search for: 2e7

i want to plot values with frequency on a logarithmic x axis. similar to this example that i found in the web: http://www.usspeaker.com/jensen%20p15n-graph.gif I would like to convert long numbers to si prefix notation like in the example (200000 to 200k, 35000000 to 3.5 M) Of course i could create labels by hand, but i have many files so i need some automatic function. Has anyone done that

On 02/02/2010 6:20 AM, Dimitri Shvorob wrote: > Ruben Roa has kindly suggested using 'scipen' option - cf. > >> fixed notation will be preferred unless it is more than ???scipen??? digits >> wider. > > However, > > options(scipen = 50) > x = c(1e7, 2e7) > barplot(x) > > still does not produce the desired result. This is strange. I see what you describe the first time through, but if I print the option I get the non-scientific labels on the second plot: options(scipen = 50) x = c(1e7, 2e7) barplot(x) options("scipen") barp...

Is there a better alternative to x = c(1e7, 2e7) x.lb = c(0,1e7,2e7) s.lb = format(x.lb, scientific = FALSE, big.mark = ",") barplot(x, yaxt = "n", ylab = "") axis(side = 2, at = x.lb, labels = s.lb) (I am sure there is a better alternative to line 2 :)). Thank you. -- View this message in context: http://n4.n...

...as kindly suggested using 'scipen' option - cf. >> >>> fixed notation will be preferred unless it is more than =C3=A2=E2=82=AC= =CB=9Cscipen=C3=A2=E2=82=AC=E2=84=A2 digits >>> wider. >> However,=20 >> >> options(scipen =3D 50) >> x =3D c(1e7, 2e7) >> barplot(x)=20 >> >> still does not produce the desired result. >=20 > This is strange. I see what you describe the first time through, but > if I print the option I get the non-scientific labels on the second plo= t: >=20 > options(scipen =3D 50) > x =3D c(...

I hope it's not too specific in my setup... I've tried with system2 added on the first line, so: Example.R: system2('ls', timeout=5) cat('Start non-interruptable functions\n') sample_a <- sample(1:1e7) sample_b <- sample(1:2e7) matching <- match(sample_a, sample_b) cat('Finished\n') Sys.sleep(10) And in terminal/bash: R --vanilla source('Example.R') Send ^C between the messages (Start... until Finished) Or if you have a more powerful CPU you can increase the samples, the exact code doesn't matte...

...e time is allowed to pass, so that when the function returns the script can be interrupted), or whether I have called base::system() or system2() with timeout other than 0. Reproducible example: cat('Start non-interruptable functions\n') sample_a <- sample(1:1e7) sample_b <- sample(1:2e7) matching <- match(sample_a, sample_b) cat('Finished\n') Sys.sleep(10) Observed behaviour: In a clean session, when I hit Ctrl-C during the execution of match, there is a delay, and as soon as Sys.sleep() is invoked, the script is interrupted, I get back my R ?>?-prompt (unless optio...

...: > > I hope it's not too specific in my setup... > I've tried with system2 added on the first line, so: > > Example.R: > system2('ls', timeout=5) > cat('Start non-interruptable functions\n') > sample_a <- sample(1:1e7) > sample_b <- sample(1:2e7) > matching <- match(sample_a, sample_b) > cat('Finished\n') > Sys.sleep(10) > > And in terminal/bash: > R --vanilla > source('Example.R') > Send ^C between the messages (Start... until Finished) > > Or if you have a more powerful CPU you can increa...

...r. I would take this one-in-ten fact quite seriously, except for the extent to which which R users are perhaps more likely (as compared with the population) to volunteer information about what packages they use. Now let's engage in some wild guesswork. * It is believed that there are roughly 2e7 desktops in the world today, running a freeware Unix system. * Debian is undoubtedly a biased source of data, in having the more geeky users. Let's knock off a factor of 10 in order to correct for this. * If we think that 1% of all freeware Unix users are R users, then we get to an es...

...s, so that when the function returns the script can be interrupted), or whether I have called base::system() or system2() with timeout other than 0. > > Reproducible example: > cat('Start non-interruptable functions\n') > sample_a <- sample(1:1e7) > sample_b <- sample(1:2e7) > matching <- match(sample_a, sample_b) > cat('Finished\n') > Sys.sleep(10) > > Observed behaviour: > In a clean session, when I hit Ctrl-C during the execution of match, there is a delay, and as soon as Sys.sleep() is invoked, the script is interrupted, I get back my...

Full_Name: Martin Frith Version: R-2.0.0 OS: linux-gnu Submission from: (NULL) (134.160.83.73) I have large vectors containing 100,000 to 20,000,000 numbers. However, they only contain a few hundred *distinct* numbers (e.g. positive integers < 200). When I do ecdf(v), it either runs out of memory, or it succeeds, but when I plot the ecdf with postscript, the output is unnecessarily bloated

I would really like the bug fixed. At least this one, because I know people in my institute using this function. I understand your arguments about open source, but I also saw in this mail list a proposal for a fix for this bug for which there were no answer from the people who are able to include it in the distribution. It looks like if there were interesting bugs and the other ones. I don't

Hi, I have a problem in accessing samba server from NT network neighbourhood. I can see the samba server icon on neighbourhood. But while trying to access then it's asking for user name & passowrd. I am not using local user & password from unix box rather it should be authenticated from NT PDC and accordingly I have modified the smb.conf file. Here is the sample of that. 103 flara %

...= 2000 , b = 0.05 ) , lower = c( 1000, 0 ) , upper = c( 3000, 1 ) ) a <- as.vector( coef( myfit )[ "a" ] ) b <- as.vector( coef( myfit )[ "b" ] ) brks <- c( 500, 1e7, 2e7, 3e7, 4e7 ) ggplot( objdtass, aes( x=a, y=b, z = x, fill=x ) ) + geom_tile() + geom_contour( breaks= brks ) + geom_point( x=a, y=b, colour="red" ) + geom_point( x=objdtassmin$a , y=objdtassmin$b , colour="green" ) + scale_fi...

...= 0.05 > ) > , lower = c( 1000, 0 ) > , upper = c( 3000, 1 ) > ) > a <- as.vector( coef( myfit )[ "a" ] ) > b <- as.vector( coef( myfit )[ "b" ] ) > > brks <- c( 500, 1e7, 2e7, 3e7, 4e7 ) > ggplot( objdtass, aes( x=a, y=b, z = x, fill=x ) ) + > geom_tile() + > geom_contour( breaks= brks ) + > geom_point( x=a, y=b, colour="red" ) + > geom_point( x=objdtassmin$a > , y=objdtassmin$b > , colour=...

I ran the following script. I satisfied the constraint by making a*b a single parameter, which isn't always possible. I also ran nlxb() from nlsr package, and this gives singular values of the Jacobian. In the unconstrained case, the svs are pretty awful, and I wouldn't trust the results as a model, though the minimum is probably OK. The constrained result has a much larger sum of squares.

https://cran.r-project.org/web/views/Optimization.html (Cran's optimization task view -- as always, you should search before posting) In general, nonlinear optimization with nonlinear constraints is hard, and the strategy used here (multiplying by a*b < 1000) may not work -- it introduces a discontinuity into the objective function, so gradient based methods may in particular be

I''ve been testing ZFS since it came out on b27 and this week I BFUed to b30. I''ve seen two problems, one I''ll call minor and the other major. The hardware is a Dell PowerEdge 2600 with 2 3.2GHz Xeons, 2GB memory and a perc3 controller. I have created a filesystem for over 1000 users on it and take hourly snapshots, which destroy the one from 24 hours ago, except the