[Numpy-discussion] fixed-point arithmetic
Robert Kern
robert.kern@gmail....
Mon Sep 21 12:09:51 CDT 2009
On Mon, Sep 21, 2009 at 12:02, Neal Becker <ndbecker2@gmail.com> wrote:
> Robert Kern wrote:
>
>> On Mon, Sep 21, 2009 at 10:57, Neal Becker <ndbecker2@gmail.com> wrote:
>>> David Cournapeau wrote:
>>>
>>>> On Mon, Sep 21, 2009 at 9:00 PM, Neal Becker <ndbecker2@gmail.com>
>>>> wrote:
>>>>>
>>>>> numpy arrays of fpi should support all numeric operations. Also mixed
>>>>> fpi/integer operations.
>>>>>
>>>>> I'm not sure how to go about implementing this. At first, I was
>>>>> thinking to just subclass numpy array. But, I don't think this
>>>>> provides fpi scalars, and their associated operations.
>>>>
>>>> Using dtype seems more straightforward. I would first try to see how
>>>> far you could go using a pure python object as a dtype. For example
>>>> (on python 2.6):
>>>>
>>>> from decimal import Decimal
>>>> import numpy as np
>>>> a = np.array([1, 2, 3], Decimal)
>>>> b = np.array([2, 3, 4], Decimal)
>>>> a + b
>>>>
>>>> works as expected. A lot of things won't work (e.g. most transcendent
>>>> functions, which would require a specific implementation anyway), but
>>>> arithmetic, etc... would work.
>>>>
>>>> Then, you could think about implementing the class in cython. If speed
>>>> is an issue, then implementing your own dtype seems the way to go - I
>>>> don't know exactly what kind of speed increase you could hope from
>>>> going the object -> dtype, though.
>>>>
>>>
>>> We don't want to create arrays of fixed-pt objects. That would be very
>>> wasteful. What I have in mind is that integer_bits, frac_bits are
>>> attributes of the entire arrays, not the individual elements. The array
>>> elements are just plain integers.
>>>
>>> At first I'm thinking that we could subclass numpy array, adding the
>>> int_bits and frac_bits attributes. The arithmetic operators would all
>>> have to be overloaded.
>>>
>>> The other aspect is that accessing an element of the array would return a
>>> fixed-pt object (not an integer).
>>
>> Actually, what you would do is create a new dtype, not a subclass of
>> ndarray. The new datetime dtypes are similar in that they too are
>> "parameterized" dtypes.
>
> But doesn't this mean that each array element has it's own int_bits,
> frac_bits attributes? I don't want that.
No, I'm suggesting that the dtype has the int_bits and frac_bits
information just like the new datetime dtypes have their unit
information.
--
Robert Kern
"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth."
-- Umberto Eco
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