first JET edits

ComputationalPsychiatry · May 4, 2024 · 9956a27 · 9956a27
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Showing 8 changed files with 49 additions and 53 deletions.
diff --git a/docs/Project.toml b/docs/Project.toml
@@ -9,6 +9,7 @@ Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 Glob = "c27321d9-0574-5035-807b-f59d2c89b15c"
 HierarchicalGaussianFiltering = "63d42c3e-681c-42be-892f-a47f35336a79"
+JET = "c3a54625-cd67-489e-a8e7-0a5a0ff4e31b"
 JuliaFormatter = "98e50ef6-434e-11e9-1051-2b60c6c9e899"
 Literate = "98b081ad-f1c9-55d3-8b20-4c87d4299306"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"

diff --git a/src/ActionModels_variations/utils/get_states.jl b/src/ActionModels_variations/utils/get_states.jl
@@ -36,7 +36,9 @@ function ActionModels.get_states(node::AbstractNode, state_name::String)
     #If the state does not exist in the node
     if !(Symbol(state_name) in fieldnames(typeof(node.states)))
         #throw an error
-        throw(ArgumentError("The node $node_name does not have the state $state_name"))
+        throw(
+            ArgumentError("The node $(node.node_name) does not have the state $state_name"),
+        )
     end
 
     #If a prediction state has been specified

diff --git a/src/create_hgf/hgf_structs.jl b/src/create_hgf/hgf_structs.jl
@@ -79,7 +79,7 @@ end
 """
 """
 Base.@kwdef mutable struct OrderedNodes
-    all_nodes::Vector{AbstractNode} = []
+    all_nodes::Vector{AbstractNode} = AbstractNode[]
     input_nodes::Vector{AbstractInputNode} = []
     all_state_nodes::Vector{AbstractStateNode} = []
     early_update_state_nodes::Vector{AbstractStateNode} = []

diff --git a/src/update_hgf/node_updates/continuous_state_node.jl b/src/update_hgf/node_updates/continuous_state_node.jl
@@ -48,7 +48,7 @@ function calculate_prediction_mean(node::ContinuousStateNode, stepsize::Real)
             coupling_transform;
             derivation_level = 0,
             child = node,
-            parent = parent
+            parent = parent,
         )
 
         #Add the drift increment
@@ -240,7 +240,7 @@ function calculate_posterior_precision_increment(
             derivation_level = 2,
             parent = node,
             child = child,
-        ) * 
+        ) *
         child.states.value_prediction_error
     )
 

diff --git a/src/update_hgf/nonlinear_transforms.jl b/src/update_hgf/nonlinear_transforms.jl
@@ -1,6 +1,6 @@
 #Transformation (of varioius derivations) for a linear transformation
 function transform_parent_value(
-    parent_value::Real, 
+    parent_value::Real,
     transform_type::LinearTransform;
     derivation_level::Integer,
     parent::AbstractNode,
@@ -31,10 +31,10 @@ function transform_parent_value(
         transform_function = child.parameters.coupling_transforms[parent.name].base_function
     elseif derivation_level == 1
         transform_function =
-        child.parameters.coupling_transforms[parent.name].first_derivation
+            child.parameters.coupling_transforms[parent.name].first_derivation
     elseif derivation_level == 2
         transform_function =
-        child.parameters.coupling_transforms[parent.name].second_derivation
+            child.parameters.coupling_transforms[parent.name].second_derivation
     else
         @error "derivation level is misspecified"
     end

diff --git a/test/testsuite/Aqua.jl b/test/testsuite/Aqua.jl
@@ -1,4 +1,3 @@
 using HierarchicalGaussianFiltering
 using Aqua
-Aqua.test_all(HierarchicalGaussianFiltering,
-ambiguities = false)
+Aqua.test_all(HierarchicalGaussianFiltering, ambiguities = false)
diff --git a/test/testsuite/test_custom_structures.jl b/test/testsuite/test_custom_structures.jl
@@ -5,35 +5,28 @@ using HierarchicalGaussianFiltering
 @testset "test custom structures" begin
 
     @testset "Many continuous nodes" begin
-    nodes = [
-        ContinuousInput(name = "u"),
-        ContinuousInput(name = "u2"),
-
-        ContinuousState(name = "x1"),
-        ContinuousState(name = "x2"),
-        ContinuousState(name = "x3"),
-        ContinuousState(name = "x4"),
-        ContinuousState(name = "x5"),
-
-    ]
-
-    edges = Dict(
-        ("u", "x1") => ObservationCoupling(),
-        ("u2", "x2") => ObservationCoupling(),
-
-        ("x1", "x2") => DriftCoupling(),
-        ("x1", "x3") => VolatilityCoupling(),
-        ("u2", "x3") => NoiseCoupling(),
-        ("x2", "x4") => VolatilityCoupling(),
-        ("x3", "x5") => DriftCoupling(),
-    )
-
-    hgf = init_hgf(
-        nodes = nodes,
-        edges = edges,
-        verbose = false,
-    )
-
-    update_hgf!(hgf, [1,1])
+        nodes = [
+            ContinuousInput(name = "u"),
+            ContinuousInput(name = "u2"),
+            ContinuousState(name = "x1"),
+            ContinuousState(name = "x2"),
+            ContinuousState(name = "x3"),
+            ContinuousState(name = "x4"),
+            ContinuousState(name = "x5"),
+        ]
+
+        edges = Dict(
+            ("u", "x1") => ObservationCoupling(),
+            ("u2", "x2") => ObservationCoupling(),
+            ("x1", "x2") => DriftCoupling(),
+            ("x1", "x3") => VolatilityCoupling(),
+            ("u2", "x3") => NoiseCoupling(),
+            ("x2", "x4") => VolatilityCoupling(),
+            ("x3", "x5") => DriftCoupling(),
+        )
+
+        hgf = init_hgf(nodes = nodes, edges = edges, verbose = false)
+
+        update_hgf!(hgf, [1, 1])
     end
-end
+end
diff --git a/test/testsuite/test_nonlinear_transforms.jl b/test/testsuite/test_nonlinear_transforms.jl
@@ -2,39 +2,40 @@ using Test
 using HierarchicalGaussianFiltering
 
 @testset "Testing nonlinear transforms" begin
-    
+
     @testset "Sinoid transform" begin
         nodes = [
             ContinuousInput(name = "u"),
             ContinuousState(name = "x1"),
             ContinuousState(name = "x2"),
         ]
 
-        base = function(x, parameters::Dict)
+        base = function (x, parameters::Dict)
             sin(x)
         end
-        first_derivative = function(x, parameters::Dict)
+        first_derivative = function (x, parameters::Dict)
             cos(x)
         end
-        second_derivative = function(x, parameters::Dict)
+        second_derivative = function (x, parameters::Dict)
             -sin(x)
         end
         transform_parameters = Dict()
 
         edges = Dict(
             ("u", "x1") => ObservationCoupling(),
-            ("x1", "x2") => DriftCoupling(2,NonlinearTransform(base, first_derivative, second_derivative, transform_parameters)),
+            ("x1", "x2") => DriftCoupling(
+                2,
+                NonlinearTransform(
+                    base,
+                    first_derivative,
+                    second_derivative,
+                    transform_parameters,
+                ),
+            ),
         )
 
-        hgf = init_hgf(
-            nodes = nodes,
-            edges = edges,
-            verbose = false,
-        )
+        hgf = init_hgf(nodes = nodes, edges = edges, verbose = false)
 
         update_hgf!(hgf, 1)
     end
 end
-
-
-