[Numpy-discussion] fixed-point arithmetic

Neal Becker ndbecker2@gmail....
Mon Sep 21 12:39:20 CDT 2009

Robert Kern wrote:

> 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.
1. Where would I find this new datetime dtype?

2. Don't know exactly what 'parameterized' dtypes are.  Does this mean that 
the dtype for 8.1 format fixed-pt is different from the dtype for 6.2 
format, for example?

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