From a114935b2dbbed67bec3f89970c0f0d85a8722ee Mon Sep 17 00:00:00 2001
From: tonaerospace <tonaerospace.etc@gmail.com>
Date: Wed, 17 May 2023 15:55:25 +0700
Subject: [PATCH] bug fix

---
 src/forward.jl | 7 ++++---
 src/learn.jl   | 9 ++++-----
 src/types.jl   | 2 --
 3 files changed, 8 insertions(+), 10 deletions(-)

diff --git a/src/forward.jl b/src/forward.jl
index 8e62121..ea55d44 100644
--- a/src/forward.jl
+++ b/src/forward.jl
@@ -52,6 +52,7 @@ function (kfn::kfn_1)(m::model, input_data::AbstractVector)
         kfn.firedNeurons_t1 = Vector{Bool}()
 
         kfn.learningStage = "learning"
+        m.learningStage = kfn.learningStage
     end
 
     # generate noise
@@ -131,7 +132,7 @@ function (n::lifNeuron)(kfn::knowledgeFn)
     
         n.alpha_v_t = n.alpha * n.v_t
         n.v_t1 = n.alpha_v_t + n.recSignal
-        n.v_t1 = no_negative!.(n.v_t1)
+        n.v_t1 = no_negative!(n.v_t1)
 
         if n.v_t1 > n.v_th
             n.z_t1 = true
@@ -176,7 +177,7 @@ function (n::alifNeuron)(kfn::knowledgeFn)
         n.recSignal = sum(n.wRec .* n.z_i_t .* n.subExInType)  # signal from other neuron that this neuron subscribed
         n.alpha_v_t = n.alpha * n.v_t
         n.v_t1 = n.alpha_v_t + n.recSignal
-        n.v_t1 = no_negative!.(n.v_t1)
+        n.v_t1 = no_negative!(n.v_t1)
         if n.v_t1 > n.av_th
             n.z_t1 = true
             n.refractoryCounter = n.refractoryDuration
@@ -221,7 +222,7 @@ function (n::linearNeuron)(kfn::T) where T<:knowledgeFn
     
         n.alpha_v_t = n.alpha * n.v_t
         n.v_t1 = n.alpha_v_t + n.recSignal
-        n.v_t1 = no_negative!.(n.v_t1)
+        n.v_t1 = no_negative!(n.v_t1)
 
         if n.v_t1 > n.v_th
             n.z_t1 = true
diff --git a/src/learn.jl b/src/learn.jl
index ef0bea8..db303fc 100644
--- a/src/learn.jl
+++ b/src/learn.jl
@@ -11,7 +11,6 @@ export learn!
 #------------------------------------------------------------------------------------------------100
 
 function learn!(m::model, modelRespond, correctAnswer=nothing)
-    m.knowledgeFn[:I].learningStage = m.learningStage
     if correctAnswer === nothing
         correctAnswer_I = zeros(length(modelRespond))
     else
@@ -84,7 +83,7 @@ end
 
 """ passthroughNeuron learn()
 """
-function learn!(n::passthroughNeuron, kfn::knowledgeFn)
+function learn!(n::passthroughNeuron, error::Number)
     # skip
 end
 
@@ -94,7 +93,7 @@ function learn!(n::lifNeuron, error::Number)
     n.eRec = n.phi * n.epsilonRec
  
     ΔwRecChange = n.eta * error * n.eRec
-    n.wRecChange = (n.subExInType * n.wRecChange) + ΔwRecChange
+    n.wRecChange .+= ΔwRecChange
     reset_epsilonRec!(n)
 end
 
@@ -106,7 +105,7 @@ function learn!(n::alifNeuron, error::Number)
     n.eRec = n.eRec_v + n.eRec_a
 
     ΔwRecChange = n.eta * error * n.eRec
-    n.wRecChange = (n.subExInType * n.wRecChange) + ΔwRecChange
+    n.wRecChange .+= ΔwRecChange
     reset_epsilonRec!(n)
     reset_epsilonRecA!(n)
 end
@@ -117,7 +116,7 @@ function learn!(n::linearNeuron, error::Number)
     n.eRec = n.phi * n.epsilonRec
  
     ΔwRecChange = n.eta * error * n.eRec
-    n.wRecChange = (n.subExInType * n.wRecChange) + ΔwRecChange
+    n.wRecChange .+= ΔwRecChange
     reset_epsilonRec!(n)
 end
 
diff --git a/src/types.jl b/src/types.jl
index eb3ecef..62d6d70 100644
--- a/src/types.jl
+++ b/src/types.jl
@@ -304,7 +304,6 @@ Base.@kwdef mutable struct lifNeuron <: computeNeuron
     id::Union{Int64,Nothing} = nothing   # this neuron ID i.e. position of this neuron in knowledgeFn
     type::String = "lifNeuron"
     ExInType::Integer = 1   # 1 excitatory, -1 inhabitory
-    # Bn::Union{Float64,Nothing} = Random.rand()  # Bias for neuron error
     knowledgeFnName::Union{String,Nothing} = nothing  # knowledgeFn that this neuron belongs to
     subscriptionList::Union{Array{Int64},Nothing} = nothing # list of other neuron that this neuron synapse subscribed to
     subExInType::Array{Int64} = Vector{Int64}()        # store ExIn type of subscribed neurons
@@ -396,7 +395,6 @@ Base.@kwdef mutable struct alifNeuron <: computeNeuron
     id::Union{Int64,Nothing} = nothing               # this neuron ID i.e. position of this neuron in knowledgeFn
     type::String = "alifNeuron"
     ExInType::Integer = -1  # 1 excitatory, -1 inhabitory
-    # Bn::Union{Float64,Nothing} = Random.rand()  # Bias for neuron error
     knowledgeFnName::Union{String,Nothing} = nothing  # knowledgeFn that this neuron belongs to
     subscriptionList::Union{Array{Int64},Nothing} = nothing # list of other neuron that this neuron synapse subscribed to
     subExInType::Array{Int64} = Vector{Int64}()        # store ExIn type of subscribed neurons