def test_span_best_over_weeks(self):
csvlines = FittingUtilTestCase.csv_content.splitlines()
csvdic = f_util.csv_value_dict_from_iter(csvlines)
dates, loads, perfs = f_util.span_best_over_weeks(csvdic,
'skiba_bike_score',
'60m_critical_power')
self.assertTrue(perfs[0] == 170)
self.assertTrue(perfs[0] == perfs[1])
self.assertTrue(perfs[1] == perfs[2])
self.assertTrue(perfs[3] == 180)
def test_collapse_perfs_per_day(self):
csvlines = FittingUtilTestCase.csv_content.splitlines()
csvdic = f_util.csv_value_dict_from_iter(csvlines)
dates, loads, perfs = f_util.span_best_over_weeks(csvdic,
'skiba_bike_score',
'60m_critical_power')
col_perfs = f_util.collapse_perfs_per_day(dates, perfs)
self.assertTrue(len(col_perfs) == 7)
expected = [(datetime.date(2014, 2, 15), 170),
(datetime.date(2014, 2, 16), 170),
(datetime.date(2014, 2, 17), 180),
(datetime.date(2014, 3, 1), 190),
(datetime.date(2014, 3, 29), 200),
(datetime.date(2015, 3, 1), 150),
(datetime.date(2015, 3, 29), 90)]
self.assertTrue(col_perfs == expected)
