[SciPy-user] Create a spectrogram from a waveform
Mon Sep 1 10:41:52 CDT 2008
I tried to run the spectrogram.py example and I appear to be having
configuration problems. I have installed the latest enthought distro,
but the enable module can seem to find it's api component. Any thoughts?
~ jeff$ python
Enthought Python Distribution (2.5.2001) -- http://code.enthought.com
Python 2.5.2 |EPD 2.5.2001| (r252:60911, Jul 1 2008, 19:18:12)
[GCC 4.0.1 (Apple Computer, Inc. build 5370)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import spectrum.py
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "spectrum.py", line 19, in <module>
from enthought.enable.api import Window
ImportError: No module named api
On Aug 30, 2008, at 6:28 PM, Peter Wang wrote:
> Quoting Ed McCaffrey <firstname.lastname@example.org>:
>> I wrote a program in C# that creates a spectrogram from the
>> waveform of a
>> .wav music file. I now want to port it to Python, and I want to
>> try to use
>> SciPy instead of a direct port of the existing code, because I am
>> not sure
>> that it is perfectly accurate, and it is probably slow.
>> I am having a hard time finding out how to do this with SciPy.
>> With my
>> code, I had a FFT function that took an array of real and imaginary
>> components for each sample, and a second function taking both that
>> the amplitude. The FFT function in SciPy just takes one array.
>> Has anyone done this task in SciPy?
> We have a realtime spectrogram plot in the Audio Spectrum example for
> Chaco. (See the very last screenshot on the gallery page here:
> You can see the full source code of the example here:
> The lines you would be interested in are the last few:
> def get_audio_data():
> pa = PyAudio()
> stream = pa.open(format=paInt16, channels=1, rate=SAMPLING_RATE,
> string_audio_data = stream.read(NUM_SAMPLES)
> audio_data = fromstring(string_audio_data, dtype=short)
> normalized_data = audio_data / 32768.0
> return (abs(fft(normalized_data))[:NUM_SAMPLES/2],
> Here we are using the PyAudio library to directly read from the sound
> card, normalize the 16-bit data, and perform an FFT on it.
> In your case, since you are reading a WAV file, you might be
> interested in the zoomed_plot example:
> This displays the time-space signal but can easily be modified to show
> the FFT. Here is the relevant code that uses the built-in python
> 'wave' module to read the data:
> You should be able to take the 'data' array in the wav_to_numeric
> function and hand that in to the fft function.
> SciPy-user mailing list
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