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author | Raymond Hettinger <python@rcn.com> | 2009-06-28 22:30:13 (GMT) |
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committer | Raymond Hettinger <python@rcn.com> | 2009-06-28 22:30:13 (GMT) |
commit | eafaf4c0b5f97613b3eaf1872b4314edc11b74bf (patch) | |
tree | 6c8c0a32bd1131e8d5c3650e0944853c59c46081 /Doc/tutorial/floatingpoint.rst | |
parent | 97479ad6075e647e600b1699678ad039a667b554 (diff) | |
download | cpython-eafaf4c0b5f97613b3eaf1872b4314edc11b74bf.zip cpython-eafaf4c0b5f97613b3eaf1872b4314edc11b74bf.tar.gz cpython-eafaf4c0b5f97613b3eaf1872b4314edc11b74bf.tar.bz2 |
Small doc fix-ups to floatingpoint.rst. More are forthcoming.
Diffstat (limited to 'Doc/tutorial/floatingpoint.rst')
-rw-r--r-- | Doc/tutorial/floatingpoint.rst | 10 |
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:: |