diff options
Diffstat (limited to '')
| -rw-r--r-- | src/gr-fadingui/python/multipath_fading.py | 95 |
1 files changed, 30 insertions, 65 deletions
diff --git a/src/gr-fadingui/python/multipath_fading.py b/src/gr-fadingui/python/multipath_fading.py index 3c34a79..dc7fcc1 100644 --- a/src/gr-fadingui/python/multipath_fading.py +++ b/src/gr-fadingui/python/multipath_fading.py @@ -31,87 +31,52 @@ class multipath_fading(gr.sync_block): """ docstring for block multipath_fading """ - def __init__(self, amplitudes, delays, los): # only default arguments here - """arguments to this function show up as parameters in GRC""" + def __init__(self, amplitudes, delays, los): gr.sync_block.__init__( self, - name='Embedded Python Block', # will show up in GRC + name='Multipath fading', 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). + + if len(amplitudes) != len(delays): + raise Exception("Amplitudes and Delay length dont match") + + if np.min(delays) < 0: + raise Exception("Delay can't be negative") + self.amplitudes = amplitudes self.delays = delays self.temp = [0] - log.debug(los) #TO DO: True False unterscheidung - if los == True: - self.los = 1 - log.debug("Los True") - else: - self.los = 0 - log.debug("Los False") - - - - + self.los = 1 if los else 0 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): # Test: Es muss gleich viele Werte für Delays und Amplituden haben. - raise Exception("Amplitudes and Delay length dont match") - if np.min(self.delays)<0: #Negativ Check - raise Exception("Delay can't be negativ") - - - # raise Exception("Delay length can't be one") - #if np.min(self.delays)<=1: - # raise Exception("Delay length can't be one") - - - max_order = 2 * np.floor(np.max(self.delays)) + 1 #Max Werte herausfinden für länge + max_order = 2 * np.floor(np.max(self.delays)) + 1 max_samples = np.arange(0, max_order +1) - max_len = len(max_samples) #Für Filter + max_len = len(max_samples) - sum_x = np.zeros(int(max_len)) + tot_h = np.zeros(int(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: + for (a, d) in zip(self.amplitudes, self.delays): order = 2 * np.floor(d) + 1 - - skip = np.floor(d) - (order - 1) / 2 #M sollte immer 0 sein - assert skip >= 0 - - samples = np.arange(0, order +1) - - h = a*(np.sinc(samples-d)) #sinc - h_len = np.concatenate([h, np.zeros(max_len-len(h))]) - - sum_x += h_len - - #x = np.concatenate([np.zeros(d-1), [a], np.zeros(max_len-d)]) - #sum_x += x - - sum_x[0] = self.los - #log.debug(sum_x) - - - y = np.convolve(inp, sum_x) - - # signal_shifted = np.convolve(h, inp, mode='full') - # y = signal_shifted - - y+=np.concatenate([self.temp,np.zeros(len(y)-len(self.temp))]) - + samples = np.arange(0, order +1) + # compute FIR + h = a * np.sinc(samples - d) + # adjust length + h = np.concatenate([h, np.zeros(max_len - len(h))]) + tot_h += h + + tot_h[0] += self.los + + # compute output and add rest from last block processing + y = np.convolve(inp, tot_h) + y += np.concatenate([self.temp, np.zeros(len(y) - len(self.temp))]) + # write output oup[:] = y[:len(inp)] - self.temp = y[len(inp):] - + # save for next block processing + self.temp = y[len(inp):] - return len(oup)
\ No newline at end of file + return len(oup) |