[SciPy-User] masked recarray, recarray with one field of type "ndarray"
Sun Feb 19 10:52:25 CST 2012
In short: do recarrays support masking?
On Wed, Feb 1, 2012 at 11:36 AM, Gustavo Goretkin
> Thanks for the help! Now is there any way to mask elements of a
> recarray? I should explain the application because I think I may be
> going about this the wrong way:
> I'll be building a tree and each node will have some attributes (for
> example, a matrix). I often have to iterate through every node of the
> tree and do a calculation -- something that I could do in a vectorized
> way with NumPy if all the attributes were stored in an array. So I
> thought I could represent the tree as a recarray (that I'd
> occasionally need to grow).
> I'd also need to delete nodes from the tree occasionally. I'd
> accomplish this by masking entries of the recarray. When I needed to
> add a node to the tree, I'd try to populate a masked entry before
> going to the end of the array.
> On Tue, Jan 31, 2012 at 9:33 AM, Warren Weckesser
> <firstname.lastname@example.org> wrote:
>> On Tue, Jan 31, 2012 at 2:36 AM, Gustavo Goretkin
>> <email@example.com> wrote:
>>> Does a recarray support masking?
>>> Can I have a recarray where one of the fields is an M-by-N ndarray
>>> (not recarray) of some dtype?
>>> ex: a = np.recarray(shape=(10),formats=['i4','f8','3-by-3 ndarray of
>> Here's how it can be done with the dtype argument (in this case, the
>> "sub-arrays" are 3x5 float32):
>> In : dt = np.dtype([('id', int32), ('values', float32, (3,5))])
>> In : a = np.recarray(shape=(3,), dtype=dt)
>> In : a.id
>> Out: array([ 7, 2345536, 8585218])
>> In : a.id
>> Out: 7
>> In : a.values
>> array([[ 9.80908925e-45, 2.15997513e-37, 3.16079124e-39,
>> 1.18408375e-38, 2.81552923e-38],
>> [ 2.13004362e-37, -7.69011974e-02, 9.80908925e-45,
>> 9.80908925e-45, 3.62636667e-21],
>> [ 5.67059093e-24, 5.67095065e-24, 5.64768872e-24,
>> 7.86448908e+11, 0.00000000e+00]], dtype=float32)
>> In : a.values.shape
>> Out: (3, 5)
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