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Resolves observingClouds#200. NaN values in input arrays cause BitInformation to produce inaccurate or unexpected results with no indication to the user. Add _check_for_nans() that issues a UserWarning per variable listing the NaN count, called at the entry point of get_bitinformation() before any computation begins. Users who intentionally pass NaN-masked data can suppress with warnings.filterwarnings.
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Summary
Fixes #200 — NaN values in input arrays cause BitInformation to produce inaccurate results with no indication to the user.
Fix in
xbitinfo/xbitinfo.py:_check_for_nans(ds)that issues oneUserWarningper affected variable with the NaN countget_bitinformation()before any computationwarnings.filterwarnings("ignore", category=UserWarning, module="xbitinfo")Test plan
ds = xr.Dataset({"a": xr.DataArray([1.0, float("nan"), 3.0])}); xb.get_bitinformation(ds)→ UserWarning raised