old_contents: __author__ = 'Jacob Bieker'
  import os, sys, random
  import numpy
  from multiprocessing import Pool
  from astropy.io import fits
  
  
  def random_number(number, seed):
      if seed > 0:
          seed = -seed
      random.seed(a=seed)
      for i in range(number):
          rand_num = random.randint(0,1)
  
  
  def line_solve():
      # TODO: Find the Least Squares for a line
      return 0
  
  
  def plane_solve():
      # TODO: Find the least Squares for a plane
      return 0
  
  
  def read_clusters(*args):
      # TODO: Read in the files containing the cluster points
      return 0
  
  
  def determine_type():
      # TODO: Determine the type (i.e. Plane or Line) to solve for
      return 0
  
  
  def initial_guess(largest_cluster, type_solution):
      if type_solution == "line":
          return 0
      elif type_solution == "plane":
          return 0
      # TODO: Get an inital guess from the perpendicular least squares method from the largest cluster
      return
  
  
  def check_guess(cluster, type_solution, guess):
      if type_solution == "line":
          return 0
      elif type_solution == "plane":
          return 0
      # TODO: check guess with another cluster
  
  
  def bootstrap_cluster(cluster):
      # TODO: bootstrap a cluster to get a different distribution to check with check_guess
      return 0
  
  
  def determine_uncertainty(solutions):
      # TODO: Take a list or dict of solutions and determine the uncertainty in them
      return 0
  
  if __name__ == "__main__":
      arguments = str(sys.argv)
      print(arguments)
     # for index, argument in enumerate(arguments):
      #    if index != 0:
      hdulist = fits.open("comafit.fits")
      print(hdulist.info())
  
  
new_contents: __author__ = 'Jacob Bieker'
  import os, sys, random
  import numpy
  from multiprocessing import Pool
  from astropy.io import fits
  
  
  def random_number(number, seed):
      if seed > 0:
          seed = -seed
      random.seed(a=seed)
      for i in range(number):
          rand_num = random.randint(0,1)
  
  
  def line_solve():
      # TODO: Find the Least Squares for a line
      return 0
  
  
  def plane_solve():
      # TODO: Find the least Squares for a plane
      return 0
  
  
  def read_clusters(*args):
      # TODO: Read in the files containing the cluster points
      return 0
  
  
  def determine_type():
      # TODO: Determine the type (i.e. Plane or Line) to solve for
      return 0
  
  
  def initial_guess(largest_cluster, type_solution):
      if type_solution == "line":
          return 0
      elif type_solution == "plane":
          return 0
      # TODO: Get an inital guess from the perpendicular least squares method from the largest cluster
      return
  
  
  def check_guess(cluster, type_solution, guess):
      if type_solution == "line":
          return 0
      elif type_solution == "plane":
          return 0
      # TODO: check guess with another cluster
  
  
  def bootstrap_cluster(cluster):
      # TODO: bootstrap a cluster to get a different distribution to check with check_guess
      return 0
  
  
  def determine_uncertainty(solutions):
      # TODO: Take a list or dict of solutions and determine the uncertainty in them
      return 0
  
  if __name__ == "__main__":
      iterations = 0
      galaxy_name = ""
      group_name = ""
      factor_change_a = 0.0
      factor_change_b = 0.0
      restart_factor = True
      num_bootstrap = 0
      rand_seed = 1
      zeropoint_choice = "median" # or mean
      min_distance = "delta100" # or quartile, delta60, rms100, rms60
      min_residual = "per" # or y, x1, x2
      y_col = "lre_GR_sc" # prompt for it
      x1_col = "lsig_re" # prompt for it
      x2_col = "lIe_GR_sccor" # prompt for it (optional)
      list_clusters = [] # prompt "List of input STSDAS tables"
  
      hdulist = fits.open("comafit.fits")
      print(hdulist.info())
      print(repr(hdulist[0].header))
  
  
  
subject: Add initial parameters from Fortran code