This is a tutorial that documents GiNaC @value{VERSION}, an open
framework for symbolic computation within the C++ programming language.
-Copyright (C) 1999-2001 Johannes Gutenberg University Mainz, Germany
+Copyright (C) 1999-2002 Johannes Gutenberg University Mainz, Germany
Permission is granted to make and distribute verbatim copies of
this manual provided the copyright notice and this permission notice
@page
@vskip 0pt plus 1filll
-Copyright @copyright{} 1999-2001 Johannes Gutenberg University Mainz, Germany
+Copyright @copyright{} 1999-2002 Johannes Gutenberg University Mainz, Germany
@sp 2
Permission is granted to make and distribute verbatim copies of
this manual provided the copyright notice and this permission notice
present day computer algebra systems (CAS) are linguistically and
semantically impoverished. Although they are quite powerful tools for
learning math and solving particular problems they lack modern
-linguistical structures that allow for the creation of large-scale
+linguistic structures that allow for the creation of large-scale
projects. GiNaC is an attempt to overcome this situation by extending a
well established and standardized computer language (C++) by some
fundamental symbolic capabilities, thus allowing for integrated systems
@section License
The GiNaC framework for symbolic computation within the C++ programming
-language is Copyright @copyright{} 1999-2001 Johannes Gutenberg
+language is Copyright @copyright{} 1999-2002 Johannes Gutenberg
University Mainz, Germany.
This program is free software; you can redistribute it and/or
pointless) bivariate polynomial with some large coefficients:
@example
+#include <iostream>
#include <ginac/ginac.h>
using namespace std;
using namespace GiNaC;
generates Hermite polynomials in a specified free variable.
@example
+#include <iostream>
#include <ginac/ginac.h>
using namespace std;
using namespace GiNaC;
Linear equation systems can be solved along with basic linear
algebra manipulations over symbolic expressions. In C++ GiNaC offers
a matrix class for this purpose but we can see what it can do using
-@command{ginsh}'s notation of double brackets to type them in:
+@command{ginsh}'s bracket notation to type them in:
@example
> lsolve(a+x*y==z,x);
y^(-1)*(z-a);
-> lsolve([3*x+5*y == 7, -2*x+10*y == -5], [x, y]);
-[x==19/8,y==-1/40]
-> M = [[ [[1, 3]], [[-3, 2]] ]];
-[[ [[1,3]], [[-3,2]] ]]
+> lsolve(@{3*x+5*y == 7, -2*x+10*y == -5@}, @{x, y@});
+@{x==19/8,y==-1/40@}
+> M = [ [1, 3], [-3, 2] ];
+[[1,3],[-3,2]]
> determinant(M);
11
> charpoly(M,lambda);
lambda^2-3*lambda+11
+> A = [ [1, 1], [2, -1] ];
+[[1,1],[2,-1]]
+> A+2*M;
+[[1,1],[2,-1]]+2*[[1,3],[-3,2]]
+> evalm(%);
+[[3,7],[-4,3]]
+> B = [ [0, 0, a], [b, 1, -b], [-1/a, 0, 0] ];
+> evalm(B^(2^12345));
+[[1,0,0],[0,1,0],[0,0,1]]
@end example
Multivariate polynomials and rational functions may be expanded,
@example
> a = x^4 + 2*x^2*y^2 + 4*x^3*y + 12*x*y^3 - 3*y^4;
--3*y^4+x^4+12*x*y^3+2*x^2*y^2+4*x^3*y
+12*x*y^3+2*x^2*y^2+4*x^3*y-3*y^4+x^4
> b = x^2 + 4*x*y - y^2;
--y^2+x^2+4*x*y
+4*x*y-y^2+x^2
> expand(a*b);
-3*y^6+x^6-24*x*y^5+43*x^2*y^4+16*x^3*y^3+17*x^4*y^2+8*x^5*y
-> collect(a*b,x);
-3*y^6+48*x*y^4+2*x^2*y^2+x^4*(-y^2+x^2+4*x*y)+4*x^3*y*(-y^2+x^2+4*x*y)
+8*x^5*y+17*x^4*y^2+43*x^2*y^4-24*x*y^5+16*x^3*y^3+3*y^6+x^6
+> collect(a+b,x);
+4*x^3*y-y^2-3*y^4+(12*y^3+4*y)*x+x^4+x^2*(1+2*y^2)
+> collect(a+b,y);
+12*x*y^3-3*y^4+(-1+2*x^2)*y^2+(4*x+4*x^3)*y+x^2+x^4
> normal(a/b);
3*y^2+x^2
@end example
> series(tgamma(x),x==0,3);
x^(-1)-Euler+(1/12*Pi^2+1/2*Euler^2)*x+
(-1/3*zeta(3)-1/12*Pi^2*Euler-1/6*Euler^3)*x^2+Order(x^3)
-> evalf(");
+> evalf(%);
x^(-1)-0.5772156649015328606+(0.9890559953279725555)*x
-(0.90747907608088628905)*x^2+Order(x^3)
> series(tgamma(2*sin(x)-2),x==Pi/2,6);
-Euler-1/12+Order((x-1/2*Pi)^3)
@end example
-Here we have made use of the @command{ginsh}-command @code{"} to pop the
+Here we have made use of the @command{ginsh}-command @code{%} to pop the
previously evaluated element from @command{ginsh}'s internal stack.
If you ever wanted to convert units in C or C++ and found this is
In order to install GiNaC on your system, some prerequisites need to be
met. First of all, you need to have a C++-compiler adhering to the
-ANSI-standard @cite{ISO/IEC 14882:1998(E)}. We used @acronym{GCC} for
-development so if you have a different compiler you are on your own.
-For the configuration to succeed you need a Posix compliant shell
-installed in @file{/bin/sh}, GNU @command{bash} is fine. Perl is needed
-by the built process as well, since some of the source files are
-automatically generated by Perl scripts. Last but not least, Bruno
-Haible's library @acronym{CLN} is extensively used and needs to be
-installed on your system. Please get it either from
-@uref{ftp://ftp.santafe.edu/pub/gnu/}, from
+ANSI-standard @cite{ISO/IEC 14882:1998(E)}. We used GCC for development
+so if you have a different compiler you are on your own. For the
+configuration to succeed you need a Posix compliant shell installed in
+@file{/bin/sh}, GNU @command{bash} is fine. Perl is needed by the built
+process as well, since some of the source files are automatically
+generated by Perl scripts. Last but not least, Bruno Haible's library
+CLN is extensively used and needs to be installed on your system.
+Please get it either from @uref{ftp://ftp.santafe.edu/pub/gnu/}, from
@uref{ftp://ftpthep.physik.uni-mainz.de/pub/gnu/, GiNaC's FTP site} or
from @uref{ftp://ftp.ilog.fr/pub/Users/haible/gnu/, Bruno Haible's FTP
site} (it is covered by GPL) and install it prior to trying to install
@end itemize
-In addition, you may specify some environment variables.
-@env{CXX} holds the path and the name of the C++ compiler
-in case you want to override the default in your path. (The
-@command{configure} script searches your path for @command{c++},
-@command{g++}, @command{gcc}, @command{CC}, @command{cxx}
-and @command{cc++} in that order.) It may be very useful to
-define some compiler flags with the @env{CXXFLAGS} environment
-variable, like optimization, debugging information and warning
-levels. If omitted, it defaults to @option{-g -O2}.
+In addition, you may specify some environment variables. @env{CXX}
+holds the path and the name of the C++ compiler in case you want to
+override the default in your path. (The @command{configure} script
+searches your path for @command{c++}, @command{g++}, @command{gcc},
+@command{CC}, @command{cxx} and @command{cc++} in that order.) It may
+be very useful to define some compiler flags with the @env{CXXFLAGS}
+environment variable, like optimization, debugging information and
+warning levels. If omitted, it defaults to @option{-g
+-O2}.@footnote{The @command{configure} script is itself generated from
+the file @file{configure.ac}. It is only distributed in packaged
+releases of GiNaC. If you got the naked sources, e.g. from CVS, you
+must generate @command{configure} along with the various
+@file{Makefile.in} by using the @command{autogen.sh} script. This will
+require a fair amount of support from your local toolchain, though.}
The whole process is illustrated in the following two
examples. (Substitute @command{setenv @var{VARIABLE} @var{value}} for
@end example
And here is a configuration for a private static GiNaC library with
-several components sitting in custom places (site-wide @acronym{GCC} and
-private @acronym{CLN}). The compiler is pursuaded to be picky and full
-assertions and debugging information are switched on:
+several components sitting in custom places (site-wide GCC and private
+CLN). The compiler is persuaded to be picky and full assertions and
+debugging information are switched on:
@example
$ export CXX=/usr/local/gnu/bin/c++
$ export CPPFLAGS="$(CPPFLAGS) -I$(HOME)/include"
-$ export CXXFLAGS="$(CXXFLAGS) -DDO_GINAC_ASSERT -ggdb -Wall -ansi -pedantic"
+$ export CXXFLAGS="$(CXXFLAGS) -DDO_GINAC_ASSERT -ggdb -Wall -pedantic"
$ export LDFLAGS="$(LDFLAGS) -L$(HOME)/lib"
$ ./configure --disable-shared --prefix=$(HOME)
@end example
to fiddle around with optimization.
Generally, the top-level Makefile runs recursively to the
-subdirectories. It is therfore safe to go into any subdirectory
-(@code{doc/}, @code{ginsh/}, ...) and simply type @code{make}
+subdirectories. It is therefore safe to go into any subdirectory
+(@code{doc/}, @code{ginsh/}, @dots{}) and simply type @code{make}
@var{target} there in case something went wrong.
@menu
* Expressions:: The fundamental GiNaC class.
* The Class Hierarchy:: Overview of GiNaC's classes.
+* Error handling:: How the library reports errors.
* Symbols:: Symbolic objects.
* Numbers:: Numerical objects.
* Constants:: Pre-defined constants.
* Lists:: Lists of expressions.
* Mathematical functions:: Mathematical functions.
* Relations:: Equality, Inequality and all that.
+* Matrices:: Matrices.
* Indexed objects:: Handling indexed quantities.
+* Non-commutative objects:: Algebras with non-commutative products.
@end menu
The most common class of objects a user deals with is the expression
@code{ex}, representing a mathematical object like a variable, number,
-function, sum, product, etc... Expressions may be put together to form
+function, sum, product, etc@dots{} Expressions may be put together to form
new expressions, passed as arguments to functions, and so on. Here is a
little collection of valid expressions:
@code{ex}.
-@node The Class Hierarchy, Symbols, Expressions, Basic Concepts
+@node The Class Hierarchy, Error handling, Expressions, Basic Concepts
@c node-name, next, previous, up
@section The Class Hierarchy
@cindex container
@cindex atom
-To get an idea about what kinds of symbolic composits may be built we
+To get an idea about what kinds of symbolic composites may be built we
have a look at the most important classes in the class hierarchy and
some of the relations among the classes:
@item @code{numeric} @tab All kinds of numbers, @math{42}, @math{7/3*I}, @math{3.14159}@dots{}
@item @code{add} @tab Sums like @math{x+y} or @math{a-(2*b)+3}
@item @code{mul} @tab Products like @math{x*y} or @math{2*a^2*(x+y+z)/b}
+@item @code{ncmul} @tab Products of non-commutative objects
@item @code{power} @tab Exponentials such as @math{x^2}, @math{a^b},
@tex
$\sqrt{2}$
@dots{}
@item @code{pseries} @tab Power Series, e.g. @math{x-1/6*x^3+1/120*x^5+O(x^7)}
@item @code{function} @tab A symbolic function like @math{sin(2*x)}
-@item @code{lst} @tab Lists of expressions [@math{x}, @math{2*y}, @math{3+z}]
-@item @code{matrix} @tab @math{n}x@math{m} matrices of expressions
+@item @code{lst} @tab Lists of expressions @{@math{x}, @math{2*y}, @math{3+z}@}
+@item @code{matrix} @tab @math{m}x@math{n} matrices of expressions
@item @code{relational} @tab A relation like the identity @math{x}@code{==}@math{y}
@item @code{indexed} @tab Indexed object like @math{A_ij}
@item @code{tensor} @tab Special tensor like the delta and metric tensors
@item @code{idx} @tab Index of an indexed object
@item @code{varidx} @tab Index with variance
+@item @code{spinidx} @tab Index with variance and dot (used in Weyl-van-der-Waerden spinor formalism)
+@item @code{wildcard} @tab Wildcard for pattern matching
@end multitable
@end cartouche
-@node Symbols, Numbers, The Class Hierarchy, Basic Concepts
+
+@node Error handling, Symbols, The Class Hierarchy, Basic Concepts
+@c node-name, next, previous, up
+@section Error handling
+@cindex exceptions
+@cindex @code{pole_error} (class)
+
+GiNaC reports run-time errors by throwing C++ exceptions. All exceptions
+generated by GiNaC are subclassed from the standard @code{exception} class
+defined in the @file{<stdexcept>} header. In addition to the predefined
+@code{logic_error}, @code{domain_error}, @code{out_of_range},
+@code{invalid_argument}, @code{runtime_error}, @code{range_error} and
+@code{overflow_error} types, GiNaC also defines a @code{pole_error}
+exception that gets thrown when trying to evaluate a mathematical function
+at a singularity.
+
+The @code{pole_error} class has a member function
+
+@example
+int pole_error::degree(void) const;
+@end example
+
+that returns the order of the singularity (or 0 when the pole is
+logarithmic or the order is undefined).
+
+When using GiNaC it is useful to arrange for exceptions to be catched in
+the main program even if you don't want to do any special error handling.
+Otherwise whenever an error occurs in GiNaC, it will be delegated to the
+default exception handler of your C++ compiler's run-time system which
+usually only aborts the program without giving any information what went
+wrong.
+
+Here is an example for a @code{main()} function that catches and prints
+exceptions generated by GiNaC:
+
+@example
+#include <iostream>
+#include <stdexcept>
+#include <ginac/ginac.h>
+using namespace std;
+using namespace GiNaC;
+
+int main(void)
+@{
+ try @{
+ ...
+ // code using GiNaC
+ ...
+ @} catch (exception &p) @{
+ cerr << p.what() << endl;
+ return 1;
+ @}
+ return 0;
+@}
+@end example
+
+
+@node Symbols, Numbers, Error handling, Basic Concepts
@c node-name, next, previous, up
@section Symbols
@cindex @code{symbol} (class)
Although symbols can be assigned expressions for internal reasons, you
should not do it (and we are not going to tell you how it is done). If
you want to replace a symbol with something else in an expression, you
-can use the expression's @code{.subs()} method (@xref{Substituting Expressions},
-for more information).
+can use the expression's @code{.subs()} method (@pxref{Substituting Expressions}).
@node Numbers, Constants, Symbols, Basic Concepts
@cindex CLN
@cindex rational
@cindex fraction
-For storing numerical things, GiNaC uses Bruno Haible's library
-@acronym{CLN}. The classes therein serve as foundation classes for
-GiNaC. @acronym{CLN} stands for Class Library for Numbers or
-alternatively for Common Lisp Numbers. In order to find out more about
-@acronym{CLN}'s internals the reader is refered to the documentation of
-that library. @inforef{Introduction, , cln}, for more
-information. Suffice to say that it is by itself build on top of another
-library, the GNU Multiple Precision library @acronym{GMP}, which is an
+For storing numerical things, GiNaC uses Bruno Haible's library CLN.
+The classes therein serve as foundation classes for GiNaC. CLN stands
+for Class Library for Numbers or alternatively for Common Lisp Numbers.
+In order to find out more about CLN's internals, the reader is referred to
+the documentation of that library. @inforef{Introduction, , cln}, for
+more information. Suffice to say that it is by itself build on top of
+another library, the GNU Multiple Precision library GMP, which is an
extremely fast library for arbitrary long integers and rationals as well
as arbitrary precision floating point numbers. It is very commonly used
-by several popular cryptographic applications. @acronym{CLN} extends
-@acronym{GMP} by several useful things: First, it introduces the complex
-number field over either reals (i.e. floating point numbers with
-arbitrary precision) or rationals. Second, it automatically converts
-rationals to integers if the denominator is unity and complex numbers to
-real numbers if the imaginary part vanishes and also correctly treats
-algebraic functions. Third it provides good implementations of
-state-of-the-art algorithms for all trigonometric and hyperbolic
-functions as well as for calculation of some useful constants.
+by several popular cryptographic applications. CLN extends GMP by
+several useful things: First, it introduces the complex number field
+over either reals (i.e. floating point numbers with arbitrary precision)
+or rationals. Second, it automatically converts rationals to integers
+if the denominator is unity and complex numbers to real numbers if the
+imaginary part vanishes and also correctly treats algebraic functions.
+Third it provides good implementations of state-of-the-art algorithms
+for all trigonometric and hyperbolic functions as well as for
+calculation of some useful constants.
The user can construct an object of class @code{numeric} in several
ways. The following example shows the four most important constructors.
integers, construction from C-float and construction from a string:
@example
+#include <iostream>
#include <ginac/ginac.h>
using namespace GiNaC;
int main()
@{
- numeric two(2); // exact integer 2
+ numeric two = 2; // exact integer 2
numeric r(2,3); // exact fraction 2/3
numeric e(2.71828); // floating point number
- numeric p("3.1415926535897932385"); // floating point number
+ numeric p = "3.14159265358979323846"; // constructor from string
// Trott's constant in scientific notation:
numeric trott("1.0841015122311136151E-2");
std::cout << two*p << std::endl; // floating point 6.283...
-@}
+ ...
@end example
-Note that all those constructors are @emph{explicit} which means you are
-not allowed to write @code{numeric two=2;}. This is because the basic
-objects to be handled by GiNaC are the expressions @code{ex} and we want
-to keep things simple and wish objects like @code{pow(x,2)} to be
-handled the same way as @code{pow(x,a)}, which means that we need to
-allow a general @code{ex} as base and exponent. Therefore there is an
-implicit constructor from C-integers directly to expressions handling
-numerics at work in most of our examples. This design really becomes
-convenient when one declares own functions having more than one
-parameter but it forbids using implicit constructors because that would
-lead to compile-time ambiguities.
+@cindex @code{I}
+@cindex complex numbers
+The imaginary unit in GiNaC is a predefined @code{numeric} object with the
+name @code{I}:
-It may be tempting to construct numbers writing @code{numeric r(3/2)}.
+@example
+ ...
+ numeric z1 = 2-3*I; // exact complex number 2-3i
+ numeric z2 = 5.9+1.6*I; // complex floating point number
+@}
+@end example
+
+It may be tempting to construct fractions by writing @code{numeric r(3/2)}.
This would, however, call C's built-in operator @code{/} for integers
first and result in a numeric holding a plain integer 1. @strong{Never
use the operator @code{/} on integers} unless you know exactly what you
digits:
@example
+#include <iostream>
#include <ginac/ginac.h>
using namespace std;
using namespace GiNaC;
@example
in 17 digits:
-0.333333333333333333
-3.14159265358979324
+0.33333333333333333334
+3.1415926535897932385
in 60 digits:
-0.333333333333333333333333333333333333333333333333333333333333333333
-3.14159265358979323846264338327950288419716939937510582097494459231
+0.33333333333333333333333333333333333333333333333333333333333333333334
+3.1415926535897932384626433832795028841971693993751058209749445923078
@end example
+@cindex rounding
+Note that the last number is not necessarily rounded as you would
+naively expect it to be rounded in the decimal system. But note also,
+that in both cases you got a couple of extra digits. This is because
+numbers are internally stored by CLN as chunks of binary digits in order
+to match your machine's word size and to not waste precision. Thus, on
+architectures with different word size, the above output might even
+differ with regard to actually computed digits.
+
It should be clear that objects of class @code{numeric} should be used
for constructing numbers or for doing arithmetic with them. The objects
one deals with most of the time are the polymorphic expressions @code{ex}.
some multiple of its denominator and test what comes out:
@example
+#include <iostream>
#include <ginac/ginac.h>
using namespace std;
using namespace GiNaC;
holds a rational number represented as integer numerator and integer
denominator. When multiplied by 10, the denominator becomes unity and
the result is automatically converted to a pure integer again.
-Internally, the underlying @acronym{CLN} is responsible for this
-behaviour and we refer the reader to @acronym{CLN}'s documentation.
-Suffice to say that the same behaviour applies to complex numbers as
-well as return values of certain functions. Complex numbers are
-automatically converted to real numbers if the imaginary part becomes
-zero. The full set of tests that can be applied is listed in the
-following table.
+Internally, the underlying CLN is responsible for this behavior and we
+refer the reader to CLN's documentation. Suffice to say that
+the same behavior applies to complex numbers as well as return values of
+certain functions. Complex numbers are automatically converted to real
+numbers if the imaginary part becomes zero. The full set of tests that
+can be applied is listed in the following table.
@cartouche
@multitable @columnfractions .30 .70
Also, expressions involving integer exponents are very frequently used,
which makes it even more dangerous to overload @code{^} since it is then
hard to distinguish between the semantics as exponentiation and the one
-for exclusive or. (It would be embarassing to return @code{1} where one
+for exclusive or. (It would be embarrassing to return @code{1} where one
has requested @code{2^3}.)
@end itemize
@cindex @code{op()}
@cindex @code{append()}
@cindex @code{prepend()}
+@cindex @code{remove_first()}
+@cindex @code{remove_last()}
-The GiNaC class @code{lst} serves for holding a list of arbitrary expressions.
-These are sometimes used to supply a variable number of arguments of the same
-type to GiNaC methods such as @code{subs()} and @code{to_rational()}, so you
-should have a basic understanding about them.
+The GiNaC class @code{lst} serves for holding a @dfn{list} of arbitrary
+expressions. These are sometimes used to supply a variable number of
+arguments of the same type to GiNaC methods such as @code{subs()} and
+@code{to_rational()}, so you should have a basic understanding about them.
-Lists of up to 15 expressions can be directly constructed from single
+Lists of up to 16 expressions can be directly constructed from single
expressions:
@example
// ...
@end example
-Finally you can append or prepend an expression to a list with the
-@code{append()} and @code{prepend()} methods:
+You can append or prepend an expression to a list with the @code{append()}
+and @code{prepend()} methods:
+
+@example
+ // ...
+ l.append(4*x); // l is now @{x, 2, y, x+y, 4*x@}
+ l.prepend(0); // l is now @{0, x, 2, y, x+y, 4*x@}
+ // ...
+@end example
+
+Finally you can remove the first or last element of a list with
+@code{remove_first()} and @code{remove_last()}:
@example
// ...
- l.append(4*x); // l is now [x, 2, y, x+y, 4*x]
- l.prepend(0); // l is now [0, x, 2, y, x+y, 4*x]
+ l.remove_first(); // l is now @{x, 2, y, x+y, 4*x@}
+ l.remove_last(); // l is now @{x, 2, y, x+y@}
@}
@end example
instance, all trigonometric and hyperbolic functions are implemented
(@xref{Built-in Functions}, for a complete list).
-These functions are all objects of class @code{function}. They accept
-one or more expressions as arguments and return one expression. If the
-arguments are not numerical, the evaluation of the function may be
-halted, as it does in the next example, showing how a function returns
-itself twice and finally an expression that may be really useful:
+These functions (better called @emph{pseudofunctions}) are all objects
+of class @code{function}. They accept one or more expressions as
+arguments and return one expression. If the arguments are not
+numerical, the evaluation of the function may be halted, as it does in
+the next example, showing how a function returns itself twice and
+finally an expression that may be really useful:
@cindex Gamma function
@cindex @code{subs()}
expansion and so on. Read the next chapter in order to learn more about
this.
+It must be noted that these pseudofunctions are created by inline
+functions, where the argument list is templated. This means that
+whenever you call @code{GiNaC::sin(1)} it is equivalent to
+@code{sin(ex(1))} and will therefore not result in a floating point
+number. Unless of course the function prototype is explicitly
+overridden -- which is the case for arguments of type @code{numeric}
+(not wrapped inside an @code{ex}). Hence, in order to obtain a floating
+point number of class @code{numeric} you should call
+@code{sin(numeric(1))}. This is almost the same as calling
+@code{sin(1).evalf()} except that the latter will return a numeric
+wrapped inside an @code{ex}.
+
-@node Relations, Indexed objects, Mathematical functions, Basic Concepts
+@node Relations, Matrices, Mathematical functions, Basic Concepts
@c node-name, next, previous, up
@section Relations
@cindex @code{relational} (class)
@code{expand()} must be called explicitly.
-@node Indexed objects, Methods and Functions, Relations, Basic Concepts
+@node Matrices, Indexed objects, Relations, Basic Concepts
+@c node-name, next, previous, up
+@section Matrices
+@cindex @code{matrix} (class)
+
+A @dfn{matrix} is a two-dimensional array of expressions. The elements of a
+matrix with @math{m} rows and @math{n} columns are accessed with two
+@code{unsigned} indices, the first one in the range 0@dots{}@math{m-1}, the
+second one in the range 0@dots{}@math{n-1}.
+
+There are a couple of ways to construct matrices, with or without preset
+elements:
+
+@cindex @code{lst_to_matrix()}
+@cindex @code{diag_matrix()}
+@cindex @code{unit_matrix()}
+@cindex @code{symbolic_matrix()}
+@example
+matrix::matrix(unsigned r, unsigned c);
+matrix::matrix(unsigned r, unsigned c, const lst & l);
+ex lst_to_matrix(const lst & l);
+ex diag_matrix(const lst & l);
+ex unit_matrix(unsigned x);
+ex unit_matrix(unsigned r, unsigned c);
+ex symbolic_matrix(unsigned r, unsigned c, const string & base_name);
+ex symbolic_matrix(unsigned r, unsigned c, const string & base_name, const string & tex_base_name);
+@end example
+
+The first two functions are @code{matrix} constructors which create a matrix
+with @samp{r} rows and @samp{c} columns. The matrix elements can be
+initialized from a (flat) list of expressions @samp{l}. Otherwise they are
+all set to zero. The @code{lst_to_matrix()} function constructs a matrix
+from a list of lists, each list representing a matrix row. @code{diag_matrix()}
+constructs a diagonal matrix given the list of diagonal elements.
+@code{unit_matrix()} creates an @samp{x} by @samp{x} (or @samp{r} by @samp{c})
+unit matrix. And finally, @code{symbolic_matrix} constructs a matrix filled
+with newly generated symbols made of the specified base name and the
+position of each element in the matrix.
+
+Matrix elements can be accessed and set using the parenthesis (function call)
+operator:
+
+@example
+const ex & matrix::operator()(unsigned r, unsigned c) const;
+ex & matrix::operator()(unsigned r, unsigned c);
+@end example
+
+It is also possible to access the matrix elements in a linear fashion with
+the @code{op()} method. But C++-style subscripting with square brackets
+@samp{[]} is not available.
+
+Here are a couple of examples of constructing matrices:
+
+@example
+@{
+ symbol a("a"), b("b");
+
+ matrix M(2, 2);
+ M(0, 0) = a;
+ M(1, 1) = b;
+ cout << M << endl;
+ // -> [[a,0],[0,b]]
+
+ cout << matrix(2, 2, lst(a, 0, 0, b)) << endl;
+ // -> [[a,0],[0,b]]
+
+ cout << lst_to_matrix(lst(lst(a, 0), lst(0, b))) << endl;
+ // -> [[a,0],[0,b]]
+
+ cout << diag_matrix(lst(a, b)) << endl;
+ // -> [[a,0],[0,b]]
+
+ cout << unit_matrix(3) << endl;
+ // -> [[1,0,0],[0,1,0],[0,0,1]]
+
+ cout << symbolic_matrix(2, 3, "x") << endl;
+ // -> [[x00,x01,x02],[x10,x11,x12]]
+@}
+@end example
+
+@cindex @code{transpose()}
+@cindex @code{inverse()}
+There are three ways to do arithmetic with matrices. The first (and most
+efficient one) is to use the methods provided by the @code{matrix} class:
+
+@example
+matrix matrix::add(const matrix & other) const;
+matrix matrix::sub(const matrix & other) const;
+matrix matrix::mul(const matrix & other) const;
+matrix matrix::mul_scalar(const ex & other) const;
+matrix matrix::pow(const ex & expn) const;
+matrix matrix::transpose(void) const;
+matrix matrix::inverse(void) const;
+@end example
+
+All of these methods return the result as a new matrix object. Here is an
+example that calculates @math{A*B-2*C} for three matrices @math{A}, @math{B}
+and @math{C}:
+
+@example
+@{
+ matrix A(2, 2, lst(1, 2, 3, 4));
+ matrix B(2, 2, lst(-1, 0, 2, 1));
+ matrix C(2, 2, lst(8, 4, 2, 1));
+
+ matrix result = A.mul(B).sub(C.mul_scalar(2));
+ cout << result << endl;
+ // -> [[-13,-6],[1,2]]
+ ...
+@}
+@end example
+
+@cindex @code{evalm()}
+The second (and probably the most natural) way is to construct an expression
+containing matrices with the usual arithmetic operators and @code{pow()}.
+For efficiency reasons, expressions with sums, products and powers of
+matrices are not automatically evaluated in GiNaC. You have to call the
+method
+
+@example
+ex ex::evalm() const;
+@end example
+
+to obtain the result:
+
+@example
+@{
+ ...
+ ex e = A*B - 2*C;
+ cout << e << endl;
+ // -> [[1,2],[3,4]]*[[-1,0],[2,1]]-2*[[8,4],[2,1]]
+ cout << e.evalm() << endl;
+ // -> [[-13,-6],[1,2]]
+ ...
+@}
+@end example
+
+The non-commutativity of the product @code{A*B} in this example is
+automatically recognized by GiNaC. There is no need to use a special
+operator here. @xref{Non-commutative objects}, for more information about
+dealing with non-commutative expressions.
+
+Finally, you can work with indexed matrices and call @code{simplify_indexed()}
+to perform the arithmetic:
+
+@example
+@{
+ ...
+ idx i(symbol("i"), 2), j(symbol("j"), 2), k(symbol("k"), 2);
+ e = indexed(A, i, k) * indexed(B, k, j) - 2 * indexed(C, i, j);
+ cout << e << endl;
+ // -> -2*[[8,4],[2,1]].i.j+[[-1,0],[2,1]].k.j*[[1,2],[3,4]].i.k
+ cout << e.simplify_indexed() << endl;
+ // -> [[-13,-6],[1,2]].i.j
+@}
+@end example
+
+Using indices is most useful when working with rectangular matrices and
+one-dimensional vectors because you don't have to worry about having to
+transpose matrices before multiplying them. @xref{Indexed objects}, for
+more information about using matrices with indices, and about indices in
+general.
+
+The @code{matrix} class provides a couple of additional methods for
+computing determinants, traces, and characteristic polynomials:
+
+@cindex @code{determinant()}
+@cindex @code{trace()}
+@cindex @code{charpoly()}
+@example
+ex matrix::determinant(unsigned algo = determinant_algo::automatic) const;
+ex matrix::trace(void) const;
+ex matrix::charpoly(const symbol & lambda) const;
+@end example
+
+The @samp{algo} argument of @code{determinant()} allows to select between
+different algorithms for calculating the determinant. The possible values
+are defined in the @file{flags.h} header file. By default, GiNaC uses a
+heuristic to automatically select an algorithm that is likely to give the
+result most quickly.
+
+
+@node Indexed objects, Non-commutative objects, Matrices, Basic Concepts
@c node-name, next, previous, up
@section Indexed objects
a @dfn{value} and a @dfn{dimension} (which is the dimension of the space
the index lives in) which can both be arbitrary expressions but are usually
a number or a simple symbol. In addition, indices of class @code{varidx} have
-a @dfn{variance} (they can be co- or contravariant).
+a @dfn{variance} (they can be co- or contravariant), and indices of class
+@code{spinidx} have a variance and can be @dfn{dotted} or @dfn{undotted}.
@item Indexed objects are of class @code{indexed} or a subclass. They
contain a @dfn{base expression} (which is the expression being indexed), and
@end itemize
@strong{Note:} when printing expressions, covariant indices and indices
-without variance are denoted @samp{.i} while contravariant indices are denoted
-@samp{~i}. In the following, we are going to use that notation in the text
-so instead of @math{A^i_jk} we will write @samp{A~i.j.k}. Index dimensions
-are not visible in the output.
+without variance are denoted @samp{.i} while contravariant indices are
+denoted @samp{~i}. Dotted indices have a @samp{*} in front of the index
+value. In the following, we are going to use that notation in the text so
+instead of @math{A^i_jk} we will write @samp{A~i.j.k}. Index dimensions are
+not visible in the output.
A simple example shall illustrate the concepts:
@example
+#include <iostream>
#include <ginac/ginac.h>
using namespace std;
using namespace GiNaC;
@code{j}.
Note the difference between the indices @code{i} and @code{j} which are of
-class @code{idx}, and the index values which are the sybols @code{i_sym}
+class @code{idx}, and the index values which are the symbols @code{i_sym}
and @code{j_sym}. The indices of indexed objects cannot directly be symbols
or numbers but must be index objects. For example, the following is not
correct and will raise an exception:
return the value and dimension of an @code{idx} object. If you have an index
in an expression, such as returned by calling @code{.op()} on an indexed
object, you can get a reference to the @code{idx} object with the function
-@code{ex_to_idx()} on the expression.
+@code{ex_to<idx>()} on the expression.
There are also the methods
bool varidx::is_contravariant(void);
@end example
-allow you to check the variance of a @code{varidx} object (use @code{ex_to_varidx()}
+allow you to check the variance of a @code{varidx} object (use @code{ex_to<varidx>()}
to get the object reference from an expression). There's also the very useful
method
which makes a new index with the same value and dimension but the opposite
variance. By using it you only have to define the index once.
+@cindex @code{spinidx} (class)
+The @code{spinidx} class provides dotted and undotted variant indices, as
+used in the Weyl-van-der-Waerden spinor formalism:
+
+@example
+ ...
+ symbol K("K"), C_sym("C"), D_sym("D");
+ spinidx C(C_sym, 2), D(D_sym); // default is 2-dimensional,
+ // contravariant, undotted
+ spinidx C_co(C_sym, 2, true); // covariant index
+ spinidx D_dot(D_sym, 2, false, true); // contravariant, dotted
+ spinidx D_co_dot(D_sym, 2, true, true); // covariant, dotted
+
+ cout << indexed(K, C, D) << endl;
+ // -> K~C~D
+ cout << indexed(K, C_co, D_dot) << endl;
+ // -> K.C~*D
+ cout << indexed(K, D_co_dot, D) << endl;
+ // -> K.*D~D
+ ...
+@end example
+
+A @code{spinidx} is a @code{varidx} with an additional flag that marks it as
+dotted or undotted. The default is undotted but this can be overridden by
+supplying a fourth argument to the @code{spinidx} constructor. The two
+methods
+
+@example
+bool spinidx::is_dotted(void);
+bool spinidx::is_undotted(void);
+@end example
+
+allow you to check whether or not a @code{spinidx} object is dotted (use
+@code{ex_to<spinidx>()} to get the object reference from an expression).
+Finally, the two methods
+
+@example
+ex spinidx::toggle_dot(void);
+ex spinidx::toggle_variance_dot(void);
+@end example
+
+create a new index with the same value and dimension but opposite dottedness
+and the same or opposite variance.
+
@subsection Substituting indices
@cindex @code{subs()}
@end example
@subsection Symmetries
+@cindex @code{symmetry} (class)
+@cindex @code{sy_none()}
+@cindex @code{sy_symm()}
+@cindex @code{sy_anti()}
+@cindex @code{sy_cycl()}
-Indexed objects can be declared as being totally symmetric or antisymmetric
-with respect to their indices. In this case, GiNaC will automatically bring
-the indices into a canonical order which allows for some immediate
-simplifications:
+Indexed objects can have certain symmetry properties with respect to their
+indices. Symmetries are specified as a tree of objects of class @code{symmetry}
+that is constructed with the helper functions
+
+@example
+symmetry sy_none(...);
+symmetry sy_symm(...);
+symmetry sy_anti(...);
+symmetry sy_cycl(...);
+@end example
+
+@code{sy_none()} stands for no symmetry, @code{sy_symm()} and @code{sy_anti()}
+specify fully symmetric or antisymmetric, respectively, and @code{sy_cycl()}
+represents a cyclic symmetry. Each of these functions accepts up to four
+arguments which can be either symmetry objects themselves or unsigned integer
+numbers that represent an index position (counting from 0). A symmetry
+specification that consists of only a single @code{sy_symm()}, @code{sy_anti()}
+or @code{sy_cycl()} with no arguments specifies the respective symmetry for
+all indices.
+
+Here are some examples of symmetry definitions:
+
+@example
+ ...
+ // No symmetry:
+ e = indexed(A, i, j);
+ e = indexed(A, sy_none(), i, j); // equivalent
+ e = indexed(A, sy_none(0, 1), i, j); // equivalent
+
+ // Symmetric in all three indices:
+ e = indexed(A, sy_symm(), i, j, k);
+ e = indexed(A, sy_symm(0, 1, 2), i, j, k); // equivalent
+ e = indexed(A, sy_symm(2, 0, 1), i, j, k); // same symmetry, but yields a
+ // different canonical order
+
+ // Symmetric in the first two indices only:
+ e = indexed(A, sy_symm(0, 1), i, j, k);
+ e = indexed(A, sy_none(sy_symm(0, 1), 2), i, j, k); // equivalent
+
+ // Antisymmetric in the first and last index only (index ranges need not
+ // be contiguous):
+ e = indexed(A, sy_anti(0, 2), i, j, k);
+ e = indexed(A, sy_none(sy_anti(0, 2), 1), i, j, k); // equivalent
+
+ // An example of a mixed symmetry: antisymmetric in the first two and
+ // last two indices, symmetric when swapping the first and last index
+ // pairs (like the Riemann curvature tensor):
+ e = indexed(A, sy_symm(sy_anti(0, 1), sy_anti(2, 3)), i, j, k, l);
+
+ // Cyclic symmetry in all three indices:
+ e = indexed(A, sy_cycl(), i, j, k);
+ e = indexed(A, sy_cycl(0, 1, 2), i, j, k); // equivalent
+
+ // The following examples are invalid constructions that will throw
+ // an exception at run time.
+
+ // An index may not appear multiple times:
+ e = indexed(A, sy_symm(0, 0, 1), i, j, k); // ERROR
+ e = indexed(A, sy_none(sy_symm(0, 1), sy_anti(0, 2)), i, j, k); // ERROR
+
+ // Every child of sy_symm(), sy_anti() and sy_cycl() must refer to the
+ // same number of indices:
+ e = indexed(A, sy_symm(sy_anti(0, 1), 2), i, j, k); // ERROR
+
+ // And of course, you cannot specify indices which are not there:
+ e = indexed(A, sy_symm(0, 1, 2, 3), i, j, k); // ERROR
+ ...
+@end example
+
+If you need to specify more than four indices, you have to use the
+@code{.add()} method of the @code{symmetry} class. For example, to specify
+full symmetry in the first six indices you would write
+@code{sy_symm(0, 1, 2, 3).add(4).add(5)}.
+
+If an indexed object has a symmetry, GiNaC will automatically bring the
+indices into a canonical order which allows for some immediate simplifications:
@example
...
- cout << indexed(A, indexed::symmetric, i, j)
- + indexed(A, indexed::symmetric, j, i) << endl;
+ cout << indexed(A, sy_symm(), i, j)
+ + indexed(A, sy_symm(), j, i) << endl;
// -> 2*A.j.i
- cout << indexed(B, indexed::antisymmetric, i, j)
- + indexed(B, indexed::antisymmetric, j, j) << endl;
- // -> -B.j.i
- cout << indexed(B, indexed::antisymmetric, i, j)
- + indexed(B, indexed::antisymmetric, j, i) << endl;
+ cout << indexed(B, sy_anti(), i, j)
+ + indexed(B, sy_anti(), j, i) << endl;
+ // -> 0
+ cout << indexed(B, sy_anti(), i, j, k)
+ - indexed(B, sy_anti(), j, k, i) << endl;
// -> 0
...
@end example
dummy nor free indices.
To be recognized as a dummy index pair, the two indices must be of the same
-class and dimension and their value must be the same single symbol (an index
-like @samp{2*n+1} is never a dummy index). If the indices are of class
-@code{varidx}, they must also be of opposite variance.
+class and their value must be the same single symbol (an index like
+@samp{2*n+1} is never a dummy index). If the indices are of class
+@code{varidx} they must also be of opposite variance; if they are of class
+@code{spinidx} they must be both dotted or both undotted.
The method @code{.get_free_indices()} returns a vector containing the free
indices of an expression. It also checks that the free indices of the terms
@itemize
@item it checks the consistency of free indices in sums in the same way
@code{get_free_indices()} does
+@item it tries to give dummy indices that appear in different terms of a sum
+ the same name to allow simplifications like @math{a_i*b_i-a_j*b_j=0}
@item it (symbolically) calculates all possible dummy index summations/contractions
with the predefined tensors (this will be explained in more detail in the
next section)
+@item it detects contractions that vanish for symmetry reasons, for example
+ the contraction of a symmetric and a totally antisymmetric tensor
@item as a special case of dummy index summation, it can replace scalar products
of two tensors with a user-defined value
@end itemize
@code{simplify_indexed()} will replace all scalar products of indexed
objects that have the symbols @code{A} and @code{B} as base expressions
with the single value 0. The number, type and dimension of the indices
-doesn't matter; @samp{A~mu~nu*B.mu.nu} would also be replaced by 0.
+don't matter; @samp{A~mu~nu*B.mu.nu} would also be replaced by 0.
@cindex @code{expand()}
The example above also illustrates a feature of the @code{expand()} method:
@subsubsection Delta tensor
The delta tensor takes two indices, is symmetric and has the matrix
-representation @code{diag(1,1,1,...)}. It is constructed by the function
+representation @code{diag(1, 1, 1, ...)}. It is constructed by the function
@code{delta_tensor()}:
@example
@}
@end example
+@cindex @code{spinor_metric()}
+@subsubsection Spinor metric tensor
+
+The function @code{spinor_metric()} creates an antisymmetric tensor with
+two indices that is used to raise/lower indices of 2-component spinors.
+It is output as @samp{eps}:
+
+@example
+@{
+ symbol psi("psi");
+
+ spinidx A(symbol("A")), B(symbol("B")), C(symbol("C"));
+ ex A_co = A.toggle_variance(), B_co = B.toggle_variance();
+
+ e = spinor_metric(A, B) * indexed(psi, B_co);
+ cout << e.simplify_indexed() << endl;
+ // -> psi~A
+
+ e = spinor_metric(A, B) * indexed(psi, A_co);
+ cout << e.simplify_indexed() << endl;
+ // -> -psi~B
+
+ e = spinor_metric(A_co, B_co) * indexed(psi, B);
+ cout << e.simplify_indexed() << endl;
+ // -> -psi.A
+
+ e = spinor_metric(A_co, B_co) * indexed(psi, A);
+ cout << e.simplify_indexed() << endl;
+ // -> psi.B
+
+ e = spinor_metric(A_co, B_co) * spinor_metric(A, B);
+ cout << e.simplify_indexed() << endl;
+ // -> 2
+
+ e = spinor_metric(A_co, B_co) * spinor_metric(B, C);
+ cout << e.simplify_indexed() << endl;
+ // -> -delta.A~C
+@}
+@end example
+
+The matrix representation of the spinor metric is @code{[[0, 1], [-1, 0]]}.
+
+@cindex @code{epsilon_tensor()}
+@cindex @code{lorentz_eps()}
@subsubsection Epsilon tensor
The epsilon tensor is totally antisymmetric, its number of indices is equal
to the dimension of the index space (the indices must all be of the same
numeric dimension), and @samp{eps.1.2.3...} (resp. @samp{eps~0~1~2...}) is
-defined to be 1. Its behaviour with indices that have a variance also
+defined to be 1. Its behavior with indices that have a variance also
depends on the signature of the metric. Epsilon tensors are output as
@samp{eps}.
dimensions, the last function creates an epsilon tensor in a 4-dimensional
Minkowski space (the last @code{bool} argument specifies whether the metric
has negative or positive signature, as in the case of the Minkowski metric
-tensor).
+tensor):
+
+@example
+@{
+ varidx mu(symbol("mu"), 4), nu(symbol("nu"), 4), rho(symbol("rho"), 4),
+ sig(symbol("sig"), 4), lam(symbol("lam"), 4), bet(symbol("bet"), 4);
+ e = lorentz_eps(mu, nu, rho, sig) *
+ lorentz_eps(mu.toggle_variance(), nu.toggle_variance(), lam, bet);
+ cout << simplify_indexed(e) << endl;
+ // -> 2*eta~bet~rho*eta~sig~lam-2*eta~sig~bet*eta~rho~lam
+
+ idx i(symbol("i"), 3), j(symbol("j"), 3), k(symbol("k"), 3);
+ symbol A("A"), B("B");
+ e = epsilon_tensor(i, j, k) * indexed(A, j) * indexed(B, k);
+ cout << simplify_indexed(e) << endl;
+ // -> -B.k*A.j*eps.i.k.j
+ e = epsilon_tensor(i, j, k) * indexed(A, j) * indexed(A, k);
+ cout << simplify_indexed(e) << endl;
+ // -> 0
+@}
+@end example
@subsection Linear algebra
-The @code{matrix} class can be used with indices to do some simple linear
-algebra (linear combinations and products of vectors and matrices, traces
-and scalar products):
+The @code{matrix} class can be used with indices to do some simple linear
+algebra (linear combinations and products of vectors and matrices, traces
+and scalar products):
+
+@example
+@{
+ idx i(symbol("i"), 2), j(symbol("j"), 2);
+ symbol x("x"), y("y");
+
+ // A is a 2x2 matrix, X is a 2x1 vector
+ matrix A(2, 2, lst(1, 2, 3, 4)), X(2, 1, lst(x, y));
+
+ cout << indexed(A, i, i) << endl;
+ // -> 5
+
+ ex e = indexed(A, i, j) * indexed(X, j);
+ cout << e.simplify_indexed() << endl;
+ // -> [[2*y+x],[4*y+3*x]].i
+
+ e = indexed(A, i, j) * indexed(X, i) + indexed(X, j) * 2;
+ cout << e.simplify_indexed() << endl;
+ // -> [[3*y+3*x,6*y+2*x]].j
+@}
+@end example
+
+You can of course obtain the same results with the @code{matrix::add()},
+@code{matrix::mul()} and @code{matrix::trace()} methods (@pxref{Matrices})
+but with indices you don't have to worry about transposing matrices.
+
+Matrix indices always start at 0 and their dimension must match the number
+of rows/columns of the matrix. Matrices with one row or one column are
+vectors and can have one or two indices (it doesn't matter whether it's a
+row or a column vector). Other matrices must have two indices.
+
+You should be careful when using indices with variance on matrices. GiNaC
+doesn't look at the variance and doesn't know that @samp{F~mu~nu} and
+@samp{F.mu.nu} are different matrices. In this case you should use only
+one form for @samp{F} and explicitly multiply it with a matrix representation
+of the metric tensor.
+
+
+@node Non-commutative objects, Methods and Functions, Indexed objects, Basic Concepts
+@c node-name, next, previous, up
+@section Non-commutative objects
+
+GiNaC is equipped to handle certain non-commutative algebras. Three classes of
+non-commutative objects are built-in which are mostly of use in high energy
+physics:
+
+@itemize
+@item Clifford (Dirac) algebra (class @code{clifford})
+@item su(3) Lie algebra (class @code{color})
+@item Matrices (unindexed) (class @code{matrix})
+@end itemize
+
+The @code{clifford} and @code{color} classes are subclasses of
+@code{indexed} because the elements of these algebras usually carry
+indices. The @code{matrix} class is described in more detail in
+@ref{Matrices}.
+
+Unlike most computer algebra systems, GiNaC does not primarily provide an
+operator (often denoted @samp{&*}) for representing inert products of
+arbitrary objects. Rather, non-commutativity in GiNaC is a property of the
+classes of objects involved, and non-commutative products are formed with
+the usual @samp{*} operator, as are ordinary products. GiNaC is capable of
+figuring out by itself which objects commute and will group the factors
+by their class. Consider this example:
+
+@example
+ ...
+ varidx mu(symbol("mu"), 4), nu(symbol("nu"), 4);
+ idx a(symbol("a"), 8), b(symbol("b"), 8);
+ ex e = -dirac_gamma(mu) * (2*color_T(a)) * 8 * color_T(b) * dirac_gamma(nu);
+ cout << e << endl;
+ // -> -16*(gamma~mu*gamma~nu)*(T.a*T.b)
+ ...
+@end example
+
+As can be seen, GiNaC pulls out the overall commutative factor @samp{-16} and
+groups the non-commutative factors (the gammas and the su(3) generators)
+together while preserving the order of factors within each class (because
+Clifford objects commute with color objects). The resulting expression is a
+@emph{commutative} product with two factors that are themselves non-commutative
+products (@samp{gamma~mu*gamma~nu} and @samp{T.a*T.b}). For clarification,
+parentheses are placed around the non-commutative products in the output.
+
+@cindex @code{ncmul} (class)
+Non-commutative products are internally represented by objects of the class
+@code{ncmul}, as opposed to commutative products which are handled by the
+@code{mul} class. You will normally not have to worry about this distinction,
+though.
+
+The advantage of this approach is that you never have to worry about using
+(or forgetting to use) a special operator when constructing non-commutative
+expressions. Also, non-commutative products in GiNaC are more intelligent
+than in other computer algebra systems; they can, for example, automatically
+canonicalize themselves according to rules specified in the implementation
+of the non-commutative classes. The drawback is that to work with other than
+the built-in algebras you have to implement new classes yourself. Symbols
+always commute and it's not possible to construct non-commutative products
+using symbols to represent the algebra elements or generators. User-defined
+functions can, however, be specified as being non-commutative.
+
+@cindex @code{return_type()}
+@cindex @code{return_type_tinfo()}
+Information about the commutativity of an object or expression can be
+obtained with the two member functions
+
+@example
+unsigned ex::return_type(void) const;
+unsigned ex::return_type_tinfo(void) const;
+@end example
+
+The @code{return_type()} function returns one of three values (defined in
+the header file @file{flags.h}), corresponding to three categories of
+expressions in GiNaC:
+
+@itemize
+@item @code{return_types::commutative}: Commutes with everything. Most GiNaC
+ classes are of this kind.
+@item @code{return_types::noncommutative}: Non-commutative, belonging to a
+ certain class of non-commutative objects which can be determined with the
+ @code{return_type_tinfo()} method. Expressions of this category commute
+ with everything except @code{noncommutative} expressions of the same
+ class.
+@item @code{return_types::noncommutative_composite}: Non-commutative, composed
+ of non-commutative objects of different classes. Expressions of this
+ category don't commute with any other @code{noncommutative} or
+ @code{noncommutative_composite} expressions.
+@end itemize
+
+The value returned by the @code{return_type_tinfo()} method is valid only
+when the return type of the expression is @code{noncommutative}. It is a
+value that is unique to the class of the object and usually one of the
+constants in @file{tinfos.h}, or derived therefrom.
+
+Here are a couple of examples:
+
+@cartouche
+@multitable @columnfractions 0.33 0.33 0.34
+@item @strong{Expression} @tab @strong{@code{return_type()}} @tab @strong{@code{return_type_tinfo()}}
+@item @code{42} @tab @code{commutative} @tab -
+@item @code{2*x-y} @tab @code{commutative} @tab -
+@item @code{dirac_ONE()} @tab @code{noncommutative} @tab @code{TINFO_clifford}
+@item @code{dirac_gamma(mu)*dirac_gamma(nu)} @tab @code{noncommutative} @tab @code{TINFO_clifford}
+@item @code{2*color_T(a)} @tab @code{noncommutative} @tab @code{TINFO_color}
+@item @code{dirac_ONE()*color_T(a)} @tab @code{noncommutative_composite} @tab -
+@end multitable
+@end cartouche
+
+Note: the @code{return_type_tinfo()} of Clifford objects is only equal to
+@code{TINFO_clifford} for objects with a representation label of zero.
+Other representation labels yield a different @code{return_type_tinfo()},
+but it's the same for any two objects with the same label. This is also true
+for color objects.
+
+A last note: With the exception of matrices, positive integer powers of
+non-commutative objects are automatically expanded in GiNaC. For example,
+@code{pow(a*b, 2)} becomes @samp{a*b*a*b} if @samp{a} and @samp{b} are
+non-commutative expressions).
+
+
+@cindex @code{clifford} (class)
+@subsection Clifford algebra
+
+@cindex @code{dirac_gamma()}
+Clifford algebra elements (also called Dirac gamma matrices, although GiNaC
+doesn't treat them as matrices) are designated as @samp{gamma~mu} and satisfy
+@samp{gamma~mu*gamma~nu + gamma~nu*gamma~mu = 2*eta~mu~nu} where @samp{eta~mu~nu}
+is the Minkowski metric tensor. Dirac gammas are constructed by the function
+
+@example
+ex dirac_gamma(const ex & mu, unsigned char rl = 0);
+@end example
+
+which takes two arguments: the index and a @dfn{representation label} in the
+range 0 to 255 which is used to distinguish elements of different Clifford
+algebras (this is also called a @dfn{spin line index}). Gammas with different
+labels commute with each other. The dimension of the index can be 4 or (in
+the framework of dimensional regularization) any symbolic value. Spinor
+indices on Dirac gammas are not supported in GiNaC.
+
+@cindex @code{dirac_ONE()}
+The unity element of a Clifford algebra is constructed by
+
+@example
+ex dirac_ONE(unsigned char rl = 0);
+@end example
+
+@strong{Note:} You must always use @code{dirac_ONE()} when referring to
+multiples of the unity element, even though it's customary to omit it.
+E.g. instead of @code{dirac_gamma(mu)*(dirac_slash(q,4)+m)} you have to
+write @code{dirac_gamma(mu)*(dirac_slash(q,4)+m*dirac_ONE())}. Otherwise,
+GiNaC will complain and/or produce incorrect results.
+
+@cindex @code{dirac_gamma5()}
+There is a special element @samp{gamma5} that commutes with all other
+gammas, has a unit square, and in 4 dimensions equals
+@samp{gamma~0 gamma~1 gamma~2 gamma~3}, provided by
+
+@example
+ex dirac_gamma5(unsigned char rl = 0);
+@end example
+
+@cindex @code{dirac_gammaL()}
+@cindex @code{dirac_gammaR()}
+The chiral projectors @samp{(1+/-gamma5)/2} are also available as proper
+objects, constructed by
+
+@example
+ex dirac_gammaL(unsigned char rl = 0);
+ex dirac_gammaR(unsigned char rl = 0);
+@end example
+
+They observe the relations @samp{gammaL^2 = gammaL}, @samp{gammaR^2 = gammaR},
+and @samp{gammaL gammaR = gammaR gammaL = 0}.
+
+@cindex @code{dirac_slash()}
+Finally, the function
+
+@example
+ex dirac_slash(const ex & e, const ex & dim, unsigned char rl = 0);
+@end example
+
+creates a term that represents a contraction of @samp{e} with the Dirac
+Lorentz vector (it behaves like a term of the form @samp{e.mu gamma~mu}
+with a unique index whose dimension is given by the @code{dim} argument).
+Such slashed expressions are printed with a trailing backslash, e.g. @samp{e\}.
+
+In products of dirac gammas, superfluous unity elements are automatically
+removed, squares are replaced by their values, and @samp{gamma5}, @samp{gammaL}
+and @samp{gammaR} are moved to the front.
+
+The @code{simplify_indexed()} function performs contractions in gamma strings,
+for example
+
+@example
+@{
+ ...
+ symbol a("a"), b("b"), D("D");
+ varidx mu(symbol("mu"), D);
+ ex e = dirac_gamma(mu) * dirac_slash(a, D)
+ * dirac_gamma(mu.toggle_variance());
+ cout << e << endl;
+ // -> gamma~mu*a\*gamma.mu
+ e = e.simplify_indexed();
+ cout << e << endl;
+ // -> -D*a\+2*a\
+ cout << e.subs(D == 4) << endl;
+ // -> -2*a\
+ ...
+@}
+@end example
+
+@cindex @code{dirac_trace()}
+To calculate the trace of an expression containing strings of Dirac gammas
+you use the function
+
+@example
+ex dirac_trace(const ex & e, unsigned char rl = 0, const ex & trONE = 4);
+@end example
+
+This function takes the trace of all gammas with the specified representation
+label; gammas with other labels are left standing. The last argument to
+@code{dirac_trace()} is the value to be returned for the trace of the unity
+element, which defaults to 4. The @code{dirac_trace()} function is a linear
+functional that is equal to the usual trace only in @math{D = 4} dimensions.
+In particular, the functional is not cyclic in @math{D != 4} dimensions when
+acting on expressions containing @samp{gamma5}, so it's not a proper trace.
+This @samp{gamma5} scheme is described in greater detail in
+@cite{The Role of gamma5 in Dimensional Regularization}.
+
+The value of the trace itself is also usually different in 4 and in
+@math{D != 4} dimensions:
+
+@example
+@{
+ // 4 dimensions
+ varidx mu(symbol("mu"), 4), nu(symbol("nu"), 4), rho(symbol("rho"), 4);
+ ex e = dirac_gamma(mu) * dirac_gamma(nu) *
+ dirac_gamma(mu.toggle_variance()) * dirac_gamma(rho);
+ cout << dirac_trace(e).simplify_indexed() << endl;
+ // -> -8*eta~rho~nu
+@}
+...
+@{
+ // D dimensions
+ symbol D("D");
+ varidx mu(symbol("mu"), D), nu(symbol("nu"), D), rho(symbol("rho"), D);
+ ex e = dirac_gamma(mu) * dirac_gamma(nu) *
+ dirac_gamma(mu.toggle_variance()) * dirac_gamma(rho);
+ cout << dirac_trace(e).simplify_indexed() << endl;
+ // -> 8*eta~rho~nu-4*eta~rho~nu*D
+@}
+@end example
+
+Here is an example for using @code{dirac_trace()} to compute a value that
+appears in the calculation of the one-loop vacuum polarization amplitude in
+QED:
+
+@example
+@{
+ symbol q("q"), l("l"), m("m"), ldotq("ldotq"), D("D");
+ varidx mu(symbol("mu"), D), nu(symbol("nu"), D);
+
+ scalar_products sp;
+ sp.add(l, l, pow(l, 2));
+ sp.add(l, q, ldotq);
+
+ ex e = dirac_gamma(mu) *
+ (dirac_slash(l, D) + dirac_slash(q, D) + m * dirac_ONE()) *
+ dirac_gamma(mu.toggle_variance()) *
+ (dirac_slash(l, D) + m * dirac_ONE());
+ e = dirac_trace(e).simplify_indexed(sp);
+ e = e.collect(lst(l, ldotq, m));
+ cout << e << endl;
+ // -> (8-4*D)*l^2+(8-4*D)*ldotq+4*D*m^2
+@}
+@end example
+
+The @code{canonicalize_clifford()} function reorders all gamma products that
+appear in an expression to a canonical (but not necessarily simple) form.
+You can use this to compare two expressions or for further simplifications:
+
+@example
+@{
+ varidx mu(symbol("mu"), 4), nu(symbol("nu"), 4);
+ ex e = dirac_gamma(mu) * dirac_gamma(nu) + dirac_gamma(nu) * dirac_gamma(mu);
+ cout << e << endl;
+ // -> gamma~mu*gamma~nu+gamma~nu*gamma~mu
+
+ e = canonicalize_clifford(e);
+ cout << e << endl;
+ // -> 2*eta~mu~nu
+@}
+@end example
+
+
+@cindex @code{color} (class)
+@subsection Color algebra
+
+@cindex @code{color_T()}
+For computations in quantum chromodynamics, GiNaC implements the base elements
+and structure constants of the su(3) Lie algebra (color algebra). The base
+elements @math{T_a} are constructed by the function
+
+@example
+ex color_T(const ex & a, unsigned char rl = 0);
+@end example
+
+which takes two arguments: the index and a @dfn{representation label} in the
+range 0 to 255 which is used to distinguish elements of different color
+algebras. Objects with different labels commute with each other. The
+dimension of the index must be exactly 8 and it should be of class @code{idx},
+not @code{varidx}.
+
+@cindex @code{color_ONE()}
+The unity element of a color algebra is constructed by
+
+@example
+ex color_ONE(unsigned char rl = 0);
+@end example
+
+@strong{Note:} You must always use @code{color_ONE()} when referring to
+multiples of the unity element, even though it's customary to omit it.
+E.g. instead of @code{color_T(a)*(color_T(b)*indexed(X,b)+1)} you have to
+write @code{color_T(a)*(color_T(b)*indexed(X,b)+color_ONE())}. Otherwise,
+GiNaC may produce incorrect results.
+
+@cindex @code{color_d()}
+@cindex @code{color_f()}
+The functions
+
+@example
+ex color_d(const ex & a, const ex & b, const ex & c);
+ex color_f(const ex & a, const ex & b, const ex & c);
+@end example
+
+create the symmetric and antisymmetric structure constants @math{d_abc} and
+@math{f_abc} which satisfy @math{@{T_a, T_b@} = 1/3 delta_ab + d_abc T_c}
+and @math{[T_a, T_b] = i f_abc T_c}.
+
+@cindex @code{color_h()}
+There's an additional function
+
+@example
+ex color_h(const ex & a, const ex & b, const ex & c);
+@end example
+
+which returns the linear combination @samp{color_d(a, b, c)+I*color_f(a, b, c)}.
+
+The function @code{simplify_indexed()} performs some simplifications on
+expressions containing color objects:
@example
@{
- idx i(symbol("i"), 2), j(symbol("j"), 2);
- symbol x("x"), y("y");
+ ...
+ idx a(symbol("a"), 8), b(symbol("b"), 8), c(symbol("c"), 8),
+ k(symbol("k"), 8), l(symbol("l"), 8);
- matrix A(2, 2, lst(1, 2, 3, 4)), X(2, 1, lst(x, y));
+ e = color_d(a, b, l) * color_f(a, b, k);
+ cout << e.simplify_indexed() << endl;
+ // -> 0
- cout << indexed(A, i, i) << endl;
- // -> 5
+ e = color_d(a, b, l) * color_d(a, b, k);
+ cout << e.simplify_indexed() << endl;
+ // -> 5/3*delta.k.l
- ex e = indexed(A, i, j) * indexed(X, j);
+ e = color_f(l, a, b) * color_f(a, b, k);
cout << e.simplify_indexed() << endl;
- // -> [[ [[2*y+x]], [[4*y+3*x]] ]].i
+ // -> 3*delta.k.l
- e = indexed(A, i, j) * indexed(X, i) + indexed(X, j) * 2;
+ e = color_h(a, b, c) * color_h(a, b, c);
cout << e.simplify_indexed() << endl;
- // -> [[ [[3*y+3*x,6*y+2*x]] ]].j
-@}
+ // -> -32/3
+
+ e = color_h(a, b, c) * color_T(b) * color_T(c);
+ cout << e.simplify_indexed() << endl;
+ // -> -2/3*T.a
+
+ e = color_h(a, b, c) * color_T(a) * color_T(b) * color_T(c);
+ cout << e.simplify_indexed() << endl;
+ // -> -8/9*ONE
+
+ e = color_T(k) * color_T(a) * color_T(b) * color_T(k);
+ cout << e.simplify_indexed() << endl;
+ // -> 1/4*delta.b.a*ONE-1/6*T.a*T.b
+ ...
@end example
-You can of course obtain the same results with the @code{matrix::add()},
-@code{matrix::mul()} and @code{matrix::trace()} methods but with indices you
-don't have to worry about transposing matrices.
+@cindex @code{color_trace()}
+To calculate the trace of an expression containing color objects you use the
+function
-Matrix indices always start at 0 and their dimension must match the number
-of rows/columns of the matrix. Matrices with one row or one column are
-vectors and can have one or two indices (it doesn't matter whether it's a
-row or a column vector). Other matrices must have two indices.
+@example
+ex color_trace(const ex & e, unsigned char rl = 0);
+@end example
-You should be careful when using indices with variance on matrices. GiNaC
-doesn't look at the variance and doesn't know that @samp{F~mu~nu} and
-@samp{F.mu.nu} are different matrices. In this case you should use only
-one form for @samp{F} and explicitly multiply it with a matrix representation
-of the metric tensor.
+This function takes the trace of all color @samp{T} objects with the
+specified representation label; @samp{T}s with other labels are left
+standing. For example:
+
+@example
+ ...
+ e = color_trace(4 * color_T(a) * color_T(b) * color_T(c));
+ cout << e << endl;
+ // -> -I*f.a.c.b+d.a.c.b
+@}
+@end example
-@node Methods and Functions, Information About Expressions, Indexed objects, Top
+@node Methods and Functions, Information About Expressions, Non-commutative objects, Top
@c node-name, next, previous, up
@chapter Methods and Functions
@cindex polynomial
@menu
* Information About Expressions::
* Substituting Expressions::
+* Pattern Matching and Advanced Substitutions::
+* Applying a Function on Subexpressions::
* Polynomial Arithmetic:: Working with polynomials.
* Rational Expressions:: Working with rational functions.
* Symbolic Differentiation::
* Series Expansion:: Taylor and Laurent expansion.
+* Symmetrization::
* Built-in Functions:: List of predefined mathematical functions.
* Input/Output:: Input and output of expressions.
@end menu
@section Getting information about expressions
@subsection Checking expression types
-@cindex @code{is_ex_of_type()}
-@cindex @code{ex_to_numeric()}
-@cindex @code{ex_to_@dots{}}
-@cindex @code{Converting ex to other classes}
+@cindex @code{is_a<@dots{}>()}
+@cindex @code{is_exactly_a<@dots{}>()}
+@cindex @code{ex_to<@dots{}>()}
+@cindex Converting @code{ex} to other classes
@cindex @code{info()}
+@cindex @code{return_type()}
+@cindex @code{return_type_tinfo()}
Sometimes it's useful to check whether a given expression is a plain number,
a sum, a polynomial with integer coefficients, or of some other specific type.
-GiNaC provides two functions for this (the first one is actually a macro):
+GiNaC provides a couple of functions for this:
@example
-bool is_ex_of_type(const ex & e, TYPENAME t);
+bool is_a<T>(const ex & e);
+bool is_exactly_a<T>(const ex & e);
bool ex::info(unsigned flag);
+unsigned ex::return_type(void) const;
+unsigned ex::return_type_tinfo(void) const;
@end example
-When the test made by @code{is_ex_of_type()} returns true, it is safe to
-call one of the functions @code{ex_to_@dots{}}, where @code{@dots{}} is
-one of the class names (@xref{The Class Hierarchy}, for a list of all
-classes). For example, assuming @code{e} is an @code{ex}:
+When the test made by @code{is_a<T>()} returns true, it is safe to call
+one of the functions @code{ex_to<T>()}, where @code{T} is one of the
+class names (@xref{The Class Hierarchy}, for a list of all classes). For
+example, assuming @code{e} is an @code{ex}:
@example
@{
@dots{}
- if (is_ex_of_type(e, numeric))
- numeric n = ex_to_numeric(e);
+ if (is_a<numeric>(e))
+ numeric n = ex_to<numeric>(e);
@dots{}
@}
@end example
-@code{is_ex_of_type()} allows you to check whether the top-level object of
-an expression @samp{e} is an instance of the GiNaC class @samp{t}
+@code{is_a<T>(e)} allows you to check whether the top-level object of
+an expression @samp{e} is an instance of the GiNaC class @samp{T}
(@xref{The Class Hierarchy}, for a list of all classes). This is most useful,
e.g., for checking whether an expression is a number, a sum, or a product:
symbol x("x");
ex e1 = 42;
ex e2 = 4*x - 3;
- is_ex_of_type(e1, numeric); // true
- is_ex_of_type(e2, numeric); // false
- is_ex_of_type(e1, add); // false
- is_ex_of_type(e2, add); // true
- is_ex_of_type(e1, mul); // false
- is_ex_of_type(e2, mul); // false
+ is_a<numeric>(e1); // true
+ is_a<numeric>(e2); // false
+ is_a<add>(e1); // false
+ is_a<add>(e2); // true
+ is_a<mul>(e1); // false
+ is_a<mul>(e2); // false
@}
@end example
+In contrast, @code{is_exactly_a<T>(e)} allows you to check whether the
+top-level object of an expression @samp{e} is an instance of the GiNaC
+class @samp{T}, not including parent classes.
+
The @code{info()} method is used for checking certain attributes of
expressions. The possible values for the @code{flag} argument are defined
in @file{ginac/flags.h}, the most important being explained in the following
@multitable @columnfractions .30 .70
@item @strong{Flag} @tab @strong{Returns true if the object is@dots{}}
@item @code{numeric}
-@tab @dots{}a number (same as @code{is_ex_of_type(..., numeric)})
+@tab @dots{}a number (same as @code{is_<numeric>(...)})
@item @code{real}
@tab @dots{}a real integer, rational or float (i.e. is not complex)
@item @code{rational}
@item @code{prime}
@tab @dots{}a prime integer (probabilistic primality test)
@item @code{relation}
-@tab @dots{}a relation (same as @code{is_ex_of_type(..., relational)})
+@tab @dots{}a relation (same as @code{is_a<relational>(...)})
@item @code{relation_equal}
@tab @dots{}a @code{==} relation
@item @code{relation_not_equal}
@item @code{relation_greater_or_equal}
@tab @dots{}a @code{>=} relation
@item @code{symbol}
-@tab @dots{}a symbol (same as @code{is_ex_of_type(..., symbol)})
+@tab @dots{}a symbol (same as @code{is_a<symbol>(...)})
@item @code{list}
-@tab @dots{}a list (same as @code{is_ex_of_type(..., lst)})
+@tab @dots{}a list (same as @code{is_a<lst>(...)})
@item @code{polynomial}
@tab @dots{}a polynomial (i.e. only consists of sums and products of numbers and symbols with positive integer powers)
@item @code{integer_polynomial}
@end multitable
@end cartouche
+To determine whether an expression is commutative or non-commutative and if
+so, with which other expressions it would commute, you use the methods
+@code{return_type()} and @code{return_type_tinfo()}. @xref{Non-commutative objects},
+for an explanation of these.
+
@subsection Accessing subexpressions
@cindex @code{nops()}
@cindex @code{op()}
-@cindex @code{has()}
@cindex container
@cindex @code{relational} (class)
ex ex::rhs();
@end example
-Finally, the method
-
-@example
-bool ex::has(const ex & other);
-@end example
-
-checks whether an expression contains the given subexpression @code{other}.
-This only works reliably if @code{other} is of an atomic class such as a
-@code{numeric} or a @code{symbol}. It is, e.g., not possible to verify that
-@code{a+b+c} contains @code{a+c} (or @code{a+b}) as a subexpression.
-
@subsection Comparing expressions
@cindex @code{is_equal()}
@code{false}.
Actually, if you construct an expression like @code{a == b}, this will be
-represented by an object of the @code{relational} class (@xref{Relations}.)
-which is not evaluated until (explicitly or implicitely) cast to a @code{bool}.
+represented by an object of the @code{relational} class (@pxref{Relations})
+which is not evaluated until (explicitly or implicitly) cast to a @code{bool}.
There are also two methods
expressions will give very surprising results.
-@node Substituting Expressions, Polynomial Arithmetic, Information About Expressions, Methods and Functions
+@node Substituting Expressions, Pattern Matching and Advanced Substitutions, Information About Expressions, Methods and Functions
@c node-name, next, previous, up
@section Substituting expressions
@cindex @code{subs()}
@}
@end example
+If you specify multiple substitutions, they are performed in parallel, so e.g.
+@code{subs(lst(x == y, y == x))} exchanges @samp{x} and @samp{y}.
+
+The second form of @code{subs()} takes two lists, one for the objects to be
+replaced and one for the expressions to be substituted (both lists must
+contain the same number of elements). Using this form, you would write
+@code{subs(lst(x, y), lst(y, x))} to exchange @samp{x} and @samp{y}.
+
@code{subs()} performs syntactic substitution of any complete algebraic
object; it does not try to match sub-expressions as is demonstrated by the
following example:
cout << e1.subs(x+y == 4) << endl;
// -> 16
- ex e2 = sin(x)*cos(x);
+ ex e2 = sin(x)*sin(y)*cos(x);
cout << e2.subs(sin(x) == cos(x)) << endl;
- // -> cos(x)^2
+ // -> cos(x)^2*sin(y)
ex e3 = x+y+z;
cout << e3.subs(x+y == 4) << endl;
@}
@end example
-If you specify multiple substitutions, they are performed in parallel, so e.g.
-@code{subs(lst(x == y, y == x))} exchanges @samp{x} and @samp{y}.
+A more powerful form of substitution using wildcards is described in the
+next section.
-The second form of @code{subs()} takes two lists, one for the objects to be
-replaced and one for the expressions to be substituted (both lists must
-contain the same number of elements). Using this form, you would write
-@code{subs(lst(x, y), lst(y, x))} to exchange @samp{x} and @samp{y}.
+
+@node Pattern Matching and Advanced Substitutions, Applying a Function on Subexpressions, Substituting Expressions, Methods and Functions
+@c node-name, next, previous, up
+@section Pattern matching and advanced substitutions
+@cindex @code{wildcard} (class)
+@cindex Pattern matching
+
+GiNaC allows the use of patterns for checking whether an expression is of a
+certain form or contains subexpressions of a certain form, and for
+substituting expressions in a more general way.
+
+A @dfn{pattern} is an algebraic expression that optionally contains wildcards.
+A @dfn{wildcard} is a special kind of object (of class @code{wildcard}) that
+represents an arbitrary expression. Every wildcard has a @dfn{label} which is
+an unsigned integer number to allow having multiple different wildcards in a
+pattern. Wildcards are printed as @samp{$label} (this is also the way they
+are specified in @command{ginsh}). In C++ code, wildcard objects are created
+with the call
+
+@example
+ex wild(unsigned label = 0);
+@end example
+
+which is simply a wrapper for the @code{wildcard()} constructor with a shorter
+name.
+
+Some examples for patterns:
+
+@multitable @columnfractions .5 .5
+@item @strong{Constructed as} @tab @strong{Output as}
+@item @code{wild()} @tab @samp{$0}
+@item @code{pow(x,wild())} @tab @samp{x^$0}
+@item @code{atan2(wild(1),wild(2))} @tab @samp{atan2($1,$2)}
+@item @code{indexed(A,idx(wild(),3))} @tab @samp{A.$0}
+@end multitable
+
+Notes:
+
+@itemize
+@item Wildcards behave like symbols and are subject to the same algebraic
+ rules. E.g., @samp{$0+2*$0} is automatically transformed to @samp{3*$0}.
+@item As shown in the last example, to use wildcards for indices you have to
+ use them as the value of an @code{idx} object. This is because indices must
+ always be of class @code{idx} (or a subclass).
+@item Wildcards only represent expressions or subexpressions. It is not
+ possible to use them as placeholders for other properties like index
+ dimension or variance, representation labels, symmetry of indexed objects
+ etc.
+@item Because wildcards are commutative, it is not possible to use wildcards
+ as part of noncommutative products.
+@item A pattern does not have to contain wildcards. @samp{x} and @samp{x+y}
+ are also valid patterns.
+@end itemize
+
+@subsection Matching expressions
+@cindex @code{match()}
+The most basic application of patterns is to check whether an expression
+matches a given pattern. This is done by the function
+
+@example
+bool ex::match(const ex & pattern);
+bool ex::match(const ex & pattern, lst & repls);
+@end example
+
+This function returns @code{true} when the expression matches the pattern
+and @code{false} if it doesn't. If used in the second form, the actual
+subexpressions matched by the wildcards get returned in the @code{repls}
+object as a list of relations of the form @samp{wildcard == expression}.
+If @code{match()} returns false, the state of @code{repls} is undefined.
+For reproducible results, the list should be empty when passed to
+@code{match()}, but it is also possible to find similarities in multiple
+expressions by passing in the result of a previous match.
+
+The matching algorithm works as follows:
+
+@itemize
+@item A single wildcard matches any expression. If one wildcard appears
+ multiple times in a pattern, it must match the same expression in all
+ places (e.g. @samp{$0} matches anything, and @samp{$0*($0+1)} matches
+ @samp{x*(x+1)} but not @samp{x*(y+1)}).
+@item If the expression is not of the same class as the pattern, the match
+ fails (i.e. a sum only matches a sum, a function only matches a function,
+ etc.).
+@item If the pattern is a function, it only matches the same function
+ (i.e. @samp{sin($0)} matches @samp{sin(x)} but doesn't match @samp{exp(x)}).
+@item Except for sums and products, the match fails if the number of
+ subexpressions (@code{nops()}) is not equal to the number of subexpressions
+ of the pattern.
+@item If there are no subexpressions, the expressions and the pattern must
+ be equal (in the sense of @code{is_equal()}).
+@item Except for sums and products, each subexpression (@code{op()}) must
+ match the corresponding subexpression of the pattern.
+@end itemize
+
+Sums (@code{add}) and products (@code{mul}) are treated in a special way to
+account for their commutativity and associativity:
+
+@itemize
+@item If the pattern contains a term or factor that is a single wildcard,
+ this one is used as the @dfn{global wildcard}. If there is more than one
+ such wildcard, one of them is chosen as the global wildcard in a random
+ way.
+@item Every term/factor of the pattern, except the global wildcard, is
+ matched against every term of the expression in sequence. If no match is
+ found, the whole match fails. Terms that did match are not considered in
+ further matches.
+@item If there are no unmatched terms left, the match succeeds. Otherwise
+ the match fails unless there is a global wildcard in the pattern, in
+ which case this wildcard matches the remaining terms.
+@end itemize
+
+In general, having more than one single wildcard as a term of a sum or a
+factor of a product (such as @samp{a+$0+$1}) will lead to unpredictable or
+ambiguous results.
+
+Here are some examples in @command{ginsh} to demonstrate how it works (the
+@code{match()} function in @command{ginsh} returns @samp{FAIL} if the
+match fails, and the list of wildcard replacements otherwise):
+
+@example
+> match((x+y)^a,(x+y)^a);
+@{@}
+> match((x+y)^a,(x+y)^b);
+FAIL
+> match((x+y)^a,$1^$2);
+@{$1==x+y,$2==a@}
+> match((x+y)^a,$1^$1);
+FAIL
+> match((x+y)^(x+y),$1^$1);
+@{$1==x+y@}
+> match((x+y)^(x+y),$1^$2);
+@{$1==x+y,$2==x+y@}
+> match((a+b)*(a+c),($1+b)*($1+c));
+@{$1==a@}
+> match((a+b)*(a+c),(a+$1)*(a+$2));
+@{$1==c,$2==b@}
+ (Unpredictable. The result might also be [$1==c,$2==b].)
+> match((a+b)*(a+c),($1+$2)*($1+$3));
+ (The result is undefined. Due to the sequential nature of the algorithm
+ and the re-ordering of terms in GiNaC, the match for the first factor
+ may be @{$1==a,$2==b@} in which case the match for the second factor
+ succeeds, or it may be @{$1==b,$2==a@} which causes the second match to
+ fail.)
+> match(a*(x+y)+a*z+b,a*$1+$2);
+ (This is also ambiguous and may return either @{$1==z,$2==a*(x+y)+b@} or
+ @{$1=x+y,$2=a*z+b@}.)
+> match(a+b+c+d+e+f,c);
+FAIL
+> match(a+b+c+d+e+f,c+$0);
+@{$0==a+e+b+f+d@}
+> match(a+b+c+d+e+f,c+e+$0);
+@{$0==a+b+f+d@}
+> match(a+b,a+b+$0);
+@{$0==0@}
+> match(a*b^2,a^$1*b^$2);
+FAIL
+ (The matching is syntactic, not algebraic, and "a" doesn't match "a^$1"
+ even though a==a^1.)
+> match(x*atan2(x,x^2),$0*atan2($0,$0^2));
+@{$0==x@}
+> match(atan2(y,x^2),atan2(y,$0));
+@{$0==x^2@}
+@end example
+
+@subsection Matching parts of expressions
+@cindex @code{has()}
+A more general way to look for patterns in expressions is provided by the
+member function
+
+@example
+bool ex::has(const ex & pattern);
+@end example
+
+This function checks whether a pattern is matched by an expression itself or
+by any of its subexpressions.
+
+Again some examples in @command{ginsh} for illustration (in @command{ginsh},
+@code{has()} returns @samp{1} for @code{true} and @samp{0} for @code{false}):
+
+@example
+> has(x*sin(x+y+2*a),y);
+1
+> has(x*sin(x+y+2*a),x+y);
+0
+ (This is because in GiNaC, "x+y" is not a subexpression of "x+y+2*a" (which
+ has the subexpressions "x", "y" and "2*a".)
+> has(x*sin(x+y+2*a),x+y+$1);
+1
+ (But this is possible.)
+> has(x*sin(2*(x+y)+2*a),x+y);
+0
+ (This fails because "2*(x+y)" automatically gets converted to "2*x+2*y" of
+ which "x+y" is not a subexpression.)
+> has(x+1,x^$1);
+0
+ (Although x^1==x and x^0==1, neither "x" nor "1" are actually of the form
+ "x^something".)
+> has(4*x^2-x+3,$1*x);
+1
+> has(4*x^2+x+3,$1*x);
+0
+ (Another possible pitfall. The first expression matches because the term
+ "-x" has the form "(-1)*x" in GiNaC. To check whether a polynomial
+ contains a linear term you should use the coeff() function instead.)
+@end example
+
+@cindex @code{find()}
+The method
+
+@example
+bool ex::find(const ex & pattern, lst & found);
+@end example
+
+works a bit like @code{has()} but it doesn't stop upon finding the first
+match. Instead, it inserts all found matches into the specified list. If
+there are multiple occurrences of the same expression, it is entered only
+once to the list. @code{find()} returns false if no matches were found (in
+@command{ginsh}, it returns an empty list):
+
+@example
+> find(1+x+x^2+x^3,x);
+@{x@}
+> find(1+x+x^2+x^3,y);
+@{@}
+> find(1+x+x^2+x^3,x^$1);
+@{x^3,x^2@}
+ (Note the absence of "x".)
+> expand((sin(x)+sin(y))*(a+b));
+sin(y)*a+sin(x)*b+sin(x)*a+sin(y)*b
+> find(%,sin($1));
+@{sin(y),sin(x)@}
+@end example
+
+@subsection Substituting expressions
+@cindex @code{subs()}
+Probably the most useful application of patterns is to use them for
+substituting expressions with the @code{subs()} method. Wildcards can be
+used in the search patterns as well as in the replacement expressions, where
+they get replaced by the expressions matched by them. @code{subs()} doesn't
+know anything about algebra; it performs purely syntactic substitutions.
+
+Some examples:
+
+@example
+> subs(a^2+b^2+(x+y)^2,$1^2==$1^3);
+b^3+a^3+(x+y)^3
+> subs(a^4+b^4+(x+y)^4,$1^2==$1^3);
+b^4+a^4+(x+y)^4
+> subs((a+b+c)^2,a+b==x);
+(a+b+c)^2
+> subs((a+b+c)^2,a+b+$1==x+$1);
+(x+c)^2
+> subs(a+2*b,a+b==x);
+a+2*b
+> subs(4*x^3-2*x^2+5*x-1,x==a);
+-1+5*a-2*a^2+4*a^3
+> subs(4*x^3-2*x^2+5*x-1,x^$0==a^$0);
+-1+5*x-2*a^2+4*a^3
+> subs(sin(1+sin(x)),sin($1)==cos($1));
+cos(1+cos(x))
+> expand(subs(a*sin(x+y)^2+a*cos(x+y)^2+b,cos($1)^2==1-sin($1)^2));
+a+b
+@end example
+
+The last example would be written in C++ in this way:
+
+@example
+@{
+ symbol a("a"), b("b"), x("x"), y("y");
+ e = a*pow(sin(x+y), 2) + a*pow(cos(x+y), 2) + b;
+ e = e.subs(pow(cos(wild()), 2) == 1-pow(sin(wild()), 2));
+ cout << e.expand() << endl;
+ // -> a+b
+@}
+@end example
+
+
+@node Applying a Function on Subexpressions, Polynomial Arithmetic, Pattern Matching and Advanced Substitutions, Methods and Functions
+@c node-name, next, previous, up
+@section Applying a Function on Subexpressions
+@cindex Tree traversal
+@cindex @code{map()}
+
+Sometimes you may want to perform an operation on specific parts of an
+expression while leaving the general structure of it intact. An example
+of this would be a matrix trace operation: the trace of a sum is the sum
+of the traces of the individual terms. That is, the trace should @dfn{map}
+on the sum, by applying itself to each of the sum's operands. It is possible
+to do this manually which usually results in code like this:
+
+@example
+ex calc_trace(ex e)
+@{
+ if (is_a<matrix>(e))
+ return ex_to<matrix>(e).trace();
+ else if (is_a<add>(e)) @{
+ ex sum = 0;
+ for (unsigned i=0; i<e.nops(); i++)
+ sum += calc_trace(e.op(i));
+ return sum;
+ @} else if (is_a<mul>)(e)) @{
+ ...
+ @} else @{
+ ...
+ @}
+@}
+@end example
+
+This is, however, slightly inefficient (if the sum is very large it can take
+a long time to add the terms one-by-one), and its applicability is limited to
+a rather small class of expressions. If @code{calc_trace()} is called with
+a relation or a list as its argument, you will probably want the trace to
+be taken on both sides of the relation or of all elements of the list.
+
+GiNaC offers the @code{map()} method to aid in the implementation of such
+operations:
+
+@example
+ex ex::map(map_function & f) const;
+ex ex::map(ex (*f)(const ex & e)) const;
+@end example
+
+In the first (preferred) form, @code{map()} takes a function object that
+is subclassed from the @code{map_function} class. In the second form, it
+takes a pointer to a function that accepts and returns an expression.
+@code{map()} constructs a new expression of the same type, applying the
+specified function on all subexpressions (in the sense of @code{op()}),
+non-recursively.
+
+The use of a function object makes it possible to supply more arguments to
+the function that is being mapped, or to keep local state information.
+The @code{map_function} class declares a virtual function call operator
+that you can overload. Here is a sample implementation of @code{calc_trace()}
+that uses @code{map()} in a recursive fashion:
+
+@example
+struct calc_trace : public map_function @{
+ ex operator()(const ex &e)
+ @{
+ if (is_a<matrix>(e))
+ return ex_to<matrix>(e).trace();
+ else if (is_a<mul>(e)) @{
+ ...
+ @} else
+ return e.map(*this);
+ @}
+@};
+@end example
+
+This function object could then be used like this:
+
+@example
+@{
+ ex M = ... // expression with matrices
+ calc_trace do_trace;
+ ex tr = do_trace(M);
+@}
+@end example
+
+Here is another example for you to meditate over. It removes quadratic
+terms in a variable from an expanded polynomial:
+
+@example
+struct map_rem_quad : public map_function @{
+ ex var;
+ map_rem_quad(const ex & var_) : var(var_) @{@}
+
+ ex operator()(const ex & e)
+ @{
+ if (is_a<add>(e) || is_a<mul>(e))
+ return e.map(*this);
+ else if (is_a<power>(e) &&
+ e.op(0).is_equal(var) && e.op(1).info(info_flags::even))
+ return 0;
+ else
+ return e;
+ @}
+@};
+
+...
+
+@{
+ symbol x("x"), y("y");
+
+ ex e;
+ for (int i=0; i<8; i++)
+ e += pow(x, i) * pow(y, 8-i) * (i+1);
+ cout << e << endl;
+ // -> 4*y^5*x^3+5*y^4*x^4+8*y*x^7+7*y^2*x^6+2*y^7*x+6*y^3*x^5+3*y^6*x^2+y^8
+
+ map_rem_quad rem_quad(x);
+ cout << rem_quad(e) << endl;
+ // -> 4*y^5*x^3+8*y*x^7+2*y^7*x+6*y^3*x^5+y^8
+@}
+@end example
+
+@command{ginsh} offers a slightly different implementation of @code{map()}
+that allows applying algebraic functions to operands. The second argument
+to @code{map()} is an expression containing the wildcard @samp{$0} which
+acts as the placeholder for the operands:
+
+@example
+> map(a*b,sin($0));
+sin(a)*sin(b)
+> map(a+2*b,sin($0));
+sin(a)+sin(2*b)
+> map(@{a,b,c@},$0^2+$0);
+@{a^2+a,b^2+b,c^2+c@}
+@end example
+
+Note that it is only possible to use algebraic functions in the second
+argument. You can not use functions like @samp{diff()}, @samp{op()},
+@samp{subs()} etc. because these are evaluated immediately:
+
+@example
+> map(@{a,b,c@},diff($0,a));
+@{0,0,0@}
+ This is because "diff($0,a)" evaluates to "0", so the command is equivalent
+ to "map(@{a,b,c@},0)".
+@end example
-@node Polynomial Arithmetic, Rational Expressions, Substituting Expressions, Methods and Functions
+@node Polynomial Arithmetic, Rational Expressions, Applying a Function on Subexpressions, Methods and Functions
@c node-name, next, previous, up
@section Polynomial arithmetic
@subsection Expanding and collecting
@cindex @code{expand()}
@cindex @code{collect()}
+@cindex @code{collect_common_factors()}
A polynomial in one or more variables has many equivalent
representations. Some useful ones serve a specific purpose. Consider
representations are the recursive ones where one collects for exponents
in one of the three variable. Since the factors are themselves
polynomials in the remaining two variables the procedure can be
-repeated. In our expample, two possibilities would be @math{(4*y + z)*x
+repeated. In our example, two possibilities would be @math{(4*y + z)*x
+ 20*y^2 + 21*y*z + 4*z^2} and @math{20*y^2 + (21*z + 4*x)*y + 4*z^2 +
x*z}.
@code{collect()} accomplishes this task:
@example
-ex ex::collect(const ex & s);
+ex ex::collect(const ex & s, bool distributed = false);
+@end example
+
+The first argument to @code{collect()} can also be a list of objects in which
+case the result is either a recursively collected polynomial, or a polynomial
+in a distributed form with terms like @math{c*x1^e1*...*xn^en}, as specified
+by the @code{distributed} flag.
+
+Note that the original polynomial needs to be in expanded form (for the
+variables concerned) in order for @code{collect()} to be able to find the
+coefficients properly.
+
+The following @command{ginsh} transcript shows an application of @code{collect()}
+together with @code{find()}:
+
+@example
+> a=expand((sin(x)+sin(y))*(1+p+q)*(1+d));
+d*p*sin(x)+p*sin(x)+q*d*sin(x)+q*sin(y)+d*sin(x)+q*d*sin(y)+sin(y)+d*sin(y)+q*sin(x)+d*sin(y)*p+sin(x)+sin(y)*p
+> collect(a,@{p,q@});
+d*sin(x)+(d*sin(x)+sin(y)+d*sin(y)+sin(x))*p+(d*sin(x)+sin(y)+d*sin(y)+sin(x))*q+sin(y)+d*sin(y)+sin(x)
+> collect(a,find(a,sin($1)));
+(1+q+d+q*d+d*p+p)*sin(y)+(1+q+d+q*d+d*p+p)*sin(x)
+> collect(a,@{find(a,sin($1)),p,q@});
+(1+(1+d)*p+d+q*(1+d))*sin(x)+(1+(1+d)*p+d+q*(1+d))*sin(y)
+> collect(a,@{find(a,sin($1)),d@});
+(1+q+d*(1+q+p)+p)*sin(y)+(1+q+d*(1+q+p)+p)*sin(x)
@end example
-Note that the original polynomial needs to be in expanded form in order
-to be able to find the coefficients properly.
+Polynomials can often be brought into a more compact form by collecting
+common factors from the terms of sums. This is accomplished by the function
+
+@example
+ex collect_common_factors(const ex & e);
+@end example
+
+This function doesn't perform a full factorization but only looks for
+factors which are already explicitly present:
+
+@example
+> collect_common_factors(a*x+a*y);
+(x+y)*a
+> collect_common_factors(a*x^2+2*a*x*y+a*y^2);
+a*(2*x*y+y^2+x^2)
+> collect_common_factors(a*(b*(a+c)*x+b*((a+c)*x+(a+c)*y)*y));
+(c+a)*a*(x*y+y^2+x)*b
+@end example
@subsection Degree and coefficients
@cindex @code{degree()}
int ex::ldegree(const ex & s);
@end example
-which also work reliably on non-expanded input polynomials (they even work
-on rational functions, returning the asymptotic degree). To extract
-a coefficient with a certain power from an expanded polynomial you use
+These functions only work reliably if the input polynomial is collected in
+terms of the object @samp{s}. Otherwise, they are only guaranteed to return
+the upper/lower bounds of the exponents. If you need accurate results, you
+have to call @code{expand()} and/or @code{collect()} on the input polynomial.
+For example
+
+@example
+> a=(x+1)^2-x^2;
+(1+x)^2-x^2;
+> degree(a,x);
+2
+> degree(expand(a),x);
+1
+@end example
+
+@code{degree()} also works on rational functions, returning the asymptotic
+degree:
+
+@example
+> degree((x+1)/(x^3+1),x);
+-2
+@end example
+
+If the input is not a polynomial or rational function in the variable @samp{s},
+the behavior of @code{degree()} and @code{ldegree()} is undefined.
+
+To extract a coefficient with a certain power from an expanded
+polynomial you use
@example
ex ex::coeff(const ex & s, int n);
polynomial is analyzed:
@example
-#include <ginac/ginac.h>
-using namespace std;
-using namespace GiNaC;
-
-int main()
@{
symbol x("x"), y("y");
ex PolyInp = 4*pow(x,3)*y + 5*x*pow(y,2) + 3*y
factorization is, however, easily implemented by noting that factors
appearing in a polynomial with power two or more also appear in the
derivative and hence can easily be found by computing the GCD of the
-original polynomial and its derivatives. Any system has an interface
-for this so called square-free factorization. So we provide one, too:
+original polynomial and its derivatives. Any decent system has an
+interface for this so called square-free factorization. So we provide
+one, too:
@example
ex sqrfree(const ex & a, const lst & l = lst());
@end example
-Here is an example that by the way illustrates how the result may depend
-on the order of differentiation:
+Here is an example that by the way illustrates how the exact form of the
+result may slightly depend on the order of differentiation, calling for
+some care with subsequent processing of the result:
@example
...
symbol x("x"), y("y");
- ex BiVarPol = expand(pow(x-2*y*x,3) * pow(x+y,2) * (x-y));
+ ex BiVarPol = expand(pow(2-2*y,3) * pow(1+x*y,2) * pow(x-2*y,2) * (x+y));
cout << sqrfree(BiVarPol, lst(x,y)) << endl;
- // -> (y+x)^2*(-1+6*y+8*y^3-12*y^2)*(y-x)*x^3
+ // -> 8*(1-y)^3*(y*x^2-2*y+x*(1-2*y^2))^2*(y+x)
cout << sqrfree(BiVarPol, lst(y,x)) << endl;
- // -> (1-2*y)^3*(y+x)^2*(-y+x)*x^3
+ // -> 8*(1-y)^3*(-y*x^2+2*y+x*(-1+2*y^2))^2*(y+x)
cout << sqrfree(BiVarPol) << endl;
// -> depending on luck, any of the above
...
@end example
+Note also, how factors with the same exponents are not fully factorized
+with this method.
@node Rational Expressions, Symbolic Differentiation, Polynomial Arithmetic, Methods and Functions
@code{.to_rational()}, described below.
This means that both expressions @code{t1} and @code{t2} are indeed
-simplified in this little program:
+simplified in this little code snippet:
@example
-#include <ginac/ginac.h>
-using namespace GiNaC;
-
-int main()
@{
symbol x("x");
ex t1 = (pow(x,2) + 2*x + 1)/(x + 1);
@cindex denominator
@cindex @code{numer()}
@cindex @code{denom()}
+@cindex @code{numer_denom()}
The numerator and denominator of an expression can be obtained with
@example
ex ex::numer();
ex ex::denom();
+ex ex::numer_denom();
@end example
These functions will first normalize the expression as described above and
-then return the numerator or denominator, respectively.
+then return the numerator, denominator, or both as a list, respectively.
+If you need both numerator and denominator, calling @code{numer_denom()} is
+faster than using @code{numer()} and @code{denom()} separately.
@subsection Converting to a rational expression
the derivatives of all the monomials:
@example
-#include <ginac/ginac.h>
-using namespace GiNaC;
-
-int main()
@{
symbol x("x"), y("y"), z("z");
ex P = pow(x, 5) + pow(x, 2) + y;
- cout << P.diff(x,2) << endl; // 20*x^3 + 2
+ cout << P.diff(x,2) << endl;
+ // -> 20*x^3 + 2
cout << P.diff(y) << endl; // 1
+ // -> 1
cout << P.diff(z) << endl; // 0
+ // -> 0
@}
@end example
@code{i} by two since all odd Euler numbers vanish anyways.
-@node Series Expansion, Built-in Functions, Symbolic Differentiation, Methods and Functions
+@node Series Expansion, Symmetrization, Symbolic Differentiation, Methods and Functions
@c node-name, next, previous, up
@section Series expansion
@cindex @code{series()}
@cindex Taylor expansion
@cindex Laurent expansion
@cindex @code{pseries} (class)
+@cindex @code{Order()}
Expressions know how to expand themselves as a Taylor series or (more
generally) a Laurent series. As in most conventional Computer Algebra
@math{1-v^2/c^2+O(v^10)}, without that call we would just have a long
series raised to the power @math{-2}.
-@cindex M@'echain's formula
+@cindex Machin's formula
As another instructive application, let us calculate the numerical
value of Archimedes' constant
@tex
$\pi$
@end tex
(for which there already exists the built-in constant @code{Pi})
-using M@'echain's amazing formula
+using Machin's amazing formula
@tex
$\pi=16$~atan~$\!\left(1 \over 5 \right)-4$~atan~$\!\left(1 \over 239 \right)$.
@end tex
#include <ginac/ginac.h>
using namespace GiNaC;
-ex mechain_pi(int degr)
+ex machin_pi(int degr)
@{
symbol x;
ex pi_expansion = series_to_poly(atan(x).series(x,degr));
using std::endl; // ...dealing with this namespace std.
ex pi_frac;
for (int i=2; i<12; i+=2) @{
- pi_frac = mechain_pi(i);
+ pi_frac = machin_pi(i);
cout << i << ":\t" << pi_frac << endl
<< "\t" << pi_frac.evalf() << endl;
@}
@end example
-@node Built-in Functions, Input/Output, Series Expansion, Methods and Functions
+@node Symmetrization, Built-in Functions, Series Expansion, Methods and Functions
+@c node-name, next, previous, up
+@section Symmetrization
+@cindex @code{symmetrize()}
+@cindex @code{antisymmetrize()}
+@cindex @code{symmetrize_cyclic()}
+
+The three methods
+
+@example
+ex ex::symmetrize(const lst & l);
+ex ex::antisymmetrize(const lst & l);
+ex ex::symmetrize_cyclic(const lst & l);
+@end example
+
+symmetrize an expression by returning the sum over all symmetric,
+antisymmetric or cyclic permutations of the specified list of objects,
+weighted by the number of permutations.
+
+The three additional methods
+
+@example
+ex ex::symmetrize();
+ex ex::antisymmetrize();
+ex ex::symmetrize_cyclic();
+@end example
+
+symmetrize or antisymmetrize an expression over its free indices.
+
+Symmetrization is most useful with indexed expressions but can be used with
+almost any kind of object (anything that is @code{subs()}able):
+
+@example
+@{
+ idx i(symbol("i"), 3), j(symbol("j"), 3), k(symbol("k"), 3);
+ symbol A("A"), B("B"), a("a"), b("b"), c("c");
+
+ cout << indexed(A, i, j).symmetrize() << endl;
+ // -> 1/2*A.j.i+1/2*A.i.j
+ cout << indexed(A, i, j, k).antisymmetrize(lst(i, j)) << endl;
+ // -> -1/2*A.j.i.k+1/2*A.i.j.k
+ cout << lst(a, b, c).symmetrize_cyclic(lst(a, b, c)) << endl;
+ // -> 1/3*@{a,b,c@}+1/3*@{b,c,a@}+1/3*@{c,a,b@}
+@}
+@end example
+
+
+@node Built-in Functions, Input/Output, Symmetrization, Methods and Functions
@c node-name, next, previous, up
@section Predefined mathematical functions
@item @strong{Name} @tab @strong{Function}
@item @code{abs(x)}
@tab absolute value
+@cindex @code{abs()}
@item @code{csgn(x)}
@tab complex sign
+@cindex @code{csgn()}
@item @code{sqrt(x)}
-@tab square root (not a GiNaC function proper but equivalent to @code{pow(x, numeric(1, 2)})
+@tab square root (not a GiNaC function, rather an alias for @code{pow(x, numeric(1, 2))})
+@cindex @code{sqrt()}
@item @code{sin(x)}
@tab sine
+@cindex @code{sin()}
@item @code{cos(x)}
@tab cosine
+@cindex @code{cos()}
@item @code{tan(x)}
@tab tangent
+@cindex @code{tan()}
@item @code{asin(x)}
@tab inverse sine
+@cindex @code{asin()}
@item @code{acos(x)}
@tab inverse cosine
+@cindex @code{acos()}
@item @code{atan(x)}
@tab inverse tangent
+@cindex @code{atan()}
@item @code{atan2(y, x)}
@tab inverse tangent with two arguments
@item @code{sinh(x)}
@tab hyperbolic sine
+@cindex @code{sinh()}
@item @code{cosh(x)}
@tab hyperbolic cosine
+@cindex @code{cosh()}
@item @code{tanh(x)}
@tab hyperbolic tangent
+@cindex @code{tanh()}
@item @code{asinh(x)}
@tab inverse hyperbolic sine
+@cindex @code{asinh()}
@item @code{acosh(x)}
@tab inverse hyperbolic cosine
+@cindex @code{acosh()}
@item @code{atanh(x)}
@tab inverse hyperbolic tangent
+@cindex @code{atanh()}
@item @code{exp(x)}
@tab exponential function
+@cindex @code{exp()}
@item @code{log(x)}
@tab natural logarithm
+@cindex @code{log()}
@item @code{Li2(x)}
@tab Dilogarithm
+@cindex @code{Li2()}
@item @code{zeta(x)}
@tab Riemann's zeta function
+@cindex @code{zeta()}
@item @code{zeta(n, x)}
@tab derivatives of Riemann's zeta function
@item @code{tgamma(x)}
@tab Gamma function
+@cindex @code{tgamma()}
+@cindex Gamma function
@item @code{lgamma(x)}
@tab logarithm of Gamma function
+@cindex @code{lgamma()}
@item @code{beta(x, y)}
@tab Beta function (@code{tgamma(x)*tgamma(y)/tgamma(x+y)})
+@cindex @code{beta()}
@item @code{psi(x)}
@tab psi (digamma) function
+@cindex @code{psi()}
@item @code{psi(n, x)}
@tab derivatives of psi function (polygamma functions)
@item @code{factorial(n)}
@tab factorial function
+@cindex @code{factorial()}
@item @code{binomial(n, m)}
@tab binomial coefficients
+@cindex @code{binomial()}
@item @code{Order(x)}
@tab order term function in truncated power series
-@item @code{Derivative(x, l)}
-@tab inert partial differentiation operator (used internally)
+@cindex @code{Order()}
@end multitable
@end cartouche
Another useful output format is for LaTeX parsing in mathematical mode.
It is rather similar to the default @code{print_context} but provides
some braces needed by LaTeX for delimiting boxes and also converts some
-common objects to conventional LaTeX names. The code snippet
+common objects to conventional LaTeX names. It is possible to give symbols
+a special name for LaTeX output by supplying it as a second argument to
+the @code{symbol} constructor.
+
+For example, the code snippet
@example
// ...
@{(-\ln(x))@}+@{(-\gamma_E)@} x+@{(1/12 \pi^2)@} x^@{2@}+\mathcal@{O@}(x^3)
@end example
+@cindex Tree traversal
If you need any fancy special output format, e.g. for interfacing GiNaC
with other algebra systems or for producing code for different
programming languages, you can always traverse the expression tree yourself:
@example
static void my_print(const ex & e)
@{
- if (is_ex_of_type(e, function))
- cout << ex_to_function(e).get_name();
+ if (is_a<function>(e))
+ cout << ex_to<function>(e).get_name();
else
cout << e.bp->class_name();
cout << "(";
desired symbols to the @code{>>} stream input operator.
Instead, GiNaC lets you construct an expression from a string, specifying the
-list of symbols to be used:
+list of symbols and indices to be used:
@example
@{
- symbol x("x"), y("y");
- ex e("2*x+sin(y)", lst(x, y));
+ symbol x("x"), y("y"), p("p");
+ idx i(symbol("i"), 3);
+ ex e("2*x+sin(y)+p.i", lst(x, y, p, i));
@}
@end example
The input syntax is the same as that used by @command{ginsh} and the stream
-output operator @code{<<}. The symbols in the string are matched by name to
-the symbols in the list and if GiNaC encounters a symbol not specified in
-the list it will throw an exception.
+output operator @code{<<}. The symbols and indices in the string are matched
+by name to the symbols and indices in the list and if GiNaC encounters a
+symbol or index not specified in the list it will throw an exception. Only
+indices whose values are single symbols can be used (i.e. numeric indices
+or compound indices as in "A.(2*n+1)" are not allowed).
With this constructor, it's also easy to implement interactive GiNaC programs:
int main()
@{
- symbol x("x");
- string s;
-
- cout << "Enter an expression containing 'x': ";
- getline(cin, s);
-
- try @{
- ex e(s, lst(x));
- cout << "The derivative of " << e << " with respect to x is ";
- cout << e.diff(x) << ".\n";
- @} catch (exception &p) @{
- cerr << p.what() << endl;
- @}
+ symbol x("x");
+ string s;
+
+ cout << "Enter an expression containing 'x': ";
+ getline(cin, s);
+
+ try @{
+ ex e(s, lst(x));
+ cout << "The derivative of " << e << " with respect to x is ";
+ cout << e.diff(x) << ".\n";
+ @} catch (exception &p) @{
+ cerr << p.what() << endl;
+ @}
@}
@end example
the @code{syms} list above, the @code{ex1.subs(x == 2)} statement would
have had no effect because the @code{x} in @code{ex1} would have been a
different symbol than the @code{x} which was defined at the beginning of
-the program, altough both would appear as @samp{x} when printed.
+the program, although both would appear as @samp{x} when printed.
You can also use the information stored in an @code{archive} object to
output expressions in a format suitable for exact reconstruction. The
switch (p[i].type) @{
case archive_node::PTYPE_BOOL: @{
bool x;
- n.find_bool(name, x);
+ n.find_bool(name, x, j);
cout << (x ? "true" : "false");
break;
@}
case archive_node::PTYPE_UNSIGNED: @{
unsigned x;
- n.find_unsigned(name, x);
+ n.find_unsigned(name, x, j);
cout << x;
break;
@}
case archive_node::PTYPE_STRING: @{
string x;
- n.find_string(name, x);
+ n.find_string(name, x, j);
cout << '\"' << x << '\"';
break;
@}
language. There are no loops or conditional expressions in
@command{ginsh}, it is merely a window into the library for the
programmer to test stuff (or to show off). Still, the design of a
-complete CAS with a language of its own, graphical capabilites and all
+complete CAS with a language of its own, graphical capabilities and all
this on top of GiNaC is possible and is without doubt a nice project for
the future.
generally. This ought to be fixed. However, doing numerical
computations with GiNaC's quite abstract classes is doomed to be
inefficient. For this purpose, the underlying foundation classes
-provided by @acronym{CLN} are much better suited.
+provided by CLN are much better suited.
@node Symbolic functions, Adding classes, What does not belong into GiNaC, Extending GiNaC
@example
static ex cos_evalf(const ex & x)
@{
- return cos(ex_to_numeric(x));
+ if (is_a<numeric>(x))
+ return cos(ex_to<numeric>(x));
+ else
+ return cos(x).hold();
@}
@end example
Now that all the ingredients for @code{cos} have been set up, we need
to tell the system about it. This is done by a macro and we are not
-going to descibe how it expands, please consult your preprocessor if you
+going to describe how it expands, please consult your preprocessor if you
are curious:
@example
string str;
@};
-GIANC_IMPLEMENT_REGISTERED_CLASS(mystring, basic)
+GINAC_IMPLEMENT_REGISTERED_CLASS(mystring, basic)
@end example
The @code{GINAC_DECLARE_REGISTERED_CLASS} and @code{GINAC_IMPLEMENT_REGISTERED_CLASS}
-macros are defined in @file{registrar.h}. They take the name of the class
+macros are defined in @file{registrar.h}. They take the name of the class
and its direct superclass as arguments and insert all required declarations
for the RTTI system. The @code{GINAC_DECLARE_REGISTERED_CLASS} should be
the first line after the opening brace of the class definition. The
@code{GINAC_DECLARE_REGISTERED_CLASS} contains, among other things the
declarations of the default and copy constructor, the destructor, the
-assignment operator and a couple of other functions that are required. It
+assignment operator and a couple of other functions that are required. It
also defines a type @code{inherited} which refers to the superclass so you
don't have to modify your code every time you shuffle around the class
-hierarchy. @code{GINAC_IMPLEMENT_REGISTERED_CLASS} implements the copy
+hierarchy. @code{GINAC_IMPLEMENT_REGISTERED_CLASS} implements the copy
constructor, the destructor and the assignment operator.
Now there are nine member functions we have to implement to get a working
it will be set by the constructor of the superclass and all hell will break
loose in the RTTI. For your convenience, the @code{basic} class provides
a constructor that takes a @code{tinfo_key} value, which we are using here
-(remember that in our case @code{inherited = basic}). If the superclass
+(remember that in our case @code{inherited = basic}). If the superclass
didn't have such a constructor, we would have to set the @code{tinfo_key}
to the right value manually.
@}
@end example
-This function is where we free all dynamically allocated resources. We don't
-have any so we're not doing anything here, but if we had, for example, used
-a C-style @code{char *} to store our string, this would be the place to
-@code{delete[]} the string storage. If @code{call_parent} is true, we have
-to call the @code{destroy()} function of the superclass after we're done
-(to mimic C++'s automatic invocation of superclass destructors where
-@code{destroy()} is called from outside a destructor).
+This function is where we free all dynamically allocated resources. We
+don't have any so we're not doing anything here, but if we had, for
+example, used a C-style @code{char *} to store our string, this would be
+the place to @code{delete[]} the string storage. If @code{call_parent}
+is true, we have to call the @code{destroy()} function of the superclass
+after we're done (to mimic C++'s automatic invocation of superclass
+destructors where @code{destroy()} is called from outside a destructor).
The @code{copy()} function just copies over the member variables from
another object:
@end example
We can simply overwrite the member variables here. There's no need to worry
-about dynamically allocated storage. The assignment operator (which is
+about dynamically allocated storage. The assignment operator (which is
automatically defined by @code{GINAC_IMPLEMENT_REGISTERED_CLASS}, as you
recall) calls @code{destroy()} before it calls @code{copy()}. You have to
explicitly call the @code{copy()} function of the superclass here so
Next are the three functions for archiving. You have to implement them even
if you don't plan to use archives, but the minimum required implementation
-is really simple. First, the archiving function:
+is really simple. First, the archiving function:
@example
void mystring::archive(archive_node &n) const
The only thing that is really required is calling the @code{archive()}
function of the superclass. Optionally, you can store all information you
deem necessary for representing the object into the passed
-@code{archive_node}. We are just storing our string here. For more
+@code{archive_node}. We are just storing our string here. For more
information on how the archiving works, consult the @file{archive.h} header
file.
@}
@end example
-You don't have to understand how exactly this works. Just copy these four
-lines into your code literally (replacing the class name, of course). It
-calls the unarchiving constructor of the class and unless you are doing
-something very special (like matching @code{archive_node}s to global
-objects) you don't need a different implementation. For those who are
-interested: setting the @code{dynallocated} flag puts the object under
-the control of GiNaC's garbage collection. It will get deleted automatically
-once it is no longer referenced.
+You don't have to understand how exactly this works. Just copy these
+four lines into your code literally (replacing the class name, of
+course). It calls the unarchiving constructor of the class and unless
+you are doing something very special (like matching @code{archive_node}s
+to global objects) you don't need a different implementation. For those
+who are interested: setting the @code{dynallocated} flag puts the object
+under the control of GiNaC's garbage collection. It will get deleted
+automatically once it is no longer referenced.
Our @code{compare_same_type()} function uses a provided function to compare
the string members:
@example
ex e = mystring("Hello, world!");
-cout << is_ex_of_type(e, mystring) << endl;
+cout << is_a<mystring>(e) << endl;
// -> 1 (true)
cout << e.bp->class_name() << endl;
// -> "GiNaC rulez"+"Hello, world!"
@end example
-(note that GiNaC's automatic term reordering is in effect here), or even
+(GiNaC's automatic term reordering is in effect here), or even
@example
e = pow(mystring("One string"), 2*sin(Pi-mystring("Another string")));
@subsection Automatic evaluation
@cindex @code{hold()}
+@cindex @code{eval()}
@cindex evaluation
When dealing with objects that are just a little more complicated than the
simple string objects we have implemented, chances are that you will want to
@}
if (new_str.length() == 0)
- return _ex0();
+ return 0;
else
return mystring(new_str).hold();
@}
@end example
The @code{level} argument is used to limit the recursion depth of the
-evaluation. We don't have any subexpressions in the @code{mystring} class
-so we are not concerned with this. If we had, we would call the @code{eval()}
-functions of the subexpressions with @code{level - 1} as the argument if
-@code{level != 1}. The @code{hold()} member function sets a flag in the
-object that prevents further evaluation. Otherwise we might end up in an
-endless loop. When you want to return the object unmodified, use
-@code{return this->hold();}.
+evaluation. We don't have any subexpressions in the @code{mystring}
+class so we are not concerned with this. If we had, we would call the
+@code{eval()} functions of the subexpressions with @code{level - 1} as
+the argument if @code{level != 1}. The @code{hold()} member function
+sets a flag in the object that prevents further evaluation. Otherwise
+we might end up in an endless loop. When you want to return the object
+unmodified, use @code{return this->hold();}.
Let's confirm that it works:
some more functions that you will want to re-implement, such as
@code{evalf()}, @code{series()} or @code{op()}. Have a look at @file{basic.h}
or the header file of the class you want to make a subclass of to see
-what's there. You can, of course, also add your own new member functions.
-In this case you will probably want to define a little helper function like
-
-@example
-inline const mystring &ex_to_mystring(const ex &e)
-@{
- return static_cast<const mystring &>(*e.bp);
-@}
-@end example
-
-that let's you get at the object inside an expression (after you have verified
-that the type is correct) so you can call member functions that are specific
-to the class.
+what's there. One member function that you will most likely want to
+implement for terminal classes like the described string class is
+@code{calcchash()} that returns an @code{unsigned} hash value for the object
+which will allow GiNaC to compare and canonicalize expressions much more
+efficiently.
+
+You can, of course, also add your own new member functions. Remember,
+that the RTTI may be used to get information about what kinds of objects
+you are dealing with (the position in the class hierarchy) and that you
+can always extract the bare object from an @code{ex} by stripping the
+@code{ex} off using the @code{ex_to<mystring>(e)} function when that
+should become a need.
That's it. May the source be with you!
disadvantages over these systems.
@menu
-* Advantages:: Stengths of the GiNaC approach.
+* Advantages:: Strengths of the GiNaC approach.
* Disadvantages:: Weaknesses of the GiNaC approach.
* Why C++?:: Attractiveness of C++.
@end menu
@item
development tools: powerful development tools exist for C++, like fancy
editors (e.g. with automatic indentation and syntax highlighting),
-debuggers, visualization tools, documentation generators...
+debuggers, visualization tools, documentation generators@dots{}
@item
modularization: C++ programs can easily be split into modules by
windows into GiNaC have been implemented and many more are possible: the
tiny @command{ginsh} that is part of the distribution exposes GiNaC's
types to a command line and second, as a more consistent approach, an
-interactive interface to the @acronym{Cint} C++ interpreter has been put
-together (called @acronym{GiNaC-cint}) that allows an interactive
-scripting interface consistent with the C++ language.
+interactive interface to the Cint C++ interpreter has been put together
+(called GiNaC-cint) that allows an interactive scripting interface
+consistent with the C++ language. It is available from the usual GiNaC
+FTP-site.
@item
-seemless integration: it is somewhere between difficult and impossible
+seamless integration: it is somewhere between difficult and impossible
to call CAS functions from within a program written in C++ or any other
programming language and vice versa. With GiNaC, your symbolic routines
are part of your program. You can easily call third party libraries,
portability: While the GiNaC library itself is designed to avoid any
platform dependent features (it should compile on any ANSI compliant C++
compiler), the currently used version of the CLN library (fast large
-integer and arbitrary precision arithmetics) can be compiled only on
-systems with a recently new C++ compiler from the GNU Compiler
-Collection (@acronym{GCC}).@footnote{This is because CLN uses
-PROVIDE/REQUIRE like macros to let the compiler gather all static
-initializations, which works for GNU C++ only.} GiNaC uses recent
-language features like explicit constructors, mutable members, RTTI,
-@code{dynamic_cast}s and STL, so ANSI compliance is meant literally.
-Recent @acronym{GCC} versions starting at 2.95, although itself not yet
-ANSI compliant, support all needed features.
+integer and arbitrary precision arithmetics) can only by compiled
+without hassle on systems with the C++ compiler from the GNU Compiler
+Collection (GCC).@footnote{This is because CLN uses PROVIDE/REQUIRE like
+macros to let the compiler gather all static initializations, which
+works for GNU C++ only. Feel free to contact the authors in case you
+really believe that you need to use a different compiler. We have
+occasionally used other compilers and may be able to give you advice.}
+GiNaC uses recent language features like explicit constructors, mutable
+members, RTTI, @code{dynamic_cast}s and STL, so ANSI compliance is meant
+literally. Recent GCC versions starting at 2.95.3, although itself not
+yet ANSI compliant, support all needed features.
@end itemize
@cindex garbage collection
An expression is extremely light-weight since internally it works like a
handle to the actual representation and really holds nothing more than a
-pointer to some other object. What this means in practice is that
+pointer to some other object. What this means in practice is that
whenever you create two @code{ex} and set the second equal to the first
no copying process is involved. Instead, the copying takes place as soon
as you try to change the second. Consider the simple sequence of code:
@example
+#include <iostream>
#include <ginac/ginac.h>
using namespace std;
using namespace GiNaC;
can be:
@example
-#include <ginac/ginac.h>
-using namespace std;
-using namespace GiNaC;
-
-int main()
@{
symbol x("x"), y("y");
AC_PROG_INSTALL
AC_LANG_CPLUSPLUS
-AM_PATH_GINAC(0.7.0, [
+AM_PATH_GINAC(0.9.0, [
LIBS="$LIBS $GINACLIB_LIBS"
CPPFLAGS="$CPPFLAGS $GINACLIB_CPPFLAGS"
], AC_MSG_ERROR([need to have GiNaC installed]))
@end example
This @file{Makefile.am}, says that we are building a single executable,
-from a single sourcefile @file{simple.cpp}. Since every program
+from a single source file @file{simple.cpp}. Since every program
we are building uses GiNaC we simply added the GiNaC options
to @env{$LIBS} and @env{$CPPFLAGS}, but in other circumstances, we might
want to specify them on a per-program basis: for instance by
@item
@cite{Computer Algebra: Systems and Algorithms for Algebraic Computation},
-J.H. Davenport, Y. Siret, and E. Tournier, ISBN 0-12-204230-1, 1988,
+James H. Davenport, Yvon Siret, and Evelyne Tournier, ISBN 0-12-204230-1, 1988,
Academic Press, London
+@item
+@cite{Computer Algebra Systems - A Practical Guide},
+Michael J. Wester (editor), ISBN 0-471-98353-5, 1999, Wiley, Chichester
+
+@item
+@cite{The Art of Computer Programming, Vol 2: Seminumerical Algorithms},
+Donald E. Knuth, ISBN 0-201-89684-2, 1998, Addison Wesley
+
+@item
+@cite{The Role of gamma5 in Dimensional Regularization}, Dirk Kreimer, hep-ph/9401354
+
@end itemize
git://www.ginac.de / ginac.git / blobdiff