Quick start <quick_start>
Usage of AnalyzerResult <AnalyzerResult>
Running a pipe with previously decoded frames <frames_stack>
- Streaming encoded audio outside TimeSide <Streaming>
+ Streaming out encoded audio <Streaming>
>>> from timeside.tools.test_samples import samples
>>> audio_source = samples['sweep.wav']
>>> decoder = get_processor('file_decoder')(uri=audio_source)
- >>> spectrogram = get_processor('spectrogram_analyzer')(input_blocksize=2048, input_stepsize=1024)
+ >>> spectrogram = get_processor('spectrogram_analyzer_buffer')(input_blocksize=2048, input_stepsize=1024)
>>> pipe = (decoder | spectrogram)
>>> pipe.run()
>>> spectrogram.results.keys()
- ['spectrogram_analyzer']
- >>> result = spectrogram.results['spectrogram_analyzer']
+ ['spectrogram_analyzer_buffer']
+ >>> result = spectrogram.results['spectrogram_analyzer_buffer']
>>> result.data.shape
(344, 1025)
from timeside.tools.test_samples import samples
audio_source = samples['sweep.wav']
decoder = get_processor('file_decoder')(uri=audio_source)
- spectrogram = get_processor('spectrogram_analyzer')(input_blocksize=2048,
+ spectrogram = get_processor('spectrogram_analyzer_buffer')(input_blocksize=2048,
input_stepsize=1024)
pipe = (decoder | spectrogram)
pipe.run()
- res = spectrogram.results['spectrogram_analyzer']
+ res = spectrogram.results['spectrogram_analyzer_buffer']
res.render()
"""