def train_model(experiment_name, groups=1, time_window=pio.TimeWindow(-90, -30, 1, 15)):
path = os.path.join(DATA_PATH, 'ts.csv')
data, group_list = get_data(path, groups)
fname = '{}_{}.csv'.format(experiment_name, '-'.join(group_list))
data.to_csv(fname, index=False)
project = pio.Project.from_id(PROJECT_ID)
dataset = project.create_dataset(name=experiment_name,
dataframe=data)
experiment_version_config = pio.TrainingConfig(
advanced_models=[pio.AdvancedModel.LinReg],
normal_models=[pio.NormalModel.LinReg],
features=[pio.Feature.Counts],
profile=pio.Profile.Quick,
)
col_config = pio.ColumnConfig(target_column='target',
time_column='time',
# group_columns=group_list
)
experiment_version = project.fit_timeseries_regression(
experiment_name,
dataset,
time_window=time_window,
training_config=experiment_version_config,
column_config=col_config,
)
return experiment_version
def time_window_test(dws, dwe, fws, fwe):
ts_label = '_'.join(str(s).replace('-', 'm') for s in (dws, dwe, fws, fwe))
experiment_name_asked = 'ts_time{}_{}'.format(ts_label, TESTING_ID)
experiment_version = train_model(experiment_name_asked,
time_window=pio.TimeWindow(dws, dwe, fws, fwe))
experiment_version.wait_until(lambda experimentv: len(experimentv.models) > 0)
experiment_version.stop()
return experiment_version
def time_window_test(dws, dwe, fws, fwe):
ts_label = '_'.join(str(s).replace('-', 'm') for s in (dws, dwe, fws, fwe))
uc_name_asked = 'ts_time{}_{}'.format(ts_label, TESTING_ID)
uc = train_model(uc_name_asked,
time_window=pio.TimeWindow(dws, dwe, fws, fwe))
uc_name_returned = uc.name
uc.wait_until(lambda usecase: len(usecase) > 0)
uc.stop()
return uc_name_returned
def test_version():
dws, dwe, fws, fwe = (-10, -5, 3, 4)
ts_label = '_'.join(str(s).replace('-', 'm') for s in (dws, dwe, fws, fwe))
experiment_name_asked = 'ts_time{}_{}'.format(ts_label, TESTING_ID)
experiment_version = train_model(experiment_name_asked,
time_window=pio.TimeWindow(dws, dwe, fws, fwe))
experiment_version.wait_until(lambda experimentv: len(experimentv.models) > 0)
experiment_version.stop()
new_experiment_version = experiment_version.new_version()
new_experiment_version.wait_until(lambda experimentv: len(experimentv.models) > 1)
experiment_version.stop()
def train_model(uc_name, groups=1, time_window=pio.TimeWindow(-90, -30, 1, 15)):
path = os.path.join(DATA_PATH, 'ts.csv')
data, group_list = get_data(path, groups)
fname = '{}_{}.csv'.format(uc_name, '-'.join(group_list))
data.to_csv(fname, index=False)
dataset = pio.Dataset.new(name=uc_name,
dataframe=data)
uc_config = pio.TrainingConfig(normal_models=[pio.Model.LinReg],
lite_models=[pio.Model.LinReg],
features=[pio.Feature.Counts],
profile=pio.Profile.Quick)
col_config = pio.ColumnConfig(target_column='target',
time_column='time',
# group_columns=group_list
)
uc = pio.TimeSeries.fit(uc_name,
dataset,
time_window=time_window,
training_config=uc_config,
column_config=col_config)
return uc