add missingval option to timeseries (#55)

CHANGELOG.md

@@ -3,6 +3,10 @@
 All notable changes to this project will be documented in this file.
 
 This project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.html).
+
+# 1.5.0
+* Option `missingval` for `timeseries`.
+
 # 1.4.0
 * New function `repeat`.
 * `combine` now works with `Vector{Vector{<:Note}}` as well.

Project.toml

@@ -1,7 +1,7 @@
 name = "MusicManipulations"
 uuid = "274955c0-c284-5bf7-b122-5ecd51c559de"
 repo = "https://github.com/JuliaMusic/MusicManipulations.jl.git"
-version = "1.4.1"
+version = "1.5.0"
 
 [deps]
 MIDI = "f57c4921-e30c-5f49-b073-3f2f2ada663e"

src/data_handling/timeseries.jl

@@ -1,7 +1,7 @@
 export timeseries, segment
 
 """
-    timeseries(notes::Notes, property::Symbol, f, grid; segmented = false) -> tvec, ts
+    timeseries(notes::Notes, property::Symbol, f, grid; kwargs...) -> tvec, ts
 Produce a timeseries of the `property` of the given notes, by
 first quantizing on the given `grid` (to avoid actual quantization
 use the grid `0:1//notes.tpq:1`). Return the time vector `tvec` in ticks
@@ -10,21 +10,21 @@ and the produced timeseries `ts`.
 After quantization, it is often the case that many notes are in the same bin of
 the grid. The **function** `f` denotes which value of the vector of the
 `property` of the notes to keep. Typical values are `minimum, maximum, mean`,
-etc. Notice that bins without any note in them obtain the value `missing`,
-regardless of the function `f` or the `property`.
+etc. Notice that bins without any note in them obtain the value of the keyword `missingval`,
+which be default is just `missing`, regardless of the function `f` or the `property`.
 
 If the `property` is `:velocity`, `:pitch`, or `:duration` the function
 behaves exactly as described. The `property` can also be `:position`.
 In this case, the timeseries `ts` contain the timing deviations of the notes
 with respect to the `tvec` vector
 (these numbers are known as *microtiming deviations* in the literature).
 
-If 'segmented = true', the notes are segmented according to the grid in order to
-respect the information of their duration, see [`segment`](@ref).
+If given keyword 'segmented = true', the notes are segmented according to the grid
+in order to respect the information of their duration, see [`segment`](@ref).
 Otherwise the notes are treated as point events with no duration
 (it makes no sense to choose `:duration` with `segmented`).
 """
-function timeseries(notes, property, f, grid; segmented = false)
+function timeseries(notes, property, f, grid; segmented = false, missingval = missing)
     isgrid(grid)
     if segmented == true
         notes = segment(notes, grid)
@@ -35,7 +35,7 @@ function timeseries(notes, property, f, grid; segmented = false)
         property ∉ (:velocity, :pitch, :duration, :position, :channel)
         error("Unknown property!")
     end
-    ts, tvec, quantizedpos = _init_timeseries_vectors(notes, grid)
+    ts, tvec, quantizedpos = _init_timeseries_vectors(notes, grid, missingval)
     i = previdx = 1; L = length(quantizedpos); M = length(tvec)
     while i ≤ L
         # find entries of same grid bin
@@ -98,7 +98,7 @@ function produce_note_value(notes, property::Nothing, f, i, j)
     val = Float64(f(v))
 end
 
-function _init_timeseries_vectors(notes, grid)
+function _init_timeseries_vectors(notes, grid, missingval)
     tpq = notes.tpq
     qnotes = quantize(notes, grid)
     quantizedpos = positions(qnotes)
@@ -114,6 +114,7 @@ function _init_timeseries_vectors(notes, grid)
         append!(tvec, bins .+ c*tpq)
         c += 1
     end
-    ts = Vector{Union{Float64, Missing}}(undef, length(tvec))
+    ts = Vector{Union{Float64, typeof(missingval)}}(undef, length(tvec))
+    fill!(ts, missingval)
     return ts, tvec, quantizedpos
 end

test/timeseries.jl

@@ -50,6 +50,10 @@ using Statistics, Test, MusicManipulations
     @test count(ismissing, [tseries[i] for i in 2:2:159*2+2]) == 160
     @test count(x -> x isa Float64, [tseries[i] for i in 2:2:159*2+2]) == 0
 
+    tvec, tseries = timeseries(notes, :velocity, mean, grid; missingval = 0.0)
+    @test tseries isa Vector{Float64}
+    @test count(iszero, [tseries[i] for i in 2:2:159*2+2]) == 160
+
 end
 
 @testset "Pitch timeseries" begin