search for: parameterisable

I downloaded the latest version of puppet 2.6.0 today, and still can''t get parameterised classes to work. At least, I think it''s 2.6.0... the version number in the RPM spec file says 0.25.5. This simple example: /etc/puppet/manifests/nodes/pax/name01.pax.xxx.com.pp: node ''name01.pax.xxx.com'' { class { amodule::afunc: version => "1.0" } }

Hi Puppet Users, For some bizzare reason I am unable to use hiera-puppet with a parameterised class. The output is: ---------------------------- root@hiera hieratest/manifests# puppet apply -e "include hieratest" Error: undefined method `catalog'' for #<Hash:0xb6c53d00> at line 1 on node hiera.localdomain Wrapped exception: undefined method `catalog'' for

Dear R users, I am struggling to fit expo-linear equation to my data using "nls" function. I am always getting error message as i highlighted below in yellow color:  Theexpo-linear equation which i am interested to fit my data:       response_variable =  (c/r)*log(1+exp(r*(Day-tt))), where "Day" is time-variable my response variable rl <-

Dear R-users, I am facing a trivial problem when trying to parameterise the start date of a time series object. I am working with monthly data (104) performing n-steps-ahead (6) forecasts and using a fixed window size (36). At the end of calculations I have a list that contains 69 forecasts. I have no problems in fixing the window size by parametrization, e.g. k<- control variable in a for

I posted last week regarding a bug in the way that smb was re-reading our config files every 60 seconds even though the files were not changing. As a result we had 396 smbd processes trying to read three files at the same moment with the obvious load average. The reason that all the smbd's were running at the same moment is because the smbd's read the config files every 60 seconds

Hi All, I am trying to use a neural network for my work, but I am not sure about my approach to select a parsimonious model. In R with nnet, the IAC has not been defined for a feed-forward neural network with a single hidden layer. Is this because it does not make sens mathematically in this case? For example, is this pseudo code sensible? Thanks in advance for your help. I am sorry if this

Hello, I have a 2 factor linear model, in which the only terms I am interested in estimating and testing are the interaction terms. I want to control for the main effects but have no interest in estimating or testing them. However, I would like an estimate of the interaction effects for every level of the interactions, whereas what I get is one fewer estimate than this, with the first level

I'm maximising a reasonably complex function using nlme (version 3.1-65, have also tried 3.1-66) and am having trouble with fixed parameter estimates slightly away from the maximum of the log likelihood. I have profiled the log likelihood and it is a parabola but with sum dips. Interestingly changing the parameterisation moves the dips around slightly. Unfortunately the PNLS step is

I sent a post to find a clever way to compute a Rolling Average of columns in a matrix and I was given the solution below which I am very pleased with. RollingAverage <- function(x, RollingObs) { cx <- cumsum(x); N <- length(x); Temp <- (cx[RollingObs:N] - c(0, cx[1:(N-RollingObs)]))/RollingObs Output <- array(NA, N) Output[RollingObs:N] <- Temp; Output } The only

I'm fairly new to LLVM, and am writing an optimisation pass to be run by 'opt'. However, i'd like this pass to be parameterisable; as such i'd like to be able to pass an option to it (preferably via the command line to 'opt'). e.g. so i can do something like this "opt -load mypass.so -MyPass=MyPassOption < inputfile.bc ..." (for example one thing I would like to do is pass a list of function names t...

> From: Peter Collingbourne [mailto:peter at pcc.me.uk] > Sent: 20 December 2010 20:11 > As with __local variables, it may be that "kernelness" cannot be > represented in a standard form in LLVM. For example on a CPU a > kernel function may have an additional parameter which is a pointer to > __local memory space, which would not be necessary on GPUs. Then in >

i have: class Library << ActiveRecord::Base has_many :books end class Book << ActiveRecord::Base belongs_to :library end in my controller i have: render :xml=> Library.find(:all).to_xml(:include=>books) but, i would like put a condition in the books ( e.: pages >= 100 ) i would like to create a xml with all Libraries, but books with pages more than 100) How to

Hi, I have been trying to improve the coding of some of my puppet recipes and had some trouble so wrote this: http://blog.wl0.org/2011/05/thoughts-about-extlookup-in-puppet/ Comments on the web seem to indicate that extlookup() solves "all problems" but I don''t really see that and hence have proposed a possible way to keep the data closer together and make the extlookup()

Hi - I''ve just started working with Rails, having come from a Cold Fusion background. I''m curious how best to deal with a huge result set. For example, I''m building an app that contains users. I''ve used scaffolding to setup my initial pages for CRUD operations on users. All that is great. The problem is, I''m going to end up with 1000+ users in

Hi all, I'm currently writing some unit tests for some debug line error handling code I'm working on (see e.g. https://reviews.llvm.org/D44382), and I just ran into an annoying disabled feature in gtest, specifically the "Combine" feature for use in combinatorially generating parameterised tests. A FIXME comment in ProfileData\CoverageMappingTest.cpp suggests that I'm not

Hi, I wish to simulate some data from a Weibull distribution. The rweibull function in R uses the parameterisation 'with shape parameter a and scale parameter b has density given by f(x) = (a/b) (x/b)^(a-1) exp(- (x/b)^a)'. However, it would be much more useful for me to simulate data using a different parameterisation of the Weibull, with shape a1 and scale b1, namely f(x) =

Hi R-fellows, can anyone explain this weird feature? I am trying to create a list of functions with apply, and it appears that there is something strange going on when the function evaluates the argument a. When I duplicate a into a local variable b, the result changes !?! Any pointers? Thank in advance. Cheers, Uffe # Create a function which returns a function > f1 <- function(a)

Hi, I was wondering if someone could please help me. I am doing a logistic regression to compare size at maturity between 3 seasons. My model is: fit <- glm(Mature ~ Season * Size - 1, family = binomial, data=dat) where Mature is a binary response, 0 for immature, 1 for mature. There are 3 Seasons. The Season * Size interaction is significant. I would like to compare the size at 50%

Paul Wayne, Kevin, Teodor and others, Thanks for your contributions in response to my postings. Paul: I was very imprecise if not plain wrong in my description. :-( Thanks for explaining what really happens. > "Rsync will not update an existing file in-place unless you use the > --inplace option. So --whole-file is irrelevant for this. > Rsync (without --inplace) will always

+Chandler who might have some thoughts on this. Could you provide an example here of the motivation for the feature you're missing? Might help motivate the discussion (and/or we'll end up nitpicking how it could be done differently without that feature... - which is sort of where I'm going with this. Combinatorial test case expansion does seem a bit suspicious to me - I'd hope we