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From: Travis Oliphant <travis <at> continuum.io>
Subject: Re: Fwd: Named dtype array: Difference between a[0]['name'] and a['name'][0]?
Newsgroups: gmane.comp.python.numeric.general
Date: Monday 21st May 2012 20:37:36 UTC (over 4 years ago)
This is the right place to ask, it's just that it can take time to get an
answer because people who might know the answer may not have the time to
respond immediately.  

The short answer is that this is not really a "normal" bug, but it could be
considered a "design" bug (although the issues may not be straightforward
to resolve).    What that means is that it may not be changed in the short
term --- and you should just use the first spelling. 

Structured arrays can be a confusing area of NumPy for several of reasons. 
 You've constructed an example that touches on several of them.   You have
a data-type that is a "structure" array with one member ("tuple").  That
member contains a 2-vector of integers.  

First of all, it is important to remember that with Python, doing
a['tuple'][0] = (1,2) is equivalent to b = a['tuple']; b[0] = (1,2).   In
like manner, a[0]['tuple'] = (1,2) is equivalent to b = a[0]; b['tuple'] =

To understand the behavior, we need to dissect both code paths and what
happens.   You built a (3,) array of those elements in 'a'.  When you write
b = a['tuple'] you should probably be getting a (3,) array of
(2,)-integers, but as there is currently no formal dtype support for
(n,)-integers as a general dtype in NumPy, you get back a (3,2) array of
integers which is the closest thing that NumPy can give you.    Setting the
[0] row of this object via 

a['tuple'][0] = (1,2)

works just fine and does what you would expect. 

On the other hand, when you type: 

b = a[0]

you are getting back an array-scalar which is a particularly interesting
kind of array scalar that can hold records.    This new object is formally
of type numpy.void and it holds a "scalar representation" of anything that
fits under the "VOID" basic dtype.  

For some reason: 

b['tuple'] = [1,2] 

is not working.   On my system I'm getting a different error: TypeError:
object of type 'int' has no len()

I think this should be filed as a bug on the issue tracker which is for the
time being here:    http://projects.scipy.org/numpy

The problem is ultimately the void->copyswap function being called in
voidtype_setfields if someone wants to investigate.   I think this behavior
should work. 


On May 21, 2012, at 1:50 PM, bmu wrote:

> dear all,
> can anybody tell me, why nobody is answering this question? is this the
> place to ask? or does nobody know an answer?
> björn
> From: bmu 
> Subject: Named dtype array: Difference between a[0]['name'] and
> Date: May 20, 2012 6:45:03 AM CDT
> To: [email protected]
> I came acroos a question on stackoverflow (http://stackoverflow.com/q/9470604)
and I am wondering if this is a bug
> import numpy as np
> dt = np.dtype([('tuple', (int, 2))])
> a = np.zeros(3, dt)
> type(a['tuple'][0])  # ndarray
> type(a[0]['tuple'])  # ndarray
> a['tuple'][0] = (1,2)  # ok
> a[0]['tuple'] = (1,2)  # ValueError: shape-mismatch on array construction
> Could somebody explain this behaviour (either in this mailing list or on
> bmu
> _______________________________________________
> NumPy-Discussion mailing list
> [email protected]
> http://mail.scipy.org/mailman/listinfo/numpy-discussion
CD: 3ms