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Returning only the real part of the FFT

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This commit is contained in:
Fabio Manganiello 2018-12-27 22:47:44 +01:00
parent 01006046e0
commit fae45d8ca3
1 changed files with 8 additions and 6 deletions
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14
platypush/plugins/sound/core.py
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@ -160,8 +160,8 @@ class Sound(object):
def fft(self, t_start=0., t_end=0., samplerate=_DEFAULT_SAMPLERATE, def fft(self, t_start=0., t_end=0., samplerate=_DEFAULT_SAMPLERATE,
freq_range=None, freq_buckets=None): freq_range=None, freq_buckets=None):
""" """
Get the Fourier transform associated to a time-bounded sample of this Get the real part of the Fourier transform associated to a time-bounded
sound sample of this sound
:param t_start: Start offset for the wave in seconds. Default: 0 :param t_start: Start offset for the wave in seconds. Default: 0
:type t_start: float :type t_start: float
@ -189,7 +189,8 @@ class Sound(object):
freq_range = (0, int(samplerate/2)) freq_range = (0, int(samplerate/2))
wave = self.get_wave(t_start=t_start, t_end=t_end, samplerate=samplerate) wave = self.get_wave(t_start=t_start, t_end=t_end, samplerate=samplerate)
fft = np.fft.fft(wave.reshape(len(wave)))[freq_range[0]:freq_range[1]] fft = np.fft.fft(wave.reshape(len(wave)))
fft = fft.real[freq_range[0]:freq_range[1]]
if freq_buckets is not None: if freq_buckets is not None:
fft = np.histogram(fft, bins=freq_buckets) fft = np.histogram(fft, bins=freq_buckets)
@ -321,8 +322,8 @@ class Mix(object):
def fft(self, t_start=0., t_end=0., samplerate=Sound._DEFAULT_SAMPLERATE, def fft(self, t_start=0., t_end=0., samplerate=Sound._DEFAULT_SAMPLERATE,
freq_range=None, freq_buckets=None): freq_range=None, freq_buckets=None):
""" """
Get the Fourier transform associated to a time-bounded sample of this Get the real part of the Fourier transform associated to a time-bounded
mix sample of this mix
:param t_start: Start offset for the wave in seconds. Default: 0 :param t_start: Start offset for the wave in seconds. Default: 0
:type t_start: float :type t_start: float
@ -350,7 +351,8 @@ class Mix(object):
freq_range = (0, int(samplerate/2)) freq_range = (0, int(samplerate/2))
wave = self.get_wave(t_start=t_start, t_end=t_end, samplerate=samplerate) wave = self.get_wave(t_start=t_start, t_end=t_end, samplerate=samplerate)
fft = np.fft.fft(wave.reshape(len(wave)))[freq_range[0]:freq_range[1]] fft = np.fft.fft(wave.reshape(len(wave)))
fft = fft.real[freq_range[0]:freq_range[1]]
if freq_buckets is not None: if freq_buckets is not None:
fft = np.histogram(fft, bins=freq_buckets) fft = np.histogram(fft, bins=freq_buckets)