search for: counterintuitively

I was implementing dirty checking for an application, and I found something that is a little counterintuitive. Let me start with a quick quiz: bob=User.find(1) alice=User.find(2) trip=Trip.new trip.driver=bob old_driver=trip.driver trip.driver=alice In this example, who is old_driver? If you guessed Alice, you''re right. Inside associations.rb, the mutator is defined as:

Hi, I stumbled across the following: > /* Builds a module from the bitcode in the specified memory buffer, > returning a > reference to the module via the OutModule parameter. Returns 0 on success. > */ > LLVMBool LLVMParseBitcode2(LLVMMemoryBufferRef MemBuf, > LLVMModuleRef *OutModule); However in most scenarios i know, a Bool is something like 0 = False !0 = True In short:

Of course, this is normal for C-APIs. But maybe change the name to LLVMResult to propagate the real use? I am not arguing about the results themself. They are standard. But the name is missguiding. As long as it's consistent i know that i have to write an extra record operator in Delphi to reflect this. 2016-09-12 11:11 GMT+02:00 David Chisnall <David.Chisnall at cl.cam.ac.uk>: > On

Okay after translating the headers to Delphi, i found more inconsistencies: > LLVMTypeRef LLVMFunctionType(LLVMTypeRef ReturnType, > LLVMTypeRef *ParamTypes, unsigned ParamCount, > LLVMBool IsVarArg); > In this case it is the other way around. 0 means False and anything else means true :/ (so it acts more like a

I wonder if someone can help me understand some counterintuitive simulation results. Below please find 12 lines of R code that theoretically, to the best of my understanding, should produce essentially a flat line with no discernable pattern. Instead, I see an initial dramatic drop followed by a slow rise to an asymptote. The simulation computes the mean of 20,000 simulated trajectories

Hello, I wonder if I ran into a bug. If I do summary(df1$X1) -> df1.y df1.y a b c d e [1,] 50.74627 8.955224 17.91045 19.40299 2.985075 sort(df1.y) a b c d e [1,] 2.985075 8.955224 17.91045 19.40299 50.74627 my numbers are sorted but do not anymore correspond to the rownames. For me it is counterintuitive that solely the numbers are sorted and not the names. Is

Hi, I bumped into the following this afternoon (on a 2.7.19 puppet master/agent combo): consider a class profile::tomcat in module profile with the following content: $ cat modules/profile/manifests/tomcat.pp class profile::tomcat { class { ''tomcat'': } notice(''Class profile::tomcat in module profile'') } and $ cat modules/tomcat/manifests/init.pp

Hello here. I'm struggling to understand R's subsetting behavior in couple of edge cases - subsetting row in a single column matrix and subsetting column in a single row matrix. I've read R's docs several times and haven't found answer. Consider following example: a = matrix(1:2, nrow = 2, dimnames = list(c("row1", "row2"), c("col1"))) a[1, ] # 1

On 2015-03-02 2:02 AM, Jochen Bern wrote: > On 03/01/2015 08:53 AM, Jim Pazarena wrote: >> I wonder if there is an easy way to provide dovecot a flat text file of >> ipv4 #'s which should be ignored or dropped? >> >> I have accumulated 45,000+ IPs which routinely try dictionary and >> 12345678 password attempts. The file is too big to create firewall >>

It was recently pointed out by Wacek Kusnierczyk that although one is prevented from doing FALSE <- TRUE one *can* do assign("FALSE",TRUE) and have an object named ``FALSE'' with value TRUE in one's workspace. This apparently has no deleterious effects; e.g. doing sample(1:7,replace=FALSE) gives a random permutation of 1:7 as expected and desired. I.e. the local

On Thu, Aug 20, 2020 at 6:54 PM Christoph Hellwig <hch at lst.de> wrote: > > On Thu, Aug 20, 2020 at 12:05:29PM +0200, Tomasz Figa wrote: > > The UAPI and V4L2/videobuf2 changes are in good shape and the only > > wrong part is the use of DMA API, which was based on an earlier email > > guidance anyway, and a change to the synchronization part . I find > >

Dmitriy Selivanov (selivanov.dmitriy at gmail.com) wrote: > Consider following example: > > a = matrix(1:2, nrow = 2, dimnames = list(c("row1", "row2"), c("col1"))) > a[1, ] > # 1 > > It returns *unnamed* vector `1` where I would expect named vector. In fact > it returns named vector when number of columns is > 1. > Same issue applicable

Thanks for the clarification. The `except` seemed dangling to me, but it's early here. Just curious... how do we end up with a mixed type BUILD_VECTOR? That's counterintuitive. On Tue, Jul 7, 2020 at 10:58 AM Krzysztof Parzyszek via llvm-dev <llvm-dev at lists.llvm.org> wrote: > > Mixed integer types are ok, but the values will get truncated to the element type of the output

Dear, I have noticed this problem while looking at the following question on Stackoverflow : http://stackoverflow.com/questions/42894213/s4-class-subset-inheritance-with-additional-arguments While going through callNextMethod, I've noticed the following odd behaviour: mc <- call("[",iris,2,"Species") mc[[1]] ## `[` is.primitive(`[`) ## [1] TRUE

Hello all, We have put a DNS server online running DJBDNS v1.06 (ndjbdns-1.06-1.el6.x86_64) on a 64-bit CentOS 6.6 server. We have done some limited testing on the machine which it passed - i.e., dnscache was talking to tinydns, the queries went through fine, etc. As soon as we put it online subjecting it to live load the following happened: 1) Within a short time period (about a minute) the

Dear R-devs, I'm working on a package where we have a function that modifies an Object via .Call to a C function. Unfortunately in some situations this counterintuitive modifies a previously made copy of the object passed to the function. For example, if I first make an assignment to "copy" the object, b<-a and then modify 'a' , the value of 'b' will be

Dear all, I have a dataset where the interaction is more than obvious, but I was asked to give a p-value, so I ran a logistic regression using glm. Very funny, in the outcome the interaction term is NOT significant, although that's completely counterintuitive. There are 3 variables : spot (binary response), constr (gene construct) and vernalized (growth conditions). Only for the FLC construct

All, Currently the X86 backend does CPU auto-detection and subtarget feature detection when the TargetMachine is created if no explicit CPU was specified. It's counterintuitive for low level tools like ‘llc’ to do this, as it means the same .ll file compiled on heterogenous machines generates different results from the same ‘llc’ command line. It is still useful to be able to opt-in to such

Hi Rui. Thanks for answer, I'm aware of drop = FALSE option. Unfortunately it doesn't resolve the issue - I'm expecting to get a vector, not a matrix . ??, 21 ????. 2018 ?. ? 20:54, Rui Barradas <ruipbarradas at sapo.pt>: > Hello, > > Use drop = FALSE. > > a[1, , drop = FALSE] > # col1 > #row1 1 > > > Hope this helps, > > Rui Barradas

When trying out some variations with `[.data.frame` I noticed some (to me) odd behaviour, which I found out has nothing to do with `[.data.frame`, but rather with the way arguments are matched, when mixing named/unnamed and missing/non-missing arguments. Consider the following example: myfun <- function(x,y,z) { ? print(match.call()) ? cat('x=',if(missing(x)) 'missing'