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Minor refactoring and cleanup. Extend looping randrange() technique to subclasses.

This commit is contained in:
Raymond Hettinger 2010-09-07 19:19:33 +00:00
parent e339651b6f
commit 05a505f106
1 changed files with 23 additions and 20 deletions
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43
Lib/random.py
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@ -212,25 +212,33 @@ class Random(_random.Random):
return self.randrange(a, b+1)
def _randbelow(self, n, int=int, _maxwidth=1<<BPF, type=type,
_Method=_MethodType, _BuiltinMethod=_BuiltinMethodType):
def _randbelow(self, n, int=int, bpf=BPF, type=type,
Method=_MethodType, BuiltinMethod=_BuiltinMethodType):
"""Return a random int in the range [0,n). Raises ValueError if n==0.
"""
k = n.bit_length() # don't use (n-1) here because n can be 1
getrandbits = self.getrandbits
# Only call self.getrandbits if the original random() builtin method
# has not been overridden or if a new getrandbits() was supplied.
# This assures that the two methods correspond.
if type(self.random) is _BuiltinMethod or type(getrandbits) is _Method:
k = n.bit_length() # don't use (n-1) here because n can be 1
if type(self.random) is BuiltinMethod or type(getrandbits) is Method:
r = getrandbits(k) # 0 <= r < 2**k
while r >= n:
r = getrandbits(k)
return r
if n >= _maxwidth:
# There's an overriden random() method but no new getrandbits() method,
# so we can only use random() from here.
if k > bpf:
_warn("Underlying random() generator does not supply \n"
"enough bits to choose from a population range this large")
return int(self.random() * n)
return int(self.random() * n)
random = self.random
N = 1 << k
r = int(N * random())
while r >= n:
r = int(N * random())
return r
## -------------------- sequence methods -------------------
@ -249,16 +257,11 @@ class Random(_random.Random):
float in [0.0, 1.0); by default, the standard random.random.
"""
if random is None:
for i in reversed(range(1, len(x))):
# pick an element in x[:i+1] with which to exchange x[i]
j = self._randbelow(i+1)
x[i], x[j] = x[j], x[i]
else:
for i in reversed(range(1, len(x))):
# pick an element in x[:i+1] with which to exchange x[i]
j = int(random() * (i+1))
x[i], x[j] = x[j], x[i]
randbelow = self._randbelow
for i in reversed(range(1, len(x))):
# pick an element in x[:i+1] with which to exchange x[i]
j = randbelow(i+1) if random is None else int(random() * (i+1))
x[i], x[j] = x[j], x[i]
def sample(self, population, k):
"""Chooses k unique random elements from a population sequence or set.
@ -292,7 +295,7 @@ class Random(_random.Random):
population = tuple(population)
if not isinstance(population, _collections.Sequence):
raise TypeError("Population must be a sequence or Set. For dicts, use list(d).")
random = self.random
randbelow = self._randbelow
n = len(population)
if not 0 <= k <= n:
raise ValueError("Sample larger than population")
@ -304,16 +307,16 @@ class Random(_random.Random):
# An n-length list is smaller than a k-length set
pool = list(population)
for i in range(k): # invariant: non-selected at [0,n-i)
j = self._randbelow(n-i)
j = randbelow(n-i)
result[i] = pool[j]
pool[j] = pool[n-i-1] # move non-selected item into vacancy
else:
selected = set()
selected_add = selected.add
for i in range(k):
j = self._randbelow(n)
j = randbelow(n)
while j in selected:
j = self._randbelow(n)
j = randbelow(n)
selected_add(j)
result[i] = population[j]
return result