[Python-checkins] r68379 - in python/branches/py3k: Doc/library/random.rst Lib/random.py

[mark.dickinson]

Author: mark.dickinson
Date: Wed Jan  7 18:54:07 2009
New Revision: 68379

Log:
Merged revisions 68378 via svnmerge from 
svn+ssh://pythondev@svn.python.org/python/trunk

........
  r68378 | mark.dickinson | 2009-01-07 17:48:33 +0000 (Wed, 07 Jan 2009) | 2 lines
  
  Issue #4869: clarify documentation for random.expovariate.
........


Modified:
   python/branches/py3k/   (props changed)
   python/branches/py3k/Doc/library/random.rst
   python/branches/py3k/Lib/random.py

Modified: python/branches/py3k/Doc/library/random.rst
==============================================================================
--- python/branches/py3k/Doc/library/random.rst	(original)
+++ python/branches/py3k/Doc/library/random.rst	Wed Jan  7 18:54:07 2009
@@ -169,9 +169,11 @@
 
 .. function:: expovariate(lambd)
 
-   Exponential distribution.  *lambd* is 1.0 divided by the desired mean.  (The
-   parameter would be called "lambda", but that is a reserved word in Python.)
-   Returned values range from 0 to positive infinity.
+   Exponential distribution.  *lambd* is 1.0 divided by the desired
+   mean.  It should be nonzero.  (The parameter would be called
+   "lambda", but that is a reserved word in Python.)  Returned values
+   range from 0 to positive infinity if *lambd* is positive, and from
+   negative infinity to 0 if *lambd* is negative.
 
 
 .. function:: gammavariate(alpha, beta)

Modified: python/branches/py3k/Lib/random.py
==============================================================================
--- python/branches/py3k/Lib/random.py	(original)
+++ python/branches/py3k/Lib/random.py	Wed Jan  7 18:54:07 2009
@@ -396,9 +396,11 @@
     def expovariate(self, lambd):
         """Exponential distribution.
 
-        lambd is 1.0 divided by the desired mean.  (The parameter would be
-        called "lambda", but that is a reserved word in Python.)  Returned
-        values range from 0 to positive infinity.
+        lambd is 1.0 divided by the desired mean.  It should be
+        nonzero.  (The parameter would be called "lambda", but that is
+        a reserved word in Python.)  Returned values range from 0 to
+        positive infinity if lambd is positive, and from negative
+        infinity to 0 if lambd is negative.
 
         """
         # lambd: rate lambd = 1/mean