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)