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"""
Embedded Python Blocks:
Each time this file is saved, GRC will instantiate the first class it finds
to get ports and parameters of your block. The arguments to __init__ will
be the parameters. All of them are required to have default values!
"""
import numpy as np
from numpy.fft import fft,ifft,fftshift
from gnuradio import gr
class blk(gr.sync_block): # other base classes are basic_block, decim_block, interp_block
"""Embedded Python Block example - a simple multiply const"""
def __init__(self, amplitudes=[], delays=[], los=True): # only default arguments here
"""arguments to this function show up as parameters in GRC"""
gr.sync_block.__init__(
self,
name='Embedded Python Block', # will show up in GRC
in_sig=[np.complex64],
out_sig=[np.complex64]
)
# if an attribute with the same name as a parameter is found,
# a callback is registered (properties work, too).
self.amplitudes = amplitudes
self.delays = delays
self.temp = [0]
if los:
self.amplitudes.append(1)
self.delays.append(0)
#self.fir =
def work(self, input_items, output_items):
"""example: multiply with constant"""
inp = input_items[0]
oup = output_items[0]
if len(self.amplitudes) != len(self.delays):
raise Exception("Amplitudes and Delay length dont match")
# raise Exception("Delay length can't be one")
#if np.min(self.delays)<=1:
# raise Exception("Delay length can't be one")
max_len = np.max(self.delays)
sum_x = np.zeros(max_len)
for(a,d) in zip(self.amplitudes,self.delays):
if d-1 <= 0:
x = np.concatenate([[a], np.zeros(max_len-1)])
else:
x = np.concatenate([np.zeros(d-1), [a], np.zeros(max_len-d)])
sum_x += x
H_int = fft(sum_x)
h = ifft(H_int)
y = np.convolve(inp, h)
y+=np.concatenate([self.temp,np.zeros(len(y)-len(self.temp))])
oup[:] = y[:len(inp)]
self.temp = y[len(inp):]
return len(oup)
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