Lib/whrandom.py

#	WICHMANN-HILL RANDOM NUMBER GENERATOR
#
#	Wichmann, B. A. & Hill, I. D. (1982)
#	Algorithm AS 183: 
#	An efficient and portable pseudo-random number generator
#	Applied Statistics 31 (1982) 188-190
#
#	see also: 
#		Correction to Algorithm AS 183
#		Applied Statistics 33 (1984) 123  
#
#		McLeod, A. I. (1985)
#		A remark on Algorithm AS 183 
#		Applied Statistics 34 (1985),198-200
#
#
#	USE:
#	whrandom.random()	yields double precision random numbers 
#				uniformly distributed between 0 and 1.
#
#	whrandom.seed(x, y, z)	must be called before whrandom.random()
#				to seed the generator
#
#	There is also an interface to create multiple independent
#	random generators, and to choose from other ranges.


#	Translated by Guido van Rossum from C source provided by
#	Adrian Baddeley.


# Multi-threading note: the random number generator used here is not
# thread-safe; it is possible that nearly simultaneous calls in
# different theads return the same random value.  To avoid this, you
# have to use a lock around all calls.  (I didn't want to slow this
# down in the serial case by using a lock here.)


class whrandom:
	#
	# Initialize an instance.
	# Without arguments, initialize from current time.
	# With arguments (x, y, z), initialize from them.
	#
	def __init__(self, x = 0, y = 0, z = 0):
		self.seed(x, y, z)
	#
	# Set the seed from (x, y, z).
	# These must be integers in the range [0, 256).
	#
	def seed(self, x = 0, y = 0, z = 0):
		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):
			raise ValueError, 'seeds must be in range(0, 256)'
		if 0 == x == y == z:
			# Initialize from current time
			import time
			t = long(time.time() * 256)
			t = int((t&0xffffff) ^ (t>>24))
			t, x = divmod(t, 256)
			t, y = divmod(t, 256)
			t, z = divmod(t, 256)
		# Zero is a poor seed, so substitute 1
		self._seed = (x or 1, y or 1, z or 1)
	#
	# Get the next random number in the range [0.0, 1.0).
	#
	def random(self):
		# This part is thread-unsafe:
		# BEGIN CRITICAL SECTION
		x, y, z = self._seed
		#
		x = (171 * x) % 30269
		y = (172 * y) % 30307
		z = (170 * z) % 30323
		#
		self._seed = x, y, z
		# END CRITICAL SECTION
		#
		return (x/30269.0 + y/30307.0 + z/30323.0) % 1.0
	#
	# Get a random number in the range [a, b).
	#
	def uniform(self, a, b):
		return a + (b-a) * self.random()
	#
	# Get a random integer in the range [a, b] including both end points.
	# (Deprecated; use randrange below.)
	#
	def randint(self, a, b):
		return self.randrange(a, b+1)
	#
	# Choose a random element from a non-empty sequence.
	#
	def choice(self, seq):
		return seq[int(self.random() * len(seq))]
	#
	# Choose a random item from range([start,] step[, stop]).
	# This fixes the problem with randint() which includes the
	# endpoint; in Python this is usually not what you want.
	#
	def randrange(self, start, stop=None, step=1,
		      # Do not supply the following arguments
		      int=int, default=None):
		# This code is a bit messy to make it fast for the
		# common case while still doing adequate error checking
		istart = int(start)
		if istart != start:
			raise ValueError, "non-integer arg 1 for randrange()"
		if stop is default:
			if istart > 0:
				return int(self.random() * istart)
			raise ValueError, "empty range for randrange()"
		istop = int(stop)
		if istop != stop:
			raise ValueError, "non-integer stop for randrange()"
		if step == 1:
			if istart < istop:
				return istart + int(self.random() *
						   (istop - istart))
			raise ValueError, "empty range for randrange()"
		istep = int(step)
		if istep != step:
			raise ValueError, "non-integer step for randrange()"
		if istep > 0:
			n = (istop - istart + istep - 1) / istep
		elif istep < 0:
			n = (istop - istart + istep + 1) / istep
 		else:
 			raise ValueError, "zero step for randrange()"

 		if n <= 0:
 			raise ValueError, "empty range for randrange()"
 		return istart + istep*int(self.random() * n)


# Initialize from the current time
#
_inst = whrandom()
seed = _inst.seed
random = _inst.random
uniform = _inst.uniform
randint = _inst.randint
choice = _inst.choice
randrange = _inst.randrange