old_contents: """
  *******************************************************
  *
  *  plot_cdf - PLOT MODEL FIT TO DATA
  *  
  *  Version:      Version 2.0
  *  License:      Apache 2.0
  *  Written by:   Michael Slugocki
  *  Created on:   April 18, 2017
  *  Last updated: April 18, 2018
  *
  *******************************************************
  """
  
  #################################################################
  #  IMPORT MODULES
  #################################################################
  import numpy as np
  import matplotlib.pyplot as plt
  from . import psyfunction as _psyfunction
  
  
  #################################################################
  #  GENERATE CDF PLOT OF MODEL FIT TO DATA
  #################################################################
  
  def plot_cdf(data, metrics, options):
      
      fig, ax = plt.subplots(nrows = 1, ncols = 1, figsize = (5, 5))
      
      # Generate smooth curve from fitted function
      x_max = data[:, 0].max()
      x_min = data[:, 0].min()
      x_est = np.linspace(x_min,x_max,1000)
      
      y_pred = _psyfunction(x_est, 
                        metrics['Fit'][0], 
                        metrics['Fit'][1], 
                        metrics['Fit'][2], 
                        metrics['Fit'][3], 
                        options['sigmoid_type'])
      if options['logspace'] is True:
          ax.set_xscale('log')
      ax.plot([x_min, metrics['threshold']],
          [options['threshold'], options['threshold']],
           color = 'black', 
           linestyle = 'dotted', 
           linewidth = 2, 
           zorder = 1)
      ax.plot([metrics['threshold'], metrics['threshold']], 
          [0, options['threshold']],
          color = 'black', 
          linestyle = 'dotted', 
          linewidth = 2, 
          zorder = 1)
      ax.set_ylim(-0.05,1.05)
      ax.axhline(y=metrics['Fit'][2], color = 'r', linestyle = 'dashed', linewidth = 2, zorder = 1)
      # Plot remainder of curve
      ax.scatter(data[:,0], data[:,1], color = '#5998ff', s = 125, alpha = 1.0, zorder = 5)
      ax.plot(x_est, y_pred, linestyle = '-', color = 'black', linewidth = 2, alpha = 0.85, zorder = 10)  
      ax.set_xlabel('Stimulus Intensity', fontsize = 16, fontweight = 'bold')
      ax.set_ylabel('Proportion correct', fontsize = 16, fontweight = 'bold')
      ax.xaxis.set_tick_params(labelsize=13)
      ax.yaxis.set_tick_params(labelsize=13)
      plt.tight_layout()
      plt.show()
new_contents: """
  *******************************************************
  *
  *  plot_cdf - PLOT MODEL FIT TO DATA
  *  
  *  Version:      Version 2.0
  *  License:      Apache 2.0
  *  Written by:   Michael Slugocki
  *  Created on:   April 18, 2017
  *  Last updated: April 18, 2018
  *
  *******************************************************
  """
  
  #################################################################
  #  IMPORT MODULES
  #################################################################
  import numpy as np
  import matplotlib.pyplot as plt
  from . import psyFunction as _psyfunction
  
  
  #################################################################
  #  GENERATE CDF PLOT OF MODEL FIT TO DATA
  #################################################################
  
  def plot_cdf(data, metrics, options):
      
      fig, ax = plt.subplots(nrows = 1, ncols = 1, figsize = (5, 5))
      
      # Generate smooth curve from fitted function
      x_max = data[:, 0].max()
      x_min = data[:, 0].min()
      x_est = np.linspace(x_min,x_max,1000)
      
      y_pred = _psyfunction(x_est, 
                        metrics['Fit'][0], 
                        metrics['Fit'][1], 
                        metrics['Fit'][2], 
                        metrics['Fit'][3], 
                        options['sigmoid_type'])
      if options['logspace'] is True:
          ax.set_xscale('log')
      ax.plot([x_min, metrics['threshold']],
          [options['threshold'], options['threshold']],
           color = 'black', 
           linestyle = 'dotted', 
           linewidth = 2, 
           zorder = 1)
      ax.plot([metrics['threshold'], metrics['threshold']], 
          [0, options['threshold']],
          color = 'black', 
          linestyle = 'dotted', 
          linewidth = 2, 
          zorder = 1)
      ax.set_ylim(-0.05,1.05)
      ax.axhline(y=metrics['Fit'][2], color = 'r', linestyle = 'dashed', linewidth = 2, zorder = 1)
      # Plot remainder of curve
      ax.scatter(data[:,0], data[:,1], color = '#5998ff', s = 125, alpha = 1.0, zorder = 5)
      ax.plot(x_est, y_pred, linestyle = '-', color = 'black', linewidth = 2, alpha = 0.85, zorder = 10)  
      ax.set_xlabel('Stimulus Intensity', fontsize = 16, fontweight = 'bold')
      ax.set_ylabel('Proportion correct', fontsize = 16, fontweight = 'bold')
      ax.xaxis.set_tick_params(labelsize=13)
      ax.yaxis.set_tick_params(labelsize=13)
      plt.tight_layout()
      plt.show()
subject: Change psyFunction name