search for: 0.1

Hi all, I'm trying to filter data into respective numbers. For example, if the data ranges from 0 to <0.1, group the data. And so on for the rest of the data. There are inconsistencies in the output. For example, b1[[3]] lumps all the 0.2s and 0.3s together while 0.6s are not in the output. Running the function - table(f1) - shows that each of the components/numbers has x number of

Dear R Helpers, I am trying to extract the modulus from divisions by a sequence of fractions. I noticed that %% seems to behave inconsistently (to my untutored eye), thus: > 0.1%%0.1 [1] 0 > 0.2%%0.1 [1] 0 > 0.3%%0.1 [1] 0.1 > 0.4%%0.1 [1] 0 > 0.5%%0.1 [1] 0.1 > 0.6%%0.1 [1] 0.1 > 0.7%%0.1 [1] 0.1 > 0.8%%0.1 [1] 0 > 0.9%%0.1 The modulus for 0.1, 0.2, 0.4 and 0.8 is

Hello, I have a small problem with dovecot 1.0RC2. This didn't happen with former versions. There are imap processes that are left open a long while after the client disconnected. I am running dovecot on OpenBSD 3.8. Below is the output of a process list. As you can see, there are many imap processes for the same login running. simon 11593 0.0 0.1 924 1140 ?? I 12:21PM

Full_Name: Sophie Smout Version: 1.5.0 OS: windows 2000, pc Submission from: (NULL) (138.251.190.17) I'm finding that nls iterates to the end of its iteration setting and does not jump out to report convergence even when it has clearly converged. It is also mis-reporting the number of iterations completed. These may not be unconnected... This is an example: [note - details of my computer,

A user question today has me stumped. Can you advise me, please? User wants a matrix that has some numbers, some variables, possibly even some function names. So that has to be a character matrix. Consider: > BM <- matrix("0.1", 5, 5) Use data.entry(BM) or similar to set some to more abstract values. > BM[3,1] <- "a" > BM[4,2] <- "b" >

CentOS Errata and Security Advisory 2015:1083 Important Upstream details at : https://rhn.redhat.com/errata/RHSA-2015-1083.html The following updated files have been uploaded and are currently syncing to the mirrors: ( sha256sum Filename ) x86_64: 4b27d42a4ed792b8cc8729cc65e6d70a82225000bbad1aa0f002a05582679de2 abrt-2.1.11-22.el7.centos.0.1.x86_64.rpm

Hello there, I am not quite sure how to interpret the output of Rprof (in the following the output I was staring at). I was poking around the web a little bit for documentation but without much success. I guess if I want to figure out what takes so long in my code the 2nd table $by.total and the total.pct column (pct = percent) is the most helpful. What does it mean that [ or [.data.frame is

Given a vector;> ab = seq(0.5,1, by=0.1)> ab[1] 0.5 0.6 0.7 0.8 0.9 1.0 The euclidean distance between the vector elements is given by the lower triangular matrix > dd1 = dist(ab,"euclidean")> dd1    1   2   3   4   52 0.1                3 0.2 0.1            4 0.3 0.2 0.1        5 0.4 0.3 0.2 0.1    6 0.5 0.4 0.3 0.2 0.1 Convert the lower triangular matrix to a full

On 23.11.2012, at 15:12, john skaller <skaller at users.sourceforge.net> wrote: > > On 23/11/2012, at 5:46 PM, Sean Silva wrote: > >> Adding LLVMdev, since this is intimately related to the optimization passes. >> >>> I think this is roughly because some function level optimisations are >>> worse than O(N) in the number of instructions. >>

Hey all, I noticed that my puppet server running CentOS 6.5 was acting a little pokey. So I logged in and did what well just about anyone would've done. And ran the uptime command to have a look at the load. And it was astonishingly high! [root at puppet:~] #uptime 21:28:01 up 1:26, 3 users, load average: 107.37, 72.06, 75.52 So then I had a look at top and saw a LOT of processes

Hello zfs-discuss, One of a disk started to behave strangely. Apr 11 16:07:42 thumper-9.srv sata: [ID 801593 kern.notice] NOTICE: /pci at 1,0/pci1022,7458 at 3/pci11ab,11ab at 1: Apr 11 16:07:42 thumper-9.srv port 6: device reset Apr 11 16:07:42 thumper-9.srv scsi: [ID 107833 kern.warning] WARNING: /pci at 1,0/pci1022,7458 at 3/pci11ab,11ab at 1/disk at 6,0 (sd27): Apr 11 16:07:42 thumper-9.srv

Hi, I need to make a cluster classification by the unique values of the data frame. I explain the problem. I need to classify this table, and assign to the same cluster each row that has the same combination of value: > data1 layer_1 layer_2 layer_3 [1,] 0.2460000000 2 -0.1 [2,] 0.5460000000 3 -0.1 [3,] 0.2460000000 2 -0.1 [4,]

-----Original Message----- From: owner-freebsd-security@freebsd.org [mailto:owner-freebsd-security@freebsd.org] On Behalf Of freebsd-security-request@freebsd.org Sent: Friday, January 11, 2008 3:00 PM To: freebsd-security@freebsd.org Subject: freebsd-security Digest, Vol 236, Issue 1 Send freebsd-security mailing list submissions to freebsd-security@freebsd.org To subscribe or unsubscribe via

Hi All, I recently encountered results that I did not expect, exhibited by the following code snippet: test <- function() { minX <- 4.2 min0 <- 4.1 sigmaG <- 0.1 Diff <- minX-min0 print(c(Diff=Diff,sigmaG=sigmaG)) cat("is Diff > sigmaG?:", Diff > sigmaG,"\n") cat("is (4.2 - 4.1) > 0.1?:",(4.2 - 4.1) >

hi! all, i'm using oidentd-2.0.8 installed through /usr/ports/security/oidentd for ident authentication what puzzled me is when im starting the daemon using the script provided at /usr/local/etc/rc.d/oidentd.sh it will create a lot of process ID and my system will become slow CPU resources will turn upside down rapidly from 90+% idle to always 0% idle this is the PIDs while querying daemon

Hello dear R users! I did not find a function which gives information about the number of digits of a value shown by R. Do you know one? I need it to solve the problem (see RFAQ 7.31)that 0.2==0.2+0.1-0.1 FALSE The solution suggested in RFAQ is to use isTRUE(all.equal(0.2,0.2+0.1-0.1)) But if I want to compare inequality: 0.2<=0.2 +0.1-0.1 TRUE but 0.2<=0.2 +0.1-0.1 FALSE bad! but in

Hi all, my problem is that R does wrong calculations, when the result should be zero. I have the following code: RD_Var1 <- ((0.1*(1-0.1))/100)+((0.2*(1-0.2))/100) RD_Var2 <- ((0.1*(1-0.1))/100)+((0.2*(1-0.2))/100) RD_1 <- 0.1-0.2 RD_1 RD_2 <- 0.1-0.2 FEM_Eff_RD <- ((1/RD_Var1)*RD_1+(1/RD_Var2)*RD_2)/(1/RD_Var1+1/RD_Var2) Q_RD <-

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R-Helpers, I'm sorry to have to ask this -- I've not used R very much in the last 8 or 10 months, and I've gotten rusty. I have the following (ff2 is a subset of a much, much larger dataset): > ff2 hostName user sys idle obsTime 10142 fred 0.4 0.5 98.0 2007-11-01 02:02:18 16886 barney 0.5 0.2 94.6 2007-10-25 19:12:12 8795 fred 0.0 0.1 99.8

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