Jean-Baptiste Rudant wrote:
> Hello,
>
> I like to use record arrays to access fields by their name, and because
> they are esay to use with pytables. But I think it's not very effiicient
> for what I have to do. Maybe I'm misunderstanding something.
>
> Example :
>
> import numpy as np
> age = np.random.randint(0, 99, 10e6)
> weight = np.random.randint(0, 200, 10e6)
> data = np.rec.fromarrays((age, weight), names='age, weight')
> # the kind of operations I do is :
> data.age += data.age + 1
> # but it's far less efficient than doing :
> age += 1
> # because I think the record array stores [(age_0, weight_0) ...(age_n,
> weight_n)]
> # and not [age0 ... age_n] then [weight_0 ... weight_n].
>
> So I think I don't use record arrays for the right purpose. I only need
> something which would make me esasy to manipulate data by accessing
> fields by their name.
>
> Am I wrong ? Is their something in numpy for my purpose ? Do I have to
> implement my own class, with something like :
>
>
> class FieldArray:
> def __init__(self, array_dict):
> self.array_list = array_dict
>
> def __getitem__(self, field):
> return self.array_list[field]
>
> def __setitem__(self, field, value):
> self.array_list[field] = value
>
> my_arrays = {'age': age, 'weight' : weight}
> data = FieldArray(my_arrays)
>
> data['age'] += 1
You can accomplish what your FieldArray class does using numpy dtypes:
import numpy as np
dt = np.dtype([('age', np.int32), ('weight', np.int32)])
N = int(10e6)
data = np.empty(N, dtype=dt)
data['age'] = np.random.randint(0, 99, 10e6)
data['weight'] = np.random.randint(0, 200, 10e6)
data['age'] += 1
Timing for recarrays (your code):
In [10]: timeit data.age += 1
10 loops, best of 3: 221 ms per loop
Timing for my example:
In [2]: timeit data['age']+=1
10 loops, best of 3: 150 ms per loop
Hope this helps.
Ryan
--
Ryan May
Graduate Research Assistant
School of Meteorology
University of Oklahoma
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