def test_open_model():
"""
Test neoruanalyzer.open_model function
"""
reg = neuroanalyzer.AgeRegressor()
reg.open_model(settings.project_folder + '/' + settings.neural_network_file)
assert 1 == 1, "It should not give any exceptions" # Passed if there will be no exception, so it is okay
def test_train_with_raw_data():
"""
Test neuroanalyzer.train_with_raw_data() function
:return:
"""
reg = neuroanalyzer.AgeRegressor()
reg.train_with_raw_data([], True)
# Passed if there will be no exception, so it is okay
assert 1 == 1, "It should not give any exceptions"
def test_query():
"""
Test neoruanalyzer.query function
"""
reg = neuroanalyzer.AgeRegressor()
reg.open_model(settings.project_folder + '/' + settings.neural_network_file)
predicted = reg._query(
[21, 21, 21, 24, 24, 51, 51, 24, 17, 16, 16, 22, 91, 91, 91, 21, 15, 15, 25, 15, 14, 35, 34,
20, 20, 28, 15, 16, 20, 15, 24, 47, 25, 15, 16])
assert abs(15 - predicted) <= 1, "Should be 15±1"
def test_train_with_raw_data():
"""
Test neuroanalyzer.train_with_raw_data() function
:return:
"""
reg = neuroanalyzer.AgeRegressor()
df_raw = pd.read_csv(settings.project_folder + '/' +
'tests/age_research1.csv')
reg.train_with_raw_data(df_raw)
# Passed if there will be no exception, so it is okay
assert 1 == 1, "It should not give any exceptions"
def test_estimate_age_recursive(target, expected, deviation):
"""Test tg.estimate_age_recursive function
:param target: Target, whom to analyze
:param expected: expected answer
:param deviation: Allowed deviation |expected-answer| <= deviation
:return: Asserts True if it was correct
"""
model = neuroanalyzer.AgeRegressor()
model.open_model('neuronet.sav')
estimated_age = telegram_bot.estimate_age_recursive(target, model)
if expected == -1:
assert estimated_age == expected
assert abs(estimated_age - expected) <= deviation
def set_real_age(domain, real_age, verify):
"""
Set person's real age
"""
target_id = age_analyzer.get_id_by_domain(domain)
domain = age_analyzer.get_domain_by_id(target_id)
model = neuroanalyzer.AgeRegressor()
model.open_model('neuronet.sav')
analyze_and_insert(domain, model, force_upgrade=True)
connection = psycopg2.connect(database=settings.db_name,
user=settings.db_login,
password=settings.db_pass,
host=settings.db_ip,
port=settings.db_port)
cur = connection.cursor()
cur.executescript(
f"UPDATE analyzed SET real_age = %s WHERE id = \'%s\';"
f"UPDATE analyzed SET verified = %s WHERE id = \'%s\';",
[real_age, target_id, verify, target_id])
connection.commit()
connection.close()
if __name__ == "__main__":
ANALYZE = True # Set it by yourself
BOT = False
FILL_CSV = False
TRAIN_MODEL = False
TRAIN_MODEL_WITH_TABLE = False
FILL_TABLE = False
FILL_TABLE_RECURSIVE = False
if FILL_CSV:
df = pd.read_csv('age_research.csv')
df = csv_connect.fill_friends_age(df)
df = csv_connect.fill_vk_age(df)
df.fillna(-1.0, inplace=True)
df.to_csv('age_research1.csv', index=False)
if TRAIN_MODEL:
model = neuroanalyzer.AgeRegressor()
if not TRAIN_MODEL_WITH_TABLE:
df = pd.read_csv('age_research1.csv')
model.train_with_raw_data(df, False)
else:
model.train_with_raw_data([], True)
model.save_model('neuronet.sav')
if FILL_TABLE:
df = pd.read_csv('age_research1.csv')
model = neuroanalyzer.AgeRegressor()
model.open_model('neuronet.sav')
for i in range(len(df)):
now_target = df['ID'][i]
try:
model.query(now_target, False, False)
postgres_report.set_real_age(now_target, df['Real Age'][i],
import logging
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import telebot
import age_analyzer
import neuroanalyzer
import settings
from age_analyzer import find_max_mode
from neuroanalyzer import AgeRegressor
bot = telebot.TeleBot(settings.tg_api)
neural_network: AgeRegressor = neuroanalyzer.AgeRegressor()
def counts_by_arr(arr: np.ndarray) -> np.ndarray:
"""
This fucntion returns array with count of each element.
A[j] = count of j meetings in input
:param arr: List
:return:
"""
answ_arr = list([0] * (max(arr) + 1))
for i in arr:
answ_arr[i] += 1
return np.array(answ_arr)
def test_analyze_and_insert(target, force_upgrade):
model = neuroanalyzer.AgeRegressor()
model.open_model('neuronet.sav')
postgres_report.analyze_and_insert(target=target, force_upgrade=force_upgrade, model=model)
assert True
def test_init():
reg = neuroanalyzer.AgeRegressor()
reg.__init__()
assert 1 == 1, "It should not give any exceptions"
def test_analyze_recursive(message):
model = neuroanalyzer.AgeRegressor()
model.open_model('neuronet.sav')
assert telegram_bot.analyze_recursive(message, True,
model) == message.chat.id
