Fixing cran notes errors

DESCRIPTION

@@ -11,8 +11,9 @@ Title: rWBclimate
 Description: A package for accessing World Bank climate data
 LazyData: True
 VignetteBuilder: knitr
-Suggests: knitr
-Depends:
+Suggests:
+    knitr
+Imports:
     ggplot2,
     httr,
     plyr,

R/get_ensemble_precip.R

@@ -21,13 +21,15 @@
 #' precip_dat <- get_ensemble_precip(c("2","231"),"annualavg",1900,3000)
 #' precip_dat <- subset(precip_dat,precip_dat$scenario!="b1")
 #' precip_dat$uniqueGroup <- paste(precip_dat$percentile,precip_dat$locator,sep="-")
-#' ggplot(precip_dat,aes(x=fromYear,y=annualVal,group=uniqueGroup,colour=as.factor(locator),linetype=as.factor(percentile)))+geom_path()
+#' ggplot(precip_dat,aes(x=fromYear,y=annualVal,group=uniqueGroup,colour=as.factor(locator),
+#' linetype=as.factor(percentile)))+ geom_path()
 #' 
 #' ### Get data for 2 countries with monthly precipitation values
 #' precip_dat <- get_ensemble_precip(c("USA","BRA"),"mavg",2020,2030)
 #' precip_dat <- subset(precip_dat,precip_dat$scenario!="b1")
 #' precip_dat$uniqueGroup <- paste(precip_dat$percentile,precip_dat$locator,sep="-")
-#' ggplot(precip_dat,aes(x=as.factor(month),y=monthVals,group=uniqueGroup,colour=locator))+geom_path()
+#' ggplot(precip_dat,aes(x=as.factor(month),y=monthVals,group=uniqueGroup,
+#' colour=locator))+geom_path()
 #'}
 #'@export
 

R/get_ensemble_stats.R

@@ -28,7 +28,8 @@
 #'  # subset to the 50th percentile and just until the year 2100
 #'  ens_dat <- subset(ens_dat, ens_dat$percentile == 50)
 #'  ens_dat <- subset(ens_dat,ens_dat$toYear == 2100)
-#'  ggplot(ens_dat,aes(x = as.factor(month), y= monthVals, group=scenario, colour=scenario)) + geom_point() + geom_line()
+#'  ggplot(ens_dat,aes(x = as.factor(month), y= monthVals, group=scenario, 
+#'  colour=scenario)) + geom_point() + geom_line()
 #'}
 #'@export
 

R/get_ensemble_temp.R

@@ -22,13 +22,15 @@
 #' temp_dat <- get_ensemble_temp(c("2","231"),"annualavg",1900,3000)
 #' temp_dat <- subset(temp_dat,temp_dat$scenario!="b1")
 #' temp_dat$uniqueGroup <- paste(temp_dat$percentile,temp_dat$locator,sep="-")
-#' ggplot(temp_dat,aes(x=fromYear,y=annualVal,group=uniqueGroup,colour=as.factor(locator),linetype=as.factor(percentile)))+geom_path()
+#' ggplot(temp_dat,aes(x=fromYear,y=annualVal,group=uniqueGroup,colour=as.factor(locator),
+#' linetype=as.factor(percentile)))+geom_path()
 #' 
 #' ### Get data for 2 countries with monthly precipitation values
 #' temp_dat <- get_ensemble_temp(c("USA","BRA"),"mavg",2020,2030)
 #' temp_dat <- subset(temp_dat,temp_dat$scenario!="b1")
 #' temp_dat$uniqueGroup <- paste(temp_dat$percentile,temp_dat$locator,sep="-")
-#' ggplot(temp_dat,aes(x=as.factor(month),y=monthVals,group=uniqueGroup,colour=locator))+geom_path()
+#' ggplot(temp_dat,aes(x=as.factor(month),y=monthVals,group=uniqueGroup,
+#' colour=locator))+geom_path()
 #'}
 #'@export
 

R/get_historical_precip.R

@@ -12,11 +12,13 @@
 #' @examples \dontrun{
 #' ## Plot annual historical data for USA, Brazil and Australia
 #' hist_dat <- get_historical_precip(c("USA","BRA","AUS"),"year")
-#' ggplot(hist_dat,aes(x = year,y = data, group = locator,colour = locator)) + geom_point() + geom_path() + ylab("Mean annual precipitaion")
+#' ggplot(hist_dat,aes(x = year,y = data, group = locator,
+#' colour = locator)) + geom_point() + geom_path() + ylab("Mean annual precipitaion")
 #'
 #' ## Plot monthly historical data
 #' hist_mo_dat <- get_historical_precip(c("USA","AUS","BRA","IDN"),time_scale="month")
-#' ggplot(hist_mo_dat,aes(x = month,y = data, group = locator,colour = locator)) + geom_point() + geom_path() + ylab("Mean monthly precipitaion")
+#' ggplot(hist_mo_dat,aes(x = month,y = data, group = locator,
+#' colour = locator)) + geom_point() + geom_path() + ylab("Mean monthly precipitaion")
 #' 
 #' }
 #' @export

R/get_historical_temp.R

@@ -12,11 +12,13 @@
 #' @examples \dontrun{
 #' ## Plot annual historical data for USA, Brazil and Australia
 #' hist_dat <- get_historical_precip(c("USA","BRA","AUS"),"year")
-#' ggplot(hist_dat,aes(x = year,y = data, group = locator,colour = locator)) + geom_point() + geom_path() + ylab("Mean annual temperature")
+#' ggplot(hist_dat,aes(x = year,y = data, group = locator,
+#' colour = locator)) + geom_point() + geom_path() + ylab("Mean annual temperature")
 #'
 #' ## Plot monthly historical data
 #' hist_mo_dat <- get_historical_precip(c("USA","AUS","BRA","IDN"),time_scale="month")
-#' ggplot(hist_mo_dat,aes(x = month,y = data, group = locator,colour = locator)) + geom_point() + geom_path() + ylab("Mean monthly temperature")
+#' ggplot(hist_mo_dat,aes(x = month,y = data, group = locator,
+#' colour = locator)) + geom_point() + geom_path() + ylab("Mean monthly temperature")
 #' 
 #' }
 #' @export

R/get_model_temp.R

@@ -20,13 +20,15 @@
 #' temp_dat <- get_model_temp(c("2","231"),"annualavg",1900,3000)
 #' temp_dat <- subset(temp_dat,temp_dat$gcm=="ukmo_hadcm3")
 #' temp_dat <- subset(temp_dat,temp_dat$scenario!="b1")
-#' ggplot(temp_dat,aes(x=fromYear,y=data,group=locator,colour=locator))+geom_path()
+#' ggplot(temp_dat,aes(x=fromYear,y=data,group=locator,
+#' colour=locator))+geom_path()
 #' 
 #' ### Get data for 4 countries with monthly tempitation values
 #' temp_dat <- get_model_temp(c("USA","BRA","CAN","YEM"),"mavg",2020,2030)
 #' temp_dat <- subset(temp_dat,temp_dat$gcm=="ukmo_hadcm3")
 #' temp_dat <- subset(temp_dat,temp_dat$scenario!="b1")
-#' ggplot(temp_dat,aes(x=as.factor(month),y=data,group=locator,colour=locator))+geom_path()
+#' ggplot(temp_dat,aes(x=as.factor(month),y=data,group=locator,
+#' colour=locator))+geom_path()
 #'}
 #'@export
 

man/get_ensemble_precip.Rd

@@ -45,13 +45,15 @@ full details.
 precip_dat <- get_ensemble_precip(c("2","231"),"annualavg",1900,3000)
 precip_dat <- subset(precip_dat,precip_dat$scenario!="b1")
 precip_dat$uniqueGroup <- paste(precip_dat$percentile,precip_dat$locator,sep="-")
-ggplot(precip_dat,aes(x=fromYear,y=annualVal,group=uniqueGroup,colour=as.factor(locator),linetype=as.factor(percentile)))+geom_path()
+ggplot(precip_dat,aes(x=fromYear,y=annualVal,group=uniqueGroup,colour=as.factor(locator),
+linetype=as.factor(percentile)))+ geom_path()
 
 ### Get data for 2 countries with monthly precipitation values
 precip_dat <- get_ensemble_precip(c("USA","BRA"),"mavg",2020,2030)
 precip_dat <- subset(precip_dat,precip_dat$scenario!="b1")
 precip_dat$uniqueGroup <- paste(precip_dat$percentile,precip_dat$locator,sep="-")
-ggplot(precip_dat,aes(x=as.factor(month),y=monthVals,group=uniqueGroup,colour=locator))+geom_path()
+ggplot(precip_dat,aes(x=as.factor(month),y=monthVals,group=uniqueGroup,
+colour=locator))+geom_path()
 }
 }
 

man/get_ensemble_stats.Rd

@@ -56,7 +56,8 @@ Average daily precipitation \tab mm }
  # subset to the 50th percentile and just until the year 2100
  ens_dat <- subset(ens_dat, ens_dat$percentile == 50)
  ens_dat <- subset(ens_dat,ens_dat$toYear == 2100)
- ggplot(ens_dat,aes(x = as.factor(month), y= monthVals, group=scenario, colour=scenario)) + geom_point() + geom_line()
+ ggplot(ens_dat,aes(x = as.factor(month), y= monthVals, group=scenario,
+ colour=scenario)) + geom_point() + geom_line()
 }
 }
 

man/get_ensemble_temp.Rd

@@ -45,13 +45,15 @@ full details.
 temp_dat <- get_ensemble_temp(c("2","231"),"annualavg",1900,3000)
 temp_dat <- subset(temp_dat,temp_dat$scenario!="b1")
 temp_dat$uniqueGroup <- paste(temp_dat$percentile,temp_dat$locator,sep="-")
-ggplot(temp_dat,aes(x=fromYear,y=annualVal,group=uniqueGroup,colour=as.factor(locator),linetype=as.factor(percentile)))+geom_path()
+ggplot(temp_dat,aes(x=fromYear,y=annualVal,group=uniqueGroup,colour=as.factor(locator),
+linetype=as.factor(percentile)))+geom_path()
 
 ### Get data for 2 countries with monthly precipitation values
 temp_dat <- get_ensemble_temp(c("USA","BRA"),"mavg",2020,2030)
 temp_dat <- subset(temp_dat,temp_dat$scenario!="b1")
 temp_dat$uniqueGroup <- paste(temp_dat$percentile,temp_dat$locator,sep="-")
-ggplot(temp_dat,aes(x=as.factor(month),y=monthVals,group=uniqueGroup,colour=locator))+geom_path()
+ggplot(temp_dat,aes(x=as.factor(month),y=monthVals,group=uniqueGroup,
+colour=locator))+geom_path()
 }
 }
 

man/get_historical_precip.Rd

@@ -37,11 +37,13 @@ will return decade averages.
 \dontrun{
 ## Plot annual historical data for USA, Brazil and Australia
 hist_dat <- get_historical_precip(c("USA","BRA","AUS"),"year")
-ggplot(hist_dat,aes(x = year,y = data, group = locator,colour = locator)) + geom_point() + geom_path() + ylab("Mean annual precipitaion")
+ggplot(hist_dat,aes(x = year,y = data, group = locator,
+colour = locator)) + geom_point() + geom_path() + ylab("Mean annual precipitaion")
 
 ## Plot monthly historical data
 hist_mo_dat <- get_historical_precip(c("USA","AUS","BRA","IDN"),time_scale="month")
-ggplot(hist_mo_dat,aes(x = month,y = data, group = locator,colour = locator)) + geom_point() + geom_path() + ylab("Mean monthly precipitaion")
+ggplot(hist_mo_dat,aes(x = month,y = data, group = locator,
+colour = locator)) + geom_point() + geom_path() + ylab("Mean monthly precipitaion")
 
 }
 }

man/get_model_temp.Rd

@@ -44,13 +44,15 @@ full details.
 temp_dat <- get_model_temp(c("2","231"),"annualavg",1900,3000)
 temp_dat <- subset(temp_dat,temp_dat$gcm=="ukmo_hadcm3")
 temp_dat <- subset(temp_dat,temp_dat$scenario!="b1")
-ggplot(temp_dat,aes(x=fromYear,y=data,group=locator,colour=locator))+geom_path()
+ggplot(temp_dat,aes(x=fromYear,y=data,group=locator,
+colour=locator))+geom_path()
 
 ### Get data for 4 countries with monthly tempitation values
 temp_dat <- get_model_temp(c("USA","BRA","CAN","YEM"),"mavg",2020,2030)
 temp_dat <- subset(temp_dat,temp_dat$gcm=="ukmo_hadcm3")
 temp_dat <- subset(temp_dat,temp_dat$scenario!="b1")
-ggplot(temp_dat,aes(x=as.factor(month),y=data,group=locator,colour=locator))+geom_path()
+ggplot(temp_dat,aes(x=as.factor(month),y=data,group=locator,
+colour=locator))+geom_path()
 }
 }