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adc-testing
Commit 31c36db1 authored by Federico Asara's avatar Federico Asara
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TwoToneSignal support added.

parent ed35d049
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Showing with 147 additions and 95 deletions
SignalProcessing/SingleToneSignal.py
View file @ 31c36db1
......@@ -13,7 +13,8 @@ import cPickle
class SingleToneSignal(Signal):
"""A class that represent a time-domain sampled signal, and also holds many
WindowedSignal that represent the signal in frequency domain.
WindowedSignal that represent the signal in frequency domain, using
different window functions.
"""
"""maximum tolerable resolution for a histogram"""
......@@ -49,12 +50,12 @@ class SingleToneSignal(Signal):
def items(self):
output = super(SingleToneSignal, self).items()
# output.append(('Peak at', "%f", self.w0index))
# output.append(('Input frequency', "%.6f Hz", self.w0/2/pi))
# output.append(('Beta', "%f", self.beta))
output.append(('Amplitude', "%f", self.amplitude))
output.append(('Phase', "%f", self.phase))
output.append(('Input frequency [0]', '%.5f Hz', self.w0/(2*pi)))
output.append(('Peak [0]', '%d', self.w0index))
output.append(('Amplitude [0]', "%f", self.amplitude))
output.append(('Phase [0]', "%f", self.phase))
output.append(('DC [0]', "%f", self.C))
output.append(('Max DNL', "%f ", self.maxDNL))
output.append(('Max INL', "%f ", self.maxINL))
output.append(('Theoretical SNR', "%.2f dB", self.thSNR))
......@@ -68,9 +69,6 @@ class SingleToneSignal(Signal):
precalculate method for each window function we know."""
if self.fullnsamples > 0:
# remove DC component
# self.fulldata -= (max(self.fulldata) +min(self.fulldata))/2.
# calculate the |fft|
self.fulldft = abs(fft.fft(self.fulldata))
......@@ -103,18 +101,17 @@ class SingleToneSignal(Signal):
# initial frequency guess
w0 = freqSample * float(self.w0index)/self.nsamples
# print "Frequency initial guess ->", w0
# fit the sine
self.w0, self.A, self.B, self.C = Sinefit.sinefit4(data, 1.0/rate, w0, 1e-7)
# print "Frequency fit ->", self.w0
self.amplitude = hypot(self.A, self.B)
self.phase = arctan2(self.B, self.A)
# limit data removing incoherency
self.w0index = self.w0 /freqSample * self.nsamples
self.limit = floor(0.5 + N*int(self.w0index)/self.w0index)
self.data = data[:self.limit]
self.nsamples = len(self.data)
# print "limit is:", self.limit
# First of all evaluate the histograms
skip = False
......@@ -130,6 +127,7 @@ class SingleToneSignal(Signal):
else:
self.DNL, self.maxDNL = self._DNL()
self.INL, self.maxINL = self._INL()
skip = False
# ..theoretical SNR and process gain
......@@ -142,7 +140,7 @@ class SingleToneSignal(Signal):
for i in WindowFunction.windows.keys():
self.windowed[i] = self.precalculate(i)
@timeit
#@timeit
def precalculate(self, windowName):
"""Evaluates all the parameters for a particular window function.
windowName: a string containing the name of the window function
......@@ -151,7 +149,6 @@ class SingleToneSignal(Signal):
output = WindowedSignal()
if windowName not in WindowFunction.windows.keys():
return None
......@@ -163,8 +160,6 @@ class SingleToneSignal(Signal):
output.rate = self.rate
window = WindowFunction.windows[windowName]
# print len(self.data), self.nsamples
output.data = self.data * window[self.nsamples]
output.dft = fft.fft(output.data)
......@@ -175,12 +170,12 @@ class SingleToneSignal(Signal):
output.ldft = 10*log10(output.dft)
output.ludft = 10*log10(output.udft)
# print output.ldft[:50]
output.w0 = w0 = self.w0
output.w0index = w0index = self.w0index
self.amplitude = amplitude = hypot(self.A, self.B)
self.phase = phase = arctan2(self.B, self.A)
output.amplitude = amplitude = hypot(self.A, self.B)
output.phase = phase = arctan2(self.B, self.A)
output.C = self.C
A, B, C = self.A, self.B, self.C
# THD
......@@ -201,16 +196,13 @@ class SingleToneSignal(Signal):
output.noiseFloor = dB(mean(filteredNoise))
output.signalPower = (norm(output.dft)**2)/self.nsamples
# output.signalPower *= output.signalPower / self.nsamples
time = arange(0, self.nsamples, dtype=float)/self.rate
thSin = C + A * cos(w0*time) + B * sin(w0*time)
output.th = copy(thSin)
#noise = self.data - thSin
noiseMask = array(ones(len(output.dft)))
noiseMask[0] = 0 # shouldn't be necessary
noiseMask[0] = 0
noiseMask[w0index] = 0
noiseMask[-w0index] = 0
for i in thindex: noiseMask[int(i)] = 0
......@@ -218,10 +210,8 @@ class SingleToneSignal(Signal):
noise = where(noiseMask, self.data, 0)
output.noisePower = (norm(noise)**2) / self.nsamples
# now we can evaluate SNR = max component - noise floor - process gain
#output.SNR = 10*log10(output.signalPower/output.noisePower)
num = output.signalPower
output.SNR = 20*log10(num/output.noisePower)
# SNR
output.SNR = 20*log10(output.signalPower/output.noisePower)
# now it's time for SINAD
rmsNoise = sqrt(sum((self.data -thSin)**2)/len(self.data))
......@@ -241,14 +231,13 @@ class SingleToneSignal(Signal):
output.SFDR = 10*log10(output.dft[w0index]/secondPeak)
#output.report()
return output
def histogram_resolution(self):
"""Upper bound to the histogram's length."""
return min(self.MAXRES , 2**self.nbits)
@timeit
#@timeit
def _histogram(self):
"""Compute histogram of a sampled signal
......@@ -258,13 +247,12 @@ class SingleToneSignal(Signal):
returns: an array of histogram_resolution() numbers (frequencies)
"""
bins = self.histogram_resolution()#2**self.nbits
bins = self.histogram_resolution()
hist, discard = histogram(self.data, bins)
print "real", len(hist) -2
return hist[1:-1]
@timeit
#@timeit
def _ideal_histogram(self):
"""Produce an ideal vector of frequencies (histogram) for the
nsamples samples of a perfect nbits ADC.
......@@ -286,18 +274,15 @@ class SingleToneSignal(Signal):
result = (n * Mt / pi)
#print "len(result):", len(result)
#print result
return result[2:]
@timeit
#@timeit
def _DNL(self):
"""Evaluate DNL, needs real and ideal histrograms."""
dnl = (self.realHistogram/self.idealHistogram) -1
return dnl, max(abs(dnl))
@timeit
#@timeit
def _INL(self):
"""Evaluate INL, needs DNL."""
inl = cumsum(self.DNL)
......
SignalProcessing/TwoToneSignal.py
View file @ 31c36db1
......@@ -31,9 +31,13 @@ class TwoToneSignal(Signal):
output.append(('Sine 1 frequency', "%f Hz", self.w1/2./pi))
output.append(('Sine 1 A', "%f", self.a1))
output.append(('Sine 1 B', "%f", self.b1))
output.append(('Sine 1 amplitude', "%f", self.amplitude1))
output.append(('Sine 1 phase', "%f", self.phase1))
output.append(('Sine 2 frequency', "%f Hz", self.w2/2./pi))
output.append(('Sine 2 A', "%f", self.a2))
output.append(('Sine 2 B', "%f", self.b2))
output.append(('Sine 2 amplitude', "%f", self.amplitude2))
output.append(('Sine 2 phase', "%f", self.phase2))
output.append(('DC component', "%f", self.c0))
......@@ -66,6 +70,11 @@ class TwoToneSignal(Signal):
(self.w1, self.a1, self.b1), (self.w2, self.a2, self.b2), self.c0 = \
Sinefit.doubleSinefit4matrix(self.fulldata, self.rate**-1, tow1, tow2)
self.amplitude1 = hypot(self.a1, self.b1)
self.amplitude2 = hypot(self.a2, self.b2)
self.phase1 = arctan2(self.b1, self.a1)
self.phase2 = arctan2(self.b2, self.a2)
delta = abs(self.w1 - self.w2)
i1 = min([self.w1, self.w2]) - delta
......
SignalProcessing/WindowedSignal.py
View file @ 31c36db1
......@@ -45,11 +45,18 @@ class WindowedSignal:
secondPeak = 0
SFDR = 0
amplitude = 0
phase = 0
def items(self):
output = []
output.append(('Input frequency', '%.5f Hz', self.w0/(2*pi)))
output.append(('Peak', '%d', self.w0index))
output.append(('Input frequency [W]', '%.5f Hz', self.w0/(2*pi)))
output.append(('Peak [W]', '%d', self.w0index))
output.append(('Amplitude [W]', "%f", self.amplitude))
output.append(('Phase [W]', "%f", self.phase))
output.append(('DC [W]', "%f", self.C))
output.append(('THD', '%.2f dB', self.THD))
output.append(('Noise floor', "%g dB", self.noiseFloor))
output.append(('Signal power', "%.f ", self.signalPower))
......
qtGUI/MainWindow.py
View file @ 31c36db1
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