Closed chanjure closed 12 months ago
Test: test_get_active_office_mask Working hour is from 9 am to 5:30 pm. So the time slots for working hours are 9:00 9:30 10:00 10:30 ... 16:00 16:30 17:00 The last timeslot represents 17:00 to 17:30. However, the original code was appending the timeslot list until 17:30, which would represent 17:30 to 18:00.
Fixed metoffice api and corresponding errors [8edae59]()
Fixed pytest error 7b0f647
Fixed test_efficiency error. aab8ebb
Fixed test_stacked_record and test_df_unstacker_on_bug_19. 6f637b2
Error messages from pytest
[x] Test: test_building_energy_demand
| Reason: sjautobidder/met_office_api/api_interpolation.get_metoffice_key cannot read metoffice key. METOFFICEAPI environment variable is not properly set up.
[x] Test: test_get_office_equipment_demand | Reason: sjautobidder/building_demand/energy_demand.get_office_equipment_demand missing argument. Not sure if this test is relevant. get_office_equipment_demand takes one argument but the test does not put any argument and just returns an error.
[x] Test: test_get_lighting_and_other_demand | Reason: Same as above
[x] Test: test_building_energy_demand.test_temp_to_energy | Reason: sjautobidder/building_demand/energy_utils.temp_to_energy not giving correct value. But not sure if we need this function. Also this might be related to the first error where metoffice key is not properly set.
[x] Test: test_get_active_office_mask | Reason: sjautobidder/building_demand/energy_utils.get_active_office_mask not counting working hour correctly. It should return 17 instead of 18, because there are 17 timeslot between 9 am to 17:30 pm. It gives correct results for weekends.
[x] Test: test_efficiency | Reason: sjautobidder/solar_power/solar_utils.temperature_efficiency suppose to return float but its returning bool? or some value is not correct and it is set to return false when the value is wrong.->why?
[x] Test: test_stacked_record | Reason: It seems like there is something called
Bug #19". bmrs_code B1620 with date
2020-02-10" gives wrong number of prediction time periods.[x] Test: test_df_unstacker_on_bug_19 | Reason: Related to the above bug