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b/src/ECCOtour.jl index 378e704..a031cb9 100644 --- a/src/ECCOtour.jl +++ b/src/ECCOtour.jl @@ -14,7 +14,7 @@ import Statistics.mean, Statistics.std, export hanncoeffs, hannsum, hannsum!, hannfilter export get_filtermatrix, matrixfilter, matrixspray, columnscale! -export seasonal_matrices, trend_matrices +export seasonal_matrices, trend_matrices, mean_matrices export position_label, searchdir export listexperiments, expnames, expsymbols, time_label export inrectangle, isnino34, issouthpac, isnino3, isnino4, isnino12 diff --git a/src/SeasonalCycle.jl b/src/SeasonalCycle.jl index bbf04b2..fd0342f 100644 --- a/src/SeasonalCycle.jl +++ b/src/SeasonalCycle.jl @@ -8,7 +8,7 @@ - `E`: matrix that solves E*parameters= seasonal cycle - `F=E†`: generalized inverse of `E` """ -function seasonal_matrices(fcycle,t,overtones=1) +function seasonal_matrices(fcycle,t,overtones=1, fit_mean = true) ω = 2π * fcycle # day^{-1} , seasonal frequency nt = length(t) @@ -31,6 +31,11 @@ function seasonal_matrices(fcycle,t,overtones=1) E[:,i+freqs+1] = cos.(i*ω*t) end + # If mean is not fitted, remove the first column + if !fit_mean + E = E[:, 2:end] + end + F = (E'*E)\E' # least squares estimator return E,F @@ -67,3 +72,24 @@ function trend_matrices(t) end +""" + function mean_matrices(t) + + computes the mean using matrix inversions +# Arguments +- `t`: time +# Output +- `E`: matrix that solves E*parameters= timeseries +- `F=E†`: generalized inverse of `E` +""" +function mean_matrices(t) + nt = length(t) + + # Create the matrix E for fitting the mean + E = ones(Float32, nt, 1) + println(size(E)) + + F = (E' * E) \ E' # least squares estimator + + return E, F +end \ No newline at end of file diff --git a/test/runtests.jl b/test/runtests.jl index d45a333..b621f9e 100644 --- a/test/runtests.jl +++ b/test/runtests.jl @@ -32,7 +32,9 @@ using Downloads @testset "basin mask" begin include(testdir("test_basinmask.jl")) end - + @testset "SeasonalCycle" begin + include(testdir("test_seasonalcycle.jl")) + end cd(srcdir()) # workaround: use a shell script #run(`sh $srcdir/download_google_drive.sh`) diff --git a/test/test_seasonalcycle.jl b/test/test_seasonalcycle.jl new file mode 100644 index 0000000..1232670 --- /dev/null +++ b/test/test_seasonalcycle.jl @@ -0,0 +1,27 @@ +# Define test parameters +fcycle = 1.0 / 365.0 +t = 1:365 # One year of daily data +overtones = 2 + +# Test fit_mean function +E_mean, F_mean = mean_matrices(t) +@test size(E_mean) == (365, 1) +@test all(E_mean[:, 1] .== 1.0) + +# Test seasonal_matrices with fit_mean = true +E1, F1 = seasonal_matrices(fcycle, t, overtones, true) +@test size(E1) == (365, (overtones + 1) * 2 + 1) +@test all(E1[:, 1] .== 1.0) + +# Test seasonal_matrices with fit_mean = false +E2, F2 = seasonal_matrices(fcycle, t, overtones, false) +@test size(E2) == (365, (overtones + 1) * 2) + +# Check that the sine and cosine values are correctly computed +ω = 2π * fcycle +for i = 1:overtones+1 + @test all(E1[:, i+1] .≈ sin.(i * ω * t)) + @test all(E1[:, i+overtones+2] .≈ cos.(i * ω * t)) + @test all(E2[:, i] .≈ sin.(i * ω * t)) + @test all(E2[:, i+overtones+1] .≈ cos.(i * ω * t)) +end \ No newline at end of file