Mean Seasonal Cycle for a single pixel

using CairoMakie
CairoMakie.activate!()
using Dates
using Statistics

We define the data span. For simplicity, three non-leap years were selected.

t =  Date("2021-01-01"):Day(1):Date("2023-12-31")
NpY = 3

3

and create some seasonal dummy data

x = repeat(range(0, 2π, length=365), NpY)
var = @. sin(x) + 0.1 * randn()

fig, ax, obj = lines(t, var; color = :purple, linewidth=1.25,
    axis=(; xlabel="Time", ylabel="Variable"),
    figure = (; size = (600,400))
    )
ax.xticklabelrotation = π / 4
ax.xticklabelalign = (:right, :center)
fig

Define the cube

julia> using YAXArrays, DimensionalData

julia> axes = (Dim{:Time}(t),)

(↓ Time Date("2021-01-01"):Dates.Day(1):Date("2023-12-31"))

julia> c = YAXArray(axes, var)

╭──────────────────────────────────╮
│ 1095-element YAXArray{Float64,1} │
├──────────────────────────────────┴───────────────────────────────────── dims ┐
  ↓ Time Sampled{Date} Date("2021-01-01"):Dates.Day(1):Date("2023-12-31") ForwardOrdered Regular Points
├──────────────────────────────────────────────────────────────────── metadata ┤
  Dict{String, Any}()
├──────────────────────────────────────────────────────────── loaded in memory ┤
  data size: 8.55 KB
└──────────────────────────────────────────────────────────────────────────────┘

Let's calculate the mean seasonal cycle of our dummy variable 'var'

function mean_seasonal_cycle(c; ndays = 365)
    ## filterig by month-day
    monthday = map(x->Dates.format(x, "u-d"), collect(c.Time))
    datesid = unique(monthday)
    ## number of years
    NpY = Int(size(monthday,1)/ndays)
    idx = Int.(zeros(ndays, NpY))
    ## get the day-month indices for data subsetting
    for i in 1:ndays
        idx[i,:] = Int.(findall(x-> x == datesid[i], monthday))
    end
    ## compute the mean seasonal cycle
    mscarray = map(x->var[x], idx)
    msc = mapslices(mean, mscarray, dims=2)
    return msc
end

msc = mean_seasonal_cycle(c);

365×1 Matrix{Float64}:
 -0.12320189493957617
  0.09317591352691727
  0.06183225090497175
  0.028497582895211832
  0.25526503219661817
  0.13853500608021024
 -0.02627341416046051
  0.18554488323324722
  0.05344184427965779
  0.09470732715757708
  ⋮
 -0.0063020041736240135
 -0.03856393968274492
 -0.08383207080301504
  0.05116592548280876
 -0.07111923498269067
 -0.07400365941169999
 -0.05345455485976908
 -0.08964458904045909
 -0.013646215450068194

TODO: Apply the new groupby funtion from DD

Plot results: mean seasonal cycle

fig, ax, obj = lines(1:365, var[1:365]; label="2021", color=:black,
    linewidth=2.0, linestyle=:dot,
    axis = (;  xlabel="Day of Year", ylabel="Variable"),
    figure=(; size = (600,400))
    )
lines!(1:365, var[366:730], label="2022", color=:brown,
    linewidth=1.5, linestyle=:dash
    )
lines!(1:365, msc[:,1]; label="MSC", color=:dodgerblue, linewidth=2.5)
axislegend()
ax.xticklabelrotation = π / 4
ax.xticklabelalign = (:right, :center)
fig
current_figure()