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authorandreas128 <Andreas>2017-01-29 15:18:40 +0000
committerandreas128 <Andreas>2017-01-29 15:18:40 +0000
commit6e0b2512e45b7a6ca03187814742cb0fe08964cb (patch)
tree763a30041c7bb539a45a3af6df17465ea6a13c7a /sync-measurement.py
parenta88e67cb485d6b4b7bc21aa3c9dedbab37190cb9 (diff)
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Add Amp characterization in sync-measurement.ipynb
Diffstat (limited to 'sync-measurement.py')
-rw-r--r--sync-measurement.py273
1 files changed, 273 insertions, 0 deletions
diff --git a/sync-measurement.py b/sync-measurement.py
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+
+# coding: utf-8
+
+# In[1]:
+
+get_ipython().magic('matplotlib inline')
+import numpy as np
+import time;
+from scipy import signal
+import matplotlib.pyplot as plt
+import matplotlib.colors as mpcol
+import src.dab_util as du
+
+
+# In[2]:
+
+import src.signal_gen as sg
+reload(sg)
+reload(du)
+
+
+# In[3]:
+
+path_in = "./input.dat"
+path_out = "./output.dat"
+a_max = 0.95
+n_steps = 64
+amps = np.linspace(0.001, a_max, num = n_steps)
+txgains = (50, 55, 60, 65, 70, 75, 81, 82, 83, 84, 85, 86, 87, 88, 89)
+rxgains = (50, 40, 40, 25, 25, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20)
+
+
+# In[4]:
+
+from grc.amam_amap import amam_amap
+
+
+# In[5]:
+
+top = amam_amap()
+
+
+# In[6]:
+
+sg.gen_ramps(amplitudes=amps)
+
+
+# In[7]:
+
+def fftlag(signal_original, signal_rec):
+ """
+ Efficient way to find lag between two signals
+ Args:
+ signal_original: The signal that has been sent
+ signal_rec: The signal that has been recored
+ """
+ c = np.flipud(signal.fftconvolve(signal_original,np.flipud(signal_rec)))
+ #plt.plot(c)
+ return np.argmax(c) - signal_original.shape[0] + 1
+
+#pattern = np.array([-2,2,-1,+3,-5,+7])
+#delays = [0,1,2,3,4]
+#padding = [0]
+#padding_fil = [0]
+#
+#res = []
+#for d in delays:
+# for p in padding:
+# for p2 in padding_fil:
+# a = np.concatenate((pattern, np.zeros(p2)))
+# b = np.concatenate((np.zeros(d), pattern, np.zeros(p)))
+# res.append((d,conv(a,b)))
+#res = np.array(res)
+#plt.plot(zip(*res)[0], zip(*res)[1], 'p')
+
+
+# In[ ]:
+
+
+
+
+# In[ ]:
+
+
+
+
+# In[8]:
+
+def get_amp_ratio(ampl_1, ampl_2, a_out_abs, a_in_abs):
+ idxs = (a_in_abs > ampl_1) & (a_in_abs < ampl_2)
+ ratio = a_out_abs[idxs] / a_in_abs[idxs]
+ return ratio.mean(), ratio.var()
+
+def get_phase(ampl_1, ampl_2, a_out, a_in):
+ idxs = (np.abs(a_in) > ampl_1) & (np.abs(a_in) < ampl_2)
+ ratio = np.angle(a_out[idxs], deg=True) - np.angle(a_in[idxs], deg=True)
+ return ratio.mean(), ratio.var()
+
+
+# In[9]:
+
+def extract_measurement(a_in, a_out, db, a_max, n_steps, debug = False):
+ a_in = du.crop_signal(a_in)
+ a_out = du.crop_signal(a_out)
+
+ if debug:
+ plt.plot(np.abs(a_in.real) + 1, color='b');
+ plt.plot(np.abs(a_out.real), color='g');
+ plt.show()
+
+ #l = min(a_out.shape[0], a_in.shape[0])
+ #a_out = a_out[0:l]
+ #a_in = a_in[0:l]
+
+ #c = du.lagcorr(np.abs(a_out), np.abs(a_in), 120000)[:,0]
+ #c = signal.fftconvolve(a_in, a_out) - a_out.shape[0]
+ delay = fftlag(np.abs(a_in), np.abs(a_out))
+
+
+ #delay = np.argmax(c)
+ a_out = a_out[delay - 1:]
+
+ l = min(a_out.shape[0], a_in.shape[0])
+ a_out = a_out[0:l]
+ a_in = a_in[0:l]
+
+ if debug:
+ print ("delay = " + str(delay))
+ plt.plot(np.abs(a_in), color='g');
+ plt.plot(np.abs(a_out) - 0.5, color='y');
+ plt.show()
+
+ bins = np.linspace(+0.5/n_steps,a_max + 0.5/n_steps,num=n_steps)
+ res = []
+ a_out_abs = np.abs(a_out)
+ a_in_abs = np.abs(a_in)
+ for ampl_1, ampl_2 in zip(bins, bins[1:]):
+ res.append(get_amp_ratio(ampl_1, ampl_2, a_out_abs, a_in_abs))
+ del a_out_abs
+ del a_in_abs
+ mean_amp, var_amp = zip(*res)
+
+ res = []
+ for ampl_1, ampl_2 in zip(bins, bins[1:]):
+ res.append(get_phase(ampl_1, ampl_2, a_out, a_in))
+ mean_phase, var_phase = zip(*res)
+ return mean_amp, var_amp, mean_phase, var_phase, db
+
+
+# In[ ]:
+
+
+
+
+# In[10]:
+
+res = []
+
+for txgain, rxgain in zip(txgains, rxgains):
+ print (txgain, rxgain)
+ res_tmp = None
+ for i in range(10):
+ top.uhd_usrp_sink_0_0.set_gain(txgain)
+ top.uhd_usrp_source_0.set_gain(rxgain)
+
+ top.file_sink_out.close()
+ top.blocks_file_source_0.close()
+
+ top.file_sink_out.open(path_out)
+ top.blocks_file_source_0.open(path_in, False)
+ top.start()
+
+ time.sleep(1)
+
+ top.stop()
+ top.wait()
+
+ a_in = np.fromfile(path_in, dtype=np.complex64)
+ a_out = np.fromfile(path_out, dtype=np.complex64)
+ res_tmp = extract_measurement(a_in, a_out, txgain, a_max, n_steps, debug=True)
+
+ def is_finite(r): return np.all([np.all(np.isfinite(c)) for c in r])
+ def has_small_jumps(mean_amp): return np.max(np.abs(np.diff(mean_amp))) / np.median(np.abs(np.diff(mean_amp))) < 100
+
+ if is_finite(res_tmp) and has_small_jumps(res_tmp[0]):
+ break
+ else:
+ print (is_finite(res_tmp), has_small_jumps(res_tmp[0]))
+
+ res.append(res_tmp)
+
+
+# In[ ]:
+
+
+
+
+# In[47]:
+
+fig = plt.figure(figsize=(10,10))
+ax1 = plt.subplot(211)
+
+def plot_with_label(x, y, color, label):
+ ax1.plot(x, y, color=color, label=txgain)
+
+for idx, (txgain, rxgain) in enumerate(zip(*(txgains, rxgains))):
+ plot_with_label(
+ x = amps[1:],
+ y = 10*np.log(res[idx][0])/np.log(10) - rxgain + 102,
+ color = mpcol.hsv_to_rgb((idx * 0.75 / len(txgains), 0.6, 1)),
+ label = txgain
+ )
+ax1.set_ylabel("Gain [dB]")
+
+ax2 = plt.subplot(212)
+
+def plot_with_label(x, y, color, label):
+ ax2.plot(x, y, color=color, label=txgain)
+
+for idx, (txgain, rxgain) in enumerate(zip(*(txgains, rxgains))):
+ plot_with_label(
+ x = amps[1:],
+ y = res[idx][2],
+ color = mpcol.hsv_to_rgb((idx * 0.75 / len(txgains), 0.6, 1)),
+ label = txgain
+ )
+
+ax2.set_ylabel("Pase [degree]")
+ax2.set_xlabel("Amplitude")
+
+#legend
+# Shrink current axis by 20%
+box = ax1.get_position()
+ax1.set_position([box.x0, box.y0, box.width * 0.8, box.height])
+box = ax2.get_position()
+ax2.set_position([box.x0, box.y0, box.width * 0.8, box.height])
+
+# Put a legend to the right of the current axis
+ax1.legend(loc='center left', bbox_to_anchor=(1.05, -0.3))
+
+
+plt.show()
+
+
+# In[ ]:
+
+
+
+
+# In[ ]:
+
+
+
+
+# In[205]:
+
+
+
+
+# In[ ]:
+
+
+
+
+# In[ ]:
+
+
+
+
+# In[ ]:
+
+
+