Update Audio FFT example.
-import image, audio, time, array, math, ulab as np
-from ulab import extras, numerical
+import image, audio, time
+from ulab import numpy as np
+from ulab import scipy as sp
SIZE = 512//4
-pcm_buf = None
+raw_buf = None
fb = image.Image(SIZE+50, SIZE, image.RGB565, copy_to_fb=True)
audio.init(channels=2, frequency=16000, gain=24, highpass=0.9883)
def audio_callback(buf):
- global pcm_buf
- if (pcm_buf == None):
- pcm_buf = np.array(array.array('h', buf))
+ # NOTE: do Not call any function that allocates memory.
+ global raw_buf
+ if (raw_buf == None):
+ raw_buf = buf
# Start audio streaming
audio.start_streaming(audio_callback)
def draw_fft(img, fft_buf):
fft_buf = (fft_buf / max(fft_buf)) * SIZE
- fft_buf = np.vector.log10(fft_buf + 1) * 20
+ fft_buf = np.log10(fft_buf + 1) * 20
color = (0xFF, 0x0F, 0x00)
for i in range(0, SIZE):
img.draw_line(i, SIZE, i, SIZE-int(fft_buf[i]), color, 1)
@@ -29,12 +31,13 @@ def draw_audio_bar(img, level, offset):
fb.draw_rectangle(SIZE+offset, SIZE - ((i+1)*blk_size) + blk_space, 20, blk_size - blk_space, color, 1, True)
while (True):
- if (pcm_buf != None):
+ if (raw_buf):
+ pcm_buf = np.frombuffer(raw_buf, dtype=np.int16)
+ raw_buf = None
+ fft_buf = sp.signal.spectrogram(pcm_buf[0::2])
+ l_lvl = int((np.mean(abs(pcm_buf[1::2])) / 32768)*100)
+ r_lvl = int((np.mean(abs(pcm_buf[0::2])) / 32768)*100)
fb.clear()
- fft_buf = extras.spectrogram(pcm_buf[0::2])
- l_lvl = int((numerical.mean(abs(pcm_buf[1::2])) / 32768)*100)
- r_lvl = int((numerical.mean(abs(pcm_buf[0::2])) / 32768)*100)
- pcm_buf = None
draw_fft(fb, fft_buf)
draw_audio_bar(fb, l_lvl, 0)
draw_audio_bar(fb, r_lvl, 25)
