+@menu
+* Information About Expressions::
+* Substituting Expressions::
+* Pattern Matching and Advanced Substitutions::
+* Applying a Function on Subexpressions::
+* Visitors and Tree Traversal::
+* 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.
+* Solving Linear Systems of Equations::
+* Input/Output:: Input and output of expressions.
+@end menu
+
+
+@node Information About Expressions, Substituting Expressions, Methods and Functions, Methods and Functions
+@c node-name, next, previous, up
+@section Getting information about expressions
+
+@subsection Checking expression types
+@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 a couple of functions for this:
+
+@example
+bool is_a<T>(const ex & e);
+bool is_exactly_a<T>(const ex & e);
+bool ex::info(unsigned flag);
+unsigned ex::return_type() const;
+unsigned ex::return_type_tinfo() const;
+@end example
+
+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_a<numeric>(e))
+ numeric n = ex_to<numeric>(e);
+ @dots{}
+@}
+@end example
+
+@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:
+
+@example
+@{
+ symbol x("x");
+ ex e1 = 42;
+ ex e2 = 4*x - 3;
+ 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
+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_<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_a<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_a<symbol>(...)})
+@item @code{list}
+@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}
+@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 (@math{x+y}, @math{z/(x+y)})
+@item @code{algebraic}
+@tab @dots{}an algebraic object (@math{sqrt(2)}, @math{sqrt(x)-1})
+@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 container
+@cindex @code{relational} (class)
+
+GiNaC provides the two methods
+
+@example
+size_t ex::nops();
+ex ex::op(size_t 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. For @code{indexed} objects, @code{op(0)}
+is the base expression and @code{op(i)}, @math{i>0} are the indices.
+
+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
+
+
+@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 (@pxref{Relations})
+which is not evaluated until (explicitly or implicitly) 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.
+
+
+@subsection Ordering expressions
+@cindex @code{ex_is_less} (class)
+@cindex @code{ex_is_equal} (class)
+@cindex @code{compare()}
+
+Sometimes it is necessary to establish a mathematically well-defined ordering
+on a set of arbitrary expressions, for example to use expressions as keys
+in a @code{std::map<>} container, or to bring a vector of expressions into
+a canonical order (which is done internally by GiNaC for sums and products).
+
+The operators @code{<}, @code{>} etc. described in the last section cannot
+be used for this, as they don't implement an ordering relation in the
+mathematical sense. In particular, they are not guaranteed to be
+antisymmetric: if @samp{a} and @samp{b} are different expressions, and
+@code{a < b} yields @code{false}, then @code{b < a} doesn't necessarily
+yield @code{true}.
+
+By default, STL classes and algorithms use the @code{<} and @code{==}
+operators to compare objects, which are unsuitable for expressions, but GiNaC
+provides two functors that can be supplied as proper binary comparison
+predicates to the STL:
+
+@example
+class ex_is_less : public std::binary_function<ex, ex, bool> @{
+public:
+ bool operator()(const ex &lh, const ex &rh) const;
+@};
+
+class ex_is_equal : public std::binary_function<ex, ex, bool> @{
+public:
+ bool operator()(const ex &lh, const ex &rh) const;
+@};
+@end example
+
+For example, to define a @code{map} that maps expressions to strings you
+have to use
+
+@example
+std::map<ex, std::string, ex_is_less> myMap;
+@end example
+
+Omitting the @code{ex_is_less} template parameter will introduce spurious
+bugs because the map operates improperly.
+
+Other examples for the use of the functors:
+
+@example
+std::vector<ex> v;
+// fill vector
+...
+
+// sort vector
+std::sort(v.begin(), v.end(), ex_is_less());
+
+// count the number of expressions equal to '1'
+unsigned num_ones = std::count_if(v.begin(), v.end(),
+ std::bind2nd(ex_is_equal(), 1));
+@end example
+
+The implementation of @code{ex_is_less} uses the member function
+
+@example
+int ex::compare(const ex & other) const;
+@end example
+
+which returns @math{0} if @code{*this} and @code{other} are equal, @math{-1}
+if @code{*this} sorts before @code{other}, and @math{1} if @code{*this} sorts
+after @code{other}.
+
+
+@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()}
+
+Algebraic objects inside expressions can be replaced with arbitrary
+expressions via the @code{.subs()} method:
+
+@example
+ex ex::subs(const ex & e, unsigned options = 0);
+ex ex::subs(const lst & syms, const lst & repls, unsigned options = 0);
+@end example
+
+In the first form, @code{subs()} accepts a relational of the form
+@samp{object == expression} or a @code{lst} of such relationals:
+
+@example
+@{
+ symbol x("x"), y("y");
+
+ ex e1 = 2*x^2-4*x+3;
+ cout << "e1(7) = " << e1.subs(x == 7) << endl;
+ // -> 73
+
+ ex e2 = x*y + x;
+ cout << "e2(-2, 4) = " << e2.subs(lst(x == -2, y == 4)) << endl;
+ // -> -10
+@}
+@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}.
+
+The optional last argument to @code{subs()} is a combination of
+@code{subs_options} flags. There are two options available:
+@code{subs_options::no_pattern} disables pattern matching, which makes
+large @code{subs()} operations significantly faster if you are not using
+patterns. The second option, @code{subs_options::algebraic} enables
+algebraic substitutions in products and powers.
+@ref{Pattern Matching and Advanced Substitutions}, for more information
+about patterns and algebraic substitutions.
+
+@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:
+
+@example
+@{
+ symbol x("x"), y("y"), z("z");
+
+ ex e1 = pow(x+y, 2);
+ cout << e1.subs(x+y == 4) << endl;
+ // -> 16
+
+ ex e2 = sin(x)*sin(y)*cos(x);
+ cout << e2.subs(sin(x) == cos(x)) << endl;
+ // -> cos(x)^2*sin(y)
+
+ ex e3 = x+y+z;
+ cout << e3.subs(x+y == 4) << endl;
+ // -> x+y+z
+ // (and not 4+z as one might expect)
+@}
+@end example
+
+A more powerful form of substitution using wildcards is described in the
+next section.
+
+
+@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 appends all found matches to 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
+
+@subsection Algebraic substitutions
+Supplying the @code{subs_options::algebraic} option to @code{subs()}
+enables smarter, algebraic substitutions in products and powers. If you want
+to substitute some factors of a product, you only need to list these factors
+in your pattern. Furthermore, if an (integer) power of some expression occurs
+in your pattern and in the expression that you want the substitution to occur
+in, it can be substituted as many times as possible, without getting negative
+powers.
+
+An example clarifies it all (hopefully):
+
+@example
+cout << (a*a*a*a+b*b*b*b+pow(x+y,4)).subs(wild()*wild()==pow(wild(),3),
+ subs_options::algebraic) << endl;
+// --> (y+x)^6+b^6+a^6
+
+cout << ((a+b+c)*(a+b+c)).subs(a+b==x,subs_options::algebraic) << endl;
+// --> (c+b+a)^2
+// Powers and products are smart, but addition is just the same.
+
+cout << ((a+b+c)*(a+b+c)).subs(a+b+wild()==x+wild(), subs_options::algebraic)
+ << endl;
+// --> (x+c)^2
+// As I said: addition is just the same.
+
+cout << (pow(a,5)*pow(b,7)+2*b).subs(b*b*a==x,subs_options::algebraic) << endl;
+// --> x^3*b*a^2+2*b
+
+cout << (pow(a,-5)*pow(b,-7)+2*b).subs(1/(b*b*a)==x,subs_options::algebraic)
+ << endl;
+// --> 2*b+x^3*b^(-1)*a^(-2)
+
+cout << (4*x*x*x-2*x*x+5*x-1).subs(x==a,subs_options::algebraic) << endl;
+// --> -1-2*a^2+4*a^3+5*a
+
+cout << (4*x*x*x-2*x*x+5*x-1).subs(pow(x,wild())==pow(a,wild()),
+ subs_options::algebraic) << endl;
+// --> -1+5*x+4*x^3-2*x^2
+// You should not really need this kind of patterns very often now.
+// But perhaps this it's-not-a-bug-it's-a-feature (c/sh)ould still change.
+
+cout << ex(sin(1+sin(x))).subs(sin(wild())==cos(wild()),
+ subs_options::algebraic) << endl;
+// --> cos(1+cos(x))
+
+cout << expand((a*sin(x+y)*sin(x+y)+a*cos(x+y)*cos(x+y)+b)
+ .subs((pow(cos(wild()),2)==1-pow(sin(wild()),2)),
+ subs_options::algebraic)) << endl;
+// --> b+a
+@end example
+
+
+@node Applying a Function on Subexpressions, Visitors and Tree Traversal, 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 (size_t 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 Visitors and Tree Traversal, Polynomial Arithmetic, Applying a Function on Subexpressions, Methods and Functions
+@c node-name, next, previous, up
+@section Visitors and Tree Traversal
+@cindex tree traversal
+@cindex @code{visitor} (class)
+@cindex @code{accept()}
+@cindex @code{visit()}
+@cindex @code{traverse()}
+@cindex @code{traverse_preorder()}
+@cindex @code{traverse_postorder()}
+
+Suppose that you need a function that returns a list of all indices appearing
+in an arbitrary expression. The indices can have any dimension, and for
+indices with variance you always want the covariant version returned.
+
+You can't use @code{get_free_indices()} because you also want to include
+dummy indices in the list, and you can't use @code{find()} as it needs
+specific index dimensions (and it would require two passes: one for indices
+with variance, one for plain ones).
+
+The obvious solution to this problem is a tree traversal with a type switch,
+such as the following:
+
+@example
+void gather_indices_helper(const ex & e, lst & l)
+@{
+ if (is_a<varidx>(e)) @{
+ const varidx & vi = ex_to<varidx>(e);
+ l.append(vi.is_covariant() ? vi : vi.toggle_variance());
+ @} else if (is_a<idx>(e)) @{
+ l.append(e);
+ @} else @{
+ size_t n = e.nops();
+ for (size_t i = 0; i < n; ++i)
+ gather_indices_helper(e.op(i), l);
+ @}
+@}
+
+lst gather_indices(const ex & e)
+@{
+ lst l;
+ gather_indices_helper(e, l);
+ l.sort();
+ l.unique();
+ return l;
+@}
+@end example
+
+This works fine but fans of object-oriented programming will feel
+uncomfortable with the type switch. One reason is that there is a possibility
+for subtle bugs regarding derived classes. If we had, for example, written
+
+@example
+ if (is_a<idx>(e)) @{
+ ...
+ @} else if (is_a<varidx>(e)) @{
+ ...
+@end example
+
+in @code{gather_indices_helper}, the code wouldn't have worked because the
+first line "absorbs" all classes derived from @code{idx}, including
+@code{varidx}, so the special case for @code{varidx} would never have been
+executed.
+
+Also, for a large number of classes, a type switch like the above can get
+unwieldy and inefficient (it's a linear search, after all).
+@code{gather_indices_helper} only checks for two classes, but if you had to
+write a function that required a different implementation for nearly
+every GiNaC class, the result would be very hard to maintain and extend.
+
+The cleanest approach to the problem would be to add a new virtual function
+to GiNaC's class hierarchy. In our example, there would be specializations
+for @code{idx} and @code{varidx} while the default implementation in
+@code{basic} performed the tree traversal. Unfortunately, in C++ it's
+impossible to add virtual member functions to existing classes without
+changing their source and recompiling everything. GiNaC comes with source,
+so you could actually do this, but for a small algorithm like the one
+presented this would be impractical.
+
+One solution to this dilemma is the @dfn{Visitor} design pattern,
+which is implemented in GiNaC (actually, Robert Martin's Acyclic Visitor
+variation, described in detail in
+@uref{http://objectmentor.com/publications/acv.pdf}). Instead of adding
+virtual functions to the class hierarchy to implement operations, GiNaC
+provides a single "bouncing" method @code{accept()} that takes an instance
+of a special @code{visitor} class and redirects execution to the one
+@code{visit()} virtual function of the visitor that matches the type of
+object that @code{accept()} was being invoked on.
+
+Visitors in GiNaC must derive from the global @code{visitor} class as well
+as from the class @code{T::visitor} of each class @code{T} they want to
+visit, and implement the member functions @code{void visit(const T &)} for
+each class.
+
+A call of
+
+@example
+void ex::accept(visitor & v) const;
+@end example
+
+will then dispatch to the correct @code{visit()} member function of the
+specified visitor @code{v} for the type of GiNaC object at the root of the
+expression tree (e.g. a @code{symbol}, an @code{idx} or a @code{mul}).
+
+Here is an example of a visitor:
+
+@example
+class my_visitor
+ : public visitor, // this is required
+ public add::visitor, // visit add objects
+ public numeric::visitor, // visit numeric objects
+ public basic::visitor // visit basic objects
+@{
+ void visit(const add & x)
+ @{ cout << "called with an add object" << endl; @}
+
+ void visit(const numeric & x)
+ @{ cout << "called with a numeric object" << endl; @}
+
+ void visit(const basic & x)
+ @{ cout << "called with a basic object" << endl; @}
+@};
+@end example
+
+which can be used as follows:
+
+@example
+...
+ symbol x("x");
+ ex e1 = 42;
+ ex e2 = 4*x-3;
+ ex e3 = 8*x;
+
+ my_visitor v;
+ e1.accept(v);
+ // prints "called with a numeric object"
+ e2.accept(v);
+ // prints "called with an add object"
+ e3.accept(v);
+ // prints "called with a basic object"
+...
+@end example
+
+The @code{visit(const basic &)} method gets called for all objects that are
+not @code{numeric} or @code{add} and acts as an (optional) default.
+
+From a conceptual point of view, the @code{visit()} methods of the visitor
+behave like a newly added virtual function of the visited hierarchy.
+In addition, visitors can store state in member variables, and they can
+be extended by deriving a new visitor from an existing one, thus building
+hierarchies of visitors.
+
+We can now rewrite our index example from above with a visitor:
+
+@example
+class gather_indices_visitor
+ : public visitor, public idx::visitor, public varidx::visitor
+@{
+ lst l;
+
+ void visit(const idx & i)
+ @{
+ l.append(i);
+ @}
+
+ void visit(const varidx & vi)
+ @{
+ l.append(vi.is_covariant() ? vi : vi.toggle_variance());
+ @}
+
+public:
+ const lst & get_result() // utility function
+ @{
+ l.sort();
+ l.unique();
+ return l;
+ @}
+@};
+@end example
+
+What's missing is the tree traversal. We could implement it in
+@code{visit(const basic &)}, but GiNaC has predefined methods for this:
+
+@example
+void ex::traverse_preorder(visitor & v) const;
+void ex::traverse_postorder(visitor & v) const;
+void ex::traverse(visitor & v) const;
+@end example
+
+@code{traverse_preorder()} visits a node @emph{before} visiting its
+subexpressions, while @code{traverse_postorder()} visits a node @emph{after}
+visiting its subexpressions. @code{traverse()} is a synonym for
+@code{traverse_preorder()}.
+
+Here is a new implementation of @code{gather_indices()} that uses the visitor
+and @code{traverse()}:
+
+@example
+lst gather_indices(const ex & e)
+@{
+ gather_indices_visitor v;
+ e.traverse(v);
+ return v.get_result();
+@}
+@end example
+
+
+@node Polynomial Arithmetic, Rational Expressions, Visitors and Tree Traversal, 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
+for example the trivariate polynomial @math{4*x*y + x*z + 20*y^2 +
+21*y*z + 4*z^2} (written down here in output-style). It is equivalent
+to the factorized polynomial @math{(x + 5*y + 4*z)*(4*y + z)}. Other
+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 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}.
+
+To bring an expression into expanded form, its method
+
+@example
+ex ex::expand(unsigned options = 0);
+@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!
+
+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:
+
+@example
+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
+
+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()}
+@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(const ex & s);
+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
+
+@example
+ex ex::coeff(const ex & s, int n);
+@end example
+
+You can also obtain the leading and trailing coefficients with the methods
+
+@example
+ex ex::lcoeff(const ex & s);
+ex ex::tcoeff(const ex & 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
+@{
+ symbol x("x"), y("y");
+ ex PolyInp = 4*pow(x,3)*y + 5*x*pow(y,2) + 3*y
+ - pow(x+y,2) + 2*pow(y+2,2) - 8;
+ ex Poly = PolyInp.expand();
+
+ for (int i=Poly.ldegree(x); i<=Poly.degree(x); ++i) @{
+ cout << "The x^" << i << "-coefficient is "
+ << Poly.coeff(x,i) << endl;
+ @}
+ cout << "As polynomial in y: "
+ << Poly.collect(y) << endl;
+@}
+@end example
+
+When run, it returns an output in the following fashion:
+
+@example
+The x^0-coefficient is y^2+11*y
+The x^1-coefficient is 5*y^2-2*y
+The x^2-coefficient is -1
+The x^3-coefficient is 4*y
+As polynomial in y: -x^2+(5*x+1)*y^2+(-2*x+4*x^3+11)*y
+@end example
+
+As always, the exact output may vary between different versions of GiNaC
+or even from run to run since the internal canonical ordering is not
+within the user's sphere of influence.
+
+@code{degree()}, @code{ldegree()}, @code{coeff()}, @code{lcoeff()},
+@code{tcoeff()} and @code{collect()} can also be used to a certain degree
+with non-polynomial expressions as they not only work with symbols but with
+constants, functions and indexed objects as well:
+
+@example
+@{
+ symbol a("a"), b("b"), c("c");
+ idx i(symbol("i"), 3);
+
+ ex e = pow(sin(x) - cos(x), 4);
+ cout << e.degree(cos(x)) << endl;
+ // -> 4
+ cout << e.expand().coeff(sin(x), 3) << endl;
+ // -> -4*cos(x)
+
+ e = indexed(a+b, i) * indexed(b+c, i);
+ e = e.expand(expand_options::expand_indexed);
+ cout << e.collect(indexed(b, i)) << endl;
+ // -> a.i*c.i+(a.i+c.i)*b.i+b.i^2
+@}
+@end example
+
+
+@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 ex & x);
+ex rem(const ex & a, const ex & b, const ex & 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 ex & 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 ex & x);
+ex ex::content(const ex & x);
+ex ex::primpart(const ex & 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
+
+@example
+ex gcd(const ex & a, const ex & b);
+ex lcm(const ex & a, const ex & b);
+@end example
+
+The functions @code{gcd()} and @code{lcm()} accept two expressions
+@code{a} and @code{b} as arguments and return a new expression, their
+greatest common divisor or least common multiple, respectively. If the
+polynomials @code{a} and @code{b} are coprime @code{gcd(a,b)} returns 1
+and @code{lcm(a,b)} returns the product of @code{a} and @code{b}.
+
+@example
+#include <ginac/ginac.h>
+using namespace GiNaC;
+
+int main()
+@{
+ symbol x("x"), y("y"), z("z");
+ ex P_a = 4*x*y + x*z + 20*pow(y, 2) + 21*y*z + 4*pow(z, 2);
+ ex P_b = x*y + 3*x*z + 5*pow(y, 2) + 19*y*z + 12*pow(z, 2);
+
+ ex P_gcd = gcd(P_a, P_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
+
+
+@subsection Square-free decomposition
+@cindex square-free decomposition
+@cindex factorization
+@cindex @code{sqrfree()}
+
+GiNaC still lacks proper factorization support. Some form of
+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 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 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(2-2*y,3) * pow(1+x*y,2) * pow(x-2*y,2) * (x+y));
+
+ cout << sqrfree(BiVarPol, lst(x,y)) << endl;
+ // -> 8*(1-y)^3*(y*x^2-2*y+x*(1-2*y^2))^2*(y+x)
+
+ cout << sqrfree(BiVarPol, lst(y,x)) << endl;
+ // -> 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
+@c node-name, next, previous, up
+@section Rational expressions
+
+@subsection The @code{normal} method
+@cindex @code{normal()}
+@cindex simplification
+@cindex temporary replacement
+
+Some basic form 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 code snippet:
+
+@example
+@{
+ symbol x("x");
+ ex t1 = (pow(x,2) + 2*x + 1)/(x + 1);
+ ex t2 = (pow(sin(x),2) + 2*sin(x) + 1)/(sin(x) + 1);
+ std::cout << "t1 is " << t1.normal() << std::endl;
+ std::cout << "t2 is " << t2.normal() << std::endl;
+@}
+@end example
+
+Of course this works for multivariate polynomials too, so the ratio of
+the sample-polynomials from the section about GCD and LCM above would be
+normalized to @code{P_a/P_b} = @code{(4*y+z)/(y+3*z)}.
+
+
+@subsection Numerator and denominator
+@cindex numerator
+@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, 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 polynomial or rational expression
+@cindex @code{to_polynomial()}
+@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_polynomial(lst &l);
+@end example
+or
+@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_polynomial()} or @code{.to_rational()}, so it's possible to use
+it on multiple expressions and get consistent results.
+
+The difference betwerrn @code{.to_polynomial()} and @code{.to_rational()}
+is probably best illustrated with an example:
+
+@example
+@{
+ symbol x("x"), y("y");
+ ex a = 2*x/sin(x) - y/(3*sin(x));
+ cout << a << endl;
+
+ lst lp;
+ ex p = a.to_polynomial(lp);
+ cout << " = " << p << "\n with " << lp << endl;
+ // = symbol3*symbol2*y+2*symbol2*x
+ // with @{symbol2==sin(x)^(-1),symbol3==-1/3@}
+
+ lst lr;
+ ex r = a.to_rational(lr);
+ cout << " = " << r << "\n with " << lr << endl;
+ // = -1/3*symbol4^(-1)*y+2*symbol4^(-1)*x
+ // with @{symbol4==sin(x)@}
+@}
+@end example
+
+The following more useful example will print @samp{sin(x)-cos(x)}:
+
+@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_polynomial(l), b.to_polynomial(l), q);
+ cout << q.subs(l) << endl;
+@}
+@end example
+
+
+@node Symbolic Differentiation, Series Expansion, Rational Expressions, Methods and Functions
+@c node-name, next, previous, up
+@section Symbolic differentiation
+@cindex differentiation
+@cindex @code{diff()}
+@cindex chain rule
+@cindex product rule
+
+GiNaC's objects know how to differentiate themselves. Thus, a
+polynomial (class @code{add}) knows that its derivative is the sum of
+the derivatives of all the monomials:
+
+@example
+@{
+ 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(y) << endl; // 1
+ // -> 1
+ cout << P.diff(z) << endl; // 0
+ // -> 0
+@}
+@end example
+
+If a second integer parameter @var{n} is given, the @code{diff} method
+returns the @var{n}th derivative.
+
+If @emph{every} object and every function is told what its derivative
+is, all derivatives of composed objects can be calculated using the
+chain rule and the product rule. Consider, for instance the expression
+@code{1/cosh(x)}. Since the derivative of @code{cosh(x)} is
+@code{sinh(x)} and the derivative of @code{pow(x,-1)} is
+@code{-pow(x,-2)}, GiNaC can readily compute the composition. It turns
+out that the composition is the generating function for Euler Numbers,
+i.e. the so called @var{n}th Euler number is the coefficient of
+@code{x^n/n!} in the expansion of @code{1/cosh(x)}. We may use this
+identity to code a function that generates Euler numbers in just three
+lines:
+
+@cindex Euler numbers
+@example
+#include <ginac/ginac.h>
+using namespace GiNaC;
+
+ex EulerNumber(unsigned n)
+@{
+ symbol x;
+ const ex generator = pow(cosh(x),-1);
+ return generator.diff(x,n).subs(x==0);
+@}
+
+int main()
+@{
+ for (unsigned i=0; i<11; i+=2)
+ std::cout << EulerNumber(i) << std::endl;
+ return 0;
+@}
+@end example
+
+When you run it, it produces the sequence @code{1}, @code{-1}, @code{5},
+@code{-61}, @code{1385}, @code{-50521}. We increment the loop variable
+@code{i} by two since all odd Euler numbers vanish anyways.
+
+
+@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
+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>
+using namespace std;
+using namespace GiNaC;
+
+int main()
+@{
+ symbol v("v"), c("c");
+
+ 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 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 John Machin's amazing formula
+@tex
+$\pi=16$~atan~$\!\left(1 \over 5 \right)-4$~atan~$\!\left(1 \over 239 \right)$.
+@end tex
+@ifnottex
+@math{Pi==16*atan(1/5)-4*atan(1/239)}.
+@end ifnottex
+This equation (and similar ones) were used for over 200 years for
+computing digits of pi (see @cite{Pi Unleashed}). We may expand the
+arcus tangent around @code{0} and insert the fractions @code{1/5} and
+@code{1/239}. However, as we have seen, a series in GiNaC carries an
+order term with it and the question arises what the system is supposed
+to do when the fractions are plugged into that order term. The solution
+is to use the function @code{series_to_poly()} to simply strip the order
+term off:
+
+@example
+#include <ginac/ginac.h>
+using namespace GiNaC;
+
+ex machin_pi(int degr)
+@{
+ symbol x;
+ 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;
+@}
+
+int main()
+@{
+ using std::cout; // just for fun, another way of...
+ using std::endl; // ...dealing with this namespace std.
+ ex pi_frac;
+ for (int i=2; i<12; i+=2) @{
+ pi_frac = machin_pi(i);
+ cout << i << ":\t" << pi_frac << endl
+ << "\t" << pi_frac.evalf() << endl;
+ @}
+ return 0;
+@}
+@end example
+
+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
+ 3.1832635983263598326
+4: 5359397032/1706489875
+ 3.1405970293260603143
+6: 38279241713339684/12184551018734375
+ 3.141621029325034425
+8: 76528487109180192540976/24359780855939418203125
+ 3.141591772182177295
+10: 327853873402258685803048818236/104359128170408663038552734375
+ 3.1415926824043995174
+@end example
+
+
+@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, Solving Linear Systems of Equations, Symmetrization, 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
+@cindex @code{abs()}
+@item @code{csgn(x)}
+@tab complex sign
+@cindex @code{csgn()}
+@item @code{sqrt(x)}
+@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
+@cindex @code{Order()}
+@item @code{Li(n,x)}
+@tab polylogarithm
+@cindex @code{Li()}
+@item @code{S(n,p,x)}
+@tab Nielsen's generalized polylogarithm
+@cindex @code{S()}
+@item @code{H(m_lst,x)}
+@tab harmonic polylogarithm
+@cindex @code{H()}
+@item @code{Li(m_lst,x_lst)}
+@tab multiple polylogarithm
+@cindex @code{Li()}
+@item @code{mZeta(m_lst)}
+@tab multiple zeta value
+@cindex @code{mZeta()}
+@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 as far as
+possible. 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 (i.e. continuous with quadrant II). The inverse
+trigonometric and hyperbolic functions are not defined for complex
+arguments by the C++ standard, however. In GiNaC we follow the
+conventions used by CLN, which in turn follow the carefully designed
+definitions in the Common Lisp standard. It should be noted that this
+convention is identical to the one used by the C99 standard and by most
+serious CAS. It is to be expected that future revisions of the C++
+standard incorporate these functions in the complex domain in a manner
+compatible with C99.
+
+
+@node Solving Linear Systems of Equations, Input/Output, Built-in Functions, Methods and Functions
+@c node-name, next, previous, up
+@section Solving Linear Systems of Equations
+@cindex @code{lsolve()}
+
+The function @code{lsolve()} provides a convenient wrapper around some
+matrix operations that comes in handy when a system of linear equations
+needs to be solved:
+
+@example
+ex lsolve(const ex &eqns, const ex &symbols, unsigned options=solve_algo::automatic);
+@end example
+
+Here, @code{eqns} is a @code{lst} of equalities (i.e. class
+@code{relational}) while @code{symbols} is a @code{lst} of
+indeterminates. (@xref{The Class Hierarchy}, for an exposition of class
+@code{lst}).
+
+It returns the @code{lst} of solutions as an expression. As an example,
+let us solve the two equations @code{a*x+b*y==3} and @code{x-y==b}:
+
+@example
+@{
+ symbol a("a"), b("b"), x("x"), y("y");
+ lst eqns;
+ eqns.append(a*x+b*y==3).append(x-y==b);
+ lst vars;
+ vars.append(x).append(y);
+ cout << lsolve(eqns, vars) << endl;
+ // -> @{x==(3+b^2)/(b+a),y==(3-b*a)/(b+a)@}
+@end example
+
+When the linear equations @code{eqns} are underdetermined, the solution
+will contain one or more tautological entries like @code{x==x},
+depending on the rank of the system. When they are overdetermined, the
+solution will be an empty @code{lst}. Note the third optional parameter
+to @code{lsolve()}: it accepts the same parameters as
+@code{matrix::solve()}. This is because @code{lsolve} is just a wrapper
+around that method.
+
+
+@node Input/Output, Extending GiNaC, Solving Linear Systems of Equations, 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
+
+Expressions can simply be written to any stream:
+
+@example
+@{
+ symbol x("x");
+ ex e = 4.5*I+pow(x,2)*3/2;
+ cout << e << endl; // prints '4.5*I+3/2*x^2'
+ // ...
+@end example
+
+The default 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}).
+
+It is possible to print expressions in a number of different formats with
+a set of stream manipulators;
+
+@example
+std::ostream & dflt(std::ostream & os);
+std::ostream & latex(std::ostream & os);
+std::ostream & tree(std::ostream & os);
+std::ostream & csrc(std::ostream & os);
+std::ostream & csrc_float(std::ostream & os);
+std::ostream & csrc_double(std::ostream & os);
+std::ostream & csrc_cl_N(std::ostream & os);
+std::ostream & index_dimensions(std::ostream & os);
+std::ostream & no_index_dimensions(std::ostream & os);
+@end example
+
+The @code{tree}, @code{latex} and @code{csrc} formats are also available in
+@command{ginsh} via the @code{print()}, @code{print_latex()} and
+@code{print_csrc()} functions, respectively.
+
+@cindex @code{dflt}
+All manipulators affect the stream state permanently. To reset the output
+format to the default, use the @code{dflt} manipulator:
+
+@example
+ // ...
+ cout << latex; // all output to cout will be in LaTeX format from now on
+ cout << e << endl; // prints '4.5 i+\frac@{3@}@{2@} x^@{2@}'
+ cout << sin(x/2) << endl; // prints '\sin(\frac@{1@}@{2@} x)'
+ cout << dflt; // revert to default output format
+ cout << e << endl; // prints '4.5*I+3/2*x^2'
+ // ...
+@end example
+
+If you don't want to affect the format of the stream you're working with,
+you can output to a temporary @code{ostringstream} like this:
+
+@example
+ // ...
+ ostringstream s;
+ s << latex << e; // format of cout remains unchanged
+ cout << s.str() << endl; // prints '4.5 i+\frac@{3@}@{2@} x^@{2@}'
+ // ...
+@end example
+
+@cindex @code{csrc}
+@cindex @code{csrc_float}
+@cindex @code{csrc_double}
+@cindex @code{csrc_cl_N}
+The @code{csrc} (an alias for @code{csrc_double}), @code{csrc_float},
+@code{csrc_double} and @code{csrc_cl_N} manipulators set the output to a
+format that can be directly used in a C or C++ program. The three possible
+formats select the data types used for numbers (@code{csrc_cl_N} uses the
+classes provided by the CLN library):
+
+@example
+ // ...
+ cout << "f = " << csrc_float << e << ";\n";
+ cout << "d = " << csrc_double << e << ";\n";
+ cout << "n = " << csrc_cl_N << e << ";\n";
+ // ...
+@end example
+
+The above example will produce (note the @code{x^2} being converted to
+@code{x*x}):
+
+@example
+f = (3.0/2.0)*(x*x)+std::complex<float>(0.0,4.5000000e+00);
+d = (3.0/2.0)*(x*x)+std::complex<double>(0.0,4.5000000000000000e+00);
+n = cln::cl_RA("3/2")*(x*x)+cln::complex(cln::cl_I("0"),cln::cl_F("4.5_17"));
+@end example
+
+@cindex @code{tree}
+The @code{tree} manipulator allows dumping the internal structure of an
+expression for debugging purposes:
+
+@example
+ // ...
+ cout << tree << e;
+@}
+@end example
+
+produces
+
+@example
+add, hash=0x0, flags=0x3, nops=2
+ power, hash=0x0, flags=0x3, nops=2
+ x (symbol), serial=0, hash=0xc8d5bcdd, flags=0xf
+ 2 (numeric), hash=0x6526b0fa, flags=0xf
+ 3/2 (numeric), hash=0xf9828fbd, flags=0xf
+ -----
+ overall_coeff
+ 4.5L0i (numeric), hash=0xa40a97e0, flags=0xf
+ =====
+@end example
+
+@cindex @code{latex}
+The @code{latex} output format is for LaTeX parsing in mathematical mode.
+It is rather similar to the default format but provides some braces needed
+by LaTeX for delimiting boxes and also converts some 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
+@{
+ symbol x("x", "\\circ");
+ ex e = lgamma(x).series(x==0,3);
+ cout << latex << e << endl;
+@}
+@end example
+
+will print
+
+@example
+ @{(-\ln(\circ))@}+@{(-\gamma_E)@} \circ+@{(\frac@{1@}@{12@} \pi^@{2@})@} \circ^@{2@}+\mathcal@{O@}(\circ^@{3@})
+@end example
+
+@cindex @code{index_dimensions}
+@cindex @code{no_index_dimensions}
+Index dimensions are normally hidden in the output. To make them visible, use
+the @code{index_dimensions} manipulator. The dimensions will be written in
+square brackets behind each index value in the default and LaTeX output
+formats:
+
+@example
+@{
+ symbol x("x"), y("y");
+ varidx mu(symbol("mu"), 4), nu(symbol("nu"), 4);
+ ex e = indexed(x, mu) * indexed(y, nu);
+
+ cout << e << endl;
+ // prints 'x~mu*y~nu'
+ cout << index_dimensions << e << endl;
+ // prints 'x~mu[4]*y~nu[4]'
+ cout << no_index_dimensions << e << endl;
+ // prints 'x~mu*y~nu'
+@}
+@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_a<function>(e))
+ cout << ex_to<function>(e).get_name();
+ else
+ cout << e.bp->class_name();
+ cout << "(";
+ size_t n = e.nops();
+ if (n)
+ for (size_t i=0; i<n; i++) @{
+ my_print(e.op(i));
+ if (i != n-1)
+ cout << ",";
+ @}
+ else
+ cout << e;
+ cout << ")";
+@}
+
+int main()
+@{
+ my_print(pow(3, x) - 2 * sin(y / Pi)); cout << endl;
+ return 0;
+@}
+@end example
+
+This will produce
+
+@example
+add(power(numeric(3),symbol(x)),mul(sin(mul(power(constant(Pi),numeric(-1)),
+symbol(y))),numeric(-2)))
+@end example
+
+If you need an output format that makes it possible to accurately
+reconstruct an expression by feeding the output to a suitable parser or
+object factory, you should consider storing the expression in an
+@code{archive} object and reading the object properties from there.
+See the section on archiving for more information.
+
+
+@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 std;
+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 <fstream>
+using namespace std;
+#include <ginac/ginac.h>
+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, 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
+@code{archive} and @code{archive_node} classes have a couple of member
+functions that let you access the stored properties:
+
+@example
+static void my_print2(const archive_node & n)
+@{
+ string class_name;
+ n.find_string("class", class_name);
+ cout << class_name << "(";
+
+ archive_node::propinfovector p;
+ n.get_properties(p);
+
+ size_t num = p.size();
+ for (size_t i=0; i<num; i++) @{
+ const string &name = p[i].name;
+ if (name == "class")
+ continue;
+ cout << name << "=";
+
+ unsigned count = p[i].count;
+ if (count > 1)
+ cout << "@{";
+
+ for (unsigned j=0; j<count; j++) @{
+ switch (p[i].type) @{
+ case archive_node::PTYPE_BOOL: @{
+ bool x;
+ n.find_bool(name, x, j);
+ cout << (x ? "true" : "false");
+ break;
+ @}
+ case archive_node::PTYPE_UNSIGNED: @{
+ unsigned x;
+ n.find_unsigned(name, x, j);
+ cout << x;
+ break;
+ @}
+ case archive_node::PTYPE_STRING: @{
+ string x;
+ n.find_string(name, x, j);
+ cout << '\"' << x << '\"';
+ break;
+ @}
+ case archive_node::PTYPE_NODE: @{
+ const archive_node &x = n.find_ex_node(name, j);
+ my_print2(x);
+ break;
+ @}
+ @}
+
+ if (j != count-1)
+ cout << ",";
+ @}
+
+ if (count > 1)
+ cout << "@}";
+
+ if (i != num-1)
+ cout << ",";
+ @}
+
+ cout << ")";
+@}
+
+int main()
+@{
+ ex e = pow(2, x) - y;
+ archive ar(e, "e");
+ my_print2(ar.get_top_node(0)); cout << endl;
+ return 0;
+@}
+@end example
+
+This will produce:
+
+@example
+add(rest=@{power(basis=numeric(number="2"),exponent=symbol(name="x")),
+symbol(name="y")@},coeff=@{numeric(number="1"),numeric(number="-1")@},
+overall_coeff=numeric(number="0"))
+@end example
+
+Be warned, however, that the set of properties and their meaning for each
+class may change between GiNaC versions.
+
+
+@node Extending GiNaC, What does not belong into GiNaC, Input/Output, Top
+@c node-name, next, previous, up
+@chapter Extending GiNaC
+
+By reading so far you should have gotten a fairly good understanding of
+GiNaC's design-patterns. From here on you should start reading the
+sources. All we can do now is issue some recommendations how to tackle
+GiNaC's many loose ends in order to fulfill everybody's dreams. If you
+develop some useful extension please don't hesitate to contact the GiNaC
+authors---they will happily incorporate them into future versions.
+
+@menu
+* What does not belong into GiNaC:: What to avoid.
+* Symbolic functions:: Implementing symbolic functions.
+* Structures:: Defining new algebraic classes (the easy way).
+* Adding classes:: Defining new algebraic classes (the hard way).
+@end menu
+
+
+@node What does not belong into GiNaC, Symbolic functions, Extending GiNaC, Extending GiNaC
+@c node-name, next, previous, up
+@section What doesn't belong into GiNaC
+
+@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
+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 capabilities and all
+this on top of GiNaC is possible and is without doubt a nice project for
+the future.
+
+There are many built-in functions in GiNaC that do not know how to
+evaluate themselves numerically to a precision declared at runtime
+(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 foundation classes
+provided by CLN are much better suited.
+
+
+@node Symbolic functions, Structures, What does not belong into GiNaC, Extending GiNaC
+@c node-name, next, previous, up
+@section Symbolic functions
+
+The easiest and most instructive way to start extending GiNaC is probably to
+create your own symbolic functions. These are implemented with the help of
+two preprocessor macros:
+
+@cindex @code{DECLARE_FUNCTION}
+@cindex @code{REGISTER_FUNCTION}
+@example
+DECLARE_FUNCTION_<n>P(<name>)
+REGISTER_FUNCTION(<name>, <options>)
+@end example
+
+The @code{DECLARE_FUNCTION} macro will usually appear in a header file. It
+declares a C++ function with the given @samp{name} that takes exactly @samp{n}
+parameters of type @code{ex} and returns a newly constructed GiNaC
+@code{function} object that represents your function.
+
+The @code{REGISTER_FUNCTION} macro implements the function. It must be passed
+the same @samp{name} as the respective @code{DECLARE_FUNCTION} macro, and a
+set of options that associate the symbolic function with C++ functions you
+provide to implement the various methods such as evaluation, derivative,
+series expansion etc. They also describe additional attributes the function
+might have, such as symmetry and commutation properties, and a name for
+LaTeX output. Multiple options are separated by the member access operator
+@samp{.} and can be given in an arbitrary order.
+
+(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 macros where we can.)
+
+@subsection A minimal example
+
+Here is an example for the implementation of a function with two arguments
+that is not further evaluated:
+
+@example
+DECLARE_FUNCTION_2P(myfcn)
+
+static ex myfcn_eval(const ex & x, const ex & y)
+@{
+ return myfcn(x, y).hold();
+@}
+
+REGISTER_FUNCTION(myfcn, eval_func(myfcn_eval))
+@end example
+
+Any code that has seen the @code{DECLARE_FUNCTION} line can use @code{myfcn()}
+in algebraic expressions:
+
+@example
+@{
+ ...
+ symbol x("x");
+ ex e = 2*myfcn(42, 3*x+1) - x;
+ // this calls myfcn_eval(42, 3*x+1), and inserts its return value into
+ // the actual expression
+ cout << e << endl;
+ // prints '2*myfcn(42,1+3*x)-x'
+ ...
+@}
+@end example
+
+@cindex @code{hold()}
+@cindex evaluation
+The @code{eval_func()} option specifies the C++ function that implements
+the @code{eval()} method, GiNaC's anonymous evaluator. This function takes
+the same number of arguments as the associated symbolic function (two in this
+case) and returns the (possibly transformed or in some way simplified)
+symbolically evaluated function (@xref{Automatic evaluation}, for a description
+of the automatic evaluation process). If no (further) evaluation is to take
+place, the @code{eval_func()} function must return the original function
+with @code{.hold()}, to avoid a potential infinite recursion. If your
+symbolic functions produce a segmentation fault or stack overflow when
+using them in expressions, you are probably missing a @code{.hold()}
+somewhere.
+
+There is not much you can do with the @code{myfcn} function. It merely acts
+as a kind of container for its arguments (which is, however, sometimes
+perfectly sufficient). Let's have a look at the implementation of GiNaC's
+cosine function.
+
+@subsection The cosine function
+
+The GiNaC header file @file{inifcns.h} contains the line
+
+@example
+DECLARE_FUNCTION_1P(cos)
+@end example
+
+which declares to all programs using GiNaC that there is a function @samp{cos}
+that takes one @code{ex} as an argument. This is all they need to know to use
+this function in expressions.
+
+The implementation of the cosine function is in @file{inifcns_trans.cpp}. The
+@code{eval_func()} function looks something like this (actually, it doesn't
+look like this at all, but it should give you an idea what is going on):