From fc676d1ccdaa3c9ffa69cebb31c5eeff76a9dc25 Mon Sep 17 00:00:00 2001
From: ton <narawat@gmail.com>
Date: Tue, 11 Jul 2023 09:26:14 +0700
Subject: [PATCH] building forward()

---
 src/type.jl | 55 +++++++++++++++++++++++++++++++++--------------------
 1 file changed, 34 insertions(+), 21 deletions(-)

diff --git a/src/type.jl b/src/type.jl
index 361be3d..af5feb7 100644
--- a/src/type.jl
+++ b/src/type.jl
@@ -26,8 +26,10 @@ Base.@kwdef mutable struct kfn_1 <: knowledgeFn
     z_i_t0::Union{AbstractArray, Nothing} = nothing
 
     lif_w::Union{AbstractArray, Nothing} = nothing
+    lif_recSignal::Union{AbstractArray, Nothing} = nothing
 
     alif_w::Union{AbstractArray, Nothing} = nothing
+    alif_recSignal::Union{AbstractArray, Nothing} = nothing
 end
 
 # outer constructor
@@ -35,35 +37,42 @@ function kfn_1(params::Dict)
     kfn = kfn_1()
     kfn.params = params
     # initialize activation matrix
-    row, col = kfn.params[:inputPort][:noise][:numbers]
-    row += kfn.params[:inputPort][:signal][:numbers][1]
+    row, col, batch = kfn.params[:inputPort][:signal][:numbers] # z-axis represent signal batch number
+    row += kfn.params[:inputPort][:noise][:numbers][1]
     col += kfn.params[:inputPort][:signal][:numbers][2]
     col += kfn.params[:computeNeuron][:lif][:numbers][2]
     col += kfn.params[:computeNeuron][:alif][:numbers][2]
 
-    kfn.z_i_t1 = zeros(row, col, 1) 
-    kfn.z_i_t0 = zeros(row, col, 1)
+    kfn.z_i_t1 = zeros(row, col, batch) 
+    kfn.z_i_t0 = zeros(row, col, batch)
     
-    kfn.lif_w = zeros(row, col, row*col)    
-    kfn.alif_w = zeros(row, col, row*col)
+    # LIF
+    z = kfn.params[:computeNeuron][:lif][:numbers][1] * kfn.params[:computeNeuron][:lif][:numbers][2]
+    kfn.lif_w = zeros(row, col, z)    # matrix z-axis represent each neurons
+    kfn.lif_recSignal = zeros(row, col, z, batch)
+
+    # ALIF
+    z = kfn.params[:computeNeuron][:alif][:numbers][1] * kfn.params[:computeNeuron][:alif][:numbers][2]
+    kfn.alif_w = zeros(row, col, z)
+    kfn.alif_recSignal = zeros(row, col, z, batch)
 
     # lif subscription
-    row, col, z = size(kfn.lif_w)   # row*col is synaptic subscribe weight for each neuron in z
+    row, col, _ = size(kfn.lif_w)   # row*col is synaptic subscribe weight for each neuron in z-axis
     synapticConnectionPercent = kfn.params[:computeNeuron][:lif][:params][:synapticConnectionPercent]
-    synapticConnection = Int(floor(z*synapticConnectionPercent/100))
+    synapticConnection = Int(floor(row*col * synapticConnectionPercent/100))
     for slice in eachslice(kfn.lif_w, dims=3)
-        pool = shuffle!([1:z...])[1:synapticConnection]
+        pool = shuffle!([1:row*col...])[1:synapticConnection]
         for i in pool
             slice[i] = randn()/10
         end
     end
 
     # alif subscription
-    row, col, z = size(kfn.alif_w)   # row*col is synaptic subscribe weight for each neuron in z
+    row, col, _ = size(kfn.alif_w)   # row*col is synaptic subscribe weight for each neuron in z-axis
     synapticConnectionPercent = kfn.params[:computeNeuron][:alif][:params][:synapticConnectionPercent]
-    synapticConnection = Int(floor(z*synapticConnectionPercent/100))
+    synapticConnection = Int(floor(row*col * synapticConnectionPercent/100))
     for slice in eachslice(kfn.alif_w, dims=3)
-        pool = shuffle!([1:z...])[1:synapticConnection]
+        pool = shuffle!([1:row*col...])[1:synapticConnection]
         for i in pool
             slice[i] = randn()/10
         end
@@ -87,19 +96,23 @@ end
 function (kfn::kfn_1)(input::AbstractArray)
     kfn.timeStep .+= 1
 
+    # time step forward
+
+
+
     # row, col = size(input)  # if input is a 2D matrix
-    println(">>> 5 ", size(input))
-    println(">>> 6 ", size(kfn.z_i_t1)) 
+    println(">>> 1 ", size(input))
+    println(">>> 2 ", size(kfn.z_i_t1)) 
 
-    #WORKING multiply input with kfn.z_i_t1 may be using cartesian coordinates
-    println(">>> 7 ", view(kfn.z_i_t1, :, 1, :))    
-    view(kfn.z_i_t1, :, 1) .= input
-    println(">>> 8 ", kfn.z_i_t1[:, 1])
+    # multiply input with kfn.z_i_t1 may be using cartesian coordinates
+    GeneralUtils.cartesianAssign!(kfn.z_i_t1, input)
+    println(">>> 3 ", sum(kfn.z_i_t1))
+    println(">>> 4 ", size(kfn.lif_recSignal))
+    println(">>> 5 ", size(kfn.lif_w))
+    kfn.lif_recSignal .= GeneralUtils.batchMatEleMul(kfn.z_i_t1, kfn.lif_w) 
+    kfn.alif_recSignal .= GeneralUtils.batchMatEleMul(kfn.z_i_t1, kfn.alif_w)
 
-    # multiply kfn.z_i_t1 with kfn.lif_w
-    r = GeneralUtils.batchMatEleMul(kfn.z_i_t1, kfn.lif_w) 
 
-    println(size(r))