Merge branch 'Gersi_Gridworld' of github.com:RiskAverseRL/MDPs.jl int…

…o Gersi_Gridworld

src/domains/gridworld.jl

@@ -4,7 +4,6 @@ import ...TabMDP, ...transition, ...state_count, ...action_count
 import ...actions, ...states
 
 # TODO: Add docs
-# TODO: Add tests
 """
 Models values of demand in `values` and probabilities in `probabilities`.
 """
@@ -27,6 +26,15 @@ struct Parameters
     rewards_s::Vector{Float64}
     max_side_length::Int
     wind::Float64
+
+    function Parameters(rewards_s, max_side_length, wind)
+        length(rewards_s) == max_side_length * max_side_length ||
+            error("Rewards must have the same length as the number of states.")
+        wind ≥ 0.0 || error("Wind must be non-negative.")
+        wind ≤ 1.0 || error("Wind must be less than or equal to 1.")
+
+        new(rewards_s, max_side_length, wind)
+    end
 end
 
 
@@ -50,7 +58,7 @@ function transition(model::Model, state::Int, action::Int)
     remaining_wind = model.params.wind / 3
     ret = []
     # Wrap the state around the grid 1-based indexing
-    # Julia for the love of God please implement a proper modulo function
+    # NOTE: Julia for the love of God please implement a proper modulo function
     upstate = state - n <= 0 ? state + n_states - n : state - n
     downstate = (state + n) > n_states ? state - n_states + n : state + n
     leftstate = state % n == 1 ? state + (n - 1) : state - 1

test/src/domains/gridworld.jl

@@ -1,30 +1,11 @@
 using MDPs.Domains
 
 @testset "Solve Gridworld" begin
-    reward = [0.1, 0.1, 0.2, -10, -15, 100, 1, 0.5]
+    reward = [0.1, 0.1, 0.2, -10, -15, 100, 1, 0.5, 0.1]
     max_side_length = 3
     wind = 0.2
     params = GridWorld.Parameters(reward, max_side_length, wind)
 
-    # Initialize flags for tests
-    stateok = true
-    actionok = true
-    transitionok = true
-
-    for s in 1:GridWorld.state_count(params)
-        state = GridWorld.state2state(params, s)  # Assuming state2state function exists
-        stateok &= (GridWorld.state2state(params, state) == s)
-        for a in 1:GridWorld.action_count(params, s)
-            action = GridWorld.action2action(params, a)  # Assuming action2action function exists
-            actionok &= (GridWorld.action2action(params, action) == a)
-            transitionok &= (GridWorld.transition(params, state, action, 0).state == state + action)  # Adjust transition logic as per the actual implementation
-        end
-    end
-
-    @test stateok
-    @test actionok
-    @test transitionok
-
     model = GridWorld.Model(params)
     simulate(model, random_π(model), 1, 10000, 500)
     model_g = make_int_mdp(model; docompress=false)