def circular_conv(request):
if request.method == 'POST':
form = Output(request.POST)
if form.is_valid():
cd = form.cleaned_data
input1 = cd['input1']
input2 = cd['input2']
x=arr_conv(input1)
h=arr_conv(input2)
xd="x(n) = " + str(x)
hd="h(n) = " + str(h)
x = np.asarray(x)
h = np.asarray(h)
xlen=len(x)
hlen=len(h)
r=xlen-hlen
if xlen>hlen:
h=np.resize(h, xlen)
lmax=xlen
if hlen>xlen:
x=np.resize(x, hlen)
lmax=hlen
if hlen==xlen:
lmax=xlen
pad_zero(r,xlen,hlen,h,x)
h_rev=h[::-1]
resn=np.resize(res, lmax)
cir_conv(x,h,lmax,resn,temp,h_rev)
resn=resn[::-1]
num=len(resn)
c='c'
gp(resn,num,c)
graphy='<img src="http://kingspp.pythonanywhere.com/media/plots/test.png" height="400px" width="500px" ></img>'
res_rev='The Circular Convolution of x(n) and y(n) is: ' + str(resn)
return render_to_response('dsp/circular_conv.html', {'form':form, 'input1': xd, 'input2':hd, 'output':res_rev, 'graphy':graphy,'right_now':datetime.now()}, context_instance=RequestContext(request))
else:
form = Output()
return render_to_response('dsp/circular_conv.html', {'form': form,'right_now':datetime.now()}, context_instance=RequestContext(request))
def linear_conv(request):
if request.method == 'POST':
form = Output(request.POST)
if form.is_valid():
cd = form.cleaned_data
input1 = cd['input1']
input2 = cd['input2']
x=arr_conv(input1)
h=arr_conv(input2)
xd="x(n) = " + str(x)
hd="h(n) = " + str(h)
resultd=np.convolve(x, h)
num=len(resultd)
result = str(resultd)
output = "The Linear Convolution of x(n) and y(n) is: " + result
c='l'
gp(resultd,num,c)
graphy='<img src="http://kingspp.pythonanywhere.com/media/plots/test.png" height="400px" width="500px" ></img>'
return render_to_response('dsp/linear_conv.html', {'form':form, 'input1': xd, 'input2': hd, 'output':output, 'graphy':graphy, 'right_now':datetime.now()}, context_instance=RequestContext(request))
else:
form = Output()
return render_to_response('dsp/linear_conv.html', {'form': form,'right_now':datetime.now()}, context_instance=RequestContext(request))
def cross_corr(request):
if request.method == 'POST':
form = Output(request.POST)
if form.is_valid():
cd = form.cleaned_data
input1 = cd['input1']
input2 = cd['input2']
x=arr_conv(input1)
h=arr_conv(input2)
output=np.correlate(x,h,'full')
output=np.asarray(output)
c='cc'
num=len(output)
gp(output,num,c)
graphy='<img src="http://kingspp.pythonanywhere.com/media/plots/test.png" height="400px" width="500px" ></img>'
output = 'The Crosscorrelation of x(n) and h(n) is : ' + str(output)
indispx='Input Sequence x(n): ' + '[' + str(input1) + ']'
indisph='Input Sequence h(n): ' + '[' + str(input2) + ']'
return render_to_response('dsp/cross_corr.html', {'form':form, 'input1': indispx,'input2': indisph, 'output':output, 'graphy':graphy,'right_now':datetime.now()}, context_instance=RequestContext(request))
else:
form = Output()
return render_to_response('dsp/cross_corr.html', {'form': form,'right_now':datetime.now()}, context_instance=RequestContext(request))
def ndft(request):
if request.method == 'POST':
form = Ndft_form(request.POST)
if form.is_valid():
cd = form.cleaned_data
input1 = cd['input1']
x=arr_conv(input1)
output = np.fft.fftn(x)
num=len(output)
c='nd'
gp(output,num,c)
graphy='<img src="http://kingspp.pythonanywhere.com/media/plots/test.png" height="400px" width="500px" aligh="center"></img>'
output = 'The N-Point Discrete Fourier Transform of x(n) is : ' + str(output)
indisp='Input Sequence x(n): ' + '[' + str(input1) + ']'
return render_to_response('dsp/ndft.html', {'form':form, 'input1': indisp, 'output':output, 'graphy':graphy,'right_now':datetime.now()}, context_instance=RequestContext(request))
else:
form = Ndft_form()
return render_to_response('dsp/ndft.html', {'form': form,'right_now':datetime.now()}, context_instance=RequestContext(request))