GUI가 포함 된 R 패키지 작성

Question

기본적으로 빌드하고, IC50 값을 예측하고 예측하는 데 사용되는 R 코드가 있습니다. 작동하는 GUI가 있습니다.

# Load the packages 
library(gWidgets) 
library(gWidgetsRGtk2) 
library(tcltk) 
library(data.table) 
library(cluster) 
library(e1071) 
library(caret) 
options(guiToolkit="RGtk2") 

#main GUI code 
win=gwindow("Naive Bayes Tool for IC50 Prediction") 
size(win)<-c(1000,600) 
group<-ggroup(cont=win) 
left_group<-ggroup(cont=group,horizontal=FALSE) 
right_group<-ggroup(cont=group,horizontal=FALSE) 
txtOutput = gtext("", cont = group, expand = TRUE) 
frame<-gframe("Bankruptcy Tool",cont=left_group,horizontal=FALSE,) 
# size(frame)<-c(300,350) 
tbl=glayout(cont=frame) 
# To Browse the file 
tbl[2,1] = gfilebrowse (text = "Select Training File...", type = "open", quote = FALSE, 
         filter = list("Text File" = list(patterns = c("*.csv"))), container = tbl) 
tbl[3,1] = gbutton("Upload File",cont=tbl,handler=uploadfile) 
enabled(tbl[3,1]) <- FALSE 

#Function to upload file 
uploadfile<-function(h,...){ 
    bipsdata <- read.csv(svalue(tbl[2,1])) 
    inputdata<-data.frame(bipsdata) 
    normo2<-capture.output(head(inputdata)) 
    str.split <- strsplit(normo2, "\\s+") 
    str.joined <- sapply(str.split,function(bits) paste(bits,collapse='\t')) 
    insert(txtOutput,normo2,font.attr = c(family="monospace")) 
    gmessage("Data Uploaded!!!", color="blue") 
} 
addHandlerChanged(tbl[2,1], handler=function(h,...) { 
    val <-svalue(tbl[2,1]) 
    # data1<-data.frame(val) 
    if(!is.na(val)) { 
    filename <<- val 
    #  df1 = read.csv(filename, header = TRUE) 
    enabled(tbl[3,1]) <- TRUE 
    } 
}) 
addHandlerChanged(tbl[3,1], handler=uploadfile) 
# Creating a frame for prediction of clustering results 
frame3<-gframe("Prediction",cont=left_group,horizontal=FALSE, font.attr=list(style="bold")) 

ARatings<- gbutton("Submit and Build Model",cont=frame3, handler=Arat) 
Enter<-glabel("Enter the Input Data:-",cont=frame3) 

IR1= gedit("AATS3e", cont=frame3,coerce.with=as.numeric) 
MR2= gedit("MATS3c", cont=frame3,coerce.with=as.numeric) 
FF3= gedit("MATS4c", cont=frame3,coerce.with=as.numeric) 
CR4= gedit("MATS3e", cont=frame3,coerce.with=as.numeric) 
CO5= gedit("MATS3s", cont=frame3,coerce.with=as.numeric) 
OP6= gedit("GATS7c", cont=frame3,coerce.with=as.numeric) 
Class1= gedit("Class", cont=frame3) 
Predict<-gbutton("Predict Model", cont=frame3, handler=AratSave) 


# Function to Train Data 
Arat<-function(ARatings,h,...) 
{ 
    library(data.table) 
    library(e1071) 
    bipsdata<-read.csv(filename) 
    inputdata<-data.frame(bipsdata) 
    naive.model<-naiveBayes(Class~.,inputdata,probability=TRUE) 
    result1<-print(naive.model) 
    normo<-data.frame(result1) 
    normo1<-capture.output(naive.model) 
    insert(txtOutput,normo1, font.attr = c(family="monospace")) 
} 

#Function to Predict Bankruptcy 
AratSave<-function(ARatings, h,...) 
{ 
    library(data.table) 
    library(e1071) 
    bipsdata<-read.csv(filename) 
    inputdata<-data.frame(bipsdata) 
    naive.model<-naiveBayes(Class~AATS3e+MATS3c+MATS4c+MATS3e+MATS3s+GATS7c,inputdata,probability=TRUE) 

    AATS3e<-as.numeric(svalue(IR1)) 
    MATS3c<-as.numeric(svalue(MR2)) 
    MATS4c<-as.numeric(svalue(FF3)) 
    MATS3e<-as.numeric(svalue(CR4)) 
    MATS3s<-as.numeric(svalue(CO5)) 
    GATS7c<-as.numeric(svalue(OP6)) 
    Class<-svalue(Class1) 

    Newinput<-data.frame(cbind(AATS3e,MATS3c,MATS4c,MATS3e,MATS3s,GATS7c)) 
    print(Newinput) 
    results<-predict(naive.model,Newinput) 
    result12<-print(results) 
    normo11<-data.frame(result12) 
    normo1<-capture.output(result12) 
    insert(txtOutput,normo1, font.attr = c(family="monospace")) 

    #Comparing Accuracy 
    #code is having error because the predicted result is only one column but the model has many columns. 
    xtab<-table(pred=results,true=svm.model) 
    cofusionMatrix(xtab) 
    y<-print(confusionMatrix(xtab)) 
    normo12<-capture.output(y) 
    insert(txtOutput,normo12, font.attr = c(family="monospace")) 
} 

R 패키지를 만들려고했습니다. 설명 파일에서 라이브러리를 가져 오는 단계를 수행했습니다. 하지만 해결책을 찾을 수 없습니다. 도와주세요. 당신이 gwindow 내가 설명 파일에서 가져 오기 라이브러리에서 호출해야하는 기능입니다 볼 수 있듯이 오류가이

Updating IC50 documentation 
Loading IC50 
Error in eval(expr, envir, enclos) (from IC50.r#7) : could not find function "gwindow" 
Calls: suppressPackageStartupMessages ... withr_with_dir -> force -> source_many -> source_one -> eval -> eval 
Execution halted 

Exited with status 1. 

같다. 하지만 작동하지 않습니다.

설명 파일은 다음과 같습니다.

Package: IC50 
Type: Package 
Title: Predicts IC50 
Version: 0.1.0 
Author: Who wrote it 
Maintainer: Who to complain to <yourfault@somewhere.net> 
Description: More about what it does (maybe more than one line) 
License: What license is it under? 
LazyData: TRUE 
RoxygenNote: 5.0.1 
Imports: gWidgets,gWidgetsRGtk2,tcltk,data.table,cluster,e1071,caret 
Depends: R (>= 3.0),gWidgets,gWidgetsRGtk2,tcltk,data.table,cluster,e1071,caret, cluster 
     , e1071, 
     ggplot2, gplots, grid, gtools, 
     gWidgetsRGtk2, nnet, 
Suggests: pmml (>= 1.2.13), bitops, colorspace, ada, amap, arules, 
     arulesViz, biclust, cairoDevice, cba, cluster, corrplot, descr, 
     doBy, dplyr, e1071, ellipse, fBasics, foreign, fpc, gdata, 
     ggdendro, ggplot2, gplots, graph, grid, gridExtra, gtools, 
     gWidgetsRGtk2, hmeasure, Hmisc, kernlab, Matrix, mice, nnet, 
     odfWeave, party, playwith, plyr, psych, randomForest, RBGL, 
     RColorBrewer, readxl, reshape, rggobi, RGtk2Extras, ROCR, 
     RODBC, rpart, rpart.plot, SnowballC, stringr, survival, 
     timeDate, tm, verification, wskm, XML, pkgDepTools, Rgraphviz 
NeedsCompilation: Yes 
LazyData: yes 

이

오류

==> devtools::document(roclets=c('rd', 'collate', 'namespace')) 

Updating IC50 documentation 
Loading IC50 

(Rterm.exe:732): Gtk-CRITICAL **: gtk_table_attach: assertion `child->parent == NULL' failed 
First time using roxygen2. Upgrading automatically... 
Error: Missing name at IC50.r:6 
Execution halted 

Exited with status 1. 

추가 업데이트 수입과 설명 파일을입니다. 설명 파일이 다음과 같이 잘 작동합니다. Main R 파일에있는 Funtion을 라이브러리로 호출하기 위해 추가했습니다.

Description: Utilizes the Naive Bayes Classifier for Drug Prediction. 
License: Public 
LazyData: TRUE 
RoxygenNote: 5.0.1 
Imports: gWidgets,gWidgetsRGtk2,tcltk,data.table,cluster,e1071,caret,gWidgetstcltk 
Depends: R (>= 3.2),gWidgets,gWidgetsRGtk2,tcltk,data.table,cluster,e1071,caret, cluster 
     ,e1071,gWidgetstcltk, ggplot2, gplots, grid, gtools, 
     gWidgetsRGtk2, nnet, 
Suggests: pmml (>= 1.2.13), bitops, colorspace, ada, amap, arules, 
     arulesViz, biclust, cairoDevice, cba, cluster, corrplot, descr, 
     doBy, dplyr, e1071, ellipse, fBasics, foreign, fpc, gdata, 
     ggdendro, ggplot2, gplots, graph, grid, gridExtra, gtools, 
     gWidgetsRGtk2, hmeasure, Hmisc, kernlab, Matrix, mice, nnet, 
     odfWeave, party, playwith, plyr, psych, randomForest, RBGL, 
     RColorBrewer, readxl, reshape, rggobi, RGtk2Extras, ROCR, 
     RODBC, rpart, rpart.plot, SnowballC, stringr, survival, 
     timeDate, tm, verification, wskm, XML, pkgDepTools, Rgraphviz 
NeedsCompilation: Yes 
LazyData: yes 

Answer 1

업데이트 된 가져 오기가 포함 된 DESCRIPTION 파일이 추가되었습니다. 설명 파일이 다음과 같이 잘 작동합니다. Main R 파일에있는 Funtion을 라이브러리로 호출하기 위해 추가했습니다.

Description: Utilizes the Naive Bayes Classifier for Drug Prediction. 
License: Public 
LazyData: TRUE 
RoxygenNote: 5.0.1 
Imports: gWidgets,gWidgetsRGtk2,tcltk,data.table,cluster,e1071,caret,gWidgetstcltk 
Depends: R (>= 3.2),gWidgets,gWidgetsRGtk2,tcltk,data.table,cluster,e1071,caret, cluster 
     ,e1071,gWidgetstcltk, ggplot2, gplots, grid, gtools, 
     gWidgetsRGtk2, nnet, 
Suggests: pmml (>= 1.2.13), bitops, colorspace, ada, amap, arules, 
     arulesViz, biclust, cairoDevice, cba, cluster, corrplot, descr, 
     doBy, dplyr, e1071, ellipse, fBasics, foreign, fpc, gdata, 
     ggdendro, ggplot2, gplots, graph, grid, gridExtra, gtools, 
     gWidgetsRGtk2, hmeasure, Hmisc, kernlab, Matrix, mice, nnet, 
     odfWeave, party, playwith, plyr, psych, randomForest, RBGL, 
     RColorBrewer, readxl, reshape, rggobi, RGtk2Extras, ROCR, 
     RODBC, rpart, rpart.plot, SnowballC, stringr, survival, 
     timeDate, tm, verification, wskm, XML, pkgDepTools, Rgraphviz 
NeedsCompilation: Yes 
LazyData: yes