mirror of
https://github.com/brmlab/ledbar.git
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139 lines
3.3 KiB
Python
Executable file
139 lines
3.3 KiB
Python
Executable file
#!/usr/bin/python
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# vim:et:sw=4:ts=4:sts=4
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import pyaudio
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import struct
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import math
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import numpy as np
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import time
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import sys
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import getopt
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from datetime import datetime
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import ledbar
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CHUNK_SIZE = 1024
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FORMAT = pyaudio.paInt16
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CHANNELS = 1
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RATE = 44100
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PIXELS = 20
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SLOW = 0
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HISTORY_SIZE = 4
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MIN_FREQ = 50
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MAX_FREQ = 12000
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def print_usage():
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print '''\
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USAGE:
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%s [-n number] [-h]
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OPTIONS:
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-n number number of controlled boxes
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-s slow mode
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-h --help show this help
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''' % sys.argv[0]
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try:
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opts, args = getopt.getopt(sys.argv[1:], 'n:sh', ['help'])
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except getopt.GetOptError:
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print_usage()
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sys.exit(1)
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if len(args):
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print_usage()
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sys.exit(1)
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for k, v in opts:
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if k == '-n':
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if not v.isdigit():
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print_usage()
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sys.exit(1)
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PIXELS = int(v)
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elif k == '-s':
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SLOW = 1
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elif k == '-h' or k == '--help':
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print_usage()
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sys.exit(0)
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if SLOW == 1:
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HISTORY_SIZE = 12
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SAMPLE_SIZE = CHUNK_SIZE*HISTORY_SIZE
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FREQ_STEP = float(RATE) / (CHUNK_SIZE * HISTORY_SIZE)
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PIXEL_FREQ_RANGE = math.pow(float(MAX_FREQ) / MIN_FREQ, 1.0/PIXELS)
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p = pyaudio.PyAudio()
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stream = p.open(format = FORMAT,
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channels = CHANNELS,
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rate = RATE,
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input = True,
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frames_per_buffer = CHUNK_SIZE)
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def get_color(volume):
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p = 1-15/(volume)
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if p <= 0: return (0, 0, 0)
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# Monochromatic mode:
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# p = p * p * p * p * p * p * p
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# return (0, p/4, p) # or any other combination
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if SLOW == 1:
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p *= p
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else:
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p *= p * p
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if p <= 0.4: return (0, 0, p*2.5)
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elif p <= 0.7: return (0, (p-0.4)*3.33, 1.0-(p-0.4)*3.33)
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elif p <= 0.9: return ((p-0.7)*5.0, 1.0-(p-0.7)*5.0, 0.0)
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else: return (1.0, (p-0.9)*10.0, (p-0.9)*10.0)
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l = ledbar.Ledbar(PIXELS)
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history = []
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window = np.array([0.5*(1-math.cos(2*math.pi*i/(SAMPLE_SIZE-1))) for i in xrange(SAMPLE_SIZE)])
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work = True
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nexttrig = 0
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try:
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while work:
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try: data = stream.read(CHUNK_SIZE)
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except IOError: continue
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nowtrig = datetime.now().microsecond / 50000
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if (nowtrig == nexttrig):
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continue
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else:
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nexttrig = nowtrig
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if len(data) == 0: break
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indata = np.array(struct.unpack('%dh'%CHUNK_SIZE,data))
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history.append(indata)
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if len(history) > HISTORY_SIZE: history.pop(0)
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elif len(history) < HISTORY_SIZE: continue
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fft = np.fft.rfft(np.concatenate(history)*window)
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freq_limit = MIN_FREQ
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freq = 0
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i = 0
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while freq < freq_limit:
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i += 1
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freq += FREQ_STEP
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freq_limit *= PIXEL_FREQ_RANGE
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pixel = 0
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count = 0
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volumes = []
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while pixel < PIXELS:
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total = 0.0
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while freq < freq_limit:
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total += abs(fft[i])**2
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i += 1; count += 1
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freq += FREQ_STEP
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volume = (total/count)**0.5/SAMPLE_SIZE
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volumes.append(volume)
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freq_limit *= PIXEL_FREQ_RANGE
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pixel += 1
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count = 0
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for pixel in xrange(PIXELS):
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c = get_color(volumes[pixel])
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l.set_pixel(pixel, c[0], c[1], c[2])
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work = l.update()
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# time.sleep(0.05)
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finally:
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stream.close()
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p.terminate()
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