add tests

Project.toml

@@ -6,7 +6,9 @@ version = "0.1.0"
 [deps]
 Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
 Libdl = "8f399da3-3557-5675-b5ff-fb832c97cbdb"
+LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Parameters = "d96e819e-fc66-5662-9728-84c9c7592b0a"
+StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 nlminb_jll = "c04a2911-6870-53d6-aa47-4d7d5aff1028"
 
@@ -18,4 +20,3 @@ Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
 test = ["Test"]
-

src/CurveFit/CurveFit.jl

@@ -1,4 +1,3 @@
-include("DataTypes.jl")
 include("init_param.jl")
 include("doubleLogistics.jl")
 

src/VegCurveFit.jl

@@ -1,11 +1,12 @@
 module VegCurveFit
 
 using LinearAlgebra
-import Libdl
+using Libdl
 using Parameters
 using Dates
 using Statistics
 
+include("DataTypes.jl")
 include("tools.jl")
 
 include("Optim/Optim.jl")

src/smooth_SG/SG.jl

@@ -1,6 +1,3 @@
-using LinearAlgebra
-
-
 multiply_col!(S::AbstractArray{T1,2}, w::AbstractArray{T}) where {
   T1<:Real,T<:Real} = begin
   nrow, ncol = size(S)

src/smooth_SG/SG_helper.jl

@@ -1,6 +1,3 @@
-using StaticArrays
-
-
 function sgmat_S(halfwin::Int=1, d::Int=2)
   frame = 2 * halfwin + 1
   mat = zeros(Int, frame, d + 1)

src/smooth_SG/main_SG.jl

@@ -1,3 +1,6 @@
+using LinearAlgebra
+using StaticArrays
+
 include("SG_helper.jl")
 include("SG.jl")
 include("SG_weighted.jl")

test/runtests.jl

@@ -1,17 +1,7 @@
 using Test
 using VegCurveFit
 
-@testset "nlminb" begin
-  # Write your own tests here.
-  start = [0.0] # [1, 2, 3, 4]
-  lower = [-4.0]
-  upper = [4.0]
-
-  function f2(x::Array{Float64,1})::Float64
-    x[1] - cos(x[1])
-  end
-
-  f(x) = x[1] - cos(x[1])
-  r = nlminb(start, f, verbose=false)
-  @test r["par"][1] == -1.5701006351106073
-end
+include("test-lambda_init.jl")
+include("test-smooth_SG.jl")
+include("test-smooth_whit.jl")
+include("test-Optim.jl")

test/test-Optim.jl

@@ -0,0 +1,14 @@
+@testset "nlminb" begin
+  # Write your own tests here.
+  start = [0.0] # [1, 2, 3, 4]
+  lower = [-4.0]
+  upper = [4.0]
+
+  function f2(x::Array{Float64,1})::Float64
+    x[1] - cos(x[1])
+  end
+
+  f(x) = x[1] - cos(x[1])
+  r = nlminb(start, f, verbose=false)
+  @test r["par"][1] == -1.5701006351106073
+end

test/test-lambda_init.jl

@@ -0,0 +1,11 @@
+# using Random
+
+@testset "lambda init" begin
+  # @examples
+  # Random.seed!(1234)
+  y = rand(100)
+  coef = [0.9809, 0.7247, -2.6752, -0.3854, -0.0604]
+  lamb = lambda_init(y, coef)
+  @test lamb > 0
+end
+# methods(lambda_init)

test/test-smooth_SG.jl

@@ -0,0 +1,57 @@
+using Test
+
+@testset "Savitzky Golay filter" begin
+  # works
+  @test wSG([2., 3, 5, 7]; halfwin=1, d=2) ≈ [2, 3, 5, 7]
+
+  y = 1.0:10 |> collect
+  @test wSG(y; halfwin=1, d=1) ≈ y
+
+  # 跟R语言版本基本一致
+  y = [2.0, 3, 4, 10, 6, 7]
+  w = [1.0, 1, 1, 0.2, 1, 1]
+  z = wSG(y, w; halfwin=1, d=1)
+  @test round.(z, digits=2) ≈ [2, 3, 5, 5.45, 7, 6.5]
+
+  # wSG对权重调整没有这么敏感
+  z = wSG(y, w; halfwin=1, d=2)
+  @test round.(z, digits=2) ≈ y
+end
+
+
+@testset "Savitzky Golay filter" begin
+  y = [1.0, 2, 5, 4, 3, 6]
+  w = collect(1.0:7)
+  halfwin = 3
+  S = sgmat_S(halfwin)
+  B = sgmat_B(S)
+  sgmat_wB(S, w)
+  z = SG(y; halfwin=1)
+  @test z ≈ y
+end
+
+
+@testset "Savitzky Golay filter" begin
+  y = rand(100)
+  w = rand(100)
+  SG(y; halfwin=5)
+  wSG(y, w; halfwin=5)
+end
+
+
+# using Plots
+# p = plot(y)
+# plot!(p, z1)
+# plot!(p, z2)
+# n = Int(1e5)
+# y = rand(n)
+# using BenchmarkTools
+
+## test the used memory
+# @time for i=1:1e3
+#     z = SG(y)
+# end
+# using Plots
+# gr()
+# plot(y)
+# plot!(z)

test/test-smooth_whit.jl

@@ -0,0 +1,48 @@
+using Test
+
+@testset "whittaker smoother" begin
+  y = [5.0, 8, 9, 10, 12, 10, 15, 10, 9, 19, 19, 17, 13, 14, 18, 19, 18, 12, 18,
+    24, 0, 1, 18, 17, 6, 13, 12, 10, 9, 6, 6, 3, 4, 3, 3, 3, 2, 3, 4, 4, 3, 2, 3, 3, 1, 3]
+  y = [y; y; y; y]
+  m = length(y)
+  FT = Float32
+
+  w = ones(Float32, m)
+  c = zeros(Float32, m)
+  d = zeros(Float32, m)
+  e = zeros(Float32, m)
+
+  lambda = 2.0
+  z = ones(m)
+  interm = interm_whit{FT}(; n=length(y))
+  cve = whit2!(y, w, lambda, interm; include_cve=true)
+  z, cve2 = whit2(y, w, lambda)
+
+  @test cve == cve2
+  lamb_cv = lambda_cv(y, w, is_plot=false)
+  lamb_vcurve = lambda_vcurve(y, w)
+
+  z1, cve_cv = whit2(y, w, lamb_cv)
+  z2, cve_vcurve = whit2(y, w, lamb_vcurve)
+  @test cve_cv < cve
+  @test cve_vcurve < cve
+  @test cve_cv < cve_vcurve
+end
+
+# using BenchmarkTools
+# @benchmark
+# 4 times faster than R
+# @time for i in 1:1e4
+#     lamb_vcurve = lambda_vcurve(y, w)
+# end
+# @time lamb_vcurve = lambda_vcurve(y, w)
+
+# @time @benchmark lamb_cv = lambda_cv(y, w)
+# BenchmarkTools.Trial: 
+#   memory estimate:  412.55 KiB
+#   allocs estimate:  374
+#   --------------
+#   minimum time:     172.600 μs (0.00% GC)
+#   median time:      179.300 μs (0.00% GC)
+#   mean time:        198.880 μs (3.88% GC)
+#   maximum time:     1.882 ms (70.58% GC)

test/test_wTSM.jl

@@ -0,0 +1,19 @@
+# @profview 
+n = 1000
+y = rand(n)
+w = rand(n)
+yfit = rand(n)
+
+# @testset "weights updating" begin
+#   w_ts = wTSM(y, yfit, w, iter=2)
+#   w_bi = wBisquare(y, yfit, w, iter=2)
+
+#   @test length(w_ts) == n
+#   @test length(w_bi) == n
+# end
+
+# using BenchmarkTools
+# @benchmark wnew = wTSM(y, yfit, w, iter = 2)
+
+# # Debugger.@run 
+# @benchmark w2 = wBisquare(y, yfit, w, iter = 2)