Delay between processes

rdelay.py

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import pylab
import datetime as dt

##
# Response time analysis
df_tbi = pd.DataFrame(np.arange(1,8))
df_tbi['response_cal_time'] = np.array([850,4345,19000,5827,3904,2756,8550])
df_tbi['response_time'] = np.array([850,4345,13240,2947,1024,2756,5670])
df_tbi['response_time_off'] = np.array([240,1650,5140,1147,360,1096,1950])
#
df_ttns = pd.DataFrame(np.arange(1,6))
df_ttns['response_cal_time'] = np.array([14214,2765,216,5690,2906])
df_ttns['response_time'] = np.array([11334,2765, 216,1370,2906])
df_ttns['response_time_off'] = np.array([3894,894, 216, 530,986])

# Response time analysis with current reading
def gshow(df,start_time):
  pylab.boxplot([df['response_cal_time'],df['response_time'],df['response_time_off']])
  # Handle weekends (only up to one weekend)
  if dt.datetime.now().weekday() < dt.datetime.strptime(start_time, "%Y-%m-%d %H:%M").weekday():
    # passed whole week
    minutes = (dt.datetime.now() - (dt.datetime.strptime(start_time, "%Y-%m-%d %H:%M")-dt.timedelta(hours=48))).total_seconds() / 60
    off = (dt.datetime.now() - (dt.datetime.strptime(start_time, "%Y-%m-%d %H:%M")-dt.timedelta(hours=48))).days*(24-8)*60
  elif dt.datetime.now().weekday() >= 5:
    # Mid-weekend
    minutes = (dt.datetime.now() - (dt.datetime.strptime(start_time, "%Y-%m-%d %H:%M")-dt.timedelta(hours=(dt.datetime.now().weekday()-4)*24))).total_seconds() / 60
    off = (dt.datetime.now() - (dt.datetime.strptime(start_time, "%Y-%m-%d %H:%M")-dt.timedelta(hours=(dt.datetime.now().weekday()-4)))).days*(24-8)*60
  else:
    # No weekend
    minutes = (dt.datetime.now() - dt.datetime.strptime(start_time, "%Y-%m-%d %H:%M")).total_seconds() / 60
    off = (dt.datetime.now() - dt.datetime.strptime(start_time, "%Y-%m-%d %H:%M")).days*(24-8)*60
  
  cal_minutes = (dt.datetime.now() - dt.datetime.strptime(start_time, "%Y-%m-%d %H:%M")).total_seconds() / 60
  pylab.scatter([1], cal_minutes)
  pylab.scatter([2], minutes)
  pylab.scatter([3], minutes-off)
  pylab.xticks([1,2,3],['Calendar days','Work days','Work time'])
  plt.show()

gshow(df_tbi,"2014-03-14 18:00")
gshow(df_ttns,"2014-03-24 13:50")