Skip to content

A
adc-testing
Commit d5c186c4 authored by Federico Asara's avatar Federico Asara
Browse files
Options

Inline documentation update.

parent 0b985a62
Hide whitespace changes
Inline Side-by-side
Showing with 39 additions and 9 deletions
SignalProcessing/Signal.py
View file @ d5c186c4
......@@ -3,58 +3,82 @@
__author__="Federico Asara"
__date__ ="$Jul 11, 2011 2:39:38 PM$"
__doc__= """This module offers the Signal class, which simple store the output
signal of an ADC with some other useful informations. """
__doc__= """This module offers the Signal class, which simply store the output
signal of an ADC, fed with a sinewave, with some other useful informations.
It is also capable to reverse incoherent sampling, in order to get more accurate
results - if needed. It also removes the DC component.
Other classes may inherit from this one to expand the signal."""
from Utilities import *
from numpy import *
import Sinefit
class Signal(object):
"""A class that represent a time-domain sampled signal.
"""A class that represent a time-domain sampled sinewave.
Evaluate a small number of parameters, find the sine frequency and
eventually correct sampling incoherency.
"""
def __init__(self, nbits = 0, rate = 1, data = []):
"""initialize a signal object
"""Initialize a signal object
nbits: bit width of the sample values
rate: sampling rate of sample production
data: an array of samples (usually nbits-long words, stored in
a numpy array)
"""
self.nbits = nbits
self.rate = rate
self.fulldata = data = array(data, dtype=float)
# convert data into an array of float, if needed, and store it in
# self.fulldata so it`s available to other methods
self.fulldata = data = array(data, dtype=float)
self.fullnsamples = len(data)
self.data = self.fulldata
self.nsamples = len(data)
# remove DC component
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))
# useful names
N = len(data)
fdft = self.fulldft
# index of the biggest peak
first = 1. + argmax(fdft[1:N/2])
# index of the biggest peak nearest to `first`
# can only be first +-1.
second = first + (argmax(fdft[first-1:first+2:2])*2) -1
ratio = (fdft[second] / fdft[first])
# save first in self
self.first = first
# self.beta quantifies the sampling incoherency, defining the
# fraction of a period sampled in excess.
self.beta = N/pi * arctan(sin(pi/N)/(cos(pi/N)+1./ratio))
# the position the peak between first and second
self.w0index = first+ self.beta
# sampling frequency
freqSample = 2 * pi * self.rate
# 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
# limit data
# 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]
......@@ -66,7 +90,12 @@ class Signal(object):
def items(self):
"""Create a list of tuples that describes the signal.
The structure of a tuple is"""
A tuple holds three values:
0. description;
1. format string for [2], can include units and such;
2. value to show.
Returns such list of tuples."""
output = []
output.append(('Number of bits', '%d b', self.nbits))
......@@ -79,5 +108,6 @@ class Signal(object):
return output
def precalculateAll(self):
"""Calculate all the parameters. Can (and should!) be overridden."""
return
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment