LED矩陣上的音頻可視化器

Question

我需要播放音頻文件，並使它的內容以均衡器的方式放在8x8矩陣中，就像在Piccolo中所做的那樣，就像適用於BeagleBone或RaspberryPI的頻譜分析儀一樣。 不需要麥克風進行環境分析：在同一塊板上播放音樂時只需可視化即可。

Adafruit建立了一個庫，使leds矩陣控制變得容易，缺少的大部分是音頻分析，直到每個音頻塊的矩陣。

語言可能是C或C ++，但最好是Python語言，為此，有Timeside和aubio之類的優秀庫，但我找不到如何像Piccolo一樣填充led矩陣，即使我我們測試了一些例子。

Answer 1

要獲得粗略的8頻段，8級正在進行的頻譜估計（在Python中，使用numpy）：

import numpy as np

fftsize = 4096  # about 100ms at 44 kHz; each bin will be ~ 10 Hz
# Band edges to define 8 octave-wide ranges in the FFT output
binedges = [8, 16, 32, 64, 128, 256, 512, 1024, 2048]
nbins = len(binedges)-1
# offsets to get our 48 dB range onto something useful, per band
offsets = [4, 4, 4, 4, 6, 8, 10, 12]
# largest value in ledval
nleds = 8
# scaling of LEDs per doubling in amplitude
ledsPerDoubling = 1.0
# initial value of per-band energy history
binval = 0.001 * np.ones(nbins, np.float)
newbinval = np.zeros(nbins, np.float)
# How rapidly the displays decay after a peak (depends on how often we're called)
decayConst = 0.9

if not_done:
    # somehow tap into the most recent 30-100ms of audio.  
    # Assume we get 44 kHz mono back
    waveform = get_latest_waveform()
    # find spectrum
    spectrum = np.abs(np.fft.rfft(waveform[:fftsize]))
    # gather into octave bands
    for i in range(nbins-1):
        newbinval[i] = np.mean(spectrum[binedges[i]:binedges[i+1]])
    # Peak smoothing - decay slowly after large values
    binval = np.maximum(newbinval, decayConst*binval)
    # Quantize into values 0..8 as the number of leds to light in each column
    ledval = np.round(np.maximum(0, np.minimum(nleds, 
                                               ledsPerDoubling * np.log2(binval) 
                                               + offsets)))
    # Now illuminate ledval[i] LEDs in column i (0..7) ...

除了獲取最新的（4096點）波形外，這還可以給您帶來啟發。