def option6(gesture_file, vector_model, top_k_input=None):
util.load_user_settings()
filenames = util.get_files('./wrd_data', '.wrd')
distances = []
for filename in filenames:
gesture_id = filename.split('.')[0]
distance = gesture_edit_distance(gesture_file, gesture_id)
distances.append((gesture_id, distance))
distances.sort(key=lambda pair: pair[1])
return distances
import task3_util as util
import general_util as gen_util
from task2 import options
import numpy as np
import os
from sklearn import decomposition
from sklearn.preprocessing import MinMaxScaler
# Main
if __name__ == '__main__':
# Load User Settings
gen_util.load_user_settings()
# Load arguments
p = int(input('How many principle components to return: '))
# List options
print('Options:')
for option_number, (option_name, _, _) in options.items():
print(f'{option_number}. {option_name}')
option = int(input('Please select an option: '))
while option not in options:
print('Invalid option. Please try again.')
option = int(input('Please select an option: '))
top_k_input = None
if option in [2,3,4,5]:
top_k_input = int(input('How many top-k components did you specify during Task 1? (e.g. 1, 2, etc.): '))
vector_model = None
option: int):
if option not in options:
raise ValueError(f'Invalid option')
top_k_input = None
if option in [2, 3, 4, 5]:
top_k_input = int(
input(
'How many top-k components did you specify during Task 1? (e.g. 1, 2, etc.): '
))
return options[option][1](gesture_file, vector_model, top_k_input)[0:10]
# Main
if __name__ == '__main__':
# Load User Settings
util.load_user_settings()
# Load arguments
gesture_file = input('Gesture file (e.g. 1, 249, 559, etc.): ')
# List options
print('Options:')
for option_number, (option_name, _, _) in options.items():
print(f'{option_number}. {option_name}')
option = int(input('Please select an option: '))
while option not in options:
print('Invalid option. Please try again.')
option = int(input('Please select an option: '))
vector_model = None