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https://github.com/hb9fxq/gr-digitalhf
synced 2024-11-05 05:55:53 +00:00
move np.bool(...) to msg_proxy
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d25b06a9d7
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@ -49,7 +49,7 @@ class msg_proxy(gr.basic_block):
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iq_samples = pmt.to_python(pmt.cdr(msg_in))
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success,doppler = self._obj.get_doppler(iq_samples)
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msg_out = pmt.make_dict()
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msg_out = pmt.dict_add(msg_out, pmt.intern('success'), pmt.to_pmt(success))
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msg_out = pmt.dict_add(msg_out, pmt.intern('success'), pmt.to_pmt(np.bool(success)))
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msg_out = pmt.dict_add(msg_out, pmt.intern('doppler'), pmt.to_pmt(doppler))
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## print(msg_out)
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self.message_port_pub(self._port_doppler, msg_out)
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@ -64,7 +64,7 @@ class msg_proxy(gr.basic_block):
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msg_out = pmt.dict_add(msg_out, pmt.intern('symb'), pmt.to_pmt(symb['symb']))
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msg_out = pmt.dict_add(msg_out, pmt.intern('scramble'), pmt.to_pmt(symb['scramble']))
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msg_out = pmt.dict_add(msg_out, pmt.intern('constellation_idx'), pmt.to_pmt(constellation_idx))
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msg_out = pmt.dict_add(msg_out, pmt.intern('do_continue'), pmt.to_pmt(do_continue))
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msg_out = pmt.dict_add(msg_out, pmt.intern('save_soft_dec'), pmt.to_pmt(save_soft_dec))
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msg_out = pmt.dict_add(msg_out, pmt.intern('do_continue'), pmt.to_pmt(np.bool(do_continue)))
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msg_out = pmt.dict_add(msg_out, pmt.intern('save_soft_dec'), pmt.to_pmt(np.bool(save_soft_dec)))
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## print(msg_out)
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self.message_port_pub(self._port_frame_info, msg_out)
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@ -139,7 +139,7 @@ class PhysicalLayer(object):
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self._frame_counter += 1
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print('test:', symbols[self._mode['unknown']:], np.mean(np.real(symbols[self._mode['unknown']:])))
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if self._frame_counter < self._num_frames_per_block-2:
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success = np.bool(np.mean(np.real(symbols[self._mode['unknown']:])) > 0.7)
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success = np.mean(np.real(symbols[self._mode['unknown']:])) > 0.7
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return [self.get_next_data_frame(success),self._mode['ci'],success,success]
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def get_next_data_frame(self, success):
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@ -177,9 +177,7 @@ class PhysicalLayer(object):
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tpks = np.abs(cc[imax+3*16*sps:imax+5*16*sps])
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print('imax=', imax, 'apks=',apks,
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np.mean(apks), np.mean(tpks))
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success = np.bool(np.mean(apks) > 5*np.mean(tpks) and
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apks[0]/apks[1] > 0.5 and
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apks[0]/apks[1] < 2.0)
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success = np.mean(apks) > 5*np.mean(tpks) and apks[0]/apks[1] > 0.5 and apks[0]/apks[1] < 2.0
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if success:
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idx = np.arange(32*sps)
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pks = [np.correlate(iq_samples[imax+i*32*sps+idx],
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@ -183,7 +183,7 @@ class PhysicalLayer(object):
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pks = [np.correlate(iq_samples[imax+i*23*sps+idx],
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zp[i*23*sps+idx])[0]
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for i in range(8)]
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success = np.bool(np.mean(np.abs(pks)) > 2*np.mean(np.abs(cc[imax+11*sps+range(-sps,sps)])))
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success = np.mean(np.abs(pks)) > 2*np.mean(np.abs(cc[imax+11*sps+range(-sps,sps)]))
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print('test:',imax, np.mean(np.abs(pks)), np.mean(np.abs(cc[imax+11*sps+range(-sps,sps)])))
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if success:
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print('doppler apks', np.abs(pks))
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@ -198,10 +198,10 @@ class PhysicalLayer(object):
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pass
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def get_preamble_quality(self, symbols):
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return np.bool(np.abs(np.mean(symbols[-40:])) > 0.5)
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return np.abs(np.mean(symbols[-40:])) > 0.5
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def get_data_frame_quality(self, symbols):
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return np.bool(np.abs(np.mean(symbols[-31:])) > 0.5)
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return np.abs(np.mean(symbols[-31:])) > 0.5
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def decode_reinserted_preamble(self, symbols):
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## decode D0,D1,D2
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@ -46,7 +46,7 @@ class PhysicalLayer(object):
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idx = range(30,80)
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z = symbols[idx]*np.conj(self._preamble['symb'][idx])
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## print('quality_preamble',np.sum(np.real(z)<0), symbols[idx])
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success = np.bool(np.sum(np.real(z)<0) < 30)
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success = np.sum(np.real(z)<0) < 30
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frame_description = [self._data,self._mode,success,True]
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self._frame_counter += 1
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@ -69,7 +69,7 @@ class PhysicalLayer(object):
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pks = cc[(imax,imax+31*sps),]
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tpks = cc[imax+15*sps:imax+16*sps]
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## print('doppler: ', np.abs(pks), np.abs(tpks))
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success = np.bool(np.mean(np.abs(pks)) > 5*np.mean(np.abs(tpks)))
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success = np.mean(np.abs(pks)) > 5*np.mean(np.abs(tpks))
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doppler = np.diff(np.unwrap(np.angle(pks)))[0]/31/self._sps if success else 0
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return success,doppler
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