---
title: "Interactive timeline plots with vistime()"
date: "`r format(Sys.Date(), '%B %Y')`"
output: 
   prettydoc::html_pretty:
     theme: architect
     highlight: github
     toc: true
vignette: >
  %\VignetteIndexEntry{Interactive timeline plots with vistime()}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
library(vistime)
```

[![Buy Me A Coffee](https://i.imgur.com/xI5UtRm.png)](https://buymeacoffee.com/shosaco)
**Feedback welcome:** <a href = "mailto:sa.ra.online@posteo.de">sa.ra.online@posteo.de</a>


## 1. Basic example

`vistime()` produces **Plotly** charts. For interactive **Highcharts** output, see `hc_vistime()`, for static **ggplot2** charts, see `gg_vistime()`.

```{r vistime_basic_ex, warning=FALSE, fig.height=1, out.width="100%"}
library(vistime)

timeline_data <- data.frame(event = c("Event 1", "Event 2"), 
                            start = c("2020-06-06", "2020-10-01"), 
                            end = c("2020-10-01", "2020-12-31"), 
                            group = "My Events")

vistime(timeline_data)
```


## 2. Installation

To install the package from CRAN, type the following in your R console:

```{r eval=FALSE}
install.packages("vistime")
```

## 3. Usage and default arguments

The simplest way to create a timeline is by providing a data frame with `event` and `start` columns. If your columns are named otherwise, you need to tell the function. You can also tweak the y positions, linewidth, title, label visibility and number of lines in the background.

```{r eval = FALSE}
vistime(data, 
        col.event = "event", 
        col.start = "start",
        col.end = "end", 
        col.group = "group", 
        col.color = "color", 
        col.fontcolor = "fontcolor",
        col.tooltip = "tooltip", 
        optimize_y = TRUE, 
        linewidth = NULL, 
        title = NULL, 
        show_labels = TRUE, 
        background_lines = NULL)
```



## 4. Arguments

parameter | optional? | data type | explanation 
--------- |----------- | -------- | ----------- 
data | mandatory | data.frame | data.frame that contains the data to be visualized
col.event | optional | character | the column name in data that contains event names. Default: *event*
col.start | optional | character | the column name in data that contains start dates. Default: *start*
col.end | optional | character | the column name in data that contains end dates. Default: *end*
col.group | optional | character | the column name in data to be used for grouping. Default: *group*
col.color | optional | character | the column name in data that contains colors for events. Can be hex codes (e.g., *#FF0000*), named colors (e.g., *red*), or categorical data to be auto-colored. Default: *color*, if not present, colors are chosen via RColorBrewer.
col.fontcolor | optional | character | the column name in data that contains the font color for event labels. Default: *fontcolor*, if not present, color will be black.
col.tooltip | optional | character | the column name in data that contains the mouseover tooltips for the events. Default: *tooltip*, if not present, then tooltips are build from event name and date. [Basic HTML](https://plotly.com/chart-studio-help/adding-HTML-and-links-to-charts/#step-2-the-essentials) is allowed.
optimize_y | optional | logical | distribute events on y-axis by smart heuristic (default) or use order of input data.
linewidth | optional | numeric | override the calculated linewidth for events. Default: heuristic value.
title | optional | character | the title to be shown on top of the timeline. Default: empty.
show_labels | optional | logical | choose whether or not event labels shall be visible. Default: `TRUE`.
background_lines | optional | integer | the number of vertical lines to draw in the background to demonstrate structure. Default: heuristic.
source | optional | character | Information for `Plotly` to identify plot in Shiny Apps. Default: `A`.
customdata | optional | character | Custom data passed to click or hover event in Shiny.


## 5. Value

* `vistime` returns an object of class `plotly` and `htmlwidget`

## 6. Examples  

### Ex. 1: Presidents
```{r presidents example, fig.height=3, out.width="100%"}
pres <- data.frame(Position = rep(c("President", "Vice"), each = 3),
                   Name = c("Washington", rep(c("Adams", "Jefferson"), 2), "Burr"),
                   start = c("1789-03-29", "1797-02-03", "1801-02-03"),
                   end = c("1797-02-03", "1801-02-03", "1809-02-03"),
                   color = c('#cbb69d', '#603913', '#c69c6e'),
                   fontcolor = c("black", "white", "black"))
                  
vistime(pres, 
        col.event = "Position", 
        col.group = "Name", 
        title = "Presidents of the USA")
```


### Ex. 2: Project Planning
```{r project planning example, fig.height=5, out.width="100%"}
data <- read.csv(text="event,group,start,end,color
                       Phase 1,Project,2016-12-22,2016-12-23,#c8e6c9
                       Phase 2,Project,2016-12-23,2016-12-29,#a5d6a7
                       Phase 3,Project,2016-12-29,2017-01-06,#fb8c00
                       Phase 4,Project,2017-01-06,2017-02-02,#DD4B39
                       Room 334,Team 1,2016-12-22,2016-12-28,#DEEBF7
                       Room 335,Team 1,2016-12-28,2017-01-05,#C6DBEF
                       Room 335,Team 1,2017-01-05,2017-01-23,#9ECAE1
                       Group 1,Team 2,2016-12-22,2016-12-28,#E5F5E0
                       Group 2,Team 2,2016-12-28,2017-01-23,#C7E9C0
                       3-200,category 1,2016-12-25,2016-12-25,#1565c0
                       3-330,category 1,2016-12-25,2016-12-25,#1565c0
                       3-223,category 1,2016-12-28,2016-12-28,#1565c0
                       3-225,category 1,2016-12-28,2016-12-28,#1565c0
                       3-226,category 1,2016-12-28,2016-12-28,#1565c0
                       3-226,category 1,2017-01-19,2017-01-19,#1565c0
                       3-330,category 1,2017-01-19,2017-01-19,#1565c0
                       1-217.0,category 2,2016-12-27,2016-12-27,#90caf9
                       4-399.7,moon rising,2017-01-13,2017-01-13,#f44336
                       8-831.0,sundowner drink,2017-01-17,2017-01-17,#8d6e63
                       9-984.1,birthday party,2016-12-22,2016-12-22,#90a4ae
                       F01.9,Meetings,2016-12-26,2016-12-26,#e8a735
                       Z71,Meetings,2017-01-12,2017-01-12,#e8a735
                       B95.7,Meetings,2017-01-15,2017-01-15,#e8a735
                       T82.7,Meetings,2017-01-15,2017-01-15,#e8a735")
                           
vistime(data)
```


### Ex. 3: Gantt Charts

The argument `optimize_y` can be used to change the look of the timeline. `TRUE` (the default) will find a nice heuristic to save `y`-space, distributing the events:

```{r gantt_true, fig.height=1.8, out.width="100%"}
data <- read.csv(text="event,start,end
                       Phase 1,2020-12-15,2020-12-24
                       Phase 2,2020-12-23,2020-12-29
                       Phase 3,2020-12-28,2021-01-06
                       Phase 4,2021-01-06,2021-02-02")
        
vistime(data, optimize_y = TRUE, linewidth = 25)
```



`FALSE` will plot events as-is, not saving any space:

```{r gantt_false, fig.height=2.5, out.width="100%"}
vistime(data, optimize_y = FALSE, linewidth = 25)
```



## 7. Export of vistime as PDF or PNG

Once created, you can use `plotly::export()` for saving your vistime chart  as PDF, PNG or JPEG:

```{r eval=FALSE}
# webshot::install_phantomjs()
chart <- vistime(pres, col.event = "Position")
plotly::export(chart, file = "presidents.pdf")
```

Note that export requires the `webshot` package and `phantomjs` on your OS. Additional arguments like width or height can be used (`?webshot` for the details). You can also download the plot as PNG by using the toolbar on the upper right side of the generated plot.

## 8. Usage in Shiny apps

- `vistime()` objects can be integrated into [Shiny](https://shiny.posit.co/) via `plotlyOutput()` and `renderPlotly()`. Using the arguments `source` and `customdata`, information can be passed to the click event.


```{r eval=FALSE}
library(vistime)
library(shiny)
library(plotly)

pres <- data.frame(Position = rep(c("President", "Vice"), each = 3),
                   Name = c("Washington", rep(c("Adams", "Jefferson"), 2), "Burr"),
                   start = c("1789-03-29", "1797-02-03", "1801-02-03"),
                   end = c("1797-02-03", "1801-02-03", "1809-02-03"),
                   color = c('#cbb69d', '#603913', '#c69c6e'),
                   fontcolor = c("black", "white", "black"))

shinyApp(
  ui = basicPage("",
                 mainPanel(plotlyOutput("my_plot"),
                           verbatimTextOutput("clicked_info"))),
  server = function(input, output) {
    output$my_plot <- plotly::renderPlotly({
      vistime(pres, col.event = "Position", col.group = "Name", source = "my_plot", customdata = "some_information")
    })
    
    output$clicked_info <- renderPrint({
            click_data <- event_data("plotly_click", source = "my_plot")
            req(click_data)
            message("CLICK!")
            click_data
        })
  }
)
```

## 9. Customization

### Using `plotly::layout()`

See `?plotly::layout` and the official [Plotly API reference](https://plotly.com/r/reference/#Layout_and_layout_style_objects) for details. 

```{r plotly_customization, fig.height=2.5, out.width="100%", message=FALSE}
library(plotly)

p2 <- vistime(data,
              optimize_y = T, 
              col.group = "event",
              title = "Plotly customization example")

p2 %>% layout(xaxis=list(fixedrange=TRUE, tickfont=list(size=30, color="violet")), 
              yaxis=list(fixedrange=TRUE, tickfont=list(size=30, color="red"), tickangle=30,
                         mirror = FALSE, range = c(0.7, 3.5), showgrid = T),
              plot_bgcolor = "lightgreen") 
```

### List manipulation

#### Changing x-axis tick font size
The following example creates the presidents example and manipulates the font size of the x axis ticks:

```{r plotly_build1, fig.height=3, out.width="100%"}
pres <- data.frame(Position = rep(c("President", "Vice"), each = 3),
                   Name = c("Washington", rep(c("Adams", "Jefferson"), 2), "Burr"),
                   start = c("1789-03-29", "1797-02-03", "1801-02-03"),
                   end = c("1797-02-03", "1801-02-03", "1809-02-03"),
                   color = c('#cbb69d', '#603913', '#c69c6e'),
                   fontcolor = c("black", "white", "black"))
 
p <- vistime(pres, 
             col.event = "Position",
             col.group = "Name", 
             title = "Presidents of the USA")

# step 1: transform into a list
pp <- plotly::plotly_build(p)

# step 2: change the font size
pp$x$layout$xaxis$tickfont <- list(size = 28)

pp
```

#### Changing y-axis tick font size
We need to change the font size of the y-axis:

```{r plotly_build2, fig.height=3, out.width="100%"}
pp$x$layout[["yaxis"]]$tickfont <- list(size = 28)
pp
```


#### Changing events font size
The following example creates the presidents example and manipulates the font size of the events:

```{r plotly_build3, fig.height=3, out.width="100%"}
pres <- data.frame(Position = rep(c("President", "Vice"), each = 3),
                    Name = c("Washington", rep(c("Adams", "Jefferson"), 2), "Burr"),
                    start = c("1789-03-29", "1797-02-03", "1801-02-03"),
                    end = c("1797-02-03", "1801-02-03", "1809-02-03"),
                    color = c('#cbb69d', '#603913', '#c69c6e'),
                    fontcolor = c("black", "white", "black"))
 
p <- vistime(pres, 
             col.event = "Position",
             col.group = "Name", 
             title = "Presidents of the USA",
             linewidth=30)

# step 1: transform into a list
pp <- plotly::plotly_build(p)

# step 2: loop over pp$x$data, and change the font size of all text elements to 28
for(i in seq_along(pp$x$data)){
    if(pp$x$data[[i]]$mode == "text") pp$x$data[[i]]$textfont$size <- 28
}

#' # or, using purrr:
#' text_idx <- which(purrr::map_chr(pp$x$data, "mode") == "text")
#' for(i in text_idx) pp$x$data[[i]]$textfont$size <- 28
#' pp

pp
```


#### Changing marker size
The following example a simple example using markers and manipulates the size of the markers:

```{r plotly_build4, fig.height=2, out.width="100%"}
dat <- data.frame(event = 1:4, start = c("2019-01-01", "2019-01-10"))
 
p <- vistime(dat)

# step 1: transform into a list
pp <- plotly::plotly_build(p)

# step 2: loop over pp$x$data, and change the marker size of all text elements to 50px
for(i in seq_along(pp$x$data)){
    if(pp$x$data[[i]]$mode == "markers") pp$x$data[[i]]$marker$size <- 20
}

# or, using purrr:
# marker_idx <- which(purrr::map_chr(pp$x$data, "mode") == "markers")
# for(i in marker_idx) pp$x$data[[i]]$marker$size <- 20
# pp

pp

```

