I'm glad you are happy with your solution. Just one inline comment below, expanding on my private reply to you:

Žroutík wrote:
Resolved.

nchar(unlist(strsplit(as.character(n),"\\.")))[2]

in the function:
NumberPrecision <- function(n) {
PocetCyklu <- 0
if(n != round(n)) {
PocetCyklu <- nchar(unlist(strsplit(n,"\\.")))[2]
}
else {
while(n == round(n)) {
n <- n/10
PocetCyklu <- PocetCyklu + 1
}
PocetCyklu <- PocetCyklu - 1
#}
PocetCyklu
}

for 130000 the precision of the given value is the last given digit -- 5,
for 12.345 it gives 3. Perfect.

Regards, Z

Thank you for the thoughtful conversation.

---------- Forwarded message ----------
From: Žroutík <zrou...@gmail.com>
Date: Fri, Feb 13, 2009 at 7:32 AM
Subject: Re: [R] trunc/floor a number -- strange bahaviour
To: Duncan Murdoch <murd...@stats.uwo.ca>


Thank you Duncan, and Thierry, to you, too, for the quick responses.

In the FAQ, there is a different example, IMO. The value sqrt(2) is created
by some function and is irrational -- I do understand in "never-ending"
numbers programs do have to cut some digits off, therefore a mismatch. But
in my example the given value is fix (it is written into an input file by a
user) and there is always a fix number of digits and the number is not
irrational.

I do not understand how can the given/fix number 0.0001 be abruptly
represented as 0.000099999.

You say it's about binary floating point. But this is way the binary
floating point was created, for real ending values, isn't it so?

12.34 is represented as 1234 (integer) times ten (integer) to the minus 2
(integer). (n - floor(n))*10 Minus floor(12) (integer), times ten gives 34
(integer) times ten to the -1 (integer).

No, that's not how standard floating point representations work.  12.34 is 
represented as a finite precision binary number between 1 and 2 (starting out 
as 1.10001 in binary notation) multiplied by 2^3.  The problem is that there is 
no way to represent it exactly in this format.  Only fractions with a power of 
2 in the denominator can be represented that way, and 12.34 is not one of 
those.  It's 1234/100, and 100 is not a power of 2.

Duncan Murdoch


Is there any way how can I check on not to crush in such a problems. I
remind you, I do not count with irrational or other "neverending" numbers.

Regrads,
Zroutik


On Thu, Feb 12, 2009 at 4:44 PM, Duncan Murdoch <murd...@stats.uwo.ca>wrote:

On 2/12/2009 10:20 AM, Žroutík wrote:

Hi everybody,

given a fresh rgui.exe load on winxp OS, I enter (a minimal exaple)

n <- 12.357531

Then the following command:
n <- (n - floor(n))*10; n

gives the following outputs:
[1] 3.57531
[1] 5.7531
[1] 7.531
[1] 5.31
[1] 3.1
[1] 1         === still as expected
[1] 10        === not expected, count with me: 1 - floor(1) is zero, times
10 gives 0, not 10!!!!

You are assuming that when R prints "1", the value is exactly 1.  But try
this:

0.999999999
[1] 1
0.999999999 == 1
[1] FALSE

R rounds values when it prints them, because people don't want to see ugly
output like this:

options(digits=18):
n <- 12.357531
n <- (n - floor(n))*10; n
[1] 3.5753100
n <- (n - floor(n))*10; n
[1] 5.75309999999998
n <- (n - floor(n))*10; n
[1] 7.530999999999821
n <- (n - floor(n))*10; n
[1] 5.30999999999821
n <- (n - floor(n))*10; n
[1] 3.099999999982117
n <- (n - floor(n))*10; n
[1] 0.999999999821171

And the reason you see such ugly output is because you are working with a
number that can't be represented exactly in binary floating point.

Duncan Murdoch

 [1] 10        === should stay forever zero (0)
[1] 10
[1] 9.999998
[1] 9.999982
[1] 9.999821
[1] 9.998212

The sama happens with trunc().
e.g. (a minimal exaple)

n <- 0.245
n <- (n - trunc(n))*10; n
[1] 2.45
[1] 4.5
[1] 5
[1] 1.776357e-13 ===== zero expected!!!
[1] 1.776357e-12

And I'm asking "what the heck?!" and where is the bug in my examples? Any
suggestion well appreciated.

p.s. The expression with floor() and trunc() are to be implemented in a
function which gives a value equal precision order of the given number.
e.g.
12.345 would have (-3), 12.1 would have (-1), 12 would have (0) and e.g.
12000 would have the order of the precision (4). Basically, it is the
order
of the last given non-zero digit.

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