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⚠️ SEE UPDATED POST: Signal Filtering in Python
While I wrote a pervious post on linear data smoothing with python, those scripts were never fully polished. Fred (KJ4LFJ) asked me about this today and I felt bad I had nothing to send him. While I might add that the script below isn’t polished, at least it’s clean. I’ve been using this method for all of my smoothing recently. Funny enough, none of my code was clean enough to copy and paste, so I wrote this from scratch tonight. It’s a function to take a list in (any size) and smooth it with a triangle window (of any size, given by “degree”) and return the smoothed data with or without flanking copies of data to make it the identical length as before. The script also graphs the original data vs. smoothed traces of varying degrees. The output is below. I hope it helps whoever wants it!
import numpy
import pylab
def smoothTriangle(data, degree, dropVals=False):
"""
performs moving triangle smoothing with a variable degree.
note that if dropVals is False, output length will be identical
to input length, but with copies of data at the flanking regions
"""
triangle = numpy.array(range(degree)+[degree]+range(degree)[::-1])+1
smoothed = []
for i in range(degree, len(data)-degree*2):
point = data[i:i+len(triangle)]*triangle
smoothed.append(sum(point)/sum(triangle))
if dropVals:
return smoothed
smoothed = [smoothed[0]]*(degree+degree/2)+smoothed
while len(smoothed) < len(data):
smoothed.append(smoothed[-1])
return smoothed
### CREATE SOME DATA ###
data = numpy.random.random(100) # make 100 random numbers from 0-1
data = numpy.array(data*100, dtype=int) # make them integers from 1 to 100
for i in range(100):
data[i] = data[i]+i**((150-i)/80.0) # give it a funny trend
### GRAPH ORIGINAL/SMOOTHED DATA ###
pylab.plot(data, "k.-", label="original data", alpha=.3)
pylab.plot(smoothTriangle(data, 3), "-", label="smoothed d=3")
pylab.plot(smoothTriangle(data, 5), "-", label="smoothed d=5")
pylab.plot(smoothTriangle(data, 10), "-", label="smoothed d=10")
pylab.title("Moving Triangle Smoothing")
pylab.grid(alpha=.3)
pylab.axis([20, 80, 50, 300])
pylab.legend()
pylab.show()
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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
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I’m starting to investigate PyGame as an alternative to PIL and K for my QRSS VD spectrograph project. This sample code makes a box bounce around a window.
import pygame, sys
pygame.init() #load pygame modules
size = width, height = 320, 240 #size of window
speed = [2, 2] #speed and direction
screen = pygame.display.set_mode(size) #make window
s=pygame.Surface((100,50)) #create surface 100px by 50px
s.fill((33,66,99)) #color the surface blue
r=s.get_rect() #get the rectangle bounds for the surface
clock=pygame.time.Clock() #make a clock
while 1: #infinite loop
clock.tick(30) #limit framerate to 30 FPS
for event in pygame.event.get(): #if something clicked
if event.type == pygame.QUIT: #if EXIT clicked
sys.exit() #close cleanly
r=r.move(speed) #move the box by the "speed" coordinates
#if we hit a wall, change direction
if r.left < 0 or r.right > width: speed[0] = -speed[0]
if r.top < 0 or r.bottom > height: speed[1] = -speed[1]
screen.fill((0,0,0)) #make redraw background black
screen.blit(s,r) #render the surface into the rectangle
pygame.display.flip() #update the screen
While it may not be perfect, it’s a whole lot better. Below is a capture from this morning of my signal (the waves near the bottom). Compare that to how it was before and you should notice a dramatic improvement! The MEPT is inside a metal box inside a 1-inch-thick Styrofoam box. Very cool!
My oscilloscope decided to die on my right as I finally was able to view my 10 MHz waveform. I used a piece of coax with a load at the connector to the o-scope, and ran the coax to my test points. It was beautiful! … and lasted about 30 seconds. The culprit seems to be a failing “focus” knob. My images had been getting blurrier by the day, and now it’s completely black unless I twist pretty hard on the focus knob. I’d stick a small pot in there, but I have no idea how much voltage/current is being regulated. I’m sure the schematics are posted somewhere, but for now I’m going to try to clean out the potentiometer manually and see if the situation improves. Here are some photos of the circuitry inside this old scope. They don’t make stuff like this anymore!
Update: I never got this scope to work again!
I completed work on my first RF receiver, and for what it is it seems to work decently. It should be self-explanatory from the photos. It’s based around an SA602. As with everything, I don’t plan on posting schematics until the project is complete because I don’t want people re-creating junky circuits! It’s stationed at the University of Florida’s club station W4DFU and its spectrograph can be viewed in real time from the QRSS VD - Web Grabber - W4DFU page.
⚠️ WARNING: This page is obsolete
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Now that my minimalist QRSS transmitter is mostly functional, I’m shifting gears toward building a minimalist receiver. These are some early tests, but I’m amazed I managed to hack something together that actually works! Once it’s finished I’ll post schematics. For now, here are some photos. This receiver is based upon an SA602 and although there *IS* an op-amp on the board, I actually bypassed it completely! The SA602 seems to put out enough juice to make my PC microphone jack happy, and those cheap op-amps are noisy anyway, so awesome! Go minimalism!
Here’s the output from 7.040 MHz. Conditions are pretty bad right now, and I’m at my apartment using my crazy indoor antenna
