Fix (most of) the check errors/warnings/notes

.gitignore

@@ -1,3 +1,4 @@
 .Rproj.user
 inst/doc
 .DS_Store
+.Rhistory

DESCRIPTION

@@ -1,6 +1,7 @@
 Package: EVI
 Title: Epidemic Volatility Index as an Early-Warning Tool
-Version: 0.1.0-1
+Version: 0.1.1-1
+Date: 2022-02-22
 Authors@R: 
     c(
     person(given = "Eletherios",
@@ -36,6 +37,8 @@ License: GPL (>= 3)
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
 RoxygenNote: 7.1.2
+Depends:
+    R (>= 3.5.0)
 Imports:
     ggplot2,
     cowplot
@@ -47,6 +50,4 @@ Suggests:
     testthat (>= 3.0.0)
 Config/testthat/edition: 3
 VignetteBuilder: knitr
-Language: en-GB
-Depends: 
-    R (>= 2.10)
+Language: en-US

EVI.Rproj

@@ -0,0 +1,21 @@
+Version: 1.0
+
+RestoreWorkspace: Default
+SaveWorkspace: Default
+AlwaysSaveHistory: Default
+
+EnableCodeIndexing: Yes
+UseSpacesForTab: Yes
+NumSpacesForTab: 2
+Encoding: UTF-8
+
+RnwWeave: Sweave
+LaTeX: pdfLaTeX
+
+AutoAppendNewline: Yes
+StripTrailingWhitespace: Yes
+
+BuildType: Package
+PackageUseDevtools: Yes
+PackageInstallArgs: --no-multiarch --with-keep.source
+PackageRoxygenize: rd,collate,namespace

NAMESPACE

@@ -10,3 +10,6 @@ export(medvol)
 export(mova)
 export(rollsd)
 export(status)
+import(cowplot)
+import(ggplot2)
+importFrom(stats,sd)

R/EVI.graphs.R

@@ -7,6 +7,7 @@
 #'
 #' An EVI_output is required as input, derived from the \code{\link[EVI:deviant]{deviant()}} function.
 #'
+#' @param EVI_output output of the \code{\link[EVI:deviant]{deviant()}} function
 #' @param graph Type of graph to be plotted. Options: "EVI", "PPV", "NPV". "EVI" (the default) is giving a plot of the confirmed cases, with red dots corresponding to time points that an early warning was issued and grey dots corresponding to time points without an early warning indication. "PPV" is giving a plot of the confirmed cases with colored dots corresponding to time points with an early warning. Color intensity is increasing with higher PPV. "NPV" is giving a plot of the confirmed cases with colored dots corresponding to time points without an early warning. Color intensity is increasing with higher NPV.
 #' @param ln  TRUE or FALSE; If TRUE (the default) the output of the graph will be presented on the logarithmic scale. IF FALSE the output data will be presented on the original scale.
 #' @param type By default, points are plotted on EVI graphs. In cases where, changes are very sudden or data sparsely available, type="l" introduces lines on top of points for the "EVI" type of graph.
@@ -18,17 +19,15 @@
 #' evi.graphs(EVI_output=EVI_output, graph="EVI", ln=T, type="l") # For the line EVI plot
 #' @export
 #'
+#' @import ggplot2
+#' @import cowplot
+#'
 #' @references
 #' Kostoulas, P., Meletis, E., Pateras, K. et al. The epidemic volatility index, a novel early warning tool for identifying new waves in an epidemic. Sci Rep 11, 23775 (2021). \doi{10.1038/s41598-021-02622-3}
 
 
-evi.graphs=function(EVI_output,graph=c("EVI"), ln=T, type="p") {
+evi.graphs <- function(EVI_output,graph=c("EVI"), ln=T, type="p") {
 
-  list.of.packages <- c("ggplot2", "cowplot")
-  new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,"Package"])]
-  if(length(new.packages)) install.packages(new.packages)
-  require(ggplot2)
-  require(cowplot)
   #EVI_output=temp
   EVI_output$cases_1=EVI_output$Cases*EVI_output$Index
   EVI_output$cases_1[EVI_output$cases_1 == 0] <- NA
@@ -42,32 +41,32 @@ evi.graphs=function(EVI_output,graph=c("EVI"), ln=T, type="p") {
   EVI_output$variable<-"x"
 
   if (graph=="EVI" && ln==F) {
-    sp3<-ggplot(EVI_output, aes(x=Days,group=variable))+
+    sp3<-ggplot(EVI_output, aes_string(x="Days",group="variable"))+
       list(
-      geom_point(aes(y=(Cases), color=Index>0), size=0.5),
+      geom_point(aes_string(y=("Cases"), color="Index>0"), size=0.5),
       scale_color_manual(values=c("grey69", "red3")),
       theme(legend.position = "none"),
       labs(y = "Cases", x="Days"),
-    if (type=="l")  geom_path(aes(y=Cases,colour=factor(Index>0)))
+    if (type=="l")  geom_path(aes_string(y="Cases",colour="factor(Index>0)"))
     )
       }
 
   if (graph=="EVI" && ln==T) {
-    sp3<-ggplot(EVI_output, aes(x=Days,group=variable))+
+    sp3<-ggplot(EVI_output, aes_string(x="Days",group="variable"))+
       list(
-      geom_point(aes(y=log(Cases), color=Index>0), size=0.5),
+      geom_point(aes_string(y="log(Cases)", color="Index>0"), size=0.5),
       scale_color_manual(values=c("grey69", "red3")),
       theme(legend.position = "none"),
       labs(y = "ln(Cases)", x="Days"),
-      if (type=="l")  geom_path(aes(y=log(Cases),colour=factor(Index>0)))
+      if (type=="l")  geom_path(aes_string(y="log(Cases)",colour="factor(Index>0)"))
       )
      }
 
   if (graph=="PPV" && ln==F) {
-    sp3<-ggplot(EVI_output, aes(x=Days,group=variable))+
+    sp3<-ggplot(EVI_output, aes_string(x="Days",group="variable"))+
       list(
-      geom_point(aes(y=(cases_1), col=ppv), size=0.5),
-      geom_point(aes(y=(cases_0)), col="grey69", size=0.5),
+      geom_point(aes_string(y="(cases_1)", col="ppv"), size=0.5),
+      geom_point(aes_string(y="(cases_0)"), col="grey69", size=0.5),
       labs(y = "Cases", x=""),
       scale_color_gradient(low = "green", high = "red", limits=c(0, 1)),
       labs(color= "PPV"),
@@ -79,10 +78,10 @@ evi.graphs=function(EVI_output,graph=c("EVI"), ln=T, type="p") {
       }
 
   if (graph=="PPV" && ln==T) {
-    sp3<-ggplot(EVI_output, aes(x=Days,group=variable))+
+    sp3<-ggplot(EVI_output, aes_string(x="Days",group="variable"))+
       list(
-      geom_point(aes(y=log(cases_1), col=ppv), size=0.5),
-      geom_point(aes(y=log(cases_0)), col="grey69", size=0.5),
+      geom_point(aes(y="log(cases_1)", col="ppv"), size=0.5),
+      geom_point(aes(y="log(cases_0)"), col="grey69", size=0.5),
       labs(y = "ln(Cases)", x=""),
       scale_color_gradient(low = "green", high = "red", limits=c(0, 1)),
       labs(color= "PPV"),
@@ -94,10 +93,10 @@ evi.graphs=function(EVI_output,graph=c("EVI"), ln=T, type="p") {
     }
 
   if (graph=="NPV" && ln==F) {
-    sp3<-ggplot(EVI_output, aes(x=Days,group=variable))+
+    sp3<-ggplot(EVI_output, aes_string(x="Days",group="variable"))+
       list(
-      geom_point(aes(y=(cases_0), col=npv), size=0.5),
-      geom_point(aes(y=(cases_1)), col="grey69", size=0.5),
+      geom_point(aes_string(y="(cases_0)", col="npv"), size=0.5),
+      geom_point(aes_string(y="(cases_1)"), col="grey69", size=0.5),
       labs(y = "Cases"),
       scale_color_gradient(low = "green", high = "red", limits=c(0, 1)),
       labs(color= "NPV"),
@@ -110,10 +109,10 @@ evi.graphs=function(EVI_output,graph=c("EVI"), ln=T, type="p") {
 
 
   if (graph=="NPV" && ln==T) {
-    sp3<-ggplot(EVI_output, aes(x=Days,group=variable))+
+    sp3<-ggplot(EVI_output, aes_string(x="Days",group="variable"))+
       list(
-      geom_point(aes(y=log(cases_0), col=npv), size=0.5),
-      geom_point(aes(y=log(cases_1)), col="grey69", size=0.5),
+      geom_point(aes_string(y="log(cases_0)", col="npv"), size=0.5),
+      geom_point(aes_string(y="log(cases_1)"), col="grey69", size=0.5),
       labs(y = "ln(Cases)"),
       scale_color_gradient(low = "green", high = "red", limits=c(0, 1)),
       labs(color= "NPV"),

R/deviant.R

@@ -38,9 +38,11 @@
 #'
 #' @examples
 #' data("Italy")
-#' deviant(new_cases=Italy$Cases, cum=F, r_a=7, r=0.2, lag_max=30)
+#' deviant(new_cases=Italy$Cases, cum=FALSE, r_a=7, r=0.2, lag_max=30)
 #' #This step should take some time and the time elapsed will be printed
 #'
+#' @importFrom stats sd
+#'
 #' @export
 #'
 #' @references
@@ -196,7 +198,7 @@ deviant=function(new_cases, cum = FALSE, r_a=7, r=0.2, lag_max=30){
 
   EVI_out=as.data.frame(cbind(Days, EVI, Cases, Index, ppv, npv,
                               lag_all, c_all, se_all, sp_all))
-  EVI_output<<-(EVI_out)
+  EVI_output<-(EVI_out)
 
   end_time = Sys.time()
 

R/deviant_update.R

@@ -15,11 +15,12 @@
 #' @examples
 #' # If we have first observed only the 148 cases from the Italian data we run the deviant function on these cases:
 #'
-#' deviant(new_cases=Italy$Cases[1:148], cum=F, r_a=7, r=0.2, lag_max=30)
+#' data("Italy")
+#' deviant(new_cases=Italy$Cases[1:148], cum=FALSE, r_a=7, r=0.2, lag_max=30)
 #'
 #' # When the number of cases for the next day is observed we want to obtain the estimates for this day without having to reanalyze the entire time series. This is done by using the deviant_update function:
 #'
-#' deviant_update(new_cases=Italy$Cases[1:149], cum=F, r_a=7, r=0.2, lag_max=30)
+#' deviant_update(new_cases=Italy$Cases[1:149], cum=FALSE, r_a=7, r=0.2, lag_max=30)
 #'
 #' # The result of running the deviant_update function is to update the output of the deviant_function by adding an additional row with estimates for the new data.
 #' # In this example the EVI_output file will now have 149 rows. If two additional days are analyzed two additional rows will be added and so on.