Wrong list. Do _read_ the Posting Guide and then check out r-sig-geo.
On June 1, 2020 5:18:49 PM PDT, Lom Navanyo wrote:
>Hello,
>I have data set of about 3400 location points with which I am trying to
>generate data of each point and their neighbors within defined radii
>(eg,
>0.25, 1, and 3 mil
Hello,
I have data set of about 3400 location points with which I am trying to
generate data of each point and their neighbors within defined radii (eg,
0.25, 1, and 3 miles).
Below is a reprex using the built-in nz_height data:
library(sf)
library(dplyr)
library(spData)
library(ggplot2)
librar
Hi Jim,
not in this case, but thanks for asking!
Ana
On Mon, Jun 1, 2020 at 10:04 PM Jim Lemon wrote:
>
> So recombination sticks out its foot before us. Do you want to account
> for gene linkage?
>
> JIm
>
> On Tue, Jun 2, 2020 at 11:55 AM Ana Marija
> wrote:
> >
> > Hi Jim
> >
> > > neu3<-n
It might be easier to diagnose if you can show us what the first ten lines
in your original file look like.
readLines("gokind.nephropathy.fin", n=10)
David L Carlson
On Mon, Jun 1, 2020 at 6:36 PM Bert Gunter wrote:
> Agreed!
>
> However, there may still be a problem, as read.table() ordinari
So recombination sticks out its foot before us. Do you want to account
for gene linkage?
JIm
On Tue, Jun 2, 2020 at 11:55 AM Ana Marija wrote:
>
> Hi Jim
>
> > neu3<-neu1[!(neu1$Marker %in% Marker3),]
> > dim(neu3)
> [1] 18579
> > nep3<-nep1[!(nep1$Marker %in% Marker3),]
> > dim(nep3)
> [1]
Hi Jim
> neu3<-neu1[!(neu1$Marker %in% Marker3),]
> dim(neu3)
[1] 18579
> nep3<-nep1[!(nep1$Marker %in% Marker3),]
> dim(nep3)
[1] 55629
> ret3<-ret1[!(ret1$Marker %in% Marker3),]
> dim(ret3)
[1] 34939
If I do:
nn1<-merge(neu1,nep1,by=c("Marker","Chr"))
nn2<-merge(nn1,ret1,by=c("Ma
Hi David,
that is a great point!
Yes indeed some are non unique:
> dim(neu1)
[1] 3742845 9
> length(unique(neu1$Marker))
[1] 3741858
> length(unique(nep1$Marker))
[1] 3745560
> dim(nep1)
[1] 3746550 9
> length(unique(ret1$Marker))
[1] 3743494
> dim(ret1)
[1] 3743494 9
How would
Hi Ana,
If I add another 6 rows to neu1, 2 to nep1 and one to ret1 and modify
the "Marker" field so that there is one more match, I get the result I
expect. I think that the program logic is correct. I can't say why
ret1 has fewer lines. If there aren't too many mismatches, maybe
checking the misma
On 6/1/20 5:40 PM, Ana Marija wrote:
Hi Jim,
thank you so much for getting back to me. I tried your code and this is
what I get:
dim(neu2)
[1] 3740988 9
dim(nep2)
[1] 3740988 9
dim(ret2)
[1] 3740001 9
I think I would need to have the same number of lines in all 3 data
Dear Ana and Jim,
On 2020-06-01 19:40 -0500, Ana Marija wrote:
> > dim(neu2)
> [1] 3740988 9
> > dim(nep2)
> [1] 3740988 9
> > dim(ret2)
> [1] 3740001 9
Jim's code works out of the box directly from
the email ... I get:
[1] 6 9
[1] 4 9
[1] 4 9
On 2020-06-01 19:40 -0500, Ana M
Hi Jim,
thank you so much for getting back to me. I tried your code and this is
what I get:
> dim(neu2)
[1] 3740988 9
> dim(nep2)
[1] 3740988 9
> dim(ret2)
[1] 3740001 9
I think I would need to have the same number of lines in all 3 data frames.
Can you please advise.
Cheers
A
Hi Ana,
Not too hard, but your example has all the "marker" fields in common.
So using a sample that will show the expected result:
neu1<-read.table(text="Chr BP Marker MAF A1 A2 Direction pValue N
1 10012 1:10012:G:T 0.229925 T G + 0.650403 1594
1 10827 1:10827:C:T 0.287014
Agreed!
However, there may still be a problem, as read.table() ordinarily would
read numeric columns correctly (via type.convert()) without the colClasses
specification.
So I would suspect that her "numeric" columns contain some non-numeric
detritus (perhaps "," or some NA symbol). But of course,
Good morning Bruce & Abby,
The fruit bats of Sydney have retreated to their camps so I can
finally answer your last two queries. Attached is a plot of your data
set on a 100 x 100 grid. This is how I did it:
bfs<-read.csv("Procen_sample.csv")
dim(bfs)
names(bfs)
library(plotrix)
# set the matrix l
On 6/1/20 2:17 PM, Ana Marija wrote:
> HI David,
>
> this is the problem:
>
> > NEP <- read.table("gokind.nephropathy.fin",
> header=T,stringsAsFactors=FALSE)
> > sapply(NEP,class)
> Chr BP Marker MAF A1 A2
> "character" "character" "character" "char
Hello,
I have 3 data frames which have about 3.4 mill lines (but they don't have
exactly the same number of lines)...they look like this:
> neu1=neu[order(neu$Marker),]
> head(neu1)
ChrBP Marker MAF A1 A2 Direction pValueN
209565 1 10012 1:10012:G:T 0.
HI David,
this is the problem:
> NEP <- read.table("gokind.nephropathy.fin",
header=T,stringsAsFactors=FALSE)
> sapply(NEP,class)
Chr BP Marker MAF A1 A2
"character" "character" "character" "character" "character" "character"
Direction pValue
On 6/1/20 1:37 PM, Ana Marija wrote:
Hello,
I have a dataframe like this:
ChrBP Marker MAF A1 A2 Direction pValueN
1 10 10625 10:10625:A:G 0.416562 G A - 0.558228 1594
2 10 10645 10:10645:A:C 0.215182 C A - 0.880622 1594
..
7th fileld, Direction contains only "+" and "-"
On Mon, Jun 1, 2020 at 3:46 PM Bert Gunter wrote:
> I count 8 fields in your data and 9 names in your heading ??
>
>
> Bert Gunter
>
> "The trouble with having an open mind is that people keep coming along and
> sticking things into it."
> -- Opus
I count 8 fields in your data and 9 names in your heading ??
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Mon, Jun 1, 2020 at 1:38 PM Ana Marija
wrote:
>
Hello,
I have a dataframe like this:
ChrBP Marker MAF A1 A2 Direction pValueN
1 10 10625 10:10625:A:G 0.416562 G A - 0.558228 1594
2 10 10645 10:10645:A:C 0.215182 C A - 0.880622 1594
...
which I load with:
NEU <- read.table("g
Please move this discussion to R-package-devel.
On June 1, 2020 12:43:01 PM PDT, Adelchi Azzalini
wrote:
>
>
>> On 1 Jun 2020, at 21:35, Sorkin, John
>wrote:
>>
>> Regardless of whether the people who wrote the Matlab code you used
>as a reference, or who wrote the paper that published the ide
> On 1 Jun 2020, at 21:35, Sorkin, John wrote:
>
> Regardless of whether the people who wrote the Matlab code you used as a
> reference, or who wrote the paper that published the idea that you included
> in your package are cited as co-authors of your package, the coders and
> authors shoul
Regardless of whether the people who wrote the Matlab code you used as a
reference, or who wrote the paper that published the idea that you included in
your package are cited as co-authors of your package, the coders and authors
should be identified as the people from whom you borrowed the idea
> On 1 Jun 2020, at 19:37, Michael Dewey wrote:
>
> You might get better answers on the list dedicated to package development
> r-pkg-devel
This is a good suggestion. Thanks, Michael.
Some initial search of that list did not lead to any indication,
but I will have a second look.
Best re
Hi,
I'm probably biased.
But my package, bivariate, contains a wrapper for KernSmooth::bkde2D,
which can produce both 3D surface plots and (pretty) contour plots of
bivariate kernel density estimates, conveniently.
https://cran.r-project.org/web/packages/bivariate/vignettes/bivariate.pdf
(pages
Dear R users, with some delay I would like to make you aware of the recent
CRAN release of *collapse* (https://CRAN.R-project.org/package=collapse), a
large new C/C++ based package for advanced and high-performance general
purpose data transformation in R.
*collapse* has 2 main objectives:
1. To
You might get better answers on the list dedicated to package
development r-pkg-devel
This may have already been discussed there so a quick look at the
archive might also help you.
On 01/06/2020 17:34, Adelchi Azzalini wrote:
The new version of a package which I maintain will include a new f
The new version of a package which I maintain will include a new function which
I have ported to R from Matlab.
The documentation of this R function indicates the authors of the original
Matlab code, reference to their paper, URL of the source code.
Question: is this adequate, or should I includ
You can read it in as 'raw'
input <- file('your.xlsx', open = 'rb') # open as binary
excel_file <- readBin(input, raw(), 1e8) # make sure you read in all the file
close(input)
output <- file('your_new.xlsx', 'wb')
writeBin(excel_file, output)
close(output)
===
Jim
You might check that n %% 1 == 0.
(Factorials do exist for fractional numbers -- check e.g. factorial(6.5). And
please don't send HTML because, well, you can see the result below)
- pd
> On 1 Jun 2020, at 12:49 , Vahid Borji wrote:
>
> I am writing a code for the factorial function. My code i
I am writing a code for the factorial function. My code is as follows:
> f<- function(n){+ factorial <- 1+ if( n < 0 )+ print("Factorial of negative
> numbers is not possible")+ else if( n == 0 )+ print("Factorial of 0 is 1")+
> else {+ for(i in 1:n)+ factorial <- factorial * i+ print(paste("Fac
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