def run_metocean_forecasting_problem(train_file_path,
test_file_path,
forecast_length=1,
is_visualise=False,
timeout=5):
# Prepare data for train and test
ssh_history, ws_history, ssh_obs = prepare_input_data(
train_file_path, test_file_path)
historical_data = {
'ws': ws_history, # additional variable
'ssh': ssh_history, # target variable
}
fedot = Fedot(
problem='ts_forecasting',
task_params=TsForecastingParams(forecast_length=forecast_length),
timeout=timeout,
verbose_level=4)
pipeline = fedot.fit(features=historical_data, target=ssh_history)
fedot.forecast(historical_data, forecast_length=forecast_length)
metric = fedot.get_metrics(target=ssh_obs)
if is_visualise:
pipeline.show()
fedot.plot_prediction()
return metric
def test_multivariate_ts():
forecast_length = 1
file_path_train = 'cases/data/metocean/metocean_data_train.csv'
full_path_train = os.path.join(str(fedot_project_root()), file_path_train)
# a dataset for a final validation of the composed model
file_path_test = 'cases/data/metocean/metocean_data_test.csv'
full_path_test = os.path.join(str(fedot_project_root()), file_path_test)
target_history, add_history, obs = prepare_input_data(
full_path_train, full_path_test)
historical_data = {
'ws': add_history, # additional variable
'ssh': target_history, # target variable
}
fedot = Fedot(
problem='ts_forecasting',
composer_params=composer_params,
task_params=TsForecastingParams(forecast_length=forecast_length))
fedot.fit(features=historical_data, target=target_history)
forecast = fedot.forecast(historical_data, forecast_length=forecast_length)
assert forecast is not None