a = [1; 2; 3]

println(a)

a = [1, 2, 3]

a = [1 2 3]

b = [4 5 6]

A = [1 2 3; 4 5 6]

A[1,3]

A[1]

A[1,1]

A[1,2]

A[2,1]

transpose(A)

A'

a = [1; 2; 3;]
c = [7; 8; 9;]

a'*c

using LinearAlgebra

dot(a, c)

Matrix(1.0I, 2, 2)
# I는 identity matrix => 단위 행렬. I가 없으면 에러남

Matrix(1.0, 2, 2)

zeros(4,1)

zeros(2,3)

ones(1,3)

ones(2,3)

B = [1 3 2; 3 2 2; 1 1 1]

inv(B)

B * inv(B)

inv(B)[2,1]

a = [1; 2; 3]

b = [1.0; 2; 3]

d = Array{Float64}(undef, 3)

d[1] = 1

d[2] = 2

d[3] = 3

d

pairs = Array{Tuple{Int64, Int64}}(undef, 3)

pairs

pairs2 = (1, 3)

pairs[1]

pairs[1] = (1,2)

pairs[2] = (2,3)
pairs[3] = (3,4)

pairs

# 이거랑 동일함
pairs = [(1,2); (2,3); (3,4)]

ijk_array = Array{Tuple{Int64, Int64, Int64}}(undef, 3)

ijk_array[1] = (1, 4, 2)

a = [10; 20; 30; 40; 50; 60; 70; 80; 90]

# range
a[1:3]

# 1부터 9까지 중 +3
a[1:3:9]

a[3]

a[2:3:7]

a[end-2:end]

b = [200; 300; 400]

a[2:4] = b

a

c = collect(1:2:9)

println("Hello World")

print("hello "); print("world"); print(" Again")

println("hello "); println("world"); println(" Again")

a = 123.0

println("The value of a = ", a)

println("a is $a, and a-10 is $(a-10).")

b = [1; 3; 10]

println("b is $b")

println("the second element of b is $(b[2])")

using Printf

@printf("The %s of a = %f", "value", a)

c = [123.12345; 10.983; 1.092312]

for i in 1:length(c)
    @printf("c[%d] = %7.2f\n", i, c[i])
end

str = @sprintf("The %s of a = %f", "value", a)

println(str)

for i in 1:5
    println("This is number $i")
end

for i in 1:5
    if i >= 3
        break
    end
    println("This is number $i")
end

my_keys = ["hi", "bye", "cool"]
my_values = ["football", "pocketmon","swim"]

d = Dict()

for i in 1:length(my_keys)
    d[my_keys[i]] = my_values[i]
end

d

for (key, value) in d
    println("$key is a $value player")
end

d["Diego Maradona"] = "football"

links = [(1,2), (3,4), (4,2)]

link_costs = [5, 13, 8]

link_dict = Dict()

for i in 1:length(links)
    link_dict[links[i]] = link_costs[i]
end

link_dict

for (link, cost) in link_dict
    println("Link $link has cost of $cost")
end

function f(x,y)
    return 3x+y
end

f(1,3)

3*(f(3,2)+f(5,6))

function my_func(n, m)
    a = zeros(n, 1)
    b = ones(m, 1)
    return a,b
end

x, y = my_func(3,2)

x

y

sqrt(9)

sqrt([9 16])

sqrt.([9 16])

myfunc(x) = sin(x) + 3*x

myfunc(3)

myfunc([5 10])

myfunc.([5 10])

function f(x)
    retun x+2
end


function g(x)
    return 3x+3
end

function f(x)
    return x+z
end

function run()
    z=10
    return f(5)
end

run()

function f(x)
    return x+a
end

function run()
    return f(5) 
end

a=10
run()

function f2(x)
    a=0
    return x+a
end

a=5

println(f2(1))

println(a)

function f3(x)
    _a = 0
    return x + _a
end


a = 5
println(f3(1))
println(a)

function f4(x, a)
    return x+a
end

a = 5
println(f4(1, a))
println(a)

a = [1 2 3 4 5]
s = 0
for i in 1:length(A)
    s += a[i]
end

function my_sum(a)
    s = 0
    for i in 1:5
        s += a[i]
    end
    return s
end

a = [1; 2; 3; 4; 5]

my_sum(a)

rand()

rand()

rand(5)

rand() * 100

rand(1:10)

randn(5)

function my_randn(n, mu, sigma)
    return randn(n) .* sigma .+mu
end

my_randn(10, 50, 3)

using Pkg

Pkg.add("StatsFuns")

Pkg.build("StatsFuns")

using StatsFuns

mu = 50; sigma = 3;

normpdf(mu, sigma, 52)

data_file_path = "data.txt"

data_file = open(data_file_path)

data = readlines(data_file)

close(data_file)

for line in data
    println(line)
end

output_file_path = "results1.txt"
output_file = open(output_file_path, "w")
print(output_file, "Magic Johnson")
println(output_file, "is a basketball player")
println(output_file, "Michael jordan is also a basketball palyer")
close(output_file)

using DelimitedFiles

csv_file_name = "data.csv"
csv_data = readdlm(csv_file_name, ',', header=true)

data = csv_data[1]
header = csv_data[2]

header

data

start_node = round.(Int, data[:,1])

end_node = round.(Int, data[:, 2])

link_length = data[:, 3]

using PyPlot

# Preparing a figure object
fig = figure()

# Data
x = range(0, stop=2*pi, length=1000)
y = sin.(3*x)

# Plotting with linewidth and linestyle specified
plot(x, y, color="blue", linewidth=2.0, linestyle="--")

# Labeling the axes
xlabel(L"value of $x$")
ylabel(L"\sin(3x)")

# Title
title("Test plotting")

# Save the figure as PNG and PDF
savefig("plot1.png")
savefig("plot1.pdf")

# Close the figure object
close(fig)

lower_bound = [4.0, 4.2, 4.4, 4.8, 4.9, 4.95, 4.99, 5.00]
upper_bound = [5.4, 5.3, 5.3, 5.2, 5.2, 5.15, 5.10, 5.05]
iter = 1:8

# Creating a new figure object
fig = figure()

# Plotting two datasets
plot(iter, lower_bound, color="red", linewidth=2.0, linestyle="-",
 marker="o", label=L"Lower Bound $Z^k_L$")
plot(iter, upper_bound, color="blue", linewidth=2.0, linestyle="-.",
 marker="D", label=L"Upper Bound $Z^k_U$")

# Labeling axes
xlabel(L"iteration clock $k$", fontsize="xx-large")
ylabel("objective function value", fontsize="xx-large")

# Putting the legend and determining the location
legend(loc="upper right", fontsize="x-large")

# Add grid lines
grid(color="#DDDDDD", linestyle="-", linewidth=1.0)
tick_params(axis="both", which="major", labelsize="x-large")

# Title
title("Lower and Upper Bounds")

# Save the figure as PNG and PDF
savefig("plot2.png")
savefig("plot2.pdf")

# Closing the figure object
close(fig)

# Data
data = randn(100) # Some Random Data
nbins = 10        # Number of bins

# Creating a new figure object
fig = figure()

# Histogram
plt[:hist](data, nbins)

# Title
title("Histogram")

# Save the figure as PNG and PDF
savefig("plot3.png")
savefig("plot3.pdf")

# Closing the figure object
close(fig)