backtransfer_notes.py

import os
import pickle
from simfile.notes import NoteData
from simfile.notes.count import *
import simfile
import torch
from simfile.notes import Note, NoteType, NoteData
from simfile.timing import Beat

# test load file
# decode whole chart
# maybe change up and downs, right lefts/mirror
# encode whole chart
# write back
from preprocess import process_chart

test_file = 'C:/Users/cassi/OneDrive/Desktop/Master_Thesis/testing_sm_overwriting/test_pack/pkg1/110/110.sm'
#test_file_2 = 'C:/Users/cassi/OneDrive/Desktop/Master_Thesis/testing_sm_overwriting/test_pack/pkg1/110/110.ssc'
save_dir = 'C:/Users/cassi/OneDrive/Desktop/Master_Thesis/testing_sm_overwriting/test_pack/pkg_generated/110/'
save_file = f'{save_dir}110 (edit).sm'
#save_file_2 = f'{save_dir}110 (edit).ssc'

os.makedirs(save_dir, exist_ok=True)
# indexed_vocabulary_path = 'C:/Users/cassi/OneDrive/Desktop/Master_Thesis/test_cluster/vocabulary.pkl'
#
# opened_file = simfile.open(f"{test_file}")
#
# with open(f"{test_file}", 'r', encoding="ISO-8859-1") as infile:
#     sm_file = simfile.load(infile)
#
# with open(f'{indexed_vocabulary_path}', 'rb') as fp:
#     indexed_vocabulary = pickle.load(fp)
#
# charts = sm_file.charts
# # get difficulty
# difficulties = []
# # sample notes over time, return list of NoteData and [] if empy (for now)
# converted_charts = []
# charts_per_song = len(charts)
# device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
# max_len_charts = 0
#
# for i, chart in enumerate(charts):
#     notes_per_time = process_chart(opened_file, sm_file, chart, indexed_vocabulary, device)
#     difficulty = chart.meter
#     difficulties.append(int(difficulty))
#     if max_len_charts < len(notes_per_time):
#         max_len_charts = len(notes_per_time)
#     converted_charts.append(notes_per_time)
#
# assert (len(converted_charts) == len(difficulties))
#
# # chart = sm_file.charts[0]
# for chart in charts:
#     note_data = NoteData(chart)
#     cols = note_data.columns
#
#     def mirror(note, cols):
#         return Note(
#             beat=note.beat,
#             column=cols - note.column - 1,
#             note_type=note.note_type,
#         )
#
#     mirrored_notes = (mirror(note, cols) for note in note_data)
#     mirrored_note_data = NoteData.from_notes(mirrored_notes, cols)
#     chart.notes = str(mirrored_note_data)
#
# save_sm_file = sm_file.copy()
# save_sm_file.charts = charts

# with simfile.mutate(
#     test_file,
#     backup_filename=f'{test_file}.old',
# ) as sm_file:
#     charts = sm_file.charts
#
#     for chart in charts:
#         note_data = NoteData(chart)
#         cols = note_data.columns
#
#         def mirror(note, cols):
#             return Note(
#                 beat=note.beat,
#                 column=cols - note.column - 1,
#                 note_type=note.note_type,
#             )
#
#
#         mirrored_notes = (mirror(note, cols) for note in note_data)
#         mirrored_note_data = NoteData.from_notes(mirrored_notes, cols)
#         chart.notes = str(mirrored_note_data)
#     sm_file.charts = charts
#     sm_file.subtitle += '(edited)'

sm_file = simfile.open(test_file, strict=False)
charts = sm_file.charts
#print(charts)
sm_file.subtitle = '(edited)'
new_charts = ''
#sm_file.title = sm_file.title + '(edited)'

print("Original first chart notes:")
print(sm_file.charts[0].notes[100:200])

for i, chart in enumerate(charts):
    note_data = NoteData(chart)
    cols = note_data.columns

    def mirror(note, cols):
        return Note(
            beat=note.beat,
            column=cols - note.column - 1,
            note_type=note.note_type,
        )

    mirrored_notes = (mirror(note, cols) for note in note_data)
    mirrored_note_data = NoteData.from_notes(mirrored_notes, cols)
    sm_file.charts[i].notes = str(mirrored_note_data)

print("Updated first chart notes:")
print(sm_file.charts[0].notes[100:200])

with open(f'{save_file}', 'w', encoding='utf-8') as outfile:
    sm_file.serialize(outfile)


new_sm_file = simfile.open(save_file, strict=False)
print("\n Loaded new first chart notes:")
print(new_sm_file.charts[0].notes[100:200])

# cols = 4
# notes = [
#     Note(beat=Beat(i, 2), column=i%cols, note_type=NoteType.TAP)
#     for i in range(8)
# ]
#
# note_data = NoteData.from_notes(notes, cols)
#
# print(str(note_data))