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import pandas as pd
import numpy as np
df=pd.read_csv('../Data/72_Trajectory.csv')
# from concurrent.futures import ThreadPoolExecutor
# max_timesteps=296
# feature_num=16
# label_nums=9
#
# ##数据增强，准确版本
# def generate_partial_sequences(row, max_timesteps=max_timesteps, features_per_timestep=feature_num, fill_value=-10):
# # 确定实际长度
# actual_length_indices = np.where(row[:-label_nums] != fill_value)[0] # 排除最后的标签列
# if len(actual_length_indices) > 0:
# actual_length = (actual_length_indices[-1] // features_per_timestep) + 1
# else:
# actual_length = 0
# partial_sequences = []
# step_size = max(1, int(actual_length * 0.1)) # 步长为实际长度的10%，至少为1
# print(f'{actual_length},{step_size}')
#
# for end_length in range(step_size, actual_length + step_size, step_size):
# # 计算结束点，不超过实际长度
# end_length = min(end_length, actual_length)
# partial_sequence_list = row[:end_length * features_per_timestep].tolist()
#
# selected_features_list = [partial_sequence_list[i:i + 10] for i in
# range(0, len(partial_sequence_list), features_per_timestep)]
# selected_features_list = [item for sublist in selected_features_list for item in sublist]
#
# hand_rotation_axis = partial_sequence_list[-6:-3]
# hand_direction = partial_sequence_list[-3:]
#
# padding_length = (max_timesteps - end_length) * 10 # 计算填充长度
# selected_features_list.extend([fill_value] * padding_length) # 添加填充
#
# selected_features_list.extend(row[-9:]) # 添加标签
# selected_features_list.extend(hand_rotation_axis) # 添加HandRotationAxis和HandDirection
# selected_features_list.extend(hand_direction)
#
# print(len(selected_features_list))
#
# partial_sequences.append(selected_features_list)
# return partial_sequences
#
#
#
# df = pd.read_csv('../Data/testing/test_data_supervised.csv')
# partial_sequences_df = generate_partial_sequences(df.iloc[0])
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