briochemc

using AIBECS, ModelingToolkit, LinearAlgebra

# dispatch for sparse matrices
Base.:*(A::SparseMatrixCSC{Operation,S}, x::StridedVector{Operation}) where {S} =
    (T = Operation; mul!(similar(x, T, A.m), A, x, true, false))
Base.:*(A::SparseMatrixCSC{Tx,S}, x::StridedVector{Operation}) where {Tx,S} =
    (T = LinearAlgebra.promote_op(LinearAlgebra.matprod, Operation, Tx); mul!(similar(x, T, A.m), A, x, true, false))
Base.:*(A::SparseMatrixCSC{Operation,S}, x::StridedVector{Tx}) where {Tx,S} =
    (T = LinearAlgebra.promote_op(LinearAlgebra.matprod, Operation, Tx); mul!(similar(x, T, A.m), A, x, true, false))

briochemc

using Luxor, Colors

function main(fname)
    Drawing(600, 600, fname)
    origin()
    circle(O, 290, :clip)
    sethue("white")
    paint()

    colors = [Luxor.julia_blue, Luxor.julia_red, Luxor.julia_green, Luxor.julia_purple]

briochemc

using AIBECS, Plots
grd, TOCIM1 = OCIM1.load()
T(p) = TOCIM1
function G(x,p)
    @unpack τ, z₀ = p
    return @. 1 - x / τ * (z < z₀)
end
z = depthvec(grd)
F, ∇ₓF = state_function_and_Jacobian(T, G)
struct IdealAgeParameters{U} <: AbstractParameters{U}

briochemc

# Load World Ocean Atlas 2D fields for PO₄, Si(OH)₄, and NO₄
using WorldOceanAtlasTools
product_year = 2018
tracer = "p"
period = 0
resolution = "1°"
ds = WorldOceanAtlasTools.WOA_Dataset(product_year, tracer, period, resolution, verbose=false) ;
field = "an"
field3D, lat, lon, depth = WorldOceanAtlasTools.get_gridded_3D_field(ds, tracer, field) ;
map_2D = field3D[:,:,1] ;

briochemc

using SparseArrays, LinearAlgebra, SuiteSparse
using Unitful

"""
    elunit(x)
    
Returns the unit of the elements of `x`.
(Returns a `Unitful.FreeUnits{(),NoDims,nothing}` object `x`'s unit is heterogeneous.)
"""
elunit(::SparseMatrixCSC{U,Int64}) where {U<:Quantity} = unit(U)

briochemc

ENV["MPLBACKEND"]="qt5agg"
"qt5agg"

using PyPlot, PyCall

clf()

ax = subplot(projection=ccrs.NearsidePerspective(central_latitude=10.0, central_longitude=170.0, satellite_height=100000000.0))

ax.add_feature(cfeature.NaturalEarthFeature("physical", "ocean", "50m", edgecolor="face", facecolor="#4063d8"))

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")

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

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

 
# 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