Added functionality for the TNMR module to write partial scans - useful for long experiments with many acquisitions, which might need to be terminated early. Also good for impatient people. Added functionality to the ZVL Network Analyser module to allow for use of inbuilt data correction (calibration).

frappy_psi/network_analysers/ZVL/test.py

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+from ZVLDriver import *
+import matplotlib.pyplot as plt
+
+# example code. profiles the per-point delay for reading data and   
+ip = '129.129.156.201'
+ip = '169.254.83.53'
+import matplotlib.pyplot as plt
+print('start')
+z = ZVLNetAnalyzer()
+z.reset()
+
+
+#mm, mmi, fr, frq = z.find_peak(50_000_000, 350_000_000, 20_000_000)
+#plt.plot(frq, fr)
+#plt.axvline(frq[mmi])
+#plt.axhline(mm)
+#plt.show()
+
+#z.reset()
+##z.set_freq_range(1_000_000, 2_000_000.5)
+##z.set_freq_span(1_000_000, 10_000)
+z.set_freq_range(25_750_000, 75_250_000)
+plt.scatter(*(z.get_data()))
+
+z.reload_calibration()
+#z.set_freq_span(220_000_000, 50_000_000)
+plt.scatter(*(z.get_data()))
+plt.show()
+
+#Ns = np.linspace(3, 1000, 100).astype(int)
+#ts = []
+#for N in Ns:
+#    st = time.time()
+#    freqs, data = z.get_data(N)
+#    et = time.time()
+#    dt = (et-st)
+#    print(f'got data, {dt/N} ({dt})')
+#    ts += [dt]
+#
+#plt.scatter(Ns, ts)
+#plt.show()
+#plt.scatter(Ns, np.array(ts)/np.array(Ns))
+#plt.show()
+    
+#input()
+#plt.plot(*z.get_data(averaging_passes=1), alpha=0.3)
+#plt.plot(*z.get_data(averaging_passes=64), alpha=0.3)
+#plt.show()
+
+input()