[UPD] update testing

Author: frapac

test/sddp.jl

@@ -71,7 +71,7 @@ facts("SDDP algorithm: 1D case") do
 
         # Test if the first subgradient has the same dimension as state:
         @fact size(V[1].lambdas, 2) --> model.dimStates
-        @fact V[1].numCuts < n_scenarios*max_iterations + n_scenarios --> true
+        @fact V[1].numCuts <= n_scenarios*max_iterations + n_scenarios --> true
         @fact size(V[1].lambdas, 1) --> V[1].numCuts
 
         # Test upper bounds estimation with Monte-Carlo:
@@ -109,10 +109,62 @@ facts("SDDP algorithm: 1D case") do
     context("Cuts pruning") do
         v = V[1]
         vt = PolyhedralFunction([v.betas[1]; v.betas[1] - 1.], v.lambdas[[1,1],:],  2)
-        isactive1 = StochDynamicProgramming.is_cut_relevant(model, 1, vt, param.SOLVER)
-        isactive2 = StochDynamicProgramming.is_cut_relevant(model, 2, vt, param.SOLVER)
+        # Check cuts counting:
+        @fact StochDynamicProgramming.get_total_number_cuts([vt]) --> 2
+
+        # Check computation of cut value:
+        @fact StochDynamicProgramming.cutvalue(vt, 1, [0., 0.]) --> v.betas[1]
+
+        # Check computation of optimal cut:
+        @fact StochDynamicProgramming.optimalcut([0., 0.], vt)[2] --> 1
+
+        terr = StochDynamicProgramming.Territories(2)
+        StochDynamicProgramming.find_territory!(terr, vt, [0. 0.; 1. 0.])
+        @fact terr.ncuts --> 2
+        @fact terr.nstates --> 2
+        @fact length(terr.territories[1]) --> 2
+        @fact length(terr.territories[2]) --> 0
+
+        # Check heuristic removal:
+        vt2 = StochDynamicProgramming.remove_empty_cuts!(terr, vt)
+        @fact isa(vt2, StochDynamicProgramming.PolyhedralFunction) --> true
+        @fact vt2.numCuts --> 1
+        @fact vt2.betas[1] --> vt.betas[1]
+
+        # Check exact dominance test:
+        isactive1 = StochDynamicProgramming.is_cut_relevant(model, 1, vt, param.SOLVER)[1]
+        isactive2 = StochDynamicProgramming.is_cut_relevant(model, 2, vt, param.SOLVER)[1]
         @fact isactive1 --> true
         @fact isactive2 --> false
+
+        # Check insertion of pruning algorithms into SDDP solver:
+        param1 = StochDynamicProgramming.SDDPparameters(solver,
+                                                    passnumber=n_scenarios,
+                                                    gap=epsilon,
+                                                    pruning_algo="exact",
+                                                    prune_cuts=1,
+                                                    max_iterations=1)
+        V1 = solve_SDDP(model, param1, 0)[1]
+        param1 = StochDynamicProgramming.SDDPparameters(solver,
+                                                    passnumber=n_scenarios,
+                                                    gap=epsilon,
+                                                    pruning_algo="territory",
+                                                    prune_cuts=1,
+                                                    max_iterations=1)
+        V2 = solve_SDDP(model, param1, 0)[1]
+        param1 = StochDynamicProgramming.SDDPparameters(solver,
+                                                    passnumber=n_scenarios,
+                                                    gap=epsilon,
+                                                    pruning_algo="mixed",
+                                                    prune_cuts=1,
+                                                    max_iterations=1)
+        V3 = solve_SDDP(model, param1, 0)[1]
+
+        n1 = StochDynamicProgramming.get_total_number_cuts(V1)
+        n2 = StochDynamicProgramming.get_total_number_cuts(V2)
+        n3 = StochDynamicProgramming.get_total_number_cuts(V3)
+        @fact n1 > n2 --> true
+        @fact n3 > n2 --> true
     end
 
     context("Quadratic regularization") do