old_contents: import json
  import numpy as np
  from EffectiveTTVProduction.EffectiveTTVProduction.operators import operators
  
  result = {}
  for o in operators:
      result[o] = list(np.hstack([np.array([0.0]), np.random.uniform(-1.0, 1.0, 999).round(3)]))
  
  with open('random_points.json', 'w') as f:
      json.dump(result, f)
  
  result = {}
  for o in operators:
      # be sure to include the NP=0 point
      lows = np.linspace(-1.0, 0.0, num=30, endpoint=False).round(3)
      highs = np.linspace(0.0, 1.0, num=30).round(3)
      result[o] = list(np.hstack([lows, highs]))
  
  with open('linspace_points.json', 'w') as f:
      json.dump(result, f)
  
new_contents: import json
  import numpy as np
  from EffectiveTTVProduction.EffectiveTTVProduction.operators import operators
  
  result = {}
  for o in operators:
      result[o] = list(np.hstack([np.array([0.0]), np.random.uniform(-1.0, 1.0, 999).round(3)]))
  
  with open('random_points.json', 'w') as f:
      json.dump(result, f)
  
  result = {}
  for o in operators:
      # be sure to include the NP=0 point
      lows = np.linspace(-1.0, 0.0, num=15, endpoint=False).round(3)
      highs = np.linspace(0.0, 1.0, num=15).round(3)
      result[o] = list(np.hstack([lows, highs]))
  
  with open('linspace_points.json', 'w') as f:
      json.dump(result, f)
  
subject: Use a courser scan