1
0
mirror of synced 2024-11-13 17:10:46 +01:00

Add proper Don/Ka types to clusters of notes (#64)

This should match most fumens. Some exceptional cases I've seen:

- [x] ~In official fumens, even-numbered clusters of 4 notes will
sometimes be ドドドド or カカカカ. Right now, my converter will always use ドドドドン
or カカカカッ, since I don't really understand the rules behind it.~ Fixed:
Now, all 16th notes and above in groups of 4 will no longer use the
don/kat ending character.
- [X] ~In official fumens, sometimes isolated notes will be grouped
together, but sometimes they will be treated as single clusters of 1.
Right now, my converter will always try to cluster isolated notes.~
Fixed: Only 4th/8th/16th/etc. notes will be clustered. Whole/half notes
will not be clustered.
- [x] ~Right now, my logic always treats big notes as their own cluster.
But, sometimes you get a cluster like `ddddD`, and right now my
converter treats this as (ドドドドン) + big DON instead of do-ko-do-ko-DON.~
Fixed: Now big notes are included in clusters.
- [x] ~For high-level Oni songs with complex groups of dense notes (e.g.
(12th/16th/24th) notes mixed with (16th/34th/32nd) notes), official
fumens seem to group them together even though they technically have
different timings. Right now, my converter will group the 32nd notes,
but treat the 16th notes as their own separate group.~ Fixed: Now
anything above an 8th note will be clustered together.
- [X] Songs with BPM gimmicks. e.g. the TJA has low base BPM, but then
everything is doubled/tripled except for one section. I can't remember
which songs have this? Something like RNG Cinderella?
- Maybe solved by
1f640c1aa1?

Fixes #41.
This commit is contained in:
Viv 2024-02-03 22:32:29 -05:00 committed by GitHub
parent 47ef31fc5c
commit 073178601f
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
5 changed files with 229 additions and 14 deletions

View File

@ -4,11 +4,12 @@ Entry points for tja2fumen.
import argparse
import os
import shutil
import sys
from typing import Sequence
from tja2fumen.parsers import parse_tja
from tja2fumen.converters import convert_tja_to_fumen
from tja2fumen.parsers import parse_tja, parse_fumen
from tja2fumen.converters import convert_tja_to_fumen, fix_dk_note_types_course
from tja2fumen.writers import write_fumen
from tja2fumen.constants import COURSE_IDS
from tja2fumen.classes import TJACourse
@ -18,10 +19,14 @@ def main(argv: Sequence[str] = ()) -> None:
"""
Main entry point for tja2fumen's command line interface.
Three steps are performed:
1. Parse TJA into multiple TJACourse objects. Then, for each course:
tja2fumen can be used in 2 ways:
- If a .tja file is provided, then three steps are performed:
1. Parse TJA into multiple TJACourse objects. Then, for each course:
2. Convert TJACourse objects into FumenCourse objects.
3. Write each FumenCourse to its own .bin file.
- If a .bin file is provided, then the existing .bin is repaired:
1. Update don/kat senote types to do-ko-don and ka-kat.
"""
if not argv:
argv = sys.argv[1:]
@ -30,20 +35,27 @@ def main(argv: Sequence[str] = ()) -> None:
description="tja2fumen"
)
parser.add_argument(
"file.tja",
help="Path to a Taiko no Tatsujin TJA file.",
"file",
help="Path to a Taiko no Tatsujin chart file.",
)
args = parser.parse_args(argv)
fname_tja = getattr(args, "file.tja")
base_name = os.path.splitext(fname_tja)[0]
fname = getattr(args, "file")
base_name = os.path.splitext(fname)[0]
# Parse lines in TJA file
parsed_tja = parse_tja(fname_tja)
if fname.endswith(".tja"):
print("Converitng TJA to fumen files...")
# Parse lines in TJA file
parsed_tja = parse_tja(fname)
# Convert parsed TJA courses and write each course to `.bin` files
for course_name, course in parsed_tja.courses.items():
convert_and_write(course, course_name, base_name,
single_course=len(parsed_tja.courses) == 1)
# Convert parsed TJA courses and write each course to `.bin` files
for course_name, course in parsed_tja.courses.items():
convert_and_write(course, course_name, base_name,
single_course=len(parsed_tja.courses) == 1)
elif fname.endswith(".bin"):
print("Repairing existing fumen file...")
repair_bin(fname)
else:
raise ValueError(f"Unexpected file extension: {fname}")
def convert_and_write(tja_data: TJACourse,
@ -52,6 +64,8 @@ def convert_and_write(tja_data: TJACourse,
single_course: bool = False) -> None:
"""Process the parsed data for a single TJA course."""
fumen_data = convert_tja_to_fumen(tja_data)
# fix don/ka types
fix_dk_note_types_course(fumen_data)
# Add course ID (e.g. '_x', '_x_1', '_x_2') to the output file's base name
output_name = base_name
if single_course:
@ -64,6 +78,16 @@ def convert_and_write(tja_data: TJACourse,
write_fumen(f"{output_name}.bin", fumen_data)
def repair_bin(fname_bin: str) -> None:
"""Repair the don/ka types of an existing .bin file."""
fumen_data = parse_fumen(fname_bin)
# fix don/ka types
fix_dk_note_types_course(fumen_data)
# write repaired fumen
shutil.move(fname_bin, fname_bin+".bak")
write_fumen(fname_bin, fumen_data)
# NB: This entry point is necessary for the Pyinstaller executable
if __name__ == "__main__":
main()

View File

@ -82,6 +82,8 @@ class FumenNote:
"""Contains all the byte values for a single Fumen note."""
note_type: str = ''
pos: float = 0.0
pos_abs: float = 0.0
diff: int = 0
score_init: int = 0
score_diff: int = 0
padding: float = 0.0

View File

@ -8,6 +8,7 @@ from typing import List, Dict, Tuple, Union
from tja2fumen.classes import (TJACourse, TJAMeasure, TJAMeasureProcessed,
FumenCourse, FumenHeader, FumenMeasure,
FumenNote)
from tja2fumen.constants import BRANCH_NAMES
def process_commands(tja_branches: Dict[str, List[TJAMeasure]], bpm: float) \
@ -410,3 +411,152 @@ def convert_tja_to_fumen(tja: TJACourse) -> FumenCourse:
int(65536 * (total_notes['normal'] / total_notes['master']))
return fumen
def fix_dk_note_types_course(fumen: FumenCourse) -> None:
"""
Call `fix_dk_note_types` once per branch on a FumenCourse.
"""
# try to determine the song's BPM from its measures
measure_bpms = [m.bpm for m in fumen.measures]
unique_bpms = set(measure_bpms)
song_bpm = max(unique_bpms, key=measure_bpms.count)
# collect the d/k notes for each branch, then fix their types
for branch_name in BRANCH_NAMES:
dk_notes = []
for measure in fumen.measures:
for note in measure.branches[branch_name].notes:
if any(note.note_type.lower().startswith(t)
for t in ['don', 'ka']):
note.pos_abs = (measure.offset_start + note.pos +
(4 * 60_000 / measure.bpm))
dk_notes.append(note)
if dk_notes:
fix_dk_note_types(dk_notes, song_bpm)
def fix_dk_note_types(dk_notes: List[FumenNote], song_bpm: float) -> None:
"""
Cluster Don/Ka notes based on their relative positions, then replace
Don/Ka notes with alternate versions (Don2, Don3, Ka2).
NB: Modifies FumenNote objects in-place
"""
# Sort the notes by their absolute positions to account for BPMCHANGE
dk_notes = sorted(dk_notes, key=lambda note: note.pos_abs)
# Get the differences between each note and the previous one
for (note_1, note_2) in zip(dk_notes, dk_notes[1:]):
note_1.diff = int(note_2.pos_abs - note_1.pos_abs)
# Isolate the unique difference values and sort them
diffs_unique = sorted(list({note.diff for note in dk_notes}))
# Avoid clustering any whole notes, half notes, or quarter notes
# i.e. only cluster 8th notes, 16th notes, etc.
measure_duration = (4 * 60_000) / song_bpm
quarter_note_duration = int(measure_duration / 4)
diffs_under_quarter: List[int] = [diff for diff in diffs_unique
if diff < quarter_note_duration]
# Anything above an 8th note (12th, 16th, 24th, 36th, etc...) should be
# clustered together as a single stream
diffs_to_cluster: List[List[int]] = []
diffs_under_8th: List[int] = []
eighth_note_duration = int(measure_duration / 8)
for diff in diffs_under_quarter:
if diff < eighth_note_duration:
diffs_under_8th.append(diff)
else:
diffs_to_cluster.append([diff])
# Make sure to cluster the close-together notes first
if diffs_under_8th:
diffs_to_cluster.insert(0, diffs_under_8th)
# Cluster the notes from the smallest difference to the largest
semi_clustered: List[Union[FumenNote, List[FumenNote]]] = list(dk_notes)
for diff_vals in diffs_to_cluster:
semi_clustered = cluster_notes(semi_clustered, diff_vals)
# Turn any remaining isolated notes into clusters (i.e. long diffs)
clustered_notes = [cluster if isinstance(cluster, list) else [cluster]
for cluster in semi_clustered]
# In each cluster, replace dons/kas with their alternate versions
replace_alternate_don_kas(clustered_notes, eighth_note_duration)
def replace_alternate_don_kas(note_clusters: List[List[FumenNote]],
eighth_note_duration: int) -> None:
"""
Replace Don/Ka notes with alternate versions (Don2, Don3, Ka2) based on
positions within a cluster of notes.
NB: Modifies FumenNote objects in-place
"""
big_notes = ['DON', 'DON2', 'KA', 'KA2']
for cluster in note_clusters:
# Replace all small notes with the basic do/ka notes ("Don2", "Ka2")
for note in cluster:
if note.note_type not in big_notes:
if note.note_type[-1].isdigit():
note.note_type = note.note_type[:-1] + "2"
else:
note.note_type += "2"
# The "ko" type of Don note only occurs every other note, and only
# in odd-length all-don runs (DDD: Do-ko-don, DDDDD: Do-ko-do-ko-don)
all_dons = all(note.note_type.startswith("Don") for note in cluster)
for i, note in enumerate(cluster):
if (all_dons and (len(cluster) % 2 == 1) and (i % 2 == 1)
and note.note_type not in big_notes):
note.note_type = "Don3"
# Replace the last note in a cluster with the ending Don/Kat
# In other words, remove the '2' from the last note.
# However, there's one exception: Groups of 4 notes, faster than 8th
is_fast_cluster_of_4 = (len(cluster) == 4 and
all(note.diff < eighth_note_duration
for note in cluster[:-1]))
if is_fast_cluster_of_4:
# Leave last note as Don2/Ka2
pass
else:
# Replace last Don2/Ka2 with Don/Ka
if cluster[-1].note_type not in big_notes:
cluster[-1].note_type = cluster[-1].note_type[:-1]
def cluster_notes(item_list: List[Union[FumenNote, List[FumenNote]]],
cluster_diffs: List[int]) \
-> List[Union[FumenNote, List[FumenNote]]]:
"""Group notes based on the differences between them."""
clustered_notes: List[Union[FumenNote, List[FumenNote]]] = []
current_cluster: List[FumenNote] = []
for item in item_list:
# If we encounter an already-clustered group of items, the current
# cluster should end
if isinstance(item, list):
if current_cluster:
clustered_notes.append(current_cluster)
current_cluster = []
clustered_notes.append(item)
# Handle values that haven't been clustered yet
else:
assert isinstance(item, FumenNote)
# Start and/or continue the current cluster
if any(item.diff == diff for diff in cluster_diffs):
current_cluster.append(item)
else:
# Finish the existing cluster
if current_cluster:
current_cluster.append(item)
clustered_notes.append(current_cluster)
current_cluster = []
# Or, if there is no cluster, append the item
else:
clustered_notes.append(item)
if current_cluster:
clustered_notes.append(current_cluster)
return clustered_notes

View File

@ -156,6 +156,12 @@ def split_tja_lines_into_courses(lines: List[str]) -> TJASong:
if not v.data]:
del parsed_tja.courses[course_name]
# Recreate dict with consistent insertion order
parsed_tja.courses = {
key: parsed_tja.courses[key] for key
in sorted(parsed_tja.courses.keys())
}
return parsed_tja

View File

@ -10,6 +10,39 @@ from conftest import convert
from tja2fumen.parsers import parse_fumen
@pytest.mark.skipif("CI" in os.environ,
reason="Test is only for local debugging")
def test_converted_tja_no_comparison(tmp_path, entry_point):
"""
A test purely to aid with debugging. It lets me drop a .tja into a
pre-determined folder and run the conversion, allowing me to set
breakpoints and debug internal state without any tedious setup.
"""
# Define the testing directory
path_test = os.path.dirname(os.path.realpath(__file__))
path_test = os.path.join(path_test, "data", "unpaired_tjs")
for fname in os.listdir(path_test):
# Copy input TJA to working directory
path_tja = os.path.join(path_test, fname)
path_tja_tmp = os.path.join(tmp_path, fname)
shutil.copy(path_tja, path_tja_tmp)
# Convert TJA file to fumen files
convert(path_test, path_tja_tmp, entry_point)
# Fetch output fumen paths
paths_out = glob.glob(os.path.join(tmp_path, "*.bin"))
assert paths_out, f"No bin files generated in {tmp_path}"
order = "xmhne" # Ura Oni -> Oni -> Hard -> Normal -> Easy
paths_out = sorted(paths_out,
key=lambda s: [order.index(c) if c in order
else len(order) for c in s])
for path_out in paths_out:
difficulty = os.path.basename(path_out).split(".")[0].split("_")[1]
song = parse_fumen(path_out, exclude_empty_measures=False)
print(f"{difficulty}: {len(song.measures)}")
@pytest.mark.parametrize('id_song', [
pytest.param('butou5'),
pytest.param('shoto9',