Nassim Haddad nassimhaddad

## sampling_example.R

# generate example:
prob <- c(2, rep(1,9))
v <- vector()
for (i in 1:10000){
  v <- c(v, sample(1:10, 1, prob = prob))
}

# print the output:
print(table(v))

## matrix_size_test.R
nrow <- 100000
ncol <- 100
big_matrix <- matrix(sample(c(0,1,2), nrow * ncol, replace = TRUE), ncol = ncol)
print(object.size(big_matrix), units = "Mb")
# 76.3 Mb

## download_gist.R
# downloads a gist
# usage: download_gist("4539629", "4539629.R")
#
# see also: source_gist {devtools}
download_gist <- function (entry, destfile, ...)
{
  if (is.numeric(entry) || grepl("^[[:digit:]]+$", entry)) {
    entry <- paste("https://raw.github.com/gist/", entry,
                   sep = "")
  }

## debugging_in_R.md

      
              1 file
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                nassimhaddad
                / debugging_in_R.md
            
            
              Last active
              December 11, 2015 03:48
            
              
                debugging process in R
              
          
    Routine:


When an error occurs, the first thing that I usually do is look at the stack
trace by calling traceback(): that shows you where the error occurred, which
is especially useful if you have several nested functions.
Next I will set
options(error=recover); this immediately switches into browser mode where the
error occurs, so you can browse the workspace from there.
If I still don't
have enough information, I usually use the debug() function and step through


## progressbaR.R
pb <- txtProgressBar(style = 3, min = 0, max = length(files_list))
i <- 0

for (file in files_list){
  i <- i+1
  setTxtProgressBar(pb, i)

  do_computations()
}

## fast_group_by.R
# Set up some example data
year <-    sample(1970:2008, 1e6, rep=T)
state <-   sample(1:50, 1e6, rep=T)
group1 <-  sample(1:6, 1e6, rep=T)
group2 <-  sample(1:3, 1e6, rep=T)
myFact <-  rnorm(100, 15, 1e6)
weights <- rnorm(1e6)
myDF <- data.frame(year, state, group1, group2, myFact, weights)

system.time({

## reorder_factor_levels.R


df <- data.frame(f = 1:4, g = letters[1:4])

df$g <- factor(df$g, levels = letters[4:1])

## read_from_clipboard.R
# windows
x <- read.delim(file("clipboard","r"),
                header=TRUE,
                stringsAsFactors = FALSE)

# mac
data <- read.table(pipe("pbpaste"), sep="\t", header=T)

# read from and write to clipboard with Kmisc (windows + OS X):
library(Kmisc)

## get_word_count.R
get_word_count <- function(string){
  length(unlist(strsplit(as.character(string), " ")))
}

## hist_compare.R
plot(density(data1))
lines(density(data2), col = blue)

	# generate example:
	prob <- c(2, rep(1,9))
	v <- vector()
	for (i in 1:10000){
	v <- c(v, sample(1:10, 1, prob = prob))
	}

	# print the output:
	print(table(v))
	nrow <- 100000
	ncol <- 100
	big_matrix <- matrix(sample(c(0,1,2), nrow * ncol, replace = TRUE), ncol = ncol)
	print(object.size(big_matrix), units = "Mb")
	# 76.3 Mb
	# downloads a gist
	# usage: download_gist("4539629", "4539629.R")
	#
	# see also: source_gist {devtools}
	download_gist <- function (entry, destfile, ...)
	{
	if (is.numeric(entry) \|\| grepl("^[[:digit:]]+$", entry)) {
	entry <- paste("https://raw.github.com/gist/", entry,
	sep = "")
	}
	pb <- txtProgressBar(style = 3, min = 0, max = length(files_list))
	i <- 0

	for (file in files_list){
	i <- i+1
	setTxtProgressBar(pb, i)

	do_computations()
	}
	# Set up some example data
	year <- sample(1970:2008, 1e6, rep=T)
	state <- sample(1:50, 1e6, rep=T)
	group1 <- sample(1:6, 1e6, rep=T)
	group2 <- sample(1:3, 1e6, rep=T)
	myFact <- rnorm(100, 15, 1e6)
	weights <- rnorm(1e6)
	myDF <- data.frame(year, state, group1, group2, myFact, weights)

	system.time({


	df <- data.frame(f = 1:4, g = letters[1:4])

	df$g <- factor(df$g, levels = letters[4:1])
	# windows
	x <- read.delim(file("clipboard","r"),
	header=TRUE,
	stringsAsFactors = FALSE)

	# mac
	data <- read.table(pipe("pbpaste"), sep="\t", header=T)

	# read from and write to clipboard with Kmisc (windows + OS X):
	library(Kmisc)
	get_word_count <- function(string){
	length(unlist(strsplit(as.character(string), " ")))
	}