Fast check for NaN in NumPy
I think np.isnan(np.min(X)) should do what you want.
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.)