[Numpy-discussion] Structured array? recarray? issue access by attribute name

Skipper Seabold jsseabold@gmail....
Sun Dec 5 22:22:04 CST 2010


On Sun, Dec 5, 2010 at 10:44 PM, Wai Yip Tung <tungwaiyip@yahoo.com> wrote:
> I'm trying to use numpy to manipulate CSV file. I'm looking for feature
> similar to relational database. So I come across a class recarray that
> seems to meet my need. And then I see other references of structured
> array. Are these just different name of the same feature?
>
> Also I encounter a problem trying to access an field by attribute name. I
> have
>
>
> In [303]: arr = np.array([
>    .....:     (1, 2.2, 0.0),
>    .....:     (3, 4.5, 0.0)
>    .....:     ],
>    .....:     dtype=[
>    .....:         ('unit',int),
>    .....:         ('price',float),
>    .....:         ('amount',float),
>    .....:     ]
>    .....: )
>
> In [304]: data0 = arr.view(recarray)
>
> In [305]: data0.price[0]
> Out[305]: 2.2000000000000002
>

You don't have to take a view as a recarray if you don't want to.  You
lose attribute lookup but gain some speed.

In [14]: arr['price']
Out[14]: array([ 2.2,  4.5])

>
>
> It works fine when I get a price vector and pick the first element of it.
> But if instead I select the first row and try to access its price
> attribute, it wouldn't work
>

I'm not sure why this doesn't work.  It looks like taking a view of
the structured array as a recarray does not cast the structs to
records  Is this a bug?  Note that you can do

In [19]: arr[0]['price']
Out[19]: 2.2000000000000002

In [20]: data0[0]['price']
Out[20]: 2.2000000000000002

also slicing seems to work

In [27]: data0[0:1].price
Out[27]: array([ 2.2])

Skipper

>
>
> In [306]: data0[0].price
> ---------------------------------------------------------------------------
> AttributeError                            Traceback (most recent call last)
>
> c:\Python26\Lib\site-packages\numpy\<ipython console> in <module>()
>
> AttributeError: 'numpy.void' object has no attribute 'price'
>
>
>
> Then I come across an alternative way to build a recarray. In that case
> both usage work fine.
>
>
>
> In [307]: data1 = np.rec.fromarrays(
>    .....:     [[1,3],[2.2,4.5],[0.0,0.0]],
>    .....:     names='unit,price,amount')
>
> In [309]: data1.price[0]
> Out[309]: 2.2000000000000002
>
> In [310]: data1[0].price
> Out[310]: 2.2000000000000002
>
>
> What's going on here?
>
>
> Wai Yip
>
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