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Code: Some Lint fixes

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terrytangyuan
2015-10-24 16:43:44 -04:00
parent 3abbd7b4c7
commit 537b34dc6f
6 changed files with 29 additions and 32 deletions
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25
R-package/R/utils.R
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@@ -17,28 +17,28 @@ xgb.setinfo <- function(dmat, name, info) {
if (name == "label") {
if (length(info)!=xgb.numrow(dmat))
stop("The length of labels must equal to the number of rows in the input data")
.Call("XGDMatrixSetInfo_R", dmat, name, as.numeric(info),
.Call("XGDMatrixSetInfo_R", dmat, name, as.numeric(info),
PACKAGE = "xgboost")
return(TRUE)
}
if (name == "weight") {
if (length(info)!=xgb.numrow(dmat))
stop("The length of weights must equal to the number of rows in the input data")
.Call("XGDMatrixSetInfo_R", dmat, name, as.numeric(info),
.Call("XGDMatrixSetInfo_R", dmat, name, as.numeric(info),
PACKAGE = "xgboost")
return(TRUE)
}
if (name == "base_margin") {
# if (length(info)!=xgb.numrow(dmat))
# stop("The length of base margin must equal to the number of rows in the input data")
.Call("XGDMatrixSetInfo_R", dmat, name, as.numeric(info),
.Call("XGDMatrixSetInfo_R", dmat, name, as.numeric(info),
PACKAGE = "xgboost")
return(TRUE)
}
if (name == "group") {
if (sum(info)!=xgb.numrow(dmat))
stop("The sum of groups must equal to the number of rows in the input data")
.Call("XGDMatrixSetInfo_R", dmat, name, as.integer(info),
.Call("XGDMatrixSetInfo_R", dmat, name, as.integer(info),
PACKAGE = "xgboost")
return(TRUE)
}
@@ -68,7 +68,7 @@ xgb.Booster <- function(params = list(), cachelist = list(), modelfile = NULL) {
if (typeof(modelfile) == "character") {
.Call("XGBoosterLoadModel_R", handle, modelfile, PACKAGE = "xgboost")
} else if (typeof(modelfile) == "raw") {
.Call("XGBoosterLoadModelFromRaw_R", handle, modelfile, PACKAGE = "xgboost")
.Call("XGBoosterLoadModelFromRaw_R", handle, modelfile, PACKAGE = "xgboost")
} else {
stop("xgb.Booster: modelfile must be character or raw vector")
}
@@ -142,8 +142,7 @@ xgb.iter.boost <- function(booster, dtrain, gpair) {
if (class(dtrain) != "xgb.DMatrix") {
stop("xgb.iter.update: second argument must be type xgb.DMatrix")
}
.Call("XGBoosterBoostOneIter_R", booster, dtrain, gpair$grad, gpair$hess,
PACKAGE = "xgboost")
.Call("XGBoosterBoostOneIter_R", booster, dtrain, gpair$grad, gpair$hess, PACKAGE = "xgboost")
return(TRUE)
}
@@ -159,7 +158,7 @@ xgb.iter.update <- function(booster, dtrain, iter, obj = NULL) {
if (is.null(obj)) {
.Call("XGBoosterUpdateOneIter_R", booster, as.integer(iter), dtrain,
PACKAGE = "xgboost")
} else {
} else {
pred <- predict(booster, dtrain)
gpair <- obj(pred, dtrain)
succ <- xgb.iter.boost(booster, dtrain, gpair)
@@ -192,7 +191,7 @@ xgb.iter.eval <- function(booster, watchlist, iter, feval = NULL, prediction = F
}
msg <- .Call("XGBoosterEvalOneIter_R", booster, as.integer(iter), watchlist,
evnames, PACKAGE = "xgboost")
} else {
} else {
msg <- paste("[", iter, "]", sep="")
for (j in 1:length(watchlist)) {
w <- watchlist[j]
@@ -253,10 +252,10 @@ xgb.cv.mknfold <- function(dall, nfold, param, stratified, folds) {
kstep <- length(randidx) %/% nfold
folds <- list()
for (i in 1:(nfold-1)) {
folds[[i]] = randidx[1:kstep]
randidx = setdiff(randidx, folds[[i]])
folds[[i]] <- randidx[1:kstep]
randidx <- setdiff(randidx, folds[[i]])
}
folds[[nfold]] = randidx
folds[[nfold]] <- randidx
}
}
ret <- list()
@@ -270,7 +269,7 @@ xgb.cv.mknfold <- function(dall, nfold, param, stratified, folds) {
}
dtrain <- slice(dall, didx)
bst <- xgb.Booster(param, list(dtrain, dtest))
watchlist = list(train=dtrain, test=dtest)
watchlist <- list(train=dtrain, test=dtest)
ret[[k]] <- list(dtrain=dtrain, booster=bst, watchlist=watchlist, index=folds[[k]])
}
return (ret)