Re: [R] introduce axis break lattice plot multipanel

[Duncan Mackay]

Hi Luigi

 

If you went down the relation = “free” road you could change the panel widths 
to reflect the scales 

eg if lhs was 1:200 and rhs was 1:100 then the lhs panel would be twice as wide 
as the rhs.

 

I have some code reasonably handy I could send it to you if needed.

 

Regards

 

Duncan

 

From: Luigi Marongiu [mailto:marongiu.lu...@gmail.com] 
Sent: Sunday, 20 December 2015 20:35
To: Duncan Mackay
Subject: RE: [R] introduce axis break lattice plot multipanel

 

thank you duncan,
but in that case the scale of the two panel would be different. i think ill 
keep it as it comes.
best wishes of a merry xmas
luigi

On 19 Dec 2015 13:42, "Duncan Mackay"  wrote:

Hi Luigi

I suppose a cheats way out would be to put

scales = list(alternating = FALSE,
  x = list(relation = "free") ),

Regards

Duncan


Duncan Mackay
Department of Agronomy and Soil Science
University of New England
Armidale NSW 2351
Email: home: mac...@northnet.com.au

-Original Message-
From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Luigi
Marongiu
Sent: Saturday, 19 December 2015 06:32
To: r-help
Subject: [R] introduce axis break lattice plot multipanel

Dear all,
I am plotting some data using lattice's barchart. One of the counts I
am plotting has a very large value with respect to the other variables
and I would like to introduce a break in the axis to compensate for
this 'anomaly' and give more breath to the other bars. In this example
the high count is for the variable 'b' and I would like to introduce a
break of 50-100 in the x axis.
I have seen from the internet that the common approach is to stack
together two figures but in my case I am using a multipanel plot and I
think this way won't work for my plot.
Is there a simple way to introduce a break in the axis of a multipanel
lattice plot?
Thank you
L

the example:
>>>
A <- c('a','b','c','d','a','b','c','d',
'b','c','d','b','c','d')
B <- c(1,1,1,1,1,1,1,1,1,1,1,
  1,1,1)
C <- c(0,0,0,0,1,1,1,1,0,0,0,
  1,1,1)
D <- c(4,120,7,23,4,24,3,12,7,1,
 1,5,0,0)
E <- c(0,0,0,0,0,0,0,0,1,1,1,
  1,1,1)
DF <- data.frame(A, B, C, D, E, stringsAsFactors = FALSE)
library(lattice)
barchart(
A ~ D|E,
DF,
groups = C,
stack = TRUE,
main = "Comparison of test results",
xlab = "Count",
col = c("yellow", "orange"),
par.settings = list(
strip.background = list(col="light grey"),
superpose.polygon=list(col= c("yellow", "orange"))
),
scales = list(
alternating = FALSE
),
key = list(
space="top",
columns=2,
text=list(c("Single infections", "Multiple infections"),
col="black"),
rectangles=list(col=c("yellow", "orange"))
),
)

__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.


[[alternative HTML version deleted]]

__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Re: [R] neuralnet to discriminate a given outcome by giving cutoff outputs

[Giorgio Garziano]

About my previous answer, I should have taken advantage of glm() in place of 
lm(), as the response is binomial.

--
GG


[[alternative HTML version deleted]]

__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

[R] neuralnet to discriminate a given outcome by giving cutoff outputs

[Luigi Marongiu]

Dear all,
I am trying to use neural networks to discriminate positive and
negative outcomes from a test; this outcome is given in the z variable
of the example I am providing. Each outcome is associated with a pair
of variables x and y and I was planning to identify the cut-offs that
could separate the positive from the negative results by splitting the
x/y space into 4 quadrants, the positive results lying in the 2nd
quadrant (the top right). In the example, the two cut-offs for x and y
are indicated with green lines (the values are absolutely subjective),
positive results are in red.
I was thinking of using the neural networks (implemented with the
neuralnet package) to obtain the x and y cut-offs but the returned
weight are off-scale. I tried to increment the number of hidden
neurons, to use more replicates and a maximum number of iteractions
but the results are never optimal.
Since I am completely new in neural networks usage, could you tell me
if the implementation is fine, where could I improve the model and
whether the neural network is the right approach for the problem I
need to solve?
Thank you
L

>>>
x<-c(31.1,32.07,33.01,36.05,17.88,26.91,27.35,
   38.44,35.92,38.08,26.14,40.35,36.12,21.51,
  22.75,37.2,16.94,25.61,25.83,34.73,36.93,
36.02,37.43,36.09,34.74,35.85,16.35,35.25,
26.98,4.74,2.89,40.39,42.18,37.76,2.73,
2.76,2.64,41.94,45,3.78,2.86,45,2.77,
4.61,2.52,42.31,2.92,2.94,3.01,2.61,45,
45,44.54,44.37,36.24,2.11,2,3.97,44.54)
y<-c(0.08,0.054,0.082,0.095,0.135,0.129,0.099,
   0.072,0.091,0.093,0.104,0.077,0.107,0.108,
  0.107,0.088,0.121,0.111,0.069,0.106,0.041,
 0.091,0.054,0.083,0.089,0.086,0.073,0.085,
0.091,0.008,0.018,0,0,0.001,0.002,0.011,
 0.001,0.002,-0.001,0.005,0.011,0.002,0.008,
 0.006,0.006,0.001,0.006,0.003,0.015,0.003,
0.002,0.001,0,0.001,0.002,0.001,-0.001,
0.002,-0.001)
z<-c(1,1,1,1,1,1,1,1,1,1,1,
1,1,1,1,1,1,1,1,1,1,1,1,
 1,1,1,1,1,1,0,0,0,0,0,0,
  0,0,0,0,0,0,0,0,0,0,0,0,
   0,0,0,0,0,0,0,0,0,0,0,
0)
m<-data.frame(x,y,z)
pos <- subset(m, z == 1)
neg <- subset(m, z == 0)
# show points
X <- max(m$x)
Y <- max(m$y)
plot(pos$x, pos$y, pch=1, col="red",
 xlim=c(1,X), ylim=c(0,Y),
 xlab="x", ylab="y", main ="Training dataset",
 sub="Red = positive outcome; Black = negative outcome")
points(neg$x, neg$y, pch=1, col="black")
abline(v=6, lty=2, col="green")
abline(h=0.03, lty=2, col="green")
library(neuralnet)
tnm <- neuralnet(z ~ x + y,
 data=m,
 hidden=1,
 algorithm = "rprop+",
 err.fct = "ce",
 act.fct = "logistic",
 linear.output = FALSE
)
tnm$result.matrix
co.x <- tnm$result.matrix[5]
co.y <- tnm$result.matrix[6]
abline(v=co.x, lty=2, col="blue")
abline(h=co.y, lty=2, col="blue")

__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Re: [R] neuralnet to discriminate a given outcome by giving cutoff outputs

[Giorgio Garziano]

I would tackle the problem in the following way:

lm.model <- lm(z~ x + y, data=m)
summary(lm.model)



Call:

lm(formula = z ~ x + y, data = m)



Residuals:

Min  1Q  Median  3Q Max

-0.34476713 -0.09571506 -0.01786731  0.05225554  0.51693389



Coefficients:

Estimate   Std. Error  t value   Pr(>|t|)

(Intercept) -0.071612058  0.041196651 -1.73830  0.0876543 .

x0.003952998  0.001336833  2.95699  0.0045417 **

y9.968145059  0.461213516 21.61286 < 0.000222 ***

---

Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1



Residual standard error: 0.157775 on 56 degrees of freedom

Multiple R-squared:  0.905464, Adjusted R-squared:  0.9020877

F-statistic: 268.1834 on 2 and 56 DF,  p-value: < 0.00022204


coef.model <- coef(lm.model)

z.hat <- coef.model[1]+coef.model[2]*x+coef.model[3]*y

z.hat.discrete <- rep(1, length(z.hat))
z.hat.discrete[z.hat <0.4] <- 0


> all.equal(z, z.hat.discrete)

[1] TRUE


I apologise for using such naif approach in place of neural net.

--
GG

http://around-r.blogspot.it


[[alternative HTML version deleted]]

__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Re: [R] Help needed in data cleaning

[PIKAL Petr]

Hi

Your question posted in HTML is somewhat scrambled. Based on what I understand 
from it, maybe you shall inspect ?merge.

Cheers
Petr


> -Original Message-
> From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Web Web
> Sent: Friday, December 18, 2015 8:15 PM
> To: r-help@r-project.org
> Subject: [R] Help needed in data cleaning
>
> Hello,
>I need some help in data cleaning using R. my CSV file looks
> as
> follows.
>
> "id","gender","age","category1","category2","category3","category4","ca
> tegory5","category6","category7","category8","category9","category10"1,
> "Male",22,"movies","music","travel","cloths","grocery",2,"Male",28,
> "travel","books","movies",,,3,"Female",27,"rent","fuel","grocery","
> cloths",,4,"Female",22,"rent","grocery","travel","movies","cloths",
> 5,"Female",22,"rent","online-shopping","utiliy",,,
>
> I need to reformat as follows.
>
> id gender age categoryrank1 Male22  movies
>   11 Male22  music21 Male22  travel
>31 Male22  cloths   41 Male22  grocery
> 51 Male22  booksNA1 Male22  rent
>   NA1 Male22  fuel NA1 Male22  utility
>  NA1 Male22  online-shopping  NA
> ...5 Female22  movies
> NA5 Female22  music  NA5 Female22  travel
>NA5 Female22  cloths NA5 Female22  grocery
>   NA5 Female22  books  NA5 Female22  rent
>  15 Female22  fuel   NA5 Female22  utility
>NA5 Female22  online-shopping2
>
> So far My efforts are as follows.
>
> mini <- read.csv("~/MS/coding/mini.csv", header=FALSE)
> mini_clean <- mini[-1,]
> df_mini <- melt(df_clean, id.vars=c("V1","V2","V3"))
> sqldf('select * from df_mini order by  "V1"')
>
> Now I want to know what is the best way to fill all missing categories
> for
> all users.
>
> Thanks
> Nash
>
>   [[alternative HTML version deleted]]
>
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-
> guide.html
> and provide commented, minimal, self-contained, reproducible code.


Tento e-mail a jakékoliv k němu připojené dokumenty jsou důvěrné a jsou určeny 
pouze jeho adresátům.
Jestliže jste obdržel(a) tento e-mail omylem, informujte laskavě neprodleně 
jeho odesílatele. Obsah tohoto emailu i s přílohami a jeho kopie vymažte ze 
svého systému.
Nejste-li zamýšleným adresátem tohoto emailu, nejste oprávněni tento email 
jakkoliv užívat, rozšiřovat, kopírovat či zveřejňovat.
Odesílatel e-mailu neodpovídá za eventuální škodu způsobenou modifikacemi či 
zpožděním přenosu e-mailu.

V případě, že je tento e-mail součástí obchodního jednání:
- vyhrazuje si odesílatel právo ukončit kdykoliv jednání o uzavření smlouvy, a 
to z jakéhokoliv důvodu i bez uvedení důvodu.
- a obsahuje-li nabídku, je adresát oprávněn nabídku bezodkladně přijmout; 
Odesílatel tohoto e-mailu (nabídky) vylučuje přijetí nabídky ze strany příjemce 
s dodatkem či odchylkou.
- trvá odesílatel na tom, že příslušná smlouva je uzavřena teprve výslovným 
dosažením shody na všech jejích náležitostech.
- odesílatel tohoto emailu informuje, že není oprávněn uzavírat za společnost 
žádné smlouvy s výjimkou případů, kdy k tomu byl písemně zmocněn nebo písemně 
pověřen a takové pověření nebo plná moc byly adresátovi tohoto emailu případně 
osobě, kterou adresát zastupuje, předloženy nebo jejich existence je adresátovi 
či osobě jím zastoupené známá.

This e-mail and any documents attached to it may be confidential and are 
intended only for its intended recipients.
If you received this e-mail by mistake, please immediately inform its sender. 
Delete the contents of this e-mail with all attachments and its copies from 
your system.
If you are not the intended recipient of this e-mail, you are not authorized to 
use, disseminate, copy or disclose this e-mail in any manner.
The sender of this e-mail shall not be liable for any possible damage caused by 
modifications of the e-mail or by delay with transfer of the email.

In case that this e-mail forms part of business dealings:
- the sender reserves the right to end negotiations about entering into a 
contract in any time, for any reason, and without stating any reasoning.
- if the e-mail contains an offer, the recipient is entitled to immediately 
accept such offer; The sender of this e-mail (offer) excludes any acceptance of 
the offer on the part of the recipient containing any amendment or variation.
- the sender insists on that the respective contract is concluded only upon an 
express mutual agreement on all its aspects.
- the sender of this e-mail informs that he/she is not authorized to enter into 
any 

Re: [R] Use of "file.choose()" or "change working directory" tab causing stall on Mac

[Robert Baer]

On 12/19/2015 10:39 PM, Vinny Mo wrote:
> Hello,
>
>
> I used to use the "file.choose()" command quite a lot, as well as the "change 
> working directory" drop down tab as part of my workflow with R, but for over 
> 1 year both of these actions have caused the spinning-wheel to crash R (just 
> R, not any other program).
>
>
> The issue seems to happen when the GUI pops up, and happens about 80% of the 
> time I use either of these actions. This issue has remained constant across 
> different computers (though all macs), different R builds, and different Mac 
> OS's. I had asked about this issue before, and had hoped that this bug might 
> be fixed at some point, but it has persisted.
The posting guide asks for a reproducible example.  This is problematic 
if you only have only an 80% failure rate. Nevertheless, do you have a 
verbatim example that has failed at least once?  If a particular 
formulation fails one time for you, does it always fail or can a certain 
syntax work 1 in 5 times?

If this is a mac-only problem you might get more help on that mailing list:
*https://stat.ethz.ch/mailman/listinfo/r-sig-mac***

You should install the most recent version of R and reproduce the 
problem there.  When posting again, it would be helpful to supply the 
results of
R.Version()   for your setup.

>
> I know I can work around this issue programmatically by typing these commands 
> manually, but both of these features represent a nice function that R has 
> that I'd like to continue to use as was intended. Does anyone have any idea 
> how I might be able to get this functionality back, or if the R Gods have any 
> thoughts about addressing this issue?
>
>   [[alternative HTML version deleted]]
>
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.


[[alternative HTML version deleted]]

__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.