similar to: Help: Input of form 1 to hidden field in form 2?

Hello, What would be the best set of R functions to parse and transform a file? My file looks as shown below. I would like to plot this data and I need to parse it into a single data frame that sorts of "transposes the data" with the following structure: > df <- data.frame(n=c(1,1,2,2),iter=c(1,2,1,2),step=as.factor(c('Step 1', 'Step2', 'Step 1',

I large datset that includes subjects(ID), Dates and events that need to be counted.  Not every date includes an event, and I need to only count one event per 30days, per subject.  So in essence, I need to create a 30-day "black out" period during which time an event cannot be "counted" for each subject.  The reason is that a rule has been set up, whereby a subject can only be

Help-Rs,   I'm doing some string manipulation in a file where I converted a string date in mm/dd/yyyy format and returned the date yyyy.   I've used regexpr (hat tip to Gabor G for a very nice earlier post on this function) in steps (I've un-nested the code and provided it and an example of what I did below.  My question is: is there a more efficient way to do this.  Specifically is

Dear all, Is there a good way of doing the following conversion: [YYYY]-[MM]-[DD] [Time] [Day] [Name][Integer].[Extention] to become C:\test\[Name]\[YYYY]-[MM]-[DD] [Time] [Day]\[YYYY]-[MM]-[DD] [Time] [Day] [Name][Integer].[Extention] i.e. these 2009-04-10 1400 Fri Foo1.txt 2009-04-10 1400 Fri Universities2.txt 2009-04-10 1400 Fri Hitchhikers Guide To The Galaxy42.txt will become

Hi! Thanks for providing great help in R-related statistics. Now, however I'm stuck. I'm not a statistics person but I was recommended to use R to perform a nmds plot and PerMANOVA of my dataset. Sample(treatment) in the columns and species (OTU) in the rows. I have 4 treatments (Ambient Temperature, Ambient temperature+Low pH, High temperature, High temperature+low pH), and I have 16

Just for fun, I tried to reproduce such an overflow. I turned on all debug macros, assertions, and checked arithmetic and then encoded 2 hours of mixed speech/audio with these parameters: Sample rate = 48000 Channels = 1 Application = OPUS_APPLICATION_AUDIO Bitrate = 24 KB/s Force Mode = MODE_SILK_ONLY Signal Type = OPUS_SIGNAL_AUTO Complexity = 10 Frame size = 480 samples (10ms) No errors came

Hi, Can anyone let me know if this is a bug? Thank you, Chandrakala ----- Original Message ----- From: "Logan Stromberg" <loganstromberg at gmail.com> To: "Chandrakala Madhira" <chandrakala.madhira at soctronics.com> Cc: opus at xiph.org Sent: Wednesday, November 22, 2017 12:12:39 PM Subject: Re: [opus] Reg an issue with smoothing factor in VAD

i have a 2 step form which contains 1 file_column field. The second form is just "This is how your post will look" kind of form and the user can click Edit (to take them back to form1) or Submit. If the user clicks edit it takes them back to the first form with fields populated. I have it working with all text fields, I just dont know how to do this with file_column field (showing the

Dear users, I'm working on binary classification problem using Support Vector Machines (SVM). My objective is to train a series of SVM models on a grid of hyperparameters and then select those that maximize the AUC based on an independent validation sample. My attempted code is shown below. It runs well on "small" data sets but when I use it on a slightly larger sample (e.g., my

Hello, I have a rather complex problem... I will have to explain everything in detail because I cannot solve it by myself...i just ran out of ideas. So here is what I want to do: I take quotes of two indices - S&P500 and DJ. And my first aim is to estimate coefficients of the DCC-GARCH model for them. This is how I do it: library(tseries) p1 = get.hist.quote(instrument =

Hi Chandrakala, Logan, Can you confirm that the attached patch fixes the overflow problem? Koen, can you confirm the fix makes sense? Cheers, Jean-Marc On 11/27/2017 12:10 PM, Logan Stromberg wrote: > Sorry, long holiday weekend in America. > I can say with pretty high certainty that there is an overflow occurring > and it is flipping smooth_coef_Q16 to be negative when it probably

Hi Jim. I'm doing custom lowering but here I have a very basic issue and the situation is like this - [Original Op] Mul Dest, Src1, Src2 [Expanded from EmitInstrWithCustomInserter] Step1 Dest, Src1, Src2    <=== BuildMI(..., Step1, Dest).addReg(Src1).addReg(Src2) Step2 Dest, Src1, Src2    <=== BuildMI(..., Step2, Dest).addReg(Src1).addReg(Src2) Step3 Dest, Src2, Src1    <===

If you're able to reproduce the infinite loop with -O3 then you should be able to dump out the IR that causes `opt -instcombine` to infloop, unless the bug is truly esoteric (e.g. only caused by a specific use-list ordering). Maybe take a closer look at the output from `opt -print-before-all -O3`? Alternatively you can use bugpoint to minimize the IR to get a small reproducer that causes

step 1 [Image: http://www.gimptr.com/gimptribay/step1.png ] step2 [Image: http://www.gimptr.com/gimptribay/step2.png ] What can i do?

Hi, I am trying to understand why some of my call transfers fail. My scenario is as follows: Legacy PBX1 ---PRI (EuroISDN) Zaptel--- Asterisk PBX2 Step1: PBX1 extension 101 calls PBX2 extension 102 Step2: PBX2 extension 102 answers the call and transfers it to PBX1 extension 103 Step3: PBX1 extension 103 answers the call and transfers it to PBX2 extension 104 Step3 fails and extension 103

Hello list, I've got a question from reading Using Samba 3rd, where it puts: ... the final permission is caculated by below filters in the order used by Samba: 1. Apply any DOS attribute mapping options << I take this as either map DOS attributes to execute bits, or store DOS attributes in extended attributes. Correct? 2. Apply the create mask settings 3. Apply the force

Hi All, When we run the command : summary ( newmod<-gam(Dlq~ formula,family,,data) ) in R, the output would the effect of smoothness in R. As of now to calculate the probability I am following the below approach: 1) Run the plot of the GAM , interpret the curves 2) Re Run the Regression as a GLM after taking into account the non linear terms in step1 3) Calculate the probability from

Hello All, I have a data frame (dput information below) with food item weight for fish species. I need to calculate the Mean proportion by weight of each food item for each specie, as show in solution data frame (dput information below). I use the ddply function (plyr package) in two steps. First calculate the proportion of weight for each individual: step1 = ddply (example, .(ID), transform,

Here is a patch to add colour to build output (make) for LLVM sources. Feedback and ideas welcome. The patch replaces $(Echo) usage in some key rules in Makefile.rules with $(Banner) which invokes a new script utils/make-banner.sh which is capable of adding appropriate ANSI escape sequences. step1: apply patch step2: chmod 755 utils/make-banner.sh step3: export MAKE_BANNER_ANSI=1 Next, you must

myDF: d1 d2 d3 d4 d5 -0.166910351 0.022304377 -0.00825924 0.008330689 -0.000925938 -0.166910351 0.022304377 -0.00825924 0.008330689 -0.000925938 -0.166910351 0.022304377 -0.00825924 0.008330689 -0.168225938 -0.166910351 0.022304377 -0.00825924 0.008330689 -0.168225938 -0.166910351 0.022304377 -0.00825924 0.008330689 -0.168225938 -0.166910351