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RunParallelSlurm2.jl
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RunParallelSlurm2.jl
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include("SlurmConnect.jl")
using ProgressMeter
using PmapProgressMeter
using Parameters
using DataArrays,DataFrames
using QuadGK
using Distributions
using StatsBase
using ParallelDataTransfer
using Match
using Lumberjack
using FileIO
using SlurmConnect
add_truck(LumberjackTruck("processrun.log"), "my-file-logger")
remove_truck("console")
info("lumberjack process started up, starting repl")
info("adding procs...")
s = SlurmManager(480)
@eval Base.Distributed import Base.warn_once
addprocs(s, partition="defq", N=15)
println("added $(nworkers()) processors")
info("starting @everywhere include process...")
@everywhere include("basicModelSlurm.jl")
################## To run this files, You must check the return of BasicModel.jl
#######################3
function dataprocess(results,P::InfluenzaParameters,numberofsims)
resultsL = Matrix{Int64}(P.sim_time,numberofsims)
resultsA = Matrix{Int64}(P.sim_time,numberofsims)
resultsS = Matrix{Int64}(P.sim_time,numberofsims)
resultsGD = Matrix{Float64}(P.sim_time,numberofsims)
resultsR0 = Vector{Int64}(numberofsims)
resultsP = Matrix{Float64}(P.matrix_strain_lines,numberofsims)
resultsEf = Matrix{Float64}(P.matrix_strain_lines,numberofsims)
for i=1:numberofsims
resultsL[:,i] = results[i][1]
resultsS[:,i] = results[i][2]
resultsA[:,i] = results[i][3]
resultsR0[i] = results[i][4]
resultsP[:,i] = results[i][5]
resultsGD[:,i] = results[i][6]
resultsEf[:,i] = results[i][7]
end
directory = "July27/results/"
writedlm(string("$directory","result","$(P.Prob_transmission)","Mut","$(P.mutation_rate)","Ef","$(P.VaccineEfficacy)","_latent.dat"),resultsL)
writedlm(string("$directory","result","$(P.Prob_transmission)","Mut","$(P.mutation_rate)","Ef","$(P.VaccineEfficacy)","_symp.dat"),resultsS)
writedlm(string("$directory","result","$(P.Prob_transmission)","Mut","$(P.mutation_rate)","Ef","$(P.VaccineEfficacy)","_asymp.dat"),resultsA)
writedlm(string("$directory","result","$(P.Prob_transmission)","Mut","$(P.mutation_rate)","Ef","$(P.VaccineEfficacy)","_R0.dat"),resultsR0)
writedlm(string("$directory","result","$(P.Prob_transmission)","Mut","$(P.mutation_rate)","Ef","$(P.VaccineEfficacy)","_P.dat"),resultsP)
writedlm(string("$directory","result","$(P.Prob_transmission)","Mut","$(P.mutation_rate)","Ef","$(P.VaccineEfficacy)","_GD.dat"),resultsGD)
writedlm(string("$directory","result","$(P.Prob_transmission)","Mut","$(P.mutation_rate)","Ef","$(P.VaccineEfficacy)","_Ef.dat"),resultsEf)
end
function run_main(P::InfluenzaParameters,numberofsims::Int64)
results = pmap((cb, x) -> main(cb, x, P), Progress(numberofsims*P.sim_time), 1:numberofsims, passcallback=true)
dataprocess(results,P,numberofsims)
end
for Vef = 0.2:0.1:0.8
@everywhere P=InfluenzaParameters(
VaccineEfficacy = $Vef,
GeneralCoverage = 1,
Prob_transmission = 0.079,
sim_time = 200,
grid_size_human = 1000,
mutation_rate = 0.3,
matrix_strain_lines = 1100
)
run_main(P,1000)
end