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librosa.chirp¶
- librosa.chirp(fmin, fmax, sr=22050, length=None, duration=None, linear=False, phi=None)[source]¶
Construct a “chirp” or “sine-sweep” signal.
The chirp sweeps from frequency
fmin
tofmax
(in Hz).- Parameters
- fminfloat > 0
initial frequency
- fmaxfloat > 0
final frequency
- srnumber > 0
desired sampling rate of the output signal
- lengthint > 0
desired number of samples in the output signal. When both
duration
andlength
are defined,length
takes priority.- durationfloat > 0
desired duration in seconds. When both
duration
andlength
are defined,length
takes priority.- linearboolean
If
True
, use a linear sweep, i.e., frequency changes linearly with timeIf
False
, use a exponential sweep.
Default is
False
.- phifloat or None
phase offset, in radians. If unspecified, defaults to
-np.pi * 0.5
.
- Returns
- chirp_signalnp.ndarray [shape=(length,), dtype=float64]
Synthesized chirp signal
- Raises
- ParameterError
If either
fmin
orfmax
are not provided.If neither
length
norduration
are provided.
See also
Examples
Generate a exponential chirp from A2 to A8
>>> exponential_chirp = librosa.chirp(110, 110*64, duration=1)
Or generate the same signal using
length
>>> exponential_chirp = librosa.chirp(110, 110*64, sr=22050, length=22050)
Or generate a linear chirp instead
>>> linear_chirp = librosa.chirp(110, 110*64, duration=1, linear=True)
Display spectrogram for both exponential and linear chirps.
>>> import matplotlib.pyplot as plt >>> fig, ax = plt.subplots(nrows=2, sharex=True, sharey=True) >>> S_exponential = np.abs(librosa.stft(y=exponential_chirp)) >>> librosa.display.specshow(librosa.amplitude_to_db(S_exponential, ref=np.max), ... x_axis='time', y_axis='linear', ax=ax[0]) >>> ax[0].set(title='Exponential chirp', xlabel=None) >>> ax[0].label_outer() >>> S_linear = np.abs(librosa.stft(y=linear_chirp)) >>> librosa.display.specshow(librosa.amplitude_to_db(S_linear, ref=np.max), ... x_axis='time', y_axis='linear', ax=ax[1]) >>> ax[1].set(title='Linear chirp')