Open detector¶
CO2¶
Nieco o CO2.
Init general models from local database¶
Pre ladiace ucely bola vytvorena lokalna databaza, ktora obsahuje predspracovane udaje a následne umoznuje rýchle pocitanie pouzitých atribútov. Ukazkovy priklad toho ako moze vyzerat vytvorenie modelu z databaze
"""
"""
from os.path import dirname, abspath, join
import sys
sys.path.append(abspath(join(dirname(__file__), '../..', '')))
from dm.models.ModelsUtil import ModelsUtil
from dm.models.open_detector.generic_training_file_from_local_db import *
import os
__author__ = ''
__email__ = ''
if __name__ == '__main__':
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)s %(levelname)s %(message)s')
no_event_shift = int(cu.open_detector('attrs.no_event.time_shift'))
# tabulka s CO2, ktora neprekroci hranicu 2000ppm
table_name = 'measured_filtered_peto'
columns = ColumnMapper.OPEN_CO2
directory = cu.open_detector('generic.directory')
if not os.path.isdir(directory):
os.mkdir(directory)
co2_csv = cu.open_detector('generic.co2.data_file.name') + '_from_local_db.bin'
co2_model = cu.open_detector('generic.co2.model.name') + '_from_local_db.bin'
data_co2 = training_set_co2(cu.package('co2.event_file.name'), no_event_shift, table_name,
co2_csv, columns)
ModelsUtil.write_model(data_co2, co2_model, ModelsUtil.replace_nothing_open)
t_h_csv = cu.open_detector('generic.t_h.data_file.name') + '_from_local_db.bin'
t_h_model = cu.open_detector('generic.t_h.model.name') + '_from_local_db.bin'
data_t_h = training_set_t_h(cu.package('t_h.event_file.name'), no_event_shift, table_name,
t_h_csv, columns)
ModelsUtil.write_model(data_t_h, t_h_model, ModelsUtil.replace_nothing_open)
Output is binary file contains model … vytvoreny pomocou kniznice sklearn
a modelu SVM
. Vsetky konfiguracne parametre su ulozene v konfiguracnom subore config.ini
, ktory
je popisany v sekcii Configuration File.
Ukazka spustenia vytvorenia modelu z lokalnej databaze:
python3 examples2/0300_open_detector/init_general_models_from_local_db.py
Init general models¶
"""
"""
from os.path import dirname, abspath, join
import sys
sys.path.append(abspath(join(dirname(__file__), '../..', '')))
import logging
import json
from dm.models.open_detector.generic_training_file import generic_training_file
from dm.ConnectionUtil import ConnectionUtil as cu
from dm.WundergroundCom import WundergroundCom
from dm.BeeeOnClient import BeeeOnClient
from dm.models.open_detector.create_attrs import ColumnMapper
from dm.models.ModelsUtil import ModelsUtil
__author__ = ''
__email__ = ''
if __name__ == '__main__':
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)s %(levelname)s %(message)s')
cls = {
'ant-work': BeeeOnClient('ant-work.fit.vutbr.cz', 8010),
'rehivetech': BeeeOnClient('beeeon.rehivetech.com', 8010),
}
cls['ant-work'].api_key = cu.ant_work_api_key('dm')
cls['rehivetech'].api_key = cu.rehivetech_api_key('acontroller')
no_event_shift = int(cu.open_detector('attrs.no_event.time_shift'))
# file with devices for training
with open(cu.open_detector('generic.devices.path'), 'r') as f:
devs = json.load(f)
w = WundergroundCom()
w.api_key = cu.wunderground_api_key()
# co2
data_co2 = generic_training_file(cu.package('co2.event_file.name'),
no_event_shift, 'co2', ColumnMapper.OPEN_CO2, cls,
devs, w)
ModelsUtil.write_model(data_co2, cu.open_detector('generic.co2.model.name'),
ModelsUtil.replace_nothing_open)
# t_h
data_t_h = generic_training_file(cu.package('t_h.event_file.name'),
no_event_shift, 't_h', ColumnMapper.OPEN_T_H, cls,
devs, w)
ModelsUtil.write_model(data_t_h, cu.open_detector('generic.t_h.model.name'),
ModelsUtil.replace_nothing_open)