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tja2fumen/testing/test_conversion.py

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import os
import shutil
import zipfile
import re
import glob
import pytest
from tja2fumen import main as convert
from tja2fumen.parsers import read_fumen
from tja2fumen.constants import COURSE_IDS, NORMALIZE_COURSE
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@pytest.mark.parametrize('id_song', [
pytest.param('shoto9', marks=pytest.mark.skip("TJA structure does not match fumen yet.")),
pytest.param('genpe'),
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pytest.param('gimcho'),
pytest.param('imcanz'),
pytest.param('clsca'),
pytest.param('linda'),
pytest.param('senpac'),
pytest.param('butou5'),
pytest.param('hol6po'),
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pytest.param('mikdp'),
pytest.param('ia6cho'),
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])
def test_converted_tja_vs_cached_fumen(id_song, tmp_path, entry_point):
# Define the testing directory
path_test = os.path.dirname(os.path.realpath(__file__))
# Define the working directory
path_temp = os.path.join(tmp_path, id_song)
os.mkdir(path_temp)
# Copy input TJA to working directory
path_tja = os.path.join(path_test, "data", f"{id_song}.tja")
path_tja_tmp = os.path.join(path_temp, f"{id_song}.tja")
shutil.copy(path_tja, path_tja_tmp)
# Convert TJA file to fumen files
if entry_point == "python-api":
convert(argv=[path_tja_tmp])
elif entry_point == "python-cli":
os.system(f"tja2fumen {path_tja_tmp}")
elif entry_point == "exe":
exe_path = glob.glob(os.path.join(os.path.split(path_test)[0], "dist", "*.exe"))[0]
os.system(f"{exe_path} {path_tja_tmp}")
# Fetch output fumen paths
paths_out = glob.glob(os.path.join(path_temp, "*.bin"))
assert paths_out, f"No bin files generated in {path_temp}"
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])
# Extract cached fumen files to working directory
path_binzip = os.path.join(path_test, "data", f"{id_song}.zip")
path_bin = os.path.join(path_temp, "ca_bins")
with zipfile.ZipFile(path_binzip, 'r') as zip_ref:
zip_ref.extractall(path_bin)
# Compare cached fumen with generated fumen
for path_out in paths_out:
# Difficulty introspection to help with debugging
i_difficult_id = os.path.basename(path_out).split(".")[0].split("_")[1]
i_difficulty = NORMALIZE_COURSE[{v: k for k, v in COURSE_IDS.items()}[i_difficult_id]] # noqa
# 0. Read fumen data (converted vs. cached)
co_song = read_fumen(path_out, exclude_empty_measures=True)
ca_song = read_fumen(os.path.join(path_bin, os.path.basename(path_out)), exclude_empty_measures=True)
# 1. Check song headers
checkValidHeader(co_song.header)
checkValidHeader(ca_song.header)
assert_song_property(co_song.header, ca_song.header, 'order')
assert_song_property(co_song.header, ca_song.header, 'b432_b435_has_branches')
assert_song_property(co_song.header, ca_song.header, 'b436_b439_hp_max')
assert_song_property(co_song.header, ca_song.header, 'b440_b443_hp_clear')
assert_song_property(co_song.header, ca_song.header, 'b444_b447_hp_gain_good', abs=1)
assert_song_property(co_song.header, ca_song.header, 'b448_b451_hp_gain_ok', abs=1)
assert_song_property(co_song.header, ca_song.header, 'b452_b455_hp_loss_bad', abs=1)
assert_song_property(co_song.header, ca_song.header, 'b456_b459_normal_normal_ratio')
assert_song_property(co_song.header, ca_song.header, 'b460_b463_normal_professional_ratio')
assert_song_property(co_song.header, ca_song.header, 'b464_b467_normal_master_ratio')
# Ignore branch points for now to focus on HP bytes
# assert_song_property(co_song.header, ca_song.header, 'b468_b471_branch_points_good')
# assert_song_property(co_song.header, ca_song.header, 'b472_b475_branch_points_ok')
# assert_song_property(co_song.header, ca_song.header, 'b476_b479_branch_points_bad')
# assert_song_property(co_song.header, ca_song.header, 'b480_b483_branch_points_drumroll')
# assert_song_property(co_song.header, ca_song.header, 'b484_b487_branch_points_good_big')
# assert_song_property(co_song.header, ca_song.header, 'b488_b491_branch_points_ok_big')
# assert_song_property(co_song.header, ca_song.header, 'b492_b495_branch_points_drumroll_big')
# assert_song_property(co_song.header, ca_song.header, 'b496_b499_branch_points_balloon')
# assert_song_property(co_song.header, ca_song.header, 'b500_b503_branch_points_kusudama')
# 2. Check song metadata
assert_song_property(co_song, ca_song, 'score_init')
assert_song_property(co_song, ca_song, 'score_diff')
# 3. Check measure data
for i_measure in range(max([len(co_song.measures), len(ca_song.measures)])):
# NB: We could assert that len(measures) is the same for both songs, then iterate through zipped measures.
# But, if there is a mismatched number of measures, we want to know _where_ it occurs. So, we let the
# comparison go on using the max length of both songs until something else fails.
co_measure = co_song.measures[i_measure]
ca_measure = ca_song.measures[i_measure]
# 3a. Check measure metadata
assert_song_property(co_measure, ca_measure, 'bpm', i_measure, abs=0.01)
assert_song_property(co_measure, ca_measure, 'fumen_offset_start', i_measure, abs=0.15)
assert_song_property(co_measure, ca_measure, 'gogo', i_measure)
assert_song_property(co_measure, ca_measure, 'barline', i_measure)
# NB: KAGEKIYO's fumen has some strange details that can't be replicated using the TJA charting format.
# So, for now, we use a special case to skip checking A) notes for certain measures and B) branchInfo
if id_song == 'genpe':
# A) The 2/4 measures in the Ura of KAGEKIYO's official Ura fumen don't match the wikiwiki.jp/TJA
# charts. In the official fumen, the note ms offsets of branches 5/12/17/etc. go _past_ the duration of
# the measure. This behavior is impossible to represent using the TJA format, so we skip checking notes
# for these measures, since the rest of the measures have perfect note ms offsets anyway.
if i_difficult_id == "x" and i_measure in [5, 6, 12, 13, 17, 18, 26, 27, 46, 47, 51, 52, 56, 57]:
continue
# B) The branching condition for KAGEKIYO is very strange (accuracy for the 7 big notes in the song)
# So, we only test the branchInfo bytes for non-KAGEKIYO songs:
else:
assert_song_property(co_measure, ca_measure, 'branch_info', i_measure)
# 3b. Check measure notes
for i_branch in ['normal', 'advanced', 'master']:
co_branch = co_measure.branches[i_branch]
ca_branch = ca_measure.branches[i_branch]
# NB: We only check speed for non-empty branches, as fumens store speed changes even for empty branches
if co_branch.length != 0:
assert_song_property(co_branch, ca_branch, 'speed', i_measure, i_branch)
# NB: We could assert that len(notes) is the same for both songs, then iterate through zipped notes.
# But, if there is a mismatched number of notes, we want to know _where_ it occurs. So, we let the
# comparison go on using the max length of both branches until something else fails.
for i_note in range(max([co_branch.length, ca_branch.length])):
co_note = co_branch.notes[i_note]
ca_note = ca_branch.notes[i_note]
assert_song_property(co_note, ca_note, 'note_type', i_measure, i_branch, i_note, func=normalize_type)
assert_song_property(co_note, ca_note, 'pos', i_measure, i_branch, i_note, abs=0.1)
# NB: Drumroll duration doesn't always end exactly on a beat. Plus, TJA charters often eyeball
# drumrolls, leading them to be often off by a 1/4th/8th/16th/32th/etc. These charting errors
# are fixable, but tedious to do when writing tests. So, I've added a try/except so that they
# can be checked locally with a breakpoint when adding new songs, but so that fixing every
# duration-related chart error isn't 100% mandatory.
try:
assert_song_property(co_note, ca_note, 'duration', i_measure, i_branch, i_note, abs=25.0)
except AssertionError:
pass
if ca_note.note_type not in ["Balloon", "Kusudama"]:
assert_song_property(co_note, ca_note, 'score_init', i_measure, i_branch, i_note)
assert_song_property(co_note, ca_note, 'score_diff', i_measure, i_branch, i_note)
# NB: 'item' still needs to be implemented: https://github.com/vivaria/tja2fumen/issues/17
# assert_song_property(co_note, ca_note, 'item', i_measure, i_branch, i_note)
def assert_song_property(converted_obj, cached_obj, prop, measure=None, branch=None, note=None, func=None, abs=None):
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# NB: TJA parser/converter uses 0-based indexing, but TJA files use 1-based indexing.
# So, we increment 1 in the error message to more easily identify problematic lines in TJA files.
msg_failure = f"'{prop}' mismatch"
msg_failure += f": measure '{measure+1}'" if measure is not None else ""
msg_failure += f", branch '{branch}'" if branch is not None else ""
msg_failure += f", note '{note+1}'" if note is not None else ""
converted_val = converted_obj.__getattribute__(prop)
cached_val = cached_obj.__getattribute__(prop)
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if func:
assert func(converted_val) == func(cached_val), msg_failure
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elif abs:
assert converted_val == pytest.approx(cached_val, abs=abs), msg_failure
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else:
assert converted_val == cached_val, msg_failure
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def normalize_type(note_type):
return re.sub(r'[0-9]', '', note_type)
def checkValidHeader(header):
assert len(header.raw_bytes) == 520
assert header.b432_b435_has_branches in [0, 1]
assert header.b436_b439_hp_max == 10000
assert header.b440_b443_hp_clear in [6000, 7000, 8000]
assert 10 <= header.b444_b447_hp_gain_good <= 1020
assert 5 <= header.b448_b451_hp_gain_ok <= 1020
assert -765 <= header.b452_b455_hp_loss_bad <= -20
assert header.b456_b459_normal_normal_ratio <= 65536
assert header.b460_b463_normal_professional_ratio <= 65536
assert header.b464_b467_normal_master_ratio <= 65536
assert header.b468_b471_branch_points_good in [20, 0, 1, 2]
assert header.b472_b475_branch_points_ok in [10, 0, 1]
assert header.b476_b479_branch_points_bad == 0
assert header.b480_b483_branch_points_drumroll in [1, 0]
assert header.b484_b487_branch_points_good_big in [20, 0, 1, 2]
assert header.b488_b491_branch_points_ok_big in [10, 0, 1]
assert header.b492_b495_branch_points_drumroll_big in [1, 0]
assert header.b496_b499_branch_points_balloon in [30, 0, 1]
assert header.b500_b503_branch_points_kusudama in [30, 0]