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#' Recursive If-Then-Else Evaluation.
#' 
#' This function will recursively evaluate conditions, element-by-element, and 
#' apply specified actions for the elements that satisfy the conditions. Each
#' \code{condition~action} pair is specified by a formula, with the condition as
#' left-hand side and action as right-hand side. Each condition is evaluated 
#' sequentially and only to the relevant elements. This means that if an element
#' satisfies an early condition, it will never reach a later condition test.
#' The final argument is a one-sided formula with only an action applied to the
#' elements that do not satisfy any of the conditions (a default).

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library(shiny)

ol <- function(...) tag("ol", list(...))
li <- function(...) tag("li", list(...))

carousel_events <- function(id) 
{
  js <- sprintf("
    $('#%s').bind('slide.bs.carousel', function (e) { 
      $(e.relatedTarget).find('.shiny-bound-output').each(function(i) {

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# Contents of test.R:
#
#  library(ggplot2)
#
#  my_plot  <- qplot(Sepal.Length, Sepal.Width, data = iris)
#  my_plot2 <- qplot(Petal.Length, Petal.Width, data = iris)
#

```R
> import::from(test.R, my_plot)

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### 
###  This is an approach to string interpolation in R.
###  First a few utility functions, then the actual function (stringterpolate): A shorter name 
###  is probably desirable. Finally a few examples to show its use. 
###

#' Utility Function for Matching a Closing Brace
#' 
#' Given positions of opening and closing braces \code{match_brace} identifies
#' the closing brace matching the first opening brace.

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library(loggr) # should be executed before sourcing the script

log_file("all.log")
log_file("messages.log", DEBUG, INFO, .warning = FALSE, .error = FALSE)
log_file("console", WARN, ERROR, CRITICAL, .message = FALSE)

top_n <- function(data_set, sort_var, n = 3, desc = FALSE)
{
  if (!is.data.frame(data_set))
    log_critical("Invalid data_set provided.")

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# a few utility funcs, might as well take them from `import`
import::here(symbol_list, symbol_as_character, .from = import)

copy_from <- function(.from, ...)
{
  symbols <- symbol_list(...)
  parent  <- parent.frame()
  from    <- symbol_as_character(substitute(.from))

  for (s in seq_along(symbols)) {

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# Allow for V(g) %$% color or g %>% V %$% color
# 
# Since %$% uses the generic `with` method, it is possible to tweek this to 
# deal with special cases like this. I know little about igraph, but this 
# may work.
# 
with.igraph.vs <- function(data, expr, ...) {
  eval(substitute(data$c, list(c = substitute(expr))))
}

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To -> or not to ->

In the blog post "A Step to the Right in R Assignments", by @hrbrmstr, and in later twitter discussions (e.g. here), it is argued that <- (and %<>% for that matter) is "illogical" and feels awkward.

Although I can see where the temptation comes from, I consider -> to be

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#' Trigger an action associated with first matched/valid condition.
#' 
#' trigger is a flavour of pattern matching (or an if-else abstraction) in which a 
#' value is matched against a sequence of condition-action sets. When a valid 
#' match/condition is found the action is triggered and the result of the action 
#' is returned. The trigger function is designed to particularly useful in pipelines
#' ala magrittr.
#' 
#' @param value the value to match agaist
#' @param ... a set of formulas containing a condition as LHS and an action as RHS.

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library(dplyr)     # These two need that it is magrittr@dev that is installed.
library(magrittr)  # i.e. the dev branch @ GitHub, not master.  
library(ggplot2)
library(mgcv)

"http://zevross.com/blog/wp-content/uploads/2014/08/chicago-nmmaps.csv" %>%
  read.csv(as.is = TRUE) %>%
  mutate(date = as.Date(date)) %>%
  filter(date > as.Date("1996-12-31")) %>%
  mutate(year = substring(date, 1, 4)) %T>%