Scope warning suppression to avoid globally silencing warnings - #696
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warnings.filterwarnings("ignore") at import time in ensembleseries.py
and warnings.simplefilter('ignore') in Series.spectral/wavelet/
wavelet_coherence mutated the global warnings filter state and never
restored it, permanently silencing all Python warnings for the rest
of the session after a single verbose=False call. This also caused
wavelet_coherence to silently swallow its own warning about
reinterpolating data onto a common time axis.
Suppression is now scoped with warnings.catch_warnings() around just
the underlying numerical computation, and the common_time()
reinterpolation notice is raised as a new DataConformationWarning to
mark it as a warning that should always reach the user regardless of
verbose.
Fixes #695
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
khider
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Aug 14, 2026
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Approving this as a I agree that we shouldn't be hiding that we are doing this but the question I have is why we are doing it in the first place. If the method requires evenly spaced data, we should raise an error and suggest the use of interp().
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warnings.filterwarnings("ignore")at import time in ensembleseries.py and warnings.simplefilter('ignore') in Series.spectral/wavelet/ wavelet_coherence mutated the global warnings filter state and never restored it, permanently silencing all Python warnings for the rest of the session after a singleverbose=Falsecall. This also causedwavelet_coherenceto silently swallow its own warning about interpolating data onto a common time axis.This fix now restricts suppression within
warnings.catch_warnings()around the relevant numerical computations, and thecommon_time()interpolation notice is raised as a new DataConformationWarning to mark it as a warning that should always reach the user regardless of verbose.Fixes #695