Interface to R

The following examples try to follow “An Introduction to R” which can be found at http://cran.r-project.org/doc/manuals/R-intro.html .

EXAMPLES:

Simple manipulations; numbers and vectors

The simplest data structure in R is the numeric vector which consists of an ordered collection of numbers. To create a vector named \(x\) using the R interface in Sage, you pass the R interpreter object a list or tuple of numbers:

sage: x = r([10.4,5.6,3.1,6.4,21.7]); x
[1] 10.4  5.6  3.1  6.4 21.7

You can invert elements of a vector x in R by using the invert operator or by doing 1/x:

sage: ~x
[1] 0.09615385 0.17857143 0.32258065 0.15625000 0.04608295
sage: 1/x
[1] 0.09615385 0.17857143 0.32258065 0.15625000 0.04608295

The following assignment creates a vector \(y\) with 11 entries which consists of two copies of \(x\) with a 0 in between:

sage: y = r([x,0,x]); y
[1] 10.4  5.6  3.1  6.4 21.7  0.0 10.4  5.6  3.1  6.4 21.7

Vector Arithmetic

The following command generates a new vector \(v\) of length 11 constructed by adding together (element by element) \(2x\) repeated 2.2 times, \(y\) repeated just once, and 1 repeated 11 times:

sage: v = 2*x+y+1; v
[1] 32.2 17.8 10.3 20.2 66.1 21.8 22.6 12.8 16.9 50.8 43.5

One can compute the sum of the elements of an R vector in the following two ways:

sage: sum(x)
[1] 47.2
sage: x.sum()
[1] 47.2

One can calculate the sample variance of a list of numbers:

sage: ((x-x.mean())^2/(x.length()-1)).sum()
[1] 53.853
sage: x.var()
[1] 53.853

sage: x.sort()
[1] 3.1  5.6  6.4 10.4 21.7
sage: x.min()
[1] 3.1
sage: x.max()
[1] 21.7
sage: x
[1] 10.4  5.6  3.1  6.4 21.7

sage: r(-17).sqrt()
[1] NaN
sage: r('-17+0i').sqrt()
[1] 0+4.123106i

Generating an arithmetic sequence:

sage: r('1:10')
[1] 1  2  3  4  5  6  7  8  9 10

Because from is a keyword in Python, it can’t be used as a keyword argument. Instead, from_ can be passed, and R will recognize it as the correct thing:

sage: r.seq(length=10, from_=-1, by=.2)
[1] -1.0 -0.8 -0.6 -0.4 -0.2  0.0  0.2  0.4  0.6  0.8

sage: x = r([10.4,5.6,3.1,6.4,21.7]);
sage: x.rep(2)
[1] 10.4  5.6  3.1  6.4 21.7 10.4  5.6  3.1  6.4 21.7
sage: x.rep(times=2)
[1] 10.4  5.6  3.1  6.4 21.7 10.4  5.6  3.1  6.4 21.7
sage: x.rep(each=2)
[1] 10.4 10.4  5.6  5.6  3.1  3.1  6.4  6.4 21.7 21.7

Missing Values:

sage: na = r('NA')
sage: z = r([1,2,3,na])
sage: z
[1]  1  2  3 NA
sage: ind = r.is_na(z)
sage: ind
[1] FALSE FALSE FALSE  TRUE
sage: zero = r(0)
sage: zero / zero
[1] NaN
sage: inf = r('Inf')
sage: inf-inf
[1] NaN
sage: r.is_na(inf)
[1] FALSE
sage: r.is_na(inf-inf)
[1] TRUE
sage: r.is_na(zero/zero)
[1] TRUE
sage: r.is_na(na)
[1] TRUE
sage: r.is_nan(inf-inf)
[1] TRUE
sage: r.is_nan(zero/zero)
[1] TRUE
sage: r.is_nan(na)
[1] FALSE

Character Vectors:

sage: labs = r.paste('c("X","Y")', '1:10', sep='""'); labs
[1] "X1"  "Y2"  "X3"  "Y4"  "X5"  "Y6"  "X7"  "Y8"  "X9"  "Y10"

Index vectors; selecting and modifying subsets of a data set:

sage: na = r('NA')
sage: x = r([10.4,5.6,3.1,6.4,21.7,na]); x
[1] 10.4  5.6  3.1  6.4 21.7   NA
sage: x['!is.na(self)']
[1] 10.4  5.6  3.1  6.4 21.7

sage: x = r([10.4,5.6,3.1,6.4,21.7,na]); x
[1] 10.4  5.6  3.1  6.4 21.7   NA
sage: (x+1)['(!is.na(self)) & self>0']
[1] 11.4  6.6  4.1  7.4 22.7
sage: x = r([10.4,-2,3.1,-0.5,21.7,na]); x
[1] 10.4 -2.0  3.1 -0.5 21.7   NA
sage: (x+1)['(!is.na(self)) & self>0']
[1] 11.4  4.1  0.5 22.7

Distributions:

sage: r.options(width="60");
$width
[1] 100

sage: rr = r.dnorm(r.seq(-3,3,0.1))
sage: rr
 [1] 0.004431848 0.005952532 0.007915452 0.010420935
 [5] 0.013582969 0.017528300 0.022394530 0.028327038
 [9] 0.035474593 0.043983596 0.053990967 0.065615815
[13] 0.078950158 0.094049077 0.110920835 0.129517596
[17] 0.149727466 0.171368592 0.194186055 0.217852177
[21] 0.241970725 0.266085250 0.289691553 0.312253933
[25] 0.333224603 0.352065327 0.368270140 0.381387815
[29] 0.391042694 0.396952547 0.398942280 0.396952547
[33] 0.391042694 0.381387815 0.368270140 0.352065327
[37] 0.333224603 0.312253933 0.289691553 0.266085250
[41] 0.241970725 0.217852177 0.194186055 0.171368592
[45] 0.149727466 0.129517596 0.110920835 0.094049077
[49] 0.078950158 0.065615815 0.053990967 0.043983596
[53] 0.035474593 0.028327038 0.022394530 0.017528300
[57] 0.013582969 0.010420935 0.007915452 0.005952532
[61] 0.004431848

Convert R Data Structures to Python/Sage:

sage: rr = r.dnorm(r.seq(-3,3,0.1))
sage: sum(rr._sage_())
9.9772125168981...

Or you get a dictionary to be able to access all the information:

sage: rs = r.summary(r.c(1,4,3,4,3,2,5,1))
sage: rs
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.
  1.000   1.750   3.000   2.875   4.000   5.000
  sage: d = rs._sage_()
  sage: d['DATA']
  [1, 1.75, 3, 2.875, 4, 5]
  sage: d['_Names']
  ['Min.', '1st Qu.', 'Median', 'Mean', '3rd Qu.', 'Max.']
  sage: d['_r_class']
  ['summaryDefault', 'table']

It is also possible to access the plotting capabilities of R through Sage. For more information see the documentation of r.plot() or r.png().

AUTHORS:

  • Mike Hansen (2007-11-01)
  • William Stein (2008-04-19)
  • Harald Schilly (2008-03-20)
  • Mike Hansen (2008-04-19)
class sage.interfaces.r.HelpExpression

Bases: str

Used to improve printing of output of r.help.

class sage.interfaces.r.R(maxread=100000, script_subdirectory=None, server_tmpdir=None, logfile=None, server=None, init_list_length=1024)

Bases: sage.interfaces.expect.Expect

An interface to the R interpreter.

R is a comprehensive collection of methods for statistics, modelling, bioinformatics, data analysis and much more. For more details, see http://www.r-project.org/about.html

Resources:

EXAMPLES:

sage: r.summary(r.c(1,2,3,111,2,3,2,3,2,5,4))
Min. 1st Qu.  Median    Mean 3rd Qu.    Max.
1.00    2.00    3.00   12.55    3.50  111.00

TESTS:

sage: r == loads(dumps(r))
True
available_packages()

Returns a list of all available R package names.

This list is not necessarily sorted.

OUTPUT: list of strings

Note

This requires an internet connection. The CRAN server is that is checked is defined at the top of sage/interfaces/r.py.

EXAMPLES:

sage: ap = r.available_packages()   # optional - internet
sage: len(ap) > 20                  #optional
True
call(function_name, *args, **kwds)

This is an alias for function_call().

EXAMPLES:

sage: r.call('length', [1,2,3])
[1] 3
chdir(dir)

Changes the working directory to dir

INPUT:

  • dir – the directory to change to.

EXAMPLES:

sage: import tempfile
sage: tmpdir = tempfile.mkdtemp()
sage: r.chdir(tmpdir)

Check that tmpdir and r.getwd() refer to the same directory. We need to use realpath() in case $TMPDIR (by default /tmp) is a symbolic link (see trac ticket #10264).

sage: os.path.realpath(tmpdir) == sageobj(r.getwd())  # known bug (:trac:`9970`)
True
completions(s)

Return all commands names that complete the command starting with the string s. This is like typing s[Ctrl-T] in the R interpreter.

INPUT:

  • s – string

OUTPUT: list – a list of strings

EXAMPLES:

sage: dummy = r.trait_names(use_disk_cache=False)    #clean doctest
sage: r.completions('tes')
['testInheritedMethods', 'testPlatformEquivalence', 'testVirtual']
console()

Runs the R console as a separate new R process.

EXAMPLES:

sage: r.console()                    # not tested
    R version 2.6.1 (2007-11-26)
    Copyright (C) 2007 The R Foundation for Statistical Computing
    ISBN 3-900051-07-0
    ...
convert_r_list(l)

Converts an R list to a Python list.

EXAMPLES:

sage: s = 'c(".GlobalEnv", "package:stats", "package:graphics", "package:grDevices", \n"package:utils", "package:datasets", "package:methods", "Autoloads", \n"package:base")'
sage: r.convert_r_list(s)
['.GlobalEnv',
 'package:stats',
 'package:graphics',
 'package:grDevices',
 'package:utils',
 'package:datasets',
 'package:methods',
 'Autoloads',
 'package:base']
eval(code, globals=None, locals=None, synchronize=True, *args, **kwds)

Evaluates a command inside the R interpreter and returns the output as a string.

EXAMPLES:

sage: r.eval('1+1')
'[1] 2'
function_call(function, args=None, kwds=None)

Return the result of calling an R function, with given args and keyword args.

OUTPUT: RElement – an object in R

EXAMPLES:

sage: r.function_call('length', args=[ [1,2,3] ])
[1] 3
get(var)

Returns the string representation of the variable var.

INPUT:

  • var – a string

OUTPUT: string

EXAMPLES:

sage: r.set('a', 2)
sage: r.get('a')
'[1] 2'
help(command)

Returns help string for a given command.

INPUT: - command – a string

OUTPUT: HelpExpression – a subclass of string whose __repr__ method is __str__, so it prints nicely

EXAMPLES:

sage: r.help('c')
c                     package:base                     R Documentation
...

.. note::

This is similar to typing r.command?.
install_packages(package_name)

Install an R package into Sage’s R installation.

EXAMPLES:

sage: r.install_packages('aaMI')       # not tested
...
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
...
Please restart Sage in order to use 'aaMI'.
library(library_name)

Load the library library_name into the R interpreter.

This function raises an ImportError if the given library is not known.

INPUT:

  • library_name – string

EXAMPLES:

sage: r.library('grid')
sage: 'grid' in r.eval('(.packages())')
True
sage: r.library('foobar')
Traceback (most recent call last):
...
ImportError: ...
na()

Returns the NA in R.

OUTPUT: RElement – an element of R

EXAMPLES:

sage: r.na()
[1] NA
plot(*args, **kwds)

The R plot function. Type r.help(‘plot’) for much more extensive documentation about this function. See also below for a brief introduction to more plotting with R.

If one simply wants to view an R graphic, using this function is is sufficient (because it calls dev.off() to turn off the device).

However, if one wants to save the graphic to a specific file, it should be used as in the example below to write the output.

EXAMPLES:

This example saves a plot to the standard R output, usually a filename like Rplot001.png - from the command line, in the current directory, and in the cell directory in the notebook:

sage: d=r.setwd('"%s"'%SAGE_TMP)    # for doctesting only; ignore if you are trying this;
sage: r.plot("1:10")                # optional -- rgraphics
null device
          1

To save to a specific file name, one should use png() to set the output device to that file. If this is done in the notebook, it must be done in the same cell as the plot itself:

sage: filename = tmp_filename() + '.png'
sage: r.png(filename='"%s"'%filename) # Note the double quotes in single quotes!; optional -- rgraphics
NULL
sage: x = r([1,2,3])
sage: y = r([4,5,6])
sage: r.plot(x,y)         # optional -- rgraphics
null device
          1
sage: import os; os.unlink(filename) # For doctesting, we remove the file; optional -- rgraphics

Please note that for more extensive use of R’s plotting capabilities (such as the lattices package), it is advisable to either use an interactive plotting device or to use the notebook. The following examples are not tested, because they differ depending on operating system:

sage: r.X11() # not tested - opens interactive device on systems with X11 support
sage: r.quartz() # not tested - opens interactive device on OSX
sage: r.hist("rnorm(100)") # not tested - makes a plot
sage: r.library("lattice") # not tested - loads R lattice plotting package
sage: r.histogram(x = "~ wt | cyl", data="mtcars") # not tested - makes a lattice plot
sage: r.dev_off() # not tested, turns off the interactive viewer

In the notebook, one can use r.png() to open the device, but would need to use the following since R lattice graphics do not automatically print away from the command line:

sage: filename = tmp_filename() + '.png' # Not needed in notebook, used for doctesting
sage: r.png(filename='"%s"'%filename) # filename not needed in notebook, used for doctesting; optional -- rgraphics
NULL
sage: r.library("lattice")
sage: r("print(histogram(~wt | cyl, data=mtcars))") # plot should appear; optional -- rgraphics
sage: import os; os.unlink(filename) # We remove the file for doctesting, not needed in notebook; optional -- rgraphics
png(*args, **kwds)

Creates an R PNG device.

This should primarily be used to save an R graphic to a custom file. Note that when using this in the notebook, one must plot in the same cell that one creates the device. See r.plot() documentation for more information about plotting via R in Sage.

These examples won’t work on the many platforms where R still gets built without graphics support.

EXAMPLES:

sage: filename = tmp_filename() + '.png'
sage: r.png(filename='"%s"'%filename)             # optional -- rgraphics
NULL
sage: x = r([1,2,3])
sage: y = r([4,5,6])
sage: r.plot(x,y) # This saves to filename, but is not viewable from command line; optional -- rgraphics
null device
          1
sage: import os; os.unlink(filename) # We remove the file for doctesting; optional -- rgraphics

We want to make sure that we actually can view R graphics, which happens differently on different platforms:

sage: s = r.eval('capabilities("png")') # Should be on Linux and Solaris
sage: t = r.eval('capabilities("aqua")') # Should be on all supported Mac versions
sage: "TRUE" in s+t                      # optional -- rgraphics
True
read(filename)

Read filename into the R interpreter by calling R’s source function on a read-only file connection.

EXAMPLES:

sage: filename = tmp_filename()
sage: f = open(filename, 'w')
sage: f.write('a <- 2+2\n')
sage: f.close()
sage: r.read(filename)
sage: r.get('a')
'[1] 4'
require(library_name)

Load the library library_name into the R interpreter.

This function raises an ImportError if the given library is not known.

INPUT:

  • library_name – string

EXAMPLES:

sage: r.library('grid')
sage: 'grid' in r.eval('(.packages())')
True
sage: r.library('foobar')
Traceback (most recent call last):
...
ImportError: ...
set(var, value)

Set the variable var in R to what the string value evaluates to in R.

INPUT:

  • var – a string
  • value – a string

EXAMPLES:

sage: r.set('a', '2 + 3')
sage: r.get('a')
'[1] 5'
source(s)

Display the R source (if possible) about the function named s.

INPUT:

  • s – a string representing the function whose source code you want to see

OUTPUT: string – source code

EXAMPLES:

sage: print r.source("c")
function (..., recursive = FALSE)  .Primitive("c")
trait_names(verbose=True, use_disk_cache=True)

Return list of all R functions.

INPUT:

  • verbose – bool (default: True); if True, display debugging information
  • use_disk_cache – bool (default: True); if True, use the disk cache of trait names to save time.

OUTPUT: list – list of string

EXAMPLES:

sage: t = r.trait_names(verbose=False)
sage: len(t) > 200
True
version()

Return the version of R currently running.

OUTPUT: tuple of ints; string

EXAMPLES:

sage: r.version() # not tested
((3, 0, 1), 'R version 3.0.1 (2013-05-16)')
sage: rint, rstr = r.version()
sage: rint[0] >= 3
True
sage: rstr.startswith('R version')
True
class sage.interfaces.r.RElement(parent, value, is_name=False, name=None)

Bases: sage.interfaces.expect.ExpectElement

dot_product(other)

Implements the notation self . other.

INPUT:

  • self, other – R elements

OUTPUT: R element

EXAMPLES:

sage: c = r.c(1,2,3,4)
sage: c.dot_product(c.t())
     [,1] [,2] [,3] [,4]
[1,]    1    2    3    4
[2,]    2    4    6    8
[3,]    3    6    9   12
[4,]    4    8   12   16

sage: v = r([3,-1,8])
sage: v.dot_product(v)
     [,1]
[1,]   74
stat_model(x)

The tilde regression operator in R.

EXAMPLES:

sage: x = r([1,2,3,4,5])
sage: y = r([3,5,7,9,11])
sage: a = r.lm( y.tilde(x) ) # lm( y ~ x )
sage: d = a._sage_()
sage: d['DATA']['coefficients']['DATA'][1]
2
tilde(x)

The tilde regression operator in R.

EXAMPLES:

sage: x = r([1,2,3,4,5])
sage: y = r([3,5,7,9,11])
sage: a = r.lm( y.tilde(x) ) # lm( y ~ x )
sage: d = a._sage_()
sage: d['DATA']['coefficients']['DATA'][1]
2
trait_names()

Return a list of all methods of this object.

Note

Currently returns all R commands.

EXAMPLES:

sage: a = r([1,2,3])
sage: t = a.trait_names()
sage: len(t) > 200
True
class sage.interfaces.r.RFunction(parent, name, r_name=None)

Bases: sage.interfaces.expect.ExpectFunction

A Function in the R interface.

INPUT:

  • parent – the R interface
  • name – the name of the function for Python
  • r_name – the name of the function in R itself (which can have dots in it)

EXAMPLES:

sage: length = r.length
sage: type(length)
<class 'sage.interfaces.r.RFunction'>
sage: loads(dumps(length))
length
class sage.interfaces.r.RFunctionElement(obj, name)

Bases: sage.interfaces.expect.FunctionElement

sage.interfaces.r.is_RElement(x)

Return True if x is an element in an R interface.

INPUT:

  • x – object

OUTPUT: bool

EXAMPLES:

sage: from sage.interfaces.r import is_RElement
sage: is_RElement(2)
False
sage: is_RElement(r(2))
True
sage.interfaces.r.r_console()

Spawn a new R command-line session.

EXAMPLES:

sage: r.console()                    # not tested
    R version 2.6.1 (2007-11-26)
    Copyright (C) 2007 The R Foundation for Statistical Computing
    ISBN 3-900051-07-0
    ...
sage.interfaces.r.r_version()

Return the R version.

EXAMPLES:

sage: r_version() # not tested
((3, 0, 1), 'R version 3.0.1 (2013-05-16)')
sage: rint, rstr = r_version()
sage: rint[0] >= 3
True
sage: rstr.startswith('R version')
True
sage.interfaces.r.reduce_load_R()

Used for reconstructing a copy of the R interpreter from a pickle.

EXAMPLES:

sage: from sage.interfaces.r import reduce_load_R
sage: reduce_load_R()
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