Hi Chad,
thanks for re-posting your code; it's much clearer to read now.
I'm not quite sure what I'm looking at now: Is this your own
implementation of the yall1 minimization function, or something that can
be tested?
If I remember correctly, the matlab call has a matrix input, and a
"target" vector, and an options argument. Is there some accessible
documentation.
Other than my confusion whether this is a GNU Radio or a general yall1
question, your code looks pretty good. A few thing's I'd note:
* self.alpha.shape should be right
* check that input_items.shape and in0.shape are as you expect them
Best regards,
Marcus
On 10/29/2015 01:27 PM, Chad R wrote:
> Sorry. Something went wrong when I copied pasted it but my actual code is:
>
> import numpy
> from gnuradio import gr
> from yall1 import *
>
> class yall1_reconstruction_cc(gr.sync_block):
> """
> Yall1_reconstruction_block
> """
> def __init__(self,n,m):
> self.N = n
> self.M = m
> phi =
> np.load("/home/chad/Desktop/PROJECT/Python/Matrices/phi_mtx%(M)dx%(N)d.npy"
> %{"M":self.M,"N":self.N})
> psi =
> np.load("/home/chad/Desktop/PROJECT/Python/Matrices/psi_mtx%(N)dx%(N)d.npy"
> %{"N":self.N})
> self.alpha = np.dot(phi,psi)
> gr.sync_block.__init__(self,
> name="yall1_reconstruction",
> in_sig=[(np.complex64,self.M)],
> out_sig=[(np.complex64,self.N)])
>
> def work(self, input_items, output_items):
> in0 = input_items[0]
> size = np.shape(in0)[0]
> out = np.zeros((size,self.N),dtype = np.complex64)
> #out = yall1(self.alpha,in0[0]).reshape(self.N,)
> for i in range(0,size):
> recon = yall1(self.alpha, in0[i].reshape(self.M,1))*4.6
> out[i] = recon.reshape(self.N,)
> output_items[0][:] = out
> return len(output_items[0])
>
>
> On Thu, Oct 29, 2015 at 2:08 PM, Marcus Müller
> <[email protected] <mailto:[email protected]>> wrote:
>
> Hi Chad,
>
> there's something wrong with the indention of the lines between
> "def __init__" and "g.sync_block", and the same goes for your work
> function; so that's my first stab at explaining misbehaviour.
>
>
> Best regards,
> Marcus
>
>
> On 29.10.2015 13:01, Chad R wrote:
>> Good day every one
>>
>> I have implemented a Python block but I am not getting the
>> results I expected. I get the results I expect at any
>> frequency=samp_rate/2^n where n is any integer. My block makes
>> use of a yall1 reconstruction algorithm to reconstruct a signal
>> from M=100 to N=1024 vector.
>> The code for my block is shown below:
>>
>> class yall1_reconstruction_cc(gr.sync_block):
>> """
>> Yall1_reconstruction_block
>> """
>> def __init__(self,n,m):
>> self.N = n
>> self.M = m
>> phi =
>>
>> np.load("/home/chad/Desktop/PROJECT/Python/Matrices/phi_mtx%(M)dx%(N)d.npy"
>> %{"M":self.M,"N":self.N})
>> psi =
>>
>> np.load("/home/chad/Desktop/PROJECT/Python/Matrices/psi_mtx%(N)dx%(N)d.npy"
>> %{"N":self.N})
>> self.alpha = np.dot(phi,psi)
>> gr.sync_block.__init__(self,
>> name="yall1_reconstruction",
>> in_sig=[(np.complex64,self.M)],
>> out_sig=[(np.complex64,self.N)])
>>
>> def work(self, input_items, output_items):
>> in0 = input_items[0]
>> size = np.shape(in0)[0]
>> out = np.zeros((size,self.N),dtype = np.complex64)
>> #out = yall1(self.alpha,in0[0]).reshape(self.N,)
>> for i in range(0,size):
>> recon = yall1(self.alpha, in0[i].reshape(self.M,1))*4.7
>> out[i] = recon.reshape(self.N,)
>> output_items[0][:] = out
>> return len(output_items[0])
>>
>> Have I implemented it right? or is my issue with my
>> implementation? I read through the tutorials but I feel some
>> aspects are quiet hard to follow.
>>
>> Thank you in advance for your help
>>
>> Chad Richs
>>
>>
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>> [email protected] <mailto:[email protected]>
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>
>
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