#import gpibprologix
import os
import json
import time
import csv
import pandas as pd
from plotly.subplots import make_subplots
import plotly.graph_objects as go
import datetime
import numpy
import GPIBPrologix

GPIB = GPIBPrologix.ResourceManager("/dev/ttyACM0")
instObj = GPIB.open_resource(22)
instObj.write("BEEP")
instObj.write("CAL? 72")
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)

def queryFunc(instObj, input):
    time.sleep(0.1)
    return instObj.query(input)

## the main program functionalities, should not be adjusted
def readRunningConfigs():
    searchPath = os.path.realpath(os.path.dirname(__file__))+'/RunningConfigs/'
    filenames = next(os.walk(searchPath), (None, None, []))[2]
    filenames = [item for item in filenames if str.endswith(item,'.json')]
    return filenames

def doACAL(dcACAL, ohmACAL, acACAL):
    output = queryFunc(instObj, "TEMP?")
    if dcACAL == "yes":
        writeFunc(instObj, "ACAL DCV")
        time.sleep(140+20)
    if acACAL == "yes":
        writeFunc(instObj, "ACAL ACV")
        time.sleep(140+20)
    if ohmACAL == "yes":
        writeFunc(instObj, "ACAL OHMS")
        time.sleep(600+60)
    return output

def interrogate3458A(instObj):
    output = []
    d = datetime.datetime.now()
    dx = d - datetime.timedelta(microseconds=d.microsecond)
    output.append(dx.strftime("%d-%m-%y %H:%M:%S"))
    output.append(queryFunc(instObj,"TEMP?"))    # get temperature in device
    output.append(queryFunc(instObj,"CAL? 1,1")) # get RREF cal value
    output.append(queryFunc(instObj,"CAL? 2,1")) # get VREF cal value
    output.append(queryFunc(instObj,"CAL? 78"))  # get 10kohm ACAL gain constrant
    output.append(queryFunc(instObj,"CAL? 79"))  # get 100kohm ACAL gain constrant
    output.append(queryFunc(instObj,"CAL? 71"))  # get 1v0 ACAL gain constrant
    output.append(queryFunc(instObj,"CAL? 70"))  # get 0v1 ACAL gain constrant
    output.append(queryFunc(instObj,"CAL? 86"))  # get 1kohm ACAL ocomp constrant
    output.append(queryFunc(instObj,"CAL? 87"))  # get 10kohm ACAL ocomp constrant
    output.append(queryFunc(instObj,"CAL? 176")) # get acal temperature for ohms
    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
    return output

## main program
#  read the config file and do the folder setup
for file in readRunningConfigs():
    dataPath = os.path.realpath(os.path.dirname(__file__))+'/RunningConfigs/'+file
    with open(dataPath, "r") as read_file:
        configData = json.load(read_file)
        serialPath = os.path.realpath(os.path.dirname(__file__))+'/data/'+configData['serial']+'/'
        if not os.path.exists(serialPath): 
            os.makedirs(serialPath)
            with open(serialPath+configData['serial']+'.csv', 'a') as g:
                writer = csv.writer(g)
                writer.writerow(["DateTime","TEMP","CAL RREF","CAL VREF","G10K","G100K", "G1V0","G0V1","OCOMP1K","OCOMP10K", "ACALTEMP", "CALTEMP", "G1mA", "G10V"])
        doACAL(configData['ACAL-DCV'],configData['ACAL-OHMS'],configData['ACAL-ACV'])
        with open(serialPath+configData['serial']+'.csv', 'a') as f:
            writer = csv.writer(f)
            writer.writerow((interrogate3458A(instObj)))
        writeFunc(instObj,"DISP OFF,''")

## do the plotting
for file in readRunningConfigs():
    dataPath = os.path.realpath(os.path.dirname(__file__))+'/RunningConfigs/'+file
    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')

        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)

        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=df['TEMP'], y=df['G10V'],mode='lines+markers',name='temp vs cal72'),row=1, col=2)
        fig.write_html(serialPath+configData['serial']+'.html')
        fig.write_image(serialPath+configData['serial']+'.png')