Added util function to generate Poisson Spike Train based on value ve…

…ctor

src/WaspNet.jl

@@ -8,10 +8,11 @@ using Parameters
 using Random
 
 include("types.jl")
+
 include("defs.jl")
-include("neurons.jl")
 include("layer.jl")
 include("network.jl")
+include("neurons.jl")
 include("simulate.jl")
 include("utils.jl")
 
@@ -22,4 +23,6 @@ export update
 
 export batch_layer_construction, network_constructor, layer_constructor, feed_forward_network
 
+export poissonST
+
 end # module

src/utilities/poisson.jl

@@ -0,0 +1,14 @@
+"""
+    poissonST(l::AbstractVector)
+
+Generates Poisson Spike Trains based on the normalized vector. Each
+pseudo-neuron (probability p in vector), fires with probability p at each
+timestep of simulation.
+
+# Inputs
+- `l`: array of values
+"""
+
+function poissonST(l::AbstractVector)
+    return poissonST(t) = [Float64(rand(Bernoulli(p), 1)[1]) for p in normalize(l)]
+end

src/utils.jl

@@ -1,6 +1,8 @@
-# Various useful utility functions 
+# Various useful utility functions
 
 include("utilities/utils.jl")
 
 # A pruning framework to remove neurons from Networks and Layers
-include("utilities/pruning.jl") 
+include("utilities/pruning.jl")
+
+include("utilities/poisson.jl")

test/utility_tests.jl

@@ -21,4 +21,10 @@ using WaspNet
 
     include("pruning_tests.jl")
 
+    @test begin
+        inputs = [1,1]
+        p = poissonST(inputs)
+        spikes = p(1)
+        spikes == [0,0] || spikes == [0,1] || spikes == [1,0] || spikes == [1,1]
+    end
 end