Deprecate AbstractMatrix inputs

src/RecurrenceAnalysis.jl

@@ -55,5 +55,6 @@ include("histograms.jl")
 include("rqa.jl")
 include("radius.jl")
 include("windowed.jl")
+include("deprecate.jl")
 
 end

src/deprecate.jl

@@ -0,0 +1,22 @@
+function RecurrenceMatrix(x::AbstractMatrix, ε; kwargs...)
+    @warn "`RecurrenceMatrix(x::AbstractMatrix, ε; kwargs...)` is deprecated, use `RecurrenceMatrix(Dataset(x), ε; kwargs...)`"
+    RecurrenceMatrix(Dataset(x), ε; kwargs...)
+end
+
+for call in (:CrossRecurrenceMatrix, :JointRecurrenceMatrix)
+    @eval function ($call)(x::AbstractMatrix, y, ε; kwargs...)
+        @warn string("`", $call, "(x::AbstractMatrix, y, ε; kwargs...)` is deprecated, use `", $call, "(Dataset(x), y, ε; kwargs...)`")
+        ($call)(Dataset(x), y, ε; kwargs...)
+    end
+
+    @eval function ($call)(x, y::AbstractMatrix, ε; kwargs...)
+        @warn string("`", $call, "(x, y::AbstractMatrix, ε; kwargs...)` is deprecated, use `", $call, "(x, Dataset(y), ε; kwargs...)`")
+        ($call)(x, Dataset(y), ε; kwargs...)
+    end
+
+    @eval function ($call)(x::AbstractMatrix, y::AbstractMatrix, ε; kwargs...)
+        @warn string("`", $call, "(x::AbstractMatrix, y::AbstractMatrix, ε; kwargs...)` is deprecated, use `", $call, "(Dataset(x), Dataset(y), ε; kwargs...)`")
+        ($call)(Dataset(x), Dataset(y), ε; kwargs...)
+    end
+end
+

src/matrices.jl

@@ -68,8 +68,8 @@ Objects of type `<:AbstractRecurrenceMatrix` are displayed as a [`recurrenceplot
 The recurrence matrix is a numeric representation of a "recurrence plot" [^1, ^2],
 in the form of a sparse square matrix of Boolean values.
 
-`x` must be a `Vector` or a `Dataset` or a `Matrix` with data points in rows
-(possibly representing and embedded phase space; see [`embed`](@ref)).
+`x` must be a `Vector` or a `Dataset`
+(possibly representing an embedded phase space; see [`embed`](@ref)).
 If `d(x[i], x[j]) ≤ ε` (with `d` the distance function),
 then the cell `(i, j)` of the matrix will have a `true`
 value. The criteria to evaluate distances between data points are defined
@@ -240,22 +240,19 @@ end
 ################################################################################
 # TODO: increase the efficiency here by not computing everything!
 
+# Core function
+
+# First, we define the non-parallel versions.
+
+# For two datasets
+
 """
     recurrence_matrix(x, y, metric::Metric, ε::Real, parallel::Val)
 
 Return a sparse matrix which encodes recurrence points.
 
 Note that `parallel` may be either `Val(true)` or `Val(false)`.
 """
-function recurrence_matrix(x::AbstractMatrix, y::AbstractMatrix,
-                           metric::Metric, ε, parallel::Val)
-    # Convert Matrices to Datasets (better performance in all cases)
-    return recurrence_matrix(Dataset(x), Dataset(y), metric, ε, parallel)
-end
-
-# First, we define the non-parallel versions.
-
-# Core function
 function recurrence_matrix(xx::Dataset, yy::Dataset, metric::Metric, ε, parallel::Val{false})
     x = xx.data
     y = yy.data

src/windowed.jl

@@ -25,6 +25,12 @@ const rqa_types = Dict(
     )
 )
 
+# Temporary workaround until `Dataset` can be sliced by single index
+# (https://github.com/JuliaDynamics/DelayEmbeddings.jl/pull/73)
+# Later on it will suffice with x[i]
+_subsetdata(x::AbstractVector, i) = x[i]
+_subsetdata(x::Dataset, i) = x[i,:]
+
 """
     ij_block_rmat(x, y, bsize, dindex, vargs...; kwargs...)
 
@@ -66,7 +72,7 @@ function ij_block_rmat(x, y, bsize, dindex, vargs...; kwargs...)
         elseif dindex > 0
             ix = ix .- dindex*bsize
         end
-        rmat_b = CrossRecurrenceMatrix(x[ix,:], y[iy,:], vargs...; kwargs...)
+        rmat_b = CrossRecurrenceMatrix(_subsetdata(x, ix), _subsetdata(y, iy), vargs...; kwargs...)
         append!(rws, rowvals(rmat_b) .+ix[1] .- 1)
         append!(cls, colvals(rmat_b) .+iy[1] .- 1)
     end
@@ -77,7 +83,7 @@ function ij_block_rmat(x, y, bsize, dindex, vargs...; kwargs...)
     rx = ix1:ix2
     ry = iy1:iy2
     if length(rx) > 0 && length(ry) > 0
-        rmat_b = CrossRecurrenceMatrix(x[ix1:ix2,:], y[iy1:iy2,:], vargs...; kwargs...)
+        rmat_b = CrossRecurrenceMatrix(_subsetdata(x, ix1:ix2), _subsetdata(y, iy1:iy2), vargs...; kwargs...)
         append!(rws, rowvals(rmat_b) .+ ix1 .- 1)
         append!(cls, colvals(rmat_b) .+ iy1 .- 1)
     end
@@ -231,8 +237,8 @@ macro windowed(ex, options...)
             x = ex.args[2]
             y = ex.args[3]
             minsz = :(min(size($x,1),size($y,1)))
-            subx = :($x[1:$minsz,:])
-            suby = :($y[1:$minsz,:])
+            subx = :(RecurrenceAnalysis._subsetdata($x, 1:$minsz))
+            suby = :(RecurrenceAnalysis._subsetdata($y, 1:$minsz))
             # Call `@windowed RecurrenceMatrix` twice, recycling the argument (`x` and `y`)
             ex.args[1] = :RecurrenceMatrix
             deleteat!(ex.args, 3)

test/deprecations.jl

@@ -0,0 +1,14 @@
+using Random
+
+xm = rand(10, 2)
+ym = rand(10, 2)
+v = Dataset(rand(10, 2))
+@testset "Deprecations" begin
+    @test_logs (:warn, "`RecurrenceMatrix(x::AbstractMatrix, ε; kwargs...)` is deprecated, use `RecurrenceMatrix(Dataset(x), ε; kwargs...)`") RecurrenceMatrix(xm, 0.5)
+    @test_logs (:warn, "`CrossRecurrenceMatrix(x::AbstractMatrix, y, ε; kwargs...)` is deprecated, use `CrossRecurrenceMatrix(Dataset(x), y, ε; kwargs...)`") CrossRecurrenceMatrix(xm, v, 0.5)
+    @test_logs (:warn, "`CrossRecurrenceMatrix(x, y::AbstractMatrix, ε; kwargs...)` is deprecated, use `CrossRecurrenceMatrix(x, Dataset(y), ε; kwargs...)`") CrossRecurrenceMatrix(v, ym, 0.5)
+    @test_logs (:warn, "`CrossRecurrenceMatrix(x::AbstractMatrix, y::AbstractMatrix, ε; kwargs...)` is deprecated, use `CrossRecurrenceMatrix(Dataset(x), Dataset(y), ε; kwargs...)`") CrossRecurrenceMatrix(xm, ym, 0.5)
+    @test_logs (:warn, "`JointRecurrenceMatrix(x::AbstractMatrix, y, ε; kwargs...)` is deprecated, use `JointRecurrenceMatrix(Dataset(x), y, ε; kwargs...)`") JointRecurrenceMatrix(xm, v, 0.5)
+    @test_logs (:warn, "`JointRecurrenceMatrix(x, y::AbstractMatrix, ε; kwargs...)` is deprecated, use `JointRecurrenceMatrix(x, Dataset(y), ε; kwargs...)`") JointRecurrenceMatrix(v, ym, 0.5)
+    @test_logs (:warn, "`JointRecurrenceMatrix(x::AbstractMatrix, y::AbstractMatrix, ε; kwargs...)` is deprecated, use `JointRecurrenceMatrix(Dataset(x), Dataset(y), ε; kwargs...)`") JointRecurrenceMatrix(xm, ym, 0.5)
+end

test/runtests.jl

@@ -3,3 +3,4 @@ using Test
 
 include("dynamicalsystems.jl")
 include("smallmatrix.jl")
+include("deprecations.jl")