new_contents: #!/usr/bin/python
  import pandas as pd
  import numpy as np
  import matplotlib
  import datetime as dt
  
  from matplotlib import pyplot as plt
  
  # Import modules from /batterym/ folder.
  import os
  import sys
  sys.path.append(os.path.abspath('../batterym'))
  import log
  import smooth
  import history
  
  
  plt.style.use('ggplot')
  
  # logs = log.get_battery('../logs/capacity_example')
  # h = history.History(logs, smoothing=True)
  # hdata = h.data()
  
  # data = pd.DataFrame(hdata)
  # data = data.rename(columns={'time': 'timestamp'})
  # data = data.sort_values(by='timestamp', ascending=True)
  
  # # Extract charging sessions
  # data = data[data['status'] == 'Charging']
  
  # # Group by sequence_id
  # # and leave the longest sessions 
  # grouped = data.groupby('sequence_id')['capacity_raw'].size()
  # grouped = grouped.sort_values(inplace=False, ascending=False)
  # grouped = grouped[:3]
  # data = data[data.sequence_id.isin(grouped.index)]
  
  #print data
  
  x = np.linspace(0, 10, 500)
  y = 10 * np.sin(x)
  y2 = np.round(y)
  
  fig, ax = plt.subplots()
  
  ax.set_ylim(-11, 11)
  ax.plot(x, y, color='b', marker='+')
  ax.plot(x, y2, color='r', marker='o')
  
  # Full screen plot window.
  mng = plt.get_current_fig_manager()
  mng.resize(*mng.window.maxsize())
  
  # Show plot.
  plt.show()
  
subject: add explore smoothing