This is an intentional "feature", not a bug.
Chris
Ah, ok, thanks. I missed the explanation in the doc string because I'm using version 1.3 and forgot to check the web docs. For the record, this was my bug: I read a fits binary table with pyfits. One of the table fields was a chararray containing a bunch of flags ('A','B','C','D'). I tried to use in1d() to identify all entries with flags of 'C' or 'D'. So
c = pyfits_table.chararray_column mask = np.in1d(c, ['C', 'D'])
It turns out the actual stored values in the chararray were 'A ', 'B ', 'C ' and 'D '. in1d() converts the chararray to an ndarray before performing the comparison, so none of the entries matches 'C' or 'D'. What is the best way to ensure this doesn't happen to other people? We could change the array set operations to special-case chararrays, but this seems like an ugly solution. Is it possible to change something in pyfits to avoid this? Neil