issue_comments: 1234368670

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https://github.com/pydata/xarray/issues/6968#issuecomment-1234368670 https://api.github.com/repos/pydata/xarray/issues/6968 1234368670 IC_kwDOAMm_X85Jkvie 39069044 2022-09-01T14:34:05Z 2022-09-01T14:34:05Z CONTRIBUTOR

I don't think curvefit works well with datetime coordinates at this point, because everything gets coerced to float by apply_ufunc. Probably room for improvement there. At a minimum you would need to specify good guesses (p0) and/or bounds in terms of datetime64[ns] values.

An easy enough workaround is to assign a separate non-datetime coordinate. This works: ```python ds = xr.tutorial.open_dataset('air_temperature') ds = ds.assign_coords({'day':(ds.time - ds.time[0]) / np.timedelta64(1, 'D')}).swap_dims({'time':'day'})

def periodic_season(x, a0, a1, a2, a3): # periodic function with both phase amplitude and shift parameters return a0 + a1 * np.cos(a2 * x - a3)

dn = ds.curvefit( 'day', func=periodic_season, p0={'a0':275, 'a1':15, 'a2':2*np.pi/365} ) ```

 
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