101 lines
4.9 KiB
Python
101 lines
4.9 KiB
Python
import os
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import shutil
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import zipfile
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import re
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import pytest
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from tja2fumen import main as convert
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from tja2fumen.parsers import readFumen
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from tja2fumen.constants import COURSE_IDS, NORMALIZE_COURSE
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def normalize_type(note_type):
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return re.sub(r'[0-9]', '', note_type)
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def assert_song_property(obj1, obj2, 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.
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# So, we increment 1 in the error message to more easily identify problematic lines in TJA files.
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msg_failure = f"'{prop}' mismatch"
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msg_failure += f": measure '{measure+1}'" if measure is not None else ""
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msg_failure += f", branch '{branch}'" if branch is not None else ""
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msg_failure += f", note '{note+1}'" if note is not None else ""
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if func:
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assert func(obj1[prop]) == func(obj2[prop]), msg_failure
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elif abs:
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assert obj1[prop] == pytest.approx(obj2[prop], abs=abs), msg_failure
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else:
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assert obj1[prop] == obj2[prop], msg_failure
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@pytest.mark.parametrize('id_song', ['mikdp'])
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def test_converted_tja_vs_cached_fumen(id_song, tmp_path):
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# Define the testing directory
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path_test = os.path.dirname(os.path.realpath(__file__))
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# Define the working directory
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path_temp = os.path.join(tmp_path, id_song)
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os.mkdir(path_temp)
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# Copy input TJA to working directory
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path_tja = os.path.join(path_test, "data", f"{id_song}.tja")
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path_tja_tmp = os.path.join(path_temp, f"{id_song}.tja")
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shutil.copy(path_tja, path_tja_tmp)
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# Convert TJA file to fumen files
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_, _, paths_out = convert(argv=[path_tja_tmp])
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# Extract cached fumen files to working directory
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path_binzip = os.path.join(path_test, "data", f"{id_song}.zip")
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path_bin = os.path.join(path_temp, "ca_bins")
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with zipfile.ZipFile(path_binzip, 'r') as zip_ref:
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zip_ref.extractall(path_bin)
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# Compare cached fumen with generated fumen
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for path_out in paths_out:
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# Difficulty introspection to help with debugging
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i_difficult_id = os.path.basename(path_out).split(".")[0].split("_")[1]
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i_difficulty = NORMALIZE_COURSE[{v: k for k, v in COURSE_IDS.items()}[i_difficult_id]] # noqa
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# 0. Read fumen data (converted vs. cached)
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co_song = readFumen(path_out)
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ca_song = readFumen(os.path.join(path_bin, os.path.basename(path_out)))
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# 1. Check song headers
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assert_song_property(co_song, ca_song, 'header', func=len)
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assert_song_property(co_song, ca_song, 'headerUnknown', func=len)
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# 2. Check song metadata
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assert_song_property(co_song, ca_song, 'order')
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assert_song_property(co_song, ca_song, 'branches')
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assert_song_property(co_song, ca_song, 'scoreInit')
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assert_song_property(co_song, ca_song, 'scoreDiff')
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assert_song_property(co_song, ca_song, 'length')
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assert_song_property(co_song, ca_song, 'measures', func=len)
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# 3. Check measure data
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for i_measure, (co_measure, ca_measure) in enumerate(zip(co_song['measures'], ca_song['measures'])):
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# 3a. Check measure metadata
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assert_song_property(co_measure, ca_measure, 'bpm', i_measure, abs=0.01)
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assert_song_property(co_measure, ca_measure, 'fumenOffset', i_measure, abs=0.5)
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assert_song_property(co_measure, ca_measure, 'gogo', i_measure)
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assert_song_property(co_measure, ca_measure, 'barline', i_measure)
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# 3b. Check measure notes
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for i_branch in ['normal', 'advanced', 'master']:
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co_branch = co_measure[i_branch]
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ca_branch = ca_measure[i_branch]
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assert_song_property(co_branch, ca_branch, 'length', i_measure, i_branch)
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# NB: We check for branching before checking speed as fumens store speed changes even for empty branches
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if co_branch['length'] == 0:
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continue
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assert_song_property(co_branch, ca_branch, 'speed', i_measure, i_branch)
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for i_note in range(co_branch['length']):
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co_note = co_branch[i_note]
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ca_note = ca_branch[i_note]
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assert_song_property(co_note, ca_note, 'type', i_measure, i_branch, i_note, func=normalize_type)
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assert_song_property(co_note, ca_note, 'pos', i_measure, i_branch, i_note, abs=0.1)
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# NB: Drumroll duration doesn't always end exactly on a beat. So, use a larger tolerance.
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assert_song_property(co_note, ca_note, 'duration', i_measure, i_branch, i_note, abs=10.0)
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if ca_note['type'] not in ["Balloon", "Kusudama"]:
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assert_song_property(co_note, ca_note, 'scoreInit', i_measure, i_branch, i_note)
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assert_song_property(co_note, ca_note, 'scoreDiff', i_measure, i_branch, i_note)
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# assert_song_property(co_note, ca_note, 'item', i_measure, i_branch, i_note)
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