Format .jl files (#123)

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JuliaReinforcementLearning · Sep 2, 2020 · a3dc0c9 · a3dc0c9
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diff --git a/src/ReinforcementLearningCore/src/components/trajectories/trajectory.jl b/src/ReinforcementLearningCore/src/components/trajectories/trajectory.jl
@@ -185,29 +185,14 @@ isfull(t::CombinedTrajectory) = isfull(t.t1) && isfull(t.t2)
 #####
 
 const VectCompactSATrajectory = CombinedTrajectory{
-    <:SharedTrajectory{
-        <:Vector,
-        <:NamedTuple{(:state, :next_state, :full_state)},
-    },
-    <:SharedTrajectory{
-        <:Vector,
-        <:NamedTuple{(:action, :next_action, :full_action)},
-    }
+    <:SharedTrajectory{<:Vector,<:NamedTuple{(:state, :next_state, :full_state)}},
+    <:SharedTrajectory{<:Vector,<:NamedTuple{(:action, :next_action, :full_action)}},
 }
 
-function VectCompactSATrajectory(;
-    state_type = Int,
-    action_type = Int,
-    )
+function VectCompactSATrajectory(; state_type = Int, action_type = Int)
     CombinedTrajectory(
-        SharedTrajectory(
-            Vector{state_type}(),
-            :state,
-        ),
-        SharedTrajectory(
-            Vector{action_type}(),
-            :action,
-        ),
+        SharedTrajectory(Vector{state_type}(), :state),
+        SharedTrajectory(Vector{action_type}(), :action),
     )
 end
 
@@ -250,14 +235,8 @@ end
 #####
 
 const ElasticCompactSATrajectory = CombinedTrajectory{
-    <:SharedTrajectory{
-        <:ElasticArray,
-        <:NamedTuple{(:state, :next_state, :full_state)},
-    },
-    <:SharedTrajectory{
-        <:ElasticArray,
-        <:NamedTuple{(:action, :next_action, :full_action)},
-    },
+    <:SharedTrajectory{<:ElasticArray,<:NamedTuple{(:state, :next_state, :full_state)}},
+    <:SharedTrajectory{<:ElasticArray,<:NamedTuple{(:action, :next_action, :full_action)}},
 }
 
 function ElasticCompactSATrajectory(;
@@ -267,14 +246,8 @@ function ElasticCompactSATrajectory(;
     action_size = (),
 )
     CombinedTrajectory(
-        SharedTrajectory(
-            ElasticArray{state_type}(undef, state_size..., 0),
-            :state,
-        ),
-        SharedTrajectory(
-            ElasticArray{action_type}(undef, action_size..., 0),
-            :action,
-        ),
+        SharedTrajectory(ElasticArray{state_type}(undef, state_size..., 0), :state),
+        SharedTrajectory(ElasticArray{action_type}(undef, action_size..., 0), :action),
     )
 end
 
@@ -316,25 +289,13 @@ end
 #####
 
 const VectCompactSARTSATrajectory = CombinedTrajectory{
-    <:Trajectory{
-        <:NamedTuple{
-            (:reward, :terminal),
-            <:Tuple{<:Vector,<:Vector},
-        },
-    },
+    <:Trajectory{<:NamedTuple{(:reward, :terminal),<:Tuple{<:Vector,<:Vector}}},
     <:VectCompactSATrajectory,
 }
 
-function VectCompactSARTSATrajectory(;
-    reward_type = Float32,
-    terminal_type = Bool,
-    kw...,
-)
+function VectCompactSARTSATrajectory(; reward_type = Float32, terminal_type = Bool, kw...)
     CombinedTrajectory(
-        Trajectory(
-            reward = Vector{reward_type}(),
-            terminal = Vector{terminal_type}(),
-        ),
+        Trajectory(reward = Vector{reward_type}(), terminal = Vector{terminal_type}()),
         VectCompactSATrajectory(; kw...),
     )
 end
@@ -375,12 +336,7 @@ end
 #####
 
 const ElasticCompactSARTSATrajectory = CombinedTrajectory{
-    <:Trajectory{
-        <:NamedTuple{
-            (:reward, :terminal),
-            <:Tuple{<:ElasticArray,<:ElasticArray},
-        },
-    },
+    <:Trajectory{<:NamedTuple{(:reward, :terminal),<:Tuple{<:ElasticArray,<:ElasticArray}}},
     <:ElasticCompactSATrajectory,
 }
 

diff --git a/src/ReinforcementLearningCore/src/extensions/ElasticArrays.jl b/src/ReinforcementLearningCore/src/extensions/ElasticArrays.jl
@@ -6,6 +6,6 @@ Base.empty!(a::ElasticArray) = ElasticArrays.resize_lastdim!(A, 0)
 function Base.pop!(a::ElasticArray)
     # ??? Is it safe to do so?
     last_frame = selectdim(a, ndims(a), size(a, ndims(a)))
-    ElasticArrays.resize_lastdim!(A, size(a, ndims(a))-1)
+    ElasticArrays.resize_lastdim!(A, size(a, ndims(a)) - 1)
     last_frame
-end
+end
diff --git a/src/ReinforcementLearningCore/test/components/trajectories.jl b/src/ReinforcementLearningCore/test/components/trajectories.jl
@@ -157,24 +157,35 @@
     end
 
     @testset "VectCompactSARTSATrajectory" begin
-        t = VectCompactSARTSATrajectory(;state_type=Vector{Float32}, action_type=Int, reward_type=Float32, terminal_type=Bool)
-        push!(t; state=Float32[1,1], action=1)
-        push!(t; reward=1f0, terminal=false, state=Float32[2,2], action=2)
-        push!(t; reward=2f0, terminal=true, state=Float32[3,3], action=3)
-
-        @test t[:state] == [Float32[1,1], Float32[2,2]]
-        @test t[:action] == [1,2]
-        @test t[:reward] == [1f0,2f0]
-        @test t[:terminal] == [false,true]
-        @test t[:next_state] == [Float32[2,2], Float32[3,3]]
-        @test t[:next_action] == [2,3]
+        t = VectCompactSARTSATrajectory(;
+            state_type = Vector{Float32},
+            action_type = Int,
+            reward_type = Float32,
+            terminal_type = Bool,
+        )
+        push!(t; state = Float32[1, 1], action = 1)
+        push!(t; reward = 1f0, terminal = false, state = Float32[2, 2], action = 2)
+        push!(t; reward = 2f0, terminal = true, state = Float32[3, 3], action = 3)
+
+        @test t[:state] == [Float32[1, 1], Float32[2, 2]]
+        @test t[:action] == [1, 2]
+        @test t[:reward] == [1f0, 2f0]
+        @test t[:terminal] == [false, true]
+        @test t[:next_state] == [Float32[2, 2], Float32[3, 3]]
+        @test t[:next_action] == [2, 3]
     end
 
     @testset "ElasticCompactSARTSATrajectory" begin
-        t = ElasticCompactSARTSATrajectory(;state_type=Float32, state_size=(2,), action_type=Int, reward_type=Float32, terminal_type=Bool)
-        push!(t; state=Float32[1,1], action=1)
-        push!(t; reward=1f0, terminal=false, state=Float32[2,2], action=2)
-        push!(t; reward=2f0, terminal=true, state=Float32[3,3], action=3)
+        t = ElasticCompactSARTSATrajectory(;
+            state_type = Float32,
+            state_size = (2,),
+            action_type = Int,
+            reward_type = Float32,
+            terminal_type = Bool,
+        )
+        push!(t; state = Float32[1, 1], action = 1)
+        push!(t; reward = 1f0, terminal = false, state = Float32[2, 2], action = 2)
+        push!(t; reward = 2f0, terminal = true, state = Float32[3, 3], action = 3)
 
         @test t[:state] == Float32[1 2; 1 2]
         @test t[:action] == [1, 2]