Mean Seasonal Cycle for a single pixel
julia
using CairoMakie
CairoMakie.activate!()
using Dates
using Statistics
We define the data span. For simplicity, three non-leap years were selected.
julia
t = Date("2021-01-01"):Day(1):Date("2023-12-31")
NpY = 3
3
and create some seasonal dummy data
julia
x = repeat(range(0, 2π, length=365), NpY)
var = @. sin(x) + 0.1 * randn()
julia
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
julia> using YAXArrays, DimensionalData
julia> axes = (Dim{:Time}(t),)
(↓ Time Date("2021-01-01"):Dates.Day(1):Date("2023-12-31"))
julia
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}()
├─────────────────────────────────────────────────────────────────── file size ┤
file size: 8.55 KB
└──────────────────────────────────────────────────────────────────────────────┘
Let's calculate the mean seasonal cycle of our dummy variable 'var'
julia
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}:
-0.03130398287109743
-0.06059678887906461
0.08125105691657612
0.019357118933250848
-0.03069412445788597
0.09901993559674853
0.2642946301720222
0.0724785553501333
0.21244822988355164
0.17115548211003082
⋮
-0.21072435162838157
-0.15326750862815794
-0.12667116885178392
-0.03650284859673286
-0.06920309673015511
0.006977886140959999
-0.10555520526290235
0.022285515523567546
-0.005783221950539453
TODO: Apply the new groupby funtion from DD
Plot results: mean seasonal cycle
julia
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()