old_contents: ###################################################################
  #  Numexpr - Fast numerical array expression evaluator for NumPy.
  #
  #      License: MIT
  #      Author:  See AUTHORS.txt
  #
  #  See LICENSE.txt and LICENSES/*.txt for details about copyright and
  #  rights to use.
  ####################################################################
  
  #######################################################################
  # This script compares the speed of the computation of a polynomial
  # for different (numpy and numexpr) in-memory paradigms.
  #
  # Author: Francesc Alted
  # Date: 2010-07-06
  #######################################################################
  
  import sys
  from time import time
  import numpy as np
  import numexpr as ne
  
  
  expr = ".25*x**3 + .75*x**2 - 1.5*x - 2"  # the polynomial to compute
  expr = "((.25*x + .75)*x - 1.5)*x - 2"  # a computer-friendly polynomial
  N = 10*1000*1000               # the number of points to compute expression
  x = np.linspace(-1, 1, N)   # the x in range [-1, 1]
  
  #what = "numpy"              # uses numpy for computations
  what = "numexpr"           # uses numexpr for computations
  
  def compute():
      """Compute the polynomial."""
      if what == "numpy":
          y = eval(expr)
      else:
          y = ne.evaluate(expr)
      return len(y)
  
  
  if __name__ == '__main__':
      if len(sys.argv) > 1:  # first arg is the package to use
          what = sys.argv[1]
      if len(sys.argv) > 2:  # second arg is the number of threads to use
          nthreads = int(sys.argv[2])
          if "ncores" in dir(ne):
              ne.set_num_threads(nthreads)
      if what not in ("numpy", "numexpr"):
          print "Unrecognized module:", what
          sys.exit(0)
      print "Computing: '%s' using %s with %d points" % (expr, what, N)
      t0 = time()
      result = compute()
      ts = round(time() - t0, 3)
      print "*** Time elapsed:", ts
  
new_contents: ###################################################################
  #  Numexpr - Fast numerical array expression evaluator for NumPy.
  #
  #      License: MIT
  #      Author:  See AUTHORS.txt
  #
  #  See LICENSE.txt and LICENSES/*.txt for details about copyright and
  #  rights to use.
  ####################################################################
  
  #######################################################################
  # This script compares the speed of the computation of a polynomial
  # for different (numpy and numexpr) in-memory paradigms.
  #
  # Author: Francesc Alted
  # Date: 2010-07-06
  #######################################################################
  
  import sys
  from time import time
  import numpy as np
  import numexpr as ne
  
  
  #expr = ".25*x**3 + .75*x**2 - 1.5*x - 2"  # the polynomial to compute
  expr = "((.25*x + .75)*x - 1.5)*x - 2"  # a computer-friendly polynomial
  N = 10*1000*1000               # the number of points to compute expression
  x = np.linspace(-1, 1, N)   # the x in range [-1, 1]
  
  #what = "numpy"              # uses numpy for computations
  what = "numexpr"           # uses numexpr for computations
  
  def compute():
      """Compute the polynomial."""
      if what == "numpy":
          y = eval(expr)
      else:
          y = ne.evaluate(expr)
      return len(y)
  
  
  if __name__ == '__main__':
      if len(sys.argv) > 1:  # first arg is the package to use
          what = sys.argv[1]
      if len(sys.argv) > 2:  # second arg is the number of threads to use
          nthreads = int(sys.argv[2])
          if "ncores" in dir(ne):
              ne.set_num_threads(nthreads)
      if what not in ("numpy", "numexpr"):
          print "Unrecognized module:", what
          sys.exit(0)
      print "Computing: '%s' using %s with %d points" % (expr, what, N)
      t0 = time()
      result = compute()
      ts = round(time() - t0, 3)
      print "*** Time elapsed:", ts
  
subject: Comment explicitly the expression that is not used