Merge

Project.toml

@@ -6,14 +6,15 @@ version = "0.1.0"
 [deps]
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 LsqFit = "2fda8390-95c7-5789-9bda-21331edee243"
+PrecompileTools = "aea7be01-6a6a-4083-8856-8a6e6704d82a"
 RecipesBase = "3cdcf5f2-1ef4-517c-9805-6587b60abb01"
-SnoopPrecompile = "66db9d55-30c0-4569-8b51-7e840670fc0c"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [compat]
 LsqFit = "0.13"
+PrecompileTools = "1"
 RecipesBase = "1"
-SnoopPrecompile = "1"
+Zygote = "0.6"
 julia = "1.8"
 
 [extras]

README.md

@@ -2,6 +2,8 @@
 
 [![CI](https://github.com/mbaz/SinusoidalRegressions.jl/actions/workflows/ci.yml/badge.svg)](https://github.com/mbaz/SinusoidalRegressions.jl/actions/workflows/ci.yml)
 
+[![Aqua QA](https://raw.githubusercontent.com/JuliaTesting/Aqua.jl/master/badge.svg)](https://github.com/JuliaTesting/Aqua.jl)
+
 SinusoidalRegressions.jl aims to provide a set of functions for conveniently fitting noisy data to a variety of sinusoidal models, with or without initial estimates of the parameters. The package is quite usable in its current state, but is still in development. Support for more sinusoidal models will be added in the future, and API changes cannot be ruled out.
 
 Its documentation is found [here](https://mbaz.github.io/SinusoidalRegressions.jl/stable/).

src/SinusoidalRegressions.jl

@@ -2,7 +2,7 @@ module SinusoidalRegressions
 
 using LsqFit
 using RecipesBase
-using SnoopPrecompile
+using PrecompileTools
 using Zygote
 using LinearAlgebra
 
@@ -63,7 +63,7 @@ Sinusoidal parameters SinusoidP{Float64}:
 
 See the documentation for more details.
 """
-sinfit(p::Problem, a::Algorithm) = sinfit(p, a)
+sinfit(p::Problem, a::Algorithm) = "Not implemented."
 
 function sinfit(p::Sin3Problem, ::IEEE1057)
     ieee1057(p)
@@ -146,21 +146,30 @@ Convert polar coordinates to rectangular coordinates `(y, x)` where ``x = M\\cos
 ``y = -M\\sin(θ)``
 """
 torect(M, θ) = (-M*sin(θ), M*cos(θ))
-#=
+
 ## Precompilation
-@precompile_setup begin
+@setup_workload begin
     x = [-1.983, -1.948, -1.837, -1.827, -1.663, -0.815, -0.778, -0.754, -0.518,  0.322,  0.418,  0.781,
           0.931,  1.510,  1.607]
     y = [ 0.936,  0.810,  0.716,  0.906,  0.247, -1.513, -1.901, -1.565, -1.896,  0.051,  0.021,  1.069,
-          0.862,  0.183,  0.311] 
-    @precompile_all_calls begin
-        t2 = ieee1057(x, y)
-        t1 = ieee1057(x, y, 1.5)
-        t3 = sinfit_j(x, y)
-        t4 = sinfit(x, y, initialguess = t3)
-        t5 = mixlinsinfit_j(x, y)
-        t6 = mixlinsinfit(x, y, t5)
+          0.862,  0.183,  0.311]
+    @compile_workload begin
+        p1 = Sin3Problem(x, y, 1.5)
+        t2 = sinfit(p1, IEEE1057())
+        t3 = sinfit(p1, LevMar())
+
+        p2 = Sin4Problem(x, y, f = 1.5)
+        t4 = sinfit(p2, IEEE1057())
+        t5 = sinfit(p2, IntegralEquations())
+        t6 = sinfit(p2, LevMar())
+        t7 = sinfit(p2, Liang())
+
+        p3 = MixedLinSin4Problem(x, y, 1.5)
+        t8 = sinfit(p3, LevMar())
+
+        p4 = MixedLinSin5Problem(x, y)
+        t9 = sinfit(p3, IntegralEquations())
     end
 end
-=#
+
 end  # module