time series blocks

Author: codeboy5

src/FastAI.jl

@@ -115,6 +115,9 @@ include("Tabular/Tabular.jl")
 include("Textual/Textual.jl")
 @reexport using .Textual
 
+include("TimeSeries/TimeSeries.jl")
+@reexport using .TimeSeries
+
 include("deprecations.jl")
 export
     methodmodel,
@@ -178,6 +181,7 @@ export
     Continuous,
     Image,
     Paragraph,
+    TimeSeriesRow,
 
     # encodings
     encode,

src/TimeSeries/TimeSeries.jl

@@ -0,0 +1,40 @@
+module TimeSeries
+
+
+using ..FastAI
+using ..FastAI:
+    # blocks
+    Block, WrapperBlock, AbstractBlock, OneHotTensor, OneHotTensorMulti, Label,
+    LabelMulti, wrapped, Continuous, getencodings, getblocks, encodetarget, encodeinput,
+    # encodings
+    Encoding, StatefulEncoding, OneHot,
+    # visualization
+    ShowText,
+    # other
+    Context, Training, Validation
+    
+# for tests
+using ..FastAI: testencoding
+
+# extending
+import ..FastAI:
+    blockmodel, blockbackbone, blocklossfn, encode, decode, checkblock,
+    encodedblock, decodedblock, showblock!, mockblock, setup
+
+import Requires: @require
+
+using FilePathsBase
+using InlineTest
+
+# Blocks
+include("blocks/timeseriesrow.jl")
+
+include("recipes.jl")
+
+function __init__()
+    _registerrecipes()
+end
+
+export TimeSeriesRow
+
+end

src/TimeSeries/blocks/timeseriesrow.jl

@@ -0,0 +1,37 @@
+"""
+    TimeSeriesRow{M,N}() <: Block
+
+[`Block`](#) for a M variate time series with N number of time steps. `obs` is valid for `TimeSeriesRow{M,N}()`
+if it is an (M,N) dimensional Matrix with number element type.
+
+## Examples
+
+Creating a block:
+
+```julia
+TimeSeriesRow{1,51}()  # Univariate time series with length 51.
+TimeSeriesRow{2,51}()  # Multivariate time series with 2 variables and length 51.
+```
+
+You can create a random observation using [`mockblock`](#):
+
+{cell=main}
+```julia
+using FastAI
+FastAI.mockblock(TimeSeriesRow{1,10}())
+```
+
+"""
+
+struct TimeSeriesRow{M,N} <: Block end
+
+function checkblock(::TimeSeriesRow{M,N}, obs::AbstractArray{T,2}) where {M,N,T<:Number}
+    size(obs) == (M,N)
+end
+
+mockblock(::TimeSeriesRow{M,N}) where {M,N} = rand(Float64, (M,N))  
+
+function setup(::Type{TimeSeriesRow}, data)
+    N, M = size(getobs(data, 1))
+    return TimeSeriesRow{N,M}()
+end

src/TimeSeries/makie.jl

@@ -0,0 +1,63 @@
+"""
+    TimeSeriesDatasetRecipe(file; loadfn = loadfile)
+
+Recipe for loading a time series dataset stored in a .ts file
+
+"""
+Base.@kwdef struct TimeSeriesDatasetRecipe <: Datasets.DatasetRecipe
+    train_file
+    test_file = nothing
+    loadfn = loadfile
+end
+
+Datasets.recipeblocks(::Type{TimeSeriesDatasetRecipe}) = Tuple{TimeSeriesRow, Label} 
+
+#TODO: Add Check if test_file is nothing.
+function Datasets.loadrecipe(recipe::TimeSeriesDatasetRecipe, path)
+    path = convert(String, path)
+    datasetpath_train = joinpath(path, recipe.train_file)
+    rows_train, labels_train = recipe.loadfn(datasetpath_train)
+    datasetpath_test = joinpath(path, recipe.test_file)
+    rows_test, labels_test = recipe.loadfn(datasetpath_test)
+    rows = [rows_train; rows_test]
+    labels = [labels_train; labels_test]
+    rows = TimeSeriesDataset(rows)
+    data = rows, labels
+    blocks = (
+        setup(TimeSeriesRow,rows),
+        Label(unique(eachobs(labels))),
+    )
+    return data, blocks
+end
+
+# Registering recipes
+
+const RECIPES = Dict{String,Vector{Datasets.DatasetRecipe}}(
+    "ecg5000" => [
+        TimeSeriesDatasetRecipe(train_file="ECG5000_TRAIN.ts", test_file="ECG5000_TEST.ts")
+    ],
+)
+
+function _registerrecipes()
+    for (name, recipes) in RECIPES, recipe in recipes
+        if !haskey(datarecipes(), name)
+            push!(datarecipes(), (
+                id = name,
+                datasetid = name,
+                blocks = Datasets.recipeblocks(recipe),
+                package = @__MODULE__,
+                recipe = recipe,
+            ))
+        end
+    end
+end
+
+# ## Tests
+
+@testset "TimeSeriesDataset [recipe]" begin
+    path = datasetpath("ecg5000")
+    recipe = TimeSeriesDatasetRecipe(train_file="ECG5000_TRAIN.ts", test_file="ECG5000_TEST.ts")
+    data, block = loadrecipe(recipe, path)
+    sample = getobs(data, 1)
+    @test checkblock(block, sample)
+end

src/TimeSeries/recipes.jl

@@ -65,10 +65,12 @@ export
     # primitive containers
     FileDataset,
     TableDataset,
+    TimeSeriesDataset,
 
     # utilities
     isimagefile,
     istextfile,
+    istimeseriesfile,
     matches,
     loadfile,
     loadmask,