Rick Giuly wrote:
Hello All,
Case 1
This generates an error, which makes sense because the argument should
be a list of numbers:
numpy.array(10,10)
Case 2
This does not generate an error and the result is an array with a
single element:
a = numpy.array([10])
b = numpy.array([10])
numpy.array(a[0],b[0])
The only different I see here between the numpy.array call in the
cases is that
a[0] is a numpy int32
10 is an int
Why would this minor difference in integer types cause a totally
different result for the two cases - or is something else causing the
difference in results?
The second argument is for a dtype. Basically, we'll accept anything there that
can be coerced to a dtype using numpy.dtype(). For some reason, we have an
undocumented feature where dtype(some_array_or_numpy_scalar) will return the
dtype of that value. Plain Python ints and floats don't have a dtype attached to
them, so we raise an exception.
If you have more numpy questions, please join us on the numpy-discussion mailing
list.
http://www.scipy.org/Mailing_Lists
--
Robert Kern
"I have come to believe that the whole world is an enigma, a harmless enigma
that is made terrible by our own mad attempt to interpret it as though it had
an underlying truth."
-- Umberto Eco
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