briochemc

using LinearAlgebra, SparseArrays, SuiteSparse
using DualNumbers, DualMatrixTools
using BenchmarkTools

n = 1000 ;

y = rand(n) ;

A = sprand(n, n, 20/n) ;
i, j, v = findnz(A) ;

briochemc

# Error check
using LinearAlgebra, SparseArrays, SuiteSparse, BenchmarkTools, MAT
M = matread("test_matrix.mat")["M"] ;
x = matread("test_matrix.mat")["x"] ;
Mf = factorize(M) ;
sol1 = Mf \ x ;
sol2 = M \ x ;
norm(x)
norm(x - M * sol1) / norm(x)
norm(x - M * sol1)

briochemc

const x = 1.0 ;

function foo(y)
    println("x = ", x)
end

foo("a string") # should print "x = 1.0"
# Invoking foo just JIT-compiled foo to use x = 1.0 if the argument is a string.

x = 2.0 ; # modify constant

briochemc

using DualNumbers, LinearAlgebra, SparseArrays, SuiteSparse

n = 10
A = randn(n, n)            # a real-valued matrix
B = randn(n, n)            # another real-valued matrix

# Create a dual-valued matrix
M = A + ε * B

# And a sparse version of it

briochemc

mutable struct ThreeVec <: AbstractVector{Float64}
    x::Float64
    y::Float64
    z::Float64
end

Base.size(V::ThreeVec) = (3,)
Base.IndexStyle(::Type{<:ThreeVec}) = IndexLinear()
using Match
Base.getindex(V::ThreeVec, i::Int) = @match i begin

briochemc

using VegaLite, DataFrames

df = DataFrame(x = [0, 1, 2, 3, 4, 0, 1, 2, 3, 4], y = 1:10, style = ["A", "A", "A", "A", "A", "B", "B", "B", "B", "B"])

list_styles = ["B", "A"]
mycolors = ["#000000", "#ee00ff"]
    
p = df |>
@vlplot(
    mark={

briochemc

 
# 1. Load packages
using DualMatrixTools, DualNumbers, SparseArrays

# 2. Create a random dual-valued vector x
n = 10
a, b = rand(n), rand(n)       # real and dual parts
x = a + ε * b                 # dual-valued x

# 3. Create a sparse random dual-valued matrix M

briochemc

using Makie
using AbstractPlotting
using FileIO, Colors

# Load World Ocean Atlas 2D fields for PO₄, Si(OH)₄, and NO₄
using WorldOceanAtlasTools
lat, lon, PO₄_2D   = WorldOceanAtlasTools.WOA13_surface_map("p", 0, "1°")
lat, lon, NO₄_2D   = WorldOceanAtlasTools.WOA13_surface_map("n", 0, "1°")
lat, lon, SiOH₄_2D = WorldOceanAtlasTools.WOA13_surface_map("i", 0, "1°")
# Add the image layer to each plot

briochemc

using Makie
using GeometryTypes

wet3d = falses(2, 2, 2)
wet3d[[1, 2, 3, 5, 6]] .= true

shoebox3d = permutedims(wet3d, [2, 1, 3])

mycolor(x) = x ? RGBAf0(0,0,1,0.4) : RGBAf0(0.5,0.5,0,1)
Ind = CartesianIndices(size(shoebox3d))

briochemc

length(ARGS) == 1 && (sheet = "Sheet1")

# Use the installed packages
using ExcelFiles, DataFrames, Interpolations

# Replace by your file with just the data!
df = DataFrame(load(abspath(ARGS[1]), sheet))
println("Resampling $(ARGS[1]) - $sheet")