src/monitor/radio/constants.py

@@ -23,7 +23,7 @@ START_FREQ = 100e6
 END_FREQ = 6000e6
 
 MAX_INST_BW = 30.72e6
-ANALOG_BW_CUTOFF_FACTOR = 0.9 #0.82 
+ANALOG_BW_CUTOFF_FACTOR = 0.9
 # Effective bandwidth we are monitoring
 ANALOG_BW = MAX_INST_BW * ANALOG_BW_CUTOFF_FACTOR # 27e6
 
@@ -59,7 +59,7 @@ COLLECT_SAMPLE = 0
 OFFSET_TEST = 0
 
 # tune request takes lo_offset
-OFFSET = 0 #0.43 * MAX_INST_BW
+OFFSET = 0
 
 #----------------------------------------------------------
 #----------------------------------------------------------
@@ -67,7 +67,7 @@ OFFSET = 0 #0.43 * MAX_INST_BW
 #----------------------------------------------------------
 
 # total data points collected
-N_SAMPLES = int(1e4) #int(2e4)
+N_SAMPLES = int(10240) #int(2e4)
 
 
 #----------------------------------------------------------

src/monitor/radio/device.py

@@ -97,7 +97,7 @@ class Device():
 
         # set to a default value to initialize the radio
         for chan in self.chans:
-            self.usrp.set_rx_rate(self.rate, chan)
+            self.usrp.set_rx_rate(self.rate, chan) #C.MAX_INST_BW
             self.usrp.set_rx_freq(uhd.libpyuhd.types.tune_request(2400e6,C.OFFSET), chan)
             self.usrp.set_rx_gain(self.gain, chan)
 

src/monitor/radio/iso_receiver.py

@@ -346,8 +346,6 @@ class IsoReceiver(receiver.Receiver):
             f.close()
 
         # shuffle data 
-        seed = random.randint(5, 50)
-        np.random.seed(seed) #for reproducibility
         shuffled_indices = np.arange(len(Center_freqs))
         np.random.shuffle(shuffled_indices)
         Freqs_shuffle = Center_freqs[shuffled_indices]
@@ -364,7 +362,7 @@ class IsoReceiver(receiver.Receiver):
                 save_samp0 = np.reshape(real_img0, -1, order='F')
                 save_samp0 = save_samp0.reshape(-1,1)
 
-                a = array(save_samp0,'float32')
+                a = np.array(save_samp0,'float32')
                 output_file = open('sample0.txt', 'wb')
                 a.tofile(output_file)
                 output_file.close()
@@ -373,7 +371,7 @@ class IsoReceiver(receiver.Receiver):
                 save_samp1 = np.reshape(real_img1, -1, order='F')
                 save_samp1 = save_samp1.reshape(-1,1)
 
-                a = array(save_samp1,'float32')
+                a = np.array(save_samp1,'float32')
                 output_file = open('sample1.txt', 'wb')
                 a.tofile(output_file)
                 output_file.close()
@@ -410,9 +408,9 @@ class IsoReceiver(receiver.Receiver):
             freqs_out[m,:] = freqs/1e6
 
             # extend devs, times to match the number of lines found per iteration.
-            trep = np.tile(int(time.time()), C.N_BINS_OUT_PER_STEP ) # C.N_SAMPLES
-            devrep = np.tile(rf_port, C.N_BINS_OUT_PER_STEP)
-            cfrep = np.tile(center_freq/1e6, C.N_BINS_OUT_PER_STEP)
+            trep = np.tile(int(time.time()), C.N) # C.N_SAMPLES
+            devrep = np.tile(rf_port, C.N)
+            cfrep = np.tile(Center_freqs[m]/1e6, C.N)
             
             times = np.append(times, trep)
             devs = np.append(devs, devrep)

src/monitor/radio/source_separation.py

@@ -50,7 +50,7 @@ class source_separation(object):
 		FFT_R0_ori = np.fft.fftshift(FFT_R0_ori)
 		FFT_R1_ori = np.fft.fftshift(FFT_R1_ori)
 		FREQ0 = np.fft.fftshift(FREQ0)
-
+		
 		################ reject samples above cutoff ##################
 		if n_remove !=0:
 			FFT_R0_ori = FFT_R0_ori[n_remove:-n_remove] 
@@ -82,11 +82,11 @@ class source_separation(object):
 		# 	print('len(ids1[ids1_check]), len(ids1)',len(ids1[ids1_check]), len(ids1))
 
 		if len(ids0[ids0_check]) < len(ids0):
-		    ids0 = ids0[ids0_check] 
-		    
-		     
+			ids0 = ids0[ids0_check]
+
+
 		if len(ids1[ids1_check]) < len(ids1):
-		    ids1 = ids1[ids1_check]
+			ids1 = ids1[ids1_check]
 
 		################### how many signal components in R0 ##################
 		idx0_diff = np.diff(ids0,n=1)
@@ -100,48 +100,48 @@ class source_separation(object):
 
 		#################  find the number of singal components   ################
 		if len(idx0_comp)>=len(idx1_comp): # detected signal components
-		    idx_comp = idx0_comp
-		    ids = ids0
+			idx_comp = idx0_comp
+			ids = ids0
 		else:
-		    idx_comp = idx1_comp
-		    ids = ids1
+			idx_comp = idx1_comp
+			ids = ids1
 
 		if not len(idx_comp): # only one signal component--no need for division
-		    SS_list = [self.rx_fft]
-		    self.cfreq_bin.append(self.Center_freq)
+			SS_list = [self.rx_fft]
+			self.cfreq_bin.append(self.Center_freq)
 
 		elif len(idx_comp)==1: # Two signal components
-		    bin_freq = FREQ0[np.argmin(FFT_R0_ori[ ids[idx_comp[0]]:ids[idx_comp[0]+1] ]) + ids[idx_comp[0]]]
-		    bin_line = np.argmin(np.abs(rx_freq-bin_freq))
+			bin_freq = FREQ0[np.argmin(FFT_R0_ori[ ids[idx_comp[0]]:ids[idx_comp[0]+1] ]) + ids[idx_comp[0]]]
+			bin_line = np.argmin(np.abs(rx_freq-bin_freq))
 		    # if self.debug:
 		    # 	print('bin_line',bin_line)
 
-		    SS_list = [np.vstack((self.rx_fft[0,0:bin_line], self.rx_fft[1,0:bin_line])), \
+			SS_list = [np.vstack((self.rx_fft[0,0:bin_line], self.rx_fft[1,0:bin_line])), \
 		             np.vstack((self.rx_fft[0,bin_line:len(self.rx_fft[0,:])], \
 		             			self.rx_fft[1,bin_line:len(self.rx_fft[0,:])]))]
 
-		    self.cfreq_bin.append(rx_freq[int(bin_line/2)] + self.Center_freq)
-		    self.cfreq_bin.append(rx_freq[int((bin_line+self.num_sampes-1)/2)] + self.Center_freq)
+			self.cfreq_bin.append(rx_freq[int(bin_line/2)] + self.Center_freq)
+			self.cfreq_bin.append(rx_freq[int((bin_line+self.num_sampes-1)/2)] + self.Center_freq)
 
 		else: # more than two signal components
-		    bin_line = []
-		    for idd in idx_comp:
-		        bin_freq = FREQ0[np.argmin(FFT_R0_ori[ ids[idd]:ids[idd+1] ]) + ids[idd]]
-		        bin_line.append(np.argmin(np.abs(rx_freq-bin_freq)))
+			bin_line = []
+			for idd in idx_comp:
+				bin_freq = FREQ0[np.argmin(FFT_R0_ori[ ids[idd]:ids[idd+1] ]) + ids[idd]]
+				bin_line.append(np.argmin(np.abs(rx_freq-bin_freq)))
 		    # if self.debug:
 		    # 	print('bin_line, partitions',bin_line, len(bin_line)+1)
 
-		    SS_list = [np.vstack((self.rx_fft[0,0:bin_line[0]], self.rx_fft[1,0:bin_line[0]]))]
-		    self.cfreq_bin.append(rx_freq[int(bin_line[0]/2)] + self.Center_freq)
+			SS_list = [np.vstack((self.rx_fft[0,0:bin_line[0]], self.rx_fft[1,0:bin_line[0]]))]
+			self.cfreq_bin.append(rx_freq[int(bin_line[0]/2)] + self.Center_freq)
 
-		    for n in range(len(bin_line)-1):
-		        SS_list.append( np.vstack((self.rx_fft[0,bin_line[n]:bin_line[n+1]], \
-		        							self.rx_fft[1,bin_line[n]:bin_line[n+1]])) )
-		        self.cfreq_bin.append(rx_freq[int((bin_line[n]+bin_line[n+1])/2)] + self.Center_freq)
+			for n in range(len(bin_line)-1):
+				SS_list.append( np.vstack((self.rx_fft[0,bin_line[n]:bin_line[n+1]], \
+		    								self.rx_fft[1,bin_line[n]:bin_line[n+1]])) )
+				self.cfreq_bin.append(rx_freq[int((bin_line[n]+bin_line[n+1])/2)] + self.Center_freq)
 		    
-		    SS_list.append(np.vstack((self.rx_fft[0,bin_line[-1]:len(self.rx_fft[0,:])], \
+			SS_list.append(np.vstack((self.rx_fft[0,bin_line[-1]:len(self.rx_fft[0,:])], \
 		    						self.rx_fft[1,bin_line[-1]:len(self.rx_fft[0,:])])))
-		    self.cfreq_bin.append(rx_freq[int((bin_line[-1]+self.num_sampes-1)/2)] + self.Center_freq)
+			self.cfreq_bin.append(rx_freq[int((bin_line[-1]+self.num_sampes-1)/2)] + self.Center_freq)
 		
 		return SS_list
 	
@@ -191,10 +191,10 @@ class source_separation(object):
 		# 	print('idx_highest', idx_highest)
 
 		if idx_highest%2:
-		    A_temp = np.array([[0,1],[1,0]]) @ A_temp
-		    SShat = np.vstack((SShat[1,:],SShat[0,:])) 
+			A_temp = np.array([[0,1],[1,0]]) @ A_temp
+			SShat = np.vstack((SShat[1,:],SShat[0,:])) 
 		else:
-		    pass
+			pass
 
 		self.mix_matrix.append(A_temp)
 		if self.debug:
@@ -292,7 +292,7 @@ class source_separation(object):
 			sep_samp0 = np.reshape(real_img0, -1, order='F')
 			sep_samp0 = sep_samp0.reshape(-1,1)
 
-			a = array(sep_samp0,'float32')
+			a = np.array(sep_samp0,'float32')
 			output_file = open('sep_sample0.txt', 'wb')
 			a.tofile(output_file)
 			output_file.close()
@@ -301,7 +301,7 @@ class source_separation(object):
 			sep_samp1 = np.reshape(real_img1, -1, order='F')
 			sep_samp1 = sep_samp1.reshape(-1,1)
 
-			a = array(sep_samp1,'float32')
+			a = np.array(sep_samp1,'float32')
 			output_file = open('sep_sample1.txt', 'wb')
 			a.tofile(output_file)
 			output_file.close()
@@ -345,11 +345,11 @@ class source_separation(object):
 			print('main_raw',main_raw,'\n')
 		
 		if main_raw!=main_ss:
-		    for m in range(len(self.cfreq_bin)):
-		        self.mix_matrix[m] = np.array([[0,1],[1,0]]) @ self.mix_matrix[m]
-		    sep_db = np.vstack((esti1,esti0))
+			for m in range(len(self.cfreq_bin)):
+				self.mix_matrix[m] = np.array([[0,1],[1,0]]) @ self.mix_matrix[m]
+			sep_db = np.vstack((esti1,esti0))
 		else:
-		    sep_db = np.vstack((esti0,esti1))
+			sep_db = np.vstack((esti0,esti1))
 
 		if issave:
 			# get mixing matrix