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/ZVLDriver.py

@@ -30,32 +30,50 @@ class ZVLNetAnalyzer():
         self.base_data = np.array([])
         self.base_data = self.get_data()[1]
         
+        self.min_freq = 0
+        self.max_freq = 0
+        
     def reset(self):
-        #self.instrument.write('*RST')
-        #self.instrument.write('SYST:PRES') # reloads current setup.
-        self.instrument.write('*CLS')
+        self.instrument.write('*RST')
         self.instrument.write('INST:NSEL 2')
         self.instrument.write('DISPlay:WINDow1:STATe ON')
         self.instrument.write(":CALC:PAR:MEAS 'Trc1', 'S11'")
         self.instrument.write('CALC:FORM MLOG')
         self.instrument.write('INIT:CONT OFF')
         self.instrument.write("SYST:USER:DISP:TITL 'Frappy connection'")
-        #self.instrument.write('INIT:SCOP OFF')
-        #self.instrument.write('DISPlay:WINDow2:STATe ON')
+        self.instrument.write('*ESE')
+        
+        self.min_freq, self.max_freq = self.get_freq_range() # default is largest.
     
-    def load_calibration(self, f):
-        self.instrument.write(f":MMEMORY:STORE:CORR 1, 'OSM1 {f}'") # put calibration in pool
-        self.instrument.write(f":MMEMORY:LOAD:CORR 1, 'OSM1 {f}'") # load from pool
+    def reload_calibration(self):
+        self.reset()
+        #self.instrument.write("DISP:MENU:KEY:SEL 'Correction Off'")
+        #self.instrument.write("DISP:MENU:KEY:EXEC 'Correction Off'")
+        self.instrument.write("DISP:MENU:KEY:EXEC 'Recall Last Cal Set'")
+        time.sleep(1)
+        self.min_freq, self.max_freq = self.get_freq_range() # default is largest.
+        
+    def get_freq_range(self):
+        start = float(self.instrument.ask('SENS1:FREQ:STAR?'))
+        stop = float(self.instrument.ask('SENS1:FREQ:STOP?'))
+    
+        return start, stop
     
     def set_freq_range(self, start, stop):
         '''In Hz'''
-        self.instrument.write(f'SENS1:FREQ:STAR {start}')
-        self.instrument.write(f'SENS1:FREQ:STOP {stop}')
+        if(start >= self.min_freq) and (stop <= self.max_freq):
+            
+            self.instrument.write(f'SENS1:FREQ:STAR {start}')
+            self.instrument.write(f'SENS1:FREQ:STOP {stop}')
+            self.start_freq = start
+            self.stop_freq = stop
         
     def set_freq_span(self, center, span):
         '''In Hz'''
-        self.instrument.write(f'SENS1:FREQ:CENT {center}')
-        self.instrument.write(f'SENS1:FREQ:SPAN {span}')
+        start = center - span/2
+        stop = center + span/2
+        
+        self.set_freq_range(start, stop)
         
     def set_averaging_passes(self,avgs):
         '''
@@ -101,6 +119,7 @@ class ZVLNetAnalyzer():
         assert(averaging_passes<=999)
         assert(units in ['dB', 'unitless'])
             
+        self.instrument.write('INIT:CONT OFF')
         self.instrument.write(f'SWE:POIN {N}')
         self.instrument.write(f'SWE:COUN {averaging_passes}')
         

frappy_psi/network_analysers/ZVL/test.py

@@ -0,0 +1,50 @@
+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()