def test_scenario1(self): """ Scenario: Successfully creating forecasts from a dataset: Given I create a data source uploading a "<data>" file And I wait until the source is ready less than <time_1> secs And I create a dataset And I wait until the dataset is ready less than <time_2> secs And I create time-series from a dataset And I wait until the time series is ready less than <time_3> secs And I update the time series name to "<time_series_name>" When I wait until the time series is ready less than <time_4> secs Then the time series name is "<time_series_name>" And I create a forecast for "<input_data>" Then the forecasts are "<forecast_points>" Examples: | data | time_1 | time_2 | time_3 | time_4 | time_series_name |input_data | forecast_points | ../data/grades.csv | 10 | 10 | 20 | 50 | my new time_series name | {"000005": {"horizon": 5}], {}} """ print self.test_scenario1.__doc__ examples = [[ 'data/grades.csv', '30', '30', '50', '50', 'my new time series name', '{"000005": {"horizon": 5}}', '{"000005": [{"point_forecast": [73.96192, 74.04106, 74.12029, 74.1996, 74.27899], "model": "M,M,N"}]}' ]] for example in examples: print "\nTesting with:\n", example source_create.i_upload_a_file(self, example[0]) source_create.the_source_is_finished(self, example[1]) dataset_create.i_create_a_dataset(self) dataset_create.the_dataset_is_finished_in_less_than( self, example[2]) time_series_create.i_create_a_time_series(self) time_series_create.the_time_series_is_finished_in_less_than( self, example[3]) time_series_create.i_update_time_series_name(self, example[5]) time_series_create.the_time_series_is_finished_in_less_than( self, example[4]) time_series_create.i_check_time_series_name(self, example[5]) forecast_create.i_create_a_forecast(self, example[6]) forecast_create.the_forecast_is(self, example[7])
def test_scenario1(self): """ Scenario: Successfully creating forecasts from a dataset: Given I create a data source uploading a "<data>" file And I wait until the source is ready less than <time_1> secs And I create a dataset And I wait until the dataset is ready less than <time_2> secs And I create time-series from a dataset And I wait until the time series is ready less than <time_3> secs And I update the time series name to "<time_series_name>" When I wait until the time series is ready less than <time_4> secs Then the time series name is "<time_series_name>" And I create a forecast for "<input_data>" Then the forecasts are "<forecast_points>" Examples: | data | time_1 | time_2 | time_3 | time_4 | time_series_name |input_data | forecast_points | ../data/grades.csv | 10 | 10 | 20 | 50 | my new time_series name | {"000005": {"horizon": 5}], {}} """ print self.test_scenario1.__doc__ examples = [ ['data/grades.csv', '10', '10', '20', '50', 'my new time series name', '{"000005": {"horizon": 5}}', '{"000005": [{"point_forecast": [68.53181, 68.53181, 68.53181, 68.53181, 68.53181], "model": "A,N,N"}]}']] for example in examples: print "\nTesting with:\n", example source_create.i_upload_a_file(self, example[0]) source_create.the_source_is_finished(self, example[1]) dataset_create.i_create_a_dataset(self) dataset_create.the_dataset_is_finished_in_less_than(self, example[2]) time_series_create.i_create_a_time_series(self) time_series_create.the_time_series_is_finished_in_less_than(self, example[3]) time_series_create.i_update_time_series_name(self, example[5]) time_series_create.the_time_series_is_finished_in_less_than(self, example[4]) time_series_create.i_check_time_series_name(self, example[5]) forecast_create.i_create_a_forecast(self, example[6]) forecast_create.the_forecast_is(self, example[7])