This is a tutorial that documents GiNaC @value{VERSION}, an open
framework for symbolic computation within the C++ programming language.
-Copyright (C) 1999 Johannes Gutenberg University Mainz, Germany
+Copyright (C) 1999-2000 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 Johannes Gutenberg University Mainz, Germany
+Copyright @copyright{} 1999-2000 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
* A Tour of GiNaC:: A quick tour of the library.
* Installation:: How to install the package.
* Basic Concepts:: Description of fundamental classes.
-* Important Algorithms:: Algorithms for symbolic manipulations.
+* Methods and Functions:: Algorithms for symbolic manipulations.
* Extending GiNaC:: How to extend the library.
* A Comparison With Other CAS:: Compares GiNaC to traditional CAS.
* Internal Structures:: Description of some internal structures.
@section License
The GiNaC framework for symbolic computation within the C++ programming
-language is Copyright @copyright{} 1999 Johannes Gutenberg University Mainz,
-Germany.
+language is Copyright @copyright{} 1999-2000 Johannes Gutenberg
+University Mainz, Germany.
This program is free software; you can redistribute it and/or
modify it under the terms of the GNU General Public License as
@section How to use it from within C++
The GiNaC open framework for symbolic computation within the C++ programming
-language does not try to define a language of it's own as conventional
+language does not try to define a language of its own as conventional
CAS do. Instead, it extends the capabilities of C++ by symbolic
manipulations. Here is how to generate and print a simple (and rather
pointless) bivariate polynomial with some large coefficients:
#include <ginac/ginac.h>
using namespace GiNaC;
-ex HermitePoly(symbol x, int deg)
+ex HermitePoly(const symbol & x, int n)
@{
- ex HKer=exp(-pow(x,2));
- // uses the identity H_n(x) == (-1)^n exp(x^2) (d/dx)^n exp(-x^2)
- return normal(pow(-1,deg) * diff(HKer, x, deg) / HKer);
+ ex HKer=exp(-pow(x, 2));
+ // uses the identity H_n(x) == (-1)^n exp(x^2) (d/dx)^n exp(-x^2)
+ return normal(pow(-1, n) * diff(HKer, x, n) / HKer);
@}
int main()
@c node-name, next, previous, up
@section What it can do for you
-@cindex @code{ginsh}
+@cindex @command{ginsh}
After invoking @command{ginsh} one can test and experiment with GiNaC's
features much like in other Computer Algebra Systems except that it does
not provide programming constructs like loops or conditionals. For a
1/3
@end example
-All numbers occuring in GiNaC's expressions can be converted into floating
-point numbers with the @code{evalf} method, to arbitrary accuracy:
+Exact numbers are always retained as exact numbers and only evaluated as
+floating point numbers if requested. For instance, with numeric
+radicals is dealt pretty much as with symbols. Products of sums of them
+can be expanded:
+
+@example
+> expand((1+a^(1/5)-a^(2/5))^3);
+1+3*a+3*a^(1/5)-5*a^(3/5)-a^(6/5)
+> expand((1+3^(1/5)-3^(2/5))^3);
+10-5*3^(3/5)
+> evalf((1+3^(1/5)-3^(2/5))^3);
+0.33408977534118624228
+@end example
+
+The function @code{evalf} that was used above converts any number in
+GiNaC's expressions into floating point numbers. This can be done to
+arbitrary predefined accuracy:
@example
> evalf(1/7);
> a=Pi^2+x;
x+Pi^2
> evalf(a);
-x+9.869604401089358619L0
+9.869604401089358619+x
> x=2;
2
> evalf(a);
-11.869604401089358619L0
+11.869604401089358619
@end example
Built-in functions evaluate immediately to exact numbers if
@example
> lsolve(a+x*y==z,x);
y^(-1)*(z-a);
-lsolve([3*x+5*y == 7, -2*x+10*y == -5], [x, y]);
+> 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]] ]]
3*y^2+x^2
@end example
-You can differentiate functions and expand them as Taylor or
-Laurent series (the third argument of series is the evaluation point,
-the fourth defines the order):
+You can differentiate functions and expand them as Taylor or Laurent
+series in a very natural syntax (the second argument of @code{series} is
+a relation defining the evaluation point, the third specifies the
+order):
+@cindex Zeta function
@example
> diff(tan(x),x);
tan(x)^2+1
-> series(sin(x),x,0,4);
+> series(sin(x),x==0,4);
x-1/6*x^3+Order(x^4)
-> series(1/tan(x),x,0,4);
+> series(1/tan(x),x==0,4);
x^(-1)-1/3*x+Order(x^2)
+> 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(");
+x^(-1)-0.5772156649015328606+(0.9890559953279725555)*x
+-(0.90747907608088628905)*x^2+Order(x^3)
+> series(tgamma(2*sin(x)-2),x==Pi/2,6);
+-(x-1/2*Pi)^(-2)+(-1/12*Pi^2-1/2*Euler^2-1/240)*(x-1/2*Pi)^2
+-Euler-1/12+Order((x-1/2*Pi)^3)
@end example
-If you ever wanted to convert units in C or C++ and found this
-is cumbersome, here is the solution. Symbolic types can always be
-used as tags for different types of objects. Converting from wrong
-units to the metric system is therefore easy:
+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
+cumbersome, here is the solution. Symbolic types can always be used as
+tags for different types of objects. Converting from wrong units to the
+metric system is now easy:
@example
> in=.0254*m;
@c node-name, next, previous, up
@section Prerequisites
-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
+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 from @uref{ftp://ftp.santafe.edu/pub/gnu/} 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 GiNaC.
-The configure script checks if it can find it and if it cannot
+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
+@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
+GiNaC. The configure script checks if it can find it and if it cannot
it will refuse to continue.
@option{--prefix=@var{PREFIX}}: The directory where the compiled library
and headers are installed. It defaults to @file{/usr/local} which means
that the library is installed in the directory @file{/usr/local/lib},
-the header files in @file{/usr/local/include/GiNaC} and the documentation
+the header files in @file{/usr/local/include/ginac} and the documentation
(like this one) into @file{/usr/local/share/doc/GiNaC}.
@item
@file{@var{PREFIX}/include/ginac/}. For instance, if you specify
@option{--includedir=/usr/include} you will end up with the header files
sitting in the directory @file{/usr/include/ginac/}. Note that the
-subdirectory @file{GiNaC} is enforced by this process in order to
+subdirectory @file{ginac} is enforced by this process in order to
keep the header files separated from others. This avoids some
clashes and allows for an easier deinstallation of GiNaC. This ought
to be considered A Good Thing (tm).
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 are switched on:
+assertions and debugging information are switched on:
@example
$ export CXX=/usr/local/gnu/bin/c++
but also on other parameters, for instance what value for @env{CXXFLAGS}
you entered. Optimization may be very time-consuming.
-Just to make sure GiNaC works properly you may run a simple test
-suite by typing
+Just to make sure GiNaC works properly you may run a collection of
+regression tests by typing
@example
$ make check
@end example
-This will compile some sample programs, run them and compare the output
-to reference output. Each of the checks should return a message @samp{passed}
-together with the CPU time used for that particular test. If it does
-not, something went wrong. This is mostly intended to be a QA-check
-if something was broken during the development, not a sanity check
-of your system. Another intent is to allow people to fiddle around
-with optimization. If @acronym{CLN} was installed all right
-this step is unlikely to return any errors.
+This will compile some sample programs, run them and check the output
+for correctness. The regression tests fall in three categories. First,
+the so called @emph{exams} are performed, simple tests where some
+predefined input is evaluated (like a pupils' exam). Second, the
+@emph{checks} test the coherence of results among each other with
+possible random input. Third, some @emph{timings} are performed, which
+benchmark some predefined problems with different sizes and display the
+CPU time used in seconds. Each individual test should return a message
+@samp{passed}. This is mostly intended to be a QA-check if something
+was broken during development, not a sanity check of your system. Some
+of the tests in sections @emph{checks} and @emph{timings} may require
+insane amounts of memory and CPU time. Feel free to kill them if your
+machine catches fire. Another quite important intent is to allow people
+to fiddle around with optimization.
Generally, the top-level Makefile runs recursively to the
subdirectories. It is therfore safe to go into any subdirectory
* Symbols:: Symbolic objects.
* Numbers:: Numerical objects.
* Constants:: Pre-defined constants.
-* Fundamental operations:: The power, add and mul classes.
-* Built-in functions:: Mathematical functions.
+* Fundamental containers:: The power, add and mul classes.
+* Lists:: Lists of expressions.
+* Mathematical functions:: Mathematical functions.
+* Relations:: Equality, Inequality and all that.
@end menu
mathematical objects, all of which (except for @code{ex} and some
helpers) are internally derived from one abstract base class called
@code{basic}. You do not have to deal with objects of class
-@code{basic}, instead you'll be dealing with symbols and functions of
-symbols. You'll soon learn in this chapter how many of the functions on
-symbols are really classes. This is because simple symbolic arithmetic
-is not supported by languages like C++ so in a certain way GiNaC has to
-implement its own arithmetic.
-
-To give an idea about what kinds of symbolic composits may be built we
+@code{basic}, instead you'll be dealing with symbols, numbers,
+containers of expressions and so on. You'll soon learn in this chapter
+how many of the functions on symbols are really classes. This is
+because simple symbolic arithmetic is not supported by languages like
+C++ so in a certain way GiNaC has to implement its own arithmetic.
+
+@cindex container
+@cindex atom
+To get an idea about what kinds of symbolic composits may be built we
have a look at the most important classes in the class hierarchy. The
-dashed line symbolizes a "points to" or "handles" relationship while the
-solid lines stand for "inherits from" relationship in the class
+oval classes are atomic ones and the squared classes are containers.
+The dashed line symbolizes a `points to' or `handles' relationship while
+the solid lines stand for `inherits from' relationship in the class
hierarchy:
@image{classhierarchy}
consisting of one expression and a number (@code{numeric}). What
@emph{is} visible to the user are the derived classes @code{add} and
@code{mul}, representing sums of terms and products, respectively.
-We'll come back later to some more details about these two classes and
-motivate the use of pairs in sums and products here.
+@xref{Internal Structures}, where these two classes are described in
+more detail.
+At this point, we only summarize what kind of mathematical objects are
+stored in the different classes in above diagram in order to give you a
+overview:
+
+@cartouche
+@multitable @columnfractions .22 .78
+@item @code{symbol} @tab Algebraic symbols @math{a}, @math{x}, @math{y}@dots{}
+@item @code{constant} @tab Constants like
+@tex
+$\pi$
+@end tex
+@ifnottex
+@math{Pi}
+@end ifnottex
+@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{a*(x+y+z)*b*2}
+@item @code{power} @tab Exponentials such as @math{x^2}, @math{a^b},
+@tex
+$\sqrt{2}$
+@end tex
+@ifnottex
+@code{sqrt(}@math{2}@code{)}
+@end ifnottex
+@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{relational} @tab A relation like the identity @math{x}@code{==}@math{y}
+@item @code{color} @tab Element of the @math{SU(3)} Lie-algebra
+@item @code{isospin} @tab Element of the @math{SU(2)} Lie-algebra
+@item @code{idx} @tab Index of a tensor object
+@item @code{coloridx} @tab Index of a @math{SU(3)} tensor
+@end multitable
+@end cartouche
@node Symbols, Numbers, The Class Hierarchy, Basic Concepts
@c node-name, next, previous, up
@section Symbols
-@cindex Symbols (class @code{symbol})
+@cindex @code{symbol} (class)
+@cindex hierarchy of classes
+@cindex atom
Symbols are for symbolic manipulation what atoms are for chemistry. You
can declare objects of class @code{symbol} as any other object simply by
saying @code{symbol x,y;}. There is, however, a catch in here having to
in the calling function. Again, comparing them (using @code{operator==}
for instance) will always reveal their difference. Watch out, please.
+@cindex @code{subs()}
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.
+can use the expression's @code{.subs()} method (@xref{Substituting Symbols},
+for more information).
@node Numbers, Constants, Symbols, Basic Concepts
@c node-name, next, previous, up
@section Numbers
-@cindex numbers (class @code{numeric})
+@cindex @code{numeric} (class)
+@cindex GMP
@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
int main()
@{
- 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 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
+ // Trott's constant in scientific notation:
+ numeric trott("1.0841015122311136151E-2");
+
cout << two*p << endl; // floating point 6.283...
- // ...
@}
@end example
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 ambiguities.
+lead to compile-time ambiguities.
It may be tempting to construct numbers 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 @code{/} on integers!} Use the constructor from two integers
-instead, as shown in the example above. Writing @code{numeric(1)/2} may
-look funny but works also.
+use the operator @code{/} on integers} unless you know exactly what you
+are doing! Use the constructor from two integers instead, as shown in
+the example above. Writing @code{numeric(1)/2} may look funny but works
+also.
@cindex @code{Digits}
@cindex accuracy
We have seen now the distinction between exact numbers and floating
point numbers. Clearly, the user should never have to worry about
-dynamically created exact numbers, since their "exactness" always
-determines how they ought to be handled, i.e. how "long" they are. The
+dynamically created exact numbers, since their `exactness' always
+determines how they ought to be handled, i.e. how `long' they are. The
situation is different for floating point numbers. Their accuracy is
controlled by one @emph{global} variable, called @code{Digits}. (For
those readers who know about Maple: it behaves very much like Maple's
cout << answer.is_integer() << endl; // false, it's 21/5
answer *= ten;
cout << answer.is_integer() << endl; // true, it's 42 now!
- // ...
@}
@end example
following table.
@cartouche
-@multitable @columnfractions .33 .67
-@item Method @tab Returns true if@dots{}
+@multitable @columnfractions .30 .70
+@item @strong{Method} @tab @strong{Returns true if the object is@dots{}}
@item @code{.is_zero()}
-@tab object is equal to zero
+@tab @dots{}equal to zero
@item @code{.is_positive()}
-@tab object is not complex and greater than 0
+@tab @dots{}not complex and greater than 0
@item @code{.is_integer()}
-@tab object is a (non-complex) integer
+@tab @dots{}a (non-complex) integer
@item @code{.is_pos_integer()}
-@tab object is an integer and greater than 0
+@tab @dots{}an integer and greater than 0
@item @code{.is_nonneg_integer()}
-@tab object is an integer and greater equal 0
+@tab @dots{}an integer and greater equal 0
@item @code{.is_even()}
-@tab object is an even integer
+@tab @dots{}an even integer
@item @code{.is_odd()}
-@tab object is an odd integer
+@tab @dots{}an odd integer
@item @code{.is_prime()}
-@tab object is a prime integer (probabilistic primality test)
+@tab @dots{}a prime integer (probabilistic primality test)
@item @code{.is_rational()}
-@tab object is an exact rational number (integers are rational, too, as are complex extensions like @math{2/3+7/2*I})
+@tab @dots{}an exact rational number (integers are rational, too)
@item @code{.is_real()}
-@tab object is a real integer, rational or float (i.e. is not complex)
+@tab @dots{}a real integer, rational or float (i.e. is not complex)
+@item @code{.is_cinteger()}
+@tab @dots{}a (complex) integer (such as @math{2-3*I})
+@item @code{.is_crational()}
+@tab @dots{}an exact (complex) rational number (such as @math{2/3+7/2*I})
@end multitable
@end cartouche
-@node Constants, Fundamental operations, Numbers, Basic Concepts
+@node Constants, Fundamental containers, Numbers, Basic Concepts
@c node-name, next, previous, up
@section Constants
-@cindex constants (class @code{constant})
-@cindex @code{evalf()}
+@cindex @code{constant} (class)
+@cindex @code{Pi}
+@cindex @code{Catalan}
+@cindex @code{Euler}
+@cindex @code{evalf()}
Constants behave pretty much like symbols except that they return some
specific number when the method @code{.evalf()} is called.
The predefined known constants are:
@cartouche
-@multitable @columnfractions .14 .29 .57
-@item Name @tab Common Name @tab Numerical Value (35 digits)
+@multitable @columnfractions .14 .30 .56
+@item @strong{Name} @tab @strong{Common Name} @tab @strong{Numerical Value (to 35 digits)}
@item @code{Pi}
@tab Archimedes' constant
@tab 3.14159265358979323846264338327950288
@item @code{Catalan}
@tab Catalan's constant
@tab 0.91596559417721901505460351493238411
-@item @code{EulerGamma}
+@item @code{Euler}
@tab Euler's (or Euler-Mascheroni) constant
@tab 0.57721566490153286060651209008240243
@end multitable
@end cartouche
-@node Fundamental operations, Built-in functions, Constants, Basic Concepts
+@node Fundamental containers, Lists, Constants, Basic Concepts
@c node-name, next, previous, up
-@section Fundamental operations: the @code{power}, @code{add} and @code{mul} classes
-@cindex polynomials
+@section Fundamental containers: the @code{power}, @code{add} and @code{mul} classes
+@cindex polynomial
@cindex @code{add}
@cindex @code{mul}
@cindex @code{power}
@}
@end example
+@cindex @code{pow()}
For exponentiation, you have already seen the somewhat clumsy (though C-ish)
statement @code{pow(x,2);} to represent @code{x} squared. This direct
construction is necessary since we cannot safely overload the constructor
has requested @code{2^3}.)
@end itemize
-@cindex @code{ginsh}
+@cindex @command{ginsh}
All effects are contrary to mathematical notation and differ from the
way most other CAS handle exponentiation, therefore overloading @code{^}
is ruled out for GiNaC's C++ part. The situation is different in
canonical form.
-@node Built-in functions, Important Algorithms, Fundamental operations, Basic Concepts
+@node Lists, Mathematical functions, Fundamental containers, Basic Concepts
+@c node-name, next, previous, up
+@section Lists of expressions
+@cindex @code{lst} (class)
+@cindex lists
+@cindex @code{nops()}
+@cindex @code{op()}
+@cindex @code{append()}
+@cindex @code{prepend()}
+
+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.
+
+Lists of up to 15 expressions can be directly constructed from single
+expressions:
+
+@example
+@{
+ symbol x("x"), y("y");
+ lst l(x, 2, y, x+y);
+ // now, l is a list holding the expressions 'x', '2', 'y', and 'x+y'
+ // ...
+@end example
+
+Use the @code{nops()} method to determine the size (number of expressions) of
+a list and the @code{op()} method to access individual elements:
+
+@example
+ // ...
+ cout << l.nops() << endl; // prints '4'
+ cout << l.op(2) << " " << l.op(0) << endl; // prints 'y x'
+ // ...
+@end example
+
+Finally 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
+
+
+@node Mathematical functions, Relations, Lists, Basic Concepts
@c node-name, next, previous, up
-@section Built-in functions
+@section Mathematical functions
+@cindex @code{function} (class)
+@cindex trigonometric function
+@cindex hyperbolic function
+
+There are quite a number of useful functions hard-wired into GiNaC. For
+instance, all trigonometric and hyperbolic functions are implemented
+(@xref{Built-in Functions}, for a complete list).
-There are quite a number of useful functions built into GiNaC. They are
-all objects of class @code{function}. They accept one or more
-expressions as arguments and return one expression. If the arguments
+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:
+@cindex Gamma function
+@cindex @code{subs()}
@example
#include <ginac/ginac.h>
using namespace GiNaC;
symbol x("x"), y("y");
ex foo = x+y/2;
- cout << "gamma(" << foo << ") -> " << gamma(foo) << endl;
+ cout << "tgamma(" << foo << ") -> " << tgamma(foo) << endl;
ex bar = foo.subs(y==1);
- cout << "gamma(" << bar << ") -> " << gamma(bar) << endl;
+ cout << "tgamma(" << bar << ") -> " << tgamma(bar) << endl;
ex foobar = bar.subs(x==7);
- cout << "gamma(" << foobar << ") -> " << gamma(foobar) << endl;
- // ...
+ cout << "tgamma(" << foobar << ") -> " << tgamma(foobar) << endl;
@}
@end example
expression that may be really useful:
@example
-gamma(x+(1/2)*y) -> gamma(x+(1/2)*y)
-gamma(x+1/2) -> gamma(x+1/2)
-gamma(15/2) -> (135135/128)*Pi^(1/2)
+tgamma(x+(1/2)*y) -> tgamma(x+(1/2)*y)
+tgamma(x+1/2) -> tgamma(x+1/2)
+tgamma(15/2) -> (135135/128)*Pi^(1/2)
@end example
-Most of these functions can be differentiated, series expanded and so
-on. Read the next chapter in order to learn more about this.
+Besides evaluation most of these functions allow differentiation, series
+expansion and so on. Read the next chapter in order to learn more about
+this.
-@node Important Algorithms, Polynomial Expansion, Built-in functions, Top
+@node Relations, Methods and Functions, Mathematical functions, Basic Concepts
@c node-name, next, previous, up
-@chapter Important Algorithms
-@cindex polynomials
+@section Relations
+@cindex @code{relational} (class)
+
+Sometimes, a relation holding between two expressions must be stored
+somehow. The class @code{relational} is a convenient container for such
+purposes. A relation is by definition a container for two @code{ex} and
+a relation between them that signals equality, inequality and so on.
+They are created by simply using the C++ operators @code{==}, @code{!=},
+@code{<}, @code{<=}, @code{>} and @code{>=} between two expressions.
+
+@xref{Mathematical functions}, for examples where various applications of
+the @code{.subs()} method show how objects of class relational are used
+as arguments. There they provide an intuitive syntax for substitutions.
+They can also used for creating systems of equations that are to be
+solved for unknown variables. More applications of this class will
+appear throughout the next chapters.
+
+
+
+@node Methods and Functions, Information About Expressions, Relations, Top
+@c node-name, next, previous, up
+@chapter Methods and Functions
+@cindex polynomial
In this chapter the most important algorithms provided by GiNaC will be
described. Some of them are implemented as functions on expressions,
cout << "As method: " << sin(x).evalf() << endl;
cout << "As function: " << evalf(sin(x)) << endl;
- // ...
@}
@end example
+@cindex @code{subs()}
The general rule is that wherever methods accept one or more parameters
(@var{arg1}, @var{arg2}, @dots{}) the order of arguments the function
wrapper accepts is the same but preceded by the object to act on
@code{A:=x^2+3; coeff(A,x,0);} (GiNaC: @code{A=pow(x,2)+3;
coeff(A,x,0);}) it is clear that MapleV is not trying to be consistent
here. Also, users of MuPAD will in most cases feel more comfortable
-with GiNaC's convention. All function wrappers are always implemented
+with GiNaC's convention. All function wrappers are implemented
as simple inline functions which just call the corresponding method and
are only provided for users uncomfortable with OO who are dead set to
-avoid method invocations. Generally, a chain of function wrappers is
-much harder to read than a chain of methods and should therefore be
+avoid method invocations. Generally, nested function wrappers are much
+harder to read than a sequence of methods and should therefore be
avoided if possible. On the other hand, not everything in GiNaC is a
method on class @code{ex} and sometimes calling a function cannot be
avoided.
@menu
-* Polynomial Expansion::
-* Collecting expressions::
-* Polynomial Arithmetic::
+* Information About Expressions::
+* Substituting Symbols::
+* Polynomial Arithmetic:: Working with polynomials.
+* Rational Expressions:: Working with rational functions.
* Symbolic Differentiation::
-* Series Expansion::
+* Series Expansion:: Taylor and Laurent expansion.
+* Built-in Functions:: List of predefined mathematical functions.
+* Input/Output:: Input and output of expressions.
@end menu
-@node Polynomial Expansion, Collecting expressions, Important Algorithms, Important Algorithms
+@node Information About Expressions, Substituting Symbols, Methods and Functions, Methods and Functions
@c node-name, next, previous, up
-@section Polynomial Expansion
+@section Getting information about expressions
+
+@subsection Checking expression types
+@cindex @code{is_ex_of_type()}
+@cindex @code{info()}
+
+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):
+
+@example
+bool is_ex_of_type(const ex & e, TYPENAME t);
+bool ex::info(unsigned flag);
+@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}
+(@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:
+
+@example
+@{
+ 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
+@}
+@end example
+
+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
+table:
+
+@cartouche
+@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)})
+@item @code{real}
+@tab @dots{}a real integer, rational or float (i.e. is not complex)
+@item @code{rational}
+@tab @dots{}an exact rational number (integers are rational, too)
+@item @code{integer}
+@tab @dots{}a (non-complex) integer
+@item @code{crational}
+@tab @dots{}an exact (complex) rational number (such as @math{2/3+7/2*I})
+@item @code{cinteger}
+@tab @dots{}a (complex) integer (such as @math{2-3*I})
+@item @code{positive}
+@tab @dots{}not complex and greater than 0
+@item @code{negative}
+@tab @dots{}not complex and less than 0
+@item @code{nonnegative}
+@tab @dots{}not complex and greater than or equal to 0
+@item @code{posint}
+@tab @dots{}an integer greater than 0
+@item @code{negint}
+@tab @dots{}an integer less than 0
+@item @code{nonnegint}
+@tab @dots{}an integer greater than or equal to 0
+@item @code{even}
+@tab @dots{}an even integer
+@item @code{odd}
+@tab @dots{}an odd integer
+@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)})
+@item @code{relation_equal}
+@tab @dots{}a @code{==} relation
+@item @code{relation_not_equal}
+@tab @dots{}a @code{!=} relation
+@item @code{relation_less}
+@tab @dots{}a @code{<} relation
+@item @code{relation_less_or_equal}
+@tab @dots{}a @code{<=} relation
+@item @code{relation_greater}
+@tab @dots{}a @code{>} relation
+@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)})
+@item @code{list}
+@tab @dots{}a list (same as @code{is_ex_of_type(..., 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}
+@tab @dots{}a polynomial with (non-complex) integer coefficients
+@item @code{cinteger_polynomial}
+@tab @dots{}a polynomial with (possibly complex) integer coefficients (such as @math{2-3*I})
+@item @code{rational_polynomial}
+@tab @dots{}a polynomial with (non-complex) rational coefficients
+@item @code{crational_polynomial}
+@tab @dots{}a polynomial with (possibly complex) rational coefficients (such as @math{2/3+7/2*I})
+@item @code{rational_function}
+@tab @dots{}a rational function
+@end multitable
+@end cartouche
+
+
+@subsection Accessing subexpressions
+@cindex @code{nops()}
+@cindex @code{op()}
+@cindex @code{has()}
+@cindex container
+@cindex @code{relational} (class)
+
+GiNaC provides the two methods
+
+@example
+unsigned ex::nops();
+ex ex::op(unsigned i);
+@end example
+
+for accessing the subexpressions in the container-like GiNaC classes like
+@code{add}, @code{mul}, @code{lst}, and @code{function}. @code{nops()}
+determines the number of subexpressions (@samp{operands}) contained, while
+@code{op()} returns the @code{i}-th (0..@code{nops()-1}) subexpression.
+In the case of a @code{power} object, @code{op(0)} will return the basis
+and @code{op(1)} the exponent.
+
+The left-hand and right-hand side expressions of objects of class
+@code{relational} (and only of these) can also be accessed with the methods
+
+@example
+ex ex::lhs();
+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()}
+@cindex @code{is_zero()}
+
+Expressions can be compared with the usual C++ relational operators like
+@code{==}, @code{>}, and @code{<} but if the expressions contain symbols,
+the result is usually not determinable and the result will be @code{false},
+except in the case of the @code{!=} operator. You should also be aware that
+GiNaC will only do the most trivial test for equality (subtracting both
+expressions), so something like @code{(pow(x,2)+x)/x==x+1} will return
+@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}.
+
+There are also two methods
+
+@example
+bool ex::is_equal(const ex & other);
+bool ex::is_zero();
+@end example
+
+for checking whether one expression is equal to another, or equal to zero,
+respectively.
+
+@strong{Warning:} You will also find a @code{ex::compare()} method in the
+GiNaC header files. This method is however only to be used internally by
+GiNaC to establish a canonical sort order for terms, and using it to compare
+expressions will give very surprising results.
+
+
+@node Substituting Symbols, Polynomial Arithmetic, Information About Expressions, Methods and Functions
+@c node-name, next, previous, up
+@section Substituting symbols
+@cindex @code{subs()}
+
+Symbols can be replaced with expressions via the @code{.subs()} method:
+
+@example
+ex ex::subs(const ex & e);
+ex ex::subs(const lst & syms, const lst & repls);
+@end example
+
+In the first form, @code{subs()} accepts a relational of the form
+@samp{symbol == expression} or a @code{lst} of such relationals. E.g.
+
+@example
+@{
+ symbol x("x"), y("y");
+ ex e1 = 2*x^2-4*x+3;
+ cout << "e1(7) = " << e1.subs(x == 7) << endl;
+ ex e2 = x*y + x;
+ cout << "e2(-2, 4) = " << e2.subs(lst(x == -2, y == 4)) << endl;
+@}
+@end example
+
+will print @samp{73} and @samp{-10}, respectively.
+
+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 symbols 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 Polynomial Arithmetic, Rational Expressions, Substituting Symbols, Methods and Functions
+@c node-name, next, previous, up
+@section Polynomial arithmetic
+
+@subsection Expanding and collecting
@cindex @code{expand()}
+@cindex @code{collect()}
A polynomial in one or more variables has many equivalent
representations. Some useful ones serve a specific purpose. Consider
+ 20*y^2 + 21*y*z + 4*z^2} and @math{20*y^2 + (21*z + 4*x)*y + 4*z^2 +
x*z}.
-To bring an expression into expanded form, its method @code{.expand()}
+To bring an expression into expanded form, its method
+
+@example
+ex ex::expand();
+@end example
+
may be called. In our example above, this corresponds to @math{4*x*y +
x*z + 20*y^2 + 21*y*z + 4*z^2}. Again, since the canonical form in
GiNaC is not easily guessable you should be prepared to see different
orderings of terms in such sums!
-
-@node Collecting expressions, Polynomial Arithmetic, Polynomial Expansion, Important Algorithms
-@c node-name, next, previous, up
-@section Collecting expressions
-@cindex @code{collect()}
-@cindex @code{coeff()}
-
Another useful representation of multivariate polynomials is as a
univariate polynomial in one of the variables with the coefficients
being polynomials in the remaining variables. The method
-@code{collect()} accomplishes this task. Here is its declaration:
+@code{collect()} accomplishes this task:
@example
-ex ex::collect(symbol const & s);
+ex ex::collect(const symbol & s);
@end example
Note that the original polynomial needs to be in expanded form in order
-to be able to find the coefficients properly. The range of occuring
-coefficients can be checked using the two methods
+to be able to find the coefficients properly.
+
+@subsection Degree and coefficients
+@cindex @code{degree()}
+@cindex @code{ldegree()}
+@cindex @code{coeff()}
+
+The degree and low degree of a polynomial can be obtained using the two
+methods
@example
-int ex::degree(symbol const & s);
-int ex::ldegree(symbol const & s);
+int ex::degree(const symbol & s);
+int ex::ldegree(const symbol & s);
@end example
-where @code{degree()} returns the highest coefficient and
-@code{ldegree()} the lowest one. (These two methods work also reliably
-on non-expanded input polynomials). An application is illustrated in
-the next example, where a multivariate polynomial is analysed:
+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
+
+@example
+ex ex::coeff(const symbol & s, int n);
+@end example
+
+You can also obtain the leading and trailing coefficients with the methods
+
+@example
+ex ex::lcoeff(const symbol & s);
+ex ex::tcoeff(const symbol & s);
+@end example
+
+which are equivalent to @code{coeff(s, degree(s))} and @code{coeff(s, ldegree(s))},
+respectively.
+
+An application is illustrated in the next example, where a multivariate
+polynomial is analyzed:
@example
#include <ginac/ginac.h>
@}
cout << "As polynomial in y: "
<< Poly.collect(y) << endl;
- // ...
@}
@end example
within the user's sphere of influence.
-@node Polynomial Arithmetic, Symbolic Differentiation, Collecting expressions, Important Algorithms
-@c node-name, next, previous, up
-@section Polynomial Arithmetic
+@subsection Polynomial division
+@cindex polynomial division
+@cindex quotient
+@cindex remainder
+@cindex pseudo-remainder
+@cindex @code{quo()}
+@cindex @code{rem()}
+@cindex @code{prem()}
+@cindex @code{divide()}
+
+The two functions
+
+@example
+ex quo(const ex & a, const ex & b, const symbol & x);
+ex rem(const ex & a, const ex & b, const symbol & x);
+@end example
+
+compute the quotient and remainder of univariate polynomials in the variable
+@samp{x}. The results satisfy @math{a = b*quo(a, b, x) + rem(a, b, x)}.
+
+The additional function
+
+@example
+ex prem(const ex & a, const ex & b, const symbol & x);
+@end example
+
+computes the pseudo-remainder of @samp{a} and @samp{b} which satisfies
+@math{c*a = b*q + prem(a, b, x)}, where @math{c = b.lcoeff(x) ^ (a.degree(x) - b.degree(x) + 1)}.
+
+Exact division of multivariate polynomials is performed by the function
+
+@example
+bool divide(const ex & a, const ex & b, ex & q);
+@end example
+
+If @samp{b} divides @samp{a} over the rationals, this function returns @code{true}
+and returns the quotient in the variable @code{q}. Otherwise it returns @code{false}
+in which case the value of @code{q} is undefined.
+
+
+@subsection Unit, content and primitive part
+@cindex @code{unit()}
+@cindex @code{content()}
+@cindex @code{primpart()}
+
+The methods
+
+@example
+ex ex::unit(const symbol & x);
+ex ex::content(const symbol & x);
+ex ex::primpart(const symbol & x);
+@end example
+
+return the unit part, content part, and primitive polynomial of a multivariate
+polynomial with respect to the variable @samp{x} (the unit part being the sign
+of the leading coefficient, the content part being the GCD of the coefficients,
+and the primitive polynomial being the input polynomial divided by the unit and
+content parts). The product of unit, content, and primitive part is the
+original polynomial.
+
@subsection GCD and LCM
@cindex GCD
@cindex LCM
+@cindex @code{gcd()}
+@cindex @code{lcm()}
The functions for polynomial greatest common divisor and least common
-multiple have the synopsis:
+multiple have the synopsis
@example
ex gcd(const ex & a, const ex & b);
// x + 5*y + 4*z
ex P_lcm = lcm(P_a, P_b);
// 4*x*y^2 + 13*y*x*z + 20*y^3 + 81*y^2*z + 67*y*z^2 + 3*x*z^2 + 12*z^3
- // ...
@}
@end example
+
+@node Rational Expressions, Symbolic Differentiation, Polynomial Arithmetic, Methods and Functions
+@c node-name, next, previous, up
+@section Rational expressions
+
@subsection The @code{normal} method
@cindex @code{normal()}
+@cindex simplification
@cindex temporary replacement
-While in common symbolic code @code{gcd()} and @code{lcm()} are not too
-heavily used, simplification is called for frequently. Therefore
-@code{.normal()}, which provides some basic form of simplification, has
-become a method of class @code{ex}, just like @code{.expand()}. It
-converts a rational function into an equivalent rational function where
-numerator and denominator are coprime. This means, it finds the GCD of
-numerator and denominator and cancels it. If it encounters some object
-which does not belong to the domain of rationals (a function for
-instance), that object is replaced by a temporary symbol. This means
-that both expressions @code{t1} and @code{t2} are indeed simplified in
-this little program:
+Some basic from of simplification of expressions is called for frequently.
+GiNaC provides the method @code{.normal()}, which converts a rational function
+into an equivalent rational function of the form @samp{numerator/denominator}
+where numerator and denominator are coprime. If the input expression is already
+a fraction, it just finds the GCD of numerator and denominator and cancels it,
+otherwise it performs fraction addition and multiplication.
+
+@code{.normal()} can also be used on expressions which are not rational functions
+as it will replace all non-rational objects (like functions or non-integer
+powers) by temporary symbols to bring the expression to the domain of rational
+functions before performing the normalization, and re-substituting these
+symbols afterwards. This algorithm is also available as a separate method
+@code{.to_rational()}, described below.
+
+This means that both expressions @code{t1} and @code{t2} are indeed
+simplified in this little program:
@example
#include <ginac/ginac.h>
ex t2 = (pow(sin(x),2) + 2*sin(x) + 1)/(sin(x) + 1);
cout << "t1 is " << t1.normal() << endl;
cout << "t2 is " << t2.normal() << endl;
- // ...
@}
@end example
normalized to @code{P_a/P_b} = @code{(4*y+z)/(y+3*z)}.
-@node Symbolic Differentiation, Series Expansion, Polynomial Arithmetic, Important Algorithms
+@subsection Numerator and denominator
+@cindex numerator
+@cindex denominator
+@cindex @code{numer()}
+@cindex @code{denom()}
+
+The numerator and denominator of an expression can be obtained with
+
+@example
+ex ex::numer();
+ex ex::denom();
+@end example
+
+These functions will first normalize the expression as described above and
+then return the numerator or denominator, respectively.
+
+
+@subsection Converting to a rational expression
+@cindex @code{to_rational()}
+
+Some of the methods described so far only work on polynomials or rational
+functions. GiNaC provides a way to extend the domain of these functions to
+general expressions by using the temporary replacement algorithm described
+above. You do this by calling
+
+@example
+ex ex::to_rational(lst &l);
+@end example
+
+on the expression to be converted. The supplied @code{lst} will be filled
+with the generated temporary symbols and their replacement expressions in
+a format that can be used directly for the @code{subs()} method. It can also
+already contain a list of replacements from an earlier application of
+@code{.to_rational()}, so it's possible to use it on multiple expressions
+and get consistent results.
+
+For example,
+
+@example
+@{
+ symbol x("x");
+ ex a = pow(sin(x), 2) - pow(cos(x), 2);
+ ex b = sin(x) + cos(x);
+ ex q;
+ lst l;
+ divide(a.to_rational(l), b.to_rational(l), q);
+ cout << q.subs(l) << endl;
+@}
+@end example
+
+will print @samp{sin(x)-cos(x)}.
+
+
+@node Symbolic Differentiation, Series Expansion, Rational Expressions, Methods and Functions
@c node-name, next, previous, up
-@section Symbolic Differentiation
+@section Symbolic differentiation
@cindex differentiation
+@cindex @code{diff()}
@cindex chain rule
@cindex product rule
cout << P.diff(x,2) << endl; // 20*x^3 + 2
cout << P.diff(y) << endl; // 1
cout << P.diff(z) << endl; // 0
- // ...
@}
@end example
ex EulerNumber(unsigned n)
@{
symbol x;
- ex generator = pow(cosh(x),-1);
+ const ex generator = pow(cosh(x),-1);
return generator.diff(x,n).subs(x==0);
@}
@code{i} by two since all odd Euler numbers vanish anyways.
-@node Series Expansion, Extending GiNaC, Symbolic Differentiation, Important Algorithms
+@node Series Expansion, Built-in Functions, Symbolic Differentiation, Methods and Functions
@c node-name, next, previous, up
-@section Series Expansion
-@cindex series expansion
+@section Series expansion
+@cindex @code{series()}
@cindex Taylor expansion
@cindex Laurent expansion
+@cindex @code{pseries} (class)
Expressions know how to expand themselves as a Taylor series or (more
-generally) a Laurent series. Similar to most conventional Computer
-Algebra Systems, no distinction is made between those two. There is a
-class of its own for storing such series as well as a class for storing
-the order of the series. A sample program could read:
+generally) a Laurent series. As in most conventional Computer Algebra
+Systems, no distinction is made between those two. There is a class of
+its own for storing such series (@code{class pseries}) and a built-in
+function (called @code{Order}) for storing the order term of the series.
+As a consequence, if you want to work with series, i.e. multiply two
+series, you need to call the method @code{ex::series} again to convert
+it to a series object with the usual structure (expansion plus order
+term). A sample application from special relativity could read:
@example
#include <ginac/ginac.h>
int main()
@{
- symbol x("x");
- numeric point(0);
- ex MyExpr1 = sin(x);
- ex MyExpr2 = 1/(x - pow(x, 2) - pow(x, 3));
- ex MyTailor, MySeries;
+ symbol v("v"), c("c");
- MyTailor = MyExpr1.series(x, point, 5);
- cout << MyExpr1 << " == " << MyTailor
- << " for small " << x << endl;
- MySeries = MyExpr2.series(x, point, 7);
- cout << MyExpr2 << " == " << MySeries
- << " for small " << x << endl;
- // ...
+ ex gamma = 1/sqrt(1 - pow(v/c,2));
+ ex mass_nonrel = gamma.series(v==0, 10);
+
+ cout << "the relativistic mass increase with v is " << endl
+ << mass_nonrel << endl;
+
+ cout << "the inverse square of this series is " << endl
+ << pow(mass_nonrel,-2).series(v==0, 10) << endl;
@}
@end example
+Only calling the series method makes the last output simplify to
+@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
-As an instructive application, let us calculate the numerical value of
-Archimedes' constant
+As another instructive application, let us calculate the numerical
+value of Archimedes' constant
@tex
$\pi$
@end tex
ex mechain_pi(int degr)
@{
symbol x;
- ex pi_expansion = series_to_poly(atan(x).series(x,0,degr));
+ ex pi_expansion = series_to_poly(atan(x).series(x,degr));
ex pi_approx = 16*pi_expansion.subs(x==numeric(1,5))
-4*pi_expansion.subs(x==numeric(1,239));
return pi_approx;
@}
@end example
-When you run this program, it will type out:
+Note how we just called @code{.series(x,degr)} instead of
+@code{.series(x==0,degr)}. This is a simple shortcut for @code{ex}'s
+method @code{series()}: if the first argument is a symbol the expression
+is expanded in that symbol around point @code{0}. When you run this
+program, it will type out:
@example
2: 3804/1195
@end example
-@node Extending GiNaC, What does not belong into GiNaC, Series Expansion, Top
+@node Built-in Functions, Input/Output, Series Expansion, Methods and Functions
+@c node-name, next, previous, up
+@section Predefined mathematical functions
+
+GiNaC contains the following predefined mathematical functions:
+
+@cartouche
+@multitable @columnfractions .30 .70
+@item @strong{Name} @tab @strong{Function}
+@item @code{abs(x)}
+@tab absolute value
+@item @code{csgn(x)}
+@tab complex sign
+@item @code{sqrt(x)}
+@tab square root (not a GiNaC function proper but equivalent to @code{pow(x, numeric(1, 2)})
+@item @code{sin(x)}
+@tab sine
+@item @code{cos(x)}
+@tab cosine
+@item @code{tan(x)}
+@tab tangent
+@item @code{asin(x)}
+@tab inverse sine
+@item @code{acos(x)}
+@tab inverse cosine
+@item @code{atan(x)}
+@tab inverse tangent
+@item @code{atan2(y, x)}
+@tab inverse tangent with two arguments
+@item @code{sinh(x)}
+@tab hyperbolic sine
+@item @code{cosh(x)}
+@tab hyperbolic cosine
+@item @code{tanh(x)}
+@tab hyperbolic tangent
+@item @code{asinh(x)}
+@tab inverse hyperbolic sine
+@item @code{acosh(x)}
+@tab inverse hyperbolic cosine
+@item @code{atanh(x)}
+@tab inverse hyperbolic tangent
+@item @code{exp(x)}
+@tab exponential function
+@item @code{log(x)}
+@tab natural logarithm
+@item @code{zeta(x)}
+@tab Riemann's zeta function
+@item @code{zeta(n, x)}
+@tab derivatives of Riemann's zeta function
+@item @code{tgamma(x)}
+@tab Gamma function
+@item @code{lgamma(x)}
+@tab logarithm of Gamma function
+@item @code{beta(x, y)}
+@tab Beta function (@code{tgamma(x)*tgamma(y)/tgamma(x+y)})
+@item @code{psi(x)}
+@tab psi (digamma) function
+@item @code{psi(n, x)}
+@tab derivatives of psi function (polygamma functions)
+@item @code{factorial(n)}
+@tab factorial function
+@item @code{binomial(n, m)}
+@tab binomial coefficients
+@item @code{Order(x)}
+@tab order term function in truncated power series
+@item @code{Derivative(x, l)}
+@tab inert partial differentiation operator (used internally)
+@end multitable
+@end cartouche
+
+@cindex branch cut
+For functions that have a branch cut in the complex plane GiNaC follows
+the conventions for C++ as defined in the ANSI standard. In particular:
+the natural logarithm (@code{log}) and the square root (@code{sqrt})
+both have their branch cuts running along the negative real axis where
+the points on the axis itself belong to the upper part.
+
+
+@node Input/Output, Extending GiNaC, Built-in Functions, Methods and Functions
+@c node-name, next, previous, up
+@section Input and output of expressions
+@cindex I/O
+
+@subsection Expression output
+@cindex printing
+@cindex output of expressions
+
+The easiest way to print an expression is to write it to a stream:
+
+@example
+@{
+ symbol x("x");
+ ex e = 7+4.2*pow(x,2);
+ cout << e << endl; // prints '7+4.2*x^2'
+ // ...
+@end example
+
+The output format is identical to the @command{ginsh} input syntax and
+to that used by most computer algebra systems, but not directly pastable
+into a GiNaC C++ program (note that in the above example, @code{pow(x,2)}
+is printed as @samp{x^2}).
+
+To print an expression in a way that can be directly used in a C or C++
+program, you use the method
+
+@example
+void ex::printcsrc(ostream & os, unsigned type, const char *name);
+@end example
+
+This outputs a line in the form of a variable definition @code{<type> <name> = <expression>}.
+The possible types are defined in @file{ginac/flags.h} (@code{csrc_types})
+and mostly affect the way in which floating point numbers are written:
+
+@example
+ // ...
+ e.printcsrc(cout, csrc_types::ctype_float, "f");
+ e.printcsrc(cout, csrc_types::ctype_double, "d");
+ e.printcsrc(cout, csrc_types::ctype_cl_N, "n");
+ // ...
+@end example
+
+The above example will produce (note the @code{x^2} being converted to @code{x*x}):
+
+@example
+float f = 4.200000e+00*(x*x)+7.000000e+00;
+double d = 4.200000e+00*(x*x)+7.000000e+00;
+cl_N n = cl_F("4.2000000000000001776")*(x*x)+cl_F("7.0");
+@end example
+
+Finally, there are the two methods @code{printraw()} and @code{printtree()} intended for GiNaC
+developers, that provide a dump of the internal structure of an expression for
+debugging purposes:
+
+@example
+ // ...
+ e.printraw(cout); cout << endl << endl;
+ e.printtree(cout);
+@}
+@end example
+
+produces
+
+@example
+ex(+((power(ex(symbol(name=x,serial=1,hash=150875740,flags=11)),ex(numeric(2)),hash=2,flags=3),numeric(4.2000000000000001776L0)),,hash=0,flags=3))
+
+type=Q25GiNaC3add, hash=0 (0x0), flags=3, nops=2
+ power: hash=2 (0x2), flags=3
+ x (symbol): serial=1, hash=150875740 (0x8fe2e5c), flags=11
+ 2 (numeric): hash=2147483714 (0x80000042), flags=11
+ 4.2000000000000001776L0 (numeric): hash=3006477126 (0xb3333346), flags=11
+ -----
+ overall_coeff
+ 7 (numeric): hash=2147483763 (0x80000073), flags=11
+ =====
+@end example
+
+The @code{printtree()} method is also available in @command{ginsh} as the
+@code{print()} function.
+
+
+@subsection Expression input
+@cindex input of expressions
+
+GiNaC provides no way to directly read an expression from a stream because
+you will usually want the user to be able to enter something like @samp{2*x+sin(y)}
+and have the @samp{x} and @samp{y} correspond to the symbols @code{x} and
+@code{y} you defined in your program and there is no way to specify the
+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:
+
+@example
+@{
+ symbol x("x"), y("y");
+ ex e("2*x+sin(y)", lst(x, y));
+@}
+@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.
+
+With this constructor, it's also easy to implement interactive GiNaC programs:
+
+@example
+#include <iostream>
+#include <string>
+#include <stdexcept>
+#include <ginac/ginac.h>
+using namespace GiNaC;
+
+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;
+ @}
+@}
+@end example
+
+
+@subsection Archiving
+@cindex @code{archive} (class)
+@cindex archiving
+
+GiNaC allows creating @dfn{archives} of expressions which can be stored
+to or retrieved from files. To create an archive, you declare an object
+of class @code{archive} and archive expressions in it, giving each
+expression a unique name:
+
+@example
+#include <ginac/ginac.h>
+#include <fstream>
+using namespace GiNaC;
+
+int main()
+@{
+ symbol x("x"), y("y"), z("z");
+
+ ex foo = sin(x + 2*y) + 3*z + 41;
+ ex bar = foo + 1;
+
+ archive a;
+ a.archive_ex(foo, "foo");
+ a.archive_ex(bar, "the second one");
+ // ...
+@end example
+
+The archive can then be written to a file:
+
+@example
+ // ...
+ ofstream out("foobar.gar");
+ out << a;
+ out.close();
+ // ...
+@end example
+
+The file @file{foobar.gar} contains all information that is needed to
+reconstruct the expressions @code{foo} and @code{bar}.
+
+@cindex @command{viewgar}
+The tool @command{viewgar} that comes with GiNaC can be used to view
+the contents of GiNaC archive files:
+
+@example
+$ viewgar foobar.gar
+foo = 41+sin(x+2*y)+3*z
+the second one = 42+sin(x+2*y)+3*z
+@end example
+
+The point of writing archive files is of course that they can later be
+read in again:
+
+@example
+ // ...
+ archive a2;
+ ifstream in("foobar.gar");
+ in >> a2;
+ // ...
+@end example
+
+And the stored expressions can be retrieved by their name:
+
+@example
+ // ...
+ lst syms(x, y);
+
+ ex ex1 = a2.unarchive_ex(syms, "foo");
+ ex ex2 = a2.unarchive_ex(syms, "the second one");
+
+ cout << ex1 << endl; // prints "41+sin(x+2*y)+3*z"
+ cout << ex2 << endl; // prints "42+sin(x+2*y)+3*z"
+ cout << ex1.subs(x == 2) << endl; // prints "41+sin(2+2*y)+3*z"
+@}
+@end example
+
+Note that you have to supply a list of the symbols which are to be inserted
+in the expressions. Symbols in archives are stored by their name only and
+if you don't specify which symbols you have, unarchiving the expression will
+create new symbols with that name. E.g. if you hadn't included @code{x} in
+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.
+
+
+
+@node Extending GiNaC, What does not belong into GiNaC, Input/Output, Top
@c node-name, next, previous, up
@chapter Extending GiNaC
@c node-name, next, previous, up
@section What doesn't belong into GiNaC
-@cindex @code{ginsh}
+@cindex @command{ginsh}
First of all, GiNaC's name must be read literally. It is designed to be
a library for use within C++. The tiny @command{ginsh} accompanying
GiNaC makes this even more clear: it doesn't even attempt to provide a
(using @code{Digits}). Some may be evaluated at certain points, but not
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 bignum-package
-@acronym{CLN} is much better suited.
+inefficient. For this purpose, the underlying foundation classes
+provided by @acronym{CLN} are much better suited.
@node Symbolic functions, A Comparison With Other CAS, What does not belong into GiNaC, Extending GiNaC
The easiest and most instructive way to start with is probably to
implement your own function. Objects of class @code{function} are
-inserted into the system via a kind of "registry". They get a serial
+inserted into the system via a kind of `registry'. They get a serial
number that is used internally to identify them but you usually need not
worry about this. What you have to care for are functions that are
called when the user invokes certain methods. These are usual
look something like this:
@example
-static ex cos_eval_method(ex const & x)
+static ex cos_eval_method(const ex & x)
@{
- // if x%2*Pi return 1
- // if x%Pi return -1
- // if x%Pi/2 return 0
+ // if (!x%(2*Pi)) return 1
+ // if (!x%Pi) return -1
+ // if (!x%Pi/2) return 0
// care for other cases...
return cos(x).hold();
@}
@end example
+@cindex @code{hold()}
+@cindex evaluation
The last line returns @code{cos(x)} if we don't know what else to do and
-stops a potential recursive evaluation by saying @code{.hold()}. We
+stops a potential recursive evaluation by saying @code{.hold()}, which
+sets a flag to the expression signaling that it has been evaluated. We
should also implement a method for numerical evaluation and since we are
lazy we sweep the problem under the rug by calling someone else's
function that does so, in this case the one in class @code{numeric}:
@example
-static ex cos_evalf_method(ex const & x)
+static ex cos_evalf(const ex & x)
@{
- return sin(ex_to_numeric(x));
+ return cos(ex_to_numeric(x));
@}
@end example
-Differentiation will surely turn up and so we need to tell
-@code{sin} how to differentiate itself:
+Differentiation will surely turn up and so we need to tell @code{cos}
+what the first derivative is (higher derivatives (@code{.diff(x,3)} for
+instance are then handled automatically by @code{basic::diff} and
+@code{ex::diff}):
@example
-static ex cos_diff_method(ex const & x, unsigned diff_param)
+static ex cos_deriv(const ex & x, unsigned diff_param)
@{
- return cos(x);
+ return -sin(x);
@}
@end example
are curious:
@example
-REGISTER_FUNCTION(cos, cos_eval_method, cos_evalf_method, cos_diff, NULL);
+REGISTER_FUNCTION(cos, eval_func(cos_eval).
+ evalf_func(cos_evalf).
+ derivative_func(cos_deriv));
@end example
-The first argument is the function's name, the second, third and fourth
-bind the corresponding methods to this objects and the fifth is a slot
-for inserting a method for series expansion. Also, the new function
-needs to be declared somewhere. This may also be done by a convenient
-preprocessor macro:
+The first argument is the function's name used for calling it and for
+output. The second binds the corresponding methods as options to this
+object. Options are separated by a dot and can be given in an arbitrary
+order. GiNaC functions understand several more options which are always
+specified as @code{.option(params)}, for example a method for series
+expansion @code{.series_func(cos_series)}. Again, if no series
+expansion method is given, GiNaC defaults to simple Taylor expansion,
+which is correct if there are no poles involved as is the case for the
+@code{cos} function. The way GiNaC handles poles in case there are any
+is best understood by studying one of the examples, like the Gamma
+(@code{tgamma}) function for instance. (In essence the function first
+checks if there is a pole at the evaluation point and falls back to
+Taylor expansion if there isn't. Then, the pole is regularized by some
+suitable transformation.) Also, the new function needs to be declared
+somewhere. This may also be done by a convenient preprocessor macro:
@example
DECLARE_FUNCTION_1P(cos)
mechanisms. Please, have a look at the real implementation in GiNaC.
(By the way: in case you are worrying about all the macros above we can
assure you that functions are GiNaC's most macro-intense classes. We
-have done our best to avoid them where we can.)
+have done our best to avoid macros where we can.)
That's it. May the source be with you!
-@node A Comparison With Other CAS, Internal Structures, Symbolic functions, Top
+@node A Comparison With Other CAS, Advantages, Symbolic functions, Top
@c node-name, next, previous, up
@chapter A Comparison With Other CAS
@cindex advocacy
@emph{Mathematica} or @emph{Reduce}, where it has advantages and
disadvantages over these systems.
+@menu
+* Advantages:: Stengths of the GiNaC approach.
+* Disadvantages:: Weaknesses of the GiNaC approach.
+* Why C++?:: Attractiveness of C++.
+@end menu
-@heading Advantages
+@node Advantages, Disadvantages, A Comparison With Other CAS, A Comparison With Other CAS
+@c node-name, next, previous, up
+@section Advantages
GiNaC has several advantages over traditional Computer
Algebra Systems, like
@item
familiar language: all common CAS implement their own proprietary
grammar which you have to learn first (and maybe learn again when your
-vendor chooses to "enhance" it). With GiNaC you can write your program
+vendor decides to `enhance' it). With GiNaC you can write your program
in common C++, which is standardized.
+@cindex STL
@item
structured data types: you can build up structured data types using
@code{struct}s or @code{class}es together with STL features instead of
@item
development tools: powerful development tools exist for C++, like fancy
editors (e.g. with automatic indentation and syntax highlighting),
-debuggers, visualization tools, documentation tools...
+debuggers, visualization tools, documentation generators...
@item
modularization: C++ programs can easily be split into modules by
by the parser. In particular, it turns out to be almost impossible to
fix bugs in a traditional system.
+@item
+multiple interfaces: Though real GiNaC programs have to be written in
+some editor, then be compiled, linked and executed, there are more ways
+to work with the GiNaC engine. Many people want to play with
+expressions interactively, as in traditional CASs. Currently, two such
+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.
+
@item
seemless integration: it is somewhere between difficult and impossible
to call CAS functions from within a program written in C++ or any other
are part of your program. You can easily call third party libraries,
e.g. for numerical evaluation or graphical interaction. All other
approaches are much more cumbersome: they range from simply ignoring the
-problem (i.e. @emph{Maple}) to providing a method for "embedding" the
+problem (i.e. @emph{Maple}) to providing a method for `embedding' the
system (i.e. @emph{Yacas}).
@item
efficiency: often large parts of a program do not need symbolic
calculations at all. Why use large integers for loop variables or
-arbitrary precision arithmetics where double accuracy is sufficient?
-For pure symbolic applications, GiNaC is comparable in speed with other
-CAS.
+arbitrary precision arithmetics where @code{int} and @code{double} are
+sufficient? For pure symbolic applications, GiNaC is comparable in
+speed with other CAS.
@end itemize
-@heading Disadvantages
+@node Disadvantages, Why C++?, Advantages, A Comparison With Other CAS
+@c node-name, next, previous, up
+@section Disadvantages
Of course it also has some disadvantages:
@itemize @bullet
-@item
-not interactive: GiNaC programs have to be written in an editor,
-compiled and executed. You cannot play with expressions interactively.
-However, such an extension is not inherently forbidden by design. In
-fact, two interactive interfaces are possible: First, a simple shell
-that exposes GiNaC's types to a command line can readily be written (and
-has been written) and second, as a more consistent approach we plan an
-integration with the @acronym{CINT} C++ interpreter.
-
@item
advanced features: GiNaC cannot compete with a program like
@emph{Reduce} which exists for more than 30 years now or @emph{Maple}
which grows since 1981 by the work of dozens of programmers, with
-respect to mathematical features. Integration, factorization,
+respect to mathematical features. Integration, factorization,
non-trivial simplifications, limits etc. are missing in GiNaC (and are
not planned for the near future).
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}). 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.
+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.
@end itemize
-@heading Why C++?
+@node Why C++?, Internal Structures, Disadvantages, A Comparison With Other CAS
+@c node-name, next, previous, up
+@section Why C++?
Why did we choose to implement GiNaC in C++ instead of Java or any other
-language? C++ is not perfect: type checking is not strict (casting is
+language? C++ is not perfect: type checking is not strict (casting is
possible), separation between interface and implementation is not
complete, object oriented design is not enforced. The main reason is
-the often scolded feature of operator overloading in C++. While it may
+the often scolded feature of operator overloading in C++. While it may
be true that operating on classes with a @code{+} operator is rarely
-meaningful, it is perfectly suited for algebraic expressions. Writing
+meaningful, it is perfectly suited for algebraic expressions. Writing
@math{3x+5y} as @code{3*x+5*y} instead of
-@code{x.times(3).plus(y.times(5))} looks much more natural. Furthermore,
-the main developers are more familiar with C++ than with any other
-programming language.
+@code{x.times(3).plus(y.times(5))} looks much more natural.
+Furthermore, the main developers are more familiar with C++ than with
+any other programming language.
-@node Internal Structures, Expressions are reference counted, A Comparison With Other CAS, Top
+@node Internal Structures, Expressions are reference counted, Why C++? , Top
@c node-name, next, previous, up
@appendix Internal Structures
cout << e2 << endl; // prints sin(x+2*y)+3*z+41
e2 += 1; // e2 is copied into a new object
cout << e2 << endl; // prints sin(x+2*y)+3*z+42
- // ...
@}
@end example
cout << e1 << endl // prints x+3*y
<< e2 << endl // prints (x+3*y)^3
<< e3 << endl; // prints 3*(x+3*y)^2*cos((x+3*y)^3)
- // ...
@}
@end example
@cindex pair-wise representation
However, doing so results in a rather deeply nested tree which will
quickly become inefficient to manipulate. We can improve on this by
-representing the sum instead as a sequence of terms, each one being a
-pair of a purely numeric multiplicative coefficient and its rest. In
-the same spirit we can store the multiplication as a sequence of terms,
-each having a numeric exponent and a possibly complicated base, the tree
+representing the sum as a sequence of terms, each one being a pair of a
+purely numeric multiplicative coefficient and its rest. In the same
+spirit we can store the multiplication as a sequence of terms, each
+having a numeric exponent and a possibly complicated base, the tree
becomes much more flat:
@image{reppair}
coefficient. This results in the realistic picture of internal
representation for
@tex
-$2d^3 \left( 4a + 5b - 3 \right)$
+$2d^3 \left( 4a + 5b - 3 \right)$:
@end tex
@ifnottex
-@math{2*d^3*(4*a+5*b-3)}
+@math{2*d^3*(4*a+5*b-3)}:
@end ifnottex
-:
@image{repreal}
+@cindex radical
This also allows for a better handling of numeric radicals, since
@code{sqrt(2)} can now be carried along calculations. Now it should be
clear, why both classes @code{add} and @code{mul} are derived from the
Prints out the linker flags necessary to link a program against GiNaC.
@item --prefix[=@var{PREFIX}]
If @var{PREFIX} is specified, overrides the configured value of @env{$prefix}.
-(And of exec-prefix, unless --exec-prefix is also specified)
+(And of exec-prefix, unless @code{--exec-prefix} is also specified)
Otherwise, prints out the configured value of @env{$prefix}.
@item --exec-prefix[=@var{PREFIX}]
If @var{PREFIX} is specified, overrides the configured value of @env{$exec_prefix}.
Otherwise, prints out the configured value of @env{$exec_prefix}.
@end table
-Typically, @command{ginac-config} will be used within a configure script,
-as described below. It, however, can also be used directly
-from the command line to compile a simple program. For example:
+Typically, @command{ginac-config} will be used within a configure
+script, as described below. It, however, can also be used directly from
+the command line using backquotes to compile a simple program. For
+example:
@example
c++ -o simple `ginac-config --cppflags` simple.cpp `ginac-config --libs`
@env{GINACLIB_CONFIG}.
@item
-Tests the installed libraries to make sure that there version
+Tests the installed libraries to make sure that their version
is later than @var{MINIMUM-VERSION}. (A default version will be used
if not specified)
@item
If you move the GiNaC package from its installed location,
-you will need either need to modify @command{ginac-config} script
+you will either need to modify @command{ginac-config} script
manually to point to the new location or rebuild GiNaC.
@end itemize
@display
If a GiNaC version greater than 0.4.0 is found, adds @env{$GINACLIB_LIBS} to
@env{$LIBS} and @env{$GINACLIB_CPPFLAGS} to @env{$CPPFLAGS}. Otherwise, dies
-with the error message "need to have GiNaC installed"
+with the error message `need to have GiNaC installed'
@end display
And the @file{Makefile.am}, which will be used to build the Makefile.
git://www.ginac.de / ginac.git / blobdiff