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NtoNC_HitObjects.py
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NtoNC_HitObjects.py
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"""
© Copyright 2024 krrcream
https://github.com/krrcream/krr-s-osumania-anyKeys-converter/
"""
import os
import hitobject
from functions import *
from hitobject import *
from concurrent.futures import ThreadPoolExecutor
def NtoNC_convert_array(keys, to_keys, blank):
# 初始化一个 [0, 1, 2, ..., keys-1] 的数组
keys_list = list(range(keys))
if keys < to_keys:
add_num = to_keys - keys
add = random.choices(keys_list, k=add_num - blank)
become = 0
add_blank_num = 0
# 将 add 中的数字随机插入到 keys_list 中
iteradd = insert_itertools(keys, add_num - blank)
indices = iteradd()
for i, index in enumerate(indices):
keys_list.insert(index, add[i])
if blank > 0:
if blank + keys <= to_keys:
add_blank_num = blank
else:
add_blank_num = to_keys - keys - blank
become = blank - (to_keys - keys)
if add_blank_num > 0:
keys_list = inserter_m1(keys_list, add_blank_num)
if become > 0:
keys_list = inserter_b1(keys_list, become)
return keys_list
elif keys == to_keys:
return keys_list
elif keys > to_keys:
while len(keys_list) > to_keys:
keys_list = deleter_b1(keys_list, keys - to_keys)
keys_list = inserter_b1(keys_list, blank)
return keys_list
# def NtoNC_convert_array(keys, to_keys, blank): 老办法备份
# # 初始化一个 [0, 1, 2, ..., keys-1] 的数组
# keys_list = list(range(keys))
# if keys + blank < to_keys:
# add_num = to_keys - keys - blank
# add_list = random.choices(keys_list, k=int(add_num))
# # 将 add_list 中的数字随机插入到 keys_list 中
# keys_list = inserter_lst(keys_list, add_list)
# # 插入 blank 个 -1
# keys_list = inserter_m1(keys_list, blank)
# return keys_list
# elif keys + blank == to_keys:
# keys_list = inserter_m1(keys_list, blank)
# return keys_list
# elif keys <= to_keys < keys + blank:
# keys_list = inserter_m1(keys_list, to_keys - keys)
# keys_list = inserter_b1(keys_list, blank + keys - to_keys)
# return keys_list
# elif keys > to_keys: # 从keys_list中在左半边和右半边轮流删除数字，直到长度为to_keys
# while len(keys_list) > to_keys:
# keys_list = deleter_b1(keys_list, keys - to_keys)
# keys_list = inserter_b1(keys_list, blank)
# return keys_list
# def NtoNC_convert_MTX(keys,to_keys,blank, MTX_start_time, Interval=400, different_num_Ratio=0.5):
# convert_MTX = []
# #执行NtoNC_convert_array(keys,to_keys,blank)得到第一个list
# list1 = NtoNC_convert_array(keys,to_keys,blank)
# convert_MTX.append(list1)
# # 从第二个MTX_start_time开始,计算每个start_time减去上一个start_time，得到间隔时间
# time_flag = 0
# for i in range(1,len(MTX_start_time)):
# time_flag += (MTX_start_time[i] - MTX_start_time[i-1])
# # 如果间隔时间小于Interval，则将上一个list复制到当前位置，并加上间隔时间
# if time_flag < Interval:
# convert_MTX.append(convert_MTX[-1])
# else:
# temp = NtoNC_convert_array(keys,to_keys,blank)
# if different_num(temp,convert_MTX[-1]) > to_keys * different_num_Ratio:
# flag = True
# while flag:
# temp = NtoNC_convert_array(keys,to_keys,blank)
# if different_num(temp,convert_MTX[-1]) <= to_keys * different_num_Ratio:
# flag = False
# convert_MTX.append(temp)
# return convert_MTX
# 生成新的class HitObjects:并继承hitobject.py中HitObjects的属性和方法
class NtoNC_HitObjects(hitobject.HitObjects):
def NtoNC_convert_MTX(self, to_keys, blank, Interval=1600, beat_time=400, del_jack_flag=True, density=10,
different_num_ratio=0.5):
keys = self.keys
convert_MTX = []
list1 = NtoNC_convert_array(keys, to_keys, blank)
convert_MTX.append(list1)
time_intervals = [self.MTX_start_time[i] - self.MTX_start_time[i - 1] for i in
range(1, len(self.MTX_start_time))]
time_flag = 0
with ThreadPoolExecutor(max_workers=min(os.cpu_count() + 4, 4)) as executor: # 使用线程池并行处理
for i, interval_time in enumerate(time_intervals, start=1):
time_flag += interval_time
if time_flag >= Interval:
try:
temp = executor.submit(NtoNC_convert_array, keys, to_keys, blank).result() # 并行生成新列表
count = 0
while (different_num(temp, convert_MTX[-1]) > to_keys * different_num_ratio) and (count < 4):
count += 1
temp = executor.submit(NtoNC_convert_array, keys, to_keys, blank).result()
except Exception as e:
temp = convert_MTX[-1][:] # 出现错误时，使用上一个结果
time_flag = 0
else:
temp = convert_MTX[-1][:] # 间隔时间不够，使用上一个结果
convert_MTX.append(temp)
convert_MTX = np.array(convert_MTX)
convert_hold_time_MTX = self.MTX_hold_time[np.arange(self.MTX_hold_time.shape[0])[:, None], convert_MTX][
:] # 更新convert_hold_time
convert_in_LN_MTX = get_in_LN_position(convert_hold_time_MTX, self.MTX_start_time) # 获取面条中的位置
convert_MTX[convert_in_LN_MTX] = -1
if del_jack_flag:
convert_MTX = MTX_del_jack(self.MTX_start_time, convert_MTX, beat_time)
if 0 <= density < 10:
MTX_density_b1(convert_MTX, density)
return convert_MTX