issue_comments: 1411048944

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https://github.com/pydata/xarray/issues/7273#issuecomment-1411048944 https://api.github.com/repos/pydata/xarray/issues/7273 1411048944 IC_kwDOAMm_X85UGuXw 630436 2023-01-31T20:48:01Z 2023-01-31T20:48:01Z NONE

Sorry for slow reply, I got pulled onto another task before Christmas and forgot to revisit. Hit this in a different way again today. I get a combo of mangled as well as NaN values.

``` print((d0.swe.y - d1.swe.y).shape == d0.swe.shape) print((d0.swe.y - d1.swe.y).shape) print(d0.swe.y.shape)

False (2509,) (2509,) ```

``` np.unique(d0.swe.y.values == d1.swe.y.values)

array([ True]) ```

``` np.unique(d0.swe.x.values == d1.swe.x.values)

array([False, True] xr.align(d0, d1, join="exact") ValueError: cannot align objects with join='exact' where index/labels/sizes are not equal along these coordinates (dimensions): 'x' ('x',) ```

Looking at x shows X off by 1e-12 np.unique(d0.swe.x.values - d1.swe.x.values) array([-1.62003744e-12, -1.60582658e-12, -1.59161573e-12, -1.57740487e-12, -1.56319402e-12, -1.54898316e-12, -1.53477231e-12, -1.52056145e-12, -1.50635060e-12, -1.49213975e-12, -1.47792889e-12, -1.46371804e-12, -1.44950718e-12, -1.43529633e-12, -1.42108547e-12, -1.40687462e-12, -1.39266376e-12, -1.37845291e-12, -1.36424205e-12, -1.35003120e-12, -1.33582034e-12, -1.32160949e-12, -1.30739863e-12, -1.29318778e-12, -1.27897692e-12, -1.26476607e-12, -1.25055521e-12, -1.23634436e-12, -1.22213351e-12, -1.20792265e-12, -1.19371180e-12, -1.17950094e-12, -1.16529009e-12, -1.15107923e-12, -1.13686838e-12, -1.12265752e-12, -1.10844667e-12, -1.09423581e-12, -1.08002496e-12, -1.06581410e-12, -1.05160325e-12, -1.03739239e-12, -1.02318154e-12, -1.00897068e-12, -9.94759830e-13, -9.80548975e-13, -9.66338121e-13, -9.52127266e-13, -9.37916411e-13, -9.23705556e-13, -9.09494702e-13, -8.95283847e-13, -8.81072992e-13, -8.66862138e-13, -8.52651283e-13, -8.38440428e-13, -8.24229573e-13, -8.10018719e-13, -7.95807864e-13, -7.81597009e-13, -7.67386155e-13, -7.53175300e-13, -7.38964445e-13, -7.24753590e-13, -7.10542736e-13, -6.96331881e-13, -6.82121026e-13, -6.67910172e-13, -6.53699317e-13, -6.39488462e-13, -6.25277607e-13, -6.11066753e-13, -5.96855898e-13, -5.82645043e-13, -5.68434189e-13, -5.54223334e-13, -5.40012479e-13, -5.25801624e-13, -5.11590770e-13, -4.97379915e-13, -4.83169060e-13, -4.68958206e-13, -4.54747351e-13, -4.40536496e-13, -4.26325641e-13, -4.12114787e-13, -3.97903932e-13, -3.83693077e-13, -3.69482223e-13, -3.55271368e-13, -3.41060513e-13, -3.26849658e-13, -3.12638804e-13, -2.98427949e-13, -2.84217094e-13, -2.70006240e-13, -2.55795385e-13, -2.41584530e-13, -2.27373675e-13, -2.13162821e-13, -1.98951966e-13, -1.84741111e-13, -1.70530257e-13, -1.56319402e-13, -1.42108547e-13, -1.27897692e-13, -1.13686838e-13, -9.94759830e-14, -8.52651283e-14, -7.10542736e-14, -5.68434189e-14, -4.26325641e-14, -2.84217094e-14, -1.42108547e-14, 0.00000000e+00])

 
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