Generic types in gdtw

src/gdtw.jl

@@ -57,12 +57,27 @@ function update_τ!(τ, t, M, l, u)
 end
 
 """
-    gdtw(x, y; M::Int=100, N=nothing, t=range(0, stop=1, length=N), λcum=0.01,
-    λinst=0.01, η=1 / 8, max_iters=3, metric=(x,y) -> norm(x-y),
-    Rcum=u -> u * u, smin::Real=0.001, smax::Real=5.0,
-    Rinst=u -> smin <= u <= smax ? u^2 : Inf,
-    verbose=false,
-    cache=GDTWWorkspace(M, N), warp=zeros(N))
+    prepare_gdtw(
+        x,
+        y,
+        ::Type{T}  = Float64;
+        M::Int     = 100,
+        N          = 100,
+        t          = range(T(0), stop = T(1), length = N),
+        λcum       = T(0.01),
+        λinst      = T(0.01),
+        η          = T(1 / 8),
+        max_iters  = 3,
+        metric     = (x, y) -> norm(x - y),
+        Rcum       = u -> u^2,
+        smin::Real = T(0.001),
+        smax::Real = T(5.0),
+        Rinst      = u -> smin <= u <= smax ? u^2 : typemax(T),
+        verbose    = false,
+        warp       = zeros(length(t)),
+        callback   = nothing,
+        cache::GDTWWorkspace{T} = GDTWWorkspace(M, length(t)),
+    )
 
 Computes a general DTW distance following [DB19](https://arxiv.org/abs/1905.12893). The parameters are:
 
@@ -78,7 +93,7 @@ Computes a general DTW distance following [DB19](https://arxiv.org/abs/1905.1289
 
 The following may be pre-allocated and reused between distance computations with the same `M` and `N` (or `length(t)`).
 
-* `cache`: a cache of matrices and vectors, generated by `GDTW.GDTWWorkspace{Float64}(N,M)`
+* `cache`: a cache of matrices and vectors, generated by `GDTW.GDTWWorkspace{T}(N,M)`
 
 """
 gdtw(args...; kwargs...) = iterative_gdtw!(prepare_gdtw(args...; kwargs...))
@@ -89,13 +104,27 @@ gdtw(args...; kwargs...) = iterative_gdtw!(prepare_gdtw(args...; kwargs...))
 Creates a NamedTuple of parameters, using the same keyword argments as `dist`.
 A preprocessing step before calling `iterative_gdtw!`.
 """
-function prepare_gdtw(x, y; M::Int=100, N=100, t = range(0, stop=1, length=N), λcum=0.01,
-                      λinst=0.01, η=1 / 8, max_iters=3, metric=(x,y) -> norm(x-y),
-                      Rcum=u -> u^2, smin::Real=0.001, smax::Real=5.0,
-                      Rinst=u -> smin <= u <= smax ? u^2 : Inf,
-                      verbose=false,
-                      cache=GDTWWorkspace(M, length(t)), warp=zeros(length(t)),
-                      callback=nothing)
+function prepare_gdtw(
+    x,
+    y,
+    ::Type{T}  = Float64;
+    M::Int     = 100,
+    N          = 100,
+    t          = range(T(0), stop = T(1), length = N),
+    cache::GDTWWorkspace = GDTWWorkspace{T}(M, length(t)),
+    λcum       = T(0.01),
+    λinst      = T(0.01),
+    η          = T(1 / 8),
+    max_iters  = 3,
+    metric     = (x, y) -> norm(x - y),
+    Rcum       = u -> u^2,
+    smin::Real = T(0.001),
+    smax::Real = T(5.0),
+    Rinst      = u -> smin <= u <= smax ? u^2 : typemax(T),
+    verbose    = false,
+    warp       = zeros(length(t)),
+    callback   = nothing,
+) where T
     N = length(t)
 
     if !(M > N / smax)
@@ -110,15 +139,30 @@ function prepare_gdtw(x, y; M::Int=100, N=100, t = range(0, stop=1, length=N), 
     node_weight(j, s) = metric(x(τ[j, s]), y(t[s])) + λcum * Rcum(τ[j, s] - t[s])
 
     @inline function edge_weight((j, s), (k, s2))
-        s + 1 ≠ s2 && return Inf
+        s + 1 ≠ s2 && return typemax(T)
         u = (τ[k, s+1] - τ[j, s]) / (t[s+1] - t[s])
         λinst * Rinst(u)
     end
 
-    return (N=N, M=M, τ=τ, node_weight=node_weight, edge_weight=edge_weight,
-            l₀=l₀, u₀=u₀, η=η, max_iters=max_iters, t=t, smin=smin, smax=smax,
-            callback=callback, verbose=verbose, metric=metric, cache=cache,
-            warp=warp)
+    return (
+        N           = N,
+        M           = M,
+        τ           = τ,
+        node_weight = node_weight,
+        edge_weight = edge_weight,
+        l₀          = l₀,
+        u₀          = u₀,
+        η           = η,
+        max_iters   = max_iters,
+        t           = t,
+        smin        = smin,
+        smax        = smax,
+        callback    = callback,
+        verbose     = verbose,
+        metric      = metric,
+        cache       = cache,
+        warp        = warp,
+    )
 end
 
 
@@ -150,7 +194,7 @@ function iterative_gdtw!(data)
         update_τ!(τ, t, M, l, u)
         cost = single_gdtw!(data)
         if callback !== nothing
-            callback((iter=iter, t=t, τ=τ, warp=warp, cost=cost))
+            callback((iter = iter, t = t, τ = τ, warp = warp, cost = cost))
         end
         iter += 1
     end

test/runtests.jl

@@ -5,9 +5,13 @@ using Distances, Plots
 @testset "DynamicAxisWarping" begin
     @info "Testing DynamicAxisWarping"
 
-    include("test_gdtw.jl")
+    @testset "GDTW" begin
+        @info "Testing GDTW"
+        include("test_gdtw.jl")
+    end
 
     @testset "LinearInterpolation" begin
+        @info "Testing LinearInterpolation"
         # Test arrays
         x = rand(20, 20, 100)
         x_interp = LinearInterpolation(x)
@@ -27,7 +31,7 @@ using Distances, Plots
         @test x_interp(1) == x[end]
         @test x_interp(4/99) == x[5]
     end
-    
+
     @testset "Normalizers" begin
         @info "Testing Normalizers"
         a = randn(2,100)