refactor data

Author: foldfelis

src/NeuralOperators.jl

@@ -2,7 +2,7 @@ module NeuralOperators
     using DataDeps
     using Fetch
     using MAT
-    
+
     using Flux
     using FFTW
     using Tullio
@@ -12,6 +12,6 @@ module NeuralOperators
         register_datasets()
     end
 
-    include("preprocess.jl")
+    include("data.jl")
     include("fourier.jl")
 end

src/preprocess.jl renamed to src/data.jl

@@ -1,5 +1,5 @@
 export
-    get_data
+    get_burgers_data
 
 function register_datasets()
     register(DataDep(
@@ -15,7 +15,7 @@ function register_datasets()
     ))
 end
 
-function get_data(; n=1000, Δsamples=2^3, grid_size=div(2^13, Δsamples))
+function get_burgers_data(; n=1000, Δsamples=2^3, grid_size=div(2^13, Δsamples))
     file = matopen(joinpath(datadep"BurgersR10", "burgers_data_R10.mat"))
     x_data = collect(read(file, "a")[1:n, 1:Δsamples:end]')
     y_data = collect(read(file, "u")[1:n, 1:Δsamples:end]')

test/preprocess.jl renamed to test/data.jl

@@ -1,5 +1,5 @@
-@testset "get data" begin
-    xs, ys = get_data()
+@testset "get burgers data" begin
+    xs, ys = get_burgers_data()
 
     @test size(xs) == (2, 1024, 1000)
     @test size(ys) == (1024, 1000)

test/fourier.jl

@@ -7,7 +7,7 @@
         SpectralConv1d(ch, modes)
     )
 
-    𝐱, _ = get_data()
+    𝐱, _ = get_burgers_data()
     @test size(m(𝐱)) == (64, 1024, 1000)
 
     T = Float32
@@ -25,7 +25,7 @@ end
         FourierOperator(ch, modes)
     )
 
-    𝐱, _ = get_data()
+    𝐱, _ = get_burgers_data()
     @test size(m(𝐱)) == (64, 1024, 1000)
 
     loss(x, y) = Flux.mse(m(x), y)
@@ -34,7 +34,7 @@ end
 end
 
 @testset "FNO" begin
-    𝐱, 𝐲 = get_data()
+    𝐱, 𝐲 = get_burgers_data()
     𝐱, 𝐲 = Float32.(𝐱), Float32.(𝐲)
     @test size(FNO()(𝐱)) == size(𝐲)
 

test/runtests.jl

@@ -3,6 +3,6 @@ using Test
 using Flux
 
 @testset "NeuralOperators.jl" begin
-    include("preprocess.jl")
+    include("data.jl")
     include("fourier.jl")
 end