issue_comments: 605395619

Hi @keewis, this is really a smart way, using rolling twice. I've refactored the code slightly as: ```python def continuous_meet(cond, count, dim): """ Continuously meet a given condition along a dimension. """ _found = cond.rolling(dim={dim:count}, center=True).sum().fillna(0).astype(np.float)

detected = (
    _found.rolling(dim={dim:count}, center=True) 
    .reduce(lambda a, axis: (a == count).any(axis=axis)) 
    .fillna(False) 
    .astype(bool) 
)

if count % 2 == 0:
    return detected.shift({dim:-1}).fillna(False)

return detected

sst = xr.DataArray( np.array( [0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 0., 0., 1., 0., 0., 1., 1., 1., 1., 1., 1., 0., 0., 0.] ), dims="time", coords={"time": np.arange(24)}, name="sst", )

ElNino = continuous_meet(sst > 0.5, count=5, dim='time')

sst.plot.step(linewidth=3) sst.where(ElNino).plot.step(linewidth=2) `` Note that whencountis a even number, truly centeredrollingcannot be obtained. So we need toshift` the result by -1. Is this perfect? I didn't check the performance.