as.factor and floating point numbers
Another option is to convert all times to base units or the sample rate from the analog-to-digital converter. If this is 100 milliseconds then use milliseconds rather than fractions of an hour or day. This approach might not help if the range in values spans more than 16 digits: slightly finer resolution than one year sampled in microseconds. Tim -----Original Message----- From: R-help <r-help-bounces at r-project.org> On Behalf Of Andrew Simmons Sent: Wednesday, January 25, 2023 4:13 AM To: Tobias Fellinger <tobby at htu.at> Cc: r-help at r-project.org Subject: Re: [R] as.factor and floating point numbers [External Email] R converts floats to strings with ~15 digits of accuracy, specifically to avoid differentiating between 1 and 1 + .Machine$double.eps, it is assumed that small differences such as this are due to rounding errors and are unimportant. So, if when making your factor, you want all digits, you could write this: `as.factor(format(x, digits = 17L))`
On Wed, Jan 25, 2023 at 4:03 AM Tobias Fellinger <tobby at htu.at> wrote:
Hello,
I'm encountering the following error:
In a package for survival analysis I use a data.frame is created, one column is created by applying unique on the event times while others are created by running table on the event times and the treatment arm.
When there are event times very close together they are put in the same factor level when coerced to factor while unique outputs both values, leading to different lengths of the columns.
Try this to reproduce:
x <- c(1, 1+.Machine$double.eps)
unique(x)
table(x)
Is there a general best practice to deal with such issues?
Should calling table on floats be avoided in general?
What can one use instead?
One could easily iterate over the unique values and compare all values with the whole vector but this are N*N comparisons, compared to N*log(N) when sorting first and taking into account that the vector is sorted.
I think for my purposes I'll round to a hundredth of a day before calling the function, but any advice on avoiding this issue an writing more fault tolerant code is greatly appreciated.
all the best, Tobias
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