Update Code/HoseiPlot.py

Code/HoseiPlot.py

@@ -11,24 +11,34 @@ import shutil
 import csv
 basePath = os.getcwd()
 
-postprocjump = 0
+## Amount of INL averages
+nrepeats = 2
 ## Initialize GPIB adapter
 GPIB = GPIBPrologix.ResourceManager("/dev/ttyACM0")
 # Connect equipment
-#inst2 = GPIB.open_resource(30) # 4805
+inst2 = GPIB.open_resource(30) # 4805
 inst3 = GPIB.open_resource(22) # 3458A
 inst4 = GPIB.open_resource(16) # R6581T
+try:
+    os.remove("data_post.csv")
+except:
+    print('no datafile found to remove')
+try:
+    os.remove("data.csv")
+except:
+    print('no datafile found to remove')
+
 # Initialize BME280 temperature/humidity sensor
 bus = smbus2.SMBus(1)
 ## Configure equipment
 # BME280 temperature/humidity sensor
 calibration_params = bme280.load_calibration_params(bus, 0x76)
-if postprocjump == 1:
 # Datron 4805 Calibrator
 inst2.query("F0=")       #DCV
 inst2.query("R6=")       #10/100K Range
-    inst2.query("S1=")       #RemoteSense
+inst2.write("G0=") #Local guard
-    inst2.query("M0.0069=")  #6.9mV Out, sanity check
+inst2.write("S0=") #Local sense
+inst2.query("M-11.5=")  #6.9mV Out, sanity check
 inst2.query("O1=")       #OutputON
 #Setup 3458A
 #inst3.write("PRESET NORM")
@@ -49,6 +59,18 @@ if postprocjump == 1:
 inst4.write(":SENS:VOLT:DC:NPLC 100")
 inst4.write(":SENS:VOLT:DC:DIG MAX")
 inst4.write(":ZERO:AUTO ON")
+
+# save original INL constants
+with open(basePath+"/original_hosei.txt", 'a') as f:
+    f.write(inst4.query("CAL:INT:DCV:HOSEI?"))
+# write Advantest correction to zero, in theory not needed as at the end coefficients get summed.
+inst4.write("CAL:EXT:EEPROM:PROTECTION 1")
+for i in range(15):
+    print("CAL:INT:DCV:HOSEI {},{}".format(i,0))
+    inst4.write("CAL:INT:DCV:HOSEI {},{}".format(i,0))
+inst4.write("CAL:INT:DCV:HOSEI {},{}".format(15,1))
+print("CAL:INT:DCV:HOSEI {},{}".format(15,1))
+
 # Measurement functions
 def readValue(instObj,handle):
     out = ""
@@ -63,11 +85,11 @@ if postprocjump == 1:
     return out
 def setValue(instObj, inputVar):
     instObj.query("M"+str(inputVar)+"=")
+    time.sleep(40)
     return inputVar
 def getEnvironment(instObj, i2cbus):
     value = instObj.sample(i2cbus, 0x76, calibration_params)
     return value
-    setValue(inst2,-1)
 #inst3.write("BEEP")
 print('3458A reading: ',readValue(inst3,"3458A"))
 #inst4.write("BEEP")
@@ -86,36 +108,33 @@ if postprocjump == 1:
     writer.writerow(["DateTime","SetVolts","RefVolts","DutVolts","Env Pressure","Env Temperature", "Env Humidity"])
 print(basePath+"/data.csv")
 
-    sweep = np.append(np.linspace(-11.5,11.5,int(11.5/0.5*2)+1), np.linspace(-0.1,0,int(0.1/0.01)+1))
-    sweep = sorted(sweep)
-
 cntr = 0
 d     = datetime.datetime.now()
 dlast = datetime.datetime.now()
 ## Collect data
 time.sleep(3)
+for n in range(nrepeats):
+    sweep = np.append(np.linspace(-10,10,int(10/2*2)+1), np.linspace(-0.1,-0.02,int((0.1-0.02)/0.02)+1))
+    np.random.shuffle(sweep)
     for x in sweep:
         cntr = cntr + 1
         try:
             #Set volt and let accimatize
             setPoint = setValue(inst2,round(x,5))
-            timebetween = (d-dlast) * (len(sweep)-cntr)
+            timebetween = (d-dlast) * (len(sweep)*nrepeats-cntr)
             dlast = d
-            print(str(cntr)+'/'+str(len(sweep))+' Estimated Time Left: '+str(timebetween))
+            print(str(cntr)+'/'+str(len(sweep)*nrepeats)+' Estimated Time Left: '+str(timebetween))
-            time.sleep(60)
             for i in range(3):
                 try:
-                    time.sleep(5)
                     #Get DUT value
                     readoutRef = readValue(inst3,"3458A")
                     readoutDut = readValue(inst4,"6581T")
-
                     #Get envirnmental values
                     data = getEnvironment(bme280, bus)
                     #Write to file
                     d = datetime.datetime.now()
                     dx = d - datetime.timedelta(microseconds=d.microsecond)
-                    fields=[dx.strftime("%d-%m-%y %H:%M:%S"),setPoint,float(readoutRef),float(readoutDut),round(data.humidity,2),round(data.temperature,2),round(data.pressure,2)]
+                    fields=[dx.strftime("%d-%m-%y %H:%M:%S"),setPoint,float(readoutRef),float(readoutDut),round(data.pressure,2),round(data.temperature,2),round(data.humidity,2)]
                     print(fields)
                     with open(basePath+"/data.csv", 'a') as f:
                         writer = csv.writer(f)
@@ -128,28 +147,36 @@ if postprocjump == 1:
             time.sleep(1)
 
 #  initialize the image to plot as correction goes
-fig = make_subplots(rows=4, cols=1)
+fig = make_subplots(rows=3, cols=1)
 
 ## Calculate high order polynomial
 df = pd.read_csv(basePath+"/data.csv")
 df = df.groupby(["SetVolts"], as_index=False).mean(numeric_only=True)
-
+tmpa = df.loc[df['SetVolts'] == 0]["RefVolts"].iloc[0]
+tmpb = df.loc[df['SetVolts'] == 0]["DutVolts"].iloc[0]
 #  compensate for offset error around 0 -> this is cal error instead of INL
-df["RefVolts"] = df["RefVolts"] - df.loc[df['SetVolts'] == 0]["RefVolts"].iloc[0]
+df["RefVolts"] = df["RefVolts"] - tmpa
-df["DutVolts"] = df["DutVolts"] - df.loc[df['SetVolts'] == 0]["DutVolts"].iloc[0]
+df["DutVolts"] = df["DutVolts"] - tmpb
+#df["OptVolts"] = df["OptVolts"] - df.loc[df['SetVolts'] == 0]["OptVolts"].iloc[0]
 
 #  get 1st order to 10V -> 10V gain error, this is cal error instead of INL, -10 could be due to INL.
 #  this is heavily dependant on cal procedure, say 7V is the reference calibration point
 alphaRef = df.loc[df['SetVolts'] == 10]["RefVolts"].iloc[0]/10
 alphaDut = df.loc[df['SetVolts'] == 10]["DutVolts"].iloc[0]/10
+#alphaOpt = df.loc[df['SetVolts'] == 10]["OptVolts"].iloc[0]/10
 #  remove 1st order to get the INL
 df["RefVolts"] = df["RefVolts"] - alphaRef*df['SetVolts']
 df["DutVolts"] = df["DutVolts"] - alphaDut*df['SetVolts']
+#df["OptVolts"] = df["OptVolts"] - alphaOpt*df['SetVolts']
 df["DutToRefVolts"] = df['DutVolts'] - df["RefVolts"]
 #  plot INL of calibrator
 fig.add_trace(go.Scatter(x=df['SetVolts'], y=df["RefVolts"],mode='lines+markers',name='Original REF INL'),row=1, col=1)
 fig.add_trace(go.Scatter(x=df['SetVolts'], y=df["DutVolts"],mode='lines+markers',name='Original DUT INL'),row=1, col=1)
-fig.add_trace(go.Scatter(x=df['SetVolts'], y=df["DutToRefVolts"],mode='lines+markers',name='DUT vs REF'),row=2, col=1)
+#fig.add_trace(go.Scatter(x=df['SetVolts'], y=df["OptVolts"],mode='lines+markers',name='Original OPT INL'),row=1, col=1)
+fig.add_trace(go.Scatter(x=df['SetVolts'], y=df["DutToRefVolts"],mode='lines+markers',name='Original DUT vs REF'),row=2, col=1)
+## Make plot and save
+fig.write_html('inl_evaluation_plots.html')
+fig.write_image('inl_evaluation_plots.png',width=720, height=1280)
 
 #  generate correction parameters
 #  default correction assumed unless minMaxEqual is set, this will equalize error above and under ideal correction
@@ -181,14 +208,93 @@ else:
     correctionfactors[13] = (df.loc[df['SetVolts'] ==    -8]["DutToRefVolts"].iloc[0] - df.loc[df['SetVolts'] ==    -6]["DutToRefVolts"].iloc[0])/2
     correctionfactors[14] = (df.loc[df['SetVolts'] ==   -10]["DutToRefVolts"].iloc[0] - df.loc[df['SetVolts'] ==    -8]["DutToRefVolts"].iloc[0])/2
     # negative 10v voltage reversal alpha error for faster measurements
-    correctionfactors[15] = 1+minusRangeScaling
+    correctionfactors[15] = round(1+minusRangeScaling,8)
-    # negative 10v voltage reversal alpha error for faster measurements
 
-## Make plot and save
-fig.write_image('inl_evaluation_plots.png',width=720, height=1280)
-fig.write_html('inl_evaluation_plots.html')
 ## Read the HOSEI parameters and save the original constants
+## add constants together in case of nonzero sweep constants
 inst4.write("CAL:EXT:EEPROM:PROTECTION 1")
 print(inst4.query("CAL:INT:DCV:HOSEI?"))
-with open(basePath+"/original_hosei.txt", 'a') as f:
+tmp = inst4.query("CAL:INT:DCV:HOSEI?")
+tmp = tmp.replace(',',' ').split()[1::2]
+tmp = [float(i) for i in tmp[:-2]]
+correctionfactors = [round(tmp[i]+correctionfactors[i],8) for i in range(0,len(correctionfactors)-1)]
+correctionfactors.append(1+minusRangeScaling+1-tmp[15])
+for idx in  range(0,len(correctionfactors)):
+    print("CAL:INT:DCV:HOSEI {},{}".format(idx,correctionfactors[idx]))
+    inst4.write("CAL:INT:DCV:HOSEI {},{}".format(idx,correctionfactors[idx]))
+with open(basePath+"/new_hosei.txt", 'a') as f:
     f.write(inst4.query("CAL:INT:DCV:HOSEI?"))
+print(inst4.query("CAL:INT:DCV:HOSEI?"))
+inst4.write("CAL:EXT:EEPROM:PROTECTION 0")
+
+## Create logfile
+with open(basePath+"/data_post.csv", 'a') as f:
+    writer = csv.writer(f)
+    writer.writerow(["DateTime","SetVolts","RefVolts","DutVolts","Env Pressure","Env Temperature", "Env Humidity"])
+print(basePath+"/data_post.csv")
+
+cntr = 0
+d     = datetime.datetime.now()
+dlast = datetime.datetime.now()
+## Collect data
+time.sleep(3)
+for n in range(nrepeats):
+    sweep = np.append(np.linspace(-10,10,int(10/2*2)+1), np.linspace(-0.1,-0.02,int((0.1-0.02)/0.02)+1))
+    np.random.shuffle(sweep)
+    for x in sweep:
+        cntr = cntr + 1
+        try:
+            #Set volt and let accimatize
+            setPoint = setValue(inst2,round(x,5))
+            timebetween = (d-dlast) * (len(sweep)*nrepeats-cntr)
+            dlast = d
+            print(str(cntr)+'/'+str(len(sweep)*nrepeats)+' Estimated Time Left: '+str(timebetween))
+            for i in range(3):
+                try:
+                    #Get DUT value
+                    readoutRef = readValue(inst3,"3458A")
+                    readoutDut = readValue(inst4,"6581T")
+                    #Get envirnmental values
+                    data = getEnvironment(bme280, bus)
+                    #Write to file
+                    d = datetime.datetime.now()
+                    dx = d - datetime.timedelta(microseconds=d.microsecond)
+                    fields=[dx.strftime("%d-%m-%y %H:%M:%S"),setPoint,float(readoutRef),float(readoutDut),round(data.pressure,2),round(data.temperature,2),round(data.humidity,2)]
+                    print(fields)
+                    with open(basePath+"/data_post.csv", 'a') as f:
+                        writer = csv.writer(f)
+                        writer.writerow(fields)
+                except Exception as e: 
+                    time.sleep(15)
+                    i = i-1
+        except Exception as e: 
+            print(e)
+            time.sleep(1)
+
+# Calculate high order polynomial
+df = pd.read_csv(basePath+"/data_post.csv")
+df = df.groupby(["SetVolts"], as_index=False).mean(numeric_only=True)
+
+#  compensate for offset error around 0 -> this is cal error instead of INL
+df["RefVolts"] = df["RefVolts"] - df.loc[df['SetVolts'] == 0]["RefVolts"].iloc[0]
+df["DutVolts"] = df["DutVolts"] - df.loc[df['SetVolts'] == 0]["DutVolts"].iloc[0]
+#df["OptVolts"] = df["OptVolts"] - df.loc[df['SetVolts'] == 0]["OptVolts"].iloc[0]
+
+#  get 1st order to 10V -> 10V gain error, this is cal error instead of INL, -10 could be due to INL.
+#  this is heavily dependant on cal procedure, say 7V is the reference calibration point
+alphaRef = df.loc[df['SetVolts'] == 10]["RefVolts"].iloc[0]/10
+alphaDut = df.loc[df['SetVolts'] == 10]["DutVolts"].iloc[0]/10
+#alphaOpt = df.loc[df['SetVolts'] == 10]["OptVolts"].iloc[0]/10
+#  remove 1st order to get the INL
+df["RefVolts"] = df["RefVolts"] - alphaRef*df['SetVolts']
+df["DutVolts"] = df["DutVolts"] - alphaDut*df['SetVolts']
+#df["OptVolts"] = df["OptVolts"] - alphaOpt*df['SetVolts']
+df["DutToRefVolts"] = df['DutVolts'] - df["RefVolts"]
+#  plot INL of calibrator
+fig.add_trace(go.Scatter(x=df['SetVolts'], y=df["RefVolts"],mode='lines+markers',name='Post REF INL'),row=3, col=1)
+fig.add_trace(go.Scatter(x=df['SetVolts'], y=df["DutVolts"],mode='lines+markers',name='Post DUT INL'),row=3, col=1)
+#fig.add_trace(go.Scatter(x=df['SetVolts'], y=df["OptVolts"],mode='lines+markers',name='Original OPT INL'),row=1, col=1)
+fig.add_trace(go.Scatter(x=df['SetVolts'], y=df["DutToRefVolts"],mode='lines+markers',name='Post DUT vs REF'),row=2, col=1)
+## Make plot and save
+fig.write_html('inl_evaluation_plots.html')
+fig.write_image('inl_evaluation_plots.png',width=720, height=1280)