maia-markov
Version:
Markov analysis and generation functions supporting various applications by Music Artificial Intelligence Algorithms, Inc.
342 lines (314 loc) • 11.4 kB
JavaScript
// Requires
const argv = require('minimist')(process.argv.slice(2))
const path = require("path")
const mu = require("maia-util")
const mm = require('../dist/index')
const an = new mm.Analyzer()
const gn = new mm.Generator()
const fs = require("fs")
const { Midi } = require('@tonejs/midi')
const sr = require('seed-random')
// const seed = "hello683482"
// sr(seed, {global: true})
const mainPaths = {
"tom": {
"inStm": path.join(
"/Users", "tomthecollins", "Shizz", "York", "Students", "Chenyu\ Gao",
"markov_infilling", "pop_909_train.json"
)
},
"chenyu": {
"inStm": "/Users/gaochenyu/Codes/markov_out/pop909_train.json",
"midi": path.join(
"/Users/gaochenyu/Dataset/POP909_with_structure_labels/29thSep2023_theme_var_extracted_for_training"),
"midiDir": "test",
"themeSample": ["002_A_0.mid", "052_B_0.mid", "597_A_0.mid", "623_A_0.mid", "866_A_0.mid"],
"sclPath": "/Users/gaochenyu/Codes/markov_out",
"sclName": "pop909_train_scl.json",
"outputDir": path.join(
"/Users/gaochenyu/Codes/markov_out/out_midi/markov_909"
),
}
}
let param = {
"stateType": "beat_rel_sq_MNN_state",
"pointReconstruction": "rel_sq_MNN",
"timeSignatures": [ {"barNo": 1, "topNo": 4, "bottomNo": 4, "ontime": 0} ],
"stm": null,
"initial": null,
"nosConsecutives": 4,
"ontimeUpperLimit": 16,
"squashRangeMidiMorph": [12, 7],
"indices": {
"ontime": 0, "MNN": 1, "MPN": 2, "duration": 3, "channel": 4, "velocity": 5
},
"randCount": 0,
"midiExport": {
"scaleFactor": 0.5,
"timeSigTopNo": 4,
"timeSigBottomNo": 4,
"noteIndices": {
"ontimeIndex": 0,
"mnnIndex": 1,
"durationIndex": 3,
"channelIndex": 4,
"velocityIndex": 5
},
"ccIndices": {
"ontimeIndex": 0,
"numberIndex": 1,
"channelIndex": 2,
"valueIndex": 3
}
},
"downbeat": {
"histType": "drumsFalseVelocityTrue",
"drumsOnly": false,
"rounding": true,
"granularity": 4,
"beatsInMeasure": 4,
"velocityIndex": 4,
"ontimeIndex": 0
},
"ontimeIndex": 0,
"noteIndices": {
"ontimeIndex": 0,
"mnnIndex": 1,
"durationIndex": 3,
"channelIndex": 4,
"velocityIndex": 5
},
"controlChanges": null,
"scaleFactor": 0.5,
"timeSigtopNo": 4,
"timeSigBottomNo": 4
}
// Grab user name from command line to set path to stm.
const mainPath = mainPaths[argv.u]
const dataEx = require(mainPath["inStm"])
// console.log("dataEx[4]['continuations']:", dataEx[4]["continuations"])
// const ans = count_continuations(dataEx[4]["continuations"], "beat_rel_sq_MNN_state")
// console.log("ans:", ans)
// Deduplicate a particular property of the continuations array, convert the
// numeric arrays to strings, use the counting performed during deduplication
// to provide distances between states, and return ready for loading onto a
// graph.
const dataExStr = dataEx.map(function(st){
// Get count of continuations.
const contnCount = count_continuations(st.continuations, "beat_rel_sq_MNN_state")
const contnAndDist = contnCount[0].map(function(contn, idx){
return {
"beat_rel_sq_MNN_state": an.state2string(contn),
"dist": 1/contnCount[1][idx]
}
})
return {
"beat_rel_sq_MNN_state": an.state2string(st.beat_rel_sq_MNN_state),
"continuations": contnAndDist
}
})
console.log("dataEx.length", dataEx.length)
// const dataExStr = dataEx.map(function(st){
// return {
// "beat_rel_sq_MNN_state": an.state2string(st.beat_rel_sq_MNN_state),
// "continuations":st.continuations.map(function(con){
// return {
// "beat_rel_sq_MNN_state": an.state2string(con.beat_rel_sq_MNN_state),
// "context": con.context
// }
// })
// }
// })
// console.log("dataExStr[4]['continuations']:", dataExStr[4]["continuations"])
let g = new mm.Graph(dataExStr, "beat_rel_sq_MNN_state", "continuations", "dist")
// let g = new mm.Graph()
// dataExStr.map(function(d){
// d.continuations.map(function(nb){
// g.add_edge(d.beat_rel_sq_MNN_state, nb.beat_rel_sq_MNN_state, 1)
// })
// })
// console.log("g", g.vertexMap['3|-5,-1,2'].nbs)
// const path2 = g.print_scenic_path("2.5|-5,-1,2", "1.5|-8,-1,11", 0.5)
// // const path2 = g.print_scenic_path("2.5|-5,-1,2", "2.5|-5,-1,2", 0.5)
// // const path2 = g.print_scenic_path("1.75|-12,-7,0,4", "1.5|-12,0,2", 0.1)
// console.log("path2:", path2)
// Trying to run the code over all themes in the test set, and check if there is any output.
let midiDirs = fs.readdirSync(path.join(mainPath["midi"], mainPath["midiDir"]))
// Filter out themes in the testing set.
midiDirs = midiDirs.filter(function(fnam){
let tmpSongNumber = fnam.split(".")[0]
let splitSongNumber = tmpSongNumber.split("_")
tmpSongNumber = splitSongNumber[splitSongNumber.length-1]
if(path.extname(fnam) === ".mid" && tmpSongNumber === "0"){
return true
}
})
// Filter MIDIs in ['themeSample']
midiDirs = midiDirs.filter(function(midiDir){
return mainPath["themeSample"].indexOf(midiDir) >= 0
})
// console.log(midiDirs)
midiDirs.slice(0,2)
.forEach(function(midiDir, jDir){
// Obtain states from a theme.
console.log("midiDir", midiDir)
const midiData = fs.readFileSync(
path.join(mainPath["midi"], mainPath["midiDir"], midiDir)
)
const midi = new Midi(midiData)
console.log("midi.header", midi.header)
const tmp_bpm = midi.header.tempos
const timeSigs = [{"barNo": 1, "topNo": 4, "bottomNo": 4, "ontime": 0}]
if (timeSigs[0].topNo !== 4){
console.log("timeSigs:", timeSigs)
}
let allPoints = []
midi.tracks.forEach(function(track, idx){
const trgTestStr = track.instrument.family + " -> " + track.instrument.name
console.log("trgTestStr:", trgTestStr)
// console.log("track.instrument.family:", track.instrument.family)
// console.log("track.instrument.name:", track.instrument.name)
track.notes.forEach(function(n){
let pt = [
n.ticks/midi.header.ppq,
n.midi,
n.durationTicks/midi.header.ppq,
track.channel,
Math.round(1000*n.velocity)/1000
]
allPoints.push(pt)
})
})
// Key detection
const fsm = mu.fifth_steps_mode(allPoints, mu.krumhansl_and_kessler_key_profiles)
// console.log("fsm:", fsm)
allPoints.forEach(function(p){
p.splice(2, 0, mu.guess_morphetic(p[1], fsm[2], fsm[3]))
})
let comp = an.note_point_set2comp_obj(
allPoints, timeSigs, false, [0, 1/4, 1/3, 1/2, 2/3, 3/4, 1]//, [0, 1/6, 1/4, 1/3, 1/2, 2/3, 3/4, 5/6, 1]
)
let current_state = an.comp_obj2beat_rel_sq_mnn_states(comp)
// console.log("current_state", current_state)
// Perhaps we could try to obtain the beginning and the end states of each measure,
// and try to find scenic_path().
let beg_idx = 0
let end_idx = 0
let full_sc_pair = []
for(let i = 0; i < current_state.length; i ++){
if(i === current_state.length-1){
end_idx = i
const beginning_state = an.state2string(current_state[beg_idx].beat_rel_sq_MNN_state)
const end_state = an.state2string(current_state[end_idx].beat_rel_sq_MNN_state)
const path3 = g.print_scenic_path(beginning_state, end_state, 0.5)
// console.log("path3", path3)
if(path3 !== undefined){
const sc_pair = path2sc_pairs(path3, mainPath['sclName'])
full_sc_pair.push(current_state[beg_idx])
for(let j = 1; j < sc_pair.length - 1; j ++){
full_sc_pair.push(sc_pair[j])
}
full_sc_pair.push(current_state[end_idx])
}
else{
for(let j = beg_idx; j <= end_idx; j ++){
full_sc_pair.push(current_state[j])
}
}
}
else if(current_state[i+1].beat_rel_sq_MNN_state[0]<current_state[i].beat_rel_sq_MNN_state[0]){
end_idx = i
const beginning_state = an.state2string(current_state[beg_idx].beat_rel_sq_MNN_state)
const end_state = an.state2string(current_state[end_idx].beat_rel_sq_MNN_state)
const path3 = g.print_scenic_path(beginning_state, end_state, 0.5)
// console.log("path3", path3)
if(path3 !== undefined){
const sc_pair = path2sc_pairs(path3, mainPath['sclName'])
full_sc_pair.push(current_state[beg_idx])
for(let j = 1; j < sc_pair.length - 1; j ++){
full_sc_pair.push(sc_pair[j])
}
full_sc_pair.push(current_state[end_idx])
}
else{
for(let j = beg_idx; j <= end_idx; j ++){
full_sc_pair.push(current_state[j])
}
}
beg_idx = i + 1
}
}
console.log(full_sc_pair.length)
// // ??? Decimal beat does not exist in 'pop909_train.json'.
// const beginning_state = an.state2string(current_state[0].beat_rel_sq_MNN_state)
// const end_state = an.state2string(current_state[current_state.length-1].beat_rel_sq_MNN_state)
// console.log("Beginning_state", beginning_state)
// console.log("End_state", end_state)
// const path3 = g.print_scenic_path(beginning_state, end_state, 0.5)
// console.log("path3", path3)
// const sc_pair = path2sc_pairs(path3, mainPath['sclName'])
// console.log('sc_pair', sc_pair)
let points = gn.get_points_from_states(full_sc_pair, param)
points = points.map(function(p){
p[param.indices.MNN] += full_sc_pair[0].context.tonic_pitch_closest[0] //60
p[param.indices.MPN] += full_sc_pair[0].context.tonic_pitch_closest[1] //60
p[param.indices.channel] = 0
return p
})
console.log("p", points.slice(0,5))
// Write tempo in MIDI.
const midiOut = new Midi()
let ntracks = 1
const tmp_out_points = points
const tmp_out_bpm = tmp_bpm
for (let i_track = 0; i_track < ntracks; i_track++){
const track = midiOut.addTrack()
track.name = "Piano"
track["channel"] = i_track
tmp_out_points.forEach(function(p){
track.addNote({
midi: p[param.noteIndices.mnnIndex],
time: param.scaleFactor*(p[param.noteIndices.ontimeIndex]),
duration: param.scaleFactor*p[param.noteIndices.durationIndex],
velocity: p[param.noteIndices.velocityIndex]
})
})
}
midiOut.header.tempos = tmp_bpm
const song_name = midiDir.split('.')[0]
fs.writeFileSync(
path.join(mainPath["outputDir"], song_name + "_markovVar" + ".mid"),
new Buffer.from(midiOut.toArray())
)
// const me = new mm.MidiExport(
// points,
// null,
// path.join(mainPath["outputDir"], "pop909_scenic_" + midiDir + ".mid"),
// param.midiExport
// )
// fs.writeFileSync(
// path.join(path.join(mainPath["outputDir"], "pop909_scenic_" + seed + ".txt")),
// JSON.stringify(sc_pair, null, 2)
// )
})
// Other functions.
function count_continuations(contn, stateType){
const states = contn.map(function(c){ return c[stateType] })
return mu.count_rows(states, undefined, true)
}
function path2sc_pairs(pathArr, sclFnam){
// Loading sclFile.
const sclData = require(path.join(mainPath["sclPath"], sclFnam))
let sc_pairs = []
// Select one object randomly from "context"
pathArr.forEach(function(p){
let beat_rel_sq_MNN_state = an.string2state(p)
let length_sclData = sclData[p].length
let sel_context = sclData[p][getRandomInt(length_sclData)]
sc_pairs.push({"beat_rel_sq_MNN_state": beat_rel_sq_MNN_state, "context": sel_context})
})
return sc_pairs
}
function getRandomInt(max) {
return Math.floor(Math.random() * max);
}