Package 'CSwR'

Subsetting tracer objects

Description

Subsetting tracer objects

Usage

## S3 method for class 'tracer'
x[i, j, ..., drop = TRUE]

Arguments

x	a tracer object.
i	the indices of the trace information to extract.
j	currently ignored.
...	other arguments passed on to get.
drop	simplify a list with one element to a vector if TRUE.

Value

a list

Examples

tr <- tracer("i", Delta = 0)

for (i in 1:3) {
  tr$tracer()
}

tr[1]

---

Torsion angles

Description

The phi and psi torsion angles between peptide planes for the human protein 1HMP.

Usage

angle

Format

A data frame with 419 rows and 5 columns:

chain

a character. The chain (either A or B) of the protein

AA

a character. The three-letter amino acid name

pos

an integer. Position in the amino acid sequence

phi

numeric. The phi angle

psi

numeric. The psi angle

Source

https://warwick.ac.uk/fac/sci/moac/people/students/peter_cock/r/ramachandran

---

Plot results from a trace

Description

Plots the value of a traced object on a log-scale against runtime.

Usage

## S3 method for class 'tracer'
autoplot(object, y, ...)

## S3 method for class 'trace'
autoplot(object, y, log = TRUE, ...)

Arguments

object	a trace or tracer object
y	the name of the traced object to plot
...	additional arguments passed to
log	logical. Should the y-axis be on a log-scale. Default is TRUE.

Value

a ggplot object

Examples

tr <- tracer("i", Delta = 0)

for (i in 1:3) {
  tr$tracer()
}

ggplot2::autoplot(tr, i)

---

Force evaluation of all arguments to a function

Description

Forces the evaluation of all arguments in the calling environment of this function.

Usage

force_all(...)

Arguments

...	arguments captured by ... are also evaluated if passed via ...

Details

Use force_all() as syntactic sugar to force evaluation of all arguments to a function and thereby circumvent lazy evaluation. If called from within a function with ... as formal argument, use force_all(...) to force evaluation of arguments captured by ....

Value

NULL invisibly

See Also

force()

Examples

affine <- function(a, b) {
  function(x) a * x + b
}

a <- 1
b <- 1

affine_11 <- affine(a, b)

a <- 2
b <- 2

affine_11(1) # Gives 4 and not 2 due to lazy evaluation

affine_forced <- function(a, b) {
  force_all()
  function(x) a * x + b
}

a <- 1
b <- 1

affine_11 <- affine_forced(a, b)

a <- 2
b <- 2

affine_11(1) # Gives 2

---

South west Greenland temperature data

Description

Monthly average temperatures in degree Celsius in Nuuk and Qaqortoq from 1873 to 2013.

Usage

greenland

Format

A data frame with 1692 rows and 5 columns:

Year

Year (numeric)

Month

Month (integer, 1 to 12)

Temp_nuuk

Monthly mean temperature in Nuuk

Temp_Qaqortoq

Monthly mean temperature in Qaqortoq

Temp_diff

Temperature difference, Temp_nuuk - Temp_Qaqortoq

Source

https://crudata.uea.ac.uk/cru/data/greenland/

---

Social media news sharing

Description

A dataset containing features about articles published by Mashable in a period of two years from January 7, 2013, to January 7, 2015. The purpose of collecting the data was to predict the number of shares of the news articles on social networks. Compared to the source, seven features are excluded. Two (url and a timestamp) are not relevant predictors and five are redundant or almost redundant, leading to collinearity.

Usage

news

Format

A data frame with 39,644 rows and 54 columns:

n_tokens_title

Number of words in the title

n_tokens_content

Number of words in the content

n_unique_tokens

Rate of unique words in the content

num_hrefs

Number of links

num_self_hrefs

Number of links to other articles published by Mashable

num_imgs

Number of images

num_videos

Number of videos

average_token_length

Average length of the words in the content

num_keywords

Number of keywords in the metadata

data_channel_is_lifestyle

Is data channel 'Lifestyle'?

data_channel_is_entertainment

Is data channel 'Entertainment'?

data_channel_is_bus

Is data channel 'Business'?

data_channel_is_socmed

Is data channel 'Social Media'?

data_channel_is_tech

Is data channel 'Tech'?

data_channel_is_world

Is data channel 'World'?

kw_min_min

Worst keyword (min. shares)

kw_max_min

Worst keyword (max. shares)

kw_avg_min

Worst keyword (avg. shares)

kw_max_max

Best keyword (max. shares)

kw_avg_max

Best keyword (avg. shares)

kw_min_avg

Avg. keyword (min. shares)

kw_max_avg

Avg. keyword (max. shares)

kw_avg_avg

Avg. keyword (avg. shares)

self_reference_min_shares

Min. shares of referenced articles in Mashable

self_reference_avg_sharess

Avg. shares of referenced articles in Mashable

weekday_is_monday

Was the article published on a Monday?

weekday_is_tuesday

Was the article published on a Tuesday?

weekday_is_wednesday

Was the article published on a Wednesday?

weekday_is_thursday

Was the article published on a Thursday?

weekday_is_friday

Was the article published on a Friday?

weekday_is_saturday

Was the article published on a Saturday?

weekday_is_sunday

Was the article published on a Sunday?

LDA_00

Closeness to LDA topic 0

LDA_01

Closeness to LDA topic 1

LDA_02

Closeness to LDA topic 2

LDA_03

Closeness to LDA topic 3

LDA_04

Closeness to LDA topic 4

global_subjectivity

Text subjectivity

global_sentiment_polarity

Text sentiment polarity

global_rate_positive_words

Rate of positive words in the content

global_rate_negative_words

Rate of negative words in the content

rate_positive_words

Rate of positive words among non-neutral tokens

rate_negative_words

Rate of negative words among non-neutral tokens

avg_positive_polarity

Avg. polarity of positive words

min_positive_polarity

Min. polarity of positive words

max_positive_polarity

Max. polarity of positive words

avg_negative_polarity

Avg. polarity of negative words

min_negative_polarity

Min. polarity of negative words

max_negative_polarity

Max. polarity of negative words

title_subjectivity

Title subjectivity

title_sentiment_polarity

Title polarity

abs_title_subjectivity

Absolute subjectivity level

abs_title_sentiment_polarity

Absolute polarity level

shares

Number of shares (target)

Source

https://archive.ics.uci.edu/dataset/332/online+news+popularity

---

Nuuk temperature data

Description

Annual summaries of monthly mean temperatures in Nuuk from 1867 to 2013.

Usage

nuuk

Format

A data frame with 147 rows and 6 columns:

Year

Year (numeric)

Temperature

Annual mean temperature

Median

Annual median of monthly mean temperatures

High

Annual maximum of monthly mean temperatures

Low

Annual minimum of monthly mean temperatures

Range

High - Low

Source

https://crudata.uea.ac.uk/cru/data/greenland/

---

Constructor of plotter expression

Description

The plotter function returns a quoted expression that adds points to a current plot. For use with tracer and terminator objects to iteratively update plots during long running function evaluations.

Usage

plotter(y, col = "black", lty = "solid", pch = 1)

Arguments

y	a name of a symbol to plot
col	point and line color
lty	line type
pch	plot symbol

Value

a quoted expression

Examples

plotter("i")

---

Print terminator information

Description

Print terminator information

Usage

## S3 method for class 'terminator'
print(x, ...)

Arguments

x	a terminator object
...	other arguments (currently ignored)

Value

The list of objects from the terminator's evaluation environment, returned invisibly.

Examples

term <- terminator(quote(i >= 3), print = FALSE)

for (i in 1:5) {
  if (term$terminator()) {
    break
  }
}

print(term, all.names = TRUE)

---

Random number stream based on caching

Description

A random number stream uses a vectorized random number generator to generate a cache of random numbers that can then be used sequentially. Whenever the cache runs empty new numbers are generated automatically.

Usage

rng_stream(m, rng, ...)

Arguments

m	initial cache size
rng	a random number generator
...	additional arguments passed to the random number generator

Value

A function that extracts random numbers from the cache and fills the cache whenever it runs empty.

Examples

runif_stream <- rng_stream(10, runif, min = -1, max = 1)
runif_stream()

---

Summarize and print trace information

Description

Summarize and print trace information

Usage

## S3 method for class 'tracer'
summary(object, ...)

## S3 method for class 'tracer'
print(x, ...)

Arguments

object	a tracer object
...	other arguments (currently ignored)
x	a tracer object

Value

summary returns a data frame (of class trace) with columns containing the values of the traced objects, and if time is traced an additional column, .time, containing the cumulative runtime in seconds.

Examples

tr <- tracer("i", Delta = 0)

for (i in 1:3) {
  tr$tracer()
}

summary(tr)
print(tr)

---

Constructor of a terminator object

Description

Terminator objects are used to write termination conditions that can be tested via a callback function within another function during its evaluation.

Usage

terminator(cond = FALSE, Delta = 1, print = TRUE, plotter = NULL, ...)

Arguments

cond	a termination condition. Either an expression or call that evaluates to a logical.
Delta	an integer specifying how often the termination condition is evaluated. Delta = 0 means never, and otherwise the condition is evaluated every Delta-th iteration. Delta = 1 is the default.
print	a variable name to print or a logical. If FALSE, nothing is printed. If a variable name is given, that variable (if it exists) will be printed every Delta-th iteration. If TRUE (the default) the last variable in cond is printed every Delta-th iteration.
plotter	an expression, possibly created by the plotter function.
...	other arguments passed to format for printing and plot.window

Details

Terminator objects are similar to tracer objects but serve a different purpose. Like tracer objects, they can be used to trace, print and plot values of a variable within the evaluation environment of another function during its evaluation. The primary purpose of a terminator object is, however, to evaluate a termination condition, which can trigger termination of a loop. Terminator objects do not save trace information and do not trace runtime.

Value

A terminator object containing the functions terminator and clear.

Examples

term <- terminator(quote(i >= 3), print = FALSE)

for (i in 1:5) {
  if (term$terminator()) {
    break
  }
}

i

---

Constructor of a tracer object

Description

Tracer objects can collect, print and summarize trace information from the evaluation environment of other functions during their evaluation.

Usage

tracer(
  objects = NULL,
  Delta = 1,
  save = TRUE,
  time = TRUE,
  expr = NULL,
  plotter = NULL,
  ...
)

Arguments

objects	a character vector of names of the objects that are to be traced. The objects are searched for in the calling environment of the tracer function. Objects created by the expr argument can also be traced.
Delta	an integer specifying if and how often trace information is printed. Delta = 0 means never, and otherwise trace information is printed every Delta-th iteration. Delta = 1 is the default.
save	a logical value. Determines if the trace information is stored.
time	a logical value. Determines if runtime information in seconds is traced.
expr	an expression that will be evaluated in an environment that has the calling environment of the tracer function as parent.
plotter	an expression, possibly created by the plotter function.
...	other arguments passed to format for printing and plot.window

Details

The function tracer constructs a tracer object containing a tracer, a get and a clear function. A call of the objects tracer function can be inserted in other functions and used to collect, print and plot trace information about the internals of that function during its evaluation. The objects get function can access that information afterwards, and its clear function deletes all stored values in the tracer object.

A tracer object can trace time (in seconds) between tracer calls, which are measured by the hires_time function from the bench package. There are print and summary methods available for summarizing the trace information. A call of the tracer function can be manually inserted into the body of the function that is to be traced, it can be inserted using base::trace, or it can be passed as an argument to any function with a callback argument.

Value

A tracer object containing the functions tracer, get and clear.

Examples

test_tracer <- tracer(c("m", "m_sq"), expr = quote(m_sq <- m^2))

test <- function(n, cb = NULL) {
  for(i in 1:n) {
    m <- 2 * i
    Sys.sleep(0.1)
    if (!is.null(cb)) cb()
  }
}

test(10, test_tracer$tracer)
summary(test_tracer)

---

Vegetable sale

Description

Weekly sale of frozen vegetables in different stores.

Usage

vegetables

Format

A data frame with 1066 rows and 3 columns:

sale

a numeric vector. Number of items sold in a week

normalSale

a numeric vector. Estimated normal sale that week

store

a character vector. Id of the different stores

Source

Obtained by package author.

---