using PyPlot
using NtToolBox
# using Autoreload
# arequire("NtToolBox")

n = 512
f = rescale(load_image("NtToolBox/nt_toolbox/data/lena.png", n));

figure(figsize = (5,5))
imageplot(f)

fF = (plan_fft(f)*f)/n;

figure(figsize = (5,5))
imageplot(log(1e-5 + abs(fftshift(fF))))

T = .3
c = fF.*(abs(fF) .> T);

fM = real((plan_ifft(c)*c)*n);

figure(figsize = (5,5))
imageplot(clamP(fM))

include("NtSolutions/coding_1_approximation/exo1.jl")

## Insert your code here.

include("NtSolutions/coding_1_approximation/exo2.jl")

## Insert your code here.

include("NtSolutions/coding_1_approximation/exo3.jl")

## Insert your code here.

Jmin = 1

h = compute_wavelet_filter("Daubechies",10)

fW = perform_wavortho_transf(f, Jmin, + 1, h);

figure(figsize = (8,8))

plot_wavelet(fW, Jmin)
title("Wavelet coefficients")

show()

include("NtSolutions/coding_1_approximation/exo4.jl")

include("NtSolutions/coding_1_approximation/exo5.jl")

## Insert your code here.

fC = plan_dct(f)*f;

figure(figsize = (5,5))
imageplot(log(1e-5 + abs(fC)))

include("NtSolutions/coding_1_approximation/exo6.jl")

include("NtSolutions/coding_1_approximation/exo7.jl")

## Insert your code here.

w = 16

fL = zeros(n, n);

i = 5
j = 7;

P = f[(i - 1)*w + 1 : i*w, (j - 1)*w + 1 : j*w];

fL[(i - 1)*w + 1 : i*w, (j - 1)*w + 1 : j*w] = plan_dct(P)*P;

figure(figsize = (8,8))
imageplot(P, "Patch", [1, 2, 1])
imageplot(plan_dct(P .- mean(P))*(P .- mean(P)), "DCT", [1, 2, 2])

include("NtSolutions/coding_1_approximation/exo8.jl")

## Insert your code here.

figure(figsize = (5,5))
imageplot(Base.clamp(abs(fL), 0, .005*w*w))

include("NtSolutions/coding_1_approximation/exo9.jl")

## Insert your code here.

include("NtSolutions/coding_1_approximation/exo10.jl")

include("NtSolutions/coding_1_approximation/exo11.jl")

## Insert your code here.

n = 512
fList = zeros(n, n, 4)
fList[: , : , 1] = rescale(load_image("NtToolBox/src/data/regular3.png", n))
fList[: , : , 2] = rescale(load_image("NtToolBox/src/data/phantom.png", n))
fList[: , : , 3] = rescale(load_image("NtToolBox/src/data/lena.png", n))
fList[: , : , 4] = rescale(load_image("NtToolBox/src/data/mandrill.png", n));


figure(figsize = (7,7))

for i in 1:4
    imageplot(fList[: , : , i], "", [2, 2, i])
end

include("NtSolutions/coding_1_approximation/exo12.jl")

## Insert your code here.
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