On Sun, Mar 6, 2011 at 11:12 PM, Ralf Gommers
<ralf.gomm...@googlemail.com> wrote:
> On Sun, Mar 6, 2011 at 1:10 AM, Skipper Seabold <jsseab...@gmail.com> wrote:
>> On Sat, Mar 5, 2011 at 9:28 AM, Ralf Gommers
>> <ralf.gomm...@googlemail.com> wrote:
>>> On Sat, Mar 5, 2011 at 8:09 AM, Russell E. Owen <ro...@uw.edu> wrote:
>>>> The page <http://docs.scipy.org/doc/numpy/user/basics.rec.html>
>>>>
>>>> gives a good introduction to structured arrays. However, it says nothing
>>>> about how to set a particular element (all fields at once) from a
>>>> collection of data.
>>>>
>>>> For instance:
>>>>
>>>> stArr = numpy.zeros([4,5], dtype=[("pos", float, (2,)), ("rot", float)])
>>>>
>>>> The question is how to set stArr[0]?
>>>>
>>>> >From experimentation it appears that you can provide a tuple, but not a
>>>> list. Hence the following works just fine (and that the tuple can
>>>> contain a list):
>>>> strArr[0,0] = ([1.0, 1.1], 2.0)
>>>>
>>>> but the following fails:
>>>> strArr[0,0] = [[1.0, 1.1], 2.0]
>>>> with an error:
>>>> TypeError: expected a readable buffer object
>>>>
>>>> This is useful information if one is trying to initialize a structured
>>>> array from a collection of data, such as that returned from a database
>>>> query.
>>>>
>>
>> I added a bit at the end here, though it is mentioned briefly above.
>> Feel free to expand. It's a wiki. You just need edit rights.
>>
>> http://docs.scipy.org/numpy/docs/numpy.doc.structured_arrays/
>
> Thanks, I'll make sure that goes in for 1.6.0.
>
>>> I'm wondering if that's not a bug? If it's intentional then it is
>>> certainly counterintuitive.
>>>
>>
>> This comes up from time to time.
>>
>> http://thread.gmane.org/gmane.comp.python.numeric.general/30793/focus=30793
>>
>> Perhaps an enhancement ticket could be filed? It doesn't sound trivial
>> to implement.
>
> I filed #1758.
>
> You can also assign with an array which fails silently, certainly a bug:
>
>>>> arr = np.zeros((5,), dtype=[('var1','f8'),('var2','f8')])
>>>> arr['var1'] = np.arange(5)
>>>> arr[0] = (10,20)
>>>> arr[0]
> (10.0, 20.0)
>
>>>> arr[0] = np.array([10,20]) # no exception, but garbage out
>>>> arr[0]
> (4.2439915824246103e-313, 0.0)
>
This is a casting issue. Your array is an integer array. You can
assign with an array.
arr = np.zeros((5,), dtype=[('var1','f8'),('var2','f8')])
arr[0] = np.array([10.0,20])
arr[0]
(10.0, 20.0)
Skipper
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