameters <- c(n_mat, food_df)
out <- ode (y = state_a,
times = times,
func = changes, parms = parameters)