Audio#
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import numpy as np
import panel as pn
pn.extension()
The Audio
pane displays an audio player given a local or remote audio file, NumPy ndarray or a Torch Tensor.
The pane also allows access and control over the player state including toggling of playing/paused
and loop
state, the current time
, and the volume
.
The audio player supports ogg
, mp3
, and wav
file formats
If SciPy is installed, 1-dim Numpy ndarrys and 1-dim Torch Tensors are also supported. The dtype must be one of the following
numpy: np.int16, np.uint16, np.float32, np.float64
torch: torch.short, torch.int16, torch.half, torch.float16, torch.float, torch.float32, torch.double, torch.float64
The array or tensor input will be downsampled to 16bit and converted to a wav file by SciPy.
Parameters:#
For details on other options for customizing the component see the layout and styling how-to guides.
autoplay
(boolean): When True, it specifies that the output will play automatically. In Chromium browsers this requires the user to click play onceloop
(boolean): Whether to loop when reaching the end of playbackmuted
(boolean): When True, it specifies that the output should be mutedname
(str): The title of the paneobject
(string): Local file path, remote URL pointing to audio file, 1-dim numpy array or 1-dim torch tensorpaused
(boolean): Whether the player is pausedsample_rate
(int): The sample_rate of the audio when given a NumPy array or Torch Tensor. Default is 44100.throttle
(int): How frequently to sample the current playback in millisecondstime
(float): Current playback time in secondsvolume
(int): Volume in the range 0-100
The Audio
pane can be constructed with a URL pointing to a remote audio file or a local audio file (in which case the data is embedded).
audio = pn.pane.Audio('https://ccrma.stanford.edu/~jos/mp3/pno-cs.mp3', name='Audio')
audio
The player can be controlled using its own widgets, as well as by using Python code as follows. To pause or unpause it in code, use the paused
property:
#audio.paused = False
The current player time
can be read and set with the time variable (in seconds):
audio.time
The volume
may also be read and set:
audio.volume = 50
When providing a NumPy Array or Torch Tensor, you should specify the sample_rate
.
In this example we plot a frequency modulated signal:
sps = 44100 # Samples per second
duration = 10 # Duration in seconds
modulator_frequency = 2.0
carrier_frequency = 120.0
modulation_index = 2.0
time = np.arange(sps*duration) / sps
modulator = np.sin(2.0 * np.pi * modulator_frequency * time) * modulation_index
carrier = np.sin(2.0 * np.pi * carrier_frequency * time)
waveform = np.sin(2. * np.pi * (carrier_frequency * time + modulator))
waveform_quiet = waveform * 0.3
pn.pane.Audio(waveform_quiet, sample_rate=sps)