old_contents: # This code is supporting material for the book
  # Building Machine Learning Systems with Python
  # by Willi Richert and Luis Pedro Coelho
  # published by PACKT Publishing
  #
  # It is made available under the MIT License
  
  # This script generates web traffic data for our hypothetical
  # web startup "MLASS" in chapter 01
  
  import os
  import scipy as sp
  from scipy.stats import gamma
  import matplotlib.pyplot as plt
  
  from utils import DATA_DIR, CHART_DIR
  
  sp.random.seed(3)  # to reproduce the data later on
  
  x = sp.arange(1, 31 * 24)
  y = sp.array(200 * (sp.sin(2 * sp.pi * x / (7 * 24))), dtype=int)
  y += gamma.rvs(15, loc=0, scale=100, size=len(x))
  y += 2 * sp.exp(x / 100.0)
  y = sp.ma.array(y, mask=[y < 0])
  print(sum(y), sum(y < 0))
  
  plt.scatter(x, y)
  plt.title("Web traffic over the last month")
  plt.xlabel("Time")
  plt.ylabel("Hits/hour")
  plt.xticks([w * 7 * 24 for w in [0, 1, 2, 3, 4]], ['week %i' % (w + 1) for w in
                                                     [0, 1, 2, 3, 4]])
  
  plt.autoscale(tight=True)
  plt.grid()
  plt.savefig(os.path.join(CHART_DIR, "1400_01_01.png"))
  
  # sp.savetxt(os.path.join("..", "web_traffic.tsv"),
  # zip(x[~y.mask],y[~y.mask]), delimiter="\t", fmt="%i")
  
  sp.savetxt(os.path.join(
      DATA_DIR, "web_traffic.tsv"), list(zip(x, y)), delimiter="\t", fmt="%s")
  
new_contents: # This code is supporting material for the book
  # Building Machine Learning Systems with Python
  # by Willi Richert and Luis Pedro Coelho
  # published by PACKT Publishing
  #
  # It is made available under the MIT License
  
  # This script generates web traffic data for our hypothetical
  # web startup "MLASS" in chapter 01
  
  import os
  import scipy as sp
  from scipy.stats import gamma
  import matplotlib.pyplot as plt
  
  from utils import DATA_DIR, CHART_DIR
  
  sp.random.seed(3)  # to reproduce the data later on
  
  x = sp.arange(1, 31*24)
  y = sp.array(200*(sp.sin(2*sp.pi*x/(7*24))), dtype=int)
  y += gamma.rvs(15, loc=0, scale=100, size=len(x))
  y += 2 * sp.exp(x/100.0)
  y = sp.ma.array(y, mask=[y<0])
  print(sum(y), sum(y<0))
  
  plt.scatter(x, y)
  plt.title("Web traffic over the last month")
  plt.xlabel("Time")
  plt.ylabel("Hits/hour")
  plt.xticks([w*7*24 for w in range(5)], 
             ['week %i' %(w+1) for w in range(5)])
  plt.autoscale(tight=True)
  plt.grid()
  plt.savefig(os.path.join(CHART_DIR, "1400_01_01.png"))
  
  sp.savetxt(os.path.join(DATA_DIR, "web_traffic.tsv"), 
             list(zip(x, y)), delimiter="\t", fmt="%s")
  
subject: format this file