search for: contrivance

Maybe there is a great website out there or white paper that discusses this but again my Google skills (or lack there of) let me down. I would like to know the best way to export several doubles from a function, where the doubles are not an array. Here is a contrived function similar to my needs: multipleoutput<-function(x) { squared<-x^2 cubed<-x^3 exponentioal<-exp(x)

This is admittedly a contrived example, but... data(housing, package ="MASS") x <- housing$Type + housing$Sat match(x, unique(x)) Hadley -- http://had.co.nz/

I apologize but that is what I meant by black box. The Samba3 server is our server. It connects to the LDAP that is out of my control and extends the users' entries to the Windows desktops. If it's easier to visualize we're getting LDAP as a service from the central campus IT department. It is then on us to provide services our school needs to our students, faculty and staff. They

I am testing 'qr' with an admittedly contrived matrix and I am getting different results than I am from another package. The matrix that I am using is: x <- matrix(seq(.1, by=.1, length.out=12), 4) So the whole test is: x <- matrix(seq(.1, by=.1, length.out=12), 4) qr(x) And the output from 'R' is: $qr [,1] [,2] [,3] [1,] -0.5477226 -1.2780193

I have the following contrived code in package format. On Solaris and Mac OS X, code runs just fine. On Windows, it crashes the R environment with the "Send Bug Report" dialog. I tried R 1.8.1 (Win2K) and R 1.9 (WinXP) binaries with the same result. PCs otherwise appear properly configured for creating R packages. Anything blatantly wrong? Suggestions? TIA Relevant files from package

On 3/12/2013 9:56 PM, Shuxin Yang wrote: > Based on my understanding of her design, following is one obtuse > motivating example: > > -------------------------- > class A; > class B; > > int foo(A* p, B* q) { > > p->a_int_field = 2; > q->another_int_field = 3; > return p->a_int_field; // !!!!! > } > ----------------------------------

After *much* digging and playing around, I finally figured out how to unit test instance variables that are created by actions. It was more difficult than I expected. It seems like there should have been a more straight forward way to do this. Can someone enlighten me? A simplified and somewhat contrived example of what I am current doing: Thanks. Matt >> # My Controller of interest

On Sep 26, 2008, at 8:41 AM, David Greene wrote: > On Thursday 25 September 2008 13:15, David Greene wrote: > >> My patch builds a map from BasicBlock to lists of loads and stores >> in that >> block in an initialization phase along with ordering information >> about the >> loads and stores. RewriteSingleStoreAlloca then queries that >> information

Based on my understanding of her design, following is one obtuse motivating example: -------------------------- class A; class B; int foo(A* p, B* q) { p->a_int_field = 2; q->another_int_field = 3; return p->a_int_field; // !!!!! } ---------------------------------- the *-statement can be optimized into "return 2" if optimizer can prove type-A does not include

Having a memory issue with Gluster 3.12.4 and not sure how to troubleshoot. I don't *think* this is expected behavior. This is on an updated CentOS 7 box. The setup is a simple two node replicated layout where the two nodes act as both server and client. The volume in question: Volume Name: GlusterWWW Type: Replicate Volume ID: 8e9b0e79-f309-4d9b-a5bb-45d065faaaa3 Status: Started Snapshot

I would like to replace a few varaibles within a data frame. For example, in the dataframe below (contrived) I would like to replace the current housesize value only if the Location is HSV. However, I would like to leave the other values intact. I tried "ifelse", but I don't really need the else condition. test_data2_df<-data.frame(Variables=c("SQR

Hi all, I am having trouble extending S4 classes in cases where I'm using both validity and initialize methods. I've read as much S4 information as I can find, but I've yet to have that "a-ha" moment. In my application, I am using validity methods to guard against inappropriate input data that my code has no way of handling, and initialize methods to detect and deal

While I''m happy to continue talking about the vagaries of Rails deployments, I also need to actually build apps. :) I may have discovered a bit of a problem with :include as it applies to has_one associations. First, let me say that I''m a big fan of :include for reducing the number of SQL calls. There are times when I wish it could go more than 1 step away from the parent

Fellow R-helpers, Suppose we create a histogram as follows (although it could be any vector with zeroes in it): R> lenh <- hist(iris$Sepal.Length, br=seq(4, 8, 0.05)) R> lenh$counts [1] 0 0 0 0 0 1 0 3 0 1 0 4 0 2 0 5 0 6 0 10 0 9 0 4 0 [26] 1 0 6 0 7 0 6 0 8 0 7 0 3 0 6 0 6 0 4 0 9 0 7 0 5 [51] 0 2 0 8 0 3 0 4 0 1 0 1 0 3

*sigh* trying again to correct formatting ... apologize for the earlier mess. Having a memory issue with Gluster 3.12.4 and not sure how to troubleshoot. I don't *think* this is expected behavior. This is on an updated CentOS 7 box. The setup is a simple two node replicated layout where the two nodes act as both server and client. The volume in question: Volume Name: GlusterWWW Type:

Hi, I found a bug in the code that generates exception tables, I've attached what I think is the correct fix. When you run out of space writing to a buffer, the buffer management code simply stops writing at the end of the buffer. It is the responsibility of the caller to verify that it has stayed in bounds and perform a retry with a larger memory estimate if not. The function writing code

Dear All, The attached code (which is a contrived test case) hits the following assertion: test: /home/vadve/criswell/src/llvm22/include/llvm/PassAnalysisSupport.h:226: AnalysisType& llvm::Pass::getAnalysisID(const llvm::PassInfo*, llvm::Function&) [with AnalysisType = Pass1]: Assertion `ResultPass && "getAnalysis*() called on an analysis that was not "

Here is a problem I am having. I would sincerely appreciate any help/advice from the experts who read this list. I have contrived a simple example, but it gives the same result I encountered in a more complicated application. Given data frame u: x y 31 19 32 18 33 17 34 16 35 15 36 14 37 13 I define the function f as follows: f <- function(a,b) sum(u$x - a) + sum(u$y - b) One might think

On 01/25/2018 11:04 PM, Dan Ragle wrote: > *sigh* trying again to correct formatting ... apologize for the > earlier mess. > > Having a memory issue with Gluster 3.12.4 and not sure how to > troubleshoot. I don't *think* this is expected behavior. > > This is on an updated CentOS 7 box. The setup is a simple two node > replicated layout where the two nodes act as

-----Original Message----- From: Dirk Eddelbuettel [mailto:dirk.eddelbuettel at gmail.com] On Behalf Of Dirk Eddelbuettel Sent: Thursday, 19 January 2017 12:41 PM To: Klint Gore Cc: Dirk Eddelbuettel; r-sig-debian at r-project.org Subject: RE: [R-sig-Debian] Taking determinant of a matrix of NAs results in intermittent memory corruption On 19 January 2017 at 01:26, Klint Gore wrote: | >So