Fix DBA to work with Julia 1.x

Project.toml

@@ -4,6 +4,7 @@ uuid = "c3fb160f-4a10-5553-b683-e707b00e83ce"
 [deps]
 BinDeps = "9e28174c-4ba2-5203-b857-d8d62c4213ee"
 Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"
+LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Parameters = "d96e819e-fc66-5662-9728-84c9c7592b0a"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 ProgressMeter = "92933f4c-e287-5a05-a399-4b506db050ca"
@@ -13,4 +14,4 @@ StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [compat]
-julia = "≥ 0.7.0"
+julia = "≥ 0.7.0"

src/dba.jl

@@ -1,3 +1,5 @@
+using LinearAlgebra
+
 """
     DBAResult(cost,converged,iterations,cost_trace)
 
@@ -18,14 +20,14 @@ and the current estimate of the average sequence.
 
 Example usage:
 
-    x = [1,2,2,3,3,4]
-    y = [1,3,4]
-    z = [1,2,2,4]
+    x = Sequence([1., 2., 2., 3., 3., 4.])
+    y = Sequence([1., 3., 4.])
+    z = Sequence([1., 2., 2., 4.])
     avg,result = dba([x,y,z])
 """
 function dba(
         sequences::AbstractVector{T},
-        method::DTWMethod,
+        method::DTWMethod = ClassicDTW(),
         dist::SemiMetric = SqEuclidean();
         init_center::T = rand(sequences),
         iterations::Int = 1000,
@@ -44,7 +46,7 @@ function dba(
     dbavg = deepcopy(init_center)
 
     # storage for each iteration
-    newavg = Sequence(zeros(length(dbavg)))
+    newavg = Sequence(zeros(size(dbavg.val)))
     counts = zeros(Int, length(dbavg))
 
     # variables storing optimization progress
@@ -111,13 +113,13 @@ function dba_iteration!(
     total_cost = 0.0
 
     # store stats for barycenter averages
-    scale!(counts,0)
-    scale!(newavg,0)
+    rmul!(counts,0)
+    rmul!(newavg,0)
 
     # main ploop
     for seq in sequences
         # time warp signal versus average
-        # if one of the two is empty, use unconstrained window. If both are nonempty, but not the same lenght, distpath will throw error
+        # if one of the two is empty, use unconstrained window. If both are nonempty, but not the same length, distpath will throw error
         if isempty(i2min) && isempty(i2max)
           cost, i1, i2 = distpath(d, oldavg, seq)
         else

src/sequence.jl

@@ -37,14 +37,6 @@ end
     :( x.val[@ntuple($N, (n-> n==$N ? i : Colon()))...] = val )
 end
 
-# convert a sequence back into an array
-# in case sequences have different lenght, throw error
-function seq_to_array(seq::AbstractVector{T}) where T <: Sequence
-  len_seq = length(seq[1])
-  arr = zeros(typeof(seq[1][1]),len_seq,length(seq))
-  for i=1:length(seq)
-    length(seq[i]) != len_seq ? error("Sequences do not have the same length, cannot construct array") : nothing
-    arr[:,i] = seq[i][:]
-  end
-  return arr
+function seq_to_array(seq::Sequence{N}) where N
+    return cat(seq..., dims=N)
 end

test/runtests.jl

@@ -298,3 +298,11 @@ end
     @test px == qx
     @test py == qy
 end
+
+@testset "DBA" begin
+    x = Sequence([1., 2., 2., 3., 3., 4.])
+    y = Sequence([1., 3., 4.])
+    z = Sequence([1., 2., 2., 4.])
+    avg, _ = dba([x, y, z], init_center=z)
+    @test avg == [1.0, 1.75, 2.75, 4.0]
+end