[Python-checkins] python/dist/src/Lib random.py,1.38,1.39

[rhettinger@projects.sourceforge.net]

Update of /cvsroot/python/python/dist/src/Lib
In directory sc8-pr-cvs1:/tmp/cvs-serv29985/Lib

Modified Files:
	random.py 
Log Message:
Improve comments.  Clarify docs.  
Replace "type(0)" with "int".
Replace "while 1" with "while True"



Index: random.py
===================================================================
RCS file: /cvsroot/python/python/dist/src/Lib/random.py,v
retrieving revision 1.38
retrieving revision 1.39
diff -C2 -d -r1.38 -r1.39
*** random.py	13 Nov 2002 15:26:37 -0000	1.38
--- random.py	18 Nov 2002 09:01:21 -0000	1.39
***************
*** 240,244 ****
          """
  
!         if not type(x) == type(y) == type(z) == type(0):
              raise TypeError('seeds must be integers')
          if not (0 <= x < 256 and 0 <= y < 256 and 0 <= z < 256):
--- 240,244 ----
          """
  
!         if not type(x) == type(y) == type(z) == int:
              raise TypeError('seeds must be integers')
          if not (0 <= x < 256 and 0 <= y < 256 and 0 <= z < 256):
***************
*** 408,413 ****
          # __contains__ for detecting repeat selections.  Discarding repeats
          # is efficient unless most of the population has already been chosen.
!         # So, tracking selections is useful when sample sizes are much
!         # smaller than the total population.
  
          n = len(population)
--- 408,412 ----
          # __contains__ for detecting repeat selections.  Discarding repeats
          # is efficient unless most of the population has already been chosen.
!         # So, tracking selections is fast only with small sample sizes.
  
          n = len(population)
***************
*** 418,434 ****
          result = [None] * k
          if n < 6 * k:     # if n len list takes less space than a k len dict
!             pool = list(population)             # track potential selections
!             for i in xrange(k):
!                 j = int(random() * (n-i))       # non-selected at [0,n-i)
!                 result[i] = pool[j]             # save selected element
!                 pool[j] = pool[n-i-1]           # non-selected to head of list
          else:
!             selected = {}                       # track previous selections
              for i in xrange(k):
                  j = int(random() * n)
!                 while j in selected:            # discard and replace repeats
                      j = int(random() * n)
                  result[i] = selected[j] = population[j]
!         return result       # return selections in the order they were picked
  
  ## -------------------- real-valued distributions  -------------------
--- 417,433 ----
          result = [None] * k
          if n < 6 * k:     # if n len list takes less space than a k len dict
!             pool = list(population)
!             for i in xrange(k):         # invariant:  non-selected at [0,n-i)
!                 j = int(random() * (n-i))
!                 result[i] = pool[j]
!                 pool[j] = pool[n-i-1]
          else:
!             selected = {}
              for i in xrange(k):
                  j = int(random() * n)
!                 while j in selected:
                      j = int(random() * n)
                  result[i] = selected[j] = population[j]
!         return result
  
  ## -------------------- real-valued distributions  -------------------
***************
*** 456,460 ****
  
          random = self.random
!         while 1:
              u1 = random()
              u2 = random()
--- 455,459 ----
  
          random = self.random
!         while True:
              u1 = random()
              u2 = random()
***************
*** 549,553 ****
          r = (1.0 + b * b)/(2.0 * b)
  
!         while 1:
              u1 = random()
  
--- 548,552 ----
          r = (1.0 + b * b)/(2.0 * b)
  
!         while True:
              u1 = random()
  
***************
*** 596,600 ****
              ccc = alpha + ainv
  
!             while 1:
                  u1 = random()
                  u2 = random()
--- 595,599 ----
              ccc = alpha + ainv
  
!             while True:
                  u1 = random()
                  u2 = random()
***************
*** 617,621 ****
              # Uses ALGORITHM GS of Statistical Computing - Kennedy & Gentle
  
!             while 1:
                  u = random()
                  b = (_e + alpha)/_e
--- 616,620 ----
              # Uses ALGORITHM GS of Statistical Computing - Kennedy & Gentle
  
!             while True:
                  u = random()
                  b = (_e + alpha)/_e