**Warning**: This post is several years old and the author has marked it as poor quality (compared to more recent posts). It has been left intact for historical reasons, but but its content (and code) may be inaccurate or poorly written.

**While thinking of ways to improve my QRSS VD high-definitions spectrograph software,** I often wish I had a better way to display large spectrographs. Currently I’m using PIL (the Python Imaging Library) with TK and it’s slow as heck. I looked into the PyGame project, and it seems to be designed with speed in mind. I whipped-up this quick demo, and it’s a simple case audio spectrograph which takes in audio from your sound card and graphs it time vs. frequency. This method is far superior to the method I was using previously to display the data, because while QRSS VD can only update the entire GUI (500px by 8,000 px) every 3 seconds, early tests with PyGame suggests it can do it about 20 times a second (wow!). With less time/CPU going into the GUI, the program can be more responsivle and my software can be less of a drain.

import pygame import numpy import threading import pyaudio import scipy import scipy.fftpack import scipy.io.wavfile import wave rate=12000 #try 5000 for HD data, 48000 for realtime soundcard=2 windowWidth=500 fftsize=512 currentCol=0 scooter=[] overlap=5 #1 for raw, realtime - 8 or 16 for high-definition def graphFFT(pcm): global currentCol, data ffty=scipy.fftpack.fft(pcm) #convert WAV to FFT ffty=abs(ffty[0:len(ffty)/2])/500 #FFT is mirror-imaged #ffty=(scipy.log(ffty))*30-50 # if you want uniform data print "MIN:t%stMAX:t%s"%(min(ffty),max(ffty)) for i in range(len(ffty)): if ffty[i]<0: ffty[i]=0 if ffty[i]>255: ffty[i]=255 scooter.append(ffty) if len(scooter)<6:return scooter.pop(0) ffty=(scooter[0]+scooter[1]*2+scooter[2]*3+scooter[3]*2+scooter[4])/9 data=numpy.roll(data,-1,0) data[-1]=ffty[::-1] currentCol+=1 if currentCol==windowWidth: currentCol=0 def record(): p = pyaudio.PyAudio() inStream = p.open(format=pyaudio.paInt16,channels=1,rate=rate, input_device_index=soundcard,input=True) linear=[0]*fftsize while True: linear=linear[fftsize/overlap:] pcm=numpy.fromstring(inStream.read(fftsize/overlap), dtype=numpy.int16) linear=numpy.append(linear,pcm) graphFFT(linear) pal = [(max((x-128)*2,0),x,min(x*2,255)) for x in xrange(256)] print max(pal),min(pal) data=numpy.array(numpy.zeros((windowWidth,fftsize/2)),dtype=int) #data=Numeric.array(data) # for older PyGame that requires Numeric pygame.init() #crank up PyGame pygame.display.set_caption("Simple Spectrograph") screen=pygame.display.set_mode((windowWidth,fftsize/2)) world=pygame.Surface((windowWidth,fftsize/2),depth=8) # MAIN SURFACE world.set_palette(pal) t_rec=threading.Thread(target=record) # make thread for record() t_rec.daemon=True # daemon mode forces thread to quit with program t_rec.start() #launch thread clk=pygame.time.Clock() while 1: for event in pygame.event.get(): #check if we need to exit if event.type == pygame.QUIT:pygame.quit();sys.exit() pygame.surfarray.blit_array(world,data) #place data in window screen.blit(world, (0,0)) pygame.display.flip() #RENDER WINDOW clk.tick(30) #limit to 30FPS