Update U180-ToolKit.py

U180-ToolKit.py

@@ -3,30 +3,39 @@ import os
 import json
 import time
 import csv
+import matplotlib.dates as mdates
 import pandas as pd
 from plotly.subplots import make_subplots
 import plotly.graph_objects as go
 import datetime
 import numpy
 import GPIBPrologix
+import git
+import shutil
+import bme280
+import smbus2
 
 GPIB = GPIBPrologix.ResourceManager("/dev/ttyACM0")
 instObj = GPIB.open_resource(22)
-instObj.write("BEEP")
+bus = smbus2.SMBus(1)
-instObj.write("CAL? 72")
+calibration_params = bme280.load_calibration_params(bus, 0x76)
-print(instObj.read())
+
-print(instObj.query("CAL? 72"))
-time.sleep(60)
 ## user customisable functions
 def readFunc(instObj):
     return instObj.read()
 
 def writeFunc(instObj, input):
     instObj.write(input)
-
+    time.sleep(1)
 def queryFunc(instObj, input):
-    time.sleep(0.1)
+    output = instObj.query(input)
-    return instObj.query(input)
+    time.sleep(1)
+    print(input, output)
+    return output
+
+def getEnvironment(instObj, i2cbus):
+    value = instObj.sample(i2cbus, 0x76, calibration_params)
+    return [str(round(value.humidity,2)),str(round(value.temperature,2)),str(round(value.pressure,2))]
 
 ## the main program functionalities, should not be adjusted
 def readRunningConfigs():
@@ -36,17 +45,24 @@ def readRunningConfigs():
     return filenames
 
 def doACAL(dcACAL, ohmACAL, acACAL):
-    output = queryFunc(instObj, "TEMP?")
+    writeFunc(instObj,"END 2")
+    writeFunc(instObj,"OFORMAT ASCII")
+    writeFunc(instObj,"BEEP")
     if dcACAL == "yes":
+        print("Starting DCV cal")
         writeFunc(instObj, "ACAL DCV")
-        time.sleep(140+20)
+        time.sleep(140+60)
     if acACAL == "yes":
-        writeFunc(instObj, "ACAL ACV")
+        print("Starting AC cal")
-        time.sleep(140+20)
+        writeFunc(instObj, "ACAL AC")
+        time.sleep(240+60)
     if ohmACAL == "yes":
+        print("Starting Ohm cal")
         writeFunc(instObj, "ACAL OHMS")
-        time.sleep(600+60)
+        time.sleep(720+60)
-    return output
+    writeFunc(instObj, "DISP OFF,  ;")
+    writeFunc(instObj,"DISP MSG,\"             \"")
+    return 0
 
 def interrogate3458A(instObj):
     output = []
@@ -66,6 +82,7 @@ def interrogate3458A(instObj):
     output.append(queryFunc(instObj,"CAL? 59"))  # get temperature from during calibration
     output.append(queryFunc(instObj,"CAL? 97"))  # get 1mamp ACAL gain constrant
     output.append(queryFunc(instObj,"CAL? 72"))  # get 10v ACAL gain constrant
+    print(output)
     return output
 
 ## main program
@@ -78,13 +95,19 @@ for file in readRunningConfigs():
         if not os.path.exists(serialPath): 
             os.makedirs(serialPath)
             with open(serialPath+configData['serial']+'.csv', 'a') as g:
+                heading = ["DateTime","TEMP","CAL RREF","CAL VREF","G10K","G100K", "G1V0","G0V1","OCOMP1K","OCOMP10K", "ACALTEMP", "CALTEMP", "G1mA", "G10V"]
+                if(configData['useBME']):
+                    heading = output.append(['EnvHumidity', 'EnvTemp', 'EnvPressure'])
                 writer = csv.writer(g)
-                writer.writerow(["DateTime","TEMP","CAL RREF","CAL VREF","G10K","G100K", "G1V0","G0V1","OCOMP1K","OCOMP10K", "ACALTEMP", "CALTEMP", "G1mA", "G10V"])
+                writer.writerow(heading)
         doACAL(configData['ACAL-DCV'],configData['ACAL-OHMS'],configData['ACAL-ACV'])
         with open(serialPath+configData['serial']+'.csv', 'a') as f:
+            output = interrogate3458A(instObj)
+            if(configData['useBME']):
+                data = getEnvironment(bme280, bus)
+                output += data
             writer = csv.writer(f)
-            writer.writerow((interrogate3458A(instObj)))
+            writer.writerow(output)
-        writeFunc(instObj,"DISP OFF,''")
 
 ## do the plotting
 for file in readRunningConfigs():
@@ -92,14 +115,54 @@ for file in readRunningConfigs():
     with open(dataPath, "r") as read_file:
         configData = json.load(read_file)
         serialPath = os.path.realpath(os.path.dirname(__file__))+'/data/'+configData['serial']+'/'
-        df = pd.read_csv(serialPath+configData['serial']+'.csv')
+        df = pd.read_csv(serialPath+configData['serial']+'.csv',delimiter=',', encoding="utf-8-sig")
+        df.columns = df.columns.str.strip()
 
         time_x = pd.to_datetime(df['DateTime'],format='%d-%m-%y %H:%M:%S')
         coefficients = numpy.polyfit(df['TEMP'], df['G10V'], 1, rcond=None, full=False, w=None, cov=False)
         polynomial = numpy.poly1d(coefficients)
+        #polynom_estimate = numpy.polyfit(mdates.date2num(time_x),df['G10V']-polynomial(df['TEMP']), 1, rcond=None, full=False, w=None, cov=False)
+        polynom_estimate = numpy.polyfit(mdates.date2num(time_x),df['G10V'], 1, rcond=None, full=False, w=None, cov=False)
+        p_est = numpy.poly1d(polynom_estimate)
 
         fig = make_subplots(rows=1, cols=2)
-        fig.add_trace(go.Scatter(x=time_x, y=df['G10V']-polynomial(df['TEMP']),mode='lines+markers',name='time vs cal72 w tempcomp'),row=1, col=1)
+        #fig.add_trace(go.Scatter(x=time_x, y=df['G10V']-polynomial(df['TEMP']),mode='lines+markers',name='time vs cal72 w tempcomp'),row=1, col=1)
+        fig.add_trace(go.Scatter(x=time_x, y=df['G10V'],mode='lines+markers',name='time vs cal72 w tempcomp'),row=1, col=1)
+        fig.add_trace(go.Scatter(x=time_x, y=p_est(mdates.date2num(time_x)),mode='lines',line = dict(color='gray', dash='dash'),name='Estimated 1st order'), row=1, col=1)
         fig.add_trace(go.Scatter(x=df['TEMP'], y=df['G10V'],mode='lines+markers',name='temp vs cal72'),row=1, col=2)
+        fig.add_trace(go.Scatter(x=df['TEMP'], y=polynomial(df['TEMP']),mode='lines',line = dict(color='gray', dash='dash'),name='Tempco 1st order'), row=1, col=2)
+
+        datenow = datetime.datetime.now()
+        date = datenow + datetime.timedelta(days=1)
+        timeframe = (time_x.max()-time_x.min()).total_seconds()/(3600*24)
+        alphaday = (p_est(mdates.date2num(date))-p_est(mdates.date2num(datenow)))
+        driftrate = round((alphaday*1000000000)/(df.loc[:, 'G10V'].mean()*timeframe),2)
+        annotation = f'Estimated drift:  {driftrate} ppb/day'
+        fig.add_annotation(dict(showarrow=False, text=annotation, xanchor='left', xref="paper", yref="paper", x=0, y=0))
+        tempcorate = round(((polynomial(1)-polynomial(0))*1000000000)/df.loc[:, 'G10V'].mean(),2)
+        annotation = f'Estimated tempco:  {tempcorate} ppb/degC'
+        fig.add_annotation(dict(showarrow=False, text=annotation, xanchor='left', xref="paper", yref="paper", x=1, y=0))
+
+
         fig.write_html(serialPath+configData['serial']+'.html')
-        fig.write_image(serialPath+configData['serial']+'.png')
+        fig.write_image(serialPath+configData['serial']+'.png',width=1280, height=720)
+
+## do the saving
+for file in readRunningConfigs():
+    localDataPath = os.path.realpath(os.path.dirname(__file__))+'/data/'
+    gitDataRepo = os.path.realpath(os.path.dirname(__file__))+'/CommitDataRepo/'
+    with open(dataPath, "r") as read_file:
+        configData = json.load(read_file)
+        if(configData['useGit']):
+            remote = f"https://{configData['gitUser']}:{configData['gitPassword']}@{configData['gitAddress']}"
+            if os.path.exists(gitDataRepo):
+                shutil.rmtree(gitDataRepo, ignore_errors=True)
+            git.Repo.clone_from(remote, gitDataRepo, b=configData['gitBranch'])
+            shutil.copytree(localDataPath, gitDataRepo+'data/',dirs_exist_ok=True)
+            repo = git.Repo(gitDataRepo)
+            repo.git.add(gitDataRepo)
+            repo.index.commit("Update")
+            repo.remotes[0].push()
+
+## if all ok, blamk screen to save VFD
+queryFunc(instObj, 'DISP OFF,""')