Pkg.add("GR")

Pkg.update("GR")

using NeuralNetDiffEq
using Base.Test
#using Plots; plotly()
using GR; gr()
using DiffEqBase, ParameterizedFunctions
using DiffEqProblemLibrary, DiffEqDevTools
using Knet

function SODE_2(t,u)
    du1 = -u[1]/5 + exp(-t/5)*cos(t)
    du2 = -u[2]
    [du1,du2]
end

prob1 = ODEProblem(SODE_2,Float32[0.0,1.0],(Float32(0.0),Float32(2.0)))

sol1 = solve(prob1,nnode(10),dt=0.2,iterations=1000)

plot(sol1)

function SODE_3(t,u)
    du1 = -u[1]/5 + exp(-t/5)*cos(t)
    du2 = -u[2]/5 + exp(-t/5)*cos(t)
    [du1,du2]
end

prob2 = ODEProblem(SODE_3,Float32[0.0,0.0],(Float32(0.0),Float32(2.0)))

sol2 = solve(prob2,nnode(10),dt=0.2,iterations=1000)

plot(sol2)

function SODE_4(t,u)
    du1 = cos(t) + u[1]^2 + u[2] - (1+ t^2 + (sin(t))^2)
    du2 = 2t - (1+t^2)*sin(t) + u[1]*u[2]
    [du1,du2]
end

prob4 = ODEProblem(SODE_4,Float32[0.0,1.0],(Float32(0.0),Float32(3.0)))

sol4 = solve(prob4,nnode(10),dt=0.3,iterations=1000)

plot(sol4)