[SciPy-dev] Is this a bugfix for scipy.hilbert?
josef.pktd@gmai...
josef.pktd@gmai...
Thu Jan 14 22:27:34 CST 2010
On Thu, Jan 14, 2010 at 11:02 PM, <josef.pktd@gmail.com> wrote:
> On Thu, Jan 14, 2010 at 10:54 PM, <josef.pktd@gmail.com> wrote:
>> On Thu, Jan 14, 2010 at 10:24 PM, Ariel Rokem <arokem@berkeley.edu> wrote:
>>> Hi everyone,
>>>
>>> I have been trying to use scipy.signal.hilbert and I got the following
>>> puzzling result:
>>>
>>> In [22]: import scipy
>>>
>>> In [23]: scipy.__version__ #I have r6182
>>> Out[23]: '0.8.0.dev'
>>>
>>> In [24]: import scipy.signal as signal
>>>
>>> In [25]: a = np.random.rand(100,100)
>>>
>>> In [26]: np.abs(signal.hilbert(a[-1]))
>>> Out[26]:
>>> array([ 0.57567681, 0.25918624, 0.50207097, 0.51834052, 0.24293389,
>>> 0.5779464 , 0.6515758 , 0.89973173, 1.00275444, 0.37352935,
>>> 0.62332717, 0.93599749, 0.40651376, 0.65088756, 0.8332281 ,
>>> 0.5770101 , 0.9288512 , 0.46671906, 0.41536055, 0.71418068,
>>> 0.81250913, 0.07652627, 0.72939072, 0.26755626, 0.36396146,
>>> 0.59725999, 1.02264694, 0.41227986, 0.98122853, 0.71906675,
>>> 0.58582611, 0.77288117, 0.3217015 , 0.65261394, 0.11947618,
>>> 0.75632703, 0.43432935, 0.52182485, 1.0277177 , 1.01104986,
>>> 0.3023265 , 0.6024772 , 0.69257548, 0.55418735, 0.46259052,
>>> 0.25832231, 0.38278355, 0.45508532, 0.26215872, 0.34207947,
>>> 0.80704729, 0.80755477, 0.95317178, 0.97458885, 0.58762294,
>>> 0.82540618, 0.62005585, 0.82494646, 1.04221293, 0.14983027,
>>> 1.01571579, 0.99381328, 0.24158714, 0.84256569, 0.53418924,
>>> 0.24067628, 0.90489883, 1.02217747, 0.34988034, 0.5310065 ,
>>> 0.48135002, 1.03020269, 0.6013679 , 0.46062485, 0.3918485 ,
>>> 0.21554545, 0.31704519, 0.04868385, 0.1787766 , 0.37361852,
>>> 0.21977912, 0.7649772 , 0.77867281, 0.37684278, 0.64432638,
>>> 0.77494951, 0.87106309, 0.77611484, 0.52666801, 0.88683667,
>>> 0.69164967, 0.98618191, 0.84811375, 0.35934198, 0.32650478,
>>> 0.1752677 , 0.60574454, 0.5109132 , 0.52332287, 0.99777805])
>>>
>>> In [27]: np.abs(signal.hilbert(a))[-1]
>>> Out[27]:
>>> array([ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
>>> 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
>>> 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
>>> 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
>>> 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
>>> 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
>>> 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
>>> 0., 0., 0., 0., 0., 0., 0., 0., 0.])
>>>
>>>
>>> ----------------------------------------------------------------------
>>>
>>> I was expecting both of these to have the same values - am I missing
>>> something?
>>>
>>> I think that the following solves this issue, but now I am not that sure
>>> whether it does what it is supposed to do and I couldn't find a test for
>>> this in test_signaltools.py. Does anyone know of a good test-case for the
>>> analytic signal, that I could create for this?
>>>
>>> Index: scipy/signal/signaltools.py
>>> ===================================================================
>>> --- scipy/signal/signaltools.py (revision 6182)
>>> +++ scipy/signal/signaltools.py (working copy)
>>> @@ -1062,13 +1062,13 @@
>>> """
>>> x = asarray(x)
>>> if N is None:
>>> - N = len(x)
>>> + N = x.shape[-1]
>>> if N <=0:
>>> raise ValueError, "N must be positive."
>>> if iscomplexobj(x):
>>> print "Warning: imaginary part of x ignored."
>>> x = real(x)
>>> - Xf = fft(x,N,axis=0)
>>> + Xf = fft(x,N,axis=-1)
>>> h = zeros(N)
>>> if N % 2 == 0:
>>> h[0] = h[N/2] = 1
>>> @@ -1078,7 +1078,7 @@
>>> h[1:(N+1)/2] = 2
>>>
>>> if len(x.shape) > 1:
>>> - h = h[:, newaxis]
>>> + h = h[newaxis,:]
>>> x = ifft(Xf*h)
>>> return x
>>
>> I think your change would break the currently advertised behavior,
>> axis=0 (The transformation is done along the first axis)
>>
>> but fft and ifft have default axis=-1
>>
>> fft in hilbert uses axis=0 as in docstring
>> but ifft uses default axis=-1
>>
>> so, I would think the fix should be x = ifft(Xf*h, axis=0)
>>
>> But as it currently looks like the axis argument doesn't work anyway,
>> there wouldn't be much breakage if the axis would be included as an
>> argument and default to -1.
>> However, I don't know what the "standard" for scipy.signal is for default axis.
>>
>> Josef
>
> after adding axis to ifft:
>>>> print hilbert(aa).real
> [[ 0.82584851 0.15215031 0.14767381]
> [ 0.95021675 0.16803995 0.43562964]
> [ 0.13033881 0.06198952 0.70729614]
> [ 0.69409563 0.06962778 0.72552601]
> [ 0.34297612 0.50579001 0.86463304]
> [ 0.28355261 0.21626889 0.85165102]
> [ 0.49481491 0.21290645 0.71416814]
> [ 0.2645843 0.95783096 0.77514016]
> [ 0.38735994 0.14274852 0.56344808]
> [ 0.88084015 0.39879649 0.64949951]]
>>>> print hilbert(aa[:,:1]).real
> [[ 0.82584851]
> [ 0.95021675]
> [ 0.13033881]
> [ 0.69409563]
> [ 0.34297612]
> [ 0.28355261]
> [ 0.49481491]
> [ 0.2645843 ]
> [ 0.38735994]
> [ 0.88084015]]
>
> but it treats a 1d array as row vector and transforms along zero axis
> of length 1, and not along the length of the array.
> so another fix to handle 1d arrays correctly should be done
>
>>>> print hilbert(aa[:,1]).real
> [ 0.15215031 0.16803995 0.06198952 0.06962778 0.50579001 0.21626889
> 0.21290645 0.95783096 0.14274852 0.39879649]
>>>> aa[:,1]
> array([ 0.15215031, 0.16803995, 0.06198952, 0.06962778, 0.50579001,
> 0.21626889, 0.21290645, 0.95783096, 0.14274852, 0.39879649])
>>>>
there's something wrong with my example, the real part is the same
which confused me
it works correctly with 1d
>>> np.abs(hilbert(aa[:,0]))
array([ 0.83251128, 1.04487091, 0.27702083, 0.69901499, 0.49170197,
0.31227114, 0.49505637, 0.26461488, 0.61385196, 0.90716272])
>>> np.abs(hilbert(aa[:,:1])).T
array([[ 0.83251128, 1.04487091, 0.27702083, 0.69901499, 0.49170197,
0.31227114, 0.49505637, 0.26461488, 0.61385196, 0.90716272]])
>>> np.abs(hilbert(aa))[:,0]
array([ 0.83251128, 1.04487091, 0.27702083, 0.69901499, 0.49170197,
0.31227114, 0.49505637, 0.26461488, 0.61385196, 0.90716272])
besides reading the docstring, I don't know what hilbert is supposed
to be good for.
Josef
> Josef
>
>
>>
>>>
>>>
>>> Cheers,
>>>
>>> Ariel
>>> --
>>> Ariel Rokem
>>> Helen Wills Neuroscience Institute
>>> University of California, Berkeley
>>> http://argentum.ucbso.berkeley.edu/ariel
>>>
>>> _______________________________________________
>>> SciPy-Dev mailing list
>>> SciPy-Dev@scipy.org
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>>>
>>>
>>
>
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