Random Jungle
This manual (8 April 2010) is for Random Jungle (RJ) version 1.0.359, a package containing an implementation of the Random Forests (TM) method.
Copyright © 2008-2010 Daniel F. Schwarz.
Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the section entitled “GNU Free Documentation License.”
Random Jungle is an implementation of Random Forests (TM).
It is mostly compatible to the original fortran code.
Random Jungle also has additional builtin functions.
Random Jungle is written by Daniel F. Schwarz and few volunteers.
All names and email addresses can be found in the
files randomjungle-1.0.359/AUTHORS and
randomjungle-1.0.359/THANKS
from the Random Jungle distribution.
This is release 1.0.359. It is considered unstable: future releases are meant to add new features, fix bugs, increase speed, or improve documentation. However...
This first chapter explains what Random Jungle is, where
Random Jungle
comes from, how to read and use this documentation, how to call the
Random Jungle program, and how to report bugs about it. It concludes by
giving tips for reading the remainder of the manual.
The following chapters then detail all the features of the Random Jungle
.
Random JungleRandom Jungle is an implementation of Random Forests (TM).
It is supposed to analyse high dimensional data.
In genetics, it can be used for analysing big Genome Wide Association (GWA)
data. Random Forests (TM) is a powerful machine learning method.
Most interesting features are variable selection, missing value imputation,
classifier creation, generalization error estimation and sample proximities
between pairs of cases.
Random Jungle is mostly compatible with the Linux and Windows (TM).
Also, there exists compatibilities with Solaris.
First ideas where seeded in 2006 during GAW15 workshop in Florida.
In the beginning of 2008, Daniel F. Schwarz released 0.5.0 and 0.5.1 which
was a "way pre-release" and fast, but lagged of features and documentation.
However, the williams award was won at the International Genetic Epidemiology
Society (IGES) converence 2008 in St. Louis with release 0.5.2.
In late 2008 and 2009, intensive
work improved the platform compatibility, added documentation and
raised the number of features of Random Jungle.
If you have problems with Random Jungle or think you've found a bug,
please report it. Before reporting a bug, make sure you've actually
found a real bug. Carefully reread the documentation and see if it
really says you can do what you're trying to do. If it's not clear
whether you should be able to do something or not, report that too; it's
a bug in the documentation!
Before reporting a bug or trying to fix it yourself, try to isolate it
to the smallest possible input file that reproduces the problem. Then
send us the input file and the exact results Random Jungle gave you.
Also say what you expected to occur; this will help us decide whether the
problem was really in the documentation.
Once you've got a precise problem, send e-mail to
bug@randomjungle.com. Please include the version number of
Random Jungle you are using. You can get this information with the
command rjungle --version or rjungle -Z.
Non-bug suggestions are always welcome as well. If you have questions about things that are unclear in the documentation or are just obscure features, please report them too.
This manual contains a number of examples of Random Jungle input and
output,
and a simple notation is used to distinguish input, output and error
messages from Random Jungle. Examples are set out from the normal text,
and shown in a fixed width font, like this
This is an example of an example!
To distinguish input from output, all output from Random Jungle is
prefixed
by the string `=>', and all error messages by the string
`error-->'. When showing how command line options affect matters,
the command line is shown with a prompt `$ like this',
otherwise, you can assume that a simple rjungle invocation will work.
Thus:
$ command line to invoke rjungle
Example of input line
=>Output line from rjungle
error-->and an error message
The sequence `^D' in an example indicates the end of the input file. The sequence `<NL>' refers to the newline character. The majority of these examples are self-contained, and you can run them with similar results by invoking rjungle -d. In fact, the testsuite that is bundled in the Random Jungle package consists of the examples in this document! Some of the examples assume that your current directory is located where you unpacked the installation, so if you plan on following along, you may find it helpful to do this now:
$ cd randomjungle-1.0.359
Random JungleThere are pre-compiled versions on the internet site http://www.randomjungle.com/. Maybe, there exists a pre-compiled version for your platform (computer) and you do not need to compile it.
Random Jungle uses some GNU tools, libraries and other free
open source code. The installation routine (./configure) prompt you
to install packages which are missing on your machine.
It is also recommended to compile the sources with an openMP supporting
compiler (i.e. GNU gcc > 4.2).
Invoke the following commands to compile rjungle:
./configuremakemake checkmake installFor compiling Random Jungle with MPI (message passing interface)
support, configure RJ using option --enable-mpi.
The program is optimized for Open MPI
(http://www.open-mpi.org/). The MPI mode should be used by experienced
users only.
./configure --enable-mpiRandom JungleThe format of the Random Jungle command is:
rjungle [option...]
or
rjunglesparse [option...]
All options begin with `-', or if long option names are used, with
`--'. On some platforms long options might not work.
A long option name need not be written completely, any
unambiguous prefix is sufficient. POSIX requires Random Jungle to
recognize arguments intermixed with files, even when
POSIXLY_CORRECT is set in the environment. Most options take
effect at startup regardless of their position, but some are documented
below as taking effect after any files that occurred earlier in the
command line. The argument -- is a marker to denote the end of
options.
With short options, options that do not take arguments may be combined into a single command line argument with subsequent options, options with mandatory arguments may be provided either as a single command line argument or as two arguments, and options with optional arguments must be provided as a single argument. In other words, rjungle -QPDfoo -d a -df is equivalent to rjungle -Q -P -D foo -d -df -- ./a, although the latter form is considered canonical.
With long options, options with mandatory arguments may be provided with
an equal sign (`=') in a single argument, or as two arguments, and
options with optional arguments must be provided as a single argument.
In other words, rjungle --def foo --debug a is equivalent to
rjungle --define=foo --debug= -- ./a, although the latter form is
considered canonical (not to mention more robust, in case a future
version of Random Jungle introduces an option named --default).
Random Jungle understands the following options, grouped by functionality.
Several options control the overall operation of rjungle:
-h--helprjungle without reading any input files or performing any other
actions.
-Z--versionrjungle without reading any input files or
performing any other actions.
-f FILENAME--file=FILENAMEwrite.table as follows:
> make.your.data.in.R
> write.table(yourData, file = "input.dat", row.names = FALSE, quote = FALSE)
> quit()
$ rjungle -f input.dat [...]
In plink (pngu.mgh.harvard.edu/~purcell/plink/), save data to raw file
using the recodeA option, set the ped file option and char memory mode option in
rjungle as follows:
$ plink --file yourDataFile --recodeA
$ rjungle -f yourDataFile.raw -p -M 2 [...]
Avoid missing values in data.
See See Input data, for more details.
-o FILEPREFIXNAME--outprefix=FILEPREFIXNAMErjungle.importance, rjungle.prediction, ...).
The default FILEPREFIXNAME is rjungle. Use for example
-o my_analysis_no123.
-e CHAR--delimeter=CHAR-w2.jungle.xml.
-P FILENAME-f). Predictions will be
written to FILEPREFIXNAME.prediction.
-y ID--treetype=IDCART, y (output variable): nominal, x (input variable(s)): numeric, ID = 1 is recommended for less different values in the input variables (i.e. GWA SNP data or integer data). ID = 5 is recommended for more different values in the input variables (i.e. many floating point numbers). Like original Breiman/Cutler/Friedman algorithm.
CART regression trees, CART regression trees, y (output variable): numeric, x (input variable(s)): nominal,
Default is a 1.
-t SIZE--ntree=SIZE-m SIZE--mtry=SIZE-x NUM--missingcode=NUMNA or NUM in your data.
The program takes NUM as a internal representation of a missing value.
Default is -99.
-i ID--impmeasure=ID.importance.
Default is 1 and you can not turn off variable importance output.
-B IDBackward elimination. Discard 50% at each step (slow). Stop if number of variables shrinked to STOPSIZE, see option
-j.
Backward elimination. Discard 33% at each step (slow). Stop if number of variables shrinked to STOPSIZE, see option
-j.
Backward elimination. Discard only negative values at each step (slow/recommended). (Shown at IGES2007 by Inke R. Konig).
-j STOPSIZE--nimpvar=STOPSIZE--impmeasure = 2,3,5,6 or 7. How many variable should
remain. The lesser STOPSIZE is, the reliable the result might be. The
smaller SIZE is, the higher computing time will be.
Default is 100.
-v--verbose.verbose (default).
-u--downsampling-M ID--memmode=IDChar (small). CHAR normally fits in one byte. DATA CELL VALUE HAS TO BE AN INTEGER IN [-127..127].
rjunglesparse a try!
Default is 0.
-C FILE--colselection=FILE var1
var20
var1000
var300
Default is take all variables.
-D NAME--depvarname=NAMErjungle switches to unsupervised mode.
-s--sampleproximities.samproximity.
Default: switched off
-z--seeed-U--nthreads=NUM-p--pedfile-I NUM--impute=NUM-A (--impcont) as well.
For more information, have a look at
http://www.stat.berkeley.edu/~breiman/RandomForests/cc_home.htm.
Do not try to impute untyped SNPs (Schwarz et al. 2009, BMC Proceedings, 3, S65) if
case-control-status is missing.
Try a different program like: IMPUTE, MACH, PLINK, ...
Default: switched off.
-k NUM--maxtreedepth=NUM-l NUM--targetpartitionsize=NUM-d -g -n -r -c -a -b -w -V -S -P -A -G -E -X
This chapter describes various input file types of rjungle.
Random Jungle analyses data given in a file, see option -f. The
file format is matrix like and is as follows:
The first line of the input file contains the variable names. The variable name must not contain quotes or space charaters. The variables are seperated by space charaters.
Each following line represents one sample (observation). Every single sample needs to have one numerical value for each variable. The values are seperated by space charaters and are ordered corresponding to the variable names (of course).
Here, an example of an input file:
responseVar inputVar1 inputVar2 inputVar3 inputVar40 1.2 3.4 5.6 7.80 1.1 3.3 5.5 7.70 2.2 4.4 6.6 8.81 1.0 3.0 5.0 7.01 1.0 3.0 5.0 7.01 2.0 4.0 6.0 8.0
If you choose the ped file option -p then the input file format is ped
like. The file must have variables FID, IID, PAT, MAT, SEX, PHENOTYPE and
at least three variables (SNPs).
Here, an example of an input file:
FID IID PAT MAT SEX PHENOTYPE rs1 rs2 rs3 rs41000 NA2001 0 0 2 0 0 1 0 11000 NA2002 0 0 2 0 0 2 0 11001 NA2003 0 0 1 0 1 2 0 11001 NA2004 0 0 1 0 1 1 1 11002 NA2005 0 0 2 1 1 1 1 11004 NA2006 0 0 2 1 1 2 1 11005 NA2007 0 0 2 1 2 2 2 21006 NA2008 0 0 1 1 2 2 2 21007 NA2008 0 0 1 1 2 2 2 2
The rjungle can be run also with just a subset of all variables
which are given in the input file (option -f).
See description of option -C, for more details.
This chapter describes various output file types of rjungle.
If rjungle is executed it will always produce three files.
See Log file, Confusion file and Importance file.
You can run an example in your randomjungle-1.0.359 directory
and see it.
$ cd tests
$ rjungle -f test.ped -p -v -M2
$ ls
rjungle.importance rjungle.log rjungle.prediction test.ped
The log file contains all options / parameter of the rjungle execution.
This is useful to reproduce results.
The rjungle always evaluates the classifier. The accuracy on training
and test data. Test data is called oob data which is collected during
growing process (similar to cross validation's test sets). The results are
shown in so-called confusion matrices in file
FILEPREFIXNAME.confusion. Columns represent the predicted values
and rows represent the real values.
When using option -y1 a file FILEPREFIXNAME.confusion2 will
be created. The file contains class specific error rates.
The rjungle is able to perform new data to a saved classifier (option
-w2 and -P). The predicted results will be saved to file
FILEPREFIXNAME.prediction.
Random Jungle estimates the importance of variables (option
-i). The results are saved to file
FILEPREFIXNAME.importance and/or
FILEPREFIXNAME.importance2. The first file contains four columns
but most interesting columns are varname (variable name) and value
(importance value). The higher the value, the more important is the
variable with name varname. This list is sorted ascending. So, look
at the tail of file to see the most important variables.
The second file contains various permutation importance informations.
If Random Jungle is invoked from command line without verbose option
it is very schtum and do not output anything to screen. It writes all
information occuring during a run to file FILEPREFIXNAME.verbose.
Nevertheless, if you want a takly rjungle which puts all process
information to screen then use option (-v)
$ cd tests
$ rjungle -f test.ped -p -v
Start: Thu Nov 27 12:19:26 2008
+---------------------+-----------------+-------------------+
| RandomJungle | ...... | 2008 |
+---------------------+-----------------+-------------------+
| (C) 2008 Daniel Frederik Schwarz et al., GNU GPL, v2 |
| daniel@randomjungle.com |
+-----------------------------------------------------------+
Output to:
rjungle.*
loading data...
Read 9 row(s) and 10 column(s).
Use 9 row(s) and 6 column(s).
dependent variable name: PHENOTYPE
Growing jungle...
Number of variables: 6 mtry = 2
1 thread(s) growing 500 tree(s)
Growing time estimate: ~0 sec.
Generating and collecting output data...
Compiling trees.
Writing accuracy information...
calculating confusion matrix...
Elapsed time: 0 sec
Finished: Thu Nov 27 12:19:26 2008
$
This chapter describes error codes.
Error code description can be found in
randomjungle-1.0.359/src/library/error_codes.txt or
http://www.randomjungle.com/tags/newest/error_codes.txt.
This chapter describes various examples of working with rjungle.
You can run the examples in your
randomjungle-1.0.359/tests directory.
We want to grow a simple forest. So, our input data contains 9 input
(V1-V9) and 1 output variable(y).
8 output variables are non informative. Only variable V1 is
informative.
$ rjungle -f test.dat -U1 -z1 -v -D y -o example1
$ ls example1.*
...
$ rjungle -f test.ped -p -o example2
...
In the first example we used the data in file test.dat. As we know,
only variable V1 is informative and therefore it is the most important
variable. Firstly, lets estimate the fast GINI-Importance with 1000 trees.
$ rjungle -f test.dat -U1 -z1 -t1000 -v -D y -o example3.1
$ cat example3.1.importance
...
We see that variable V1 is the most important (highest value).
Secondly, we now want to estimate the permutation importance.
$ rjungle -f test.dat -U1 -z1 -t1000 -v -D y -i2 -o example3.2
$ cat example3.2.importance2
...
Now, we got even a more reliable result. In most cases, only variable
V1 is positive. It means that only V1 contributes to
a high accurate classification.
We want to analyse data from R.
$ R
...
> mydata = iris
> mydata$Species = as.integer(mydata$Species) # convert factor to integer
> write.table(mydata, file = "data_from_r.dat",
+ row.names = FALSE, quote = FALSE)
> quit("no")
$ rjungle -f data_from_r.dat -U1 -z1 -t500 -v -D Species -o example4
$ cat example4.confusion
...
$ cat example4.importance
...
$ plink --file gwadata --recodeA
$ rjungle -f plink.raw -p -M2 -v -o example5
...
$ tail example5.importance
or
$ plink --file gwadata --recodeA
$ rjunglesparse -f plink.raw -p -v -o example5
...
$ tail example5.importance
The rjunglesparse uses less memory than rjungle. But
your data should only use the values 0,1,2 and 3(missing code).
$ rjungle -f train.dat -D DependVar -v -w2 -o example6a
...
$ rjungle -f test.dat -D DependVar -v -P example6a.jungle.xml -o example6b
$ cat example6b.confusion
$ cat example6b.prediction
...
SNP data (raw/fast imputation):
$ rjunglesparse -f mypedfile.raw -p -t1 -I1 -o example7_1_1
The imputation result was written to example7_1_1.imputed.dat.gz and can be used for analysis. E.g.:
$ rjunglesparse -f example7_1_1.imputed.dat.gz -p ... -o example8_1_2
Imputing continuous data:
$ rjungle -f continuous.dat -A -D DependVar -I6 -o example7_2
or imputing categorical data:
$ rjungle -f cate.dat -D DependVar -I6 -o example7_3
or imputing data with no groups to classify on (unsupervised learning):
$ rjungle -f continuousAndNoGroups.dat -A -I5 -o example7_4
The rjunglesparse is the same program like rjungle, but you can
use just a small set of values: 0,1,2 (and 3 as missing coding). You might
want to use rjunglesparse in conjunction with plink.
The memory consumption of rjunglesparse is very small.
$ plink --file gwadata --recodeA
$ rjunglesparse -f plink.raw -p -v -o example8
...
$ tail example8.importance
For high speed parallel processing, RJ could be used on computer
clusters using MPI mode (RJ has to be compiled for MPI!). The program
was performed on huge data successfully using 150 processors (300 processes) in
parallel on a high performance cluster. However, the MPI mode should be used by
experienced users only. In MPI mode, performing permutation importance (option
-i2, .., -i5) is allow exclusivly. Execute RJ as follows:
$ plink --file gwadata --recodeA
$ mpirun -np 200 --host hostname1, hostname2, ... rjunglesparse -f plink.raw -p -v -i4 -o example9
...
$ tail example9.importance
Each process writes temp files to working directory (example9_mpi_id_*.*). Final results are written to usual files (example9.*).
This appendix covers the license for copying the source code of the overall Random Jungle package. This manual is under a different set of restrictions, covered later (see Copying This Manual).
Copyright © 2007 Free Software Foundation, Inc. http://fsf.org/
Everyone is permitted to copy and distribute verbatim copies of this
license document, but changing it is not allowed.
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The licenses for most software and other practical works are designed to take away your freedom to share and change the works. By contrast, the GNU General Public License is intended to guarantee your freedom to share and change all versions of a program—to make sure it remains free software for all its users. We, the Free Software Foundation, use the GNU General Public License for most of our software; it applies also to any other work released this way by its authors. You can apply it to your programs, too.
When we speak of free software, we are referring to freedom, not price. Our General Public Licenses are designed to make sure that you have the freedom to distribute copies of free software (and charge for them if you wish), that you receive source code or can get it if you want it, that you can change the software or use pieces of it in new free programs, and that you know you can do these things.
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If you develop a new program, and you want it to be of the greatest possible use to the public, the best way to achieve this is to make it free software which everyone can redistribute and change under these terms.
To do so, attach the following notices to the program. It is safest to attach them to the start of each source file to most effectively state the exclusion of warranty; and each file should have at least the “copyright” line and a pointer to where the full notice is found.
one line to give the program's name and a brief idea of what it does.
Copyright (C) year name of author
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or (at
your option) any later version.
This program is distributed in the hope that it will be useful, but
WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see http://www.gnu.org/licenses/.
Also add information on how to contact you by electronic and paper mail.
If the program does terminal interaction, make it output a short notice like this when it starts in an interactive mode:
program Copyright (C) year name of author
This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
This is free software, and you are welcome to redistribute it
under certain conditions; type `show c' for details.
The hypothetical commands `show w' and `show c' should show the appropriate parts of the General Public License. Of course, your program's commands might be different; for a GUI interface, you would use an “about box”.
You should also get your employer (if you work as a programmer) or school, if any, to sign a “copyright disclaimer” for the program, if necessary. For more information on this, and how to apply and follow the GNU GPL, see http://www.gnu.org/licenses/.
The GNU General Public License does not permit incorporating your program into proprietary programs. If your program is a subroutine library, you may consider it more useful to permit linking proprietary applications with the library. If this is what you want to do, use the GNU Lesser General Public License instead of this License. But first, please read http://www.gnu.org/philosophy/why-not-lgpl.html.
This appendix covers the license for copying this manual. Note that some of the longer examples in this manual are also distributed in the directory Random Jungle-1.0.359/examples/, where a more permissive license is in effect when copying just the examples.
Copyright © 2000,2001,2002 Free Software Foundation, Inc.
51 Franklin St, Fifth Floor, Boston, MA 02110-1301, USA
Everyone is permitted to copy and distribute verbatim copies
of this license document, but changing it is not allowed.
The purpose of this License is to make a manual, textbook, or other functional and useful document free in the sense of freedom: to assure everyone the effective freedom to copy and redistribute it, with or without modifying it, either commercially or noncommercially. Secondarily, this License preserves for the author and publisher a way to get credit for their work, while not being considered responsible for modifications made by others.
This License is a kind of “copyleft”, which means that derivative works of the document must themselves be free in the same sense. It complements the GNU General Public License, which is a copyleft license designed for free software.
We have designed this License in order to use it for manuals for free software, because free software needs free documentation: a free program should come with manuals providing the same freedoms that the software does. But this License is not limited to software manuals; it can be used for any textual work, regardless of subject matter or whether it is published as a printed book. We recommend this License principally for works whose purpose is instruction or reference.
This License applies to any manual or other work, in any medium, that contains a notice placed by the copyright holder saying it can be distributed under the terms of this License. Such a notice grants a world-wide, royalty-free license, unlimited in duration, to use that work under the conditions stated herein. The “Document”, below, refers to any such manual or work. Any member of the public is a licensee, and is addressed as “you”. You accept the license if you copy, modify or distribute the work in a way requiring permission under copyright law.
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The Document may include Warranty Disclaimers next to the notice which states that this License applies to the Document. These Warranty Disclaimers are considered to be included by reference in this License, but only as regards disclaiming warranties: any other implication that these Warranty Disclaimers may have is void and has no effect on the meaning of this License.
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If you publish printed copies (or copies in media that commonly have printed covers) of the Document, numbering more than 100, and the Document's license notice requires Cover Texts, you must enclose the copies in covers that carry, clearly and legibly, all these Cover Texts: Front-Cover Texts on the front cover, and Back-Cover Texts on the back cover. Both covers must also clearly and legibly identify you as the publisher of these copies. The front cover must present the full title with all words of the title equally prominent and visible. You may add other material on the covers in addition. Copying with changes limited to the covers, as long as they preserve the title of the Document and satisfy these conditions, can be treated as verbatim copying in other respects.
If the required texts for either cover are too voluminous to fit legibly, you should put the first ones listed (as many as fit reasonably) on the actual cover, and continue the rest onto adjacent pages.
If you publish or distribute Opaque copies of the Document numbering more than 100, you must either include a machine-readable Transparent copy along with each Opaque copy, or state in or with each Opaque copy a computer-network location from which the general network-using public has access to download using public-standard network protocols a complete Transparent copy of the Document, free of added material. If you use the latter option, you must take reasonably prudent steps, when you begin distribution of Opaque copies in quantity, to ensure that this Transparent copy will remain thus accessible at the stated location until at least one year after the last time you distribute an Opaque copy (directly or through your agents or retailers) of that edition to the public.
It is requested, but not required, that you contact the authors of the Document well before redistributing any large number of copies, to give them a chance to provide you with an updated version of the Document.
You may copy and distribute a Modified Version of the Document under the conditions of sections 2 and 3 above, provided that you release the Modified Version under precisely this License, with the Modified Version filling the role of the Document, thus licensing distribution and modification of the Modified Version to whoever possesses a copy of it. In addition, you must do these things in the Modified Version:
If the Modified Version includes new front-matter sections or appendices that qualify as Secondary Sections and contain no material copied from the Document, you may at your option designate some or all of these sections as invariant. To do this, add their titles to the list of Invariant Sections in the Modified Version's license notice. These titles must be distinct from any other section titles.
You may add a section Entitled “Endorsements”, provided it contains nothing but endorsements of your Modified Version by various parties—for example, statements of peer review or that the text has been approved by an organization as the authoritative definition of a standard.
You may add a passage of up to five words as a Front-Cover Text, and a passage of up to 25 words as a Back-Cover Text, to the end of the list of Cover Texts in the Modified Version. Only one passage of Front-Cover Text and one of Back-Cover Text may be added by (or through arrangements made by) any one entity. If the Document already includes a cover text for the same cover, previously added by you or by arrangement made by the same entity you are acting on behalf of, you may not add another; but you may replace the old one, on explicit permission from the previous publisher that added the old one.
The author(s) and publisher(s) of the Document do not by this License give permission to use their names for publicity for or to assert or imply endorsement of any Modified Version.
You may combine the Document with other documents released under this License, under the terms defined in section 4 above for modified versions, provided that you include in the combination all of the Invariant Sections of all of the original documents, unmodified, and list them all as Invariant Sections of your combined work in its license notice, and that you preserve all their Warranty Disclaimers.
The combined work need only contain one copy of this License, and multiple identical Invariant Sections may be replaced with a single copy. If there are multiple Invariant Sections with the same name but different contents, make the title of each such section unique by adding at the end of it, in parentheses, the name of the original author or publisher of that section if known, or else a unique number. Make the same adjustment to the section titles in the list of Invariant Sections in the license notice of the combined work.
In the combination, you must combine any sections Entitled “History” in the various original documents, forming one section Entitled “History”; likewise combine any sections Entitled “Acknowledgements”, and any sections Entitled “Dedications”. You must delete all sections Entitled “Endorsements.”
You may make a collection consisting of the Document and other documents released under this License, and replace the individual copies of this License in the various documents with a single copy that is included in the collection, provided that you follow the rules of this License for verbatim copying of each of the documents in all other respects.
You may extract a single document from such a collection, and distribute it individually under this License, provided you insert a copy of this License into the extracted document, and follow this License in all other respects regarding verbatim copying of that document.
A compilation of the Document or its derivatives with other separate and independent documents or works, in or on a volume of a storage or distribution medium, is called an “aggregate” if the copyright resulting from the compilation is not used to limit the legal rights of the compilation's users beyond what the individual works permit. When the Document is included in an aggregate, this License does not apply to the other works in the aggregate which are not themselves derivative works of the Document.
If the Cover Text requirement of section 3 is applicable to these copies of the Document, then if the Document is less than one half of the entire aggregate, the Document's Cover Texts may be placed on covers that bracket the Document within the aggregate, or the electronic equivalent of covers if the Document is in electronic form. Otherwise they must appear on printed covers that bracket the whole aggregate.
Translation is considered a kind of modification, so you may distribute translations of the Document under the terms of section 4. Replacing Invariant Sections with translations requires special permission from their copyright holders, but you may include translations of some or all Invariant Sections in addition to the original versions of these Invariant Sections. You may include a translation of this License, and all the license notices in the Document, and any Warranty Disclaimers, provided that you also include the original English version of this License and the original versions of those notices and disclaimers. In case of a disagreement between the translation and the original version of this License or a notice or disclaimer, the original version will prevail.
If a section in the Document is Entitled “Acknowledgements”, “Dedications”, or “History”, the requirement (section 4) to Preserve its Title (section 1) will typically require changing the actual title.
You may not copy, modify, sublicense, or distribute the Document except as expressly provided for under this License. Any other attempt to copy, modify, sublicense or distribute the Document is void, and will automatically terminate your rights under this License. However, parties who have received copies, or rights, from you under this License will not have their licenses terminated so long as such parties remain in full compliance.
The Free Software Foundation may publish new, revised versions of the GNU Free Documentation License from time to time. Such new versions will be similar in spirit to the present version, but may differ in detail to address new problems or concerns. See http://www.gnu.org/copyleft/.
Each version of the License is given a distinguishing version number. If the Document specifies that a particular numbered version of this License “or any later version” applies to it, you have the option of following the terms and conditions either of that specified version or of any later version that has been published (not as a draft) by the Free Software Foundation. If the Document does not specify a version number of this License, you may choose any version ever published (not as a draft) by the Free Software Foundation.
To use this License in a document you have written, include a copy of the License in the document and put the following copyright and license notices just after the title page:
Copyright (C) year your name.
Permission is granted to copy, distribute and/or modify this document
under the terms of the GNU Free Documentation License, Version 1.2
or any later version published by the Free Software Foundation;
with no Invariant Sections, no Front-Cover Texts, and no Back-Cover
Texts. A copy of the license is included in the section entitled ``GNU
Free Documentation License''.
If you have Invariant Sections, Front-Cover Texts and Back-Cover Texts, replace the “with...Texts.” line with this:
with the Invariant Sections being list their titles, with
the Front-Cover Texts being list, and with the Back-Cover Texts
being list.
If you have Invariant Sections without Cover Texts, or some other combination of the three, merge those two alternatives to suit the situation.
If your document contains nontrivial examples of program code, we recommend releasing these examples in parallel under your choice of free software license, such as the GNU General Public License, to permit their use in free software.
rjungle macrosThis index covers all rjungle builtins, as well as several useful
composite macros. References are exclusively to the places where a
macro is introduced the first time.
Random Jungle: HistoryRandom Jungle: Invoking Random JungleRandom Jungle: Intro