[SciPy-User] Using scipy.signal.fftconvolve() and scipy.signal.convolve()

[josef.pktd at gmail.com]

On Tue, Jan 18, 2011 at 9:21 PM, Chris Rodgers
<chris.rodgers at berkeley.edu> wrote:
> While the output from the convolution statements looks qualitatively
> correct to me, I always have difficulty interpreting them because I
> don't know the "lags" associated with each value. By lag I mean the
> amount by which one signal was delayed before calculating the dot
> product of the two signals. In Matlab for example, the conv function
> returns both the values and a separate array called "lags" of the same
> size, which is very helpful.
>
> The scipy documentation is not very clear on this point. Does anyone
> know a good resource documenting the lags in each of the 3 modes of
> operation ('same', 'valid', 'full')? I tried convolving dummy
> sequences ([0,1,0,0] etc) but I couldn't figure it out.

valid and full have a clear definition
for valid, signal convolve cuts on both sides symmetrically, I think.
I wrote some helper functions, so I don't have to think. And I found
the comparison
with ndimage useful, because it has an option for this.

integer is start, decimal is end, if I did it correctly:

>>> from scipy.signal import convolve
>>> convolve(np.arange(1,10), [0.1, 0, 1], mode='valid')
array([ 1.3,  2.4,  3.5,  4.6,  5.7,  6.8,  7.9])
>>> convolve(np.arange(1,10), [0.1, 0, 1], mode='full')
array([ 0.1,  0.2,  1.3,  2.4,  3.5,  4.6,  5.7,  6.8,  7.9,  8. ,  9. ])
>>> convolve(np.arange(1,10), [0.1, 0, 1], mode='same')
array([ 0.2,  1.3,  2.4,  3.5,  4.6,  5.7,  6.8,  7.9,  8. ])

not so clear with even length window

>>> convolve(np.arange(1,10), [0.1, 0, 0, 1], mode='full')
array([ 0.1,  0.2,  0.3,  1.4,  2.5,  3.6,  4.7,  5.8,  6.9,  7. ,  8. ,
        9. ])
>>> convolve(np.arange(1,10), [0.1, 0, 0, 1], mode='same')
array([ 0.2,  0.3,  1.4,  2.5,  3.6,  4.7,  5.8,  6.9,  7. ])

>>> convolve(np.arange(1,10), [0.1, 0, 0,0, 1], mode='full')
array([ 0.1,  0.2,  0.3,  0.4,  1.5,  2.6,  3.7,  4.8,  5.9,  6. ,  7. ,
        8. ,  9. ])
>>> convolve(np.arange(1,10), [0.1, 0, 0,0, 1], mode='same')
array([ 0.3,  0.4,  1.5,  2.6,  3.7,  4.8,  5.9,  6. ,  7. ])

I think I usually avoided same

Josef

>
> Thanks!!
> Chris
>
>
>
> On Tue, Jan 18, 2011 at 1:19 PM, David Baddeley
> <david_baddeley at yahoo.com.au> wrote:
>> What you're getting form fftconvolve looks about right - with ordinary convolve
>> I suspect your problem might be that you're using 8 bit ints and it's
>> overflowing & thus giving you the random noise pattern. Ffts cast their inputs
>> to double first. I'd suggest casting your image to float - ie:
>> a = a.astype('f')
>> before doing the standard convolutions.
>>
>> cheers,
>> David
>>
>>
>> ----- Original Message ----
>> From: Ábel Dániel <abli at freemail.hu>
>> To: scipy-user <scipy-user at scipy.org>
>> Sent: Wed, 19 January, 2011 8:58:28 AM
>> Subject: [SciPy-User] Using scipy.signal.fftconvolve() and
>> scipy.signal.convolve()
>>
>> [apologies if this might get duplicated, it appears my first
>> submission didn't show up on the mailling list]
>>
>> Hi!
>>
>> I would like to ask some help with the use of scipy.signal.convolve
>> and scipy.signal.fftconvolve. (On a greyscale 2d image.)
>>
>> Based on the documentation of fftconvolve (which is simply 'See
>> convolve.'), I am assuming that they should give (mostly) the same
>> result. (I.e. the result won't be exactly identical since they are
>> using different methods, but they shouldn't be too different.)
>>
>> However, I am getting drastically different results: using convolve
>> results in basically random noise, while fftconvolve gives a very
>> sharp peak.
>>
>> I uploaded a short program with the input and the results I am getting
>> to http://hal.elte.hu/~abeld/scipy_signal_issue/
>>
>> Am I doing something wrong? Should there be such a difference in the
>> output of these functions? What is causing the difference?
>>
>> (I am using Ubuntu Lucid, version of python-scipy package is
>> 0.7.0-2ubuntu0.1)
>>
>> Thanks in advance,
>> Daniel Abel
>> abli at freemail.hu
>>
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