using StochasticDiffEq, DiffEqNoiseProcess

f(du,u,p,t) = (du .= u)
g(du,u,p,t) = (du .= u)
u0 = rand(4,2)

W = WienerProcess(0.0,0.0,0.0)
prob = SDEProblem(f,g,u0,(0.0,1.0),noise=W)
sol = solve(prob,SRIW1())
sol = solve(prob,SRIW1())

W = WienerProcess(0.0,0.0,0.0)
prob = SDEProblem(f,g,u0,(0.0,1.0),noise=W)
sol = solve(prob,SRI())
sol = solve(prob,SRI())

W = WienerProcess(0.0,0.0,0.0,reset=false)
prob = SDEProblem(f,g,u0,(0.0,1.0),noise=W)
sol = solve(prob,SRI())
@test_throws ErrorException sol = solve(prob,SRI())

g(du,u,p,t) = (du .= 1)

W = WienerProcess(0.0,0.0,0.0)
prob = SDEProblem(f,g,u0,(0.0,1.0),noise=W)
sol = solve(prob,SRA1())

W = WienerProcess(0.0,0.0,0.0)
prob = SDEProblem(f,g,u0,(0.0,1.0),noise=W)
sol = solve(prob,SRA2())

W = WienerProcess(0.0,0.0,0.0)
prob = SDEProblem(f,g,u0,(0.0,1.0),noise=W)
sol = solve(prob,SRA3())

W = WienerProcess(0.0,0.0,0.0)
prob = SDEProblem(f,g,u0,(0.0,1.0),noise=W)
sol = solve(prob,SOSRA())

W = WienerProcess(0.0,0.0,0.0)
prob = SDEProblem(f,g,u0,(0.0,1.0),noise=W)
sol = solve(prob,SOSRA2())

W = WienerProcess(0.0,0.0,0.0)
prob = SDEProblem(f,g,u0,(0.0,1.0),noise=W)
sol = solve(prob,SRA())
