feedBack/tests/test_gp_autosync_warp.py
Byron Gamatos 92dc321fdf
feat(gp_autosync): piecewise time-warp helpers + refine_sync onset pass (#787)
* feat(gp_autosync): piecewise time-warp helpers + refine_sync onset pass

auto_sync computes per-bar sync points but consumers only ever applied the
scalar bar-1 audio_offset, so any tempo drift between the recording and the
tab's authored tempo accumulated over the song. Add the librosa-free helpers
needed to apply the full piecewise mapping:

- bar_start_times(gp_path): per-bar score times sharing auto_sync's axis
  (GPIF bar-resolution map, GP3/4/5 per-tick integration)
- build_warp_anchors(points, bar_starts): monotonic (score, audio) anchors
- warp_time(t, anchors): piecewise-linear map with edge-slope extrapolation
- warp_song_times(song, warp): retime a lib.song.Song in place (notes,
  sustains, chords, beats, sections, anchors, handshapes, phrase levels,
  tone changes, tempo overrides)
- gp_has_expandable_repeats(gp_path): detects GP3/4/5 repeat/volta/direction
  markup whose playback expansion auto_sync's as-written points cannot map

Also implement refine_sync() — the editor's refine-sync endpoint has imported
it since the snapshot but it never existed in lib, so the Refine button 500'd.
It densifies the DTW points to every Nth bar and re-times each with a local
onset phase sweep (radius clamped under half a beat to avoid one-beat locks,
short scoring grid + median residual snap against the first beats). Synthetic
click-track validation: ~13ms mean / ~40ms max error from ±180ms coarse input
across 117-123 BPM recordings of a 120 BPM tab.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* review: Copilot round 1 — normalize bar_start_times GP3/4/5 parse failures to ValueError, document ImportError

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

---------

Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
2026-07-05 20:08:19 +02:00

285 lines
11 KiB
Python

"""Tests for the librosa-free piecewise time-warp helpers in lib/gp_autosync.py
(bar_start_times / build_warp_anchors / warp_time / warp_song_times /
gp_has_expandable_repeats) plus refine_sync's pure fallbacks.
Fixture-free, matching tests/test_gp_audio_sync.py: every test drives a pure
helper with hand-built inputs (in-memory GPIF zips, synthetic sync points,
hand-rolled Song objects). The librosa-backed sweep inside refine_sync needs
real audio and is covered by manual validation in the PR.
"""
import io
import zipfile
import xml.etree.ElementTree as ET
import pytest
import gp_autosync as ga
from gp8_audio_sync import GpSyncData, SyncPoint
from song import (
Anchor,
Arrangement,
Beat,
Chord,
HandShape,
Note,
Phrase,
PhraseLevel,
Section,
Song,
)
# ── helpers ───────────────────────────────────────────────────────────────────
def _gpif_zip(gpif_xml: str) -> bytes:
"""Build an in-memory .gp container holding the given score.gpif."""
buf = io.BytesIO()
with zipfile.ZipFile(buf, "w") as zf:
zf.writestr("Content/score.gpif", gpif_xml)
return buf.getvalue()
def _gpif(tempo_autos: list[tuple[int, float]], bar_sigs: list[str]) -> str:
autos = "".join(
f"<Automation><Type>Tempo</Type><Bar>{bar}</Bar>"
f"<Value>{bpm} 2</Value></Automation>"
for bar, bpm in tempo_autos
)
bars = "".join(f"<MasterBar><Time>{sig}</Time></MasterBar>" for sig in bar_sigs)
return (
"<GPIF><MasterTrack><Automations>"
f"{autos}</Automations></MasterTrack>"
f"<MasterBars>{bars}</MasterBars></GPIF>"
)
def _sp(bar, t, mod=120.0, orig=120.0):
return SyncPoint(bar=bar, time_secs=t, modified_tempo=mod, original_tempo=orig)
# ── bar_start_times ───────────────────────────────────────────────────────────
def test_bar_start_times_constant_tempo(tmp_path):
# 120 BPM, 4/4 → every bar is exactly 2s
gp = tmp_path / "song.gp"
gp.write_bytes(_gpif_zip(_gpif([(0, 120.0)], ["4/4"] * 4)))
assert ga.bar_start_times(str(gp)) == pytest.approx([0.0, 2.0, 4.0, 6.0])
def test_bar_start_times_tempo_change_and_meter(tmp_path):
# Bar 0-1 at 120 (4/4 → 2s each), bar 2 switches to 60 in 3/4 (3s)
gp = tmp_path / "song.gp"
gp.write_bytes(
_gpif_zip(_gpif([(0, 120.0), (2, 60.0)], ["4/4", "4/4", "3/4", "3/4"]))
)
assert ga.bar_start_times(str(gp)) == pytest.approx([0.0, 2.0, 4.0, 7.0])
# ── build_warp_anchors ────────────────────────────────────────────────────────
def test_build_warp_anchors_maps_bars_to_score_time():
bar_starts = [0.0, 2.0, 4.0, 6.0]
points = [_sp(0, 1.0), _sp(2, 5.4)]
assert ga.build_warp_anchors(points, bar_starts) == [(0.0, 1.0), (4.0, 5.4)]
def test_build_warp_anchors_drops_nonmonotonic_and_out_of_range():
bar_starts = [0.0, 2.0, 4.0, 6.0]
points = [
_sp(0, 1.0),
_sp(1, 0.5), # audio time goes backwards — dropped
_sp(2, 5.4),
_sp(99, 9.9), # bar out of range — dropped
]
assert ga.build_warp_anchors(points, bar_starts) == [(0.0, 1.0), (4.0, 5.4)]
def test_build_warp_anchors_drops_implausible_slopes():
# 2s score bars. A DTW fold (or a run of monotonicity-clamped refine
# points) can produce a near-flat audio segment — slope far below the
# 0.2x plausibility floor — which would crush every bar in the span.
bar_starts = [float(2 * b) for b in range(11)]
points = [
_sp(0, 1.0),
_sp(4, 9.0), # slope 1.0 — kept
_sp(8, 9.1), # slope 0.0125 over 8s of score — dropped
_sp(10, 21.0), # slope 1.0 vs the last KEPT anchor — kept
]
assert ga.build_warp_anchors(points, bar_starts) == [
(0.0, 1.0), (8.0, 9.0), (20.0, 21.0)
]
def test_build_warp_anchors_requires_two_points():
assert ga.build_warp_anchors([_sp(0, 1.0)], [0.0, 2.0]) == []
assert ga.build_warp_anchors([], [0.0, 2.0]) == []
# ── warp_time ─────────────────────────────────────────────────────────────────
def test_warp_time_interpolates_between_anchors():
anchors = [(0.0, 1.0), (10.0, 21.0)] # slope 2, offset 1
assert ga.warp_time(0.0, anchors) == pytest.approx(1.0)
assert ga.warp_time(5.0, anchors) == pytest.approx(11.0)
assert ga.warp_time(10.0, anchors) == pytest.approx(21.0)
def test_warp_time_piecewise_segments():
# First half plays at authored speed, second half at half speed
anchors = [(0.0, 0.0), (10.0, 10.0), (20.0, 30.0)]
assert ga.warp_time(5.0, anchors) == pytest.approx(5.0)
assert ga.warp_time(15.0, anchors) == pytest.approx(20.0)
def test_warp_time_extrapolates_with_edge_slopes():
anchors = [(10.0, 20.0), (20.0, 40.0)] # slope 2
assert ga.warp_time(5.0, anchors) == pytest.approx(10.0) # before first
assert ga.warp_time(25.0, anchors) == pytest.approx(50.0) # after last
def test_warp_time_preserves_order():
anchors = [(0.0, 0.5), (4.0, 4.1), (8.0, 9.3), (12.0, 12.9)]
times = [i * 0.37 for i in range(40)]
warped = [ga.warp_time(t, anchors) for t in times]
assert warped == sorted(warped)
# ── warp_song_times ───────────────────────────────────────────────────────────
def _shifted_double(t):
return 2.0 * t + 1.0
def test_warp_song_times_covers_all_time_fields():
song = Song(
song_length=100.0,
beats=[Beat(time=0.0, measure=1), Beat(time=1.0, measure=-1)],
sections=[Section(name="verse", number=1, start_time=10.0)],
arrangements=[
Arrangement(
name="Lead",
notes=[Note(time=2.0, string=0, fret=3, sustain=1.0)],
chords=[
Chord(
time=4.0,
chord_id=0,
notes=[Note(time=4.0, string=1, fret=2, sustain=0.5)],
)
],
anchors=[Anchor(time=6.0, fret=3)],
hand_shapes=[HandShape(chord_id=0, start_time=4.0, end_time=5.0)],
phrases=[
Phrase(
start_time=0.0,
end_time=8.0,
max_difficulty=0,
levels=[
PhraseLevel(
difficulty=0,
notes=[Note(time=3.0, string=0, fret=0, sustain=2.0)],
)
],
)
],
tones={"base": "clean", "changes": [{"t": 7.0, "name": "lead"}]},
tempos=[{"time": 0.0, "bpm": 120.0}],
)
],
)
ga.warp_song_times(song, _shifted_double)
assert song.song_length == pytest.approx(201.0)
assert [b.time for b in song.beats] == pytest.approx([1.0, 3.0])
assert song.sections[0].start_time == pytest.approx(21.0)
arr = song.arrangements[0]
n = arr.notes[0]
assert n.time == pytest.approx(5.0)
assert n.sustain == pytest.approx(2.0) # (2+1)*2+1 - 5
ch = arr.chords[0]
assert ch.time == pytest.approx(9.0)
assert ch.notes[0].time == pytest.approx(9.0)
assert ch.notes[0].sustain == pytest.approx(1.0)
assert arr.anchors[0].time == pytest.approx(13.0)
hs = arr.hand_shapes[0]
assert (hs.start_time, hs.end_time) == (pytest.approx(9.0), pytest.approx(11.0))
ph = arr.phrases[0]
assert (ph.start_time, ph.end_time) == (pytest.approx(1.0), pytest.approx(17.0))
assert ph.levels[0].notes[0].time == pytest.approx(7.0)
assert ph.levels[0].notes[0].sustain == pytest.approx(4.0)
assert arr.tones["changes"][0]["t"] == pytest.approx(15.0)
assert arr.tempos[0]["time"] == pytest.approx(1.0)
def test_warp_song_times_clamps_negative_sustain():
# A non-monotonic warp callable must not produce negative sustains
song = Song(arrangements=[
Arrangement(name="Lead",
notes=[Note(time=1.0, string=0, fret=0, sustain=1.0)])
])
ga.warp_song_times(song, lambda t: 5.0 - t) # decreasing map
assert song.arrangements[0].notes[0].sustain == 0.0
# ── gp_has_expandable_repeats ─────────────────────────────────────────────────
def test_gpif_files_never_expand_repeats(tmp_path):
# GPIF conversion is single-pass as-written, so .gp/.gpx are always False
gp = tmp_path / "song.gp"
gp.write_bytes(_gpif_zip(_gpif([(0, 120.0)], ["4/4"])))
assert ga.gp_has_expandable_repeats(str(gp)) is False
def test_gp345_unparseable_returns_false(tmp_path):
bad = tmp_path / "song.gp5"
bad.write_bytes(b"not a real gp5 file")
assert ga.gp_has_expandable_repeats(str(bad)) is False
def test_gp345_repeats_detected(tmp_path):
guitarpro = pytest.importorskip("guitarpro")
song = guitarpro.models.Song()
track = guitarpro.models.Track(song)
song.tracks = [track]
# Bar 2 of 3 opens a repeat
for _ in range(2):
header = guitarpro.models.MeasureHeader()
song.addMeasureHeader(header)
song.measureHeaders[1].isRepeatOpen = True
for header in song.measureHeaders:
track.measures.append(guitarpro.models.Measure(track, header))
path = tmp_path / "repeat.gp5"
guitarpro.write(song, str(path))
assert ga.gp_has_expandable_repeats(str(path)) is True
def test_gp345_plain_song_no_repeats(tmp_path):
guitarpro = pytest.importorskip("guitarpro")
song = guitarpro.models.Song()
track = guitarpro.models.Track(song)
song.tracks = [track]
for _ in range(2):
header = guitarpro.models.MeasureHeader()
song.addMeasureHeader(header)
for header in song.measureHeaders:
track.measures.append(guitarpro.models.Measure(track, header))
path = tmp_path / "plain.gp5"
guitarpro.write(song, str(path))
assert ga.gp_has_expandable_repeats(str(path)) is False
# ── refine_sync pure fallbacks ────────────────────────────────────────────────
def test_refine_sync_empty_points_returns_input():
sync = GpSyncData(audio_offset=0.0, audio_asset_id="", sync_points=[])
assert ga.refine_sync(sync, "/nonexistent.ogg") is sync
def test_refine_sync_single_point_returns_input():
# One point → fewer than 2 warp anchors → unchanged, no audio load
sync = GpSyncData(audio_offset=-1.0, audio_asset_id="",
sync_points=[_sp(0, 1.0)])
assert ga.refine_sync(sync, "/nonexistent.ogg") is sync