[SciPy-dev] FFT docstrings (was: Scipy Tutorial (and updating it))
Tom Grydeland
tom.grydeland@gmail....
Wed Dec 17 01:48:03 CST 2008
On Tue, Dec 16, 2008 at 6:05 PM, <jh@physics.ucf.edu> wrote:
> I like it! A lot!
Excellent! Thanks.
> I added the helper routines and defined the time and frequency domains
> near the top (and took out similar text near the bottom), fixed some
> commas, etc.
Looks good. I didn't like the parentheses "(each gets exactly half
the spectrum) in the discussion on real transforms", I think it is too
easy to misunderstand (as I did on first reading).
> I think all it needs now is examples.
Indeed. I'll see what I can do about that.
> One point: (I'm not sure it's worth putting these distinctions on the
> page, I'm just justifying a change I made.) Power is energy per unit
> time; the energy spectrum and power spectrum are colloquially the
> same.
I was fairly sure what I wrote was not correct, but that it could be
fixed. I hope what ends up in the docstring is correct, not just
colloquially.
> Both are proportional to the square of the amplitude spectrum.
> In areas where it matters, np.abs(A)**2 is the energy spectrum and
> varies with the signal length (longer signals have more energy). The
> power spectrum is the energy spectrum divided by the time span (in
> physical units) of the dataset, and is independent of the signal
> length. Both these must be adjusted by a constant to make the
> sampling rate not affect the output.
I think perhaps this should be included, it is clarifying.
> The zero channel of np.fft(a) is
> the mean, not the energy.
Well -- A[0], according to the definition in the first equation, is
simply the sum of all the values in the input vector (since k == 0,
all the exponentials are == 1). I would not call that the mean.
> The zero channel of np.abs(A)**2 is the
> total energy or power, each to within different constants.
Agree.
> --jh--
--
Tom Grydeland
<Tom.Grydeland@(gmail.com)>
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