How to do it...

1. Create a script called log_adc.py:

#!/usr/bin/python3 
#log_adc.c 
import time 
import datetime 
import data_adc as dataDevice 
 
DEBUG=True 
FILE=True 
VAL0=0;VAL1=1;VAL2=2;VAL3=3 #Set data order 
FORMATHEADER = "t%st%st%st%st%s" 
FORMATBODY = "%dt%st%ft%ft%ft%f" 
 
if(FILE):f = open("data.log",'w') 
 
def timestamp(): 
  ts = time.time()  
  return datetime.datetime.fromtimestamp(ts).strftime( 
                                    '%Y-%m-%d %H:%M:%S') 
 
def main(): 
    counter=0 
    myData = dataDevice.device() 
    myDataNames = myData.getName() 
    header = (FORMATHEADER%("Time", 
                        myDataNames[VAL0],myDataNames[VAL1], 
                        myDataNames[VAL2],myDataNames[VAL3])) 
    if(DEBUG):print (header) 
    if(FILE):f.write(header+"n") 
    while(1): 
      data = myData.getNew() 
      counter+=1 
      body = (FORMATBODY%(counter,timestamp(), 
                        data[0],data[1],data[2],data[3])) 
      if(DEBUG):print (body) 
      if(FILE):f.write(body+"n") 
      time.sleep(0.1) 
 
try: 
  main() 
finally: 
  f.close() 
#End 

2. Create a second script called log_graph.py, as follows:

#!/usr/bin/python3 
#log_graph.py 
import numpy as np 
import matplotlib.pyplot as plt 
 
filename = "data.log" 
OFFSET=2 
with open(filename) as f: 
    header = f.readline().split('t') 
     
data = np.genfromtxt(filename, delimiter='t', skip_header=1, 
                    names=['sample', 'date', 'DATA0', 
                           'DATA1', 'DATA2', 'DATA3']) 
fig = plt.figure(1) 
ax1 = fig.add_subplot(211)#numrows, numcols, fignum 
ax2 = fig.add_subplot(212) 
ax1.plot(data['sample'],data['DATA0'],'r', 
         label=header[OFFSET+0]) 
ax2.plot(data['sample'],data['DATA1'],'b', 
         label=header[OFFSET+1]) 
ax1.set_title("ADC Samples")     
ax1.set_xlabel('Samples') 
ax1.set_ylabel('Reading') 
ax2.set_xlabel('Samples') 
ax2.set_ylabel('Reading') 
 
leg1 = ax1.legend() 
leg2 = ax2.legend() 
 
plt.show() 
#End