search for: env1

...w (question has same title as this email, except for the version of R). Running the code bellow we can see that the numericDeriv function gives an error as the derivative of x^a wrt a is x^a * log(x) and log is not defined for negative numbers. However, seems like the function changes the value of env1$a from 3 to 3.000000044703483581543. If x is a vector of positive values numericDeriv function completes the task without errors and env1$a remains unchanged as expected. This happened to me running R 4.0.1 on Ubuntu 20.04 and also to another StackOverflow user using running the same version of R...

...of R). > > > > Running the code bellow we can see that the numericDeriv function gives > an > > error as the derivative of x^a wrt a is x^a * log(x) and log is not > defined > > for negative numbers. However, seems like the function changes the value > of > > env1$a from 3 to 3.000000044703483581543. If x is a vector of positive > > values numericDeriv function completes the task without errors and > env1$a > > remains unchanged as expected. > > > > This happened to me running R 4.0.1 on Ubuntu 20.04 and also to another > >...

While using parallelization R seems to clone all environments (that are normally passed by reference) that are returned from a child process. In particular, consider the following example: library(parallel) env1 <- new.env() envs2 <- lapply(1:4, function(x) env1) cl<-makeCluster(2, type="FORK") envs3 <- parLapply(cl, 1:4, function(x) env1) envs4 <- parLapply(cl, 1:4, function(x) capture.output(str(env1))) stopCluster(cl) First I make an environment (env1). Then using the non-para...

...> this email, except for the version of R). > > Running the code bellow we can see that the numericDeriv function gives an > error as the derivative of x^a wrt a is x^a * log(x) and log is not defined > for negative numbers. However, seems like the function changes the value of > env1$a from 3 to 3.000000044703483581543. If x is a vector of positive > values numericDeriv function completes the task without errors and env1$a > remains unchanged as expected. > > This happened to me running R 4.0.1 on Ubuntu 20.04 and also to another > StackOverflow user using runni...

On 12.09.2018 20:20, G?bor Cs?rdi wrote: > This is all normal, a fork cluster works with processes, that do not > share memory. And if you are after shared-memory parallelism, you can try the 'Rdsm' package: https://cran.r-project.org/package=Rdsm Greetings Ralf -- Ralf Stubner Senior Software Engineer / Trainer daqana GmbH Dortustra?e 48 14467 Potsdam T: +49 331 23 61 93 11 F:

...l, I'm searching for a little clarification on partial mantel tests (ecodist package) I've a distance matrix (x,y), and several others containing environmental/chemical variables. Based on the help file, and the package instructions I've managed to implement the tests as; var1 ~ env1 + space to partial out the effect of space and test the relationship between the variable of interest vs variable env1. My questions are as follows; 1) can "raw" data be used to construct the dissimilarity matricies? or should they be standardized? different variables have differen...

Hi, I am running a logistic regression model using lrm library and I get the following error when I run the command: mod1 <- lrm(death ~ factor(score), x=T, y=T, data = env1) Unable to fit model using ?lrm.fit? where score is a numeric variable from 0 to 6. LRM executes fine for the following commands: mod1 <- lrm(death ~ score, x=T, y=T, data = env1) mod1<- lrm(death ~ factor(score)+ factor(var1)+factor(var2)+factor(var3)+...

...2, 2018 at 7:09 PM Niek Bouman <niek.bouman at keygene.com> wrote: > > While using parallelization R seems to clone all environments (that are normally passed by reference) that are returned from a child process. In particular, consider the following example: > library(parallel) > env1 <- new.env() > envs2 <- lapply(1:4, function(x) env1) > > cl<-makeCluster(2, type="FORK") > envs3 <- parLapply(cl, 1:4, function(x) env1) > envs4 <- parLapply(cl, 1:4, function(x) capture.output(str(env1))) > stopCluster(cl) > > First I make an envir...

Hi, Currently object.size() is not very useful on environments as it always returns 56 bytes, no matter how big the environment is: env1 <- new.env() object.size(env1) # 56 bytes env2 <- new.env(hash=TRUE, size=75000000L) object.size(env2) # 56 bytes env3 <- list2env(list(a=runif(25000000), L=LETTERS)) object.size(env3) # 56 bytes This makes it pretty useless on reference class instances and other objec...

Hello, I'm trying to illustrate the relationships between various trait and environment data gathered from a number of sites. I've created a GAM to do this: gam1=gam(trait~s(env1)+s(env2)+te(env1,env2)) and I know how to create a 3D plot using vis.gam. I want to be able to show points on the 3D plot indicating the sites that the data came from. I can do this on a 2D plot when there is one term, e.g. gam2=gam(trait~s(env1)) but cannot figure it out for the 3D plot. Any hel...

..., 2015 at 2:42 PM, Herv? Pag?s <hpages at fredhutch.org > <mailto:hpages at fredhutch.org>> wrote: > > Hi, > > Currently object.size() is not very useful on environments as it always > returns 56 bytes, no matter how big the environment is: > > env1 <- new.env() > object.size(env1) # 56 bytes > > env2 <- new.env(hash=TRUE, size=75000000L) > object.size(env2) # 56 bytes > > env3 <- list2env(list(a=runif(25000000), L=LETTERS)) > object.size(env3) # 56 bytes > > This ma...

I am running into a problem with my LDAP puppet setup with this error message: PuppetClient: err: Could not retrieve catalog from remote server: Error 400 on SERVER: Could not parse for environment DR: undefined method `to_sym'' for ["ENV1", "ENV2"]:Array PuppetMaster: err: Could not parse for environment DR: undefined method `to_sym'' for ["ENV1", "ENV2"]:Array The "environment" variable is part of the LDAP node definition and in this case, the node in question belongs to two di...

...ts defaults: # - /var/lib/hiera on *nix # - %CommonAppData%\PuppetLabs\hiera\var on Windows # When specifying a datadir, make sure the directory exists. #:datadir: /etc/puppet/hieradata :datadir: /etc/puppet/environments/%{environment}/hieradata :merge_behavior: deeper /etc/puppet/environments/env1/manifests/site.pp node default { hiera_include ( "classes", [] ) } /etc/puppet/environments/env1/hieradata/common.yaml classes: - accounts /etc/puppet/environments/env1/modules/accounts/manifests/init.pp class accounts::users ( $accounts, $groups, ) { c...

...with this I would be truly grateful for your help! I am fairly new to R, and I have quickly found myself in a place where "Google-ing" has no longer proven useful. Below are my scripts and error messages. Using Vegan: > vare.cca <- cca(InvertR.csv ~ Space1 + Space2... + Condition(Env1) + > Condition(Env2)..., HabitatSpaceR.csv) > randtest(vare.cca, nrepet = 1000) Error in randtest.cca(vare.cca, nrepet = 1000) : Object of class dudi expected Using ade4: > vare.cca <- cca(InvertR.csv ~ Space1 + Space2... + Condition(Env1) + > Condition(Env2)..., HabitatSpaceR.cs...

Hi. I'm trying to perform what should be a reasonably basic analysis of some spatial presence/absence data but am somewhat overwhelmed by the options available and could do with a helpful pointer. My researches so far indicate that if my data were normal, I would simply use gls() (in nlme) and one of the various corSpatial functions (eg. corSpher() to be analagous to similar analysis in SAS)

...ould only be using ~ N + 2*56 bytes, right? ~G On Tue, Sep 29, 2015 at 2:42 PM, Herv? Pag?s <hpages at fredhutch.org> wrote: > Hi, > > Currently object.size() is not very useful on environments as it always > returns 56 bytes, no matter how big the environment is: > > env1 <- new.env() > object.size(env1) # 56 bytes > > env2 <- new.env(hash=TRUE, size=75000000L) > object.size(env2) # 56 bytes > > env3 <- list2env(list(a=runif(25000000), L=LETTERS)) > object.size(env3) # 56 bytes > > This makes it pretty useless on refe...

Hello, I''m using the following expression to format a list: $valid_environments = [''env1'', ''env2'', ''env3''] $env_message = $valid_environments.reduce |$message, $env| { "${message}, ${env}" } It works at run-time (Puppet 3.2.4 standalone with "--parser=future"). However in Eclipse (v4.3.1), Geppetto (v4.0) shows...

Hi all, I made sure that it's "env$sRes1$nPositionsOptimizedM" that's correct... not the "env$sRes1$nPositionsOptimized"... But it seems both point to the same memory area... This is very dangerous because I have used naming conventions such as: MyLongVariableNameForA MyLongVariableNameForB MyLongVariableNameForC ... ... Then if internally they are actually the

...2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("Control", "Treatment"), class = "factor"), Env1 = c(-23.99, 0, -23.4, -24.77, 4.92, 4.94, 4.96, 4.93, 4.97, 4.99, 5.06, -12.12, 5.2, 0, 0, 5.07, 5.09, 0, 5.07, 0, 5, 0, -27.63, 4.44, 0, 0, 0, 4.33, 4.33, 0, 5.07, 5.07, 5.03, 5.01, 0, 0, 4.97, 0, 4.98, 5.07, 0, 5.08, 0, 0, 4.91, -35.98, 0, 0, 0, 5.2, 0, 4.89, 5.07, 0, 4.96, 4....

Dear list, I have a problem with nested functions and I don't manage to get it solved. I know I should be looking in environments, and I have tried a lot, but it keeps on erroring. An easy version of the problem is as follows: innerfunction<-function() { print(paste(a, " from inner function")) print(paste(b, " from inner function")) setwd(wd) }