Please help! I am trying to make a convolution but i am receiving a syntax error. If anyone can help with how to do the convolution it would be much appreciated!

This first part is the main program.

import numpy as np

from numpy import *

import pylab as pl

import wave

import struct

from my_conv import myconv

#import scipy.signal as signal

##--------------------------------------------------------------------

## read the input wave file "speech.wav"

f = wave.open("speech.wav", "rb")

params = f.getparams()

nchannels, sampwidth, framerate, nframes = params[:4]

str_data = f.readframes(nframes)

f.close()

if (framerate!=44100): # if Fs is not equal to 44100

print 'Fs is not 44.1KHz' # display error and abort

waveData = np.fromstring(str_data, dtype=np.short)

waveData = waveData/32768.0 #normalization

len_data = len(waveData)

#pl.plot(waveData)

#pl.show()

##--------------------------------------------------------------------

## read the impulse response for the system

len_imp = 128 # length of left/right impulse response (fixed)

fp = open("H0e090a.dat", 'rb') # open imp_filename

sysData=zeros(2*len_imp)

for i in range(0,2*len_imp):

strd = fp.read(2)

data1 = struct.unpack(">h", strd)

sysData[i] = int(data1[0])

fp.close() # close imp_filename

## separate the left and right channel impulse response

leftimp = sysData[0:2*len_imp-1:2] # left ear impulse response: hl[1]...hl[len_imp]

rightimp = sysData[1:2*len_imp:2] # right ear impulse response: hr[1]...hr[len_imp]

#pl.plot(rightimp)

#pl.show()

##--------------------------------------------------------------------

#leftCh = signal.convolve(waveData, leftimp, mode='valid')

#rightCh = signal.convolve(waveData, rightimp, mode='valid')

leftCh = myconv(leftimp, waveData) # convolution of left ear impulse response and waveData

rightCh = myconv(rightimp, waveData) # convolution of left ear impulse response and waveData

len_R= len(rightCh)

len_L= len(leftCh)

#pl.plot(leftCh)

#pl.plot(rightCh)

#pl.show()

##--------------------------------------------------------------------

LR_Ch = vstack((leftCh, rightCh))

norml= 1.05*abs(LR_Ch).max()

leftCh = leftCh.reshape(len(leftCh ), 1,order='F').copy()

rightCh = rightCh.reshape(len(rightCh ), 1,order='F').copy()

##--------------------------------------------------------------------

outWave = hstack((leftCh, rightCh))/norml*32768.

# Since we'll write outWave to the output wav file which has 16bits short int as the data,

#we should map the values in outWave to the range of 16bits short int by multiplying 32768.

#pl.plot(outWave)

#pl.show()

##--------------------------------------------------------------------

f1 = wave.open("testOutput.wav",'wb')

f1.setnchannels(2)

f1.setsampwidth(2) # width = 2 Bytes

f1.setframerate(framerate)

f1.setnframes(len_L)

f1.writeframes(outWave.astype(np.short).tostring())

# The outWave is float64 type after the convolution, thus we should first translate outWave

# into 16bits int using astype(np.short) and then write it as a string to the target file.

f1.close()

##--------------------------------------------------------------------

print "Finished!"

This part is where i write the convolution function.

import numpy as np

import numpy as np

from numpy import *

import scipy as Sci

import scipy.linalg

import speech.wav

def myconv(x,h):

############################################################################

# A function to generate the output signal y as convolution of input signal

# x and impulse response signal h

############################################################################

# INPUT PARAMETERS---------------------------------------------------------

# x: input signal

# h: impulse response

len_x = len(x) # length of x

len_h = len(h) # length of h

y = signal.convolve(x,h)

############################################################################

# Data processing: convolution (TO BE COMPLETED BY STUDENTS)

############################################################################

# OUTPUT PARAMETERS--------------------------------------------------------

# y: output signal as convolution of input signal x and impulse response h

# Write the code including comments to explain what you are doing

return y