This is yap.info, produced by makeinfo version 4.6 from yap.tex.

START-INFO-DIR-ENTRY
* Yap: (yap).           YAP Prolog User's Manual.
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File: yap.info,  Node: Top,  Up: (dir)

YAP Prolog
**********

This file documents the YAP Prolog System version 4.5.2, a
high-performance Prolog compiler developed at LIACC, Universidade do
Porto. YAP is based on David H. D. Warren's WAM (Warren Abstract
Machine), with several optimizations for better performance. YAP follows
the Edinburgh tradition, and is largely compatible with DEC-10 Prolog,
Quintus Prolog, and especially with C-Prolog.

   This file contains the CLP(Q,R) manual as distributed by the Austrian
Research Institute for Artificial Intelligence (OFAI). Permission on
this document follows the following license:

   Copyright (C) 1992,1993,1994,1995 OFAI Austrian Research Institute
for Artificial Intelligence (OFAI) Schottengasse 3 A-1010 Vienna,
Austria

   Permission is granted to make and distribute verbatim copies of this
manual provided the copyright notice and this permission notice are
preserved on all copies.

   Permission is granted to copy and distribute modified versions of
this manual under the conditions for verbatim copying, provided that the
entire resulting derived work is distributed under the terms of a
permission notice identical to this one.

   Permission is granted to copy and distribute translations of this
manual into another language, under the above conditions for modified
versions, except that this permission notice may be stated in a
translation approved by the OFAI.

   This file contains a chapter on CHR. This package is distributed
under license from LMU (Ludwig-Maximilians-University), Munich, Germany:

   Permission is granted to copy and distribute modified versions of
this chapter under the conditions for verbatim copying, provided that
the entire resulting derived work is distributed under the terms of a
permission notice identical to this one.

   Permission is granted to copy and distribute translations of this
chapter into another language, under the above conditions for modified
versions, except that this permission notice may be stated in a
translation approved by LMU.

   Copyright (C) 1996-98 LMU (Ludwig-Maximilians-University)
Munich, Germany

   This file contains extracts of the SWI-Prolog manual, as written by
Jan Wielemaker. Our thanks to the author for his kind permission in
allowing us to include his text in this document.

* Menu:

* Intro:: Introduction
* Install:: Installation
* Run:: Running YAP
* Syntax:: The syntax of YAP
* Loading Programs:: Loading Prolog programs
* Modules:: Using Modules in YAP
* Builtins:: Built In Predicates
* Library:: Library Predicates
* Extensions:: Extensions to Standard YAP
* Rational Trees:: Working with Rational Trees
* Coroutining:: Changing the Execution of Goals
* Attributed Variables:: Using attributed Variables
* CLPQR:: The CLP(Q,R) System
* CHR:: The CHR System
* Logtalk:: The Logtalk Object-Oriented System
* Threads:: Thread Library
* Parallelism:: Running in Or-Parallel
* Tabling:: Storing Intermediate Solutions of programs
* Low Level Profiling:: Profiling Abstract Machine Instructions
* Low Level Tracing:: Tracing at Abstract Machine Level
* Debugging:: Using the Debugger
* Efficiency:: Efficiency Considerations
* C-Interface:: Interfacing predicates written in C
* YapLibrary:: Using YAP as a library in other programs
* Compatibility:: Compatibility with other Prolog systems
* Predicate Index:: An item for each predicate
* Concept Index:: An item for each concept

Built In Predicates
* Control:: Controlling the execution of Prolog programs
* Undefined Procedures:: Handling calls to Undefined Procedures
* Testing Terms:: Predicates on Terms
* Comparing Terms:: Comparison of Terms
* Arithmetic:: Arithmetic in YAP
* I/O:: Input/Output with YAP
* Database:: Modifying Prolog's Database
* Sets:: Finding All Possible Solutions
* Grammars:: Grammar Rules
* Preds:: Predicate Information
* OS:: Access to Operating System Functionality
* Term Modification:: Updating Prolog Terms
* Profiling:: Profiling Prolog Execution
* Call Counting:: Limiting the Maximum Number of Reductions
* Arrays:: Supporting Global and Local Arrays
* Preds:: Information on Predicates
* Misc:: Miscellaneous Predicates


Subnodes of Running
* Running Yap Interactively:: Interacting with Yap
* Running Prolog Files:: Running Prolog files as scripts

Subnodes of Syntax
* Formal Syntax:: Syntax of Terms
* Tokens:: Syntax of Prolog tokens

Subnodes of Tokens
* Numbers:: Integer and Floating-Point Numbers
* Strings:: Sequences of Characters
* Atoms:: Atomic Constants
* Variables:: Logical Variables
* Punctuation Tokens:: Tokens that separate other tokens
* Layout:: Comments and Other Layout Rules

Subnodes of Numbers
* Integers:: How Integers are read and represented
* Floats:: Floating Point Numbers

Subnodes of Loading Programs
* Compiling:: Program Loading and Updating
* Setting the Compiler:: Changing the compiler's parameters
* Saving:: Saving and Restoring Programs

Subnodes of Modules
* Module Concepts:: The Key Ideas in Modules
* Defining Modules:: How To Define a New Module
* Using Modules:: How to Use a Module
* Meta-Predicates in Modules:: How to Handle New Meta-Predicates

Subnodes of Input/Output
* Streams and Files:: Handling Streams and Files
* C-Prolog File Handling:: C-Prolog Compatible File Handling
* I/O of Terms:: Input/Output of terms
* I/O of Characters:: Input/Output of Characters
* I/O for Streams:: Input/Output using Streams
* C-Prolog to Terminal:: C-Prolog compatible Character I/O to terminal
* I/O Control:: Controlling your Input/Output
* Sockets:: Using Sockets from YAP

Subnodes of Database
* Modifying the Database:: Asserting and Retracting
* Looking at the Database:: Finding out what is in the Data Base
* Database References:: Using Data Base References
* Internal Database:: YAP's Internal Database
* BlackBoard:: Storing and Fetching Terms in the BlackBoard

Subnodes of Library
* Apply Macros:: Apply a Predicate to a list or to sub-terms.
* Association Lists:: Binary Tree Implementation of Association Lists.
* AVL Trees:: Predicates to add and lookup balanced binary  trees.
* Heaps:: Labelled binary tree where the key of each node is less
    than or equal to the keys of its children.
* Lists:: List Manipulation
* Ordered Sets:: Ordered Set Manipulation
* Pseudo Random:: Pseudo Random Numbers
* Queues:: Queue Manipulation
* Random:: Random Numbers
* Red-Black Trees:: Predicates to add, lookup and delete in red-black binary  trees.
* RegExp:: Regular Expression Manipulation
* Splay Trees:: Splay Trees
* String I/O:: Writing To and Reading From Strings
* System:: System Utilities
* Terms:: Utilities on Terms
* Cleanup:: Call With registered Cleanup Calls
* Timeout:: Call With Timeout
* Trees:: Updatable Binary Trees
* UGraphs:: Unweighted Graphs

Subnodes of Debugging
* Deb Preds:: Debugging Predicates
* Deb Interaction:: Interacting with the debugger

Subnodes of Compatibility
* C-Prolog:: Compatibility with the C-Prolog interpreter
* SICStus Prolog:: Compatibility with the Quintus and SICStus Prolog systems
* ISO Prolog::  Compatibility with the ISO Prolog standard

Subnodes of Attributes
* Attribute Declarations:: Declaring New Attributes
* Attribute Manipulation:: Setting and Reading Attributes
* Attributed Unification:: Tuning the Unification Algorithm
* Displaying Attributes:: Displaying Attributes in User-Readable Form
* Projecting Attributes:: Obtaining the Attributes of Interest
* Attribute Examples:: Two Simple Examples of how to use Attributes.

Subnodes of CLP(Q,R)
* Introduction to CLPQR:: The CLP(Q,R) System
* Referencing CLPQR:: How to Reference CLP(Q,R)
* CLPQR Acknowledgments:: Acknowledgments for CLP(Q,R)
* Solver Interface:: Using the CLP(Q,R) System
* Notational Conventions:: The CLP(Q,R) Notation
* Solver Predicates:: The CLP(Q,R) Interface Predicates
* Unification:: Unification and CLP(Q,R)
* Feedback and Bindings:: Information flow in CLP(Q,R)
* Linearity and Nonlinear Residues:: Linear and Nonlinear Constraints
* How Nonlinear Residues are made to disappear:: Handling Nonlinear Residues
* Isolation Axioms:: Isolating the Variable to be Solved
* Numerical Precision and Rationals:: Reals and Rationals
* Projection and Redundancy Elimination:: Presenting Bindings for Query Variables
* Variable Ordering:: Linear Relationships between Variables
* Turning Answers into Terms:: using `call_residue/2'
* Projecting Inequalities:: How to project linear inequations
* Why Disequations:: Using Disequations in CLP(Q,R)
* Syntactic Sugar:: An easier syntax
* Monash Examples:: The Monash Library
* Compatibility Notes:: CLP(Q,R) and the clp(R) interpreter
* A Mixed Integer Linear Optimization Example:: MIP models
* Implementation Architecture:: CLP(Q,R) Components
* Fragments and Bits:: Final Last Words on CLP(Q,R)
* CLPQR Bugs:: Bugs in CLP(Q,R)
* CLPQR References:: References for CLP(Q,R)

Subnodes of CHR
* CHR Copyright::
* CHR Introduction::
* CHR Introductory Examples::
* CHR Library::
* CHR Debugging::
* CHR Programming Hints::
* CHR Constraint Handlers::
* CHR Backward Compatibility::

Subnodes of C-Interface
* Manipulating Terms:: Primitives available to the C programmer
* Unifying Terms:: How to Unify Two Prolog Terms
* Manipulating Strings:: From character arrays to Lists of codes and back
* Memory Allocation:: Stealing Memory From Yap
* Controlling Streams:: Control How Yap sees Streams
* Calling Yap From C:: From C to Yap to C to Yap
* Writing C:: Writing Predicates in C
* Loading Objects:: Loading Object Files
* Sav&Rest:: Saving and Restoring
* Yap4 Notes:: Changes in Foreign Predicates Interface

Subnodes of C-Prolog
* Major Differences with C-Prolog:: Major Differences between YAP and C-Prolog
* Fully C-Prolog Compatible:: Yap predicates fully compatible with
C-Prolog
* Not Strictly C-Prolog Compatible:: Yap predicates not strictly as C-Prolog
* Not in C-Prolog:: Yap predicates not available in C-Prolog
* Not in YAP:: C-Prolog predicates not available in YAP

Subnodes of SICStus Prolog
* Major Differences with SICStus:: Major Differences between YAP and SICStus Prolog
* Fully SICStus Compatible:: Yap predicates fully compatible with
SICStus Prolog
* Not Strictly SICStus Compatible:: Yap predicates not strictly as
SICStus Prolog
* Not in SICstus Prolog:: Yap predicates not available in SICStus Prolog


Tables
* Operators:: Predefined operators


File: yap.info,  Node: Intro,  Next: Install,  Up: Top

Introduction
************

This document provides User information on version 4.5.2 of YAP (_yet
another prolog_). The YAP Prolog System is a high-performance Prolog
compiler developed at LIACC, Universidade do Porto. YAP provides
several important features:

   * Speed: YAP is widely considered one of the fastest available Prolog
     systems.

   * Functionality: it supports stream I/O, sockets, modules,
     exceptions, Prolog debugger, C-interface, dynamic code, internal
     database, DCGs, saved states, co-routining, arrays.

   * We explicitly allow both commercial and non-commercial use of YAP.

   YAP is based on the David H. D. Warren's WAM (Warren Abstract
Machine), with several optimizations for better performance. YAP
follows the Edinburgh tradition, and was originally designed to be
largely compatible with DEC-10 Prolog, Quintus Prolog, and especially
with C-Prolog.

   YAP implements most of the ISO-Prolog standard. We are striving at
full compatibility, and the manual describes what is still missing. The
manual also includes a (largely incomplete) comparison with SICStus
Prolog.

   The document is intended neither as an introduction to Prolog nor to
the implementation aspects of the compiler. A good introduction to
programming in Prolog is the book `The Art of Prolog', by L. Sterling
and E. Shapiro, published by "The MIT Press, Cambridge MA". Other
references should include the classical `Programming in Prolog', by
W.F. Clocksin and C.S. Mellish, published by Springer-Verlag.

   YAP 4.3 is known to build with many versions of gcc (<= gcc-2.7.2, >=
gcc-2.8.1, >= egcs-1.0.1, gcc-2.95.*) and on a variety of Unixen: SunOS
4.1, Solaris 2.*, Irix 5.2, HP-UX 10, Dec Alpha Unix, Linux 1.2 and
Linux 2.* (RedHat 4.0 thru 5.2, Debian 2.*) in both the x86 and alpha
platforms. It has been built on Windows NT 4.0 using Cygwin from Cygnus
Solutions (see README.nt) and using Visual C++ 6.0.

   The overall copyright and permission notice for YAP4.3 can be found
in the Artistic file in this directory. YAP follows the Perl Artistic
license, and it is thus non-copylefted freeware.

   If you have a question about this software, desire to add code,
found a bug, want to request a feature, or wonder how to get further
assistance, please send e-mail to <yappers@ncc.up.pt>.  To subscribe to
the mailing list, send a request to <majordomo@ncc.up.pt> with body
"subscribe yappers".

   Online documentation is available for YAP at:

   <http://www.ncc.up.pt/~vsc/Yap/>

   Recent versions of Yap, including both source and selected binaries,
can be found from this same URL.

   This manual was written by Vi'tor Santos Costa, Lui's Damas,
Roge'rio Reis, and Ru'ben Azevedo. The manual is largely based on the
DECsystem-10 Prolog User's Manual by D.L. Bowen, L. Byrd, F. C. N.
Pereira, L. M. Pereira, and D. H. D. Warren. We have also used comments
from the Edinburgh Prolog library written by R. O'Keefe. We would also
like to gratefully acknowledge the contributions from Ashwin
Srinivasian.

   We are happy to include in YAP several excellent packages developed
under separate licenses. Our thanks to the authors for their kind
authorization to include these packages.

   The packages are, in alphabetical order:

   * The CHR package developed at TUM by
     Ludwig-Maximilians-Universitaet Muenchen (LMU) by Dr. Fruehwirth
     Thom and by Dr. Christian Holzbaur. The package is distributed
     under license from LMU (Ludwig-Maximilians-University), Munich,
     Germany:

     Permission is granted to copy and distribute modified versions of
     this chapter under the conditions for verbatim copying, provided
     that the entire resulting derived work is distributed under the
     terms of a permission notice identical to this one.

     Permission is granted to copy and distribute translations of this
     chapter into another language, under the above conditions for
     modified versions, except that this permission notice may be
     stated in a translation approved by LMU.

     Copyright (C) 1996-98 LMU (Ludwig-Maximilians-University)
     Munich, Germany

   * The CLP(Q,R) package developed at OFAI Austrian Research Institute
     for Artificial Intelligence by Christian Holzbaur. The package is
     distributed under the OFAI license. Documentation on this package
     is a chapter of this manual, which is covered by the OFAI license:

     Copyright (C) 1992,1993,1994,1995 OFAI Austrian Research Institute
     for Artificial Intelligence (OFAI) Schottengasse 3 A-1010 Vienna,
     Austria

     Permission is granted to make and distribute verbatim copies of
     this manual provided the copyright notice and this permission
     notice are preserved on all copies.

     Permission is granted to copy and distribute modified versions of
     this manual under the conditions for verbatim copying, provided
     that the entire resulting derived work is distributed under the
     terms of a permission notice identical to this one.

     Permission is granted to copy and distribute translations of this
     manual into another language, under the above conditions for
     modified versions, except that this permission notice may be
     stated in a translation approved by the OFAI.

   * The Logtalk Object-Oriented system is developed at the University
     of Beira Interior, Portugal, by Paulo Moura.  The package is
     distributed under the Perl Artistic License.  Instructions about
     loading this package are included in this document.  The
     documentation on this package is distributed separately from
     yap.tex.

     Copyright (C) 1998-2001 Paulo Moura

   * The Pillow WEB library developed at Universidad Politecnica de
     Madrid by the CLIP group. This package is distributed under the
     FSF's LGPL. Documentation on this package is distributed
     separately from yap.tex.

   * The yap2swi library implements some of the functionality of SWI's
     PL interface. Please do refer to the SWI-Prolog home page:

     `http://www.swi-prolog.org'

     for more information on SWI-Prolog and for a detailed description
     of its foreign interface.



File: yap.info,  Node: Install,  Next: Run,  Prev: Intro,  Up: Top

Installing YAP
**************

* Menu:

* Configuration Options:: Tuning the Functionality of YAP Machine
* Machine Options:: Tuning YAP for a Particular Machine and Compiler

   To compile YAP it should be sufficient to:

  1. `mkdir ARCH'.

  2. `cd ARCH'.

  3. `../configure ...options...'.

     Notice that by default `configure' gives you a vanilla
     configuration. For instance, in order to use coroutining and/or CLP
     you need to do

          ../configure --enable-coroutining ...options...
     Please *note Configuration Options:: for extra options.

  4. check the Makefile for any extensions or changes you want to make.

     YAP uses `autoconf'. Recent versions of Yap try to follow GNU
     conventions on where to place software.

        * The main executable is placed at `BINDIR'. This executable is
          actually a script that calls the Prolog engine, stored at
          `LIBDIR'.

        * `LIBDIR' is the directory where libraries are stored.
          YAPLIBDIR is a subdirectory that contains the Prolog engine
          and a Prolog library.

        * `INCLUDEDIR' is used if you want to use Yap as a library.

        * `INFODIR' is where to store `info' files. Usually
          `/usr/local/info', `/usr/info', or `/usr/share/info'.

  5. `make'.

  6. If the compilation succeeds, try `./yap'.

  7. If you feel satisfied with the result, do `make install'.

  8. `make install-info' will create the info files in the standard
     info directory.

  9. `make html' will create documentation in html format in the
     predefined directory.

     In most systems you will need to be superuser in order to do `make
     install' and `make info' on the standard directories.


File: yap.info,  Node: Configuration Options,  Next: Machine Options,  Up: Install

Tuning the Functionality of YAP
===============================

Compiling Yap with the standard options give you a plain vanilla
Prolog. You can tune Yap to include extra functionality by calling
`configure' with the appropriate options:

   * `--enable-rational-trees=yes' gives you support for infinite
     rational trees.

   * `--enable-coroutining=yes' gives you support for coroutining,
     including freezing of goals, attributed variables, and
     constraints. This will also enable support for infinite rational
     trees.

   * `--enable-depth-limit=yes' allows depth limited evaluation, say for
     implementing iterative deepening.

   * `--enable-low-level-tracer=yes' allows support for tracing all
     calls, retries, and backtracks in the system. This can help in
     debugging your application, but results in performance loss.

   * `--enable-wam-profile=yes' allows profiling of abstract machine
     instructions. This is useful when developing YAP, should not be so
     useful for normal users.

   * `--enable-condor=yes' allows using the Condor system that support
     High Throughput Computing (HTC) on large collections of
     distributively owned computing resources.

   * `--enable-tabling={local,batched}' allows one of the two forms of
     tabling. This option is still experimental.

   * `--enable-parallelism={env-copy,sba,a-cow}' allows or-parallelism
     supported by one of these three forms. This option is still highly
     experimental.

   * `--with-gmp[=DIR]' give a path to where one can find the `GMP'
     library if not installed in the default path.


   Next follow machine dependent details:


File: yap.info,  Node: Machine Options,  Prev: Configuration Options,  Up: Install

Tuning YAP for a Particular Machine and Compiler
================================================

The default options should give you best performance under `GCC'.
Although the system is tuned for this compiler we have been able to
compile versions of Yap under lcc in Linux, Sun's cc compiler, IBM's
xlc, SGI's cc, and Microsoft's Visual C++ 6.0.

* Menu:

* Tuning for GCC:: Using the GNUCC compiler
* Compiling Under Visual C++:: Using Microsoft's Visual C++ environment
* Tuning for SGI cc:: Compiling Under SGI's `cc'


File: yap.info,  Node: Tuning for GCC,  Next: Compiling Under Visual C++,  Up: Machine Options

Tuning YAP for `GCC'.
=====================

Yap has been developed to take advantage of `GCC' (but not to depend on
it). The major advantage of `GCC' is threaded code and explicit
register reservation.

   YAP is set by default to compile with the best compilation flags we
know. Even so, a few specific options reduce portability.  The option
   * `--enable-max-performance=yes' will try to support the best
     available flags for a specific architectural model. Currently, the
     option assumes a recent version of `GCC'.

   * `--enable-debug-yap' compiles Yap so that it can be debugged by
     tools such as `dbx' or `gdb'.

   Here follow a few hints:

   On x86 machines the flags:

     YAP_EXTRAS= ... -DBP_FREE=1

   tells us to use the `%bp' register (frame-pointer) as the emulator's
program counter. This seems to be stable and is now default.

   On  Sparc/Solaris2 use:

     YAP_EXTRAS= ...   -mno-app-regs -DOPTIMISE_ALL_REGS_FOR_SPARC=1

   and YAP will get two extra registers! This trick does not work on
SunOS 4 machines.

   Note that versions of GCC can be tweaked to recognize different
processors within the same instruction set, eg, 486, Pentium, and
PentiumPro for the x86; or Ultrasparc, and Supersparc for Sparc.
Unfortunately, some of these tweaks do may make Yap run slower or not
at all in other machines with the same instruction set, so they cannot
be made default.

   Last, the best options also depends on the version of GCC you are
using, and it is a good idea to consult the GCC manual under the menus
"Invoking GCC"/"Submodel Options". Specifically, you should check
`-march=XXX' for recent versions of GCC/EGCS. In the case of `GCC2.7'
and other recent versions of `GCC' you can check:

`486:'
     In order to take advantage of 486 specific optimizations in GCC
     2.7.*:

          YAP_EXTRAS= ... -m486 -DBP_FREE=1

`Pentium:'
          YAP_EXTRAS= ... -m486 -malign-loops=2 -malign-jumps=2 \
                                -malign-functions=2

`PentiumPro and other recent Intel and AMD machines:'
     PentiumPros are known not to require alignment. Check your version
     of `GCC' for the best `-march' option.

`Super and UltraSparcs:'
          YAP_EXTRAS= ... -msupersparc

`MIPS: if have a recent machine and you need a 64 bit wide address'
     space you can use the abi 64 bits or eabi option, as in:
          CC="gcc -mabi=64" ./configure --...
     Be careful. At least for some versions of `GCC', compiling with
     `-g' seems to result in broken code.

`WIN32: GCC is distributed in the MINGW32 and CYGWIN packages.'
     The Mingw32 environment is available from the URL:

     `http://www.mingw.org'

     You will need to install the `msys' and `mingw' packages. You
     should be able to do configure, make and make install.

     If you use mingw32 you may want to search the contributed packages
     for the `gmp' multi-precision arithmetic library. If you do setup
     Yap with `gmp' note that `libgmp.dll' must be in the path,
     otherwise Yap will not be able to execute.

     CygWin environment is available from the URL:

     `http://www.cygwin.com'

     and mirrors. We suggest using recent versions of the cygwin shell.
     The compilation steps under the cygwin shell are as follows:

          mkdir cyg
          $YAPSRC/configure --enable-coroutining \\
                            --enable-depth-limit \\
                            --enable-max-performance
          make
          make install

     By default, Yap will use the `--enable-cygwin=no' option to
     disable the use of the cygwin dll and to enable the mingw32
     subsystem instead. Yap thus will not need the cygwin dll. It
     instead accesses the system's `CRTDLL.DLL' `C' run time library
     supplied with Win32 platforms through the mingw32 interface. Note
     that some older WIN95 systems may not have `CRTDLL.DLL', in this
     case it should be sufficient to import the file from a newer WIN95
     or WIN98 machine.

     You should check the default installation path which is set to
     `/PROGRA~1/Yap' in the standard Makefile. This string will usually
     be expanded into `c:\Program Files\Yap' by Windows.

     The cygwin environment does not provide gmp. You can fetch a dll
     for the gmp library from <http://www.sf.net/projects/mingwrep>.

     It is also possible to configure Yap to be a part of the cygwin
     environment. In this case you should use:
          mkdir cyg
          $YAPSRC/configure --enable-coroutining \\
                            --enable-max-performance \\
                            --enable-cygwin=yes
          make
          make install
     Yap will then compile using the cygwin library and will be
     installed in cygwin's `/usr/local'. You can use Yap from a cygwin
     console, or as a standalone application as long as it can find
     `cygwin1.dll' in its path.



File: yap.info,  Node: Compiling Under Visual C++,  Next: Tuning for SGI cc,  Prev: Tuning for GCC,  Up: Machine Options

Compiling Under Visual C++
--------------------------

Yap compiles cleanly under Microsoft's Visual C++ release 6.0. We next
give a step-by-step tutorial on how to compile Yap manually using this
environment.

   First, it is a good idea to build Yap as a DLL:

  1. create a project named yapdll using File.New. The project will be a
     DLL project, initially empty.

     Notice that either the project is named yapdll or you must replace
     the preprocessors variable YAPDLL_EXPORTS to match your project
     names in the files `YapInterface.h' and `c_interface.c'.

  2. add all .c files in the $YAPSRC/C directory and in the
     $YAPSRC\OPTYAP directory to the Project's `Source Files' (use
     FileView).

  3. add all .h files in the $YAPSRC/H directory, $YAPSRC\INCLUDE
     directory and in the $YAPSRC\OPTYAP subdirectory to the Project's
     `Header Files'.

  4. Ideally, you should now use `m4' to generate extra  .h from .m4
     files and use `configure' to create a `config.h'. Or, you can be
     lazy, and fetch these files from $YAPSRC\VC\INCLUDE.

  5. You may want to go to `Build.Set Active Configuration' and set
     `Project Type' to `Release'

  6. To use Yap's own include directories you have to set the Project
     option  `Project.Project Settings.C/C++.Preprocessor.Additional
     Include Directories' to include the directories $YAPSRC\H,
     $YAPSRC\VC\INCLUDE, $YAPSRC\OPTYAP and $YAPSRC\INCLUDE.  The
     syntax is:

          $YAPSRC\H, $YAPSRC\VC\include, $YAPSRC\OPTYap, $YAPSRC\include

  7. Build: the system should generate an `yapdll.dll' and an
     `yapdll.lib'.

  8. Copy the file `yapdll.dll' to your path. The file `yapdll.lib'
     should also be copied to a location where the linker can find it.

   Now you are ready to create a console interface for Yap:
  1. create a second project  say `wyap' with `File.New'. The project
     will be a WIN32 console project, initially empty.

  2. add $YAPSRC\CONSOLE\YAP.C to the `Source Files'.

  3. add $YAPSRC\VC\INCLUDE\CONFIG.H and the files in $YAPSRC\INCLUDE to
     the `Header Files'.

  4. You may want to go to `Build.Set Active Configuration' and set
     `Project Type' to `Release'.

  5. you will eventually need to bootstrap the system by booting from
     `boot.yap', so write:

                  -b $YAPSRC\pl\boot.yap

     in `Project.Project Settings.Debug.Program Arguments'.

  6. You need the sockets and yap libraries. Add

          ws2_32.lib yapdll.lib to

     to

     to `Project.Project Settings.Link.Object/Library Modules'

     You may also need to set the `Link Path' so that VC++ will find
     `yapdll.lib'.

  7. set `Project.Project Settings.C/C++.Preprocessor.Additional
     Include Directories' to include the $YAPSRC/VC/INCLUDE and
     $YAPSRC/INCLUDE.

     The syntax is:

          $YAPSRC\VC\include, $YAPSRC\include

  8. Build the system.

  9. Use `Build.Start Debug' to boot the system, and then create the
     saved state with

          ['$YAPSRC\\pl\\init'].
          save_program(startup).
          ^Z

     That's it, you've got Yap and the saved state!

   The $YAPSRC\VC directory has the make files to build Yap4.3.17 under
VC++ 6.0.


File: yap.info,  Node: Tuning for SGI cc,  Prev: Compiling Under Visual C++,  Up: Machine Options

Compiling Under SGI's cc
------------------------

YAP should compile under the Silicon Graphic's `cc' compiler, although
we advise using the GNUCC compiler, if available.

`64 bit'
     Support for 64 bits should work by using (under Bourne shell
     syntax):
          CC="cc -64" $YAP_SRC_PATH/configure --...


File: yap.info,  Node: Run,  Next: Syntax,  Prev: Install,  Up: Top

Running YAP
***********

* Menu:

* Running Yap Interactively:: Interacting with Yap
* Running Prolog Files:: Running Prolog files as scripts

   We next describe how to invoke Yap in Unix systems.


File: yap.info,  Node: Running Yap Interactively,  Prev: Running Prolog Files,  Up: Run

Running Yap Interactively
=========================

Most often you will want to use Yap in interactive mode. Assuming that
YAP is in the user's search path, the top-level can be invoked under
Unix with the following command:

     yap [-s n] [-h n] [-a n] [-c IP_HOST port ] [filename]

All the arguments and flags are optional and have the following meaning:
`-?'
     print a short error message.

`-s N'
     allocate N K bytes for local and global stacks

`-h N'
     allocate N K bytes for heap and auxiliary stacks

`-t N'
     allocate N K bytes for the trail stack

`-l YAP_FILE'
     compile the Prolog file YAP_FILE before entering the top-level.

`-L YAP_FILE'
     compile the Prolog file YAP_FILE and then halt. This option is
     useful for implementing scripts.

`-b BOOT_FILE'
     boot code is in Prolog file BOOT_FILE. The filename must define
     the predicate '$live'/0.

`-c IP_HOST port'
     connect standard streams to host IP_HOST at port port

`filename'
     restore state saved in the given file

`--'
     separator for arguments to Prolog code. These arguments are visible
     through the unix/1 built-in.

   Note that YAP will output an error message on the following
conditions:

   * a file name was given but the file does not exist or is not a saved
     YAP state;

   * the necessary amount of memory could not be allocated;

   * the allocated memory is not enough to restore the state.

   When restoring a saved state, YAP will allocate the same amount of
memory as that in use when the state was saved, unless a different
amount is specified by flags in the command line. By default, YAP
restores the file `startup' from the current directory or from the YAP
library.

   * YAP usually boots from a saved state. The saved state will use the
     default installation directory to search for the YAP binary unless
     you define the environment variable YAPBINDIR.

   * YAP always tries to find saved states from the current directory
     first. If it cannot it will use the environment variable
     YAPLIBDIR, if defined, or search the default library directory.

   * YAP will try to find library files from the YAPSHAREDIR/library
     directory.


File: yap.info,  Node: Running Prolog Files,  Next: Running Yap Interactively,  Up: Run

Running Prolog Files
====================

YAP can also be used to run Prolog files as scripts, at least in
Unix-like environments. A simple example is shown next:

     #!/usr/local/bin/yap -L
     #
     # Hello World script file using Yap
     #
     
     :- write('Hello World'), nl.

   The `#!'  characters specify that the script should call the binary
file Yap. Notice that many systems will require the complete path to the
Yap binary. The `-L' flag indicates that YAP should consult the current
file when booting and then halt. The remaining arguments are then
passed to YAP. Note that YAP will skip the first lines if they start
with `#' (the comment sign for Unix's shell). YAP will consult the file
and execute any commands.

   A slightly more sophisticated example is:

     #!/usr/bin/yap -L --
     #
     # Hello World script file using Yap
     # .
     
     :- initialization(main).
     
     main :- write('Hello World'), nl.

   The `initialization' directive tells Yap to execute the goal main
after consulting the file. Source code is thus compiled and `main'
executed at the end. The `.' is useful while debugging the script as a
Prolog program: it guarantees that the syntax error will not propagate
to the Prolog code.

   Notice that the `--' is required so that the shell passes the extra
arguments to YAP.  As an example, consider the following script
`dump_args':

     #!/usr/bin/yap -L --
     #.
     
     main( [] ).
     main( [H|T] ) :-
             write( H ), nl,
             main( T ).
     
     :- unix( argv(AllArgs) ), main( AllArgs ).

   If you this run this script with the arguments:
     ./dump_args -s 10000

the script will start an YAP process with stack size `10MB', and the
list of arguments to the process will be empty.

   Often one wants to run the script as any other program, and for this
it is convenient to ignore arguments to YAP. This is possible by using
`L --' as in the next version of `dump_args':

     #!/usr/bin/yap -L --
     
     main( [] ).
     main( [H|T] ) :-
             write( H ), nl,
             main( T ).
     
     :- unix( argv(AllArgs) ), main( AllArgs ).

   The `--' indicates the next arguments are not for YAP. Instead, they
must be sent directly to the `argv' builtin. Hence, running
     ./dump_args test

will write `test' on the standard output.


File: yap.info,  Node: Syntax,  Next: Loading Programs,  Prev: Run,  Up: Top

Syntax
******

We will describe the syntax of YAP at two levels. We first will
describe the syntax for Prolog terms. In a second level we describe the
tokens from which Prolog terms are built.

* Menu:

* Formal Syntax:: Syntax of terms
* Tokens:: Syntax of Prolog tokens


File: yap.info,  Node: Formal Syntax,  Next: Tokens,  Up: Syntax

Syntax of Terms
===============

Below, we describe the syntax of YAP terms from the different classes
of tokens defined above. The formalism used will be _BNF_, extended
where necessary with attributes denoting integer precedence or operator
type.


     `
      term       ---->     subterm(1200)   end_of_term_marker
     
      subterm(N) ---->     term(M)         [M <= N]
     
      term(N)    ---->     op(N, fx) subterm(N-1)
                  |        op(N, fy) subterm(N)
                  |        subterm(N-1) op(N, xfx) subterm(N-1)
                  |        subterm(N-1) op(N, xfy) subterm(N)
                  |        subterm(N) op(N, yfx) subterm(N-1)
                  |        subterm(N-1) op(N, xf)
                  |        subterm(N) op(N, yf)
     
      term(0)   ---->      atom '(' arguments ')'
                  |        '(' subterm(1200)  ')'
                  |        '{' subterm(1200)  '}'
                  |        list
                  |        string
                  |        number
                  |        atom
                  |        variable
     
      arguments ---->      subterm(999)
                  |        subterm(999) ',' arguments
     
      list      ---->      '[]'
                  |        '[' list_expr ']'
     
      list_expr ---->      subterm(999)
                  |        subterm(999) list_tail
     
      list_tail ---->      ',' list_expr
                  |        ',..' subterm(999)
                  |        '|' subterm(999)
     '

Notes:

   * op(N,T) denotes an atom which has been previously declared with
     type T and base precedence N.

   * Since ',' is itself a pre-declared operator with type xfy and
     precedence 1000, is subterm starts with a '(', op must be followed
     by a space to avoid ambiguity with the case of a functor followed
     by arguments, eg:

          ` + (a,b)        [the same as '+'(','(a,b)) of arity one]'
     versus
          ` +(a,b)         [the same as '+'(a,b) of arity two]'

   * In the first rule for term(0) no blank space should exist between
     atom and '('.

   * Each term to be read by the YAP parser must end with a single dot,
     followed by a blank (in the sense mentioned in the previous
     paragraph). When a name consisting of a single dot could be taken
     for the end of term marker, the ambiguity should be avoided by
     surrounding the dot with single quotes.



File: yap.info,  Node: Tokens,  Prev: Formal Syntax,  Up: Syntax

Prolog Tokens
=============

Prolog tokens are grouped into the following categories:

* Menu:

* Numbers:: Integer and Floating-Point Numbers
* Strings:: Sequences of Characters
* Atoms:: Atomic Constants
* Variables:: Logical Variables
* Punctuation Tokens:: Tokens that separate other tokens
* Layout:: Comments and Other Layout Rules


File: yap.info,  Node: Numbers,  Next: Strings,  Up: Tokens

Numbers
-------

Numbers can be further subdivided into integer and floating-point
numbers.

* Menu:

* Integers:: How Integers are read and represented
* Floats:: Floating Point Numbers


File: yap.info,  Node: Integers,  Next: Floats,  Up: Numbers

Integers
........

Integer numbers are described by the following regular expression:

     `
     <integer> := {<digit>+<single-quote>|0{xXo}}<alpha_numeric_char>+
     '

where {...} stands for optionality, + optional repetition (one or more
times), <digit> denotes one of the characters 0 ... 9, | denotes or,
and <single-quote> denotes the character "'". The digits before the
<single-quote> character, when present, form the number basis, that can
go from 0, 1 and up to 36. Letters from `A' to `Z' are used when the
basis is larger than 10.

   Note that if no basis is specified then base 10 is assumed. Note also
that the last digit of an integer token can not be immediately followed
by one of the characters 'e', 'E', or '.'.

   Following the ISO standard, YAP also accepts directives of the form
`0x' to represent numbers in hexadecimal base and of the form `0o' to
represent numbers in octal base. For usefulness, YAP also accepts
directives of the form `0X' to represent numbers in hexadecimal base.

   Example: the following tokens all denote the same integer
     `10  2'1010  3'101  8'12  16'a  36'a  0xa  0o12'

   Numbers of the form `0'a' are used to represent character constants.
So, the following tokens denote the same integer:
     `0'd  100'

   YAP (version 4.5.2) supports integers that can fit the word size of
the machine. This is 32 bits in most current machines, but 64 in some
others, such as the Alpha running Linux or Digital Unix. The scanner
will read larger or smaller integers erroneously.


File: yap.info,  Node: Floats,  Prev: Integers,  Up: Numbers

Floating-point Numbers
......................

Floating-point numbers are described by:

     `
        <float> := <digit>+{<dot><digit>+}
                    <exponent-marker>{<sign>}<digit>+
                 |<digit>+<dot><digit>+
                    {<exponent-marker>{<sign>}<digit>+}
     '

where <dot> denotes the decimal-point character '.', <exponent-marker>
denotes one of 'e' or 'E', and <sign> denotes one of '+' or '-'.

   Examples:
     `10.0   10e3   10e-3   3.1415e+3'

   Floating-point numbers are represented as a double in the target
machine. This is usually a 64-bit number.


File: yap.info,  Node: Strings,  Next: Atoms,  Prev: Numbers,  Up: Tokens

Character Strings
-----------------

Strings are described by the following rules:
       string --> '"' string_quoted_characters '"'
     
       string_quoted_characters --> '"' '"' string_quoted_characters
       string_quoted_characters --> '\'
                               escape_sequence string_quoted_characters
       string_quoted_characters -->
                               string_character string_quoted_characters
     
       escape_sequence --> 'a' | 'b' | 'r' | 'f' | 't' | 'n' | 'v'
       escape_sequence --> '\' | '"' | ''' | '`'
       escape_sequence --> at_most_3_octal_digit_seq_char '\'
       escape_sequence --> 'x' at_most_2_hexa_digit_seq_char '\'
   where `string_character' in any character except the double quote
and escape characters.

   Examples:
     `""   "a string"   "a double-quote:""" '

   The first string is an empty string, the last string shows the use of
double-quoting. The implementation of YAP represents strings as lists
of integers. Since Yap4.3.0 there is no static limit on string size.

   Escape sequences can be used to include the non-printable characters
`a' (alert), `b' (backspace), `r' (carriage return), `f' (form feed),
`t' (horizontal tabulation), `n' (new line), and `v' (vertical
tabulation). Escape sequences also be include the meta-characters `\',
`"', `'', and ``'. Last, one can use escape sequences to include the
characters either as an octal or hexadecimal number.

   The next examples demonstrates the use of escape sequences in YAP:

     `"\x0c\" "\01\" "\f" "\\" '

   The first three examples return a list including only character 12
(form feed). The last example escapes the escape character.

   Escape sequences were not available in C-Prolog and in original
versions of YAP up to 4.2.0. Escape sequences can be disable by using:
     `:- yap_flag(character_escapes,off).'


File: yap.info,  Node: Atoms,  Next: Variables,  Prev: Strings,  Up: Tokens

Atoms
-----

Atoms are defined by one of the following rules:
        atom --> solo-character
        atom --> lower-case-letter name-character*
        atom --> symbol-character+
        atom --> single-quote  single-quote
        atom --> ''' atom_quoted_characters '''
     
     
       atom_quoted_characters --> ''' ''' atom_quoted_characters
       atom_quoted_characters --> '\' atom_sequence string_quoted_characters
       atom_quoted_characters --> character string_quoted_characters

   where:
        <solo-character>     denotes one of:    ! ;
        <symbol-character>   denotes one of:    # & * + - . / : <
                                                = > ? @ \ ^ ` ~
        <lower-case-letter>  denotes one of:    a...z
        <name-character>     denotes one of:    _ a...z A...Z 0....9
        <single-quote>       denotes:           '

   and `string_character' denotes any character except the double quote
and escape characters. Note that escape sequences in strings and atoms
follow the same rules.

   Examples:
     `a   a12x   '$a'   !   =>  '1 2''

   Version `4.2.0' of YAP removed the previous limit of 256 characters
on an atom. Size of an atom is now only limited by the space available
in the system.


File: yap.info,  Node: Variables,  Next: Punctuation Tokens,  Prev: Atoms,  Up: Tokens

Variables
---------

Variables are described by:
        <variable-starter><variable-character>+
   where
       <variable-starter>   denotes one of:    _ A...Z
       <variable-character> denotes one of:    _ a...z A...Z

   If a variable is referred only once in a term, it needs not to be
named and one can use the character `_' to represent the variable. These
variables are known as anonymous variables. Note that different
occurrences of `_' on the same term represent _different_ anonymous
variables.


File: yap.info,  Node: Punctuation Tokens,  Next: Layout,  Prev: Variables,  Up: Tokens

Punctuation Tokens
------------------

Punctuation tokens consist of one of the following characters:
                              ( ) , [ ] { } |

   These characters are used to group terms.


File: yap.info,  Node: Layout,  Prev: Punctuation Tokens,  Up: Tokens

Layout
------

Any characters with ASCII code less than or equal to 32 appearing before
a token are ignored.

   All the text appearing in a line after the character % is taken to
be a comment and ignored (including %).  Comments can also be inserted
by using the sequence `/*' to start the comment and `*/' to finish it.
In the presence of any sequence of comments or layout characters, the
YAP parser behaves as if it had found a single blank character. The end
of a file also counts as a blank character for this purpose.


File: yap.info,  Node: Loading Programs,  Next: Modules,  Prev: Syntax,  Up: Top

Loading Programs
****************

* Menu:


Loading Programs
* Compiling:: Program Loading and Updating
* Setting the Compiler:: Changing the compiler's parameters
* Saving:: Saving and Restoring Programs


File: yap.info,  Node: Compiling,  Next: Setting the Compiler,  Up: Loading Programs

Program loading and updating
============================

`consult(+F)'
     Adds the clauses written in file F or in the list of files F to
     the program.

     In YAP `consult/1' does not remove previous clauses for the
     procedures defined in F. Moreover, note that all code in YAP is
     compiled.

`reconsult(+F)'
     Updates the program replacing the previous definitions for the
     predicates defined in F.

`[+F]'
     The same as `consult(F)'.

`[-+F]'
     The same as `reconsult(F)'

     Example:

          ?- [file1, -file2, -file3, file4].

     will consult `file1' `file4' and reconsult `file2' and `file3'.

`compile(+F)'
     In YAP, the same as `reconsult/1'.

`ensure_loaded(+F) [ISO]'
     When the files specified by F are module files, `ensure_loaded/1'
     loads them if they have note been previously loaded, otherwise
     advertises the user about the existing name clashes and prompts
     about importing or not those predicates. Predicates which are not
     public remain invisible.

     When the files are not module files, `ensure_loaded/1' loads them
     if they have not been loaded before, does nothing otherwise.

     F must be a list containing the names of the files to load.

`include(+F) [ISO]'
     The `include' directive includes the text files or sequence of text
     files specified by F into the file being currently consulted.



File: yap.info,  Node: Setting the Compiler,  Next: Saving,  Prev: Compiling,  Up: Loading Programs

Changing the Compiler's Behavior
================================

This section presents a set of built-ins predicates designed to set the
environment for the compiler.

`source_mode(-O,+N)'
     The state of source mode can either be on or off. When the source
     mode is on, all clauses are kept both as compiled code and in a
     "hidden" database. O is unified with the previous state and the
     mode is set according to N.

`source'
     After executing this goal, YAP keeps information on the source of
     the predicates that will be consulted. This enables the use of
     `listing/0', `listing/1' and `clause/2' for those clauses.

     The same as `source_mode(_,on)' or as declaring all newly defined
     static procedures as `public'.

`no_source'
     The opposite to `source'.

     The same as `source_mode(_,off)'.

`compile_expressions'
     After a call to this predicate, arithmetical expressions will be
     compiled.  (see example below). This is the default behavior.

`do_not_compile_expressions'
     After a call to this predicate, arithmetical expressions will not
     be compiled.
          ?- source, do_not_compile_expressions.
          yes
          ?- [user].
          | p(X) :- X is 2 * (3 + 8).
          | :- end_of_file.
          ?- compile_expressions.
          yes
          ?- [user].
          | q(X) :- X is 2 * (3 + 8).
          | :- end_of_file.
          :- listing.
          
          p(A):-
                A is 2 * (3 + 8).
          
          q(A):-
                A is 22.

`hide(+ATOM)'
     Make atom ATOM invisible.

`unhide(+ATOM)'
     Make hidden atom ATOM visible.

`hide_predicate(+PRED)'
     Make predicate PRED invisible to `current_predicate/2', `listing',
     and friends.

`expand_exprs(-O,+N)'
     Puts YAP in state N (`on' or `off') and unify O with the previous
     state, where ON is equivalent to `compile_expressions' and `off'
     is equivalent to `do_not_compile_expressions'. This predicate was
     kept to maintain compatibility with C-Prolog.

`path(-D)'
     Unifies D with the current directory search-path of YAP.  Note
     that this search-path is only used by YAP to find the files for
     `consult/1', `reconsult/1' and `restore/1' and should not be taken
     for the system search path.

`add_to_path(+D)'
     Adds D to the end of YAP's directory search path.

`add_to_path(+D,+N)'
     Inserts D in the position, of the directory search path of YAP,
     specified by N.  N must be either of `first' or `last'.

`remove_from_path(+D)'
     Remove D from YAP's directory search path.

`style_check(+X)'
     Turns on style checking according to the attribute specified by X,
     which must be one of the following:
    `single_var'
          Checks single occurrences of named variables in a clause.

    `discontiguous'
          Checks non-contiguous clauses for the same predicate in a
          file.

    `multiple'
          Checks the presence of clauses for the same predicate in more
          than one file when the predicate has not been declared as
          `multifile'

    `all'
          Performs style checking for all the cases mentioned above.
     By default, style checking is disabled in YAP unless we are in
     `sicstus' or `iso' language mode.

     The `style_check/1' built-in is now deprecated. Please use the
     `set_prolog_flag/1' instead.

`no_style_check(+X)'
     Turns off style checking according to the attribute specified by
     X, which has the same meaning as in `style_check/1'.

     The `no_style_check/1' built-in is now deprecated. Please use the
     `set_prolog_flag/1' instead.

`multifile P [ISO]'
     Instructs the compiler about the declaration of a predicate P in
     more than one file. It must appear in the first of the loaded files
     where the predicate is declared, and before declaration of any of
     its clauses.

     Multifile declarations affect `reconsult/1' and `compile/1': when
     a multifile predicate is reconsulted, only the clauses from the
     same file are removed.

     Since Yap4.3.0 multifile procedures can be static or dynamic.

`discontiguous(+G) [ISO]'
     Declare that the arguments are discontiguous procedures, that is,
     clauses for discontigous procedures may be separated by clauses
     from other procedures.

`initialization(+G) [ISO]'
     The compiler will execute goals G after consulting the current
     file.

`library_directory(+D)'
     Succeeds when D is a current library directory name. Library
     directories are the places where files specified in the form
     `library(FILE)' are searched by the predicates `consult/1',
     `reconsult/1', `use_module/1' or `ensure_loaded/1'.

`file_search_path(+NAME,-DIRECTORY)'
     Allows writing file names as compound terms. The NAME and
     DIRECTORY must be atoms. The predicate may generate multiple
     solutions. The predicate is originally defined as follows:

          file_search_path(library,A) :-
             library_directory(A).
          file_search_path(system,A) :-
             prolog_flag(host_type,A).

     Thus, [library(A)] will search for a file using
     LIBRARY_DIRECTORY/1 to obtain the prefix.

`library_directory(+D)'
     Succeeds when D is a current library directory name. Library
     directories are the places where files specified in the form
     `library(FILE)' are searched by the predicates `consult/1',
     `reconsult/1', `use_module/1' or `ensure_loaded/1'.

`prolog_file_name(+NAME,-FULLPATH)'
     Unify FULLPATH with the absolute path YAP would use to consult
     file NAME.

`public P [ISO]'
     Instructs the compiler that the source of a predicate of a list of
     predicates P must be kept. This source is then accessible through
     the `clause/2' procedure and through the `listing' family of
     built-ins.

     Note that all dynamic procedures are public. The `source' directive
     defines all new or redefined predicates to be public.

     Since Yap4.3.0 multifile procedures can be static or dynamic.



File: yap.info,  Node: Saving,  Prev: Setting the Compiler,  Up: Loading Programs

Saving and Loading Prolog States
================================

`save(+F)'
     Saves an image of the current state of YAP in file F. From
     *Yap4.1.3* onwards, YAP saved states are executable files in the
     Unix ports.

`save(+F,-OUT)'
     Saves an image of the current state of YAP in file F. From
     *Yap4.1.3* onwards, YAP saved states are executable files in the
     Unix ports.

     Unify OUT with 1 when saving the file and OUT with 0 when
     restoring the saved state.

`save_program(+F)'
     Saves an image of the current state of the YAP database in file F.

`save_program(+F, :G)'
     Saves an image of the current state of the YAP database in file F,
     and guarantee that execution of the restored code will start by
     trying goal G.

`restore(+F)'
     Restores a previously saved state of YAP from file F.

     YAP always tries to find saved states from the current directory
     first. If it cannot it will use the environment variable
     YAPLIBDIR, if defined, or search the default library directory.


File: yap.info,  Node: Modules,  Next: Builtins,  Prev: Loading Programs,  Up: Top

The Module System
*****************

Module systems are quite important for the development of large
applications. YAP implements a module system compatible with the Quintus
Prolog module system.

   The YAP module system is predicate-based. This means a module
consists of a set of predicates (or procedures), such that some
predicates are public and the others are local to a module. Atoms and
terms in general are global to the system. Moreover, the module system
is flat, meaning that we do not support an hierarchy of modules.
Modules can automatically import other modules, though. For
compatibility with other module systems the YAP module system is
non-strict, meaning both that there is both a way to access predicates
private to a module and that is possible to declare predicates for a
module from some other module.

   YAP allows one to ignore the module system if one does not want to
use it. Last note that using the module system does not introduce any
significant overheads: only meta-calls that cross module boundaries are
slowed down by the presence of modules.

* Menu:


* Module Concepts:: The Key Ideas in Modules
* Defining Modules:: How To Define a New Module
* Using Modules:: How to Use a Module
* Meta-Predicates in Modules:: How to Handle New Meta-Predicates


File: yap.info,  Node: Module Concepts,  Next: Defining Modules,  Up: Modules

Module Concepts
===============

The YAP module system applies to predicates. All predicates belong to a
module. System predicates belong to the module `primitives', and by
default new predicates belong to the module `user'. Predicates from the
module `primitives' are automatically visible to every module.

   Every predicate must belong to a module. This module is called its
_source module_.

   By default, the source module for a clause occurring in a source file
with a module declaration is the declared module. For goals typed in a
source file without module declarations, their module is the module the
file is being loaded into. If no module declarations exist, this is the
current _type-in module_. The default type-in module is `user', but one
can set the current module by using the built-in `module/1'.

   Note that in this module system one can explicitly specify the source
mode for a clause by prefixing a clause with its module, say:
     user:(a :- b).

In fact, to specify the source module for a clause it is sufficient to
specify the source mode for the clause's head:
     user:a :- b.

The rules for goals are similar. If a goal appears in a text file with a
module declaration, the goal's source module is the declared module.
Otherwise, it is the module the file is being loaded into or the
type-in module.

   One can override this rule by prefixing a goal with the module it is
supposed to be executed into, say:
     nasa:launch(apollo,13).
   will execute the goal `launch(apollo,13)' as if the current source
module was `nasa'.

   Note that this rule breaks encapsulation and should be used with
care.


File: yap.info,  Node: Defining Modules,  Next: Using Modules,  Prev: Module Concepts,  Up: Modules

Defining a New Module
=====================

A new module is defined by a `module' declaration:

`module(+M,+L)'
     This predicate defines the file where it appears as a module file;
     it must be the first declaration in the file.  M must be an atom
     specifying the module name; L must be a list containing the
     module's public predicates specification, in the form
     `[predicate_name/arity,...]'.

     The public predicates of a module file can be made accessible by
     other files through the predicates `consult/1', `reconsult/1',
     `ensure_loaded/1' or `use_module/2'. The non-public predicates of
     a module file are not visible by other files; they can, however, be
     accessed if the module name is prefixed to the file name through
     the `:/2' operator.


   The built-in `module/1' sets the current source module:
`module(+M,+L, +OPTIONS)'
     Similar to `module/2', this predicate defines the file where it
     appears as a module file; it must be the first declaration in the
     file.  M must be an atom specifying the module name; L must be a
     list containing the module's public predicates specification, in
     the form `[predicate_name/arity,...]'.

     The last argument OPTIONS must be a list of options, which can be:

    `filename'
          the filename for a module to import into the current module.

    `library(file)'
          a library file to import into the current module.

    `hide(OPT)'
          if OPT is `false', keep source code for current module, if
          `true', disable.

`module(+M)'
     Defines M to be the current working or type-in module. All files
     which are not binded to a module are assumed to belong to the
     working module (also referred to as type-in module). To compile a
     non-module file into a module which is not the working one, prefix
     the file name with the module name, in the form `MODULE:FILE', when
     loading the file.



File: yap.info,  Node: Using Modules,  Next: Meta-Predicates in Modules,  Prev: Defining Modules,  Up: Modules

Using Modules
=============

By default, all procedures to consult a file will load the modules
defined therein. The two following declarations allow one to import a
module explicitly. They differ on whether one imports all predicate
declared in the module or not.

`use_module(+F)'
     Loads the files specified by F, importing all their public
     predicates. Predicate name clashes are resolved by asking the user
     about importing or not the predicate. A warning is displayed when
     F is not a module file.

`use_module(+F,+L)'
     Loads the files specified by F, importing the predicates specified
     in the list L. Predicate name clashes are resolved by asking the
     user about importing or not the predicate. A warning is displayed
     when F is not a module file.

`use_module(?M,?F,+L)'
     If module M has been defined, import the procedures in L to the
     current module. Otherwise, load the files specified by F,
     importing the predicates specified in the list L.


File: yap.info,  Node: Meta-Predicates in Modules,  Prev: Using Modules,  Up: Modules

Meta-Predicates in Modules
==========================

The module system must know whether predicates operate on goals or
clauses. Otherwise, such predicates would call a goal in the module they
were defined, instead of calling it in the module they are currently
executing. So, for instance:
     :- module(example,[a/1]).
     
     ...
     
     a(G) :- call(G)
     
     ...
   The expected behavior for this procedure is to execute goal G within
the current module, that is, within `example'.  On the other hand,
when executing `call/1' the system only knows where `call/1' was
defined, that is, it only knows of `primitives'. A similar problem
arises for `assert/1' and friends.

   The `meta_call/1' declaration informs the system that some arguments
of a procedure are goals, clauses or clauses heads, and that these
arguments must be expanded to receive the current source module:

`meta_predicate G1,....,GN'
     Each GI is a mode specification. For example, a declaration for
     `call/1' and `setof/3' would be of the form:

          :- meta_predicate call(:), setof(?,:,?).

     If the argument is `:' or an integer, the argument is a call and
     must be expanded. Otherwise, the argument should not be expanded.
     Note that the system already includes declarations for all
     built-ins.


   In the previous example, the only argument to `call/1' must be
expanded, resulting in the following code:

     :- module(example,[a/1]).
     
     ...
     
     a(G) :- call(example:G)
     
     ...


File: yap.info,  Node: Builtins,  Next: Library,  Prev: Modules,  Up: Top

Built-In Predicates
*******************

* Menu:


Builtins, Debugging, Syntax, Top
* Control:: Controlling the Execution of Prolog Programs
* Undefined Procedures:: Handling calls to Undefined Procedures
* Testing Terms:: Predicates on Terms
* Comparing Terms:: Comparison of Terms
* Arithmetic:: Arithmetic in Yap
* I/O:: Input/Output with Yap
* Database:: Modifying Prolog's Database
* Sets:: Finding All Possible Solutions
* Grammars:: Grammar Rules
* Preds:: Predicate Information
* OS:: Access to Operating System Functionality
* Term Modification:: Updating Prolog Terms
* Profiling:: Profiling Prolog Execution
* Call Counting:: Limiting the Maximum Number of Reductions
* Arrays:: Supporting Global and Local Arrays
* Preds:: Information on Predicates
* Misc:: Miscellaneous Predicates


File: yap.info,  Node: Control,  Next: Undefined Procedures,  Up: Top

Control Predicates
==================

This chapter describes the predicates for controlling the execution of
Prolog programs.

   In the description of the arguments of functors the following
notation will be used:

   * a preceding plus sign will denote an argument as an "input
     argument" - it cannot be a free variable at the time of the call;

   *  a preceding minus sign will denote an "output argument";

   * an argument with no preceding symbol can be used in both ways.

`+P, +Q [ISO]'
     Conjunction of goals (and).

     Example:
           p(X) :- q(X), r(X).

     should be read as "p(X) if q(X) and r(X)".

`+P ; +Q [ISO]'
     Disjunction of goals (or).

     Example:
           p(X) :- q(X); r(X).

     should be read as "p(X) if q(X) or r(X)".

`true [ISO]'
     Succeeds once.

`fail [ISO]'
     Fails always.

`false'
     The same as fail

`! [ISO]'
     Read as "cut". Cuts any choices taken in the current procedure.
     When first found "cut" succeeds as a goal, but if backtracking
     should later return to it, the parent goal (the one which matches
     the head of the clause containing the "cut", causing the clause
     activation) will fail. This is an extra-logical predicate and
     cannot be explained in terms of the declarative semantics of
     Prolog.

     example:

           member(X,[X|_]).
           member(X,[_|L]) :- member(X,L).

     With the above definition

           ?- member(X,[1,2,3]).

     will return each element of the list by backtracking. With the
     following definition:

           member(X,[X|_]) :- !.
           member(X,[_|L]) :- member(X,L).

     the same query would return only the first element of the list,
     since backtracking could not "pass through" the cut.

`\+ +P [ISO]'
     Goal P is not provable. The execution of this predicate fails if
     and only if the goal P finitely succeeds. It is not a true logical
     negation, which is impossible in standard Prolog, but
     "negation-by-failure".

     This predicate might be defined as:
           \+(P) :- P, !, fail.
           \+(_).

     if P did not include "cuts".

`not +P'
     Goal P is not provable. The same as `'\+ P''.

     This predicate is kept for compatibility with C-Prolog and previous
     versions of YAP. Uses of `not/1' should be replace by `(\+)/1', as
     YAP does not implement true negation.

`+P -> +Q [ISO]'
     Read as "if-then-else" or "commit". This operator is similar to the
     conditional operator of imperative languages and can be used alone
     or with an else part as follows:

    `+P -> +Q'
          "if P then Q".

    `+P -> +Q; +R'
          "if P then Q else R".

     These two predicates could be defined respectively in Prolog as:
           (P -> Q) :- P, !, Q.

     and
           (P -> Q; R) :- P, !, Q.
           (P -> Q; R) :- R.

     if there were no "cuts" in P, Q and R.

     Note that the commit operator works by "cutting" any alternative
     solutions of P.

     Note also that you can use chains of commit operators like:
              P -> Q ; R -> S ; T.

     Note that `(->)/2' does not affect the scope of cuts in its
     arguments.

`repeat [ISO]'
     Succeeds repeatedly.

     In the next example, `repeat' is used as an efficient way to
     implement a loop. The next example reads all terms in a file:

           a :- repeat, read(X), write(X), nl, X=end_of_file, !.

     the loop is effectively terminated by the cut-goal, when the
     test-goal `X=end' succeeds. While the test fails, the goals
     `read(X)', `write(X)', and `nl' are executed repeatedly, because
     backtracking is caught by the `repeat' goal.

     The built-in `repeat/1' could be defined in Prolog by:
           repeat.
           repeat :- repeat.

`call(+P) [IS0]'
     If P is instantiated to an atom or a compound term, the goal
     `call(P)' is executed as if the value of `P' was found instead of
     the call to `call/1', except that any "cut" occurring in P only
     cuts alternatives in the execution of P.

`incore(+P)'
     The same as `call/1'.

`call_with_args(+NAME,...,?AI,...)'
     Meta-call where NAME is the name of the procedure to be called and
     the AI are the arguments. The number of arguments varies between 0
     and 10.

     If NAME is a complex term, then `call_with_args/n' behaves as
     `call/n':

          call(p(X1,...,Xm), Y1,...,Yn) :- p(X1,...,Xm,Y1,...,Yn).

`+P'
     The same as `call(P)'. This feature has been kept to provide
     compatibility with C-Prolog. When compiling a goal, YAP generates
     a `call(X)' whenever a variable X is found as a goal.

           a(X) :- X.

     is converted to:
           a(X) :- call(X).

`if(?G,?H,?I) [IS0]'
     Call goal H once per each solution of goal H. If goal H has no
     solutions, call goal I.

     The builtin `if/3' is similar to `->/3', with the difference that
     it will backtrack over the test goal. Consider the following small
     data-base:

          a(1).        b(a).          c(x).
          a(2).        b(b).          c(y).

     Execution of an `if/3' query will proceed as follows:

             ?- if(a(X),b(Y),c(Z)).
          
          X = 1,
          Y = a ? ;
          
          X = 1,
          Y = b ? ;
          
          X = 2,
          Y = a ? ;
          
          X = 2,
          Y = b ? ;
          
          no

     The system will backtrack over the two solutions for `a/1' and the
     two solutions for `b/1', generating four solutions.

     Cuts are allowed inside the first goal G, but they will only prune
     over G.

     If you want G to be deterministic you should use if-then-else, as
     it is both more efficient and more portable.

`once(:G) [IS0]'
     Execute the goal G only once. The predicate is defined by:

           once(G) :- call(G), !.

     Note that cuts inside `once/1' can only cut the other goals inside
     `once/1'.

`abort'
     Abandons the execution of the current goal and returns to top
     level. All break levels (see `break/0' below) are terminated. It
     is mainly used during debugging or after a serious execution
     error, to return to the top-level.

`break'
     Suspends the execution of the current goal and creates a new
     execution level similar to the top level, displaying the following
     message:

           [ Break (level <number>) ]

     telling the depth of the break level just entered. To return to the
     previous level just type the end-of-file character or call the
     end_of_file predicate.  This predicate is especially useful during
     debugging.

`halt [ISO]'
     Halts Prolog, and exits to the calling application. In YAP,
     `halt/0' returns the exit code `0'.

`halt(+ I) [ISO]'
     Halts Prolog, and exits to the calling application returning the
     code given by the integer I.

`catch(+GOAL,+EXCEPTION,+ACTION) [IS0]'
     The goal `catch(GOAL,EXCEPTION,ACTION)' tries to execute goal
     GOAL. If during its execution, GOAL throws an exception E' and
     this exception unifies with EXCEPTION, the exception is considered
     to be caught and ACTION is executed. If the exception E' does not
     unify with EXCEPTION, control again throws the exception.

     The top-level of YAP maintains a default exception handler that is
     responsible to capture uncaught exceptions.

`throw(+BALL) [ISO]'
     The goal `throw(BALL)' throws an exception. Execution is stopped,
     and the exception is sent to the ancestor goals until reaching a
     matching `catch/3', or until reaching top-level.

`garbage_collect'
     The goal `garbage_collect' forces a garbage collection.

`garbage_collect_atoms'
     The goal `garbage_collect' forces a garbage collection of the atoms
     in the data-base. Currently, only atoms are recovered.

`gc'
     The goal `gc' enables garbage collection. The same as
     `yap_flag(gc,on)'.

`nogc'
     The goal `nogc' disables garbage collection. The same as
     `yap_flag(gc,off)'.

`grow_heap(+SIZE)'
     Increase heap size SIZE kilobytes.

`grow_stack(+SIZE)'
     Increase stack size SIZE kilobytes.



File: yap.info,  Node: Undefined Procedures,  Next: Testing Terms,  Prev: Control,  Up: Top

Handling Undefined Procedures
=============================

A predicate in a module is said to be undefined if there are no clauses
defining the predicate, and if the predicate has not been declared to be
dynamic. What YAP does when trying to execute undefined predicates can
be specified through three different ways:
   * By setting an YAP flag, through the `yap_flag/2' or
     `set_prolog_flag/2' built-ins. This solution generalizes the ISO
     standard.

   * By using the `unknown/2' built-in (this solution is compatible
     with previous releases of YAP).

   * By defining clauses for the hook predicate
     `user:unknown_predicate_handler/3'. This solution is compatible
     with SICStus Prolog.

   In more detail:
`unknown(-O,+N)'
     Specifies an handler to be called is a program tries to call an
     undefined static procedure P.

     The arity of N may be zero or one. If the arity is `0', the new
     action must be one of `fail', `warning', or `error'. If the arity
     is `1', P is an user-defined handler and at run-time, the argument
     to the handler P will be unified with the undefined goal. Note
     that N must be defined prior to calling `unknown/2', and that the
     single argument to N must be unbound.

     In YAP, the default action is to `fail' (note that in the ISO
     Prolog standard the default action is `error').

     After defining `undefined/1' by:
          undefined(A) :- format('Undefined predicate: ~w~n'), fail.

     and executing the goal:
          unknown(U,undefined(X)).

     a call to a predicate for which no clauses were defined will
     result in the output of a message of the form:
          Undefined predicate: user:xyz(A1,A2)

     followed by the failure of that call.

`yap_flag(unknown,+SPEC)'
     Alternatively, one can use `yap_flag/2', `current_prolog_flag/2',
     or `set_prolog_flag/2', to set this functionality. In this case,
     the first argument for the built-ins should be `unknown', and the
     second argument should be either `error', `warning', `fail', or a
     goal.

`user:unknown_predicate_handler(+G,+M,?NG)'
     The user may also define clauses for
     `user:unknown_predicate_handler/3' hook predicate. This
     user-defined procedure is called before any system processing for
     the undefined procedure, with the first argument G set to the
     current goal, and the second M set to the current module.

     If `user:unknown_predicate_handler/3' succeeds, the system will
     execute NG. If  `user:unknown_predicate_handler/3' fails, the
     system will execute default action as specified by `unknown/2'.


File: yap.info,  Node: Testing Terms,  Next: Comparing Terms,  Prev: Undefined Procedures,  Up: Top

Predicates on terms
===================

`var(T) [ISO]'
     Succeeds if T is currently a free variable, otherwise fails.

`atom(T) [ISO]'
     Succeeds if and only if T is currently instantiated to an  atom.

`atomic(T) [ISO]'
     Checks whether T is an atomic symbol (atom or number).

`compound(T) [ISO]'
     Checks whether T is a compound term.

`db_reference(T)'
     Checks whether T is a database reference.

`float(T) [ISO]'
     Checks whether T is a floating point number.

`integer(T) [ISO]'
     Succeeds if and only if T is currently instantiated to an  integer.

`nonvar(T) [ISO]'
     The opposite of `var(T)'.

`number(T) [ISO]'
     Checks whether `T' is an integer or a float.

`primitive(T)'
     Checks whether T is an atomic term or a database reference.

`simple(T)'
     Checks whether T is unbound, an atom, or a number.

`callable(T)'
     Checks whether T is a callable term, that is, an atom or a
     compound term.

`name(A,L)'
     The predicate holds when at least one of the arguments is ground
     (otherwise, an error message will be displayed). The argument A
     will be unified with an atomic symbol and L with the list of the
     ASCII codes for the characters of the external representation of A.

           name(yap,L).

     will return:
           L = [121,97,112].

     and
           name(3,L).

     will return:
           L = [51].

`atom_chars(?A,?L) [ISO]'
     The predicate holds when at least one of the arguments is ground
     (otherwise, an error message will be displayed). The argument A
     must be unifiable with an atom, and the argument L with the list
     of the ASCII codes for the characters of the external
     representation of A.

     The ISO-Prolog standard dictates that `atom_chars/2' should unify
     the second argument with a list of one-char atoms, and not the
     character codes. For compatibility with previous versions of YAP,
     and with other Prolog implementations, YAP unifies the second
     argument with the character codes, as in `atom_codes/2'. Use the
     `set_prolog_flag(to_chars_mode,iso)' to obtain ISO standard
     compatibility.

`atom_codes(?A,?L) [ISO]'
     The predicate holds when at least one of the arguments is ground
     (otherwise, an error message will be displayed). The argument A
     will be unified with an atom and L with the list of the ASCII
     codes for the characters of the external representation of A.

`atom_concat(+AS,?A)'
     The predicate holds when the first argument is a list of atoms,
     and the second unifies with the atom obtained by concatenating all
     the atoms in the first list.

`atom_concat(+A1,+A2,?A)'
     The predicate holds when the first argument and second argument are
     atoms, and the third unifies with the atom obtained by
     concatenating the first two arguments.

`atom_length(+A,?I) [ISO]'
     The predicate holds when the first argument is an atom, and the
     second unifies with the number of characters forming that atom.

`atom_concat(?A1,?A2,?A12) [ISO]'
     The predicate holds when the third argument unifies with an atom,
     and the first and second unify with atoms such that their
     representations concatenated are the representation for A12.

     If A1 and A2 are unbound, the built-in will find all the atoms
     that concatenated give A12.

`number_chars(?I,?L)'
     The predicate holds when at least one of the arguments is ground
     (otherwise, an error message will be displayed). The argument I
     must be unifiable with a number, and the argument L with the list
     of the ASCII codes for the characters of the external
     representation of I.

     The ISO-Prolog standard dictates that `number_chars/2' should unify
     the second argument with a list of one-char atoms, and not the
     character codes. For compatibility with previous versions of YAP,
     and with other Prolog implementations, YAP unifies the second
     argument with the character codes, as in `number_codes/2'. Use the
     `set_prolog_flag(to_chars_mode,iso)' to obtain ISO standard
     compatibility.

`number_codes(?A,?L) [ISO]'
     The predicate holds when at least one of the arguments is ground
     (otherwise, an error message will be displayed). The argument A
     will be unified with a number and L with the list of the ASCII
     codes for the characters of the external representation of A.

`number_atom(?I,?L)'
     The predicate holds when at least one of the arguments is ground
     (otherwise, an error message will be displayed). The argument I
     must be unifiable with a number, and the argument L must be
     unifiable with an atom representing the number.

`char_code(?A,?I) [ISO]'
     The built-in succeeds with A bound to character represented as an
     atom, and I bound to the character code represented as an integer.
     At least, one of either A or I must be bound before the call.

`sub_atom(+A,?BEF, ?SIZE, ?AFTER, ?AT_OUT) [ISO]'
     True when A and AT_OUT are atoms such that the name of AT_OUT has
     size SIZE and is a substring of the name of A, such that BEF is
     the number of characters before and AFTER the number of characters
     afterwards.

     Note that A must always be known, but AT_OUT can be unbound when
     calling this built-in. If all the arguments for `sub_atom/5' but A
     are unbound, the built-in will backtrack through all possible
     substrings of A.

`numbervars(T,+N1,-NN)'
     Instantiates each variable in term T to a term of the form:
     `'$VAR'(I)', with I increasing from N1 to NN.

`ground(T)'
     Succeeds if there are no free variables in the term T.

`arg(+N,+T,A) [ISO]'
     Succeeds if the argument N of the term T unifies with A. The
     arguments are numbered from 1 to the arity of the term.

     The current version will generate an error if T or N are unbound,
     if T is not a compound term, of if N is not a positive integer.
     Note that previous versions of YAP would fail silently under these
     errors.

`functor(T,F,N)'
     The top functor of term T is named F and has  arity N.

     When T is not instantiated, F and N must be. If N is 0, F must be
     an atomic symbol, which will be unified with T. If N is not 0,
     then F must be an atom and T becomes instantiated to the most
     general term having functor F and arity N. If T is instantiated to
     a term then F and N are respectively unified with its top functor
     name and arity.

     In the current version of YAP the arity N must be an integer.
     Previous versions allowed evaluable expressions, as long as the
     expression would evaluate to an integer. This feature is not
     available in the ISO Prolog standard.

`T =.. L [ISO]'
     The list L is built with the functor and arguments of the term T.
     If T is instantiated to a variable, then L must be instantiated
     either to a list whose head is an atom, or to a list consisting of
     just a number.

`X = Y [ISO]'
     Tries to unify terms X and Y.

`X \= Y [ISO]'
     Succeeds if terms X and Y are not unifiable.

`unify_with_occurs_check(?T1,?T2) [ISO]'
     Obtain the most general unifier of terms T1 and T2, if there is
     one.

     This predicate implements the full unification algorithm. An
     example:n
          unify_with_occurs_check(a(X,b,Z),a(X,A,f(B)).

     will succeed with the bindings `A = b' and `Z = f(B)'. On the
     other hand:
          unify_with_occurs_check(a(X,b,Z),a(X,A,f(Z)).

     would fail, because `Z' is not unifiable with `f(Z)'. Note that
     `(=)/2' would succeed for the previous examples, giving the
     following bindings `A = b' and `Z = f(Z)'.

`copy_term(?TI,-TF) [ISO]'
     Term TF is a variant of the original term TI, such that for each
     variable V in the term TI there is a new variable V' in term TF.



File: yap.info,  Node: Comparing Terms,  Next: Arithmetic,  Prev: Testing Terms,  Up: Top

Comparing Terms
===============

The following predicates are used to compare and order terms, using the
standard ordering:

   * variables come before numbers, numbers come before atoms which in
     turn come before compound terms, ie: variables @< numbers @< atoms
     @< compound terms.

   * variables are roughly ordered by "age" (the "oldest" variable is
     put first);

   * floating point numbers are sorted in increasing order;

   * Integers are sorted in increasing order;

   * atoms are sorted in lexicographic order;

   * compound terms are ordered first by name, then by arity of the main
     functor, and finally by their arguments in left-to-right order.

`compare(C,X,Y)'
     As a result of comparing X and Y, C may take one of the following
     values:

        * `=' if X and Y are identical;

        * `<' if X precedes Y in the defined order;

        * `>' if Y precedes X in the defined order;

`X == Y [ISO]'
     Succeeds if terms X and Y are strictly identical. The difference
     between this predicate and `=/2' is that, if one of the arguments
     is a free variable, it only succeeds when they have already been
     unified.

          ?- X == Y.

     fails, but,
          ?- X = Y, X == Y.

     succeeds.
          ?- X == 2.

     fails, but,
          ?- X = 2, X == 2.

     succeeds.

`X \== Y [ISO]'
     Terms X and Y are not strictly identical.

`X @< Y [ISO]'
     Term X precedes term Y in the standard order.

`X @=< Y [ISO]'
     Term X does not follow term Y in the standard order.

`X @> Y [ISO]'
     Term X follows term Y in the standard order.

`X @>= Y [ISO]'
     Term X does not precede term Y in the standard order.

`sort(+L,-S)'
     Unifies S with the list obtained by sorting L and  merging
     identical (in the sense of `==') elements.

`keysort(+L,S)'
     Assuming L is a list of the form `KEY-VALUE', `keysort(+L,S)'
     unifies S with the list obtained from L, by sorting its elements
     according to the value of KEY.
          ?- keysort([3-a,1-b,2-c,1-a,1-b],S).

     would return:
          S = [1-b,1-a,1-b,2-c,3-a]

`length(?L,?S)'
     Unify the well-defined list L with its length. The procedure can
     be used to find the length of a pre-defined list, or to build a
     list of length S.



File: yap.info,  Node: Arithmetic,  Next: I/O,  Prev: Comparing Terms,  Up: Top

Arithmetic
==========

Arithmetic expressions in YAP may use the following operators or
evaluable predicates:

`+X'
     The value of X itself.

`-X [ISO]'
     Symmetric value.

`X+Y [ISO]'
     Sum.

`X-Y [ISO]'
     Difference.

`X*Y [ISO]'
     Product.

`X/Y [ISO]'
     Quotient.

`X//Y [ISO]'
     Integer quotient.

`X mod Y [ISO]'
     Integer remainder.

`X rem Y'
     Integer remainder, the same as `mod'.

`exp(X) [ISO]'
     Natural exponential.

`log(X) [ISO]'
     Natural logarithm.

`log10(X)'
     Decimal logarithm.

`sqrt(X) [ISO]'
     Square root.

`sin(X) [ISO]'
     Sine.

`cos(X) [ISO]'
     Cosine.

`tan(X)'
     Tangent.

`asin(X)'
     Arc sine.

`acos(X)'
     Arc cosine.

`atan(X) [ISO]'
     Arc tangent.

`atan2(X)'
     Four-quadrant arc tangent.

`sinh(X)'
     Hyperbolic sine.

`cosh(X)'
     Hyperbolic cosine.

`tanh(X)'
     Hyperbolic tangent.

`asinh(X)'
     Hyperbolic arc sine.

`acosh(X)'
     Hyperbolic arc cosine.

`atanh(X)'
     Hyperbolic arc tangent.

`integer(X) [ISO]'
     If X evaluates to a float, the integer between the value of X and
     0 closest to the value of X, else if X evaluates to an integer,
     the value of X.

`float(X) [ISO]'
     If X evaluates to an integer, the corresponding float, else the
     float itself.

`float_fractional_part(X) [ISO]'
     The fractional part of the floating point number X, or `0.0' if X
     is an integer. In the `iso' language mode, X must be an integer.

`float_integer_part(X) [ISO]'
     The float giving the integer part of the floating point number X,
     or X if X is an integer. In the `iso' language mode, X must be an
     integer.

`abs(X) [ISO]'
     The absolute value of X.

`ceiling(X) [ISO]'
     The float that is the smallest integral value not smaller than X.

     In `iso' language mode the argument must be a floating
     point-number and the result is an integer.

`floor(X) [ISO]'
     The float that is the greatest integral value not greater than X.

     In `iso' language mode the argument must be a floating
     point-number and the result is an integer.

`round(X) [ISO]'
     The nearest integral value to X. If X is equidistant to two
     integers, it will be rounded to the closest even integral value.

     In `iso' language mode the argument must be a floating
     point-number, the result is an integer and it the float is
     equidistant it is rounded up, that is, to the least integer
     greater than X.

`sign(X) [ISO]'
     Return 1 if the X evaluates to a positive integer, 0 it if
     evaluates to 0, and -1 if it evaluates to a negative integer. If X
     evaluates to a floating-point number return 1.0 for a positive X,
     0.0 for 0.0, and -1.0 otherwise.

`truncate(X)'
     The float that is the integral value between X and 0 closest to X.

`max(X,Y)'
     The greater value of X and Y.

`min(X,Y)'
     The lesser value of X and Y.

`X ^ Y'
     X raised to the power of Y, (from the C-Prolog syntax).

`exp(X,Y)'
     X raised to the power of Y, (from the Quintus Prolog syntax).

`X ** Y [ISO]'
     X raised to the power of Y  (from ISO).

`X /\ Y [ISO]'
     Integer bitwise conjunction.

`X \/ Y [ISO]'
     Integer bitwise disjunction.

`X # Y [ISO]'
     Integer bitwise exclusive disjunction.

`X << Y'
     Integer bitwise left logical shift of X by Y places.

`X >> Y [ISO]'
     Integer bitwise right logical shift of X by Y places.

`\ X [ISO]'
     Integer bitwise negation.

`gcd(X,Y)'
     The greatest common divisor of the two integers X and Y.

`msb(X)'
     The most significant bit of the integer X.

`[X]'
     Evaluates to X for expression X. Useful because character strings
     in Prolog are lists of character codes.

          X is Y*10+C-"0"

     is the same as
          X is Y*10+C-[48].

     which would be evaluated as:
          X is Y*10+C-48.


   Besides numbers and the arithmetic operators described above, certain
atoms have a special meaning when present in arithmetic expressions:

`pi'
     The value of _pi_, the ratio of a circle's circumrefence to its
     diameter.

`e'
     The base of the natural logarithms.

`inf'
     Infinity according to the IEEE Floating-Point standard. Note that
     evaluating this term will generate a domain error in the `iso'
     language mode.

`nan'
     Not-a-number according to the IEEE Floating-Point standard. Note
     that evaluating this term will generate a domain error in the `iso'
     language mode.

`cputime'
     CPU time in seconds, since YAP was invoked.

`heapused'
     Heap space used, in bytes.

`local'
     Local stack in use, in bytes.

`global'
     Global stack in use, in bytes.

`random'
     A "random" floating point number between 0 and 1.


   The primitive YAP predicates involving arithmetic expressions are:

`X is +Y [2]'
     This predicate succeeds iff the result of evaluating the expression
     Y unifies with X. This is the predicate normally used to perform
     evaluation of arithmetic expressions:

          X is 2+3*4

     succeeds with `X = 14'.

`+X < +Y [ISO]'
     The value of the expression X is less than the value of expression
     Y.

`+X =< +Y [ISO]'
     The value of the expression X is less than or equal to the value
     of expression Y.

`+X > +Y [ISO]'
     The value of the expression X is greater than the value of
     expression Y.

`+X >= +Y [ISO]'
     The value of the expression X is greater than or equal to the
     value of expression Y.

`+X =:= +Y [ISO]'
     The value of the expression X is equal to the value of expression
     Y.

`+X =\= +Y [ISO]'
     The value of the expression X is different from the value of
     expression Y.

`srandom(+X)'
     Use the argument X as a new seed for YAP's random number
     generator. The argument should be an integer, but floats are
     acceptable.

*Notes:*

   * In contrast to previous versions of Yap, Yap4 _does not_ convert
     automatically between integers and floats.

   * arguments to trigonometric functions are expressed in radians.

   * if a (non-instantiated) variable occurs in an arithmetic expression
     YAP will generate an exception. If no error handler is available,
     execution will be thrown back to the top-level.


File: yap.info,  Node: I/O,  Next: Database,  Prev: Arithmetic,  Up: Top

I/O Predicates
==============

Some of the I/O predicates described below will in certain conditions
provide error messages and abort only if the file_errors flag is set.
If this flag is cleared the same predicates will just fail. Details on
setting and clearing this flag are given under 7.7.

* Menu:


Subnodes of Input/Output
* Streams and Files:: Handling Streams and Files
* C-Prolog File Handling:: C-Prolog Compatible File Handling
* I/O of Terms:: Input/Output of terms
* I/O of Characters:: Input/Output of Characters
* I/O for Streams:: Input/Output using Streams
* C-Prolog to Terminal:: C-Prolog compatible Character I/O to terminal
* I/O Control:: Controlling your Input/Output
* Sockets:: Using Sockets from Yap


File: yap.info,  Node: Streams and Files,  Next: C-Prolog File Handling,  Up: I/O

Handling Streams and Files
--------------------------

`open(+F,+M,-S) [ISO]'
     Opens the file with name F in mode M ('read', 'write' or
     'append'), returning S unified with the stream name.

     At most, there are 17 streams  opened at the same time. Each
     stream is either an input or an output stream but not both. There
     are always 3 open streams:  `user_input' for reading,
     `user_output' for writing and `user_error' for writing. If there
     is no  ambiguity, the atoms `user_input' and `user_output' may be
     referred to as  `user'.

     The `file_errors' flag controls whether errors are reported when in
     mode 'read' or 'append' the file F does not exist or is not
     readable, and whether in mode 'write' or 'append' the file is not
     writable.

`open(+F,+M,-S,+OPTS) [ISO]'
     Opens the file with name F in mode M ('read',  'write' or
     'append'), returning S unified with the stream name, and following
     these options:

    `type(+T)'
          Specify whether the stream is a `text' stream (default), or a
          `binary' stream.

    `reposition(+BOOL)'
          Specify whether it is possible to reposition the stream
          (`true'), or not (`false'). By default, YAP enables
          repositioning for all files, except terminal files and
          sockets.

    `eof_action(+ACTION)'
          Specify the action to take if attempting to input characters
          from a stream where we have previously found an
          `end-of-file'. The possible actions are `error', that raises
          an error, `reset', that tries to reset the stream and is used
          for `tty' type files, and `eof_code', which generates a new
          `end-of-file' (default for non-tty files).

    `alias(+NAME)'
          Specify an alias to the stream. The alias Name must be an
          atom. The alias can be used instead of the stream descriptor
          for every operation concerning the stream.

          The operation will fail and give an error if the alias name
          is already in use. YAP allows several aliases for the same
          file, but only one is returned by `stream_property/2'

`close(+S) [ISO]'
     Closes the stream S. If S does not stand for a stream currently
     opened an error is reported. The streams `user_input',
     `user_output', and `user_error' can never be closed.

     By default, give a file name, `close/1' will also try to close a
     corresponding open stream. This feature is not available in ISO or
     SICStus languages mode and is deprecated.

`close(+S,+O) [ISO]'
     Closes the stream S, following options O.

     The only valid options are `force(true)' and `force(false)'.  YAP
     currently ignores these options.

`absolute_file_name(+NAME,-FULLPATH)'
     Give the path a full path FULLPATH Yap would use to consult a file
     named NAME.  Unify FULLPATH with `user' if the file name is `user'.

`current_stream(F,M,S)'
     Defines the relation: The stream S is opened on the file F in mode
     M. It might be used to obtain all open streams (by backtracking)
     or to access the stream for a file F in mode M, or to find
     properties for a stream S.

`flush_output [ISO]'
     Send all data in the output buffer to current output stream.

`flush_output(+S) [ISO]'
     Send all data in the output buffer to stream S.

`set_input(+S)'
     Set stream S as the current input stream. Predicates like `read/1'
     and `get/1' will start using stream S.

`set_output(+S)'
     Set stream S as the current output stream. Predicates like
     `write/1' and `put/1' will start using stream S.

`stream_select(+STREAMS,+TIMEOUT,-READSTREAMS)'
     Given a list of open STREAMS openeded in read mode and a TIMEOUT
     return a list of streams who are now available for reading.

     If the TIMEOUT is instantiated to `off', `stream_select/3' will
     wait indefinitely for a stream to become open. Otherwise the
     timeout must be of the form `SECS:USECS' where `SECS' is an
     integer gives the number of seconds to wait for a timeout and
     `USECS' adds the number of micro-seconds.

     This built-in is only defined if the system call `select' is
     available in the system.

`current_input(-S) [ISO]'
     Unify S with the current input stream.

`current_output(-S) [ISO]'
     Unify S with the current output stream.

`at_end_of_stream [ISO]'
     Succeed if the current stream has stream position end-of-stream or
     past-end-of-stream.

`at_end_of_stream(+S) [ISO]'
     Succeed if the stream S has stream position end-of-stream or
     past-end-of-stream. Note that S must be a readable stream.

`set_stream_position(+S, +POS) [ISO]'
     Given a stream position POS for a stream S, set the current stream
     position for S to be POS.

`stream_property(?STREAM,?PROP) [ISO]'
     Obtain the properties for the open streams. If the first argument
     is unbound, the procedure will backtrack through all open streams.
     Otherwise, the first argument must be a stream term (you may use
     `current_stream' to obtain a current stream given a file name).

     The following properties are recognized:

    `file_name(P)'
          An atom giving the file name for the current stream. The file
          names are `user_input', `user_output', and `user_error' for
          the standard streams.

    `mode(P)'
          The mode used to open the file. It may be one of `append',
          `read', or `write'.

    `input'
          The stream is readable.

    `output'
          The stream is writable.

    `alias(A)'
          ISO-Prolog primitive for stream aliases. Yap returns one of
          the existing aliases for the stream.

    `position(P)'
          A term describing the position in the stream.

    `end_of_stream(E)'
          Whether the stream is `at' the end of stream, or it has found
          the end of stream and is `past', or whether it has `not' yet
          reached the end of stream.

    `eof_action(A)'
          The action to take when trying to read after reaching the end
          of stream. The action may be one of `error', generate an
          error, `eof_code', return character code `-1', or `reset' the
          stream.

    `reposition(B)'
          Whether the stream can be repositioned or not, that is,
          whether it is seekable.

    `type(T)'
          Whether the stream is a `text' stream or a `binary' stream.




File: yap.info,  Node: C-Prolog File Handling,  Next: I/O of Terms,  Prev: Streams and Files,  Up: I/O

Handling Streams and Files
--------------------------

`tell(+S)'
     If S is a currently opened stream for output, it becomes the
     current output stream. If S is an atom it is taken to be a
     filename.  If there is no output stream currently associated with
     it, then it is opened for output, and the new output stream
     created becomes the current output stream. If it is not possible
     to open the file, an error occurs.  If there is a single opened
     output stream currently associated with the file, then it becomes
     the current output stream; if there are more than one in that
     condition, one of them is chosen.

     Whenever S is a stream not currently opened for output, an error
     may be reported, depending on the state of the file_errors flag.
     The predicate just fails, if S is neither a stream nor an atom.

`telling(-S)'
     The current output stream is unified with S.

`told'
     Closes the current output stream, and the user's terminal becomes
     again the current output stream. It is important to remember to
     close streams after having finished using them, as the maximum
     number of simultaneously opened streams is 17.

`see(+S)'
     If S is a currently opened input stream then it is assumed to be
     the current input stream. If S is an atom it is taken as a
     filename. If there is no input stream currently associated with
     it, then it is opened for input, and the new input stream thus
     created becomes the current input stream. If it is not possible to
     open the file, an error occurs.  If there is a single opened input
     stream currently associated with the file, it becomes the current
     input stream; if there are more than one in that condition, then
     one of them is chosen.

     When S is a stream not currently opened for input, an error may be
     reported, depending on the state of the `file_errors' flag. If S
     is neither a stream nor an atom the predicates just fails.

`seeing(-S)'
     The current input stream is unified with S.

`seen'
     Closes the current input stream (see 6.7.).



File: yap.info,  Node: I/O of Terms,  Next: I/O of Characters,  Prev: C-Prolog File Handling,  Up: I/O

Handling Input/Output of Terms
------------------------------

`read(-T) [ISO]'
     Reads the next term from the current input stream, and unifies it
     with T. The term must be followed by a dot ('.') and any
     blank-character as previously defined. The syntax of the term must
     match the current declarations for operators (see op). If the
     end-of-stream is reached, T is unified with the atom
     `end_of_file'. Further reads from of the same stream may cause an
     error failure (see `open/3').

`read_term(-T,+OPTIONS) [ISO]'
     Reads term T from the current input stream with execution
     controlled by the following options:

    `singletons(-NAMES)'
          Unify NAMES with a list of the form NAME=VAR, where NAME is
          the name of a non-anonymous singleton variable in the
          original term, and `Var' is the variable's representation in
          YAP.

    `syntax_errors(+VAL)'
          Control action to be taken after syntax errors. See
          `yap_flag/2' for detailed information.

    `variable_names(-NAMES)'
          Unify NAMES with a list of the form NAME=VAR, where NAME is
          the name of a non-anonymous variable in the original term,
          and VAR is the variable's representation in YAP.

    `variables(-NAMES)'
          Unify NAMES with a list of the variables in term T.


`char_conversion(+IN,+OUT) [ISO]'
     While reading terms convert unquoted occurrences of the character
     IN to the character OUT. Both IN and OUT must be bound to single
     characters atoms.

     Character conversion only works if the flag `char_conversion' is
     on. This is default in the `iso' and `sicstus' language modes. As
     an example, character conversion can be used for instance to
     convert characters from the ISO-LATIN-1 character set to ASCII.

     If IN is the same character as OUT, `char_conversion/2' will
     remove this conversion from the table.

`current_char_conversion(?IN,?OUT) [ISO]'
     If IN is unbound give all current character translations.
     Otherwise, give the translation for IN, if one exists.

`write(T) [ISO]'
     The term T is written to the current output stream according to
     the operator declarations in force.

`display(+T)'
     Displays term T on the current output stream. All Prolog terms are
     written in standard parenthesized prefix notation.

`write_canonical(+T) [ISO]'
     Displays term T on the current output stream. Atoms are quoted
     when necessary, and operators are ignored, that is, the term is
     written in standard parenthesized prefix notation.

`write_term(+T, +OPTS) [ISO]'
     Displays term T on the current output stream, according to the
     following options:

    `quoted(+BOOL)'
          If `true', quote atoms if this would be necessary for the
          atom to be recognized as an atom by YAP's parser. The default
          value is `false'.

    `ignore_ops(+BOOL)'
          If `true', ignore operator declarations when writing the
          term. The default value is `false'.

    `numbervars(+BOOL)'
          If `true', output terms of the form `'$VAR'(N)', where N is
          an integer, as a sequence of capital letters. The default
          value is `false'.

    `portrayed(+BOOL)'
          If `true', use portray/1 to portray bound terms. The default
          value is `false'.

    `max_depth(+DEPTH)'
          If `Depth' is a positive integer, use Depth as the maximum
          depth to portray a term. The default is `0', that is,
          unlimited depth.


`writeq(T) [ISO]'
     Writes the term T, quoting names to make the result acceptable to
     the predicate 'read' whenever necessary.

`print(T)'
     Prints the term T to the current output stream using `write/1'
     unless T is bound and a call to the user-defined  predicate
     `portray/1' succeeds. To do pretty  printing of terms the user
     should define suitable clauses for `portray/1' and use `print/1'.

`format(+T,+L)'
     Print formatted output to the current output stream. The arguments
     in list L are output according to the string or atom T.

     A control sequence is introduced by a `w'. The following control
     sequences are available in YAP:

    `'~~''
          Print a single tilde.

    `'~a''
          The next argument must be an atom, that will be printed as if
          by `write'.

    `'~Nc''
          The next argument must be an integer, that will be printed as
          a character code. The number N is the number of times to
          print the character (default 1).

    `'~Ne''
    `'~NE''
    `'~Nf''
    `'~Ng''
    `'~NG''
          The next argument must be a floating point number. The float
          F, the number N and the control code `c' will be passed to
          `printf' as:

                   printf("%s.Nc", F)

          As an example:

               ?- format("~8e, ~8E, ~8f, ~8g, ~8G~w",
                         [3.14,3.14,3.14,3.14,3.14,3.14]).
               3.140000e+00, 3.140000E+00, 3.140000, 3.14, 3.143.14

    `'~Nd''
          The next argument must be an integer, and N is the number of
          digits after the decimal point. If N is `0' no decimal points
          will be printed. The default is N = 0.

               ?- format("~2d, ~d",[15000, 15000]).
               150.00, 15000

    `'~ND''
          Identical to `'~Nd'', except that commas are used to separate
          groups of three digits.

               ?- format("~2D, ~D",[150000, 150000]).
               1,500.00, 150,000

    `'~i''
          Ignore the next argument in the list of arguments:

               ?- format('The ~i met the boregrove',[mimsy]).
               The  met the boregrove

    `'~k''
          Print the next argument with `write_canonical':

               ?- format("Good night ~k",a+[1,2]).
               Good night +(a,[1,2])

    `'~Nn''
          Print N newlines (where N defaults to 1).

    `'~NN''
          Print N newlines if at the beginning of the line (where N
          defaults to 1).

    `'~Nr''
          The next argument must be an integer, and N is interpreted as
          a radix, such that `2 <= N <= 36' (the default is 8).

               ?- format("~2r, 0x~16r, ~r",
                         [150000, 150000, 150000]).
               100100100111110000, 0x249f0, 444760

          Note that the letters `a-z' denote digits larger than 9.

    `'~NR''
          Similar to '~NR'. The next argument must be an integer, and N
          is interpreted as a radix, such that `2 <= N <= 36' (the
          default is 8).

               ?- format("~2r, 0x~16r, ~r",
                         [150000, 150000, 150000]).
               100100100111110000, 0x249F0, 444760

          The only difference is that letters `A-Z' denote digits
          larger than 9.

    `'~p''
          Print the next argument with `print/1':

               ?- format("Good night ~p",a+[1,2]).
               Good night a+[1,2]

    `'~q''
          Print the next argument with `writeq/1':

               ?- format("Good night ~q",'Hello'+[1,2]).
               Good night 'Hello'+[1,2]

    `'~Ns''
          The next argument must be a list of character codes. The
          system then outputs their representation as a string, where N
          is the maximum number of characters for the string (N
          defaults to the length of the string).

               ?- format("The ~s are ~4s",["woods","lovely"]).
               The woods are love

    `'~w''
          Print the next argument with `writeq/1':

               ?- format("Good night ~w",'Hello'+[1,2]).
               Good night Hello+[1,2]

     The number of arguments, `N', may be given as an integer, or it
     may be given as an extra argument. The next example shows a small
     procedure to write a variable number of `a' characters:

          write_many_as(N) :-
                  format("~*c",[N,0'a]).

     The `format/2' built-in also allows for formatted output.  One can
     specify column boundaries and fill the intermediate space by a
     padding character:

    `'~N|''
          Set a column boundary at position N, where N defaults to the
          current position.

    `'~N+''
          Set a column boundary at N characters past the current
          position, where N defaults to `8'.

    `'~Nt''
          Set padding for a column, where N is the fill code (default is
          <SPC>).


     The next example shows how to align columns and padding. We first
     show left-alignment:


          `
             ?- format("~n*Hello~16+*~n",[]).
          *Hello          *
          '

     Note that we reserve 16 characters for the column.

     The following example shows how to do right-alignment:

          `
             ?- format("*~tHello~16+*~n",[]).
          *          Hello*
          '

     The `~t' escape sequence forces filling before `Hello'.

     We next show how to do centering:

          `
             ?- format("*~tHello~t~16+*~n",[]).
          *     Hello     *
          '

     The two `~t' escape sequence force filling both before and after
     `Hello'. Space is then evenly divided between the right and the
     left sides.

`format(+S,+T,+L)'
     Print formatted output to stream S.



File: yap.info,  Node: I/O of Characters,  Next: I/O for Streams,  Prev: I/O of Terms,  Up: I/O

Handling Input/Output of Characters
-----------------------------------

`put(+N)'
     Outputs to the current output stream the character whose ASCII
     code is N. The character N must be a legal ASCII character code, an
     expression yielding such a code, or a list in which case only the
     first element is used.

`put_byte(+N) [ISO]'
     Outputs to the current output stream the character whose code is
     N. The current output stream must be a binary stream.

`put_char(+N) [ISO]'
     Outputs to the current output stream the character who is used to
     build the representation of atom `A'. The current output stream
     must be a text stream.

`put_code(+N) [ISO]'
     Outputs to the current output stream the character whose ASCII
     code is N. The current output stream must be a text stream. The
     character N must be a legal ASCII character code, an expression
     yielding such a code, or a list in which case only the first
     element is used.

`get(-C)'
     The next non-blank character from the current input stream is
     unified with C. Blank characters are the ones whose ASCII codes
     are not greater than 32. If there are no more non-blank characters
     in the stream, C is unified with -1. If `end_of_stream' has already
     been reached in the previous reading, this call will give an error
     message.

`get0(-C)'
     The next character from the current input stream is consumed, and
     then unified with C. There are no restrictions on the possible
     values of the ASCII code for the character, but the character will
     be internally converted by YAP.

`get_byte(-C) [ISO]'
     If C is unbound, or is a character code, and the current stream is
     a binary stream, read the next byte from the current stream and
     unify its code with C.

`get_char(-C) [ISO]'
     If C is unbound, or is an atom representation of a character, and
     the current stream is a text stream, read the next character from
     the current stream and unify its atom representation with C.

`get_code(-C) [ISO]'
     If C is unbound, or is the code for a character, and the current
     stream is a text stream, read the next character from the current
     stream and unify its code with C.

`peek_byte(-C) [ISO]'
     If C is unbound, or is a character code, and the current stream is
     a binary stream, read the next byte from the current stream and
     unify its code with C, while leaving the current stream position
     unaltered.

`peek_char(-C) [ISO]'
     If C is unbound, or is an atom representation of a character, and
     the current stream is a text stream, read the next character from
     the current stream and unify its atom representation with C, while
     leaving the current stream position unaltered.

`peek_code(-C) [ISO]'
     If C is unbound, or is the code for a character, and the current
     stream is a text stream, read the next character from the current
     stream and unify its code with C, while leaving the current stream
     position unaltered.

`skip(+N)'
     Skips input characters until the next occurrence of the character
     with ASCII code N. The argument to this predicate can take the
     same forms as those for `put' (see 6.11).

`tab(+N)'
     Outputs N spaces to the current output stream.

`nl [ISO]'
     Outputs a new line to the current output stream.



File: yap.info,  Node: I/O for Streams,  Next: C-Prolog to Terminal,  Prev: I/O of Characters,  Up: I/O

Input/Output Predicates applied to Streams
------------------------------------------

`read(+S,-T) [ISO]'
     Reads term T from the stream S instead of from the current input
     stream.

`read_term(+S,-T,+OPTIONS) [ISO]'
     Reads term T from stream S with execution controlled by the same
     options as `read_term/2'.

`write(+S,T) [ISO]'
     Writes term T to stream S instead of to the current output stream.

`write_canonical(+S,+T) [ISO]'
     Displays term T on the stream S. Atoms are quoted when necessary,
     and operators are ignored.

`write_term(+S, +T, +OPTS) [ISO]'
     Displays term T on the current output stream, according to the same
     options used by `write_term/3'.

`writeq(+S,T) [ISO]'
     As `writeq/1', but the output is sent to the stream S.

`display(+S,T)'
     Like `display/1', but using stream S to display the term.

`print(+S,T)'
     Prints term T to the stream S instead of to the current output
     stream.

`put(+S,+N)'
     As `put(N)', but to stream S.

`put_byte(+S,+N) [ISO]'
     As `put_byte(N)', but to binary stream S.

`put_char(+S,+A) [ISO]'
     As `put_char(A)', but to text stream S.

`put_code(+S,+N) [ISO]'
     As `put_code(N)', but to text stream S.

`get(+S,-C)'
     The same as `get(C)', but from stream S.

`get0(+S,-C)'
     The same as `get0(C)', but from stream S.

`get_byte(+S,-C) [ISO]'
     If C is unbound, or is a character code, and the stream S is a
     binary stream, read the next byte from that stream and unify its
     code with C.

`get_char(+S,-C) [ISO]'
     If C is unbound, or is an atom representation of a character, and
     the stream S is a text stream, read the next character from that
     stream and unify its representation as an atom with C.

`get_code(+S,-C) [ISO]'
     If C is unbound, or is a character code, and the stream S is a
     text stream, read the next character from that stream and unify its
     code with C.

`peek_byte(+S,-C) [ISO]'
     If C is unbound, or is a character code, and S is a binary stream,
     read the next byte from the current stream and unify its code with
     C, while leaving the current stream position unaltered.

`peek_char(+S,-C) [ISO]'
     If C is unbound, or is an atom representation of a character, and
     the stream S is a text stream, read the next character from that
     stream and unify its representation as an atom with C, while
     leaving the current stream position unaltered.

`peek_code(+S,-C) [ISO]'
     If C is unbound, or is an atom representation of a character, and
     the stream S is a text stream, read the next character from that
     stream and unify its representation as an atom with C, while
     leaving the current stream position unaltered.

`skip(+S,-C)'
     Like `skip/1', but using stream S instead of the current input
     stream.

`tab(+S,+N)'
     The same as `tab/1', but using stream S.

`nl(+S)'
     Outputs a new line to stream S.



File: yap.info,  Node: C-Prolog to Terminal,  Next: I/O Control,  Prev: I/O for Streams,  Up: I/O

Compatible C-Prolog predicates for Terminal I/O
-----------------------------------------------

`ttyput(+N)'
     As `put(N)' but always to `user_output'.

`ttyget(-C)'
     The same as `get(C)', but from stream `user_input'.

`ttyget0(-C)'
     The same as `get0(C)', but from stream `user_input'.

`ttyskip(-C)'
     Like `skip/1', but always using stream `user_input'.  stream.

`ttytab(+N)'
     The same as `tab/1', but using stream `user_output'.

`ttynl'
     Outputs a new line to stream `user_output'.



File: yap.info,  Node: I/O Control,  Next: Sockets,  Prev: C-Prolog to Terminal,  Up: I/O

Controlling Input/Output
------------------------

`exists(+F)'
     Checks if file F exists in the current directory.

`nofileerrors'
     Switches off the file_errors flag, so that the predicates `see/1',
     `tell/1', `open/3' and `close/1' just fail, instead of producing
     an error message and aborting whenever the specified file cannot be
     opened or closed.

`fileerrors'
     Switches on the file_errors flag so that in certain error
     conditions I/O predicates will produce an appropriated message and
     abort.

`write_depth(T,L)'
     Unifies T and L, respectively, with the values of  the maximum
     depth of a term and the maximum length of a list, that will be
     used by `write/1' or `write/2'. The default value for both
     arguments is 0, meaning unlimited depth and length.

          ?- write_depth(3,5).
          yes
          ?- write(a(b(c(d(e(f(g))))))).
          a(b(c(....)))
          yes
          ?- write([1,2,3,4,5,6,7,8]).
          [1,2,3,4,5,...]
          yes

`always_prompt_user'
     Force the system to prompt the user even if the `user_input' stream
     is not a terminal. This command is useful if you want to obtain
     interactive control from a pipe or a socket.



File: yap.info,  Node: Sockets,  Prev: I/O Control,  Up: I/O

Using Sockets From Yap
----------------------

YAP includes a SICStus Prolog compatible socket interface. This is a
low level interface that provides direct access to the major socket
system calls. These calls can be used both to open a new connection in
the network or connect to a networked server. Socket connections are
described as read/write streams, and standard I/O builtins can be used
to write on or read from sockets. The following calls are available:

`socket(+DOMAIN,+TYPE,+PROTOCOL,-SOCKET)'
     Corresponds to the BSD system call `socket'. Create a socket for
     domain DOMAIN of type TYPE and protocol PROTOCOL. Both DOMAIN and
     TYPE should be atoms, whereas PROTOCOL must be an integer. The new
     socket object is accessible through a descriptor bound to the
     variable SOCKET.

     The current implementation of YAP only accepts two socket domains:
     `'AF_INET'' and `'AF_UNIX''. Socket types depend on the underlying
     operating system, but at least the following types are supported:
     `'SOCK_STREAM'' and `'SOCK_DGRAM''.

`socket(+DOMAIN,-SOCKET)'
     Call `socket/4' with TYPE bound to `'SOCK_STREAM'' and PROTOCOL
     bound to `0'.

`socket_close(+SOCKET)'
     Close socket SOCKET. Note that sockets used in `socket_connect'
     (that is, client sockets) should not be closed with
     `socket_close', as they will be automatically closed when the
     corresponding stream is closed with `close/1' or `close/2'.

`socket_bind(+SOCKET, ?PORT)'
     Interface to system call `bind', as used for servers: bind socket
     to a port. Port information depends on the domain:
    `'AF_UNIX'(+FILENAME)'

    `'AF_FILE'(+FILENAME)'
          use file name FILENAME for UNIX or local sockets.

    `'AF_INET'(?HOST,?PORT)'
          If HOST is bound to an atom, bind to host HOST, otherwise if
          unbound bind to local host (HOST remains unbound). If port
          PORT is bound to an integer, try to bind to the corresponding
          port. If variable PORT is unbound allow operating systems to
          choose a port number, which is unified with PORT.


`socket_connect(+SOCKET, +PORT, -STREAM)'
     Interface to system call `connect', used for clients: connect
     socket SOCKET to PORT. The connection results in the read/write
     stream STREAM.

     Port information depends on the domain:
    `'AF_UNIX'(+FILENAME)'

    `'AF_FILE'(+FILENAME)'
          connect to socket at file FILENAME.

    `'AF_INET'(+HOST,+PORT)'
          Connect to socket at host HOST and port PORT.

`socket_listen(+SOCKET, +LENGTH)'
     Interface to system call `listen', used for servers to indicate
     willingness to wait for connections at socket SOCKET. The integer
     LENGTH gives the queue limit for incoming connections, and should
     be limited to `5' for portable applications. The socket must be of
     type `SOCK_STREAM' or `SOCK_SEQPACKET'.

`socket_accept(+SOCKET, -STREAM)'

`socket_accept(+SOCKET, -CLIENT, -STREAM)'
     Interface to system call `accept', used for servers to wait for
     connections at socket SOCKET. The stream descriptor STREAM
     represents the resulting connection.  If the socket belongs to the
     domain `'AF_INET'', CLIENT unifies with an atom containing the IP
     address for the client in numbers and dots notation.

`socket_accept(+SOCKET, -STREAM)'
     Accept a connection but do not return client information.

`socket_buffering(+SOCKET, -MODE, -OLD, +NEW)'
     Set buffering for SOCKET in `read' or `write' MODE. OLD is unified
     with the previous status, and NEW receives the new status which
     may be one of `unbuf' or `fullbuf'.

`socket_select(+SOCKETS, -NEWSTREAMS, +TIMEOUT, +STREAMS, -READSTREAMS)'
     Interface to system call `select', used for servers to wait for
     connection requests or for data at sockets. The variable SOCKETS
     is a list of form KEY-SOCKET, where KEY is an user-defined
     identifier and SOCKET is a socket descriptor. The variable TIMEOUT
     is either `off', indicating execution will wait until something is
     available, or of the form SEC-USEC, where SEC and USEC give the
     seconds and microseconds before `socket_select/5' returns. The
     variable SOCKETS is a list of form KEY-STREAM, where KEY is an
     user-defined identifier and STREAM is a stream descriptor

     Execution of `socket_select/5' unifies READSTREAMS from STREAMS
     with readable data, and NEWSTREAMS with a list of the form
     KEY-STREAM, where KEY was the key for a socket with pending data,
     and STREAM the stream descriptor resulting from accepting the
     connection.

`current_host(?HOSTNAME)'
     Unify HOSTNAME with an atom representing the fully qualified
     hostname for the current host. Also succeeds if HOSTNAME is bound
     to the unqualified hostname.

`hostname_address(?HOSTNAME,?IP_ADDRESS)'
     HOSTNAME is an host name and IP_ADDRESS its IP address in number
     and dots notation.



File: yap.info,  Node: Database,  Next: Sets,  Prev: I/O,  Up: Top

Using the Clausal Data Base
===========================

Predicates in YAP may be dynamic or static. By default, when consulting
or reconsulting, predicates are assumed to be static: execution is
faster and the code will probably use less space.  Static predicates
impose some restrictions: in general there can be no addition or
removal of  clauses for a procedure if it is being used in the current
execution.

   Dynamic predicates allow programmers to change the Clausal Data Base
with the same flexibility as in C-Prolog. With dynamic predicates it is
always possible to add or remove clauses during execution and the
semantics will be the same as for C-Prolog. But the programmer should be
aware of the fact that asserting or retracting are still expensive
operations, and therefore he should try to avoid them whenever possible.

`dynamic +P'
     Declares predicate P or list of predicates [P1,...,PN] as a
     dynamic predicate. P must be written in form: NAME/ARITY.

          :- dynamic god/1.

     a more convenient form can be used:

          :- dynamic son/3, father/2, mother/2.

     or, equivalently,

          :- dynamic [son/3, father/2, mother/2].

     Note:

     a predicate is assumed to be dynamic when asserted before being
     defined.

`dynamic_predicate(+P,+SEMANTICS)'
     Declares predicate P or list of predicates [P1,...,PN] as a
     dynamic predicate following either `logical' or `immediate'
     semantics.

     * Menu:
     
     
     Subnodes of Database
     * Modifying the Database:: Asserting and Retracting
     * Looking at the Database:: Finding out what is in the Data Base
     * Database References:: Using Data Base References
     * Internal Database:: Yap's Internal Database
     * BlackBoard:: Storing and Fetching Terms in the BlackBoard



File: yap.info,  Node: Modifying the Database,  Next: Looking at the Database,  Up: Database

Modification of the Data Base
-----------------------------

These predicates can be used either for static or for dynamic
predicates:

`assert(+C)'
     Adds clause C to the program. If the predicate is undefined,
     declare it as dynamic.

     Most Prolog systems only allow asserting clauses for dynamic
     predicates. This is also as specified in the ISO standard. YAP
     allows asserting clauses for static predicates, as long as the
     predicate is not in use and the language flag is cprolog. Note
     that this feature is deprecated, if you want to assert clauses for
     static procedures you should use `assert_static/1'.

`asserta(+C) [ISO]'
     Adds clause C to the beginning of the program. If the predicate is
     undefined, declare it as dynamic.

`assertz(+C) [ISO]'
     Adds clause C to the end of the program. If the predicate is
     undefined, declare it as dynamic.

     Most Prolog systems only allow asserting clauses for dynamic
     predicates. This is also as specified in the ISO standard. YAP
     allows asserting clauses for static predicates. The current
     version of YAP supports this feature, but this feature is
     deprecated and support may go away in future versions.

`abolish(+PREDSPEC) [ISO]'
     Deletes the predicate given by PREDSPEC from the database. If
     PREDSPEC is an unbound variable, delete all predicates for the
     current module. The specification must include the name and arity,
     and it may include module information. Under iso language mode
     this builtin will only abolish dynamic procedures. Under other
     modes it will abolish any procedures.

`abolish(+P,+N)'
     Deletes the predicate with name P and arity N. It will remove both
     static and dynamic predicates.

`assert_static(:C)'
     Adds clause C to a static procedure. Asserting a static clause for
     a predicate while choice-points for the predicate are available has
     undefined results.

`asserta_static(:C)'
     Adds clause C to the beginning of a static procedure.

`assertz_static(:C)'
     Adds clause C to the end of a static procedure.  Asserting a
     static clause for a predicate while choice-points for the
     predicate are available has undefined results.


   The following predicates can be used for dynamic predicates and for
static predicates, if source mode was on when they were compiled:

`clause(+H,B) [ISO]'
     A clause whose head matches H is searched for in the program. Its
     head and body are respectively unified with H and B. If the clause
     is a unit clause, B is unified with TRUE.

     This predicate is applicable to static procedures compiled with
     `source' active, and to all dynamic procedures.

`clause(+H,B,-R)'
     The same as `clause/2', plus R is unified with the reference to
     the clause in the database. You can use `instance/2' to access the
     reference's value. Note that you may not use `erase/1' on the
     reference on static procedures.

`nth_clause(+H,I,-R)'
     Find the Ith clause in the predicate defining H, and give a
     reference to the clause. Alternatively, if the reference R is
     given the head H is unified with a description of the predicate
     and I is bound to its position.


   The following predicates can only be used for dynamic predicates:

`retract(+C) [ISO]'
     Erases the first clause in the program that matches C. This
     predicate may also be used for the static predicates that have been
     compiled when the source mode was `on'. For more information on
     `source/0' (*note Setting the Compiler::).

`retractall(+G)'
     Retract all the clauses whose head matches the goal G. Goal G must
     be a call to a dynamic predicate.



File: yap.info,  Node: Looking at the Database,  Next: Database References,  Prev: Modifying the Database,  Up: Database

Looking at the Data Base
------------------------

`listing'
     Lists in the current output stream all the clauses for which
     source code is available (these include all clauses for dynamic
     predicates and clauses for static predicates compiled when source
     mode was `on').

`listing(+P)'
     Lists predicate P if its source code is available.

`portray_clause(+C)'
     Write clause C as if written by `listing/0'.

`portray_clause(+S,+C)'
     Write clause C on stream S as if written by `listing/0'.

`current_atom(A)'
     Checks whether A is a currently defined atom. It is used to find
     all currently defined atoms by backtracking.

`current_predicate(F) [ISO]'
     F is the predicate indicator for a currently defined user or
     library predicate. F is of the form NA/AR, where the atom NA is
     the name of the predicate, and AR its arity.

`current_predicate(A,P)'
     Defines the relation: P is a currently defined predicate whose
     name is the atom A.

`system_predicate(A,P)'
     Defines the relation:  P is a built-in predicate whose name is the
     atom A.

`predicate_property(P,PROP)'
     For the predicates obeying the specification P unify PROP with a
     property of P. These properties may be:
    `built_in'
          true for built-in predicates,

    `dynamic'
          true if the predicate is dynamic

    `static'
          true if the predicate is static

    `meta_predicate(M)'
          true if the predicate has a meta_predicate declaration M.

    `multifile'
          true if the predicate was declared to be multifile

    `imported_from(MOD)'
          true if the predicate was imported from module MOD.

    `exported'
          true if the predicate is exported in the current module.

    `public'
          true if the predicate is public; note that all dynamic
          predicates are public.

    `tabled'
          true if the predicate is tabled; note that only static
          predicates can be tabled in YAP.

    `source'
          true if source for the predicate is available.

    `number_of_clauses(CLAUSECOUNT)'
          Number of clauses in the predicate definition. Always one if
          external or built-in.



File: yap.info,  Node: Database References,  Next: Internal Database,  Prev: Looking at the Database,  Up: Database

Using Data Base References
--------------------------

Data Base references are a fast way of accessing terms. The predicates
`erase/1' and `instance/1' also apply to these references and may
sometimes be used instead of `retract/1' and `clause/2'.

`assert(+C,-R)'
     The same as `assert(C)' (*note Modifying the Database::) but
     unifies R with the  database reference that identifies the new
     clause, in a one-to-one way. Note that `asserta/2' only works for
     dynamic predicates. If the predicate is undefined, it will
     automatically be declared dynamic.

`asserta(+C,-R)'
     The same as `asserta(C)' but unifying R with the  database
     reference that identifies the new clause, in a one-to-one way.
     Note that `asserta/2' only works for dynamic predicates. If the
     predicate is undefined, it will automatically be declared dynamic.

`assertz(+C,-R)'
     The same as `assertz(C)' but unifying R with the  database
     reference that identifies the new clause, in a one-to-one way.
     Note that `asserta/2' only works for dynamic predicates. If the
     predicate is undefined, it will automatically be declared dynamic.

`retract(+C,-R)'
     Erases from the program the clause C whose database reference is
     R. The predicate must be dynamic.



File: yap.info,  Node: Internal Database,  Next: BlackBoard,  Prev: Database References,  Up: Database

Internal Data Base
==================

Some programs need global information for, eg.,  counting or collecting
data obtained by backtracking. As a rule, to keep this information, the
internal data base should be used instead of asserting and retracting
clauses (as most novice programmers  do), .  In YAP (as in some other
Prolog systems) the internal data base (i.d.b.  for short) is faster,
needs less space and provides a better insulation of program and data
than using asserted/retracted clauses.  The i.d.b. is implemented as a
set of terms, accessed by keys that unlikely what happens in
(non-Prolog) data bases are not part of the term. Under each key a list
of terms is kept. References are provided so that terms can be
identified: each term in the i.d.b. has a unique reference (references
are also available for clauses of dynamic predicates).

`recorda(+K,T,-R)'
     Makes term T the first record under key K and  unifies R with its
     reference.

`recordz(+K,T,-R)'
     Makes term T the last record under key K and unifies R with its
     reference.

`recorda_at(+R0,T,-R)'
     Makes term T the record preceeding record with reference R0, and
     unifies R with its reference.

`recordz_at(+R0,T,-R)'
     Makes term T the record following record with reference R0, and
     unifies R with its reference.

`recordaifnot(+K,T,-R)'
     If a term equal to T up to variable renaming is stored under key K
     fail. Otherwise, make term T the first record under key K and
     unify R with its reference.

`recordzifnot(+K,T,-R)'
     If a term equal to T up to variable renaming is stored under key K
     fail. Otherwise, make term T the first record under key K and
     unify R with its reference.

`recorded(+K,T,R)'
     Searches in the internal database under the key K, a term that
     unifies with T and whose reference matches R. This built-in may be
     used in one of two ways:
        * K may be given, in this case the built-in will return all
          elements of the internal data-base that match the key.

        * R may be given, if so returning the key and element that
          match the reference.

`nth_instance(?K,?INDEX,T,?R)'
     Fetches the INDEXnth entry in the internal database under the key
     K. Entries are numbered from one. If the key K are the INDEX are
     bound, a reference is unified with R. Otherwise, the reference R
     must be given, and the term the system will find the matching key
     and index.

`erase(+R)'
     The term referred to by R is erased from the internal database. If
     reference R does not exist in the database, `erase' just fails.

`erased(+R)'
     Succeeds if the object whose database reference is R has been
     erased.

`instance(+R,-T)'
     If R refers to a clause or a recorded term, T is unified with its
     most general instance. If R refers to an unit clause C, then T is
     unified with `C :- true'. When R is not a reference to an existing
     clause or to a recorded term, this goal fails.

`eraseall(+K)'
     All terms belonging to the key `K' are erased from the internal
     database. The predicate always succeeds.

`current_key(?A,?K)'
     Defines the relation: K is a currently defined database key whose
     name is the atom A. It can be used to generate all the keys for
     the internal data-base.

`key_statistics(+K,-ENTRIES,-SIZE,-INDEXSIZE)'
     Returns several statistics for a key K. Currently, it says how
     many entries we have for that key, ENTRIES, what is the total size
     spent on entries, SIZE, and what is the amount of space spent in
     indices.

`key_statistics(+K,-ENTRIES,-TOTALSIZE)'
     Returns several statistics for a key K. Currently, it says how
     many entries we have for that key, ENTRIES, what is the total size
     spent on this key.

`get_value(+A,-V)'
     In YAP, atoms can be associated with constants. If one such
     association exists for atom A, unify the second argument with the
     constant. Otherwise, unify V with `[]'.

     This predicate is YAP specific.

`set_value(+A,+C)'
     Associate atom A with constant C.

     The `set_value' and `get_value' built-ins give a fast alternative
     to the internal data-base. This is a simple form of implementing a
     global counter.
                 read_and_increment_counter(Value) :-
                          get_value(counter, Value),
                          Value1 is Value+1,
                          set_value(counter, Value1).

     This predicate is YAP specific.

`recordzifnot(+K,T,-R)'
     If a variant of T is stored under key K fail. Otherwise, make term
     T the last record under key K and unify R with its reference.

     This predicate is YAP specific.

`recordaifnot(+K,T,-R)'
     If a variant of T is stored under key K fail. Otherwise, make term
     T the first record under key K and unify R with its reference.

     This predicate is YAP specific.


   There is a strong analogy between the i.d.b. and the way dynamic
predicates are stored. In fact, the main i.d.b. predicates might be
implemented using dynamic predicates:

     recorda(X,T,R) :- asserta(idb(X,T),R).
     recordz(X,T,R) :- assertz(idb(X,T),R).
     recorded(X,T,R) :- clause(idb(X,T),R).

We can take advantage of this, the other way around, as it is quite
easy to write a simple Prolog interpreter, using the i.d.b.:

     asserta(G) :- recorda(interpreter,G,_).
     assertz(G) :- recordz(interpreter,G,_).
     retract(G) :- recorded(interpreter,G,R), !, erase(R).
     call(V) :- var(V), !, fail.
     call((H :- B)) :- !, recorded(interpreter,(H :- B),_), call(B).
     call(G) :- recorded(interpreter,G,_).

In YAP, much attention has been given to the implementation of the
i.d.b., especially to the problem of accelerating the access to terms
kept in a large list under the same key. Besides using the key, YAP
uses an internal lookup function, transparent to the user, to find only
the terms that might unify. For instance, in a data base containing the
terms

     b
     b(a)
     c(d)
     e(g)
     b(X)
     e(h)

stored under the key k/1, when executing the query

     :- recorded(k(_),c(_),R).

`recorded' would proceed directly to the third term, spending almost the
time as if `a(X)' or `b(X)' was being searched.   The lookup function
uses the functor of the term, and its first three arguments (when they
exist). So, `recorded(k(_),e(h),_)' would go directly to the last term,
while `recorded(k(_),e(_),_)' would find first the fourth term, and
then, after backtracking, the last one.

   This mechanism may be useful to implement a sort of hierarchy, where
the functors of the terms (and eventually the first arguments) work as
secondary keys.

   In the YAP's i.d.b. an optimized representation is used for terms
without free variables. This results in a faster retrieval of terms and
better space usage. Whenever possible, avoid variables in terms in
terms stored in the  i.d.b.


File: yap.info,  Node: BlackBoard,  Prev: Internal Database,  Up: Database

The Blackboard
==============

YAP implements a blackboard in the style of the SICStus Prolog
blackboard. The blackboard uses the same underlying mechanism as the
internal data-base but has several important differences:
   * It is module aware, in contrast to the internal data-base.

   * Keys can only be atoms or integers, and not compound terms.

   * A single term can be stored per key.

   * An atomic update operation is provided; this is useful for
     parallelism.

`bb_put(+KEY,?TERM)'
     Store term table TERM in the blackboard under key KEY. If a
     previous term was stored under key KEY it is simply forgotten.

`bb_get(+KEY,?TERM)'
     Unify TERM with a term stored in the blackboard under key KEY, or
     fail silently if no such term exists.

`bb_delete(+KEY,?TERM)'
     Delete any term stored in the blackboard under key KEY and unify
     it with TERM. Fail silently if no such term exists.

`bb_update(+KEY,?TERM,?NEW)'
     Atomically  unify a term stored in the blackboard under key KEY
     with TERM, and if the unification succeeds replace it by NEW. Fail
     silently if no such term exists or if unification fails.



File: yap.info,  Node: Sets,  Next: Grammars,  Prev: Database,  Up: Top

Collecting Solutions to a Goal
==============================

When there are several solutions to a goal, if the user wants to
collect all the solutions he may be led to use the data base, because
backtracking will forget previous solutions.

   YAP allows the programmer to choose from several system predicates
instead of writing his own routines.  `findall/3' gives you the
fastest, but crudest solution. The other built-in predicates
postprocess the result of the query in several different ways:

`findall(T,+G,-L) [ISO]'
     Unifies L with a list that contains all the instantiations of the
     term T satisfying the goal G.

     With the following program:
          a(2,1).
          a(1,1).
          a(2,2).

     the answer to the query
          findall(X,a(X,Y),L).

     would be:
          X = _32
          Y = _33
          L = [2,1,2];
          no

`findall(T,+G,+L,-L0)'
     Similar to `findall/3', but appends all answers to list L0.

`all(T,+G,-L)'
     Similar to `findall(T,G,L)' but eliminating repeated elements.
     Thus, assuming the same clauses as in the above example, the reply
     to the query

          all(X,a(X,Y),L).

     would be:

          X = _32
          Y = _33
          L = [2,1];
          no

`bagof(T,+G,-L) [ISO]'
     For each set of possible instances of the free variables occurring
     in G but not in T, generates the list L of the instances of T
     satisfying G. Again, assuming the same clauses as in the examples
     above, the reply to the query

          bagof(X,a(X,Y),L).
          
          would be:
          X = _32
          Y = 1
          L = [2,1];
          X = _32
          Y = 2
          L = [2];
          no

`setof(X,+P,-B) [ISO]'
     Similar to `bagof(T,G,L)' but sorting list L and keeping only one
     copy of each element.  Again, assuming the same clauses as in the
     examples above, the reply to the query
          setof(X,a(X,Y),L).

     would be:
          X = _32
          Y = 1
          L = [1,2];
          X = _32
          Y = 2
          L = [2];
          no



File: yap.info,  Node: Grammars,  Next: OS,  Prev: Sets,  Up: Top

Grammar Rules
=============

Grammar rules in Prolog are both a convenient way to express definite
clause grammars and  an extension of the well known context-free
grammars.

   A grammar rule is of the form:

      head -> body

where both head and body are sequences of one or more items linked by
the standard conjunction operator ','.

   _Items can be:_

   * a _non-terminal_ symbol may be either a complex term or an atom.

   * a _terminal_ symbol may be any Prolog symbol. Terminals are
     written as Prolog lists.

   * an _empty body_ is written as the empty list '[ ]'.

   * _extra conditions_ may be inserted as Prolog procedure calls, by
     being written inside curly brackets '{' and '}'.

   * the left side of a rule consists of a nonterminal and an optional
     list of terminals.

   * alternatives may be stated in the right-hand side of the rule by
     using the disjunction operator ';'.

   * the _cut_ and _conditional_ symbol ('->') may be inserted in the
     right hand side of a grammar rule

   Grammar related built-in predicates:

`expand_term(T,-X)'
     This predicate is used by YAP for preprocessing each top level
     term read when consulting a file and before asserting or executing
     it.  It rewrites a term T to a term X according to the following
     rules: first try to use the user defined predicate
     `term_expansion/2'. If this call fails then the translating process
     for DCG rules is applied, together with the arithmetic optimizer
     whenever the compilation of arithmetic expressions is in progress.

`user:goal_expansion(+G,+M,-NG)'
     Yap now supports `goal_expansion/3'. This is an user-defined
     procedure that is called after term expansion when compiling or
     asserting goals for each sub-goal in a clause. The first argument
     is bound to the goal and the second to the module under which the
     goal G will execute. If `goal_expansion/3' succeeds the new
     sub-goal NG will replace G and will be processed in the same way.
     If `goal_expansion/3' fails the system will use the default rules.

`phrase(+P,L,R)'
     This predicate succeeds when the difference list `L-R' is a phrase
     of type P.

`phrase(+P,L)'
     This predicate succeeds when L is a phrase of type P. The same as
     `phrase(P,L,[])'.

     Both this predicate and the previous are used as a convenient way
     to start execution of grammar rules.

`'C'(S1,T,S2)'
     This predicate is used by the grammar rules compiler and is
     defined as `'C'([H|T],H,T)'.



File: yap.info,  Node: OS,  Next: Term Modification,  Prev: Grammars,  Up: Top

Access to Operating System Functionality
========================================

The following built-in predicates allow access to underlying Operating
System functionality:

`cd(+D)'
     Changes the current directory (on UNIX environments).

`environ(+E,-S)'
     Given an enviromment variable E this predicate unifies the second
     argument S with its value.

`getcwd(-D)'
     Unify the current directory, represented as an atom, with the
     argument D.

`putenv(+E,+S)'
     Set environment variable E to the value S. If the environment
     variable E does not exist, create a new one. Both the environment
     variable and the value must be atoms.

`rename(+F,+G)'
     Renames file F to G.

`sh'
     Creates a new shell interaction.

`system(+S)'
     Passes command S to the Bourne shell (on UNIX environments) or the
     current command interpreter in WIN32 environments.

`unix(+S)'
     Access to Unix-like functionality:
    `argv/1'
          Return a list of arguments to the program. These are the
          arguments that follow a `--', as in the usual Unix convention.

    `cd/0'
          Change to home directory.

    `cd/1'
          Change to given directory. Acceptable directory names are
          strings or atoms.

    `environ/2'
          If the first argument is an atom, unify the second argument
          with the value of the corresponding environment variable.

    `getcwd/1'
          Unify the first argument with an atom representing the
          current directory.

    `putenv/2'
          Set environment variable E to the value S. If the environment
          variable E does not exist, create a new one. Both the
          environment variable and the value must be atoms.

    `shell/1'
          Execute command under current shell. Acceptable commands are
          strings or atoms.

    `system/1'
          Execute command with `/bin/sh'. Acceptable commands are
          strings or atoms.

    `shell/0'
          Execute a new shell.

`alarm(+SECONDS,+CALLABLE,+OLDALARM)'
     Arranges for YAP to be interrupted in SECONDS seconds. When
     interrupted, YAP will execute CALLABLE and then return to the
     previous execution. If SECONDS is `0', no new alarm is scheduled.
     In any event, any previously set alarm is canceled.

     The variable OLDALARM unifies with the number of seconds remaining
     until any previously scheduled alarm was due to be delivered, or
     with `0' if there was no previously scheduled alarm.

     Note that execution of CALLABLE will wait if YAP is executing
     built-in predicates, such as Input/Output operations.

     The next example shows how ALARM/3 can be used to implement a
     simple clock:

          loop :- loop.
          
          ticker :- write('.'), flush_output,
                    get_value(tick, yes),
                    alarm(1,ticker,_).
          
          :- set_value(tick, yes), alarm(1,ticker,_), loop.

     The clock, `ticker', writes a dot and then checks the flag `tick'
     to see whether it can continue ticking. If so, it calls itself
     again. Note that there is no guarantee that the each dot
     corresponds a second: for instance, if the YAP is waiting for user
     input, `ticker' will wait until the user types the entry in.

     The next example shows how `alarm/3' can be used to guarantee that
     a certain procedure does not take longer than a certain amount of
     time:

          loop :- loop.
          
          :-   catch((alarm(10, throw(ball), _),loop),
                  ball,
                  format('Quota exhausted.~n',[])).
     In this case after `10' seconds our `loop' is interrupted, `ball'
     is thrown,  and the handler writes `Quota exhausted'.  Execution
     then continues from the handler.

     Note that in this case `loop/0' always executes until the alarm is
     sent. Often, the code you are executing succeeds or fails before
     the alarm is actually delivered. In this case, you probably want
     to disable the alarm when you leave the procedure. The next
     procedure does exactly so:
          once_with_alarm(Time,Goal,DoOnAlarm) :-
             catch(execute_once_with_alarm(Time, Goal), alarm, DoOnAlarm).
          
          execute_once_with_alarm(Time, Goal) :-
                  alarm(Time, alarm, _),
                  ( call(Goal) -> alarm(0, alarm, _) ; alarm(0, alarm, _)).

     The procedure has three arguments: the TIME before the alarm is
     sent; the GOAL to execute; and the goal DOONALARM to execute if
     the alarm is sent. It uses `catch/3' to handle the case the
     `alarm' is sent. Then it starts the alarm, calls the goal GOAL,
     and disables the alarm on success or failure.

`on_signal(+SIGNAL,?OLDACTION,+CALLABLE)'
     Set the interrupt handler for soft interrupt SIGNAL to be
     CALLABLE. OLDACTION is unified with the previous handler.

     Only a subset of the software interrupts (signals) can have their
     handlers manipulated through `on_signal/3'.  Their POSIX names,
     YAP names and default behavior is given below.  The "YAP name" of
     the signal is the atom that is associated with each signal, and
     should be used as the first argument to `on_signal/3'. It is
     chosen so that it matches the signal's POSIX name.

     `on_signal/3' succeeds, unless when called with an invalid signal
     name or one that is not supported on this platform. No checks are
     made on the handler provided by the user.

    `SIGHUP (Hangup)'
          sig_hup in YAP; Reconsult the initialization files
          ~/.yaprc, ~/.prologrc and ~/prolog.ini.

    `SIGUSR1 and SIGUSR2 (User signals)'
          sig_usr1 and sig_usr2 in YAP; Print a message and halt.

     A special case is made, where if CALLABLE is bound to `default',
     then the default handler is restored for that signal.

     A call in the form `on_signal(S,H,H)' can be used to retrieve a
     signal's current handler without changing it.

     It must be noted that although a signal can be received at all
     times, the handler is not executed while Yap is waiting for a
     query at the prompt. The signal will be, however, registered and
     dealt with as soon as the user makes a query.

     Please also note, that neither POSIX Operating Systems nor Yap
     guarantee that the order of delivery and handling is going to
     correspond with the order of dispatch.



File: yap.info,  Node: Term Modification,  Next: Profiling,  Prev: OS,  Up: Top

Term Modification
=================

It is sometimes useful to change the value of instantiated variables.
Although, this is against the spirit of logic programming, it is
sometimes useful. As in other Prolog systems, YAP has several
primitives that allow updating Prolog terms. Note that these primitives
are also backtrackable.

   The `setarg/3' primitive allows updating any argument of a Prolog
compound terms. The `mutable' family of predicates provides _mutable
variables_. They should be used instead of `setarg/3', as they allow
the encapsulation of accesses to updatable variables. Their
implementation can also be more efficient for long deterministic
computations.

`setarg(+I,+S,?T)'
     Set the value of the Ith argument of term S to term T.

`create_mutable(+D,-M)'
     Create new mutable variable M with initial value D.

`get_mutable(?D,+M)'
     Unify the current value of mutable term M with term D.

`is_mutable(?D)'
     Holds if D is a mutable term.

`get_mutable(?D,+M)'
     Unify the current value of mutable term M with term D.

`update_mutable(+D,+M)'
     Set the current value of mutable term M to term D.


File: yap.info,  Node: Profiling,  Next: Call Counting,  Prev: Term Modification,  Up: Top

Profiling Prolog Programs
=========================

Predicates compiled with YAP's flag `profiling' set to `on', keep
information on the number of times the predicate was called. This
information can be used to detect what are the most commonly called
predicates in the program.

   The YAP profiling sub-system is currently under-development.
Functionality for this sub-system will increase with newer
implementation.

   *Notes:*

   * Profiling works for both static and dynamic predicates.

   * Currently only information on entries and retries to a predicate
     are maintained. This may change in the future.

   * As an example, the following user-level program gives a list of
     the most often called procedures in a program. The procedure
     `list_profile' shows all procedures, irrespective of module, and
     the procedure `list_profile/1' shows the procedures being used in
     a specific module.
          list_profile :-
                  % get number of calls for each profiled procedure
                  setof(D-[M:P|D1],(current_module(M),profile_data(M:P,calls,D),profile_data(M:P,retries,D1)),LP),
                  % output so that the most often called
                  % predicates will come last:
                  write_profile_data(LP).
          
          list_profile(Module) :-
                  % get number of calls for each profiled procedure
                  setof(D-[Module:P|D1],(profile_data(Module:P,calls,D),profile_data(Module:P,retries,D1)),LP),
                  % output so that the most often called
                  % predicates will come last:
                  write_profile_data(LP).
          
          write_profile_data([]).
          write_profile_data([D-[M:P|R]|SLP]) :-
                  % swap the two calls if you want the most often
                  %  called predicates first.
                  format('~a:~w: ~32+~t~d~12+~t~d~12+~n', [M,P,D,R]),
                  write_profile_data(SLP).

   These are  the current predicates to access and clear profiling data:

`profile_data(?NA/AR, ?PARAMETER, -DATA)'
     Give current profile data on PARAMETER for a predicate described
     by the predicate indicator NA/AR. If any of NA/AR or PARAMETER are
     unbound, backtrack through all profiled predicates or stored
     parameters. Current parameters are:

    `calls'
          Number of times a procedure was called.

    `retries'
          Number of times a call to the procedure was backtracked to
          and retried.

`profile_reset'
     Reset all profiling information.



File: yap.info,  Node: Call Counting,  Next: Arrays,  Prev: Profiling,  Up: Top

Counting Calls
==============

Predicates compiled with YAP's flag `call_counting' set to `on' update
counters on the numbers of calls and of retries. Counters are actually
decreasing counters, so that they can be used as timers.  Three
counters are available:
   * `calls': number of predicate calls since execution started or since
     system was reset;

   * `retries': number of retries for predicates called since execution
     started or since counters were reset;

   * `calls_and_retries': count both on predicate calls and retries.
   These counters can be used to find out how many calls a certain goal
takes to execute. They can also be used as timers.

   The code for the call counters piggybacks on the profiling code.
Therefore, activating the call counters also activates the profiling
counters.

   These are  the predicates that access and manipulate the call
counters:

`call_count_data(-CALLS, -RETRIES, -CALLSANDRETRIES)'
     Give current call count data. The first argument gives the current
     value for the CALLS counter, next the RETRIES counter, and last
     the CALLSANDRETRIES counter.

`call_count_reset'
     Reset call count counters. All timers are also reset.

`call_count(?CALLSMAX, ?RETRIESMAX, ?CALLSANDRETRIESMAX)'
     Set call count counter as timers. YAP will generate an exception
     if one of the instantiated call counters decreases to 0. YAP will
     ignore unbound arguments:
        * CALLSMAX: throw the exception `call_counter' when the counter
          `calls' reaches 0;

        * RETRIESMAX: throw the exception `retry_counter' when the
          counter `retries' reaches 0;

        * CALLSANDRETRIESMAX: throw the exception
          `call_and_retry_counter' when the counter `calls_and_retries'
          reaches 0.

   Next, we show a simple example of how to use call counters:
        ?- yap_flag(call_counting,on), [-user]. l :- l. end_of_file. yap_flag(call_counting,off).
     
     yes
     
     yes
        ?- catch((call_count(10000,_,_),l),call_counter,format("limit_exceeded.~n",[])).
     
     limit_exceeded.
     
     yes
   Notice that we first compile the looping predicate `l/0' with
`call_counting' `on'. Next, we `catch/3' to handle an exception when
`l/0' performs more than 10000 reductions.


File: yap.info,  Node: Arrays,  Next: Preds,  Prev: Call Counting,  Up: Top

Arrays
======

The YAP system includes experimental support for arrays. The support is
enabled with the option `YAP_ARRAYS'.

   There are two very distinct forms of arrays in YAP. The _dynamic
arrays_ are a different way to access compound terms created during the
execution. Like any other terms, any bindings to these terms and
eventually the terms themselves will be destroyed during backtracking.
Our goal in supporting dynamic arrays is twofold. First, they provide
an alternative to the standard `arg/3' built-in. Second, because
dynamic arrays may have name that are globally visible, a dynamic array
can be visible from any point in the program. In more detail, the clause
     g(X) :- array_element(a,2,X).
   will succeed as long as the programmer has used the builtin array/2
to create an array term with at least 3 elements in the current
environment, and the array was associated with the name `a'.  The
element `X' is a Prolog term, so one can bind it and any such bindings
will be undone when backtracking. Note that dynamic arrays do not have
a type: each element may be any Prolog term.

   The _static arrays_ are an extension of the database. They provide a
compact way for manipulating data-structures formed by characters,
integers, or floats imperatively. They can also be used to provide
two-way communication between YAP and external programs through shared
memory.

   In order to efficiently manage space elements in a static array must
have a type. Currently, elements of static arrays in YAP should have
one of the following predefined types:

   * `byte': an 8-bit signed character.

   * `unsigned_byte': an 8-bit unsigned character.

   * `int': Prolog integers. Size would be the natural size for the
     machine's architecture.

   * `float': Prolog floating point number. Size would be equivalent to
     a double in `C'.

   * `atom': a Prolog atom.

   * `dbref': an internal database reference.

   * `term': a generic Prolog term. Note that this will term will not
     be stored in the array itself, but instead will be stored in the
     Prolog internal database.

   Arrays may be _named_ or _anonymous_. Most arrays will be _named_,
that is associated with an atom that will be used to find the array.
Anonymous arrays do not have a name, and they are only of interest if
the `TERM_EXTENSIONS' compilation flag is enabled. In this case, the
unification and parser are extended to replace occurrences of Prolog
terms of the form `X[I]' by run-time calls to `array_element/3', so
that one can use array references instead of extra calls to `arg/3'. As
an example:
     g(X,Y,Z,I,J) :- X[I] is Y[J]+Z[I].
   should give the same results as:
     G(X,Y,Z,I,J) :-
             array_element(X,I,E1),
             array_element(Y,J,E2),
             array_element(Z,I,E3),
             E1 is E2+E3.

   Note that the only limitation on array size are the stack size for
dynamic arrays; and, the heap size for static (not memory mapped)
arrays. Memory mapped arrays are limited by available space in the file
system and in the virtual memory space.

   The following predicates manipulate arrays:

`array(+NAME, +SIZE)'
     Creates a new dynamic array. The SIZE must evaluate to an integer.
     The NAME may be either an atom (named array) or an unbound
     variable (anonymous array).

     Dynamic arrays work as standard compound terms, hence space for the
     array is recovered automatically on backtracking.

`static_array(+NAME, +SIZE, +TYPE)'
     Create a new static array with name NAME. Note that the NAME must
     be an atom (named array). The SIZE must evaluate to an integer.
     The TYPE must be bound to one of types mentioned previously.

`static_array_properties(?NAME, ?SIZE, ?TYPE)'
     Show the properties size and type of a static array with name
     NAME. Can also be used to enumerate all current static arrays.

     This built-in will silently fail if the there is no static array
     with that name.

`static_array_to_term(?NAME, ?TERM)'
     Convert a static array with name NAME to a compound term of name
     NAME.

     This built-in will silently fail if the there is no static array
     with that name.

`mmapped_array(+NAME, +SIZE, +TYPE, +FILE)'
     Similar to `static_array/3', but the array is memory mapped to file
     FILE. This means that the array is initialized from the file, and
     that any changes to the array will also be stored in the file.

     This built-in is only available in operating systems that support
     the system call `mmap'. Moreover, mmapped arrays do not store
     generic terms (type `term').

`close_static_array(+NAME)'
     Close an existing static array of name NAME. The NAME must be an
     atom (named array). Space for the array will be recovered and
     further accesses to the array will return an error.

`resize_static_array(+NAME, -OLDSIZE, +NEWSIZE)'
     Expand or reduce a static array, The SIZE must evaluate to an
     integer. The NAME must be an atom (named array). The TYPE must be
     bound to one of `int', `dbref', `float' or `atom'.

     Note that if the array is a mmapped array the size of the mmapped
     file will be actually adjusted to correspond to the size of the
     array.

`array_element(+NAME, +INDEX, ?ELEMENT)'
     Unify ELEMENT with NAME[INDEX]. It works for both static and
     dynamic arrays, but it is read-only for static arrays, while it
     can be used to unify with an element of a dynamic array.

`update_array(+NAME, +INDEX, ?VALUE)'
     Attribute value VALUE to NAME[INDEX]. Type restrictions must be
     respected for static arrays. This operation is available for
     dynamic arrays if `MULTI_ASSIGNMENT_VARIABLES' is enabled (true by
     default). Backtracking undoes UPDATE_ARRAY/3 for dynamic arrays,
     but not for static arrays.

     Note that `update_array/3' actually uses `setarg/3' to update
     elements of dynamic arrays, and `setarg/3' spends an extra cell for
     every update. For intensive operations we suggest it may be less
     expensive to unify each element of the array with a mutable terms
     and to use the operations on mutable terms.

`add_to_array_element(+NAME, +INDEX, , +NUMBER, ?NEWVALUE)'
     Add NUMBER NAME[INDEX] and unify NEWVALUE with the incremented
     value. Observe that NAME[INDEX] must be an number. If NAME is a
     static array the type of the array must be `int' or `float'. If
     the type of the array is `int' you only may add integers, if it is
     `float' you may add integers or floats. If NAME corresponds to a
     dynamic array the array element must have been previously bound to
     a number and `Number' can be any kind of number.

     The `add_to_array_element/3' built-in actually uses `setarg/3' to
     update elements of dynamic arrays. For intensive operations we
     suggest it may be less expensive to unify each element of the
     array with a mutable terms and to use the operations on mutable
     terms.



File: yap.info,  Node: Preds,  Next: Misc,  Prev: Arrays,  Up: Top

Predicate Information
=====================

Built-ins that return information on the current predicates and modules:

`current_module(M)'
     Succeeds if M are defined modules. A module is defined as soon as
     some predicate defined in the module is loaded, as soon as a goal
     in the module is called, or as soon as it becomes the current
     typein module.

`current_module(M,F)'
     Succeeds if M are current modules associated to the file F.



File: yap.info,  Node: Misc,  Prev: Preds,  Up: Top

Miscellaneous
=============

`statistics/0'
     Send to the current user error stream general information on space
     used and time spent by the system.
          ?- statistics.
          memory (total)        4784124 bytes
             program space      3055616 bytes:    1392224 in use,      1663392 free
                                                                       2228132  max
             stack space        1531904 bytes:        464 in use,      1531440 free
               global stack:                           96 in use,       616684  max
                local stack:                          368 in use,       546208  max
             trail stack         196604 bytes:          8 in use,       196596 free
          
                 0.010 sec. for 5 code, 2 stack, and 1 trail space overflows
                 0.130 sec. for 3 garbage collections which collected 421000 bytes
                 0.000 sec. for 0 atom garbage collections which collected 0 bytes
                 0.880 sec. runtime
                 1.020 sec. cputime
                25.055 sec. elapsed time
     The example shows how much memory the system spends. Memory is
     divided into Program Space, Stack Space and Trail. In the example
     we have 3MB allocated for program spaces, with less than half
     being actually used. Yap also shows the maximum amount of heap
     space having been used which was over 2MB.

     The stack space is divided into two stacks which grow against each
     other. We are in the top level so very little stack is being used.
     On the other hand, the system did use a lot of global and local
     stack during the previous execution (we refer the reader to a WAM
     tutorial in order to understand what are the global and local
     stacks).

     Yap also shows information on how many memory overflows and garbage
     collections the system executed, and statistics on total execution
     time. Cputime includes all running time, runtime excludes garbage
     collection and stack overflow time.

`statistics(?PARAM,-INFO)'
     Gives statistical information on the system parameter given by
     first argument:

    `cputime'
          `[TIME SINCE BOOT,TIME FROM LAST CALL TO CPUTIME]'
          This gives the total cputime in milliseconds spent executing
          Prolog code, garbage collection and stack shifts time
          included.

    `garbage_collection'
          `[NUMBER OF GCS,TOTAL GLOBAL RECOVERED,TOTAL TIME SPENT]'
          Number of garbage collections, amount of space recovered in
          kbytes, and total time spent doing garbage collection in
          milliseconds. More detailed information is available using
          `yap_flag(gc_trace,verbose)'.

    `global_stack'
          `[GLOBAL STACK USED,EXECUTION STACK FREE]'
          Space in kbytes currently used in the global stack, and space
          available for expansion by the local and global stacks.

    `local_stack'
          `[LOCAL STACK USED,EXECUTION STACK FREE]'
          Space in kbytes currently used in the local stack, and space
          available for expansion by the local and global stacks.

    `heap'
          `[HEAP USED,HEAP FREE]'
          Total space in kbytes not recoverable in backtracking. It
          includes the program code, internal data base, and, atom
          symbol table.

    `program'
          `[PROGRAM SPACE USED,PROGRAM SPACE FREE]'
          Equivalent to `heap'.

    `runtime'
          `[TIME SINCE BOOT,TIME FROM LAST CALL TO RUNTIME]'
          This gives the total cputime in milliseconds spent executing
          Prolog code, not including garbage collections and stack
          shifts. Note that until Yap4.1.2 the `runtime' statistics
          would return time spent on garbage collection and stack
          shifting.

    `stack_shifts'
          `[NUMBER OF HEAP SHIFTS,NUMBER OF STACK SHIFTS,NUMBER OF
          TRAIL SHIFTS]'
          Number of times YAP had to expand the heap, the stacks, or
          the trail. More detailed information is available using
          `yap_flag(gc_trace,verbose)'.

    `trail'
          `[TRAIL USED,TRAIL FREE]'
          Space in kbytes currently being used and still available for
          the trail.

    `walltime'
          `[TIME SINCE BOOT,TIME FROM LAST CALL TO RUNTIME]'
          This gives the clock time in milliseconds since starting
          Prolog.


`yap_flag(?PARAM,?VALUE)'
     Set or read system properties for PARAM:

    `argv'
          Read-only flag. It unifies with a list of atoms that gives the
          arguments to Yap after `--'.

    `bounded [ISO]'
          Read-only flag telling whether integers are bounded. The
          value depends on whether YAP uses the GMP library or not.

    `profiling'
          If `off' (default) do not compile call counting information
          for procedures. If `on' compile predicates so that they calls
          and retries to the predicate may be counted. Profiling data
          can be read through the `call_count_data/3' built-in.

    `char_conversion [ISO]'
          Writable flag telling whether a character conversion table is
          used when reading terms. The default value for this flag is
          `off' except in `sicstus' and `iso' language modes, where it
          is `on'.

    `character_escapes [ISO]'
          Writable flag telling whether a character escapes are enables,
          `on', or disabled, `off'. The default value for this flag is
          `on'.

    `debug [ISO]'
          If VALUE is unbound, tell whether debugging is `on' or `off'.
          If VALUE is bound to `on' enable debugging, and if it is
          bound to `off' disable debugging.

    `discontiguous_warnings'
          If VALUE is unbound, tell whether warnings for discontiguous
          predicates are `on' or `off'. If VALUE is bound to `on'
          enable these warnings, and if it is bound to `off' disable
          them. The default for YAP is `off', unless we are in
          `sicstus' or `iso' mode.

    `dollar_as_lower_case'
          If `off' (default)  consider the character '$' a control
          character, if `on' consider '$' a lower case character.

    `double_quotes [ISO]'
          If VALUE is unbound, tell whether a double quoted list of
          characters token is converted to a list of atoms, `chars', to
          a list of integers, `codes', or to a single atom, `atom'. If
          VALUE is bound, set to the corresponding behavior. The
          default value is `codes'.

    `fast'
          If `on' allow fast machine code, if `off' (default) disable
          it. Only available in experimental implementations.

    `fileerrors'
          If `on' `fileerrors' is `on', if `off' (default) `fileerrors'
          is disabled.

    `gc'
          If `on' allow garbage collection (default), if `off' disable
          it.

    `gc_margin'
          Set or show the minimum free stack before starting garbage
          collection. The default depends on total stack size.

    `gc_trace'
          If `off' (default) do not show information on garbage
          collection and stack shifts, if `on' inform when a garbage
          collection or stack shift happened, if `verbose' give
          detailed information on garbage collection and stack shifts.
          Last, if `very_verbose' give detailed information on
          data-structures found during the garbage collection process,
          namely, on choice-points.

    `host_type'
          Return `configure' system information, including the
          machine-id for which Yap was compiled and Operating System
          information.

    `index'
          If `on' allow indexing (default), if `off' disable it.

    `informational_messages'
          If `on' allow printing of informational messages, such as the
          ones that are printed when consulting. If `off' disable
          printing these messages. It is `on' by default except if Yap
          is booted with the `-L' flag.

    `integer_rounding_function [ISO]'
          Read-only flag telling the rounding function used for
          integers. Takes the value `down' for the current version of
          YAP.

    `language'
          Choose whether YAP is closer to C-Prolog, `cprolog',
          iso-prolog, `iso' or SICStus Prolog, `sicstus'. The current
          default is `cprolog'. This flag affects update semantics,
          leashing mode, style_checking, handling calls to undefined
          procedures, how directives are interpreted, when to use
          dynamic, character escapes, and how files are consulted.

    `max_arity [ISO]'
          Read-only flag telling the maximum arity of a functor. Takes
          the value `unbounded' for the current version of YAP.

    `max_integer [ISO]'
          Read-only flag telling the maximum integer in the
          implementation. Depends on machine and Operating System
          architecture, and on whether YAP uses the `GMP' multiprecision
          library. If `bounded' is false, requests for `max_integer'
          will fail.

    `min_integer [ISO]'
          Read-only flag telling the minimum integer in the
          implementation. Depends on machine and Operating System
          architecture, and on whether YAP uses the `GMP'
          multiprecision library. If `bounded' is false, requests for
          `min_integer' will fail.

    `n_of_integer_keys_in_bb'
          Read or set the size of the hash table that is used for
          looking up the blackboard when the key is an integer.

    `n_of_integer_keys_in_db'
          Read or set the size of the hash table that is used for
          looking up the internal data-base when the key is an integer.

    `profiling'
          If `off' (default) do not compile profiling information for
          procedures. If `on' compile predicates so that they will
          output profiling information. Profiling data can be read
          through the `profile_data/3' built-in.

    `redefine_warnings'
          If VALUE is unbound, tell whether warnings for procedures
          defined in several different files are `on' or `off'. If
          VALUE is bound to `on' enable these warnings, and if it is
          bound to `off' disable them. The default for YAP is `off',
          unless we are in `sicstus' or `iso' mode.

    `single_var_warnings'
          If VALUE is unbound, tell whether warnings for singleton
          variables are `on' or `off'. If VALUE is bound to `on' enable
          these warnings, and if it is bound to `off' disable them. The
          default for YAP is `off', unless we are in `sicstus' or `iso'
          mode.

    `strict_iso'
          If VALUE is unbound, tell whether strict ISO compatibility
          mode is `on' or `off'. If VALUE is bound to `on' set language
          mode to `iso' and enable strict mode. If VALUE is bound to
          `off' disable strict mode, and keep the current language
          mode. The default for YAP is `off'.

          Under strict ISO prolog mode all calls to non-ISO built-ins
          generate an error. Compilation of clauses that would call
          non-ISO built-ins will also generate errors. Pre-processing
          for grammar rules is also disabled. Module expansion is still
          performed.

          Arguably, ISO Prolog does not provide all the functionality
          required from a modern Prolog system. Moreover, because most
          Prolog implementations do not fully implement the standard
          and because the standard itself gives the implementor
          latitude in a few important questions, such as the
          unification algorithm and maximum size for numbers there is
          not guarantee that programs compliant with this mode will
          work the same way in every Prolog and in every platform. We
          thus believe this mode is mostly useful when investigating
          how a program depends on a Prolog's platform specific
          features.

    `stack_dump_on_error'
          If `on' show a stack dump when Yap finds an error. The
          default is `off'.

    `syntax_errors'
          Control action to be taken after syntax errors while
          executing `read/1', `read/2', or `read_term/3':
         `dec10'
               Report the syntax error and retry reading the term.

         `fail'
               Report the syntax error and fail (default).

         `error'
               Report the syntax error and generate an error.

         `quiet'
               Just fail

    `system_options'
          This read only flag tells which options were used to compile
          Yap. Currently it informs whether the system supports
          `coroutining', `depth_limit', the `low_level_tracer',
          `or-parallelism', `rational_trees', `tabling', `threads', or
          the `wam_profiler'.

    `to_chars_mode'
          Define whether YAP should follow `quintus'-like semantics for
          the `atom_chars/1' or `number_chars/1' built-in, or whether
          it should follow the ISO standard (`iso' option).

          +

    `toplevel_hook'
          +If bound, set the argument to a goal to be executed before
          entering the top-level. If unbound show the current goal or
          `true' if none is presented. Only the first solution is
          considered and the goal is not backtracked into.

    `typein_module'
          If bound, set the current working or type-in module to the
          argument, which must be an atom. If unbound, unify the
          argument with the current working module.

    `unknown [ISO]'
          Corresponds to calling the `unknown/2' built-in.

    `update_semantics'
          Define whether YAP should follow `immediate' update
          semantics, as in C-Prolog (default), `logical' update
          semantics, as in Quintus Prolog, SICStus Prolog, or in the
          ISO standard. There is also an intermediate mode,
          `logical_assert', where dynamic procedures follow logical
          semantics but the internal data base still follows immediate
          semantics.

    `user_error'
          If the second argument is bound to a stream, set `user_error'
          to this stream. If the second argument is unbound, unify the
          argument with the current `user_error' stream.

          By default, the `user_error' stream is set to a stream
          corresponding to the Unix `stderr' stream.

          The next example shows how to use this flag:
                  ?- open( '/dev/null', append, Error,
                          [alias(mauri_tripa)] ).
               
               Error = '$stream'(3) ? ;
               
               no
                  ?- set_prolog_flag(user_error, mauri_tripa).
               
               close(mauri_tripa).
               
               yes
                  ?-
          We execute three commands. First, we open a stream in write
          mode and give it an alias, in this case `mauri_tripa'. Next,
          we set `user_error' to the stream via the alias. Note that
          after we did so prompts from the system were redirected to
          the stream `mauri_tripa'. Last, we close the stream. At this
          point, YAP automatically redirects the `user_error' alias to
          the original `stderr'.

    `user_input'
          If the second argument is bound to a stream, set `user_input'
          to this stream. If the second argument is unbound, unify the
          argument with the current `user_input' stream.

          By default, the `user_input' stream is set to a stream
          corresponding to the Unix `stdin' stream.

    `user_output'
          If the second argument is bound to a stream, set
          `user_output' to this stream. If the second argument is
          unbound, unify the argument with the current `user_output'
          stream.

          By default, the `user_output' stream is set to a stream
          corresponding to the Unix `stdout' stream.

    `version'
          Read-only flag that giving the current version of Yap.

    `write_strings'
          Writable flag telling whether the system should write lists of
          integers that are writable character codes using the list
          notation. It is `on' if enables or `off' if disabled. The
          default value for this flag is `off'.


`current_prolog_flag(?FLAG,-VALUE) [ISO]'
     Obtain the value for a YAP Prolog flag. Equivalent to calling
     `yap_flag/2' with the second argument unbound, and unifying the
     returned second argument with VALUE.

`prolog_flag(?FLAG,-OLDVALUE,+NEWVALUE)'
     Obtain the value for a YAP Prolog flag and then set it to a new
     value. Equivalent to first calling `current_prolog_flag/2' with the
     second argument OLDVALUE unbound and then calling
     `set_prolog_flag/2' with the third argument NEWVALUE.

`set_prolog_flag(+FLAG,+VALUE) [ISO]'
     Set the value for YAP Prolog flag `Flag'. Equivalent to calling
     `yap_flag/2' with both arguments bound.

`op(+P,+T,+A) [ISO]'
     Defines the operator A or the list of operators A with type T
     (which must be one of `xfx', `xfy',`yfx', `xf', `yf', `fx' or
     `fy') and precedence P (see appendix iv for a list of predefined
     operators).

     Note that if there is a preexisting operator with the same name and
     type, this operator will be discarded. Also, `','' may not be
     defined as an operator, and it is not allowed to have the same for
     an infix and a postfix operator.

`current_op(P,T,F) [ISO]'
     Defines the relation: P is a currently defined  operator of type T
     and precedence P.

`prompt(-A,+B)'
     Changes YAP input prompt from A to B.

`initialization'
     Execute the goals defined by initialization/1. Only the first
     answer is considered.

`prolog_initialization(G)'
     Add a goal to be executed on system initialization. This is
     compatible with SICStus Prolog's `initialization/1'.

`version'
     Write YAP's boot message.

`version(-MESSAGE)'
     Add a message to be written when yap boots or after aborting. It
     is not possible to remove messages.

`prolog_load_context(?KEY, ?VALUE)'
     Obtain information on what is going on in the compilation process.
     The following keys are available:

    `directory'
          Full name for the directory where YAP is currently consulting
          the file.

    `file'
          Full name for the file currently being consulted. Notice that
          included filed are ignored.

    `module'
          Current source module.

    `source'
          Full name for the file currently being read in, which may be
          consulted, reconsulted, or included.

    `stream'
          Stream currently being read in.

    `term_position'
          Stream position at the stream currently being read in.



File: yap.info,  Node: Library,  Next: Extensions,  Prev: Builtins,  Up: Top

Library Predicates
******************

Library files reside in the library_directory path (set by the `LIBDIR'
variable in the Makefile for YAP). Currently, most files in the library
are from the Edinburgh Prolog library.

* Menu:


Library, Extensions, Builtins, Top
* Apply Macros:: Apply a Predicate to a list or to sub-terms.
* Association Lists:: Binary Tree Implementation of Association Lists.
* AVL Trees:: Predicates to add and lookup balanced binary  trees.
* Heaps:: Labelled binary tree where the key of each node is less
    than or equal to the keys of its children.
* Lists:: List Manipulation
* Ordered Sets:: Ordered Set Manipulation
* Pseudo Random:: Pseudo Random Numbers
* Queues:: Queue Manipulation
* Random:: Random Numbers
* Red-Black Trees:: Predicates to add, lookup and delete in red-black binary  trees.
* RegExp:: Regular Expression Manipulation
* Splay Trees:: Splay Trees
* String I/O:: Writing To and Reading From Strings
* System:: System Utilities
* Terms:: Utilities on Terms
* Cleanup:: Call With registered Cleanup Calls
* Timeout:: Call With Timeout
* Trees:: Updatable Binary Trees
* UGraphs:: Unweighted Graphs


File: yap.info,  Node: Apply Macros,  Next: Association Lists,  Up: Library

Apply Macros
============

This library provides a set of utilities for applying a predicate to
all elements of a list or to all sub-terms of a term. They allow to
easily perform the most common do-loop constructs in Prolog. To avoid
performance degradation due to apply/2, each call creates an equivalent
Prolog program, without meta-calls, which is executed by the Prolog
engine instead. Note that if the equivalent Prolog program already
exists, it will be simply used. The library is based on code by Joachim
Schimpf.

   The following routines are available once included with the
`use_module(library(apply_macros))' command.

`maplist(+PRED, ?LISTIN, ?LISTOUT)'
     Creates LISTOUT by applying the predicate PRED to all elements of
     LISTIN.

`checklist(+PRED, +LIST)'
     Succeeds if the predicate PRED succeeds on all elements of LIST.

`selectlist(+PRED, +LISTIN, ?LISTOUT)'
     Creates LISTOUT of all list elements of LISTIN that pass a given
     test

`convlist(+PRED, +LISTIN, ?LISTOUT)'
     A combination of maplist and selectlist: creates LISTOUT by
     applying the predicate PRED to all list elements on which PRED
     succeeds

`sumlist(+PRED, +LIST, ?ACCIN, ?ACCOUT)'
     Calls PRED on all elements of List and collects a result in
     ACCUMULATOR.

`mapargs(+PRED, ?TERMIN, ?TERMOUT)'
     Creates TERMOUT by applying the predicate PRED to all
     arguments of TERMIN

`sumargs(+PRED, +TERM, ?ACCIN, ?ACCOUT)'
     Calls the predicate PRED on all arguments of TERM and collects a
     result in ACCUMULATOR

`mapnodes(+PRED, +TERMIN, ?TERMOUT)'
     Creates TERMOUT by applying the predicate PRED       to all
     sub-terms of TERMIN (depth-first and left-to-right order)

`checknodes(+PRED, +TERM)'
     Succeeds if the predicate PRED succeeds on all sub-terms of
     TERM (depth-first and left-to-right order)

`sumnodes(+PRED, +TERM, ?ACCIN, ?ACCOUT)'
     Calls the predicate PRED on all sub-terms of TERM and collect a
     result in ACCUMULATOR (depth-first and left-to-right order)

   Examples:

     %given
     plus(X,Y,Z) :- Z is X + Y.
     plus_if_pos(X,Y,Z) :- Y > 0, Z is X + Y.
     vars(X, Y, [X|Y]) :- var(X), !.
     vars(_, Y, Y).
     trans(TermIn, TermOut) :-
       (compound(TermIn) ; atom(TermIn)),
       TermIn =.. [p|Args],
       TermOut =..[q|Args],
       !.
     trans(X,X).
     
     %success
     
     maplist(plus(1), [1,2,3,4], [2,3,4,5]).
     checklist(var, [X,Y,Z]).
     selectlist(<(0), [-1,0,1], [1]).
     convlist(plus_if_pos(1), [-1,0,1], [2]).
     sumlist(plus, [1,2,3,4], 1, 11).
     mapargs(number_atom,s(1,2,3), s('1','2','3')).
     sumargs(vars, s(1,X,2,Y), [], [Y,X]).
     mapnodes(trans, p(a,p(b,a),c), q(a,q(b,a),c)).
     checknodes(\==(T), p(X,p(Y,X),Z)).
     sumnodes(vars, [c(X), p(X,Y), q(Y)], [], [Y,Y,X,X]).
     % another one
     maplist(mapargs(number_atom),[c(1),s(1,2,3)],[c('1'),s('1','2','3')]).


File: yap.info,  Node: Association Lists,  Next: AVL Trees,  Prev: Apply Macros,  Up: Library

Association Lists
=================

The following association list manipulation predicates are available
once included with the `use_module(library(assoc))' command.

`assoc_to_list(+ASSOC,?LIST)'
     Given an association list ASSOC unify LIST with a list of the form
     KEY-VAL, where the elements KEY are in ascending order.

`empty_assoc(+ASSOC)'
     Succeeds if association list ASSOC is empty.

`gen_assoc(+ASSOC,?KEY,?VALUE)'
     Given the association list ASSOC, unify KEY and VALUE with two
     associated elements. It can be used to enumerate all elements in
     the association list.

`get_assoc(+KEY,+ASSOC,?VALUE)'
     If KEY is one of the elements in the association list ASSOC,
     return the associated value.

`get_assoc(+KEY,+ASSOC,?VALUE,+NASSOC,?NVALUE)'
     If KEY is one of the elements in the association list ASSOC,
     return the associated value VALUE and a new association list
     NASSOC where KEY is associated with NVALUE.

`list_to_assoc(+LIST,?ASSOC)'
     Given a list LIST such that each element of LIST is of the form
     KEY-VAL, and all the KEYS are unique, ASSOC is the corresponding
     association list.

`map_assoc(+PRED,+ASSOC,?NEW)'
     Given the binary predicate name PRED and the association list
     ASSOC, NEW in an association list with keys in ASSOC, and such
     that if KEY-VAL is in ASSOC, and KEY-ANS is in NEW, then
     PRED(VAL,ANS) holds.

`ord_list_to_assoc(+LIST,?ASSOC)'
     Given an ordered list LIST such that each element of LIST is of
     the form KEY-VAL, and all the KEYS are unique, ASSOC is the
     corresponding association list.

`put_assoc(+KEY,+ASSOC,+VAL,+NEW)'
     The association list NEW includes and element of association KEY
     with VAL, and all elements of ASSOC that did not have key KEY.



File: yap.info,  Node: AVL Trees,  Next: Heaps,  Prev: Association Lists,  Up: Library

AVL Trees
=========

AVL trees are balanced search binary trees. They are named after their
inventors, Adelson-Velskii and Landis, and they were the first
dynamically balanced trees to be proposed. The YAP AVL tree manipulation
predicates library uses code originally written by Martin van Emdem and
published in the Logic Programming Newsletter, Autumn 1981.  A bug in
this code was fixed by Philip Vasey, in the Logic Programming
Newsletter, Summer 1982. The library currently only includes routines to
insert and lookup elements in the tree. Please try red-black trees if
you need deletion.

`avl_insert(+KEY,?VALUE,+T0,+TF)'
     Add an element with key KEY and VALUE to the AVL tree T0 creating
     a new AVL tree TF. Duplicated elements are allowed.

`avl_lookup(+KEY,-VALUE,+T)'
     Lookup an element with key KEY in the AVL tree T, returning the
     value VALUE.



File: yap.info,  Node: Heaps,  Next: Lists,  Prev: AVL Trees,  Up: Library

Heaps
=====

A heap is a labelled binary tree where the key of each node is less than
or equal to the keys of its sons.  The point of a heap is that we can
keep on adding new elements to the heap and we can keep on taking out
the minimum element.  If there are N elements total, the total time is
O(NlgN).  If you know all the elements in advance, you are better off
doing a merge-sort, but this file is for when you want to do say a
best-first search, and have no idea when you start how many elements
there will be, let alone what they are.

   The following heap manipulation routines are available once included
with the `use_module(library(heaps))' command.

`add_to_heap(+HEAP,+KEY,+DATUM,-NEWHEAP)'
     Inserts the new KEY-DATUM pair into the heap. The insertion is not
     stable, that is, if you insert several pairs with the same KEY it
     is not defined which of them will come out first, and it is
     possible for any of them to come out first depending on the
     history of the heap.

`empty_heap(?HEAP)'
     Succeeds if HEAP is an empty heap.

`get_from_heap(+HEAP,-KEY,-DATUM,-HEAP)'
     Returns the KEY-DATUM pair in OLDHEAP with the smallest KEY, and
     also a HEAP which is the OLDHEAP with that pair deleted.

`heap_size(+HEAP, -SIZE)'
     Reports the number of elements currently in the heap.

`heap_to_list(+HEAP, -LIST)'
     Returns the current set of KEY-DATUM pairs in the HEAP as a LIST,
     sorted into ascending order of KEYS.

`list_to_heap(+LIST, -HEAP)'
     Takes a list of KEY-DATUM pairs (such as keysort could be used to
     sort) and forms them into a heap.

`min_of_heap(+HEAP,  -KEY,  -DATUM)'
     Returns the Key-Datum pair at the top of the heap (which is of
     course the pair with the smallest Key), but does not remove it
     from the heap.

`min_of_heap(+HEAP,  -KEY1,  -DATUM1,'
     -KEY2,  -DATUM2) Returns the smallest (Key1) and second smallest
     (Key2) pairs in the heap, without deleting them.


File: yap.info,  Node: Lists,  Next: Ordered Sets,  Prev: Heaps,  Up: Library

List Manipulation
=================

The following list manipulation routines are available once included
with the `use_module(library(lists))' command.

`append(?PREFIX,?SUFFIX,?COMBINED)'
     True when all three arguments are lists, and the members of
     COMBINED are the members of PREFIX followed by the members of
     SUFFIX.  It may be used to form COMBINED from a given PREFIX,
     SUFFIX or to take a given COMBINED apart.

`delete(+LIST, ?ELEMENT, ?RESIDUE)'
     True when LIST is a list, in which ELEMENT may or may not occur,
     and RESIDUE is a copy of LIST with all elements identical to
     ELEMENT deleted.

`flatten(+LIST, ?FLATTENEDLIST)'
     Flatten a list of lists LIST into a single list FLATTENEDLIST.

          ?- flatten([[1],[2,3],[4,[5,6],7,8]],L).
          
          L = [1,2,3,4,5,6,7,8] ? ;
          
          no

`is_list(+LIST)'
     True when LIST is a proper list. That is, LIST is bound to the
     empty list (nil) or a term with functor '.' and arity 2.

`last(+LIST,?LAST)'
     True when LIST is a list and LAST is identical to its last element.

`list_concat(+LISTS,?LIST)'
     True when LISTS is a list of lists and LIST is the concatenation
     of LISTS.

`member(?ELEMENT, ?SET)'
     True when SET is a list, and ELEMENT occurs in it.  It may be used
     to test for an element or to enumerate all the elements by
     backtracking.

`memberchk(+ELEMENT, +SET)'
     As `member/2', but may only be used to test whether a known
     ELEMENT occurs in a known Set.  In return for this limited use, it
     is more efficient when it is applicable.

`nth0(?N, ?LIST, ?ELEM)'
     True when ELEM is the Nth member of LIST, counting the first as
     element 0.  (That is, throw away the first N elements and unify
     ELEM with the next.)  It can only be used to select a particular
     element given the list and index.  For that task it is more
     efficient than `member/2'

`nth(?N, ?LIST, ?ELEM)'
     The same as `nth0/3', except that it counts from 1, that is
     `nth(1, [H|_], H)'.

`nth0(?N, ?LIST, ?ELEM, ?REST)'
     Unifies ELEM with the Nth element of LIST, counting from 0, and
     REST with the other elements.  It can be used to select the Nth
     element of LIST (yielding ELEM and REST), or to insert ELEM before
     the Nth (counting from 1) element of REST, when it yields LIST,
     e.g. `nth0(2, List, c, [a,b,d,e])' unifies List with
     `[a,b,c,d,e]'.  `nth/4' is the same except that it counts from 1.
     `nth0/4' can be used to insert ELEM after the Nth element of REST.

`nth(?N, ?LIST, ?ELEM, ?REST)'
     Unifies ELEM with the Nth element of LIST, counting from 1, and
     REST with the other elements.  It can be used to select the Nth
     element of LIST (yielding ELEM and REST), or to insert ELEM before
     the Nth (counting from 1) element of REST, when it yields LIST,
     e.g. `nth(1, List, c, [a,b,d,e])' unifies List with `[a,b,c,d,e]'.
     `nth/4' can be used to insert ELEM after the Nth element of REST.

`permutation(+LIST,?PERM)'
     True when LIST and PERM are permutations of each other.

`remove_duplicates(+LIST, ?PRUNED)'
     Removes duplicated elements from LIST.  Beware: if the LIST has
     non-ground elements, the result may surprise you.

`reverse(+LIST, ?REVERSED)'
     True when LIST and REVERSED are lists with the same elements but
     in opposite orders.

`same_length(?LIST1, ?LIST2)'
     True when LIST1 and LIST2 are both lists and have the same number
     of elements.  No relation between the values of their elements is
     implied.  Modes `same_length(-,+)' and `same_length(+,-)' generate
     either list given the other; mode `same_length(-,-)' generates two
     lists of the same length, in which case the arguments will be
     bound to lists of length 0, 1, 2, ...

`select(?ELEMENT, ?SET, ?RESIDUE)'
     True when SET is a list, ELEMENT occurs in SET, and RESIDUE is
     everything in SET except ELEMENT (things stay in the same order).

`sublist(?SUBLIST, ?LIST)'
     True when both `append(_,Sublist,S)' and `append(S,_,List)' hold.

`suffix(?SUFFIX, ?LIST)'
     Holds when `append(_,Suffix,List)' holds.

`sum_list(?NUMBERS, ?TOTAL)'
     True when NUMBERS is a list of integers, and TOTAL is their sum.

`sumlist(?NUMBERS, ?TOTAL)'
     True when NUMBERS is a list of integers, and TOTAL is their sum.
     The same as `sum_list/2', please do use `sum_list/2' instead.



File: yap.info,  Node: Ordered Sets,  Next: Pseudo Random,  Prev: Lists,  Up: Library

Ordered Sets
============

The following ordered set manipulation routines are available once
included with the `use_module(library(ordsets))' command.  An ordered
set is represented by a list having unique and ordered elements. Output
arguments are guaranteed to be ordered sets, if the relevant inputs
are. This is a slightly patched version of Richard O'Keefe's original
library.

`list_to_ord_set(+LIST, ?SET)'
     Holds when SET is the ordered representation of the set
     represented by the unordered representation LIST.

`merge(+LIST1, +LIST2, -MERGED)'
     Holds when MERGED is the stable merge of the two given lists.

     Notice that `merge/3' will not remove duplicates, so merging
     ordered sets will not necessarily result in an ordered set. Use
     `ord_union/3' instead.

`ord_add_element(+SET1, +ELEMENT, ?SET2)'
     Inserting ELEMENT in SET1 returns SET2.  It should give exactly
     the same result as `merge(Set1, [Element], Set2)', but a bit
     faster, and certainly more clearly. The same as `ord_insert/3'.

`ord_del_element(+SET1, +ELEMENT, ?SET2)'
     Removing ELEMENT from SET1 returns SET2.

`ord_disjoint(+SET1, +SET2)'
     Holds when the two ordered sets have no element in common.

`ord_member(+ELEMENT, +SET)'
     Holds when ELEMENT is a member of SET.

`ord_insert(+SET1, +ELEMENT, ?SET2)'
     Inserting ELEMENT in SET1 returns SET2.  It should give exactly
     the same result as `merge(Set1, [Element], Set2)', but a bit
     faster, and certainly more clearly. The same as
     `ord_add_element/3'.

`ord_intersect(+SET1, +SET2)'
     Holds when the two ordered sets have at least one element in
     common.

`ord_intersection(+SET1, +SET2, ?INTERSECTION)'
     Holds when Intersection is the ordered representation of SET1 and
     SET2.

`ord_seteq(+SET1, +SET2)'
     Holds when the two arguments represent the same set.

`ord_setproduct(+SET1, +SET2, -SET)'
     If Set1 and Set2 are ordered sets, Product will be an ordered set
     of x1-x2 pairs.

`ord_subset(+SET1, +SET2)'
     Holds when every element of the ordered set SET1 appears in the
     ordered set SET2.

`ord_subtract(+SET1, +SET2, ?DIFFERENCE)'
     Holds when DIFFERENCE contains all and only the elements of SET1
     which are not also in SET2.

`ord_symdiff(+SET1, +SET2, ?DIFFERENCE)'
     Holds when DIFFERENCE is the symmetric difference of SET1 and SET2.

`ord_union(+SETS, ?UNION)'
     Holds when UNION is the union of the lists SETS.

`ord_union(+SET1, +SET2, ?UNION)'
     Holds when UNION is the union of SET1 and SET2.

`ord_union(+SET1, +SET2, ?UNION, ?DIFF)'
     Holds when UNION is the union of SET1 and SET2 and DIFF is the
     difference.



File: yap.info,  Node: Pseudo Random,  Next: Queues,  Prev: Ordered Sets,  Up: Library

Pseudo Random Number Integer Generator
======================================

The following routines produce random non-negative integers in the range
0 .. 2^(w-1) -1, where w is the word size available for integers, e.g.,
32 for Intel machines and 64 for Alpha machines. Note that the numbers
generated by this random number generator are repeatable. This generator
was originally written by Allen Van Gelder and is based on Knuth Vol 2.

`rannum(-I)'
     Produces a random non-negative integer I whose low bits are not
     all that random, so it should be scaled to a smaller range in
     general.  The integer I is in the range 0 .. 2^(w-1) - 1. You can
     use:
          rannum(X) :- yap_flag(max_integer,MI), rannum(R), X is R/MI.
     to obtain a floating point number uniformly distributed between 0
     and 1.

`ranstart'
     Initialize the random number generator using a built-in seed. The
     `ranstart/0' built-in is always called by the system when loading
     the package.

`ranstart(+SEED)'
     Initialize the random number generator with user-defined SEED. The
     same SEED always produces the same sequence of numbers.

`ranunif(+RANGE,-I)'
     `ranunif/2' produces a uniformly distributed non-negative random
     integer I over a caller-specified range R.  If range is R, the
     result is in 0 .. R-1.



File: yap.info,  Node: Queues,  Next: Random,  Prev: Pseudo Random,  Up: Library

Queues
======

The following queue manipulation routines are available once included
with the `use_module(library(queues))' command. Queues are implemented
with difference lists.

`make_queue(+QUEUE)'
     Creates a new empty queue. It should only be used to create a new
     queue.

`join_queue(+ELEMENT, +OLDQUEUE, -NEWQUEUE)'
     Adds the new element at the end of the queue.

`list_join_queue(+LIST, +OLDQUEUE, -NEWQUEUE)'
     Ads the new elements at the end of the queue.

`jump_queue(+ELEMENT, +OLDQUEUE, -NEWQUEUE)'
     Adds the new element at the front of the list.

`list_jump_queue(+LIST, +OLDQUEUE, +NEWQUEUE)'
     Adds all the elements of LIST at the front of the queue.

`head_queue(+QUEUE, ?HEAD)'
     Unifies Head with the first element of the queue.

`serve_queue(+OLDQUEUE, +HEAD, -NEWQUEUE)'
     Removes the first element of the queue for service.

`empty_queue(+QUEUE)'
     Tests whether the queue is empty.

`length_queue(+QUEUE, -LENGTH)'
     Counts the number of elements currently in the queue.

`list_to_queue(+LIST, -QUEUE)'
     Creates a new queue with the same elements as LIST.

`queue_to_list(+QUEUE, -LIST)'
     Creates a new list with the same elements as QUEUE.



File: yap.info,  Node: Random,  Next: Red-Black Trees,  Prev: Queues,  Up: Library

Random Number Generator
=======================

The following random number operations are included with the
`use_module(library(random))' command. Since Yap-4.3.19 Yap uses the
O'Keefe public-domain algorithm, based on the "Applied Statistics"
algorithm AS183.

`getrand(-KEY)'
     Unify KEY with a term of the form `rand(X,Y,Z)' describing the
     current state of the random number generator.

`random(-NUMBER)'
     Unify NUMBER with a floating-point number in the range `[0...1)'.

`random(+LOW, +HIGH, -NUMBER)'
     Unify NUMBER with a number in the range `[LOW...HIGH)'. If both
     LOW and HIGH are integers then NUMBER will also be an integer,
     otherwise NUMBER will be a floating-point number.

`randseq(+LENGTH, +MAX, -NUMBERS)'
     Unify NUMBERS with a list of LENGTH unique random integers in the
     range `[1 ...MAX)'.

`randset(+LENGTH, +MAX, -NUMBERS)'
     Unify NUMBERS with an ordered list of LENGTH unique random
     integers in the range `[1 ...MAX)'.

`setrand(+KEY)'
     Use a term of the form `rand(X,Y,Z)' to set a new state for the
     random number generator. The integer `X' must be in the range
     `[1...30269)', the integer `Y' must be in the range `[1...30307)',
     and the integer `Z' must be in the range `[1...30323)'.



File: yap.info,  Node: Red-Black Trees,  Next: RegExp,  Prev: Random,  Up: Library

Red-Black Trees
===============

Red-Black trees are balanced search binary trees. They are named because
nodes can be classified as either red or black. The code we include is
based on "Introduction to Algorithms", second edition, by Cormen,
Leiserson, Rivest and Stein.  The library includes routines to insert,
lookup and delete elements in the tree.

`insert(+T0,+KEY,?VALUE,+TF)'
     Add an element with key KEY and VALUE to the tree T0 creating a
     new AVL tree TF. Duplicated elements are not allowed.

`lookup(+KEY,-VALUE,+T)'
     Lookup an element with key KEY in the AVL tree T, returning the
     value VALUE.

`new(?T)'
     Create a new tree.

`delete(+T,+KEY,-TN)'
     Delete element with key KEY from the tree T, returning a new tree
     TN.



File: yap.info,  Node: RegExp,  Next: Splay Trees,  Prev: Red-Black Trees,  Up: Library

Regular Expressions
===================

This library includes routines to determine whether a regular expression
matches part or all of a string. The routines can also return which
parts parts of the string matched the expression or subexpressions of
it. This library relies on Henry Spencer's `C'-package and is only
available in operating systems that support dynamic loading. The
`C'-code has been obtained from the sources of FreeBSD-4.0 and is
protected by copyright from Henry Spencer and from the Regents of the
University of California (see the file library/regex/COPYRIGHT for
further details).

   Much of the description of regular expressions below is copied
verbatim from Henry Spencer's manual page.

   A regular expression is zero or more branches, separated by "|".  It
matches anything that matches one of the branches.

   A branch is zero or more pieces, concatenated.  It matches a match
for the first, followed by a match for the second, etc.

   A piece is an atom possibly followed by "*", "+", or "?".  An atom
followed by "*" matches a sequence of 0 or more matches of the atom.
An atom followed by "+" matches a sequence of 1 or more matches of the
atom.  An atom followed by "?" matches a match of the atom, or the null
string.

   An atom is a regular expression in parentheses (matching a match for
the regular expression), a range (see below), "."  (matching any single
character), "^" (matching the null string at the beginning of the input
string), "$" (matching the null string at the end of the input string),
a "\" followed by a single character (matching that character), or a
single character with no other significance (matching that character).

   A range is a sequence of characters enclosed in "[]".  It normally
matches any single character from the sequence.  If the sequence begins
with "^", it matches any single character not from the rest of the
sequence.  If two characters in the sequence are separated by "-", this
is shorthand for the full list of ASCII characters between them (e.g.
"[0-9]" matches any decimal digit).  To include a literal "]" in the
sequence, make it the first character (following a possible "^").  To
include a literal "-", make it the first or last character.

`regexp(+REGEXP,+STRING,+OPTS)'
     Match regular expression REGEXP to input string STRING according
     to options OPTS. The options may be:
        * `nocase': Causes upper-case characters  in  STRING to
          be treated  as  lower case during the matching process.

`regexp(+REGEXP,+STRING,+OPTS,SUBMATCHVARS)'
     Match regular expression REGEXP to input string STRING according
     to options OPTS. The variable SUBMATCHVARS should be originally a
     list of unbound variables all will contain a sequence of matches,
     that is, the head of SUBMATCHVARS will contain the characters in
     STRING that matched the leftmost parenthesized subexpression
     within REGEXP, the next head of list will contain the characters
     that matched the next parenthesized subexpression to the right in
     REGEXP, and so on.

     The options may be:
        * `nocase': Causes upper-case characters  in  STRING to
          be treated  as  lower case during the matching process.

        * `indices': Changes what  is  stored  in SUBMATCHVARS. Instead
          of storing the matching characters from STRING, each
          variable will contain a term of the form IO-IF giving the
          indices in STRING of the first and last characters  in the
          matching range of characters.


     In general there may be more than one way to match a regular
     expression to an input string.  For example,  consider the command
            regexp("(a*)b*","aabaaabb", [], [X,Y])
     Considering only the rules given so far, X and Y could end up with
     the values `"aabb"' and `"aa"', `"aaab"' and `"aaa"', `"ab"' and
     `"a"', or any of several other combinations.  To resolve this
     potential ambiguity regexp chooses among alternatives using the
     rule "first then longest".  In other words, it considers the
     possible matches in order working from left to right across the
     input string and the pattern, and it attempts to match longer
     pieces of the input string before shorter ones.  More
     specifically, the following rules apply in decreasing order of
     priority:

       1. If a regular expression could match  two  different parts of
          an input string then it will match the one that begins
          earliest.

       2. If a regular expression contains "|"  operators  then the
          leftmost matching sub-expression is chosen.

       3. In *, +, and ? constructs, longer matches are chosen in
          preference to shorter ones.

       4. In sequences of expression  components  the  components are
          considered from left to right.

     In the example from above, `"(a*)b*"' matches `"aab"': the
     `"(a*)"' portion of the pattern is matched first and it consumes
     the leading `"aa"'; then the `"b*"' portion of the pattern
     consumes the next `"b"'.  Or, consider the following example:
            regexp("(ab|a)(b*)c",  "abc", [], [X,Y,Z])

     After this command X will be `"abc"', Y will be `"ab"', and Z will
     be an empty string.  Rule 4 specifies that `"(ab|a)"' gets first
     shot at the input string and Rule 2 specifies that the `"ab"'
     sub-expression is checked before the `"a"' sub-expression.  Thus
     the `"b"' has already been claimed before the `"(b*)"' component
     is checked and `(b*)' must match an empty string.



File: yap.info,  Node: Splay Trees,  Next: String I/O,  Prev: RegExp,  Up: Library

Splay Trees
===========

Splay trees are explained in the paper "Self-adjusting Binary Search
Trees", by D.D. Sleator and R.E. Tarjan, JACM, vol. 32, No.3, July 1985,
p. 668. They are designed to support fast insertions, deletions and
removals in binary search trees without the complexity of traditional
balanced trees. The key idea is to allow the tree to become unbalanced.
To make up for this, whenever we find a node, we move it up to the top.
We use code by Vijay Saraswat originally posted to the Prolog
mailing-list.

`splay_access(-RETURN,+KEY,?VAL,+TREE,-NEWTREE)'
     If item KEY is in tree TREE, return its VAL and unify RETURN with
     `true'. Otherwise unify RETURN with `null'. The variable NEWTREE
     unifies with the new tree.

`splay_delete(+KEY,?VAL,+TREE,-NEWTREE)'
     Delete item KEY from tree TREE, assuming that it is present
     already. The variable VAL unifies with a value for key KEY, and
     the variable NEWTREE unifies with the new tree. The predicate will
     fail if KEY is not present.

`splay_init(-NEWTREE)'
     Initialize a new splay tree.

`splay_insert(+KEY,?VAL,+TREE,-NEWTREE)'
     Insert item KEY in tree TREE, assuming that it is not there
     already. The variable VAL unifies with a value for key KEY, and
     the variable NEWTREE unifies with the new tree. In our
     implementation, KEY is not inserted if it is already there: rather
     it is unified with the item already in the tree.

`splay_join(+LEFTTREE,+RIGHTREE,-NEWTREE)'
     Combine trees LEFTTREE and RIGHTREE into a single treeNEWTREE
     containing all items from both trees. This operation assumes that
     all items in LEFTTREE are less than all those in RIGHTREE and
     destroys both LEFTTREE and RIGHTREE.

`splay_split(+KEY,?VAL,+TREE,-LEFTTREE,-RIGHTTREE)'
     Construct and return two trees LEFTTREE and RIGHTTREE, where
     LEFTTREE contains all items in TREE less than KEY, and RIGHTTREE
     contains all items in TREE greater than KEY. This operations
     destroys TREE.



File: yap.info,  Node: String I/O,  Next: System,  Prev: Splay Trees,  Up: Library

Reading From and Writing To Strings
===================================

From Version 4.3.2 onwards YAP implements SICStus Prolog compatible
String I/O. The library allows users to read from and write to a memory
buffer as if it was a file. The memory buffer is built from or converted
to a string of character codes by the routines in library. Therefore, if
one wants to read from a string the string must be fully instantiated
before the library builtin opens the string for reading. These commands
are available through the `use_module(library(charsio))' command.

`format_to_chars(+FORM, +ARGS, -RESULT)'
     Execute the built-in procedure `format/2' with form FORM and
     arguments ARGS outputting the result to the string of character
     codes RESULT.

`format_to_chars(+FORM, +ARGS, -RESULT0, -RESULT)'
     Execute the built-in procedure `format/2' with form FORM and
     arguments ARGS outputting the result to the difference list of
     character codes RESULT-RESULT0.

`write_to_chars(+TERM, -RESULT)'
     Execute the built-in procedure `write/1' with argument TERM
     outputting the result to the string of character codes RESULT.

`write_to_chars(+TERM, -RESULT0, -RESULT)'
     Execute the built-in procedure `write/1' with argument TERM
     outputting the result to the difference list of character codes
     RESULT-RESULT0.

`atom_to_chars(+ATOM, -RESULT)'
     Convert the atom ATOM to the string of character codes RESULT.

`atom_to_chars(+ATOM, -RESULT0, -RESULT)'
     Convert the atom ATOM to the difference list of character codes
     RESULT-RESULT0.

`number_to_chars(+NUMBER, -RESULT)'
     Convert the number NUMBER to the string of character codes RESULT.

`number_to_chars(+NUMBER, -RESULT0, -RESULT)'
     Convert the atom NUMBER to the difference list of character codes
     RESULT-RESULT0.

`read_from_chars(+CHARS, -TERM)'
     Parse the list of character codes CHARS and return the result in
     the term TERM. The character codes to be read must terminate with
     a dot character such that either (i) the dot character is followed
     by blank characters; or (ii) the dot character is the last
     character in the string.

`open_chars_stream(+CHARS, -STREAM)'
     Open the list of character codes CHARS as a stream STREAM.

`with_output_to_chars(?GOAL, -CHARS)'
     Execute goal GOAL such that its standard output will be sent to a
     memory buffer. After successful execution the contents of the
     memory buffer will be converted to the list of character codes
     CHARS.

`with_output_to_chars(?GOAL, ?CHARS0, -CHARS)'
     Execute goal GOAL such that its standard output will be sent to a
     memory buffer. After successful execution the contents of the
     memory buffer will be converted to the difference list of
     character codes CHARS-CHARS0.

`with_output_to_chars(?GOAL, -STREAM, ?CHARS0, -CHARS)'
     Execute goal GOAL such that its standard output will be sent to a
     memory buffer. After successful execution the contents of the
     memory buffer will be converted to the difference list of
     character codes CHARS-CHARS0 and STREAM receives the stream
     corresponding to the memory buffer.


   The implementation of the character IO operations relies on three YAP
builtins:
`charsio:open_mem_read_stream(+STRING, -STREAM)'
     Store a string in a memory buffer and output a stream that reads
     from this memory buffer.

`charsio:open_mem_write_stream(-STREAM)'
     Create a new memory buffer and output a stream that writes to  it.

`charsio:peek_mem_write_stream(-STREAM, L0, L)'
     Convert the memory buffer associated with stream STREAM to the
     difference list of character codes L-L0.


These builtins are initialized to belong to the module `charsio' in
`init.yap'. Novel procedures for manipulating strings by explicitly
importing these built-ins.

   YAP does not currently support opening a `charsio' stream in
`append' mode, or seeking in such a stream.


File: yap.info,  Node: System,  Next: Terms,  Prev: String I/O,  Up: Library

Calling The Operating System from YAP
=====================================

Yap now provides a library of system utilities compatible with the
SICStus Prolog system library. This library extends and to some point
replaces the functionality of Operating System access routines. The
library includes Unix/Linux and Win32 `C' code. They are available
through the `use_module(library(system))' command.

`datime(datime(-YEAR, -MONTH, -DAYOFTHEMONTH,'
     -HOUR, -MINUTE, -SECOND) The `datime/1' procedure returns the
     current date and time, with information on YEAR, MONTH,
     DAYOFTHEMONTH, HOUR, MINUTE, and SECOND. The HOUR is returned on
     local time. This function uses the WIN32 `GetLocalTime' function
     or the Unix `localtime' function.

             ?- datime(X).
          
          X = datime(2001,5,28,15,29,46) ?

`delete_file(+FILE)'
     The `delete_file/1' procedure removes file FILE. If FILE is a
     directory, remove the directory _and all its subdirectories_.

             ?- delete_file(x).

`delete_file(+FILE,+OPTS)'
     The `delete_file/2' procedure removes file FILE according to
     options OPTS. These options are `directory' if one should remove
     directories, `recursive' if one should remove directories
     recursively, and `ignore' if errors are not to be reported.

     This example is equivalent to using the `delete_file/1' predicate:
             ?- delete_file(x, [recursive]).

`directory_files(+DIR,+LIST)'
     Given a directory DIR,  `directory_files/2' procedures a listing
     of all files and directories in the directory:
              ?- directory_files('.',L), writeq(L).
          ['Makefile.~1~','sys.so','Makefile','sys.o',x,..,'.']
     The predicates uses the `dirent' family of routines in Unix
     environments, and `findfirst' in WIN32.

`file_exists(+FILE)'
     The atom FILE corresponds to an existing file.

`file_exists(+FILE,+PERMISSIONS)'
     The atom FILE corresponds to an existing file with permissions
     compatible with PERMISSIONS. YAP currently only accepts for
     permissions to be described as a number. The actual meaning of this
     number is Operating System dependent.

`file_property(+FILE,?PROPERTY)'
     The atom FILE corresponds to an existing file, and PROPERTY will
     be unified with a property of this file. The properties are of the
     form `type(TYPE)', which gives whether the file is a regular file,
     a directory, a fifo file, or of unknown type; `size(SIZE)', with
     gives the size for a file, and `mod_time(TIME)', which gives the
     last time a file was modified according to some Operating System
     dependent timestamp; `mode(MODE)', gives the permission flags for
     the file, and `linkto(FILENAME)', gives the file pointed to by a
     symbolic link. Properties can be obtained through backtracking:

             ?- file_property('Makefile',P).
          
          P = type(regular) ? ;
          
          P = size(2375) ? ;
          
          P = mod_time(990826911) ? ;
          
          no

`make_directory(+DIR)'
     Create a directory DIR. The name of the directory must be an atom.

`rename_file(+OLDFILE,+NEWFILE)'
     Create file OLDFILE to NEWFILE. This predicate uses the `C'
     builtin function `rename'.

`environ(?ENVVAR,+ENVVALUE)'
     Unify environment variable ENVVAR with its value ENVVALUE, if
     there is one. This predicate is backtrackable in Unix systems, but
     not currently in Win32 configurations.

             ?- environ('HOME',X).
          
          X = 'C:\\cygwin\\home\\administrator' ?

`host_id(-ID)'
     Unify ID with an identifier of the current host. Yap uses the
     `hostid' function when available,

`host_name(-NAME)'
     Unify NAME with a name for the current host. Yap uses the
     `hostname' function in Unix systems when available, and the
     `GetComputerName' function in WIN32 systems.

`kill(ID,+SIGNAL)'
     Send signal SIGNAL to process ID. In Unix this predicate is a
     direct interface to `kill' so one can send signals to groups of
     processes. In WIN32 the predicate is an interface to
     `TerminateProcess', so it kills ID indepent of SIGNAL.

`mktemp(SPEC,-FILE)'
     Direct interface to `mktemp': given a SPEC, that is a file name
     with six X to it, create a file name FILE. Use `tmpnam/1' instead.

`pid(-ID)'
     Unify ID with the process identifier for the current process. An
     interface to the getpid function.

`tmpnam(-FILE)'
     Interface with TMPNAM: create an unique file and unify its name
     with FILE.

`'
     exec(+COMMAND,[+INPUTSTREAM,+OUTPUTSTREAM,+ERRORSTREAM], -STATUS)
     Execute command COMMAND with its streams connected to INPUTSTREAM,
     OUTPUTSTREAM, and ERRORSTREAM. The result for the command is
     returned in STATUS. The command is executed by the default shell
     `bin/sh -c' in Unix.

     The following example demonstrates the use of `exec/3' to send a
     command and process its output:

          exec(ls,[std,pipe(S),null],P),repeat, get0(S,C), (C = -1, close(S) ! ; put(C)).

     The streams may be one of standard stream, `std', null stream,
     `null', or `pipe(S)', where S is a pipe stream. Note that it is up
     to the user to close the pipe.

`working_directory(-CURDIR,?NEXTDIR)'
     Fetch the current directory at CURDIR. If NEXTDIR is bound to an
     atom, make its value the current working directory.

`popen(+COMMAND, +TYPE, -STREAM)'
     Interface to the popen function. It opens a process by creating a
     pipe, forking and invoking COMMAND on the current shell. Since a
     pipe is by definition unidirectional the TYPE argument may be
     `read' or `write', not both. The stream should be closed using
     `close/1', there is no need for a special `pclose' command.

     The following example demonstrates the use of `popen/3' to process
     the output of a command, as `exec/3' would do:

             ?- popen(ls,read,X),repeat, get0(X,C), (C = -1, ! ; put(C)).
          
          X = 'C:\\cygwin\\home\\administrator' ?

     The WIN32 implementation of `popen/3' relies on `exec/3'.

`shell'
     Start a new shell and leave Yap in background until the shell
     completes. Yap uses the shell given by the environment variable
     `SHELL'. In WIN32 environment YAP will use `COMSPEC' if `SHELL' is
     undefined.

`shell(+COMMAND)'
     Execute command COMMAND under a new shell. Yap will be in
     background until the command completes. In Unix environments Yap
     uses the shell given by the environment variable `SHELL' with the
     option `" -c "'. In WIN32 environment YAP will use `COMSPEC' if
     `SHELL' is undefined, in this case with the option `" /c "'.

`shell(+COMMAND,-STATUS)'
     Execute command COMMAND under a new shell and unify STATUS with
     the exit for the command. Yap will be in background until the
     command completes. In Unix environments Yap uses the shell given
     by the environment variable `SHELL' with the option `" -c "'. In
     WIN32 environment YAP will use `COMSPEC' if `SHELL' is undefined,
     in this case with the option `" /c "'.

`sleep(+TIME)'
     Block the current process for TIME seconds. The number of seconds
     must be a positive number, and it may an integer or a float. The
     Unix implementation uses `usleep' if the number of seconds is
     below one, and `sleep' if it is over a second. The WIN32
     implementation uses `Sleep' for both cases.

`system'
     Start a new default shell and leave Yap in background until the
     shell completes. Yap uses `/bin/sh' in Unix systems and `COMSPEC'
     in WIN32.

`system(+COMMAND,-RES)'
     Interface to `system': execute command COMMAND and unify RES with
     the result.

`wait(+PID,-STATUS)'
     Wait until process PID terminates, and return its exits STATUS.



File: yap.info,  Node: Terms,  Next: Cleanup,  Prev: System,  Up: Library

Utilities On Terms
==================

The next routines provide a set of commonly used utilities to manipulate
terms. Most of these utilities have been implemented in `C' for
efficiency. They are available through the `use_module(library(terms))'
command.

`acyclic_term(?TERM)'
     Succeed if the argument TERM is an acyclic term.

`cyclic_term(?TERM)'
     Succeed if the argument TERM is a cyclic term.

`term_hash(+TERM, ?HASH)'
     If TERM is ground unify HASH with a positive integer calculated
     from the structure of the term. Otherwise the argument HASH is
     left unbound. The range of the positive integer is from `0' to,
     but not including, `33554432'.

`term_hash(+TERM, +DEPTH, +RANGE, ?HASH)'
     Unify HASH with a positive integer calculated from the structure
     of the term.  The range of the positive integer is from `0' to, but
     not including, RANGE. If DEPTH is `-1' the whole term is
     considered. Otherwise, the term is considered only up to depth
     `1', where the constants and the principal functor have depth `1',
     and an argument of a term with depth I has depth I+1.

`term_variables(?TERM, -VARIABLES)'
     Unify VARIABLES with a list of all variables in term TERM.

`variant(?TERM1, ?TERM2)'
     Succeed if TERM1 and TERM2 are variant terms.

`subsumes(?TERM1, ?TERM2)'
     Succeed if TERM1 subsumes TERM2.  Variables in term TERM1 are
     bound so that the two terms become equal.

`subsumes_chk(?TERM1, ?TERM2)'
     Succeed if TERM1 subsumes TERM2 but does not bind any variable in
     TERM1.

`variable_in_term(?TERM,?VAR)'
     Succeed if the second argument VAR is a variable and occurs in
     term TERM.



File: yap.info,  Node: Cleanup,  Next: Timeout,  Prev: Terms,  Up: Library

Call With registered Cleanup Calls
==================================

call_cleanup/1 and call_cleanup/2 allow predicates to register code for
execution after the call is finished. Predicates can be declared to be
fragile to ensure that call_cleanup is called for any Goal which needs
it. This library is loaded with the `use_module(library(cleanup))'
command.

`:- fragile P,....,PN'
     Declares the predicate P=[module:]name/arity as a fragile
     predicate, module is optional, default is the current
     typein_module. Whenever such a fragile predicate is used in a query
     it will be called through call_cleanup/1.
          :- fragile foo/1,bar:baz/2.

`call_cleanup(+GOAL)'
     Execute goal GOAL within a cleanup-context. Called predicates
     might register cleanup Goals which are called right after the end
     of the call to GOAL. Cuts and exceptions inside Goal do not
     prevent the execution of the cleanup calls. call_cleanup might be
     nested.

`call_cleanup(+GOAL, +CLEANUPGOAL)'
     This is similar to call_cleanup/1 with an additional CLEANUPGOAL
     which gets called after GOAL is finished.

`on_cleanup(+CLEANUPGOAL)'
     Any Predicate might registers a CLEANUPGOAL. The CLEANUPGOAL is
     put onto the current cleanup context. All such CleanUpGoals are
     executed in reverse order of their registration when the
     surrounding cleanup-context ends. This call will throw an exception
     if a predicate tries to register a CLEANUPGOAL outside of any
     cleanup-context.

`cleanup_all'
     Calls all pending CleanUpGoals and resets the cleanup-system to an
     initial state. Should only be used as one of the last calls in the
     main program.


   There are some private predicates which could be used in special
cases, such as manually setting up cleanup-contexts and registering
CleanUpGoals for other than the current cleanup-context.  Read the
Source Luke.


File: yap.info,  Node: Timeout,  Next: Trees,  Prev: Cleanup,  Up: Library

Calls With Timeout
==================

The time_out/3 command relies on the alarm/3 built-in to implement a
call with a maximum time of execution. The command is available with
the `use_module(library(timeout))' command.

`time_out(+GOAL, +TIMEOUT, -RESULT)'
     Execute goal GOAL with time limited TIMEOUT, where TIMEOUT is
     measured in milliseconds. If the goal succeeds, unify RESULT with
     success. If the timer expires before the goal terminates, unify
     RESULT with timeout.

     This command is implemented by activating an alarm at procedure
     entry. If the timer expires before the goal completes, the alarm
     will through an exception TIMEOUT.

     One should note that `time_out/3' is not reentrant, that is, a goal
     called from `time_out' should never itself call time_out.
     Moreover, `time_out/3' will deactivate any previous alarms set by
     `alarm/3' and vice-versa, hence only one of these calls should be
     used in a program.

     Last, even though the timer is set in milliseconds, the current
     implementation relies on alarm/3, and therefore can only offer
     precision on the scale of seconds.



File: yap.info,  Node: Trees,  Next: UGraphs,  Prev: Timeout,  Up: Library

Updatable Binary Trees
======================

The following queue manipulation routines are available once included
with the `use_module(library(trees))' command.

`get_label(+INDEX, +TREE, ?LABEL)'
     Treats the tree as an array of N elements and returns the INDEX-th.

`list_to_tree(+LIST, -TREE)'
     Takes a given LIST of N elements and constructs a binary TREE.

`map_tree(+PRED, +OLDTREE, -NEWTREE)'
     Holds when OLDTREE and NEWTREE are binary trees of the same shape
     and `Pred(Old,New)' is true for corresponding elements of the two
     trees.

`put_label(+INDEX, +OLDTREE, +LABEL, -NEWTREE)'
     constructs a new tree the same shape as the old which moreover has
     the same elements except that the INDEX-th one is LABEL.

`tree_size(+TREE, -SIZE)'
     Calculates the number of elements in the TREE.

`tree_to_list(+TREE, -LIST)'
     Is the converse operation to list_to_tree.



File: yap.info,  Node: UGraphs,  Prev: Trees,  Up: Library

Unweighted Graphs
=================

The following graph manipulation routines are based from code originally
written by Richard O'Keefe. The code was then extended to be compatible
with the SICStus Prolog ugraphs library. The routines assume directed
graphs, undirected graphs may be implemented by using two edges. Graphs
are represented in one of two ways:

   * The P-representation of a graph is a list of (from-to) vertex
     pairs, where the pairs can be in any old order.  This form is
     convenient for input/output.

   * The S-representation of a graph is a list of (vertex-neighbors)
     pairs, where the pairs are in standard order (as produced by
     keysort) and the neighbors of each vertex are also in standard
     order (as produced by sort).  This form is convenient for many
     calculations.

   These builtins are available once included with the
`use_module(library(ugraphs))' command.

`vertices_edges_to_ugraph(+VERTICES, +EDGES, -GRAPH)'
     Given a graph with a set of vertices VERTICES and a set of edges
     EDGES, GRAPH must unify with the corresponding s-representation.
     Note that the vertices without edges will appear in VERTICES but
     not in EDGES. Moreover, it is sufficient for a vertice to appear
     in EDGES.
          ?- vertices_edges_to_ugraph([],[1-3,2-4,4-5,1-5],L).
          
          L = [1-[3,5],2-[4],3-[],4-[5],5-[]] ?
     In this case all edges are defined implicitly. The next example
     shows three unconnected edges:
          ?- vertices_edges_to_ugraph([6,7,8],[1-3,2-4,4-5,1-5],L).
          
          L = [1-[3,5],2-[4],3-[],4-[5],5-[],6-[],7-[],8-[]] ?

`vertices(+GRAPH, -VERTICES)'
     Unify VERTICES with all vertices appearing in graph GRAPH. In the
     next example:
          ?- vertices([1-[3,5],2-[4],3-[],4-[5],5-[]], V).
          
          L = [1,2,3,4,5]

`edges(+GRAPH, -EDGES)'
     Unify EDGES with all edges appearing in graph GRAPH. In the next
     example:
          ?- vertices([1-[3,5],2-[4],3-[],4-[5],5-[]], V).
          
          L = [1,2,3,4,5]

`add_vertices(+GRAPH, +VERTICES, -NEWGRAPH)'
     Unify NEWGRAPH with a new graph obtained by adding the list of
     vertices VERTICES to the graph GRAPH. In the next example:
          ?- add_vertices([1-[3,5],2-[4],3-[],4-[5],
                           5-[],6-[],7-[],8-[]],
                          [0,2,9,10,11],
                             NG).
          
          NG = [0-[],1-[3,5],2-[4],3-[],4-[5],5-[],
                6-[],7-[],8-[],9-[],10-[],11-[]]

`del_vertices(+VERTICES, +GRAPH, -NEWGRAPH)'
     Unify NEWGRAPH with a new graph obtained by deleting the list of
     vertices VERTICES and all the edges that start from or go to a
     vertex in VERTICES to the graph GRAPH. In the next example:
          ?- del_vertices([2,1],[1-[3,5],2-[4],3-[],
                           4-[5],5-[],6-[],7-[2,6],8-[]],NL).
          
          NL = [3-[],4-[5],5-[],6-[],7-[6],8-[]]

`add_edges(+GRAPH, +EDGES, -NEWGRAPH)'
     Unify NEWGRAPH with a new graph obtained by adding the list of
     edges EDGES to the graph GRAPH. In the next example:
          ?- add_edges([1-[3,5],2-[4],3-[],4-[5],5-[],6-[],
                        7-[],8-[]],[1-6,2-3,3-2,5-7,3-2,4-5],NL).
          
          NL = [1-[3,5,6],2-[3,4],3-[2],4-[5],5-[7],6-[],7-[],8-[]]

`sub_edges(+GRAPH, +EDGES, -NEWGRAPH)'
     Unify NEWGRAPH with a new graph obtained by removing the list of
     edges EDGES from the graph GRAPH. Notice that no vertices are
     deleted. In the next example:
          ?- del_edges([1-[3,5],2-[4],3-[],4-[5],5-[],
                        6-[],7-[],8-[]],
                       [1-6,2-3,3-2,5-7,3-2,4-5,1-3],NL).
          
          NL = [1-[5],2-[4],3-[],4-[],5-[],6-[],7-[],8-[]]

`transpose(+GRAPH, -NEWGRAPH)'
     Unify NEWGRAPH with a new graph obtained from GRAPH by replacing
     all edges of the form V1-V2 by edges of the form V2-V1. The cost
     is `O(|V|^2)'. In the next example:
          ?- transpose([1-[3,5],2-[4],3-[],
                        4-[5],5-[],6-[],7-[],8-[]], NL).
          
          NL = [1-[],2-[],3-[1],4-[2],5-[1,4],6-[],7-[],8-[]]
     Notice that an undirected graph is its own transpose.

`neighbors(+VERTEX, +GRAPH, -VERTICES)'
     Unify VERTICES with the list of neighbors of vertex VERTEX in
     GRAPH. If the vertice is not in the graph fail. In the next
     example:
          ?- neighbors(4,[1-[3,5],2-[4],3-[],
                          4-[1,2,7,5],5-[],6-[],7-[],8-[]],
                       NL).
          
          NL = [1,2,7,5]

`neighbours(+VERTEX, +GRAPH, -VERTICES)'
     Unify VERTICES with the list of neighbours of vertex VERTEX in
     GRAPH. In the next example:
          ?- neighbours(4,[1-[3,5],2-[4],3-[],
                           4-[1,2,7,5],5-[],6-[],7-[],8-[]], NL).
          
          NL = [1,2,7,5]

`complement(+GRAPH, -NEWGRAPH)'
     Unify NEWGRAPH with the graph complementary to GRAPH.   In the
     next example:
          ?- complement([1-[3,5],2-[4],3-[],
                         4-[1,2,7,5],5-[],6-[],7-[],8-[]], NL).
          
          NL = [1-[2,4,6,7,8],2-[1,3,5,6,7,8],3-[1,2,4,5,6,7,8],
                4-[3,5,6,8],5-[1,2,3,4,6,7,8],6-[1,2,3,4,5,7,8],
                7-[1,2,3,4,5,6,8],8-[1,2,3,4,5,6,7]]

`compose(+LEFTGRAPH, +RIGHTGRAPH, -NEWGRAPH)'
     Compose the graphs LEFTGRAPH and RIGHTGRAPH to form NEWGRAPH.   In
     the next example:
          ?- compose([1-[2],2-[3]],[2-[4],3-[1,2,4]],L).
          
          L = [1-[4],2-[1,2,4],3-[]]

`top_sort(+GRAPH, -SORT)'
     Generate the set of nodes SORT as a topological sorting of graph
     GRAPH, if one is possible.   In the next example we show how
     topological sorting works for a linear graph:
          ?- top_sort([_138-[_219],_219-[_139], _139-[]],L).
          
          L = [_138,_219,_139]

`transitive_closure(+GRAPH, +CLOSURE)'
     Generate the graph CLOSURE as the transitive closure of graph
     GRAPH.   In the next example:
          ?- transitive_closure([1-[2,3],2-[4,5],4-[6]],L).
          
          L = [1-[2,3,4,5,6],2-[4,5,6],4-[6]]

`reachable(+NODE, +GRAPH, -VERTICES)'
     Unify VERTICES with the set of all vertices in graph GRAPH that
     are reachable from NODE. In the next example:
          ?- reachable(1,[1-[3,5],2-[4],3-[],4-[5],5-[]],V).
          
          V = [1,3,5]



File: yap.info,  Node: Extensions,  Next: Debugging,  Prev: Library,  Up: Top

Extensions
**********

YAP includes several extensions that are not enabled by default, but
that can be used to extend the functionality of the system. These
options can be set at compilation time by enabling the related
compilation flag, as explained in the `Makefile'

* Menu:


Extensions to Traditional Prolog

* Rational Trees:: Working with Rational Trees
* Coroutining:: Changing the Execution of Goals
* Attributed Variables:: Using attributed Variables
* CLPQR:: The CLP(Q,R) System
* Logtalk:: The Logtalk Object-Oriented system
* Threads:: Thread Library
* Parallelism:: Running in Or-Parallel
* Tabling:: Storing Intermediate Solutions of programs
* Low Level Profiling:: Profiling Abstract Machine Instructions
* Low Level Tracing:: Tracing at Abstract Machine Level


File: yap.info,  Node: Rational Trees,  Next: Coroutining,  Up: Extensions

Rational Trees
**************

Prolog unification is not a complete implementation. For efficiency
considerations, Prolog systems do not perform occur checks while
unifying terms. As an example, `X = a(X)' will not fail but instead
will create an infinite term of the form `a(a(a(a(a(...)))))', or
_rational tree_.

   By default, rational trees are not supported in YAP, and these terms
can easily lead to infinite computation. For example, `X = a(X), X = X'
will enter an infinite loop.

   The `RATIONAL_TREES' flag improves support for these terms. Internal
primitives are now aware that these terms can exist, and will not enter
infinite loops. Hence, the previous unification will succeed. Another
example, `X = a(X), ground(X)' will succeed instead of looping. Other
affected builtins include the term comparison primitives,
`numbervars/3', `copy_term/2', and the internal data base routines. The
support does not extend to Input/Output routines or to `assert/1' YAP
does not allow directly reading rational trees, and you need to use
`write_depth/2' to avoid entering an infinite cycle when trying to
write an infinite term.


File: yap.info,  Node: Coroutining,  Next: Attributed Variables,  Prev: Rational Trees,  Up: Extensions

Coroutining
***********

Prolog uses a simple left-to-right flow of control. It is sometimes
convenient to change this control so that goals will only be executed
when conditions are fulfilled. This may result in a more "data-driven"
execution, or may be necessary to correctly implement extensions such as
negation by default.

   The `COROUTINING' flag enables this option. Note that the support for
coroutining  will in general slow down execution.

   The following declaration is supported:

`block/1'
     The argument to `block/1' is a condition on a goal or a conjunction
     of conditions, with each element separated by commas. Each
     condition is of the form `predname(C1,...,CN)', where N is the
     arity of the goal, and each CI is of the form `-', if the argument
     must suspend until the variable is bound, or `?', otherwise.

`wait/1'
     The argument to `wait/1' is a predicate descriptor or a conjunction
     of these predicates. These predicates will suspend until their
     first argument is bound.

   The following primitives are supported:

`dif(X,Y)'
     Succeed if the two arguments do not unify. A call to `dif/2' will
     suspend if unification may still succeed or fail, and will fail if
     they always unify.

`freeze(?X,:G)'
     Delay execution of goal G until the variable X is bound.

`frozen(X,G)'
     Unify G with a conjunction of goals suspended on variable X, or
     `true' if no goal has suspended.

`when(+C,:G)'
     Delay execution of goal G until the conditions C are satisfied.
     The conditions are of the following form:

    `C1,C2'
          Delay until both conditions C1 and C2 are satisfied.

    `C1;C2'
          Delay until either condition C1 or condition C2 is satisfied.

    `?=(V1,C2)'
          Delay until terms V1 and V1 have been unified.

    `nonvar(V)'
          Delay until variable V is bound.

    `ground(V)'
          Delay until variable V is ground.

     Note that `when/2' will fail if the conditions fail.

`call_residue(:G,L)'
     Call goal G. If subgoals of G are still blocked, return a list
     containing these goals and the variables they are blocked in. The
     goals are then considered as unblocked. The next example shows a
     case where `dif/2' suspends twice, once outside `call_residue/2',
     and the other inside:

          ?- dif(X,Y),
                 call_residue((dif(X,Y),(X = f(Z) ; Y = f(Z))), L).
          
          X = f(Z),
          L = [[Y]-dif(f(Z),Y)],
          dif(f(Z),Y) ? ;
          
          Y = f(Z),
          L = [[X]-dif(X,f(Z))],
          dif(X,f(Z)) ? ;
          
          no
     The system only reports one invocation of `dif/2' as having
     suspended.



File: yap.info,  Node: Attributed Variables,  Next: CLPQR,  Prev: Coroutining,  Up: Extensions

Attributed Variables
********************

* Menu:


* Attribute Declarations:: Declaring New Attributes
* Attribute Manipulation:: Setting and Reading Attributes
* Attributed Unification:: Tuning the Unification Algorithm
* Displaying Attributes:: Displaying Attributes in User-Readable Form
* Projecting Attributes:: Obtaining the Attributes of Interest
* Attribute Examples:: Two Simple Examples of how to use Attributes.

   YAP now supports the attributed variables packaged developed at OFAI
by Christian Holzbaur. Attributes are a means of declaring that an
arbitrary term is a property for a variable. These properties can be
updated during forward execution. Moreover, the unification algorithm is
aware of attributed variables and will call user defined handlers when
trying to unify these variables.

   Attributed variables provide an elegant abstraction over which one
can extend Prolog systems. Their main application so far has been in
implementing constraint handlers, such as Holzbaur's CLPQR and Fruewirth
and Holzbaur's CHR, but other applications have been proposed in the
literature.

   The command
     | ?- use_module(library(atts)).
   enables the use of attributed variables. The package provides the
following functionality:
   * Each attribute must be declared first. Attributes are described by
     a functor and are declared per module. Each Prolog module declares
     its own sets of attributes. Different modules may have different
     functors with the same module.

   * The built-in `put_atts/2' adds or deletes attributes to a
     variable. The variable may be unbound or may be an attributed
     variable. In the latter case, YAP discards previous values for the
     attributes.

   * The built-in `get_atts/2' can be used to check the values of an
     attribute associated with a variable.

   * The unification algorithm calls the user-defined predicate
     verify_attributes/3 before trying to bind an attributed variable.
     Unification will resume after this call.

   * The user-defined predicate attribute_goal/2 converts from an
     attribute to a goal.

   * The user-defined predicate project_attributes/2 is used from a set
     of variables into a set of constraints or goals. One application
     of project_attributes/2 is in the top-level, where it is used to
     output the set of floundered constraints at the end of a query.


File: yap.info,  Node: Attribute Declarations,  Next: Attribute Manipulation,  Up: Attributed Variables

Attribute Declarations
======================

Attributes are compound terms associated with a variable. Each attribute
has a _name_ which is _private_ to the module in which the attribute
was defined. Variables may have at most one attribute with a name.
Attribute names are defined with the following declaration:

     :- attribute ATTRIBUTESPEC, ..., ATTRIBUTESPEC.

where each ATTRIBUTESPEC has the form (NAME/ARITY).  One single such
declaration is allowed per module MODULE.

   Although the YAP module system is predicate based, attributes are
local to modules. This is implemented by rewriting all calls to the
builtins that manipulate attributes so that attribute names are
preprocessed depending on the module.  The `user:goal_expansion/3'
mechanism is used for this purpose.


File: yap.info,  Node: Attribute Manipulation,  Next: Attributed Unification,  Prev: Attribute Declarations,  Up: Attributed Variables

Attribute Manipulation
======================

The  attribute manipulation predicates always work as follows:
  1. The first argument is the unbound variable associated with
     attributes,

  2. The second argument is a list of attributes. Each attribute will
     be a Prolog term or a constant, prefixed with the + and - unary
     operators. The prefix + may be dropped for convenience.

   The following three procedures are available to the user. Notice that
these builtins are rewritten by the system into internal builtins, and
that the rewriting process _depends_ on the module on which the
builtins have been invoked.

`MODULE:get_atts(-VAR,?LISTOFATTRIBUTES)'
     Unify the list ?LISTOFATTRIBUTES with the attributes for the
     unbound variable VAR. Each member of the list must be a bound term
     of the form `+(ATTRIBUTE)', `-(ATTRIBUTE)' (the kbd prefix may be
     dropped). The meaning of + and - is:
    `+(ATTRIBUTE)'
          Unifies ATTRIBUTE with a corresponding attribute associated
          with VAR, fails otherwise.

    `-(ATTRIBUTE)'
          Succeeds if a corresponding attribute is not associated with
          VAR. The arguments of ATTRIBUTE are ignored.

`MODULE:put_atts(-VAR,?LISTOFATTRIBUTES)'
     Associate with or remove attributes from a variable VAR. The
     attributes are given in ?LISTOFATTRIBUTES, and the action depends
     on how they are prefixed:

`+(ATTRIBUTE)'
     Associate VAR with ATTRIBUTE. A previous value for the attribute
     is simply replace (like with `set_mutable/2').

`-(ATTRIBUTE)'
     Remove the attribute with the same name. If no such attribute
     existed, simply succeed.


File: yap.info,  Node: Attributed Unification,  Next: Displaying Attributes,  Prev: Attribute Manipulation,  Up: Attributed Variables

Attributed Unification
======================

The user-predicate predicate `verify_attributes/3' is called when
attempting to unify an attributed variable which might have attributes
in some MODULE.

`MODULE:verify_attributes(-VAR, +VALUE, -GOALS)'
     The predicate is called when trying to unify the attributed
     variable VAR with the Prolog term VALUE. Note that VALUE may be
     itself an attributed variable, or may contain attributed
     variables.  The goal verify_attributes/3 is actually called before
     VAR is unified with VALUE.

     It is up to the user to define which actions may be performed by
     verify_attributes/3 but the procedure is expected to return in
     GOALS a list of goals to be called _after_ VAR is unified with
     VALUE. If verify_attributes/3 fails, the unification will fail.

     Notice that the verify_attributes/3 may be called even if VAR has
     no attributes in module Module. In this case the routine should
     simply succeed with GOALS unified with the empty list.


File: yap.info,  Node: Displaying Attributes,  Next: Projecting Attributes,  Prev: Attributed Unification,  Up: Attributed Variables

Displaying Attributes
=====================

Attributes are usually presented as goals. The following routines are
used by builtin predicates such as `call_residue/2' and by the Prolog
top-level to display attributes:

`MODULE:attribute_goal(-VAR, -GOAL)'
     User-defined procedure, called to convert the attributes in VAR to
     a GOAL. Should fail when no interpretation is available.

`MODULE:project_attributes(-QUERYVARS, +ATTRVARS)'
     User-defined procedure, called to project the attributes in the
     query, ATTRVARS, given that the set of variables in the query is
     QUERYVARS.



File: yap.info,  Node: Projecting Attributes,  Next: Attribute Examples,  Prev: Displaying Attributes,  Up: Attributed Variables

Projecting Attributes
=====================

Constraint solvers must be able to project a set of constraints to a set
of variables. This is useful when displaying the solution to a goal, but
may also be used to manipulate computations. The user-defined
`project_attributes/2' is responsible for implementing this projection.

`MODULE:project_attributes(+QUERYVARS, +ATTRVARS)'
     Given a list of variables QUERYVARS and list of attributed
     variables ATTRVARS, project all attributes in ATTRVARS to
     QUERYVARS. Although projection is constraint system dependent,
     typically this will involve expressing all constraints in terms of
     QUERYVARS and considering all remaining variables as existentially
     quantified.

   Projection interacts with `attribute_goal/2' at the prolog top
level. When the query succeeds, the system first calls
`project_attributes/2'. The system then calls `attribute_goal/2' to get
a user-level representation of the constraints. Typically,
`attribute_goal/2' will convert from the original constraints into a
set of new constraints on the projection, and these constraints are the
ones that will have an `attribute_goal/2' handler.


File: yap.info,  Node: Attribute Examples,  Prev: Projecting Attributes,  Up: Attributed Variables

Attribute Examples
==================

The following two examples example is taken from the SICStus Prolog
manual. It sketches the implementation of a simple finite domain
"solver".  Note that an industrial strength solver would have to
provide a wider range of functionality and that it quite likely would
utilize a more efficient representation for the domains proper.  The
module exports a single predicate `domain(-VAR,?DOMAIN)' which
associates DOMAIN (a list of terms) with VAR.  A variable can be
queried for its domain by leaving DOMAIN unbound.

   We do not present here a definition for `project_attributes/2'.
Projecting finite domain constraints happens to be difficult.

     :- module(domain, [domain/2]).
     
     :- use_module(library(atts)).
     :- use_module(library(ordsets), [
             ord_intersection/3,
             ord_intersect/2,
             list_to_ord_set/2
        ]).
     
     :- attribute dom/1.
     
     verify_attributes(Var, Other, Goals) :-
             get_atts(Var, dom(Da)), !,          % are we involved?
             (   var(Other) ->                   % must be attributed then
                 (   get_atts(Other, dom(Db)) -> %   has a domain?
                     ord_intersection(Da, Db, Dc),
                     Dc = [El|Els],              % at least one element
                     (   Els = [] ->             % exactly one element
                         Goals = [Other=El]      % implied binding
                     ;   Goals = [],
                         put_atts(Other, dom(Dc))% rescue intersection
                     )
                 ;   Goals = [],
                     put_atts(Other, dom(Da))    % rescue the domain
                 )
             ;   Goals = [],
                 ord_intersect([Other], Da)      % value in domain?
             ).
     verify_attributes(_, _, []).                % unification triggered
                                                 % because of attributes
                                                 % in other modules
     
     attribute_goal(Var, domain(Var,Dom)) :-     % interpretation as goal
             get_atts(Var, dom(Dom)).
     
     domain(X, Dom) :-
             var(Dom), !,
             get_atts(X, dom(Dom)).
     domain(X, List) :-
             list_to_ord_set(List, Set),
             Set = [El|Els],                     % at least one element
             (   Els = [] ->                     % exactly one element
                 X = El                          % implied binding
             ;   put_atts(Fresh, dom(Set)),
                 X = Fresh                       % may call
                                                 % verify_attributes/3
             ).

   Note that the "implied binding" `Other=El' was deferred until after
the completion of `verify_attribute/3'.  Otherwise, there might be a
danger of recursively invoking `verify_attribute/3', which might bind
`Var', which is not allowed inside the scope of `verify_attribute/3'.
Deferring unifications into the third argument of `verify_attribute/3'
effectively serializes the calls to `verify_attribute/3'.

   Assuming that the code resides in the file `domain.yap', we can use
it via:

     | ?- use_module(domain).

   Let's test it:

     | ?- domain(X,[5,6,7,1]), domain(Y,[3,4,5,6]), domain(Z,[1,6,7,8]).
     
     domain(X,[1,5,6,7]),
     domain(Y,[3,4,5,6]),
     domain(Z,[1,6,7,8]) ?
     
     yes
     | ?- domain(X,[5,6,7,1]), domain(Y,[3,4,5,6]), domain(Z,[1,6,7,8]),
          X=Y.
     
     Y = X,
     domain(X,[5,6]),
     domain(Z,[1,6,7,8]) ?
     
     yes
     | ?- domain(X,[5,6,7,1]), domain(Y,[3,4,5,6]), domain(Z,[1,6,7,8]),
          X=Y, Y=Z.
     
     X = 6,
     Y = 6,
     Z = 6

   To demonstrate the use of the GOALS argument of
`verify_attributes/3', we give an implementation of `freeze/2'.  We
have to name it `myfreeze/2' in order to avoid a name clash with the
built-in predicate of the same name.

     :- module(myfreeze, [myfreeze/2]).
     
     :- use_module(library(atts)).
     
     :- attribute frozen/1.
     
     verify_attributes(Var, Other, Goals) :-
             get_atts(Var, frozen(Fa)), !,       % are we involved?
             (   var(Other) ->                   % must be attributed then
                 (   get_atts(Other, frozen(Fb)) % has a pending goal?
                 ->  put_atts(Other, frozen((Fa,Fb))) % rescue conjunction
                 ;   put_atts(Other, frozen(Fa)) % rescue the pending goal
                 ),
                 Goals = []
             ;   Goals = [Fa]
             ).
     verify_attributes(_, _, []).
     
     attribute_goal(Var, Goal) :-                % interpretation as goal
             get_atts(Var, frozen(Goal)).
     
     myfreeze(X, Goal) :-
             put_atts(Fresh, frozen(Goal)),
             Fresh = X.

   Assuming that this code lives in file `myfreeze.yap', we would use
it via:

     | ?- use_module(myfreeze).
     | ?- myfreeze(X,print(bound(x,X))), X=2.
     
     bound(x,2)                      % side effect
     X = 2                           % bindings

   The two solvers even work together:

     | ?- myfreeze(X,print(bound(x,X))), domain(X,[1,2,3]),
          domain(Y,[2,10]), X=Y.
     
     bound(x,2)                      % side effect
     X = 2,                          % bindings
     Y = 2

   The two example solvers interact via bindings to shared attributed
variables only.  More complicated interactions are likely to be found
in more sophisticated solvers.  The corresponding `verify_attributes/3'
predicates would typically refer to the attributes from other known
solvers/modules via the module prefix in `MODULE:get_atts/2'.


File: yap.info,  Node: CLPQR,  Next: CHR,  Prev: Attributed Variables,  Up: Extensions

CLP(Q,R) Manual
***************

* Menu:

CLP(Q,R)
* Introduction to CLPQR:: The CLP(Q,R) System
* Referencing CLPQR:: How to Reference CLP(Q,R)
* CLPQR Acknowledgments:: Acknowledgments for CLP(Q,R)
* Solver Interface:: Using the CLP(Q,R) System
* Notational Conventions:: The CLP(Q,R) Notation
* Solver Predicates:: The CLP(Q,R) Interface Predicates
* Unification:: Unification and CLP(Q,R)
* Feedback and Bindings:: Information flow in CLP(Q,R)
* Linearity and Nonlinear Residues:: Linear and Nonlinear Constraints
* How Nonlinear Residues are made to disappear:: Handling Nonlinear Residues
* Isolation Axioms:: Isolating the Variable to be Solved
* Numerical Precision and Rationals:: Reals and Rationals
* Projection and Redundancy Elimination:: Presenting Bindings for Query Variables
* Variable Ordering:: Linear Relationships between Variables
* Turning Answers into Terms:: using `call_residue/2'
* Projecting Inequalities:: How to project linear inequations
* Why Disequations:: Using Disequations in CLP(Q,R)
* Syntactic Sugar:: An easier syntax
* Monash Examples:: The Monash Library
* Compatibility Notes:: CLP(Q,R) and the clp(R) interpreter
* A Mixed Integer Linear Optimization Example:: MIP models
* Implementation Architecture:: CLP(Q,R) Components
* Fragments and Bits:: Final Last Words on CLP(Q,R)
* CLPQR Bugs:: Bugs in CLP(Q,R)
* CLPQR References:: References for CLP(Q,R)

   This Manual documents a Prolog implementation of clp(Q,R), based on
SICStus featuring extensible unification via attributed variables.

   Edition 1.3.3 December 1995

   Christian Holzbaur `christian@ai.univie.ac.at'

   Copyright (C) 1992,1993,1994,1995 OFAI Austrian Research Institute
for Artificial Intelligence (OFAI) Schottengasse 3 A-1010 Vienna,
Austria

   Permission is granted to make and distribute verbatim copies of this
manual provided the copyright notice and this permission notice are
preserved on all copies.

   Permission is granted to copy and distribute modified versions of
this manual under the conditions for verbatim copying, provided that the
entire resulting derived work is distributed under the terms of a
permission notice identical to this one.

   Permission is granted to copy and distribute translations of this
manual into another language, under the above conditions for modified
versions, except that this permission notice may be stated in a
translation approved by the OFAI.


File: yap.info,  Node: Introduction to CLPQR,  Next: Referencing CLPQR,  Up: CLPQR

Introduction to CLP(Q,R)
========================

The clp(Q,R) system described in this document is an instance of the
general Constraint Logic Programming scheme introduced by [Jaffar &
Michaylov 87].

   The implementation is at least as complete as other existing clp(R)
implementations: It solves linear equations over rational or real
valued variables, covers the lazy treatment of nonlinear equations,
features a decision algorithm for linear inequalities that detects
implied equations, removes redundancies, performs projections
(quantifier elimination), allows for linear dis-equations, and provides
for linear optimization.

   The full clp(Q,R) distribution, including a stand-alone manual and an
examples directory that is possibly more up to date than the version in
the SICStus Prolog distribution, is available from:
http://www.ai.univie.ac.at/clpqr/.


File: yap.info,  Node: Referencing CLPQR,  Next: CLPQR Acknowledgments,  Prev: Introduction to CLPQR,  Up: CLPQR

Referencing CLP(Q,R)
====================

When referring to this implementation of clp(Q,R) in publications, you
should use the following reference:

   Holzbaur C.: OFAI clp(q,r) Manual, Edition 1.3.3, Austrian Research
Institute for Artificial Intelligence, Vienna, TR-95-09, 1995.


File: yap.info,  Node: CLPQR Acknowledgments,  Next: Solver Interface,  Prev: Referencing CLPQR,  Up: CLPQR

CLP(QR) Acknowledgments
=======================

Acknowledgments

   The development of this software was supported by the Austrian Fonds
zur Foerderung der Wissenschaftlichen Forschung under grant P9426-PHY.
Financial support for the Austrian Research Institute for Artificial
Intelligence is provided by the Austrian Federal Ministry for Science
and Research.

   We include a collection of examples that has been distributed with
the Monash University version of clp(R) [Heintze et al. 87], and its
inclusion into this distribution was kindly permitted by Roland Yap.


File: yap.info,  Node: Solver Interface,  Next: Notational Conventions,  Prev: CLPQR Acknowledgments,  Up: CLPQR

Solver Interface
================

Rational numbers are not first class citizens in SICStus Prolog, so
rational arithmetics has to be emulated. Because of the emulation it is
too expensive to support arithmetics with automatic coercion between
all sorts of numbers, like you find it in CommonLisp, for example.

   You must choose whether you want to operate in the field of Q
(Rationals) or R (Reals):

      ?- use_module(library(clpq)).

   or
      ?- use_module(library(clpr)).


File: yap.info,  Node: Notational Conventions,  Next: Solver Predicates,  Prev: Solver Interface,  Up: CLPQR

Notational Conventions
======================

Throughout this chapter, the prompts `clp(q) ?-' and `clp(r) ?-' are
used to differentiate between clp(Q) and clp(R) in exemplary
interactions.

   In general there are many ways to express the same linear
relationship. This degree of freedom is manifest in the fact that the
printed manual and an actual interaction with the current version of
clp(Q,R) may show syntactically different answer constraints, despite
the fact the same semantic relationship is being expressed. There are
means to control the presentation, see *note Variable Ordering::. The
approximative nature of floating point numbers may also produce
numerical differences between the text in this manual and the actual
results of clp(R), for a given edition of the software.


File: yap.info,  Node: Solver Predicates,  Next: Unification,  Prev: Notational Conventions,  Up: CLPQR

Solver Predicates
=================

The solver interface for both Q and R consists of the following
predicates which are exported from module(linear).

`{+CONSTRAINT}'
     CONSTRAINT is a term accepted by the the grammar below. The
     corresponding constraint is added to the current constraint store
     and checked for satisfiability. If you want to overload {}/1 with
     other solvers, you can avoid its importation via:
     `use_module(clpq, [])'.

          CONSTRAINT --> C
                      | C , C                 conjunction
          
          C -->          EXPR =:= EXPR         equation
                      | EXPR = EXPR           equation
                      | EXPR < EXPR           strict inequation
                      | EXPR > EXPR           strict inequation
                      | EXPR =< EXPR          nonstrict inequation
                      | EXPR >= EXPR          nonstrict inequation
                      | EXPR =\= EXPR         disequation
          
          EXPR -->       variable             Prolog variable
                      | number                floating point or integer
                      | + EXPR                unary plus
                      | - EXPR                unary minus
                      | EXPR + EXPR           addition
                      | EXPR - EXPR           subtraction
                      | EXPR * EXPR           multiplication
                      | EXPR / EXPR           division
                      | abs(EXPR)             absolute value
                      | sin(EXPR)             trigonometric sine
                      | cos(EXPR)             trigonometric cosine
                      | tan(EXPR)             trigonometric tangent
                      | pow(EXPR,EXPR)        raise to the power
                      | exp(EXPR,EXPR)        raise to the power
                      | min(EXPR,EXPR)        minimum of the two
                                                          arguments
                      | max(EXPR,EXPR)        maximum of the two
                                                          arguments
                      | #(Const)              symbolic numerical
                                                          constant

     Conjunctive constraints {-C,C} have been made part of the syntax
     in order to enable grouped submission of constraints, which could
     be exploited by future versions of this software. Symbolic
     numerical constants are provided for compatibility only, see *note
     Monash Examples::.

`entailed(+CONSTRAINT)'
     Succeeds iff the linear CONSTRAINT is entailed by the current
     constraint store. This predicate does not change the state of the
     constraint store.

          clp(q) ?- {A =< 4}, entailed(A=\=5).
          
          {A=<4}
          yes
          
          clp(q) ?- {A =< 4}, entailed(A=\=3).
          no

`inf(+EXPR, -INF )'
     Computes the infimum of the linear expression EXPR and unifies it
     with INF. Failure indicates unboundedness.

`sup(+EXPR, -SUP)'
     Computes the supremum of the linear expression EXPR and unifies it
     with SUP. Failure indicates unboundedness.

          clp(q) ?- { 2*X+Y =< 16, X+2*Y =< 11,
                       X+3*Y =< 15, Z = 30*X+50*Y
                    }, sup(Z, Sup).
          
          Sup = 310,
          {Z=30*X+50*Y},
          {X+1/2*Y=<8}
          
          {X+3*Y=<15},
          {X+2*Y=<11}

`minimize(+EXPR)'
     Computes the infimum of the linear expression EXPR and equates it
     with the expression, i.e. as if defined as:

          minimize(Expr) :- inf(Expr, Expr).

`maximize(+EXPR)'
     Computes the supremum of the linear expression EXPR and equates it
     with the expression.

          clp(q) ?- { 2*X+Y =< 16, X+2*Y =< 11,
                       X+3*Y =< 15, Z = 30*X+50*Y
                    }, maximize(Z).
          
          X = 7,
          Y = 2,
          Z = 310

`bb_inf(+INTS, +EXPR, -INF)'
     Computes the infimum of the linear expression EXPR under the
     additional constraint that all of variables in the list INTS
     assume integral values at the infimum. This allows for the
     solution of mixed integer linear optimization problems, see *note
     A Mixed Integer Linear Optimization Example::.

`ordering(+SPEC)'
     Provides a means to control one aspect of the presentation of the
     answer constraints, see *note Variable Ordering::.


File: yap.info,  Node: Unification,  Next: Feedback and Bindings,  Prev: Solver Predicates,  Up: CLPQR

Unification
===========

Equality constraints are added to the store implicitly each time
variables that have been mentioned in explicit constraints are bound -
either to another such variable or to a number.

     clp(r) ?- {2*A+3*B=C/2}, C=10.0, A=B.
     
     A = 1.0,
     B = 1.0,
     C = 10.0

   Is equivalent modulo rounding errors to

     clp(r) ?- {2*A+3*B=C/2, C=10, A=B}.
     
     A = 1.0,
     B = 0.9999999999999999,
     C = 10.0

   The shortcut bypassing the use of {}q/1 is allowed and makes sense
because the interpretation of this equality in Prolog and clp(R)
coincides. In general, equations involving interpreted functors, `+/2'
in this case, must be fed to the solver explicitly:

     clp(r) ?- X=3.0+1.0, X=4.0.
     
     no

   Further, variables known by clp(R) may be bound directly to floats
only. Likewise, variables known by clp(Q) may be bound directly to
rational numbers only, see *note Numerical Precision and Rationals::.
Failing to do so is rewarded with an exception:

     clp(q) ?- {2*A+3*B=C/2}, C=10.0, A=B.
     
     [ERROR: not.normalized(10.0)]

   This is because 10.0 is not a rational constant. To make clp(Q) happy
you have to say:

     clp(q) ?- {2*A+3*B=C/2}, C=rat(10,1), A=B.
     
     A = 1,
     B = 1,
     C = 10

   If you use `{}/1', you don't have to worry about such details.
Alternatively, you may use the automatic expansion facility, check
*note Syntactic Sugar::.


File: yap.info,  Node: Feedback and Bindings,  Next: Linearity and Nonlinear Residues,  Prev: Unification,  Up: CLPQR

Feedback and Bindings
=====================

What was covered so far was how the user populates the constraint
store. The other direction of the information flow consists of the
success and failure of the above predicates and the binding of variables
to numerical values and the aliasing of variables. Example:

     clp(r) ?- {A-B+C=10, C=5+5}.
     
     B = A,
     C = 10.0

   The linear constraints imply `A=B' and the solver consequently
exports this binding to the Prolog world, which is manifest in the fact
that the test `A==B' will succeed. More about answer presentation in
*note Projection and Redundancy Elimination::.


File: yap.info,  Node: Linearity and Nonlinear Residues,  Next: How Nonlinear Residues are made to disappear,  Prev: Feedback and Bindings,  Up: CLPQR

Linearity and Nonlinear Residues
================================

The clp(Q,R) system is restricted to deal with linear constraints
because the decision algorithms for general nonlinear constraints are
prohibitively expensive to run. If you need this functionality badly,
you should look into symbolic algebra packages. Although the clp(Q,R)
system cannot solve nonlinear constraints, it will collect them
faithfully in the hope that through the addition of further (linear)
constraints they might get simple enough to solve eventually. If an
answer contains constraints, you have to be aware of the fact that
success is qualified modulo the existence of a solution to the system of
residual (nonlinear) constraints:

     clp(r) ?- {sin(X) = cos(X)}.
     
     nonlin:{sin(X)-cos(X)=0.0}

   There are indeed infinitely many solutions to this constraint (`X =
0.785398 + n*Pi'), but clp(Q,R) has no direct means to find and
represent them.

   The systems goes through some lengths to recognize linear
expressions as such. The method is based on a normal form for
multivariate polynomials. In addition, some simple isolation axioms,
that can be used in equality constraints, have been added. The current
major limitation of the method is that full polynomial division has not
been implemented.

   This is an example where the isolation axioms are sufficient to
determine the value of X.

     clp(r) ?- {sin(cos(X)) = 1/2}.
     
     X = 1.0197267436954502

   If we change the equation into an inequation, clp(Q,R) gives up:

     clp(r) ?- {sin(cos(X)) < 1/2}.
     
     nonlin:{sin(cos(X))-0.5!0.0}

   The following is easy again:

     clp(r) ?- {sin(X+2+2)/sin(4+X) = Y}.
     
     Y = 1.0

   And so is this:

     clp(r) ?- {(X+Y)*(Y+X)/X = Y*Y/X+99}.
     
     {Y=49.5-0.5*X}

   An ancient symbol manipulation benchmark consists in rising the
expression `X+Y+Z+1' to the 15th power:

     clp(q) ?- {exp(X+Y+Z+1,15)=0}.
     
     nonlin:{Z^15+Z^14*15+Z^13*105+Z^12*455+Z^11*1365+Z^10*3003+...
              ... polynomial continues for a few pages ...
              =0}

   Computing its roots is another story.


File: yap.info,  Node: How Nonlinear Residues are made to disappear,  Next: Isolation Axioms,  Prev: Linearity and Nonlinear Residues,  Up: CLPQR

How Nonlinear Residues are made to disappear
============================================

Binding variables that appear in nonlinear residues will reduce the
complexity of the nonlinear expressions and eventually results in linear
expressions:

     clp(q) ?- {exp(X+Y+1,2) = 3*X*X+Y*Y}.
     
     nonlin:{Y*2-X^2*2+Y*X*2+X*2+1=0}

   Equating X and Y collapses the expression completely and even
determines the values of the two variables:

     clp(q) ?- {exp(X+Y+1,2) = 3*X*X+Y*Y}, X=Y.
     
     X = -1/4,
     Y = -1/4


File: yap.info,  Node: Isolation Axioms,  Next: Numerical Precision and Rationals,  Prev: How Nonlinear Residues are made to disappear,  Up: CLPQR

Isolation Axioms
================

These axioms are used to rewrite equations such that the variable to be
solved for is moved to the left hand side and the result of the
evaluation of the right hand side can be assigned to the variable. This
allows, for example, to use the exponentiation operator for the
computation of roots and logarithms, see below.

`A = B * C'
     Residuates unless B or C is ground or A and B or C are ground.

`A = B / C'
     Residuates unless C is ground or A and B are ground.

`X = min(Y,Z)'
     Residuates unless Y and Z are ground.

`X = max(Y,Z)'
     Residuates unless Y and Z are ground.

`X = abs(Y)'
     Residuates unless Y is ground.

`X = pow(Y,Z), X = exp(Y,Z)'
     Residuates unless any pair of two of the three variables is
     ground. Example:

          clp(r) ?- { 12=pow(2,X) }.
          
          X = 3.5849625007211565
          
          clp(r) ?- { 12=pow(X,3.585) }.
          
          X = 1.9999854993443926
          
          clp(r) ?- { X=pow(2,3.585) }.
          
          X = 12.000311914286545

`X = sin(Y)'
     Residuates unless X or Y is ground. Example:

          clp(r) ?- { 1/2 = sin(X) }.
          
          X = 0.5235987755982989

`X = cos(Y)'
     Residuates unless X or Y is ground.

`X = tan(Y)'
     Residuates unless X or Y is ground.


File: yap.info,  Node: Numerical Precision and Rationals,  Next: Projection and Redundancy Elimination,  Prev: Isolation Axioms,  Up: CLPQR

Numerical Precision and Rationals
=================================

The fact that you can switch between clp(R) and clp(Q) should solve most
of your numerical problems regarding precision. Within clp(Q), floating
point constants will be coerced into rational numbers automatically.
Transcendental functions will be approximated with rationals. The
precision of the approximation is limited by the floating point
precision. These two provisions allow you to switch between clp(R) and
clp(Q) without having to change your programs.

   What is to be kept in mind however is the fact that it may take quite
big rationals to accommodate the required precision. High levels of
precision are for example required if your linear program is
ill-conditioned, i.e., in a full rank system the determinant of the
coefficient matrix is close to zero. Another situation that may call for
elevated levels of precision is when a linear optimization problem
requires exceedingly many pivot steps before the optimum is reached.

   If your application approximates irrational numbers, you may be out
of space particularly soon. The following program implements N steps of
Newton's approximation for the square root function at point 2.

     %
     % from file: library('clpqr/examples/root')
     %
     
     root(N, R) :-
       root(N, 1, R).
     
     root(0, S, R) :- !, S=R.
     root(N, S, R) :-
       N1 is N-1,
       { S1 = S/2 + 1/S },
       root(N1, S1, R).

   It is known that this approximation converges quadratically, which
means that the number of correct digits in the decimal expansion roughly
doubles with each iteration. Therefore the numerator and denominator of
the rational approximation have to grow likewise:

     clp(q) ?- use_module(library('clpqr/examples/root')).
     clp(q) ?- root(3,R),print_decimal(R,70).
     1.4142156862 7450980392 1568627450 9803921568 6274509803 9215686274
     5098039215
     
     R = 577/408
     
     clp(q) ?- root(4,R),print_decimal(R,70).
     1.4142135623 7468991062 6295578890 1349101165 5962211574 4044584905
     0192000543
     
     R = 665857/470832
     
     clp(q) ?- root(5,R),print_decimal(R,70).
     
     1.4142135623 7309504880 1689623502 5302436149 8192577619 7428498289
     4986231958
     
     R = 886731088897/627013566048
     
     clp(q) ?- root(6,R),print_decimal(R,70).
     
     1.4142135623 7309504880 1688724209 6980785696 7187537723 4001561013
     1331132652
     
     R = 1572584048032918633353217/1111984844349868137938112
     
     clp(q) ?- root(7,R),print_decimal(R,70).
     
     1.4142135623 7309504880 1688724209 6980785696 7187537694 8073176679
     7379907324
     
     R = 4946041176255201878775086487573351061418968498177 /
         3497379255757941172020851852070562919437964212608

   Iterating for 8 steps produces no further change in the first 70
decimal digits of `sqrt(2)'. After 15 steps the approximating rational
number has a numerator and a denominator with 12543 digits each, and the
next step runs out of memory.

   Another irrational number that is easily computed is `e'. The
following program implements an alternating series for `1/e', where the
absolute value of last term is an upper bound on the error.

     %
     % from file: library('clpqr/examples/root')
     %
     
     e(N, E) :-
       { Err =:= exp(10,-(N+2)), Half =:= 1/2 },
       inv_e_series(Half, Half, 3, Err, Inv.E),
       { E =:= 1/Inv_E }.
     
     inv_e_series(Term, S0, ., Err, Sum) :-
       { abs(Term) =< Err }, !,
       S0 = Sum.
     
     inv_e_series(Term, S0, N, Err, Sum) :-
       N1 is N+1,
       { Term1 =:= -Term/N, S1 =:= Term1+S0 },
       inv_e_series(Term1, S1, N1, Err, Sum).

   The computation of the rational number E that approximates `e' up to
at least 1000 digits in its decimal expansion requires the evaluation
of 450 terms of the series, i.e. 450 calls of inv.e. series/5.

     clp(q) ?- e(1000,E).
     
     E = 7149056228932760213666809592072842334290744221392610955845565494
         3708750229467761730471738895197792271346693089326102132000338192
         0131874187833985420922688804220167840319199699494193852403223700
         5853832741544191628747052136402176941963825543565900589161585723
         4023097417605004829991929283045372355639145644588174733401360176
         9953973706537274133283614740902771561159913069917833820285608440
         3104966899999651928637634656418969027076699082888742481392304807
         9484725489080844360397606199771786024695620205344042765860581379
         3538290451208322129898069978107971226873160872046731879753034549
         3130492167474809196348846916421782850086985668680640425192038155
         4902863298351349469211627292865440876581064873866786120098602898
         8799130098877372097360065934827751120659213470528793143805903554
         7928682131082164366007016698761961066948371407368962539467994627
         1374858249110795976398595034606994740186040425117101588480000000
         0000000000000000000000000000000000000000000000000000000000000000
         00000000000000000000000000000000000000
         /
         2629990810403002651095959155503002285441272170673105334466808931
         6863103901346024240326549035084528682487048064823380723787110941
         6809235187356318780972302796570251102928552003708556939314795678
         1978390674393498540663747334079841518303636625888963910391440709
         0887345797303470959207883316838346973393937778363411195624313553
         8835644822353659840936818391050630360633734935381528275392050975
         7271468992840907541350345459011192466892177866882264242860412188
         0652112744642450404625763019639086944558899249788084559753723892
         1643188991444945360726899532023542969572584363761073528841147012
         2634218045463494055807073778490814692996517359952229262198396182
         1838930043528583109973872348193806830382584040536394640895148751
         0766256738740729894909630785260101721285704616818889741995949666
         6303289703199393801976334974240815397920213059799071915067856758
         6716458821062645562512745336709063396510021681900076680696945309
         3660590933279867736747926648678738515702777431353845466199680991
         73361873421152165477774911660108200059

   The decimal expansion itself looks like this:

     clp(q) ?- e(1000, E), print_decimal(E, 1000).
     2.
     7182818284 5904523536 0287471352 6624977572 4709369995 9574966967
     6277240766 3035354759 4571382178 5251664274 2746639193 2003059921
     8174135966 2904357290 0334295260 5956307381 3232862794 3490763233
     8298807531 9525101901 1573834187 9307021540 8914993488 4167509244
     7614606680 8226480016 8477411853 7423454424 3710753907 7744992069
     5517027618 3860626133 1384583000 7520449338 2656029760 6737113200
     7093287091 2744374704 7230696977 2093101416 9283681902 5515108657
     4637721112 5238978442 5056953696 7707854499 6996794686 4454905987
     9316368892 3009879312 7736178215 4249992295 7635148220 8269895193
     6680331825 2886939849 6465105820 9392398294 8879332036 2509443117
     3012381970 6841614039 7019837679 3206832823 7646480429 5311802328
     7825098194 5581530175 6717361332 0698112509 9618188159 3041690351
     5988885193 4580727386 6738589422 8792284998 9208680582 5749279610
     4841984443 6346324496 8487560233 6248270419 7862320900 2160990235
     3043699418 4914631409 3431738143 6405462531 5209618369 0888707016
     7683964243 7814059271 4563549061 3031072085 1038375051 0115747704
     1718986106 8739696552 1267154688 9570350354


File: yap.info,  Node: Projection and Redundancy Elimination,  Next: Variable Ordering,  Prev: Numerical Precision and Rationals,  Up: CLPQR

Projection and Redundancy Elimination
=====================================

Once a derivation succeeds, the Prolog system presents the bindings for
the variables in the query. In a CLP system, the set of answer
constraints is presented in analogy. A complication in the CLP context
are variables and associated constraints that were not mentioned in the
query. A motivating example is the familiar mortgage relation:

     %
     % from file: library('clpqr/examples/mg')
     %
     
     mg(P,T,I,B,MP):-
       {
         T = 1,
         B + MP = P * (1 + I)
       }.
     mg(P,T,I,B,MP):-
       {
         T > 1,
         P1 = P * (1 + I) - MP,
         T1 = T - 1
       }, mg(P1, T1, I, B, MP).

   A sample query yields:

     clp(r) ?- use_module(library('clpqr/examples/mg')).
     
     clp(r) ?- mg(P,12,0.01,B,Mp).
     
     {B=1.1268250301319698*P-12.682503013196973*Mp}

   Without projection of the answer constraints onto the query
variables we would observe the following interaction:

     clp(r) ?- mg(P,12,0.01,B,Mp).
     
     {B=12.682503013196973*_A-11.682503013196971*P},
     {Mp= -(_A)+1.01*P},
     {_B=2.01*_A-1.01*P}
     {_C=3.0301*_A-2.0301*P},
     {_D=4.060401000000001*_A-3.0604009999999997*P},
     {_E=5.101005010000001*_A-4.10100501*P},
     {_F=6.152015060100001*_A-5.152015060099999*P},
     {_G=7.213535210701001*_A-6.213535210700999*P},
     {_H=8.285670562808011*_A-7.285670562808009*P},
     {_I=9.368527268436091*_A-8.36852726843609*P},
     {_J=10.462212541120453*_A-9.46221254112045*P},
     {_K=11.566834666531657*_A-10.566834666531655*P}

   The variables _A ... _K are not part of the query, they originate
from the mortgage program proper. Although the latter answer is
equivalent to the former in terms of linear algebra, most users would
prefer the former.


File: yap.info,  Node: Variable Ordering,  Next: Turning Answers into Terms,  Prev: Projection and Redundancy Elimination,  Up: CLPQR

Variable Ordering
=================

In general, there are many ways to express the same linear relationship
between variables. clp(Q,R) does not care to distinguish between them,
but the user might. The predicate ordering(+SPEC) gives you some
control over the variable ordering. Suppose that instead of B, you want
MP to be the defined variable:

     clp(r) ?- mg(P,12,0.01,B,Mp).
     
     {B=1.1268250301319698*P-12.682503013196973*Mp}

   This is achieved with:

     clp(r) ?- mg(P,12,0.01,B,Mp), ordering([Mp]).
     
     {Mp= -0.0788487886783417*B+0.08884878867834171*P}

   One could go one step further and require P to appear before (to the
left of) B in a addition:

     clp(r) ?- mg(P,12,0.01,B,Mp), ordering([Mp,P]).
     
     {Mp=0.08884878867834171*P-0.0788487886783417*B}

   SPEC in ordering(+SPEC) is either a list of variables with the
intended ordering, or of the form `A<B'. The latter form means that A
goes to the left of B. In fact, `ordering([A,B,C,D])' is shorthand for:

     ordering(A < B), ordering(A < C), ordering(A < D),
     ordering(B < C), ordering(B < D),
     ordering(C < D)

   The ordering specification only affects the final presentation of the
constraints. For all other operations of clp(Q,R), the ordering is
immaterial. Note that ordering/1 acts like a constraint: you can put it
anywhere in the computation, and you can submit multiple specifications.

     clp(r) ?- ordering(B < Mp), mg(P,12,0.01,B,Mp).
     
     {B= -12.682503013196973*Mp+1.1268250301319698*P}
     
     yes
     clp(r) ?- ordering(B < Mp), mg(P,12,0.01,B,Mp), ordering(P < Mp).
     
     {P=0.8874492252651537*B+11.255077473484631*Mp}


File: yap.info,  Node: Turning Answers into Terms,  Next: Projecting Inequalities,  Prev: Variable Ordering,  Up: CLPQR

Turning Answers into Terms
==========================

In meta-programming applications one needs to get a grip on the results
computed by the clp(Q,R) solver. The SISCtus Prolog predicate
`call_residue/2' provides this functionality:

     clp(r) ?- call_residue({2*A+B+C=10,C-D=E,A<10}, Constraints).
     
     Constraints = [
                    [A]-{A<10.0},
                    [B]-{B=10.0-2.0*A-C},
                    [D]-{D=C-E}
                   ]


File: yap.info,  Node: Projecting Inequalities,  Next: Why Disequations,  Prev: Turning Answers into Terms,  Up: CLPQR

Projecting Inequalities
=======================

As soon as linear inequations are involved, projection gets more
demanding complexity wise. The current clp(Q,R) version uses a
Fourier-Motzkin algorithm for the projection of linear inequalities. The
choice of a suitable algorithm is somewhat dependent on the number of
variables to be eliminated, the total number of variables, and other
factors. It is quite easy to produce problems of moderate size where the
elimination step takes some time. For example, when the dimension of the
projection is 1, you might be better off computing the supremum and the
infimum of the remaining variable instead of eliminating n-1 variables
via implicit projection.

   In order to make answers as concise as possible, redundant
constraints are removed by the system as well. In the following set of
inequalities, half of them are redundant.

     %
     % from file: library('clpqr/examples/elimination')
     %
     
     example(2, [X0,X1,X2,X3,X4]) :-
       {
            +87*X0 +52*X1 +27*X2 -54*X3 +56*X4 =< -93,
            +33*X0 -10*X1 +61*X2 -28*X3 -29*X4 =<  63,
            -68*X0  +8*X1 +35*X2 +68*X3 +35*X4 =< -85,
            +90*X0 +60*X1 -76*X2 -53*X3 +24*X4 =< -68,
            -95*X0 -10*X1 +64*X2 +76*X3 -24*X4 =<  33,
            +43*X0 -22*X1 +67*X2 -68*X3 -92*X4 =< -97,
            +39*X0  +7*X1 +62*X2 +54*X3 -26*X4 =< -27,
            +48*X0 -13*X1  +7*X2 -61*X3 -59*X4 =<  -2,
            +49*X0 -23*X1 -31*X2 -76*X3 +27*X4 =<   3,
            -50*X0 +58*X1  -1*X2 +57*X3 +20*X4 =<   6,
            -13*X0 -63*X1 +81*X2  -3*X3 +70*X4 =<  64,
            +20*X0 +67*X1 -23*X2 -41*X3 -66*X4 =<  52,
            -81*X0 -44*X1 +19*X2 -22*X3 -73*X4 =< -17,
            -43*X0  -9*X1 +14*X2 +27*X3 +40*X4 =<  39,
            +16*X0 +83*X1 +89*X2 +25*X3 +55*X4 =<  36,
            +2*X0  +40*X1 +65*X2 +59*X3 -32*X4 =<  13,
            -65*X0 -11*X1 +10*X2 -13*X3 +91*X4 =<  49,
            +93*X0 -73*X1 +91*X2  -1*X3 +23*X4 =< -87
       }.

   Consequently, the answer consists of the system of nine non-redundant
inequalities only:

     clp(q) ?- use_module(library('clpqr/examples/elimination')).
     clp(q) ?- example(2, [X0,X1,X2,X3,X4]).
     
     {X0-2/17*X1-35/68*X2-X3-35/68*X4?=5/4},
     {X0-73/93*X1+91/93*X2-1/93*X3+23/93*X4=<-29/31},
     {X0-29/25*X1+1/50*X2-57/50*X3-2/5*X4>=-3/25},
     {X0+7/39*X1+62/39*X2+18/13*X3-2/3*X4=<-9/13},
     {X0+2/19*X1-64/95*X2-4/5*X3+24/95*X4>=-33/95},
     {X0+2/3*X1-38/45*X2-53/90*X3+4/15*X4=<-34/45},
     {X0-23/49*X1-31/49*X2-76/49*X3+27/49*X4=<3/49},
     {X0+44/81*X1-19/81*X2+22/81*X3+73/81*X4>=17/81},
     {X0+9/43*X1-14/43*X2-27/43*X3-40/43*X4>=-39/43}

   The projection (the shadow) of this polyhedral set into the X0,X1
space can be computed via the implicit elimination of non-query
variables:

     clp(q) ?- example(2, [X0,X1--.]).
     
     {X0+2619277/17854273*X1>=-851123/17854273},
     {X0+6429953/16575801*X1=<-12749681/16575801},
     {X0+19130/1213083*X1>=795400/404361},
     {X0-1251619/3956679*X1?=21101146/3956679},
     {X0+601502/4257189*X1>=220850/473021}

   Projection is quite a powerful concept that leads to surprisingly
terse executable specifications of nontrivial problems like the
computation of the convex hull from a set of points in an n-dimensional
space: Given the program

     %
     % from file: library('clpqr/examples/elimination')
     %
     conv.hull(Points, Xs) :-
       lin_comb(Points, Lambdas, Zero, Xs),
       zero(Zero),
       polytope(Lambdas).
     
     polytope(Xs) :-
       positive_sum(Xs, 1).
     
       positive_sum([], Z) :- {Z=0}.
       positive_sum([X--Xs], SumX) :-
         {X >= 0, SumX = X+Sum },
         positive_sum(Xs, Sum).
     
     zero([]).
     zero([Z--Zs]) :- {Z=0}, zero(Zs).
     
     lin_comb([], [], S1, S1).
     lin_comb([Ps--Rest], [K--Ks], S1, S3) :-
       lin_comb_r(Ps, K, S1, S2),
       lin_comb(Rest, Ks, S2, S3).
     
       lin_comb_r([], ., [], []).
       lin_comb_r([P--Ps], K, [S--Ss], [Kps--Ss1]) :-
         { Kps = K*P+S },
         lin_comb_r(Ps, K, Ss, Ss1).

   we can post the following query:

     clp(q) ?- conv.hull([ [1,1], [2,0], [3,0], [1,2], [2,2] ], [X,Y]).
     
     {Y=<2},
     {X+1/2*Y=<3},
     {X>=1},
     {Y>=0},
     {X+Y>=2}

   This answer is easily verified graphically:

      |
     2-   *   *
      |
      |
     1|   *
      |
      |
     0 ---|---*---*----
          1   2   3

   The convex hull program directly corresponds to the mathematical
definition of the convex hull. What does the trick in operational terms
is the implicit elimination of the Lambdas from the program
formulation. Please note that this program does not limit the number of
points or the dimension of the space they are from. Please note further
that quantifier elimination is a computationally expensive operation and
therefore this program is only useful as a benchmark for the projector
and not so for the intended purpose.


File: yap.info,  Node: Why Disequations,  Next: Syntactic Sugar,  Prev: Projecting Inequalities,  Up: CLPQR

Why Disequations
================

A beautiful example of disequations at work is due to [Colmerauer 90].
It addresses the task of tiling a rectangle with squares of
all-different, a priori unknown sizes. Here is a translation of the
original Prolog-III program to clp(Q,R):

     %
     % from file: library('clpqr/examples/squares')
     filled_rectangle( A, C) :-
       { A >= 1 },
       distinct_squares( C),
       filled_zone( [-1,A,1], _, C, []).
     
     distinct_squares( []).
     distinct_squares( [B|C]) :-
       { B > 0 },
       outof( C, B),
       distinct_squares( C).
     
     outof( [],     _).
     outof( [B1|C], B) :-
       { B =\= B1 },       % *** note disequation ***
       outof( C, B).
     
     filled_zone( [V|L], [V|L], C0, C0) :-
       { V >= 0 }.
     filled_zone( [V|L], L3, [B|C], C2) :-
       { V < 0 },
       placed_square( B, L, L1),
       filled_zone( L1, L2, C, C1),
       { Vb=V+B },
       filled_zone( [Vb,B|L2], L3, C1, C2).
     
     placed_square( B, [H,H0,H1|L], L1) :-
       { B > H, H0=0, H2=H+H1 },
       placed_square( B, [H2|L], L1).
     placed_square( B, [B,V|L], [X|L]) :-
       { X=V-B }.
     placed_square( B, [H|L], [X,Y|L]) :-
       { B < H, X= -B, Y=H-B }.

   There are no tilings with less than nine squares except the trivial
one where the rectangle equals the only square. There are eight
solutions for nine squares. Six further solutions are rotations of the
first two.

     clp(q) ?- use_module(library('clpqr/examples/squares')).
     clp(q) ?- filled_rectangle(A, Squares).
     
     A = 1,f
     Squares = [1] ? ;
     
     A = 33/32,
     Squares = [15/32,9/16,1/4,7/32,1/8,7/16,1/32,5/16,9/32] ? ;
     
     A = 69/61,
     Squares = [33/61,36/61,28/61,5/61,2/61,9/61,25/61,7/61,16/61]

   Depending on your hardware, the above query may take a few minutes.
Supplying the knowledge about the minimal number of squares beforehand
cuts the computation time by a factor of roughly four:

     clp(q) ?- length(Squares, 9), filled.rectangle(A, Squares).
     
     A = 33/32,
     Squares = [15/32,9/16,1/4,7/32,1/8,7/16,1/32,5/16,9/32] ? ;
     
     A = 69/61,
     Squares = [33/61,36/61,28/61,5/61,2/61,9/61,25/61,7/61,16/61]


File: yap.info,  Node: Syntactic Sugar,  Next: Monash Examples,  Prev: Why Disequations,  Up: CLPQR

Syntactic Sugar
===============

There is a package that transforms programs and queries from a
eval-quote variant of clp(Q,R) into corresponding programs and queries
in a quote-eval variant. Before you use it, you need to know that in an
eval-quote language, all symbols are interpreted unless explicitly
quoted. This means that interpreted terms cannot be manipulated
syntactically directly. Meta-programming in a CLP context by definition
manipulates interpreted terms, therefore you need `quote/1' (just as in
LISP) and some means to put syntactical terms back to their interpreted
life: `{}/1'.

   In a quote-eval language, meta-programming is (pragmatically) simpler
because everything is implicitly quoted until explicitly evaluated. On
the other hand, now object programming suffers from the dual
inconvenience.

   We chose to make our version of clp(Q,R) of the quote-eval type
because this matches the intended use of the already existing boolean
solver of SICStus. In order to keep the users of the eval-quote variant
happy, we provide a source transformation package. It is activated via:

     | ?- use_module(library('clpqr/expand')).

   Loading the package puts you in a mode where the arithmetic functors
like `+/2', `*/2' and all numbers (functors of arity 0) are interpreted
semantically.

     clp(r) ?- 2+2=X. X = 4.0

   The package works by purifying programs and queries in the sense that
all references to interpreted terms are made explicit. The above query
is expanded prior to evaluation into:

     linear:{2.0+2.0=X}

   The same mechanism applies when interpreted terms are nested deeper:

     some_predicate(10, f(A+B/2), 2*cos(A))

   Expands into:

     linear:{Xc=2.0*cos(A)},
     linear:{Xb=A+B/2},
     linear:{Xa=10.0},
     some_predicate(Xa, f(Xb), Xc)

   This process also applies when files are consulted or compiled. In
fact, this is the only situation where expansion can be applied with
relative safety. To see this, consider what happens when the toplevel
evaluates the expansion, namely some calls to the clp(Q,R) solver,
followed by the call of the purified query. As we learned in *note
Feedback and Bindings::, the solver may bind variables, which produces
a goal with interpreted functors in it (numbers), which leads to
another stage of expansion, and so on.

   We recommend that you only turn on expansion temporarily while
consulting or compiling files needing expansion with `expand/0' and
`noexpand/0'.


File: yap.info,  Node: Monash Examples,  Next: Compatibility Notes,  Prev: Syntactic Sugar,  Up: CLPQR

Monash Examples
===============

This collection of examples has been distributed with the Monash
University Version of clp(R) [Heintze et al. 87], and its inclusion into
this distribution was kindly permitted by Roland Yap.

   In order to execute the examples, a small compatibility package has
to be loaded first:

     clp(r) ?- use_module(library('clpqr/monash')).

   Then, assuming you are using clp(R):

     clp(r) ?- expand, [library('clpqr/examples/monash/rkf45')],
               noexpand.
     
     clp(r) ?- go.
     Point    0.00000 :    0.75000    0.00000
     Point    0.50000 :    0.61969    0.47793
     Point    1.00000 :    0.29417    0.81233
     Point    1.50000 :   -0.10556    0.95809
     Point    2.00000 :   -0.49076    0.93977
     Point    2.50000 :   -0.81440    0.79929
     Point    3.00000 :   -1.05440    0.57522
     
     Iteration finished
     ------------------
      439 derivative evaluations


File: yap.info,  Node: Compatibility Notes,  Next: A Mixed Integer Linear Optimization Example,  Prev: Monash Examples,  Up: CLPQR

Compatibility Notes
===================

The Monash examples have been written for clp(R). Nevertheless, all but
rkf45 complete nicely in clp(Q). With `rkf45', clp(Q) runs out of
memory. This is an instance of the problem discussed in *note Numerical
Precision and Rationals::.

   The Monash University clp(R) interpreter features a `dump/n'
predicate. It is used to print the target variables according to the
given ordering. Within this version of clp(Q,R), the corresponding
functionality is provided via `ordering/1'. The difference is that
`ordering/1' does only specify the ordering of the variables and no
printing is performed. We think Prolog has enough predicates to perform
output already. You can still run the examples referring to `dump/n'
from the Prolog toplevel:

     clp(r) ?- expand, [library('clpqr/examples/monash/mortgage')], noexpand.
     
     % go2
     %
     clp(r) ?- mg(P,120,0.01,0,MP), dump([P,MP]).
     
     {P=69.7005220313972*MP}
     
     % go3
     %
     clp(r) ?- mg(P,120,0.01,B,MP), dump([P,B,MP]).
     
     {P=0.30299477968602706*B+69.7005220313972*MP}
     
     % go4
     %
     clp(r) ?- mg(999, 3, Int, 0, 400), dump.
     
     nonlin:{_B-_B*Int+.A+400.0=0.0},
     nonlin:{_A-_A*Int+400.0=0.0},
     {_B=599.0+999.0*Int}

