Created
April 16, 2020 14:35
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Curve Fitting using ANN for sin(x)
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using Flux, Plots | |
using Base.Iterators: repeated | |
using Flux: @epochs | |
using LinearAlgebra | |
gridsize = 150; | |
tstart=0.0 | |
tend=20.0 | |
myfunc(x) = sin(x); | |
x = collect(range(tstart,stop=tend,length=gridsize)); | |
y= myfunc.(x); | |
xtest=collect(tend:0.1:2*tend) | |
xpred=collect(tstart:0.1:2*tend) | |
#Build the input data | |
data = [] | |
for i in 1:length(x) | |
push!(data, ([x[i]], y[i])) #have to input a list | |
end | |
Q = 20; | |
ann = Chain(Dense(1,Q,tanh),Dense(Q,Q,tanh),Dense(Q,1)); | |
#Simple Mean-square loss2 | |
function loss(x, y) | |
pred=ann(x) | |
loss=Flux.mse(ann(x), y) | |
return loss | |
end | |
opt = ADAM() | |
ps=params(ann) | |
@epochs 3000 Flux.train!(loss,ps, data, opt) | |
plot(xpred, ann(xpred')', color=:red, lw=2.0, label="") | |
scatter!(x,myfunc.(x), color=:blue, legend=false) | |
scatter!(xtest,myfunc.(xtest), color=:green, lw=2.0, label="", markershape=:cross) | |
ylims!((-1.5,1.5)) | |
xlims!((tstart,2*tend)) | |
title!("Curve Fitting with Neural Networks") | |
xlabel!("Input") | |
ylabel!("Output") |
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