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authorRaymond Hettinger <python@rcn.com>2009-06-28 22:30:13 (GMT)
committerRaymond Hettinger <python@rcn.com>2009-06-28 22:30:13 (GMT)
commiteafaf4c0b5f97613b3eaf1872b4314edc11b74bf (patch)
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parent97479ad6075e647e600b1699678ad039a667b554 (diff)
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Small doc fix-ups to floatingpoint.rst. More are forthcoming.
Diffstat (limited to 'Doc/tutorial')
-rw-r--r--Doc/tutorial/floatingpoint.rst10
1 files changed, 5 insertions, 5 deletions
diff --git a/Doc/tutorial/floatingpoint.rst b/Doc/tutorial/floatingpoint.rst
index a8a4202..2db1842 100644
--- a/Doc/tutorial/floatingpoint.rst
+++ b/Doc/tutorial/floatingpoint.rst
@@ -82,7 +82,7 @@ values share the same approximation, any one of them could be displayed
while still preserving the invariant ``eval(repr(x)) == x``.
Historically, the Python prompt and built-in :func:`repr` function would chose
-the one with 17 significant digits, ``0.10000000000000001``, Starting with
+the one with 17 significant digits, ``0.10000000000000001``. Starting with
Python 3.1, Python (on most systems) is now able to choose the shortest of
these and simply display ``0.1``.
@@ -123,9 +123,9 @@ Also, since the 0.1 cannot get any closer to the exact value of 1/10 and
Though the numbers cannot be made closer to their intended exact values,
the :func:`round` function can be useful for post-rounding so that results
-have inexact values that are comparable to one another::
+with inexact values become comparable to one another::
- >>> round(.1 + .1 + .1, 1) == round(.3, 1)
+ >>> round(.1 + .1 + .1, 10) == round(.3, 10)
True
Binary floating-point arithmetic holds many surprises like this. The problem
@@ -137,7 +137,7 @@ As that says near the end, "there are no easy answers." Still, don't be unduly
wary of floating-point! The errors in Python float operations are inherited
from the floating-point hardware, and on most machines are on the order of no
more than 1 part in 2\*\*53 per operation. That's more than adequate for most
-tasks, but you do need to keep in mind that it's not decimal arithmetic, and
+tasks, but you do need to keep in mind that it's not decimal arithmetic and
that every float operation can suffer a new rounding error.
While pathological cases do exist, for most casual use of floating-point
@@ -165,7 +165,7 @@ fraction::
>>> x = 3.14159
>>> x.as_integer_ratio()
- (3537115888337719L, 1125899906842624L)
+ (3537115888337719, 1125899906842624)
Since the ratio is exact, it can be used to losslessly recreate the
original value::