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From: | Vikas Rawal |
Subject: | Re: [O] Trouble evaluating R source code blocks with C-c C-c |
Date: | Sun, 29 May 2016 18:43:58 +0530 |
And this time it has this additional line: run-hook-with-args-until-success(org-babel-execute-safely-maybe) ------------------ sit-for(0.25) org-babel-comint-eval-invisibly-and-wait-for-file("type2" "/var/folders/hj/hqfjch716qg5php160jbtfgh0000gn/T/babel-53134TSq/R-53134vJF" "{\n function(object,transfer.file) {\n object\n invisible(\n if (\n inherits(\n try(\n {\n tfile<-tempfile()\n write.table(object, file=tfile, sep=\"\\t\",\n na=\"nil\",row.names=FALSE,col.names=TRUE,\n quote=FALSE)\n file.rename(tfile,transfer.file)\n },\n silent=TRUE),\n \"try-error\"))\n {\n if(!file.exists(transfer.file))\n file.create(transfer.file)\n }\n )\n }\n}(object=.Last.value,transfer.file=\"/var/folders/hj/hqfjch716qg5php160jbtfgh0000gn/T/babel-53134TSq/R-53134vJF\")") org-babel-R-evaluate-session("type2" "library(plyr)\nlibrary(Hmisc)\ng->tempg\n\n # CV_untreated\nas.integer(tempg$state_region/10)->tempg$State.code.68\nfactor(tempg$State.code.68)->tempg$State.code.68\ndata.frame(State=0,adjusted_cv=0)->e\n\nfor (i in c(1:35)) {\n subset(tempg,as.numeric(tempg$State.code.68)==i)->dd\n wtd.var(dd$adj_cal,weight=dd$weight)^0.5/wtd.mean(dd$adj_cal,weight=dd$weight)->cvs\n data.frame(State=i,adjusted_cv=cvs)->e1\n rbind(e,e1)->e\n}\n\nddply(tempg,.(State.code.68),summarise,value=wtd.mean(adj_cal,weight))->s1\n\ndata.frame(State=99,adjusted_cv=0)->f2\nwtd.var(tempg$adj_cal,weight=tempg$weight)^0.5/wtd.mean(tempg$adj_cal,weight=tempg$weight)->f2[1,2]\nrbind(e,f2)->cv1\n\n # CV_grouped data\nddply(tempg,.(sex,agegroup,fractile_adj),summarise,calories=wtd.mean(adj_cal,weight))->l1\nddply(tempg,.(sex,agegroup,fractile_adj),summarise,weight=sum(weight))->w\n\nmerge(w,l1,by=c(\"sex\",\"agegroup\",\"fractile_adj\"))->l1\n\nddply(tempg,.(fractile_adj_state,State.code.68,agegroup,sex),summarise,value=wtd.mean(adj_cal,weight))->s3\n\nddply(tempg,.(fractile_adj_state,State.code.68,agegroup,sex),summarise,sum_weight=sum(weight))->sw\n\nmerge(s3,sw,by=c(\"fractile_adj_state\",\"State.code.68\",\"agegroup\",\"sex\"))->s3\n\nfactor(s3$State.code.68)->s3$State.code.68\n\ndata.frame(State=99,grouped_cv=wtd.var(l1$calories,weight=l1$weight)^0.5/wtd.mean(l1$calories,weight=l1$weight))->cv3\n\nfor (i in c(1:35)) {\n subset(s3,as.numeric(s3$State.code.68)==i)->s3sub\n data.frame(State=i,grouped_cv=wtd.var(s3sub$value,s3sub$sum_weight)^0.5/wtd.mean(s3sub$value,s3sub$sum_weight))->t1\n rbind(cv3,t1)->cv3\n}\n\n# CV_from regression model\nregdata->p\nexp(predict.lm(reg))->p$predicted_cal\n\ndata.frame(State=99,predicted_cv=wtd.var(p$predicted_cal,weight=p$weight)^0.5/wtd.mean(p$predicted_cal,weight=p$weight),adjr2=summary(reg)$adj.r.squared)->cv2\n\n\n#data.frame(State=0,predicted_cv=0,adjr2=0)->e\n\nfor (i in c(1:35)) {\n subset(regdata,as.numeric(p$State.code.68)==i)->dd\n factor(dd$state_region)->dd$state_region\nfmla <- as.formula(\n ifelse(length(levels(dd$state_region))==1,\"log_cal~sector+sex+AgeChild+AgeAdult+foodprice+log(MPCE)\",\"log_cal~sector+sex+AgeChild+AgeAdult+foodprice+log(MPCE)+state_region\"))\n\n\n lm(fmla,data="" exp(predict.lm(regstate))->dd$predicted_cal\n wtd.var(dd$predicted_cal,weight=dd$weight)^0.5/wtd.mean(dd$predicted_cal,weight=dd$weight)->cvs\n data.frame(State=i,predicted_cv=cvs,adjr2=summary(regstate)$adj.r.squared)->e1\n rbind(cv2,e1)->cv2\n}\n\nsubset(cv2,select=-adjr2)->cv2\n\nmerge(cv1,cv3,by=\"State\")->t\nmerge(t,cv2,by=\"State\")->t\nmerge(t,statecode,by.x=\"State\",by.y=\"State.code.68\",all.x=TRUE)->t\nt$State.68[t$State==99]<-\"India\"\nround(t$grouped_cv,4)->t$grouped_cv\nround(t$adjusted_cv,4)->t$adjusted_cv\nround(t$predicted_cv,4)->t$predicted_cv\nnames(t)<-c(\"State.code.68\",\"CV (unit-level data)\",\"CV (grouped data)\",\"CV (based on regression model)\",\"State\")\nt->finvar\nt[order(t$State),c(5,2,3,4)]" value ("replace" "value") t nil) org-babel-R-evaluate("type2" "library(plyr)\nlibrary(Hmisc)\ng->tempg\n\n # CV_untreated\nas.integer(tempg$state_region/10)->tempg$State.code.68\nfactor(tempg$State.code.68)->tempg$State.code.68\ndata.frame(State=0,adjusted_cv=0)->e\n\nfor (i in c(1:35)) {\n subset(tempg,as.numeric(tempg$State.code.68)==i)->dd\n wtd.var(dd$adj_cal,weight=dd$weight)^0.5/wtd.mean(dd$adj_cal,weight=dd$weight)->cvs\n data.frame(State=i,adjusted_cv=cvs)->e1\n rbind(e,e1)->e\n}\n\nddply(tempg,.(State.code.68),summarise,value=wtd.mean(adj_cal,weight))->s1\n\ndata.frame(State=99,adjusted_cv=0)->f2\nwtd.var(tempg$adj_cal,weight=tempg$weight)^0.5/wtd.mean(tempg$adj_cal,weight=tempg$weight)->f2[1,2]\nrbind(e,f2)->cv1\n\n # CV_grouped data\nddply(tempg,.(sex,agegroup,fractile_adj),summarise,calories=wtd.mean(adj_cal,weight))->l1\nddply(tempg,.(sex,agegroup,fractile_adj),summarise,weight=sum(weight))->w\n\nmerge(w,l1,by=c(\"sex\",\"agegroup\",\"fractile_adj\"))->l1\n\nddply(tempg,.(fractile_adj_state,State.code.68,agegroup,sex),summarise,value=wtd.mean(adj_cal,weight))->s3\n\nddply(tempg,.(fractile_adj_state,State.code.68,agegroup,sex),summarise,sum_weight=sum(weight))->sw\n\nmerge(s3,sw,by=c(\"fractile_adj_state\",\"State.code.68\",\"agegroup\",\"sex\"))->s3\n\nfactor(s3$State.code.68)->s3$State.code.68\n\ndata.frame(State=99,grouped_cv=wtd.var(l1$calories,weight=l1$weight)^0.5/wtd.mean(l1$calories,weight=l1$weight))->cv3\n\nfor (i in c(1:35)) {\n subset(s3,as.numeric(s3$State.code.68)==i)->s3sub\n data.frame(State=i,grouped_cv=wtd.var(s3sub$value,s3sub$sum_weight)^0.5/wtd.mean(s3sub$value,s3sub$sum_weight))->t1\n rbind(cv3,t1)->cv3\n}\n\n# CV_from regression model\nregdata->p\nexp(predict.lm(reg))->p$predicted_cal\n\ndata.frame(State=99,predicted_cv=wtd.var(p$predicted_cal,weight=p$weight)^0.5/wtd.mean(p$predicted_cal,weight=p$weight),adjr2=summary(reg)$adj.r.squared)->cv2\n\n\n#data.frame(State=0,predicted_cv=0,adjr2=0)->e\n\nfor (i in c(1:35)) {\n subset(regdata,as.numeric(p$State.code.68)==i)->dd\n factor(dd$state_region)->dd$state_region\nfmla <- as.formula(\n ifelse(length(levels(dd$state_region))==1,\"log_cal~sector+sex+AgeChild+AgeAdult+foodprice+log(MPCE)\",\"log_cal~sector+sex+AgeChild+AgeAdult+foodprice+log(MPCE)+state_region\"))\n\n\n lm(fmla,data="" exp(predict.lm(regstate))->dd$predicted_cal\n wtd.var(dd$predicted_cal,weight=dd$weight)^0.5/wtd.mean(dd$predicted_cal,weight=dd$weight)->cvs\n data.frame(State=i,predicted_cv=cvs,adjr2=summary(regstate)$adj.r.squared)->e1\n rbind(cv2,e1)->cv2\n}\n\nsubset(cv2,select=-adjr2)->cv2\n\nmerge(cv1,cv3,by=\"State\")->t\nmerge(t,cv2,by=\"State\")->t\nmerge(t,statecode,by.x=\"State\",by.y=\"State.code.68\",all.x=TRUE)->t\nt$State.68[t$State==99]<-\"India\"\nround(t$grouped_cv,4)->t$grouped_cv\nround(t$adjusted_cv,4)->t$adjusted_cv\nround(t$predicted_cv,4)->t$predicted_cv\nnames(t)<-c(\"State.code.68\",\"CV (unit-level data)\",\"CV (grouped data)\",\"CV (based on regression model)\",\"State\")\nt->finvar\nt[order(t$State),c(5,2,3,4)]" value ("replace" "value") t nil) org-babel-execute:R("library(plyr)\nlibrary(Hmisc)\ng->tempg\n\n # CV_untreated\nas.integer(tempg$state_region/10)->tempg$State.code.68\nfactor(tempg$State.code.68)->tempg$State.code.68\ndata.frame(State=0,adjusted_cv=0)->e\n\nfor (i in c(1:35)) {\n subset(tempg,as.numeric(tempg$State.code.68)==i)->dd\n wtd.var(dd$adj_cal,weight=dd$weight)^0.5/wtd.mean(dd$adj_cal,weight=dd$weight)->cvs\n data.frame(State=i,adjusted_cv=cvs)->e1\n rbind(e,e1)->e\n}\n\nddply(tempg,.(State.code.68),summarise,value=wtd.mean(adj_cal,weight))->s1\n\ndata.frame(State=99,adjusted_cv=0)->f2\nwtd.var(tempg$adj_cal,weight=tempg$weight)^0.5/wtd.mean(tempg$adj_cal,weight=tempg$weight)->f2[1,2]\nrbind(e,f2)->cv1\n\n # CV_grouped data\nddply(tempg,.(sex,agegroup,fractile_adj),summarise,calories=wtd.mean(adj_cal,weight))->l1\nddply(tempg,.(sex,agegroup,fractile_adj),summarise,weight=sum(weight))->w\n\nmerge(w,l1,by=c(\"sex\",\"agegroup\",\"fractile_adj\"))->l1\n\nddply(tempg,.(fractile_adj_state,State.code.68,agegroup,sex),summarise,value=wtd.mean(adj_cal,weight))->s3\n\nddply(tempg,.(fractile_adj_state,State.code.68,agegroup,sex),summarise,sum_weight=sum(weight))->sw\n\nmerge(s3,sw,by=c(\"fractile_adj_state\",\"State.code.68\",\"agegroup\",\"sex\"))->s3\n\nfactor(s3$State.code.68)->s3$State.code.68\n\ndata.frame(State=99,grouped_cv=wtd.var(l1$calories,weight=l1$weight)^0.5/wtd.mean(l1$calories,weight=l1$weight))->cv3\n\nfor (i in c(1:35)) {\n subset(s3,as.numeric(s3$State.code.68)==i)->s3sub\n data.frame(State=i,grouped_cv=wtd.var(s3sub$value,s3sub$sum_weight)^0.5/wtd.mean(s3sub$value,s3sub$sum_weight))->t1\n rbind(cv3,t1)->cv3\n}\n\n# CV_from regression model\nregdata->p\nexp(predict.lm(reg))->p$predicted_cal\n\ndata.frame(State=99,predicted_cv=wtd.var(p$predicted_cal,weight=p$weight)^0.5/wtd.mean(p$predicted_cal,weight=p$weight),adjr2=summary(reg)$adj.r.squared)->cv2\n\n\n#data.frame(State=0,predicted_cv=0,adjr2=0)->e\n\nfor (i in c(1:35)) {\n subset(regdata,as.numeric(p$State.code.68)==i)->dd\n factor(dd$state_region)->dd$state_region\nfmla <- as.formula(\n ifelse(length(levels(dd$state_region))==1,\"log_cal~sector+sex+AgeChild+AgeAdult+foodprice+log(MPCE)\",\"log_cal~sector+sex+AgeChild+AgeAdult+foodprice+log(MPCE)+state_region\"))\n\n\n lm(fmla,data="" exp(predict.lm(regstate))->dd$predicted_cal\n wtd.var(dd$predicted_cal,weight=dd$weight)^0.5/wtd.mean(dd$predicted_cal,weight=dd$weight)->cvs\n data.frame(State=i,predicted_cv=cvs,adjr2=summary(regstate)$adj.r.squared)->e1\n rbind(cv2,e1)->cv2\n}\n\nsubset(cv2,select=-adjr2)->cv2\n\nmerge(cv1,cv3,by=\"State\")->t\nmerge(t,cv2,by=\"State\")->t\nmerge(t,statecode,by.x=\"State\",by.y=\"State.code.68\",all.x=TRUE)->t\nt$State.68[t$State==99]<-\"India\"\nround(t$grouped_cv,4)->t$grouped_cv\nround(t$adjusted_cv,4)->t$adjusted_cv\nround(t$predicted_cv,4)->t$predicted_cv\nnames(t)<-c(\"State.code.68\",\"CV (unit-level data)\",\"CV (grouped data)\",\"CV (based on regression model)\",\"State\")\nt->finvar\nt[order(t$State),c(5,2,3,4)]" ((:colname-names) (:rowname-names) (:result-params "replace" "value") (:result-type . value) (:comments . "") (:shebang . "") (:cache . "no") (:padline . "") (:noweb . "no") (:tangle . "no") (:exports . "results") (:results . "replace value") (:hlines . "no") (:session . "type2") (:colnames . "yes") (:hline . "yes"))) org-babel-execute-src-block(nil) org-babel-execute-src-block-maybe() org-babel-execute-maybe() org-babel-execute-safely-maybe() run-hook-with-args-until-success(org-babel-execute-safely-maybe) org-ctrl-c-ctrl-c(nil) call-interactively(org-ctrl-c-ctrl-c nil nil) command-execute(org-ctrl-c-ctrl-c)
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