ass2

dsplab.py

from numpy import *
from scipy import *
from matplotlib.pyplot import *
from pylab import *
from numpy.fft import *
import scipy.signal as signal

def mfreqz(b,n,a=1):
    """ function to plot the response of a filter"""
    figure(n) 
    w,h = signal.freqz(b,a)
    h_dB = 20 * log10 (abs(h))
    subplot(211)
    plot(w/max(w),h_dB)
    ylim(-80, 30)
    ylabel('Magnitude (db)')
    xlabel(r'Frequency normalized to 1')
    title(r'Frequency response')
    subplot(212)
    h_Phase = unwrap(arctan2(imag(h),real(h)))
    plot(w/max(w),h_Phase)
    ylabel('Phase (radians)')
    xlabel(r'Normalized Frequency (x$\pi$rad/sample)')
    title(r'Phase response')
    subplots_adjust(hspace=0.5)

def bitcheck(filt,bits):
    """function to convert  the filter coefficients to a fixed bit coefficient"""
    temp = array(filt*(2**bits),dtype='int32')
    filt2 = array(temp/(2.0**bits),dtype='float')
    mfreqz(filt2,bits)
def quantize(wave,bits):
    """quantizes the waveform to the number of bits"""
    
    temp = array(wave*(2**(bits-1)),dtype='int32')
    quantizedWave= array(temp/(2.0**(bits-1)),dtype='float')
    return quantizedWave
def binary(coeffs,bits):
    """converts float values to its binary form . coeffs should not be greater than 1"""
    tempCoeffs = array(coeffs*(2**bits-1),dtype='int32')
    print tempCoeffs
    bincoef = []
    binstr = lambda n: n>0 and binstr(n>>1)+str(n&1) or ''
    for coef in tempCoeffs:
        temp=coef
        if(coef>=0):
            tempstr=('0'+binstr(temp))
        else:
            tempstr=('1'+binstr(abs(temp)))
        bincoef.append(tempstr+'0'*(bits-len(tempstr)))


        
    print bincoef



    pass
filt = signal.remez(18,array([0.0,700,1150,2000]),[1.0,0],Hz=4000)
mfreqz(filt,0)
F = 4000 #sampling frequency
N = 8000
wave = sin(2*pi*300*arange(N)/F)+sin(2*pi*1500*arange(N)/F)
filteredWave=signal.lfilter(filt,1,wave)
filtWavefft = fftshift(fft(filteredWave))
figure(1)
subplot(211)
title("Filtered wave")
plot(range(200),filteredWave[:200])
freq = linspace(-F/2,F/2,N)
subplot(212)
plot(freq,abs(filtWavefft),'k')
title("frequency response of the wave")
subplots_adjust(hspace=0.5)

quantizedWave = quantize(wave,8)
filteredWave=signal.lfilter(filt,1,wave)
figure(3)
subplot(211)
title("Filtered quantized wave")
plot(range(200),filteredWave[:200])
freq = linspace(-F/2,F/2,N)
subplot(212)
plot(freq,abs(filtWavefft),'k')
title("frequency response of the filtered quantized wave")
subplots_adjust(hspace=0.5)
binary(filt,8)

show()

sine.py

from numpy import *
from scipy import *
from matplotlib.pyplot import *
from pylab import *
from numpy.fft import *
import scipy.signal as signal
F = 4000 #sampling frequency
N = 8000
sig1 = sin(2*pi*500*arange(N)/F)
figure(1)
title("plot of the sine wave of 500Hz")
plot(arange(50),sig1[:50],'k')
fsig1 = fftshift(fft(sig1))
freq = linspace(-F/2,F/2,N)
figure(2)
title("fft of sine wave of 500Hz")
plot(freq,abs(fsig1))
sig2 = sin(2*pi*500*arange(N)/F)+0.5*randn(N)
figure(3)
title("plot of the sine wave of 500Hz with gaussian noise")
plot(arange(50),sig2[:50],'k')
fsig2 = fftshift(fft(sig2))
freq = linspace(-F/2,F/2,N)
figure(4)
title("fft of sine wave of 500Hz with gaussian noise")
plot(freq,abs(fsig2))
show()