def create_file_analysis_all_group(pre_path):
print('---------create_file_analysis_all_group---------')
f_all_group = read.line_in_file_rstrip(path_file=pre_path +
'all_group.txt')
list_name_file = read.name_file_in_folder(path_folfer=pre_path +
'divide_groups_in_label')
list_file_search = []
for name_file in list_name_file:
list_data = read.get_list_obj_in_file_json(
path_file=pre_path + 'divide_groups_in_label/' + name_file)
list_file_search.append(list_data)
matrix = []
for group in f_all_group:
list_find_times = []
for data_file in list_file_search:
result_find = lib.find_obj_by_field(L=data_file,
target=group,
field="group_id")
if result_find:
list_find_times.append(result_find["times"])
else:
list_find_times.append(0)
matrix.append(list_find_times)
write.matrix(path_file=pre_path + 'analysis_all_group.txt',
list_data=matrix)
def create_data(pre_path):
print('---------create_data_get_label_for_groups---------')
list_name_file = read.name_file_in_folder(path_folfer=pre_path +
'groups_in')
list_group_label = read.get_list_obj_in_file_json(path_file=pre_path +
'group_label.json')
#print(list_name_file)
count_num_lines_no_guess = 0
for name_file in list_name_file:
list_data = read.elements_in_each_line_of_file(
path=pre_path + 'groups_in/' + name_file)
new_file = []
for line in list_data:
new_line = []
for group in line:
label = lib.find_obj_by_field(L=list_group_label,
target=group,
field="group_id")
if label:
new_line.append(label["label"])
new_line.sort()
if len(new_line) > 0:
new_file.append(new_line)
else:
count_num_lines_no_guess = count_num_lines_no_guess + 1
write.w_space_w_in_line(path_file=pre_path + 'get_label_for_groups/' +
name_file,
list_data=new_file)
print("Quantity lines no guess in " + name_file + ": " +
str(count_num_lines_no_guess))
def create_file_all_group(pre_path):
print('---------create_file_all_group---------')
list_file_name = read.name_file_in_folder(path_folfer=pre_path + 'divide_groups_in_label')
list_group = []
for name in list_file_name:
data_in_file = read.line_in_file(path_file=pre_path + 'divide_groups_in_label/' + name)
for line in data_in_file:
obj = json.loads(line)
list_group.append(obj["group_id"])
list_group.sort()
s_list_group = lib.distinct(list_group)
write.each_line_by_path(path_file=pre_path + 'all_group.txt', list_data=s_list_group)
def read_list_percent():
list_name_file = read.name_file_in_folder(path_folfer=path_percent_train)
list_model = [
'__label__18-24', '__label__25-34', '__label__35-44', '__label__45-54',
'__label__55+'
]
list_data_train_X = []
list_label_y = []
i = 0
for file_name in list_name_file:
data_file = read.matrix_percent(path=path_percent_train + file_name)
label = list_model[i]
for line in data_file:
list_data_train_X.append(line)
list_label_y.append(label)
i = i + 1
return list_data_train_X, list_label_y
def create_data(pre_path):
print('---------create_data_percent---------')
list_file_name = read.name_file_in_folder(path_folfer=pre_path +
'get_label_for_groups')
list_model = [
"__label__18-24", "__label__25-34", "__label__35-44", "__label__45-54",
"__label__55+"
]
for file_name in list_file_name:
data_in_file = read.elements_in_each_line_of_file(
path=pre_path + 'get_label_for_groups/' + file_name)
print(file_name)
matrix = []
for line in data_in_file:
list_analysis = lib.analysis_list_sorted(line)
vector = [0] * 5
for i in range(0, 5):
vector[i] = 1 / (len(line) + 5)
for obj in list_analysis:
index = lib.find_index(list_model, obj["label"])
vector[index] = (obj["times"] + 1) / (len(line) + 5)
matrix.append(vector)
write.matrix(path_file=pre_path + 'percent/' + file_name,
list_data=matrix)
