refined the package according to recommendations of package check

Author: Junbin Zhao

.Rbuildignore

@@ -2,3 +2,7 @@
 ^\.Rproj\.user$
 ^README\.Rmd$
 ^\.travis\.yml$
+^.*\.zip$
+^CONTRIBUTING\.md$
+^paper\.bib$
+^paper\.md$

DESCRIPTION

@@ -1,16 +1,16 @@
 Package: FluxCalR
 Type: Package
 Title: Calculate CO2 and CH4 gas fluxes measured with static chamber method
-Version: 0.1.0
+Version: 0.2.0
 Author: Junbin Zhao
 Maintainer: Junbin Zhao <[email protected]>
 Year: 2018
 Description: This R package is used to calculate CO2 and CH4 gas fluxes measured with static chamber method. It provide a easy way to calculate multiple flux measurements from one data file. The format of data input are specialized to that of from Los Gatos Research (LGR) Ultraportable Gas Analyzers <http://www.lgrinc.com/analyzers/ultraportable/>. A function is also provided to load and convert data from other sources (e.g. LICOR) into the format that is compatible with the flux calculation fuction. 
-Depends: R (>= 3.4.1)
-License: MIT
+Depends: R (>= 3.4.0)
+License: MIT + file LICENSE
 Encoding: UTF-8
 LazyData: true
-Imports: dplyr, lubridate, assertthat, magrittr
+Imports: dplyr, lubridate, assertthat, magrittr, threadr, utils
 RoxygenNote: 7.0.0
 Suggests: 
     knitr,

R/FluxCal.R

@@ -3,7 +3,7 @@
 #' @description A function to calculate CO2 and CH4 gas fluxes from the data loaded by the function \code{\link{LoadLGR}}
 #' or \code{\link{LoadOther}}.
 #' It takes a time cue data frame (argument \code{df_cue}), either created by the function \code{\link{SelCue}} or prepared by the
-#' user following the format of example files "Time & Ta_1.csv" and "Time & Ta_2.csv" at
+#' user following the format of example files "Time_&_Ta_1.csv" and "Time_&_Ta_2.csv" at
 #'  https://github.com/junbinzhao/FluxCalR/tree/master/inst/extdata
 #' to separate the measurements and then calculate the fluxes for all the measurements at once.
 #' Note that the header for the time cue column must be either \strong{"Start"} or \strong{"End"}.
@@ -20,7 +20,7 @@
 #' @param df_cue A data frame that includes "Start" and/or "End" time (HH:MM:SS) of each measurement.
 #' The header for the time must be either \strong{"Start"} or \strong{"End"}. This data frame can either be created by the
 #' function \code{\link{SelCue}} or be prepared by the user
-#' (see example files "Time & Ta_1.csv" and "Time & Ta_2.csv" at https://github.com/junbinzhao/FluxCalR/tree/master/inst/extdata).
+#' (see example files "Time_&_Ta_1.csv" and "Time_&_Ta_2.csv" at https://github.com/junbinzhao/FluxCalR/tree/master/inst/extdata).
 #' @param cue_type A string, either "Start", "End" (default) or "Start_End", indicates if start, end or both time in the
 #' data frame assigned to \code{df_cue} will be used as the cues . When "Start_End" is chosen, both "Start" and "End" columns
 #' have to be present in the data frame for \code{df_cue} and the flux with the largest R2 within the range will be calculated
@@ -29,7 +29,7 @@
 #' that need to be passed along to the final output data frame. Default: NULL.
 #' @param df_Ta A data frame contains a column "Ta" with the air temperature values (ideally, this is temperature measured inside
 #'  of the chamber during the flux measurement; unit: degree C. This can be the same data frame as in \code{df_cue}.
-#'  See example files "Time & Ta_1.csv" and "Time & Ta_2.csv" at https://github.com/junbinzhao/FluxCalR/tree/master/inst/extdata).
+#'  See example files "Time_&_Ta_1.csv" and "Time_&_Ta_2.csv" at https://github.com/junbinzhao/FluxCalR/tree/master/inst/extdata).
 #'  Note the row number of the data frame must be the same as the number of flux measurements.
 #' Default: NULL, then the temperature used is either the average ambient air temperature measured by the LGR analyzer
 #' (column "AmbT_C") or, if the data measured by other analyzers, Ta input from function \code{\link{LoadOther}}.
@@ -77,7 +77,7 @@
 #' Flux_output1
 #'
 #' # input the time cues from a prepared file and calculate the fluxes over a 3-minute window
-#' Example_cue1 <- system.file("extdata", "Time & Ta_1.csv", package = "FluxCalR") # directory of the file with time cues and Ta
+#' Example_cue1 <- system.file("extdata", "Time_&_Ta_1.csv", package = "FluxCalR") # directory of the file with time cues and Ta
 #' Time_Ta1 <- read.csv(Example_cue1)
 #' head(Time_Ta1)
 #' Flux_output2 <- FluxCal(data = Flux_lgr,
@@ -102,7 +102,7 @@
 #'                         Ta = "Tem_C")
 #'
 #' # input the time cues from a prepared file and calculate the fluxes over a 3-minute window
-#' Example_cue2 <- system.file("extdata", "Time & Ta_2.csv", package = "FluxCalR") # directory of the file with time cues and Ta
+#' Example_cue2 <- system.file("extdata", "Time_&_Ta_2.csv", package = "FluxCalR") # directory of the file with time cues and Ta
 #' Time_Ta2 <- read.csv(Example_cue2)
 #' head(Time_Ta2)
 #' Flux_output3 <- FluxCal(data = Flux_other,
@@ -171,7 +171,7 @@ FluxCal <- function(data,
   if (cue_type == "End"){ ### if end time is given
     df_cue$End <- lubridate::ymd_hms(paste(date_m,df_cue$End,sep = "_")) # add date of measurement to time cues
     # match the closest
-    for(i in 1:nrow(df_cue)){
+    for(i in seq_len(nrow(df_cue))){
       In[i] <- threadr::which_closest(data$Time,df_cue$End[i])
     }
     In1 <- In # start moving
@@ -186,7 +186,7 @@ FluxCal <- function(data,
     if (cue_type == "Start"){ ### if start time is given
       df_cue$Start <- lubridate::ymd_hms(paste(date_m,df_cue$Start,sep = "_")) # add date of measurement to time cues
       # match the closest
-      for(i in 1:nrow(df_cue)){
+      for(i in seq_len(nrow(df_cue))){
         In[i] <- threadr::which_closest(data$Time,df_cue$Start[i])
       }
       In1 <- In+ext*win_f
@@ -201,14 +201,14 @@ FluxCal <- function(data,
       df_cue$End <- lubridate::ymd_hms(paste(date_m,df_cue$End,sep = "_")) # add date of measurement to time cues
       df_cue$Start <- lubridate::ymd_hms(paste(date_m,df_cue$Start,sep = "_"))
       # match the closest
-      for(i in 1:nrow(df_cue)){
+      for(i in seq_len(nrow(df_cue))){
         In[i] <- threadr::which_closest(data$Time,df_cue$End[i])
       }
       In1 <- In
       # recycle In
       In <- vector()
       #
-      for(i in 1:nrow(df_cue)){
+      for(i in seq_len(nrow(df_cue))){
         In[i] <- threadr::which_closest(data$Time,df_cue$Start[i])
       }
       In2 <- In+win_f
@@ -235,7 +235,7 @@ FluxCal <- function(data,
     dft <- data.frame(matrix(0,nrow(df_cue),9)) # for record the data
     names(dft) <- c("Num","Date","Start","End","Gas","Slope","R2","Ta","Index")
     ########## 1. calculate the max R2 and slopes of the regression winthin the window with an extended range
-    for (a in 1:nrow(df_cue)){
+    for (a in seq_len(nrow(df_cue))){
       # the window is moving backwards from the end point
       for (b in In1[a]:In2[a]){
         if (flux == "CO2"){ # for CO2
@@ -307,7 +307,7 @@ FluxCal <- function(data,
                xlab="Time",bty="n", xaxt="n",
                ylim=ylim),silent=TRUE)
       # plot the regression lines
-      for (i in 1:nrow(dft)){
+      for (i in seq_len(nrow(dft))){
         Slm <- try(lm(data[(dft[i,"Index"]-win_f):dft[i,"Index"],var]~
                         data$Row[(dft[i,"Index"]-win_f):dft[i,"Index"]]),silent=TRUE)
         try(lines(data$Row[(dft[i,"Index"]-win_f):dft[i,"Index"]], Slm$fitted.values,
@@ -330,10 +330,10 @@ FluxCal <- function(data,
   ###### calculate the flux using the function and, if required, output the file and plot the result ------------------
   if (check_plot == TRUE){ # if the checking plot is needed, create a window for plotting
     if (cal == "CO2_CH4"){ # both CO2 and CH4 are calculated, plot 2 graphs
-      x11(width = 16,height = 12)
+      dev.new(width = 16,height = 12,noRStudioGD=TRUE)
       par(mfrow=c(2,1),mar=c(2,1,2,1),xpd=NA,oma=c(4,4,1,1))
     } else { # only CO2 or CH4 is calculated, plot 1 graph
-      x11(width = 16,height = 5)
+      dev.new(width = 16,height = 5,noRStudioGD=TRUE)
       par(mar=c(0.5,1,0.5,1),xpd=NA,oma=c(4,4,1,1))
     }
   }
@@ -349,7 +349,7 @@ FluxCal <- function(data,
   }
   # check if the data frame needs to be output as a file
   if (assertthat::is.string(output)){
-    write.csv(dfoutput,file = output,row.names = F)
+    utils::write.csv(dfoutput,file = output,row.names = F)
   }
 
   return(dfoutput)

R/Load.R

@@ -6,7 +6,7 @@
 #'
 #' @param file A string contains the directory path and file name of the raw data.
 #' The data should be provided as what is exported from the LGR analyzer.
-#' @param Time_format A string indicates the format of timestamps. Default: "mdy_HMS".
+#' @param time_format A string indicates the format of timestamps. Default: "mdy_HMS".
 #' It also takes the format "dmy_HMS" or "ymd_HMS", depending on the timestamps output from the analyzer.
 #'
 #' @return A data frame with all data in the right format for the functions \code{\link{SelCue}} and \code{\link{FluxCal}}.
@@ -26,7 +26,7 @@ LoadLGR <- function(file,
   # argument check
   time_format <- match.arg(time_format,c("mdy_HMS","dmy_HMS","ymd_HMS"))
   # Load the raw data after deleting the text massages at the beginning and the end of each raw data file generate by LGR
-  flux <- read.table(file, sep= ",", header = TRUE,skip = 1,fill = TRUE,stringsAsFactors = FALSE)
+  flux <- utils::read.table(file, sep= ",", header = TRUE,skip = 1,fill = TRUE,stringsAsFactors = FALSE)
   flux <- subset(flux,!is.na(flux[,2])) # remove the comments generated by LGR
   # replace the time with "lubridated" time with different format
   flux$Time <- try(suppressWarnings(lubridate::parse_date_time(flux$Time,orders = time_format)),
@@ -94,7 +94,7 @@ LoadOther <- function(file,
   # define the pipe from the package "magrittr"
   `%>%` <- magrittr::`%>%`
   # Load the raw data after deleting the text massages at the beginning and the end of each raw data file
-  flux1 <- read.table(file, sep= sep, header = TRUE,skip = skip,fill = TRUE,stringsAsFactors = FALSE,...)
+  flux1 <- utils::read.table(file, sep= sep, header = TRUE,skip = skip,fill = TRUE,stringsAsFactors = FALSE,...)
   flux1 <- subset(flux1,!is.na(flux1[,2])) # remove the comments generated by analyzer
   # replace the time with "lubridated" time with different format
   if (time_format=="HMS"){ # if only time is provided, then combine the time with date first

R/Select time cues.R R/Select_time_cues.R

@@ -4,7 +4,7 @@
 #' clicking the corresponding start or end measurement points on the interactive graphs generated by the function.
 #' The data frame returned from this function can be assigned to the argument \code{df_cue} in the \code{\link{FluxCal}} function.
 #' Note that the time cue data frame can also be prepared by the user independent of this function following the format of
-#' "Time & Ta_1.csv" and "Time & Ta_2.csv" at https://github.com/junbinzhao/FluxCalR/tree/master/inst/extdata).
+#' "_1.csv" and "_2.csv" at https://github.com/junbinzhao/FluxCalR/tree/master/inst/extdata).
 #'
 #' @param data A dataframe generated by the function \code{\link{LoadLGR}} or \code{\link{LoadOther}}.
 #'
@@ -81,7 +81,7 @@ SelCue <- function(data,
   # plot flux vs time for locating the peaks and valleys
   In <- c() # create a variable as Index
   for (i in 1:spt){
-    x11(width = 16,height = 10)
+    dev.new(width = 16,height = 10,noRStudioGD=TRUE)
     with(data[c(((i-1)*nr/spt)+1):c(i*nr/spt),],
          plot(Time,flux_plot,
               ylab = ylab,
@@ -110,7 +110,7 @@ SelCue <- function(data,
 
   # output the time cues if necessary
   if (assertthat::is.string(save)){
-    write.csv(Time_q,file = save,row.names = F)
+    utils::write.csv(Time_q,file = save,row.names = F)
   }
   return(Time_q)
 }

README.Rmd

@@ -48,7 +48,7 @@ Then, install the `FluxCalR` package (with vignettes) in R by:
 ```r
 remotes::install_github("junbinzhao/FluxCalR",build_vignettes = TRUE)
 ```
-The functioning of the package is based on other R packages: `dplyr`, `lubridate`, `assertthat`, `magrittr` and they will/must be installed before using the functions in the `FluxCalR` package.
+The functioning of the package is based on other R packages: `dplyr`, `lubridate`, `assertthat`, `magrittr`,`threadr` and they will/must be installed before using the functions in the `FluxCalR` package.
 
 *Note: in case the installation fails in Rstudio, try to install the package in the original R program and then load the package in Rstudio.* 
 
@@ -93,7 +93,7 @@ knitr::include_graphics("vignettes/images/timecue.png") # add time cue graph wit
 time_cue <- read.csv("vignettes/Time_cue.csv")
 ```
 
-This is how the "time_cue" data frame looks like. Instead of having it created by the function `SelCue()`, one can also manually prepare such a file and load it into R as a data frame. But the column name ("End" or "Start") and time format must be in line with the "time_cue" here, or see example files "Time & Ta_1.csv" and "Time & Ta_2.csv" at https://github.com/junbinzhao/FluxCalR/tree/master/inst/extdata).  
+This is how the "time_cue" data frame looks like. Instead of having it created by the function `SelCue()`, one can also manually prepare such a file and load it into R as a data frame. But the column name ("End" or "Start") and time format must be in line with the "time_cue" here, or see example files "Time_&_Ta_1.csv" and "Time_&_Ta_2.csv" at https://github.com/junbinzhao/FluxCalR/tree/master/inst/extdata).  
 
 ```{r}
 time_cue

README.md

@@ -99,8 +99,8 @@ remotes::install_github("junbinzhao/FluxCalR",build_vignettes = TRUE)
 ```
 
 The functioning of the package is based on other R packages: `dplyr`,
-`lubridate`, `assertthat`, `magrittr` and they will/must be installed
-before using the functions in the `FluxCalR` package.
+`lubridate`, `assertthat`, `magrittr`,`threadr` and they will/must be
+installed before using the functions in the `FluxCalR` package.
 
 *Note: in case the installation fails in Rstudio, try to install the
 package in the original R program and then load the package in Rstudio.*
@@ -130,7 +130,7 @@ library(FluxCalR)
 # get the directory of the example LGR raw data
 example_data1 <- system.file("extdata", "Flux_example_1_LGR.txt", package = "FluxCalR")
 example_data1 # check the directory
-#> [1] "C:/Users/Zhao/Documents/R/win-library/3.6/FluxCalR/extdata/Flux_example_1_LGR.txt"
+#> [1] "C:/Users/juzh/Documents/R/R-3.6.1/library/FluxCalR/extdata/Flux_example_1_LGR.txt"
 
 # load the data
 Flux_lgr <- LoadLGR(file = example_data1,
@@ -158,7 +158,7 @@ This is how the “time\_cue” data frame looks like. Instead of having it
 created by the function `SelCue()`, one can also manually prepare such a
 file and load it into R as a data frame. But the column name (“End” or
 “Start”) and time format must be in line with the “time\_cue” here, or
-see example files “Time & Ta\_1.csv” and “Time & Ta\_2.csv” at
+see example files "Time\_&*Ta\_1.csv" and "Time*&\_Ta\_2.csv" at
 <https://github.com/junbinzhao/FluxCalR/tree/master/inst/extdata>).
 
 ``` r
@@ -213,7 +213,7 @@ head(Flux_output1)
 #> 3   3 2016-11-21 12:20:08 12:23:12 CO2  0.019 0.97 31.57  0.608
 #> 4   4 2016-11-21 12:25:19 12:28:23 CO2  0.017 0.95 32.11  0.543
 #> 5   5 2016-11-21 12:34:04 12:37:09 CO2  0.009 0.79 32.84  0.287
-#> 6   6 2016-11-21 12:39:21 12:42:25 CO2  0.050 0.99 33.20  1.591
+#> 6   6 2016-11-21 12:39:20 12:42:24 CO2  0.050 0.99 33.20  1.591
 ```
 
 For more details of the functions and examples, please check the