some tests

README.md

@@ -40,6 +40,8 @@ consecutive windows of `A` will be compared to the entire `B`. The resulting mat
 
 If `dist` is provided, a generic (slow) method is used. If `dist` is not provided and the inputs `A,B` are one dimensional vectors of numbers, a fast method is used. The fast method handles long time series, `length(A) = length(B) = 100k` takes less than 30s.
 
+If the time-series is sampled very fast in relation to the time scale on which interesting things happen, you may try the function [`resample(T, fraction::Real)`](https://juliadsp.github.io/DSP.jl/stable/filters/#DSP.Filters.resample) to reduce the amount of data to process. Example, `resample(T, desired_samplerate/original_samplerate)`.
+
 ## Motif grouping
 Using the fake data from the example above, we can do
 ```julia
@@ -50,7 +52,7 @@ plot(profile, mot)
 ```
 - `k` is the number of motifs to extract
 - `r` controls how similar two windows must be to belong to the same motif. A higher value leads to more windows being grouped together.
-- `th` is a threshold on how far nearby in time two motifs are allowed to be.
+- `th` is a threshold on how nearby in time two motifs are allowed to be.
 ![motif_plot](figures/motifs.svg)
 
 Also see the function `anomalies(profile)` to find anomalies in the data, sometimes called *discords*.

src/MatrixProfile.jl

@@ -8,7 +8,7 @@ using RecipesBase
 using SlidingDistancesBase
 import SlidingDistancesBase: floattype, lastlength, distance_profile, distance_profile!
 
-export matrix_profile, distance_profile, motifs, anomalies, mpdist, mpdist_profile, onsets, snippets, seqs
+export matrix_profile, distance_profile, motifs, anomalies, mpdist, mpdist_profile, onsets, snippets, seqs, resample
 
 
 struct Profile{TT,TP,QT}

src/motifs.jl

@@ -15,7 +15,7 @@ const SubSeqType = Union{AbstractSubSequence, AbstractVector{<:AbstractSubSequen
 onsets(m::Motif) = getfield.(m.seqs, :onset)
 seqs(m::Motif) = getfield.(m.seqs, :seq)
 seqlength(m::Motif) = length(m.seqs[1].seq)
-subseqtype(::Motif) = "Motif"
+subseqtype(::Union{Motif, Vector{<:Motif}}) = "Motif"
 
 onsets(m::Subsequence) = m.onset
 seqs(m::Subsequence) = [m.seq]
@@ -24,7 +24,7 @@ subseqtype(m::Subsequence) = m.type
 
 onsets(m::Array{<:Subsequence}) = onsets.(m)
 seqs(m::Array{<:Subsequence}) = getfield.(m, :seq)
-seqlength(m::Array{<:Subsequence}) = seqlength(length(m[1]))
+seqlength(m::Array{<:Subsequence}) = length(m[1].seq)
 subseqtype(m::Array{<:Subsequence}) = subseqtype(m[1])
 
 function motifs(p::Profile, k, r, th = 0, found_motifs = Motif[])

test/runtests.jl

@@ -134,14 +134,19 @@ end
        profile = matrix_profile(T, length(y0))
 
        @time mot = motifs(profile, 2, 2, 5)
+       @test MatrixProfile.subseqtype(mot) == "Motif"
        @test onsets(mot[1]) == [51, 112]
        @test_nowarn plot(mot)
        @test_nowarn plot(profile, mot)
 
        an = MatrixProfile.anomalies(profile, 3)
        @test length(an) == 3
+       @test length(seqs(an)) == 3
+       @test MatrixProfile.subseqtype(an) == "Anomaly"
        @test onsets(an)[1] == argmax(profile.P)
        @test_nowarn plot(an)
+       @test MatrixProfile.seqlength(an) == length(y0)
+
    end