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Alex Rivera
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I'm looking for the fastest way to check for the occurrence of NaN ( np.nan ) in a NumPy array X . np.isnan(X) is out of the question, since it builds a boolean array of shape X.shape , which is potentially gigantic. I tried np.nan in X , but that seems not to work because np.nan != np.nan . Is there a fast and memory-efficient way to do this at all? (To those who would ask "how gigantic": I can't tell. This is input validation for library code.)
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