parameters: (how_many, min_temperature, max_temperature)
return_statement: return temperatures
docstring: Used to generate temperature schedules for the simulated annealing
      algorithm. how_many specifies the amount of temperatures to be generated.
      min_temperature and max_temperature defines the boundaries for the
      values of the generated temperatures. The list of generated temperatures
      is sorted in ascending order before it is returned.
docstring_summary: Used to generate temperature schedules for the simulated annealing
      algorithm. how_many specifies the amount of temperatures to be generated.
      min_temperature and max_temperature defines the boundaries for the
      values of the generated temperatures. The list of generated temperatures
      is sorted in ascending order before it is returned.
docstring_tokens: Used to generate temperature schedules for the simulated annealing algorithm . how_many specifies the amount of temperatures to be generated . min_temperature and max_temperature defines the boundaries for the values of the generated temperatures . The list of generated temperatures is sorted in ascending order before it is returned .
function: def random_temperature_schedule(how_many, min_temperature, max_temperature):
      '''Used to generate temperature schedules for the simulated annealing
      algorithm. how_many specifies the amount of temperatures to be generated.
      min_temperature and max_temperature defines the boundaries for the
      values of the generated temperatures. The list of generated temperatures
      is sorted in ascending order before it is returned.
      '''
      temperatures = []
      for i in xrange(how_many):
          temperatures.append(min_temperature + random.random() * max_temperature)
      temperatures.sort()
  
      return temperatures
function_tokens: def random_temperature_schedule ( how_many , min_temperature , max_temperature ) : temperatures = [ ] for i in xrange ( how_many ) : temperatures . append ( min_temperature + random . random ( ) * max_temperature ) temperatures . sort ( ) return temperatures