Working ADC | Python Fiddle

import Queue
import os
import sys
import datetime as DT
import collections
import matplotlib.pyplot as plt
from matplotlib import gridspec
import numpy as np
import multiprocessing as mp
import time
import datetime
import matplotlib.dates as mdates
import matplotlib.animation as animation
from ABE_DeltaSigmaPi import DeltaSigma 
from ABE_helpers import ABEHelpers

i2c_helper = ABEHelpers() 
bus = i2c_helper.get_smbus() 
adc = DeltaSigma(bus, 0x68, 0x69, 16)

#Rename file to date
base_dir = '/home/pi/Desktop/DATA'
ts = time.time()
filename_time = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d')
filename_base = os.path.join(base_dir, filename_time)
filename = '%s.txt' % filename_base

# you will want to change read_delay to 5000
read_delay = int(5000)    # in milliseconds 
write_delay = read_delay/1000.0  # in seconds 
window_size = 60
nlines = 8
ypadding = 0.5
datenums = collections.deque(maxlen=window_size)
ys = [collections.deque(maxlen=window_size) for i in range(nlines)]

def animate(i, queue):
    try:
        row = queue.get_nowait()
    except Queue.Empty:
        return
    datenums.append(mdates.date2num(row[0]))
    for i, y in enumerate(row[1:]):
        ys[i].append(y)
    for i, y in enumerate(ys):
        lines[i].set_data(datenums, y)
    ymin1 = min(min(y) for y in ys)
    ymin = ymin1 - ypadding
    ymax1 = max(max(y) for y in ys)
    ymax = ymax1 + ypadding
    xmin = min(datenums)
    xmax = max(datenums)
    if xmin < xmax:
        ax1.set_xlim(xmin, xmax)
    ax1.set_ylim(ymin, ymax)
    
    ax2.plot(0, 0)
    ax2.set_xlim(0, 1)
    ax2.set_ylim(0, 1)
    channel1 = row[-8]
    channel2 = row[-7]
    channel3 = row[-6]
    channel4 = row[-5]
    channel5 = row[-4]
    channel6 = row[-3]
    channel7 = row[-2]
    channel8 = row[-1]

ax2.text(0.1,0.8,'CH1: %.02f \n CH2: %.02f \n CH3: %.02f \n CH4: %.02f \n CH5: %.02f \n CH6: %.02f \n CH7: %.02f \n CH8: %.02f \n' % (channel1,channel2,channel3,channel4,channel5,channel6,channel7,channel8) , ha='left', va='top', backgroundcolor='w')
    fig.canvas.draw()

def write_data(filename, queue):
    while True:
        delay1 = DT.datetime.now()
        row = []
        for i in range(nlines):
            # read from adc channels and print to screen
            channel = adc.read_voltage(i)
            row.append(channel)

queue.put([delay1]+row)

#print voltage variables to local file
        with open(filename, 'a') as DAQrecording:
            time1 = delay1.strftime('%Y-%m-%d')
            time2 = delay1.strftime('%H:%M:%S')
            row = [time1, time2] + row
            row = map(str, row)
            DAQrecording.write('{}\n'.format(', '.join(row)))

#Delay until next 5 second interval
        delay2 = DT.datetime.now()
        difference = (delay2 - delay1).total_seconds()
        time.sleep(write_delay - difference)

def main():
    global fig, ax1, ax2, lines
    queue = mp.Queue()
    proc = mp.Process(target=write_data, args=(filename, queue))
    # terminate proc when main process ends
    proc.daemon = True
    # spawn the writer in a separate process
    proc.start()

fig, (ax1, ax2) = plt.subplots(1, 2, sharey=False) 
    gs = gridspec.GridSpec(1,2, width_ratios=[3, 1] wspace=None)
    ax1 = plt.subplot(gs[0])
    ax2 = plt.subplot(gs[1])
    ax2.axes.xaxis.set_ticklabels([])
    ax2.axes.yaxis.set_ticklabels([])
    xfmt = mdates.DateFormatter('%H:%M:%S')
    ax1.xaxis.set_major_formatter(xfmt)

# make matplotlib treat x-axis as times
    ax1.xaxis_date()
    fig.autofmt_xdate()
    fig.suptitle('Data Acquisition', fontsize=14, fontweight='bold')

lines = []
    for i in range(nlines):
        line, = ax1.plot([], [])
        lines.append(line)

ani = animation.FuncAnimation(fig, animate, interval=read_delay, fargs=(queue,))
    plt.show()

if __name__ == '__main__':
    main()

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