Move Monte Carlo out

SciML · Jan 11, 2017 · 265fb11 · 265fb11
1 parent bba75af
commit 265fb11
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diff --git a/src/StochasticDiffEq.jl b/src/StochasticDiffEq.jl
@@ -6,11 +6,7 @@ module StochasticDiffEq
         DataStructures, ResettableStacks
   import DiffEqBase: solve
 
-
-  abstract AbstractMonteCarloSimulation
-
   include("algorithms.jl")
-  include("stochastic_utils.jl")
   include("solve.jl")
   include("initdt.jl")
   include("integrators/integrator_utils.jl")
@@ -22,9 +18,6 @@ module StochasticDiffEq
    export StochasticDiffEqAlgorithm, EM, RKMil, SRA, SRI, SRIW1,
           SRA1
 
-   #Stochastic Utils
-   export monte_carlo_simulation
-
    #General Functions
    export solve
 

diff --git a/src/stochastic_utils.jl b/src/stochastic_utils.jl
diff --git a/test/sde/sde_additive_tests.jl b/test/sde/sde_additive_tests.jl
@@ -12,8 +12,6 @@ println("Solve and Plot")
 sol =solve(prob,SRA(),dt=1/2^(3))
 sol =solve(prob,SRA1(),dt=1/2^(3))
 
-#Now do the simulation 10000 times in parallel. Return an array
-solArr = monte_carlo_simulation(prob,SRA1(),dt=1//2^(3),numMonte=5)
 
 #First index is the sime, so sol.timeseries[1,..] is the initial condition
 #Last indices are the indexes of the variables. Since our initial condition

diff --git a/test/sde/sde_twodimlinear_tests.jl b/test/sde/sde_twodimlinear_tests.jl
@@ -14,10 +14,6 @@ sol = solve(prob,SRIW1(),dt=1/2^(3),save_timeseries=false)
 
 sol = solve(prob,SRIW1(),dt=1/2^(3),progress=true,progress_steps=1)
 
-
-#Now do the simulation 5 times in parallel. Return an array
-solArr = monte_carlo_simulation(prob,SRIW1(),dt=1//2^(3),numMonte=5)
-
 #TEST_PLOT && plot(sol,plot_analytic=true)
 
 ## Convergence Testing