[Numpy-discussion] Request for a bit more info on structured arrays in the "basics" page

[Skipper Seabold]

On Tue, Mar 8, 2011 at 8:08 PM, Skipper Seabold <jsseabold at gmail.com> wrote:
> On Sun, Mar 6, 2011 at 11:12 PM, Ralf Gommers
> <ralf.gommers at googlemail.com> wrote:
>> On Sun, Mar 6, 2011 at 1:10 AM, Skipper Seabold <jsseabold at gmail.com> wrote:
>>> On Sat, Mar 5, 2011 at 9:28 AM, Ralf Gommers
>>> <ralf.gommers at googlemail.com> wrote:
>>>> On Sat, Mar 5, 2011 at 8:09 AM, Russell E. Owen <rowen at 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)
>

FYI, I fixed the docs to reflect this.

I know numpy is already pretty verbose by default, but should the
integer case throw up a warning similar to casting from complex to
real?

>>> x = np.zeros(2)
>>> x[:] = np.array([1+1j,1+1j])
ComplexWarning: Casting complex values to real discards the imaginary part

Skipper