test.Rmd

---
title: "Test"
author: "Ryo®, Eng Lian Hu"
date: "October 25, 2015"
output: 
  html_document: 
    fig_caption: yes
    highlight: haddock
    theme: cerulean
    toc: yes
  word_document: 
    fig_caption: yes
  pdf_document: 
    fig_caption: yes
    toc: yes
---


Testing output of the coding.

```{r load-packages, include=FALSE}
## Setup Options, Loading Required Libraries and Preparing Environment
## Setup `knitr` options and loading the required libraries.

## Setting to omit all warnings
options(warn=-1)

## Loading the packages
if(!suppressPackageStartupMessages(require('devtools'))){
  install.packages('devtools')}
if(!suppressPackageStartupMessages(require('BBmisc'))){
  install.packages('BBmisc')}
if(!suppressPackageStartupMessages(require('BiocParallel'))){
  devtools::install_github('Bioconductor/BiocParallel')}

suppressPackageStartupMessages(library('BBmisc'))
pkgs <- c('devtools','zoo','chron','stringr','stringi','reshape','reshape2','tbl_df','sparkline','data.table','DT','plyr','dplyr','magrittr','foreach','manipulate','ggplot2','ggthemes','proto','extrafont','directlabels','PerformanceAnalytics','plotly','doParallel','rvest','highlightHTML','knitr','rmarkdown','scales','lubridate','tidyr','whisker','gtable','grid','gridExtra','pander','arules','arulesViz','googleVis','rlist')
#'@ c('memoise','RStudioAMI','parallel','BiocParallel','RSelenium','doMC','editR') #load if needed
suppressAll(lib(pkgs)); rm(pkgs)
```

```{r setting}
## Creating a parallel computing Cluster and support functions.

## Preparing the parallel cluster using the cores
doParallel::registerDoParallel(cores = 16)

# Set the googleVis options first to change the behaviour of plot.gvis, so that only the chart component of the HTML file is written into the output file.
op <- options(gvis.plot.tag='chart')
```

```{r read-data-summary-table, results='asis'}
## Read the datasets
## Refer to **Testing efficiency of coding.Rmd** at chunk `get-data-summary-table-2.1`
source(paste0(getwd(),'/function/readfirmDatasets.R'))
source(paste0(getwd(),'/function/arrfirmDatasets.R'))
years <- 2011:2014

lProfile <- c(AH=0.10,OU=0.12)
mbase <- readfirmDatasets(years=years) %>% arrfirmDatasets(., lProfile=lProfile)
r <- range(mbase$datasets$Stakes)
```

```{r, echo=FALSE}
bar_string <- "type: 'bar', barColor: 'orange', negBarColor: 'purple', highlightColor: 'black'"

cb_bar = JS(paste0("function (oSettings, json) { $('.spark:not(:has(canvas))').sparkline('html', { ", bar_string, " }); }"), collapse = "")

line_string <- "type: 'line', lineColor: 'black', fillColor: '#ccc', highlightLineColor: 'orange', highlightSpotColor: 'orange'"

cb_line <- JS(paste0("function (oSettings, json) { $('.spark:not(:has(canvas))').sparkline('html', { ", line_string, ", chartRangeMin: ", r[1], ", chartRangeMax: ", r[2], " }); }"), collapse = "")

box_string <- "type: 'box', lineColor: 'black', whiskerColor: 'black', outlierFillColor: 'black', outlierLineColor: 'black', medianColor: 'black', boxFillColor: 'orange', boxLineColor: 'black'"

cb_box1 = JS(paste0("function (oSettings, json) { $('.spark:not(:has(canvas))').sparkline('html', { ", box_string, " }); }"), collapse = "")
cb_box2 = JS(paste0("function (oSettings, json) { $('.spark:not(:has(canvas))').sparkline('html', { ", box_string, ", chartRangeMin: ", r[1], ", chartRangeMax: ", r[2], " }); }"), collapse = "")
```
  
  Please refer to [Natural Language Analysis](http://rpubs.com/englianhu/natural-language-analysis) to see the firm A staking sample dataset.
  
```{r data-month-summary-plots, results='asis'}
## Before we start analyse the staking model, we are firstly see the monthly Stakes and Profit & Lose of the Agency A
## the stakes amount display as $1 = $10,000

dat <- mbase$datasets %>% mutate(Month=paste(month(Date,label=TRUE),year(Date))) %>% tbl_df
#'@ dat <- mbase$datasets %>% mutate(Month=month(ymd(Date), label=TRUE)) %>% tbl_df
m <- ddply(dat, .(Sess, Month), summarise, Stakes=sum(Stakes)/10000, PL=sum(PL)/10000) %>% tbl_df
#'@ melted <- melt(m, id.vars=c('Sess','Month')) %>% tbl_df

## http://help.plot.ly/make-a-3D-surface-plot
## Will doing research on 3D graph some other days.
gvis.options <- list(hAxis="{title:'Month'}", vAxis="{title:'Stakes'}",width='automatic', height='automatic')
line.gvis <- gvisLineChart(xvar='Month', yvar=c('Stakes','PL'), data=m, options=gvis.options)
plot(line.gvis)
#'@ print(line.gvis, tag='chart')
```

*graph 3.1.1*

```{r}
#'@ CityPopularity$Mean=mean(CityPopularity$Popularity)
#'@ plots <- gvisComboChart(CityPopularity, xvar='City', yvar=c('Mean', 'Popularity'), options=list(seriesType='bars', width=450, height=300, title='City Popularity', series='{0: {type:"line"}}'))
#'@ plot(plots)
```

```{r}
## aaaaaaaaaaaaaaa
#'@ plots <- gvisComboChart(m, xvar='Month', yvar=c('Stakes','PL'), options=list(seriesType='bars', width=450, height=300, title='Monthly Summary', series='{0: {type:"line"}}'))
#'@ plot(plots)
#'@ print(plots, tag='chart')
```

```{r, results='asis'}
## Set options back to original options
options(op)
```

## DT data tables

  Here is the full data table generated with DT. There are various feature options for data table html widgets in the browser using DT. See this introduction for details.

### DT

```{r, echo=FALSE}
dat <- mbase$datasets %>% mutate(Month=month(ymd(Date), label=TRUE)) %>% tbl_df
m <- ddply(dat, .(Sess, Month, Day), summarise, Stakes=sum(Stakes)/10000, PL=sum(PL)/10000) %>% tbl_df

m %>% select(Sess,Month,Day,Stakes) %>% datatable(.,caption="Table 3.1.1 : Annual Summary of Staking Data.",extensions=c('ColReorder','ColVis','TableTools'),options=list(dom='TC<"clear">rlfrtip',colVis=list(exclude=c(0),activate='mouseover'),tableTools=list(sSwfPath=copySWF(pdf=TRUE)),scrollX=TRUE,scrollCollapse=TRUE))
```

```{r, echo=FALSE}
## 12 columns which are counting from Jan until Dec
colDefs1 <- list(list(targets = c(1:12), render = JS("function(data, type, full){ return '<span class=spark>' + data + '</span>' }")))

## 4 columns which are counting the Soccer Session from 2011 untli 2014
colDefs2 <- list(list(targets = c(1:4), render = JS("function(data, type, full){ return '<span class=spark>' + data + '</span>' }")))
```

```{r,echo=FALSE}
dat.t <- m %>% group_by(Sess, Month) %>% summarise(Stakes = paste(Stakes, collapse = ",")) %>% tbl_df
dat.ta <- suppressAll(dcast(dat.t, Sess ~ Month)) %>% tbl_df
dat.tb <- suppressAll(dcast(dat.t, Month ~ Sess)) %>% tbl_df
```

### d1

```{r, echo=FALSE}
#'@ d1 <- dat.ta %>% datatable(.,caption="Table 3.1.1 : Annual Summary of Staking Data.",extensions=c('ColReorder','ColVis','TableTools'),options=list(dom='TC<"clear">rlfrtip',colVis=list(exclude=c(0),activate='mouseover'),tableTools=list(sSwfPath=copySWF(pdf=TRUE)),scrollX=TRUE,scrollCollapse=TRUE,columnDefs = colDefs2, fnDrawCallback = cb_bar))
#'@ d1 <- datatable(tbl_df(dat.ta), rownames = FALSE, options = list(columnDefs = colDefs1, fnDrawCallback = cb_line))

d1 <- dat.ta %>% data.table %>% datatable(., rownames=FALSE, options=list(columnDefs=colDefs1, fnDrawCallback=cb_line))
d1$dependencies <- append(d1$dependencies, htmlwidgets:::getDependency("sparkline"))
d1
```

### d2

```{r}
#'@ d2 <- dat.tb %>% datatable(.,caption="Table 3.1.1 : Annual Summary of Staking Data.",extensions=c('ColReorder','ColVis','TableTools'),options=list(dom='TC<"clear">rlfrtip',colVis=list(exclude=c(0),activate='mouseover'),tableTools=list(sSwfPath=copySWF(pdf=TRUE)),scrollX=TRUE,scrollCollapse=TRUE, options = list(columnDefs = colDefs2, fnDrawCallback = cb_line)))

#'@ d2 <- datatable(tbl_df(dat.tb), rownames = FALSE, options = list(columnDefs = colDefs2, fnDrawCallback = cb_bar))
d2 <- dat.tb %>% data.table %>% datatable(., rownames=FALSE, options=list(columnDefs=colDefs2, fnDrawCallback=cb_bar))
d2$dependencies <- append(d2$dependencies, htmlwidgets:::getDependency("sparkline"))
d2
```

Here I try to plot an inline graph `r sparkline(mbase$datasets$HKPrice, type='bar')` testing `r sparkline(mbase$datasets$netProbB)`... line `r sparkline(mbase$datasets$netProbB, type='line')`

```{r}
d3 <- datatable(data.table(dat.tb), rownames = FALSE, options = list(columnDefs = colDefs2, 
    fnDrawCallback = cb_box1))
d3$dependencies <- append(d3$dependencies, htmlwidgets:::getDependency("sparkline"))
d3
```

```{r}
d4 <- datatable(data.table(dat.tb), rownames = FALSE, options = list(columnDefs = colDefs2, 
    fnDrawCallback = cb_box2))
d4$dependencies <- append(d4$dependencies, htmlwidgets:::getDependency("sparkline"))
d4
```

```{r, echo=FALSE}
dat.t2 <- dat %>% group_by(Sess, Month, Day) %>% summarise(Mean = round(mean(Stakes), 1)/10000, SD = round(sd(Stakes), 2)/10000, Min = min(Stakes)/10000, Max = max(Stakes)/10000, Samples = paste(Stakes/10000, collapse = ",")) %>% mutate(Series = Samples) %>% tbl_df

cd <- list(list(targets=7, render=JS("function(data, type, full){ return '<span class=sparkSamples>' + data + '</span>' }")), list(targets=8, render=JS("function(data, type, full){ return '<span class=sparkSeries>' + data + '</span>' }")))

cb = JS(paste0("function (oSettings, json) {\n  $('.sparkSeries:not(:has(canvas))').sparkline('html', { ", line_string, " });\n  $('.sparkSamples:not(:has(canvas))').sparkline('html', { ", box_string, " });\n}"), collapse = "")
```

```{r}
d5 <- dat.t2 %>% datatable(., rownames = FALSE, options = list(columnDefs=cd, fnDrawCallback=cb))
d5$dependencies <- append(d5$dependencies, htmlwidgets:::getDependency("sparkline"))
d5
```

### res

```{r, echo=FALSE}
## Annual summary
res <- ldply(.data=split(mbase$datasets, mbase$datasets$Sess), summarise, S.total=sum(Stakes), S.median=median(Stakes), S.mean=mean(Stakes), S.sd=sd(Stakes), Count=length(PL), minHKPrcB=min(HKPrice), maxHKPrcB=max(HKPrice), minProbB=min(netProbB), maxProbB=max(netProbB), Return=sum(PL,Stakes), PL.Total=sum(PL), PL.percent=sum(PL)/sum(Stakes), S.box=as.character(paste(Stakes,collapse=','))) %>% tbl_df
##, S.graph=as.character(paste(x$Stakes,collapse=',', PL.box=paste(x$PL,collapse=','), PL.graph=paste(x$PL,collapse=','))))) %>% tbl_df
names(res)[1] <- 'Sess'

cd <- list(list(targets=12, render=JS("function(data, type, full){ return '<span class=sparkSamples>' + data + '</span>' }")), list(targets=13, render=JS("function(data, type, full){ return '<span class=sparkSeries>' + data + '</span>' }")))

cb = JS(paste0("function (oSettings, json) {\n  $('.sparkSeries:not(:has(canvas))').sparkline('html', { ", line_string, " });\n  $('.sparkSamples:not(:has(canvas))').sparkline('html', { ", box_string, " });\n}"), collapse = "")
```

```{r, echo=FALSE}
#'@ res %>% datatable(.,caption="Table 3.1.1 : Annual Summary of Staking Data.",extensions=c('ColReorder','ColVis','TableTools'),options=list(dom='TC<"clear">rlfrtip',colVis=list(exclude=c(0),activate='mouseover'),tableTools=list(sSwfPath=copySWF(pdf=TRUE)),scrollX=TRUE,scrollCollapse=TRUE,columnDefs=cd, fnDrawCallback=cb))

res %>% datatable(., rownames=FALSE, options=list(dom='t', scrollX=TRUE, scrollCollapse=TRUE, columnDefs=cd, fnDrawCallback=cb))
res$dependencies <- append(res$dependencies, htmlwidgets:::getDependency("sparkline"))
```