On Wed, Apr 30, 2014 at 9:53 AM, Roy Smith <r...@panix.com> wrote:
> In article <mailman.9575.1398789020.18130.python-l...@python.org>,
> Chris Angelico <ros...@gmail.com> wrote:
>
>> On Tue, Apr 29, 2014 at 11:38 PM, Roy Smith <r...@panix.com> wrote:
>> > I'm trying to intuit, from the values I've been given, which coordinates
>> > are likely to be accurate to within a few miles. I'm willing to accept
>> > a few false negatives. If the number is float("38"), I'm willing to
>> > accept that it might actually be float("38.0000"), and I might be
>> > throwing out a good data point that I don't need to.
>>
>> You have one chance in ten, repeatably, of losing a digit. That is,
>> roughly 10% of your four-decimal figures will appear to be
>> three-decimal, and 1% of them will appear to be two-decimal, and so
>> on. Is that "a few" false negatives?
>
> You're looking at it the wrong way. It's not that the glass is 10%
> empty, it's that it's 90% full, and 90% is a lot of good data :-)
Hah! That's one way of looking at it.
At least you don't have to worry about junk digits getting in. The
greatest precision you're working with is three digits before the
decimal and four after, and a Python float can handle that easily.
(Which is what I was concerned about when I first queried your
terminology - four digits to the right of the decimal and, say, 10-12
to the left, and you're starting to see problems.)
ChrisA
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