[SciPy-Dev] Strange code in scipy.signal.decimate

[Eric Quintero]

Warren is correct; there were some changes to how the `dlti` objects were being internally passed around on PR 7835, and this extra instantiation flew under the radar. A PR to simplify the code would be very welcome.

-Eric Q.

> On Oct 18, 2018, at 7:07 PM, Warren Weckesser <warren.weckesser at gmail.com> wrote:
> 
> On 10/18/18, Daniele Nicolodi <daniele at grinta.net> wrote:
>> On 18-10-2018 15:28, Paul Hobson wrote:
>>> Dan,
>>> 
>>> I might be missing something, but dlti returns a subclass of
>>> LinearTimeInvariant. Point is, it's not a tuple, but a class with
>>> multiple attributes and method. Simple tuple unpacking won't likely work
>>> unless the authors of LinearTimeInvariant really went out of their way
>>> to make it so.
>> 
>> The point is not to go through the `dlti` class at all.
>> 
>> Please look at the replacement code I posted: it works.
>> 
> 
> 
> There have been several incremental changes to that function over the
> years.  I suspect the last person to change it simply did not notice
> that the code could be simplified.  Your proposed change looks good.
> 
> Warren
> 
> 
>> Cheers,
>> Dan
>> 
>>> -Paul
>>> 
>>> On Thu, Oct 18, 2018 at 1:58 PM Daniele Nicolodi <daniele at grinta.net
>>> <mailto:daniele at grinta.net>> wrote:
>>> 
>>>    Hello,
>>> 
>>>    I was having a look at the scipy.signal.decimate() function and I
>>>    noticed some strange looking code:
>>> 
>>>        elif ftype == 'iir':
>>>            if n is None:
>>>                n = 8
>>>            system = dlti(*cheby1(n, 0.05, 0.8 / q))
>>>            b, a = system.num, system.den
>>> 
>>>    This is used to setup the anti aliasing low pass filter. What I don't
>>>    understand is the dance to obtain the IIR numerator and denominator
>>>    coefficients. Couldn't the above be simply as the code below?
>>> 
>>>        elif ftype == 'iir':
>>>            if n is None:
>>>                n = 8
>>>            b, a = cheby1(n, 0.05, 0.8 / q)
>>> 
>>>    Am I missing something?
>>> 
>>>    Thanks!
>>> 
>>>    Cheers,
>>>    Dan
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>> 
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