old_contents: import json
  import matplotlib
  import numpy as np
  import pymc as pm
  from matplotlib import pyplot as plt
  
  
  def main():
      matplotlibrc_path = '/home/noel/repo/playground/matplotlibrc.json'
      matplotlib.rcParams.update(json.load(open(matplotlibrc_path)))
  
      tau = pm.rdiscrete_uniform(0, 80)
      print tau
  
      alpha = 1. / 20.
      lambda_1, lambda_2 = pm.rexponential(alpha, 2)
      print lambda_1, lambda_2
  
      data = np.r_[pm.rpoisson(lambda_1, tau), pm.rpoisson(lambda_2, 80 - tau)]
  
      def plot_artificial_sms_dataset():
          tau = pm.rdiscrete_uniform(0, 80)
          alpha = 1. / 20.
          lambda_1, lambda_2 = pm.rexponential(alpha, 2)
          data = np.r_[pm.rpoisson(lambda_1, tau), pm.rpoisson(lambda_2, 80 - tau)]
          plt.bar(np.arange(80), data, color="#348ABD")
          plt.bar(tau - 1, data[tau - 1], color="r", label="user behaviour changed")
          plt.xlim(0, 80)
  
      plt.title("More example of artificial datasets")
      for i in range(1, 5):
          plt.subplot(4, 1, i)
          plot_artificial_sms_dataset()
      plt.show()
  
  
  if __name__ == '__main__':
      main()
  
new_contents: import json
  import matplotlib
  import numpy as np
  import pymc as pm
  from matplotlib import pyplot as plt
  
  
  def main():
      tau = pm.rdiscrete_uniform(0, 80)
      print tau
  
      alpha = 1. / 20.
      lambda_1, lambda_2 = pm.rexponential(alpha, 2)
      print lambda_1, lambda_2
  
      data = np.r_[pm.rpoisson(lambda_1, tau), pm.rpoisson(lambda_2, 80 - tau)]
  
      def plot_artificial_sms_dataset():
          tau = pm.rdiscrete_uniform(0, 80)
          alpha = 1. / 20.
          lambda_1, lambda_2 = pm.rexponential(alpha, 2)
          data = np.r_[pm.rpoisson(lambda_1, tau), pm.rpoisson(lambda_2, 80 - tau)]
          plt.bar(np.arange(80), data, color="#348ABD")
          plt.bar(tau - 1, data[tau - 1], color="r", label="user behaviour changed")
          plt.xlim(0, 80)
  
      plt.title("More example of artificial datasets")
      for i in range(1, 5):
          plt.subplot(4, 1, i)
          plot_artificial_sms_dataset()
      plt.show()
  
  
  if __name__ == '__main__':
      main()
  
subject: Change of repo name. Update effected paths