def test_apply_factors_single_parameter2():
factors = {
'January': 1.5,
'February': 2.0,
'March': 2.5,
'April': 3.0,
'May': 3.5,
'June': 4.0,
'July': 4.5,
'August': 5.5,
'September': 6.0,
'October': 6.5,
'November': 7.0,
'December': 7.5
}
dates = np.array([datetime.datetime(2014, 04, 01, 0, 0),
datetime.datetime(2014, 04, 02, 0, 0),
datetime.datetime(2014, 04, 03, 0, 0)
])
updated_discharge_data = np.array([5, 9, 13])
expected = {
"user": "******",
"date_created": "4/9/2014 15:50:47 PM",
"stationid": "012345",
"column_names": ['Discharge (cfs)', 'Subsurface Flow (mm/day)', 'Impervious Flow (mm/day)', 'Infiltration Excess (mm/day)', 'Initial Abstracted Flow (mm/day)', 'Overland Flow (mm/day)', 'PET (mm/day)', 'AET(mm/day)', 'Average Soil Root zone (mm)', 'Average Soil Unsaturated Zone (mm)', 'Snow Pack (mm)', 'Precipitation (mm/day)', 'Storage Deficit (mm/day)', 'Return Flow (mm/day)'],
"dates": dates,
"parameters": [
{"name": "Discharge (cfs)",
"index": 0,
"data": updated_discharge_data,
"mean": np.mean(updated_discharge_data),
"max": np.max(updated_discharge_data),
"min": np.min(updated_discharge_data)
}]
}
actual = watertxt.apply_factors(watertxt_data = fixture["sample_data_dict"], name = "Discharge", factors = factors, is_additive = True)
nose.tools.assert_equals(expected["parameters"][0]["name"], actual["parameters"][0]["name"])
nose.tools.assert_equals(expected["parameters"][0]["index"], actual["parameters"][0]["index"])
nose.tools.assert_almost_equals(actual["parameters"][0]["data"].all(), expected["parameters"][0]["data"].all())
nose.tools.assert_almost_equals(actual["parameters"][0]["mean"], expected["parameters"][0]["mean"])
nose.tools.assert_almost_equals(actual["parameters"][0]["max"], expected["parameters"][0]["max"])
nose.tools.assert_almost_equals(actual["parameters"][0]["min"], expected["parameters"][0]["min"])
def test_apply_factors_multi_parameters():
factors = {
"January": 1.5,
"February": 2.0,
"March": 2.5,
"April": 3.0,
"May": 3.5,
"June": 4.0,
"July": 4.5,
"August": 5.5,
"September": 6.0,
"October": 6.5,
"November": 7.0,
"December": 7.5
}
dates = np.array([datetime.datetime(2014, 1, 1, 0, 0),
datetime.datetime(2014, 2, 1, 0, 0),
datetime.datetime(2014, 3, 1, 0, 0),
datetime.datetime(2014, 4, 1, 0, 0),
datetime.datetime(2014, 5, 1, 0, 0),
datetime.datetime(2014, 6, 1, 0, 0),
datetime.datetime(2014, 7, 1, 0, 0),
datetime.datetime(2014, 8, 1, 0, 0),
datetime.datetime(2014, 9, 1, 0, 0),
datetime.datetime(2014, 10, 1, 0, 0),
datetime.datetime(2014, 11, 1, 0, 0),
datetime.datetime(2014, 12, 1, 0, 0)]
)
discharge_data_all_months = np.array([4.5, 12, 25, 36, 52.5, 64, 81, 82.5, 66, 45.5, 35, 15])
subsurface_data_all_months = np.array([75, 110, 112.5, 120, 122.5, 120, 112.5, 110, 90, 130, 175, 225])
expected = {
"user": "******",
"date_created": "4/9/2014 15:50:47 PM",
"stationid": "012345",
"column_names": ['Discharge (cfs)', 'Subsurface Flow (mm/day)', 'Impervious Flow (mm/day)', 'Infiltration Excess (mm/day)', 'Initial Abstracted Flow (mm/day)', 'Overland Flow (mm/day)', 'PET (mm/day)', 'AET(mm/day)', 'Average Soil Root zone (mm)', 'Average Soil Unsaturated Zone (mm)', 'Snow Pack (mm)', 'Precipitation (mm/day)', 'Storage Deficit (mm/day)', 'Return Flow (mm/day)'],
"dates": dates,
"parameters": [
{"name": "Discharge (cfs)",
"index": 0,
"data": discharge_data_all_months,
"mean": np.mean(discharge_data_all_months),
"max": np.max(discharge_data_all_months),
"min": np.min(discharge_data_all_months)
},
{"name": "Subsurface Flow (mm/day)",
"index": 1,
"data": subsurface_data_all_months,
"mean": np.mean(subsurface_data_all_months),
"max": np.max(subsurface_data_all_months),
"min": np.min(subsurface_data_all_months)
}
],
}
actual_q = watertxt.apply_factors(watertxt_data = fixture["sample_data_dict_all_months"], name = "Discharge", factors = factors)
actual_s = watertxt.apply_factors(watertxt_data = fixture["sample_data_dict_all_months"], name = "Subsurface Flow", factors = factors)
nose.tools.assert_equals(actual_q["parameters"][0]["name"], expected["parameters"][0]["name"])
nose.tools.assert_equals(actual_q["parameters"][0]["index"], expected["parameters"][0]["index"])
nose.tools.assert_equals(actual_s["parameters"][1]["name"], expected["parameters"][1]["name"])
nose.tools.assert_equals(actual_s["parameters"][1]["index"], expected["parameters"][1]["index"])
nose.tools.assert_almost_equals(actual_q["parameters"][0]["data"].all(), expected["parameters"][0]["data"].all())
nose.tools.assert_almost_equals(actual_s["parameters"][1]["data"].all(), expected["parameters"][1]["data"].all())
nose.tools.assert_almost_equals(actual_q["parameters"][0]["mean"], expected["parameters"][0]["mean"])
nose.tools.assert_almost_equals(actual_q["parameters"][0]["max"], expected["parameters"][0]["max"])
nose.tools.assert_almost_equals(actual_q["parameters"][0]["min"], expected["parameters"][0]["min"])
nose.tools.assert_almost_equals(actual_s["parameters"][1]["mean"], expected["parameters"][1]["mean"])
nose.tools.assert_almost_equals(actual_s["parameters"][1]["max"], expected["parameters"][1]["max"])
nose.tools.assert_almost_equals(actual_s["parameters"][1]["min"], expected["parameters"][1]["min"])
