R/UniDesc.R

In BrailleR: Improved Access for Blind Users

UniDesc =
    function(
        Response = NULL, ResponseName = as.character(match.call()$Response),
        Basic = TRUE, Graphs = TRUE, Normality = TRUE, Tests = TRUE,
        Title = NULL, Filename = NULL, Folder = ResponseName, Process = TRUE,
        VI = getOption("BrailleR.VI"), Latex = getOption("BrailleR.Latex"),
        View = getOption("BrailleR.View"),
        PValDigits = getOption("BrailleR.PValDigits")) {

      if (is.null(Response)) {
        if (length(ResponseName) == 0)
          .NoResponse() 
        Response = get(ResponseName)
      }

      if(VI){
        VIOpenText = "VI("
        VICloseText = ")"
        }
      else {
        VIOpenText = ""
        VICloseText = ""
        }


      if(Latex){
        LatexOpenText = "VI("
        LatexCloseText = ")"
        }
      else {
        LatexOpenText = ""
        LatexCloseText = ""
        }


      # to ensure consistent and predictable appearance
      StartChunk =
          function(ChunkName, ThisFile = Filename) {
            cat('\n```{r', ChunkName, '}   \n', file = ThisFile, append = TRUE)
          }
      CloseChunk = function(ThisFile = Filename) {
                     cat('\n```   \n\n', file = ThisFile, append = TRUE)
                   }
      GraphHead = function(GraphName, AltTag, ThisFile = Filename) {
                    cat(paste0('\n```{r ', GraphName, ', fig.cap="', AltTag,
                               '", fig.height=5}    \n'), file = ThisFile,
                        append = TRUE)
                  }
      GraphHeadSq =
          function(GraphName, AltTag, ThisFile = Filename) {
            cat(paste0('\n```{r ', GraphName, ', fig.cap="', AltTag,
                       '", fig.height=7}  \n'), file = ThisFile, append = TRUE)
          }
      GraphHeadWide = function(GraphName, AltTag, ThisFile = Filename) {
                        cat(paste0('\n```{r ', GraphName, ', fig.cap="', AltTag,
                                   '", fig.height=3.5}  \n'), file = ThisFile,
                            append = TRUE)
                      }

      # to avoid errors for missing folders
      if (Graphs || Latex) {
        if (Folder != "." && !file.exists(Folder)) dir.create(Folder)
      }

      # make sure there is a filename to write the markdown to.
      if (is.null(Filename)) {
        Filename = paste0(.simpleCap(ResponseName), "-UniDesc.Rmd")
      }


      # Start writing mark down here.
      if (is.null(Title)) {
        Title = paste0('Univariate analysis for ', .simpleCap(ResponseName))
      }

      cat('#', Title, '
#### Prepared by', getOption("BrailleR.Author"),
          '  \n\n', file = Filename)

      cat(paste0(
              '```{r setup, purl=FALSE, include=FALSE}
library(BrailleR)
opts_chunk$set(dev=c("png", "pdf", "postscript", "svg"))
opts_chunk$set(comment="", echo=FALSE, fig.path="',
              Folder, '/', .simpleCap(ResponseName),
              '-", fig.width=7)
```  

<!--- IMPORTANT NOTE: This Rmd file does not yet import the data it uses. 
You will need to add a data import command of some description into the next R chunk to use the file as a stand alone file. --->

```{r importData}
```\n\n'), file = Filename, append = TRUE)


      if (Basic) {
        cat(paste0(
                '## Basic summary measures

```{r BasicSummaries}
',
                ResponseName,
                '.count = length(',
                ResponseName,
                ')
',
                ResponseName,
                '.unique = length(unique(',
                ResponseName,
                '))
',
                ResponseName,
                '.Nobs = sum(!is.na(',
                ResponseName,
                '))
',
                ResponseName,
                '.Nmiss = sum(is.na(',
                ResponseName,
                '))
',
                ResponseName,
                '.mean = mean(',
                ResponseName,
                ', na.rm = TRUE)
',
                ResponseName,
                '.tmean5 = mean(',
                ResponseName,
                ', trim =0.025, na.rm = TRUE)
',
                ResponseName,
                '.tmean10 = mean(',
                ResponseName,
                ', trim =0.05, na.rm = TRUE)
',
                ResponseName,
                '.IQR = IQR(',
                ResponseName,
                ', na.rm = TRUE)
',
                ResponseName,
                '.sd = sd(',
                ResponseName,
                ', na.rm = TRUE)
',
                ResponseName,
                '.var = var(',
                ResponseName,
                ', na.rm = TRUE)
',
                ResponseName,
                '.skew = moments::skewness(',
                ResponseName,
                ', na.rm = TRUE)
',
                ResponseName,
                '.kurt = moments::kurtosis(',
                ResponseName,
                ', na.rm = TRUE)
```

### Counts

`r ',
                ResponseName,
                '.count` values in all, made up of
`r ',
                ResponseName,
                '.unique` unique values,
`r ',
                ResponseName,
                '.Nobs` observed, and
`r ',
                ResponseName,
                '.Nmiss` missing values.   \n\n

### Measures of location

Data | all | 5% trimmed | 10% trimmed
----- | ------ | ----- | ------
Mean | `r ',
                ResponseName,
                '.mean` | `r ',
                ResponseName,
                '.tmean5` | `r ',
                ResponseName,
                '.tmean10`

### Quantiles

```{r Quantiles1}
Quantiles=quantile(',
                ResponseName,
                ', na.rm=TRUE)
QList=c("Minimum", "Lower Quartile", "Median", "Upper Quartile", "Maximum")
Results=data.frame(Quantile=QList, Value=Quantiles[1:5])
```

```{r QuantilesPrint, eval=FALSE}
Results
```

```{r QuantilesKable, results="asis", purl=FALSE}
kable(Results, digits=4)
```

### Measures of spread

Measure | IQR | Standard deviation | Variance
-------- | ------ | -------- | ------
Value | `r ',
                ResponseName,
                '.IQR` | `r ',
                ResponseName,
                '.sd` | `r ',
                ResponseName,
                '.var`   \n\n'), file = Filename, append = TRUE)

        if (!Tests) {
          cat(paste0(
                  '### Other moments

Moment | Skewness | Kurtosis
-------- | ------ | ------
Value | `r ',
                  ResponseName, '.skew` | `r ', ResponseName, '.kurt`   \n\n'),
              file = Filename, append = TRUE)
        }
      }

      if (Graphs) {
        cat("\n## Basic univariate graphs    \n### Histogram    \n",
            file = Filename, append = TRUE)
        GraphHead("Hist", "The histogram")
        cat(paste0(VIOpenText, 'hist(', ResponseName, ', xlab="',
                   ResponseName, '", main="Histogram of ',
                   .simpleCap(ResponseName), '")', VICloseText),
            file = Filename, append = TRUE)
        CloseChunk()

        cat("\n### Boxplot    \n", file = Filename, append = TRUE)
        GraphHeadWide("Boxplot", "The boxplot")
        cat(paste0(VIOpenText, 'boxplot(', ResponseName,
                   ', horizontal=TRUE, main = "Boxplot of ',
                   .simpleCap(ResponseName), '")', VICloseText),
            file = Filename, append = TRUE)
        CloseChunk()

        #cat("\n### Density plot    \n", file=Filename, append=TRUE)
        #GraphHead("Density")
        #cat(paste0('density(', ResponseName, ', na.rm=TRUE, main = "Density plot for ', .simpleCap(ResponseName), '")'), file=Filename, a#ppend=TRUE)
        #CloseChunk()
        #MyDensity=plot(density(x, xlab=ResponseName)
        #cat(paste0("The title put on this density plot was: Density plot of",ResponseName,"\n"))
        #cat(paste0("The x-axis for this density plot was given the label:",ResponseName,"\n"))
        #VI(MyDensity)

      }  # end of basic graphs section

      if (Normality) {
        cat(paste0(
                '\n## Assessing normality

### Formal tests for normality

```{r NormalityTests}
library(nortest)
Results = matrix(0, nrow=6, ncol=2)
dimnames(Results) = list(c("Shapiro-Wilk", "Anderson-Darling", "Cramer-von Mises",
"Lilliefors (Kolmogorov-Smirnov)", "Pearson chi-square", "Shapiro-Francia"), c("Statistic", "P Value"))
 SW =shapiro.test(',
                ResponseName,
                ')
Results[1,] = c(SW$statistic, SW$p.value)
AD = ad.test(',
                ResponseName,
                ')
Results[2,] = c(AD$statistic, AD$p.value)
CV = cvm.test(',
                ResponseName,
                ')
Results[3,] = c(CV$statistic, CV$p.value)
LI = lillie.test(',
                ResponseName,
                ')
Results[4,] = c(LI$statistic, LI$p.value)
PE = pearson.test(',
                ResponseName,
                ')
Results[5,] = c(PE$statistic, PE$p.value)
SF = sf.test(',
                ResponseName,
                ')
Results[6,] = c(SF$statistic, SF$p.value)
```

```{r NormalityTestsPrint, eval=FALSE}
Results
```

```{r NormalityTestsKable, results="asis", purl=FALSE}
kable(Results, digits=c(4,',
                PValDigits, '))
```   \n'), file = Filename, append = TRUE)

        if (Latex) {
          cat(paste0(
                  '```{r NormalityTestsTex, purl=FALSE}
library(xtable)
ThisTexFile = "',
                  Folder, "/", ResponseName,
                  '-Normality.tex"
TabCapt= "Tests for normality: Variable is ',
                  ResponseName,
                  '."
print(xtable(Results, caption=TabCapt, label=\"',
                  ResponseName,
                  'Normality", digits=4, align="lrr"), file=ThisTexFile)
```   \n'),
              file = Filename, append = TRUE)
        }
      }  # end of normality test statistics section

      if (Graphs) {
        cat("\n### Normality plot    \n", file = Filename, append = TRUE)
        GraphHeadSq("NormPlot", "The normality plot")
        cat(paste0('qqnorm(', ResponseName, ', main = "Normality Plot for ',
                   .simpleCap(ResponseName), '")\nqqline(', ResponseName, ')'),
            file = Filename, append = TRUE)
        CloseChunk()
      }  # end of normality plot section

      if (Tests) {
        cat(paste0(
                '\n## Formal tests of moments

```{r MomentsTests}
library(moments)
Results = matrix(0, nrow=2, ncol=3)
dimnames(Results)= list(c( "D\'Agostino skewness", "Anscombe-Glynn kurtosis"),
 c("Statistic","Z",  "P Value"))
AG = moments::agostino.test(',
                ResponseName, ')
AN = moments::anscombe.test(', ResponseName,
                ')
Results[1,] = c(AG$statistic, AG$p.value)
Results[2,] = c(AN$statistic, AN$p.value)
```

```{r MomentsTestsPrint, eval=FALSE}
Results
```

```{r MomentsTests2, results="asis", purl=FALSE}
kable(Results, digits=c(4,3,',
                PValDigits, '))
```   \n\n'), file = Filename, append = TRUE)

        if (Latex) {
          cat(paste0(
                  '```{r MomentsTestsTex, purl=FALSE}
library(xtable)
ThisTexFile = "',
                  Folder, "/", ResponseName,
                  '-Moments.tex"
TabCapt= "Tests on moments: Variable is',
                  ResponseName,
                  '"
print(xtable(Results, caption=TabCapt, label=\"',
                  ResponseName,
                  'Moments", digits=4, align="lrrr"), file=ThisTexFile)
```   \n\n'),
              file = Filename, append = TRUE)
        }
      }  # end of formal tests of normality via moments section

      if (Process) {
        # finish writing markdown and process the written file into html and an R script
        knit2html(Filename, quiet = TRUE,
                meta = list(css = FindCSSFile(getOption("BrailleR.Style"))))
        file.remove(sub(".Rmd", ".md", Filename))
        purl(Filename, quiet = TRUE)
        if (View) browseURL(sub(".Rmd", ".html", Filename))
      }  # end of processing chunk
    }  # end of UniDesc function definition