def gen_m(config):
num = config['TOTAL_NUM']
features = pre_process_config(config['FEATURES'])
# print(features)
theta1_list = gen_theta(features['theta1'],num)
theta2_list = gen_theta(features['theta2'],num)
theta3_list = gen_theta(features['theta3'],num)
theta4_list = gen_theta(features['theta4'],num)
theta5_list = gen_theta(features['theta5'],num)
theta6_list = gen_theta(features['theta6'],num)
theta7_list = gen_theta(features['theta7'],num)
theta8_list = gen_theta(features['theta8'],num)
theta9_list = gen_theta(features['theta9'],num)
k1_list = gen_theta(features['k1'],num)
k2_list = gen_theta(features['k2'],num)
season_list = []
noise_list = []
trend_list = []
for i in range(0,num):
noise_generator = ng.NoiseGeneratorFactory().get_generator(None)
trend_generator = tg.TrendGenerator()
season_generator = sg.SeasonGeneratorFactory(theta5_list[i],theta3_list[i],theta4_list[i],k1_list[i],k2_list[i],forking_depth=7).get_generator(None)
season = season_generator.gen_season()
noise = noise_generator.gen(theta6_list[i],theta7_list[i],theta8_list[i],theta9_list[i],len(season[0]))
trend = trend_generator.gen(theta1_list[i],theta2_list[i],len(season[0]))
season_list.append(season)
noise_list.append(noise)
trend_list.append(trend)
# print(noise[1].shape,trend[1].shape,season[1].shape)
# print(noise[0].shape,trend[0].shape,season[0].shape)
print(noise)
print(trend)
print(season)
assembler = assem.AbstractAssembler(season_list,noise_list,trend_list)
assembler.assemble()
assembler.save(path=out_path)
import generator.trend_generator as tg
import generator.noise_generator as ng
import generator.season_generator as sg
import matplotlib.pyplot as plt
#====================================================================================
# Group1
# spike, beat, type1, type2, control noise level.
season_generator = sg.NormalSeasonGenerator(10,
10,
200,
drift_a=0,
drift_f=0,
forking_depth=7)
noise_generator = ng.Gaussian()
trend_generator = tg.TrendGenerator()
season = season_generator.gen_season()
length = len(season[0])
noise = [
noise_generator.gen(0, sigma, length)
for sigma in np.linspace(0.5, 2, 100)
]
trend = trend_generator.gen(0, 0, length)
# assembler = assem.AssemblerWithAdditiveAnomalyInjector_v1(season,noise,trend,'noise',10e-7,0.2,a_type='spike')
assembler = assem.AssemblerWithAdditiveAnomalyInjector_v1(season,
noise,
trend,
'noise',
10e-7,
def gen_v(config):
config
# season_generator = sg.SeasonGeneratorFactory(10,10,200,drift_a=0,drift_f=0,forking_depth=7,'vanish')
noise_generator = ng.Gaussian()
trend_generator = tg.TrendGenerator()