using Random, LinearAlgebra
Random.seed!(13)

# Activation function: Step function
Step(X::Float64) = (X > 0 ? 1.0 : -1.0)
Step(X::Array{Float64,1}) = [Step(x) for x in X]

# Matrix rows sum
RowSum(A) = sum(A, dims=1)[1, :]

# Training function
function TrainPerceptron(Xin, Y, γ)
	print("da fare")
end


Xand = [0 0; 0 1; 1 0; 1 1]
Yand = [-1, -1, -1, 1]
println("START LEARNING AND")
TrainPerceptron(Xand, Yand, 0.01)

#Xor = [0 0; 0 1; 1 0; 1 1]
#Yor = [-1, 1, 1, 1]
#println("START LEARNING OR")
#TrainPerceptron(Xor, Yor, 0.01)


#Xxor = [0 0; 0 1; 1 0; 1 1]
#Yxor = [-1, 1, 1, -1]
#println("START LEARNING OR")
#TrainPerceptron(Xxor, Yxor, 0.01)

#L = [1 1 1; 1 0 1; 1 1 0; 1 0 0; 0 1 1; 0 0 1; 0 1 0; 0 0 0]
#Y = [1, 1, 1, 1, 0, 1, 0, 0]
#TrainPerceptron(L, Y, 0.01)
println("DONE")