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"""Functions used to transform and manipulate audio for use by visualizers"""
from copy import copy
import numpy
def createSpectrumArray(
component,
completeAudioArray,
sampleSize,
smoothConstantDown,
smoothConstantUp,
scale,
progressBarUpdate,
progressBarSetText,
):
lastProgress = 0
lastSpectrum = None
spectrumArray = {}
for i in range(0, len(completeAudioArray), sampleSize):
if component.canceled:
break
lastSpectrum = transformData(
i,
completeAudioArray,
sampleSize,
smoothConstantDown,
smoothConstantUp,
lastSpectrum,
scale,
)
spectrumArray[i] = copy(lastSpectrum)
progress = int(100 * (i / len(completeAudioArray)))
if progress >= 100:
progress = 100
if progress == lastProgress:
continue
progressText = f"Analyzing audio: {str(progress)}%"
progressBarSetText.emit(progressText)
progressBarUpdate.emit(int(progress))
lastProgress = progress
return spectrumArray
def transformData(
i,
completeAudioArray,
sampleSize,
smoothConstantDown,
smoothConstantUp,
lastSpectrum,
scale,
):
if len(completeAudioArray) < (i + sampleSize):
sampleSize = len(completeAudioArray) - i
window = numpy.hanning(sampleSize)
data = completeAudioArray[i : i + sampleSize][::1] * window
paddedSampleSize = 2048
paddedData = numpy.pad(data, (0, paddedSampleSize - sampleSize), "constant")
spectrum = numpy.fft.fft(paddedData)
sample_rate = 44100
frequencies = numpy.fft.fftfreq(len(spectrum), 1.0 / sample_rate)
y = abs(spectrum[0 : int(paddedSampleSize / 2) - 1])
# filter the noise away
# y[y<80] = 0
with numpy.errstate(divide="ignore"):
y = scale * numpy.log10(y)
y[numpy.isinf(y)] = 0
if lastSpectrum is not None:
lastSpectrum[y < lastSpectrum] = y[
y < lastSpectrum
] * smoothConstantDown + lastSpectrum[y < lastSpectrum] * (
1 - smoothConstantDown
)
lastSpectrum[y >= lastSpectrum] = y[
y >= lastSpectrum
] * smoothConstantUp + lastSpectrum[y >= lastSpectrum] * (1 - smoothConstantUp)
else:
lastSpectrum = y
x = frequencies[0 : int(paddedSampleSize / 2) - 1]
return lastSpectrum
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