Creating a stochastic SIR model in Julia - julia

Question

I am new to julia and want to create a Stochastic SIR model by following: http://epirecip.es/epicookbook/chapters/sir-stochastic-discretestate-continuoustime/julia
I have written my own interpretation which is nearly the same:
# Following the Gillespie algorthim:
# 1. Initialization of states & parameters
# 2. Monte-carlo step. Random process/step selection.
# 3. Update all states. e.g., I = I + 1 (increase of infected by 1 person). Note: only +/- by 1.
# 4. Repeat until stopTime.
# p - Parameter array: β, ɣ for infected rate and recovered rate, resp.
# initialState - initial states of S, I, R information.
# stopTime - Total run time.
using Plots, Distributions
function stochasticSIR(p, initialState, stopTime)
# Hold the states of S,I,R separately w/ a NamedTuple. See '? NamedTuple' in the REML for details
# Populate the data storage arrays with the initial data and initialize the run time
sirData = (dataₛ = [initialState[1]], dataᵢ = [initialState[2]], dataᵣ = [initialState[3]], time = [0]);
while sirData.time[end] < stopTime
if sirData.dataᵢ[end] == 0 # If somehow # of infected = 0, break the loop.
break
end
# Probabilities of each process (infection, recovery). p[1] = β and p[2] = ɣ
probᵢ = p[1] * sirData.dataₛ[end] * sirData.dataᵢ[end];
probᵣ = p[2] * sirData.dataᵣ[end];
probₜ = probᵢ + probᵣ; # Total reaction rate
# When the next process happens
k = rand(Exponential(1/probₜ));
push!(sirData.time, sirData.time[end] + k) # time step by k
# Probability that the reaction is:
# probᵢ, probᵣ resp. is: probᵢ / probₜ, probᵣ / probₜ
randNum = rand();
# Update the states by randomly picking process (Gillespie algo.)
if randNum < (probᵢ / probₜ)
push!(sirData.dataₛ, sirData.dataₛ[end] - 1);
push!(sirData.dataᵢ, sirData.dataᵢ[end] + 1);
else
push!(sirData.dataᵢ, sirData.dataᵢ[end] - 1);
push!(sirData.dataᵣ, sirData.dataᵣ[end] +1)
end
end
end
sirOutput = stochasticSIR([0.0001, 0.05], [999,1,0], 200)
#plot(hcat(sirData.dataₛ, sirData.dataᵢ, sirData.dataᵣ), sirData.time)
Error:
InexactError: Int64(2.508057234147307)
Stacktrace: [1] Int64 at .\float.jl:709 [inlined] [2] convert at
.\number.jl:7 [inlined] [3] push! at .\array.jl:868 [inlined] [4]
stochasticSIR(::Array{Float64,1}, ::Array{Int64,1}, ::Int64) at
.\In[9]:33 [5] top-level scope at In[9]:51
Could someone please explain why I receive this error? It does not tell me what line (I am using Jupyter notebook) and I do not understand it.

Answer 1

First error
You have to qualify your references to time as sirData.time
The error message is a bit confusing because time is a function in Base as well, so it is automatically in scope.
Second error
You need your data to be represented as Float64, so you have to explictly type your input array:
sirOutput = stochasticSIR([0.0001, 0.05], Float64[999,1,0], 200)
Alternatively, you can create the array with float literals: [999.0,1,0]. If you create an array with only literal integers, Julia will create an integer array.

Answer 2

I'm not sure StackOverflow is the best venue for this, as you seem to editing the original post as you go along with new errors.
Your current error at the time of writing (InexactError: Int(2.50805)) tells you that you are trying to create an integer from a Float64 floating point number, which you can't do without rounding explicitly.
I would highly recommend reading the Julia docs to get the hang of basic usage, and maybe use the Julia Discourse forum for more interactive back-and-forth debugging with the community.