On 9/18/11 10:55 AM, Alex van der Spek wrote:
Why does this not work?
dat=[[1,2,3],[4,5,6]]
col=[('a','f4'),('b','f4'),('c','f4')]
arr=numpy.array(dat,dtype=col)
Traceback (most recent call last):
File "<pyshell#91>", line 1, in <module>
arr=numpy.array(dat,dtype=col)
TypeError: expected a readable buffer object
But this does:
dat=[(1,2,3),(4,5,6)]
arr=numpy.array(dat,dtype=col)
arr
array([(1.0, 2.0, 3.0), (4.0, 5.0, 6.0)], dtype=[('a', '<f4'), ('b', '<f4'),
('c', '<f4')])
The only difference that the object is a list of tuples now?
numpy questions are best asked on the numpy mailing list:
http://www.scipy.org/Mailing_Lists
To answer your question, though, numpy.array() needs to figure out a lot of
different things about the input data simultaneously, in particular its shape.
Structured arrays (i.e. with elements that have individual fields as above) pose
a new problem in that its individual elements are sequences themselves. In order
to help it decide whether it should recurse down into a sequence to find its
elements or decide that the sequence *is* an element in its own right, we
settled on the convention that tuples are to be considered elements and that
lists are sequences of elements.
--
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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