The index for CFTimeIndex is in units of days. This means that if two series using a 360 and 365 days calendar each have a trend of .01C/year, the linear regression coefficients will be different because they have different number of days. Another option would be to have an index in uni
(cf_da, calendar)
| 600 | @requires_cftime |
| 601 | @pytest.mark.parametrize("calendar", _CFTIME_CALENDARS) |
| 602 | def test_get_clean_interp_index_cf_calendar(cf_da, calendar): |
| 603 | """The index for CFTimeIndex is in units of days. This means that if two series using a 360 and 365 days |
| 604 | calendar each have a trend of .01C/year, the linear regression coefficients will be different because they |
| 605 | have different number of days. |
| 606 | |
| 607 | Another option would be to have an index in units of years, but this would likely create other difficulties. |
| 608 | """ |
| 609 | i = get_clean_interp_index(cf_da(calendar), dim="time") |
| 610 | np.testing.assert_array_equal(i, np.arange(10) * 1e9 * 86400) |
| 611 | |
| 612 | |
| 613 | @requires_cftime |
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