Generate the list yourself:
$ cd /Applications/Xcode.app/Contents/Developer/Platforms/iPhoneOS.platform/Developer/SDKs/iPhoneOS*.sdk/System/Library/Frameworks/UIKit.framework/Headers
$ grep -H UI_APPEARANCE_SELECTOR ./* | sed 's/ __OSX_AVAILABLE_STARTING(__MAC_NA,__IPHONE_5_0) UI_APPEARANCE_SELECTOR;//'
| gar.fun<-function(out.var,mod.in,bar.plot=T,x.names=NULL,...){ | |
| require(devtools) | |
| source_gist('5086859') | |
| best.wts<-plot.nnet(mod.in,wts.only=T) | |
| out.ind<-which(out.var==colnames(eval(mod.in$call$y))) | |
| #get input-hidden weights and hidden-output weights, remove bias | |
| inp.hid<-data.frame( |
| plot.nnet<-function(mod.in,nid=T,all.out=T,all.in=T,wts.only=F,rel.rsc=5,circle.cex=5,node.labs=T, | |
| line.stag=NULL,cex.val=1,alpha.val=1,circle.col='lightgrey',pos.col='black',neg.col='grey',...){ | |
| require(scales) | |
| #gets weights for neural network, output is list | |
| #if rescaled argument is true, weights are returned but rescaled based on abs value | |
| nnet.vals<-function(mod.in,nid,rel.rsc){ | |
| library(scales) |