[EMAIL PROTECTED] (David M. Cooke) writes: > > Bruno's already mentioned that iterators and generators aren't > sequences. Numpy arrays act like the other sequence types: > >>>> a = numpy.array([]) >>>> a > array([], dtype=int64) >>>> len(a) > 0 >>>> bool(a) > False > > (0-dimensional numpy arrays are pathological anyways)
*cough* as a Numpy developer I should know better. Numpy arrays that have more than one element don't work in a boolean context: >>> a = numpy.array([1,2]) >>> bool(a) Traceback (most recent call last): File "<stdin>", line 1, in ? ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() The reason for this is that it really was a common source of errors, because of the rich comparision semantics used. If a and b are numpy arrays, 'a == b' is an array of booleans. Numpy arrays of one element act like scalars in boolean contexts: >>> a = numpy.array([0]) >>> bool(a) False >>> a = numpy.array([1]) >>> bool(a) True (this is partly because we define a comphensive hierarchy of scalar types to match those available in C). -- |>|\/|< /--------------------------------------------------------------------------\ |David M. Cooke |cookedm(at)physics(dot)mcmaster(dot)ca -- http://mail.python.org/mailman/listinfo/python-list
