This is a tutorial that documents GiNaC @value{VERSION}, an open
framework for symbolic computation within the C++ programming language.
-Copyright (C) 1999-2016 Johannes Gutenberg University Mainz, Germany
+Copyright (C) 1999-2018 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{} 1999-2016 Johannes Gutenberg University Mainz, Germany
+Copyright @copyright{} 1999-2018 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
@section License
The GiNaC framework for symbolic computation within the C++ programming
-language is Copyright @copyright{} 1999-2016 Johannes Gutenberg
+language is Copyright @copyright{} 1999-2018 Johannes Gutenberg
University Mainz, Germany.
This program is free software; you can redistribute it and/or
as "@code{\Box}" in LaTeX code (@xref{Input/output}, for more
information about the different output formats of expressions in GiNaC).
GiNaC automatically creates proper LaTeX code for symbols having names of
-greek letters (@samp{alpha}, @samp{mu}, etc.).
+greek letters (@samp{alpha}, @samp{mu}, etc.). You can retrieve the name
+and the LaTeX name of a symbol using the respective methods:
+@cindex @code{get_name()}
+@cindex @code{get_TeX_name()}
+@example
+symbol::get_name() const;
+symbol::get_TeX_name() const;
+@end example
@cindex @code{subs()}
Symbols in GiNaC can't be assigned values. If you need to store results of
ex matrix::determinant(unsigned algo=determinant_algo::automatic) const;
ex matrix::trace() const;
ex matrix::charpoly(const ex & lambda) const;
-unsigned matrix::rank() const;
+unsigned matrix::rank(unsigned algo=solve_algo::automatic) const;
@end example
-The @samp{algo} argument of @code{determinant()} allows to select
-between different algorithms for calculating the determinant. The
-asymptotic speed (as parametrized by the matrix size) can greatly differ
-between those algorithms, depending on the nature of the matrix'
-entries. The possible values are defined in the @file{flags.h} header
-file. By default, GiNaC uses a heuristic to automatically select an
-algorithm that is likely (but not guaranteed) to give the result most
-quickly.
+The optional @samp{algo} argument of @code{determinant()} and @code{rank()}
+functions allows to select between different algorithms for calculating the
+determinant and rank respectively. The asymptotic speed (as parametrized
+by the matrix size) can greatly differ between those algorithms, depending
+on the nature of the matrix' entries. The possible values are defined in
+the @file{flags.h} header file. By default, GiNaC uses a heuristic to
+automatically select an algorithm that is likely (but not guaranteed)
+to give the result most quickly.
-@cindex @code{inverse()} (matrix)
@cindex @code{solve()}
-Matrices may also be inverted using the @code{ex matrix::inverse()}
-method and linear systems may be solved with:
+Linear systems can be solved with:
@example
matrix matrix::solve(const matrix & vars, const matrix & rhs,
contain some of the indeterminates from @code{vars}. If the system is
overdetermined, an exception is thrown.
+@cindex @code{inverse()} (matrix)
+To invert a matrix, use the method:
+
+@example
+matrix matrix::inverse(unsigned algo=solve_algo::automatic) const;
+@end example
+
+The @samp{algo} argument is optional. If given, it must be one of
+@code{solve_algo} defined in @file{flags.h}.
@node Indexed objects, Non-commutative objects, Matrices, Basic concepts
@c node-name, next, previous, up
@code{dirac_gamma} have more efficient simplification mechanism.
@cindex @code{get_metric()}
Also, the object created by @code{clifford_unit(mu, minkmetric())} is
-not aware about the symmetry of its metric, see the start of the pevious
+not aware about the symmetry of its metric, see the start of the previous
paragraph. A more accurate analog of 'dirac_gamma(mu)' should be
specifies as follows:
@example
ex clifford_prime(const ex & e)
- inline ex clifford_star(const ex & e) @{ return e.conjugate(); @}
- inline ex clifford_bar(const ex & e) @{ return clifford_prime(e.conjugate()); @}
+ inline ex clifford_star(const ex & e)
+ inline ex clifford_bar(const ex & e)
@end example
The automorphism of a Clifford algebra @code{clifford_prime()} simply
changes signs of all Clifford units in the expression. The reversion
-of a Clifford algebra @code{clifford_star()} coincides with the
-@code{conjugate()} method and effectively reverses the order of Clifford
+of a Clifford algebra @code{clifford_star()} reverses the order of Clifford
units in any product. Finally the main anti-automorphism
of a Clifford algebra @code{clifford_bar()} is the composition of the
previous two, i.e. it makes the reversion and changes signs of all Clifford units
@cindex @code{ldegree()}
@cindex @code{coeff()}
-The degree and low degree of a polynomial can be obtained using the two
-methods
+The degree and low degree of a polynomial in expanded form 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). By definition, the
-degree of zero is zero. To extract a coefficient with a certain power from
-an expanded polynomial you use
+These functions even work on rational functions, returning the asymptotic
+degree. By definition, the degree of zero is zero. To extract a coefficient
+with a certain power from an expanded polynomial you use
@example
ex ex::coeff(const ex & s, int n);
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.
+If you need both numerator and denominator, call @code{numer_denom()}: it
+is faster than using @code{numer()} and @code{denom()} separately. And even
+more important: a separate evaluation of @code{numer()} and @code{denom()}
+may result in a spurious sign, e.g. for $x/(x^2-1)$ @code{numer()} may
+return $x$ and @code{denom()} $1-x^2$.
@subsection Converting to a polynomial or rational expression
@example
ex ex::to_polynomial(exmap & m);
-ex ex::to_polynomial(lst & l);
@end example
or
@example
ex ex::to_rational(exmap & m);
-ex ex::to_rational(lst & l);
@end example
-on the expression to be converted. The supplied @code{exmap} or @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.
+on the expression to be converted. The supplied @code{exmap} 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 between @code{.to_polynomial()} and @code{.to_rational()}
is probably best illustrated with an example:
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;
+ exmap mp;
+ ex p = a.to_polynomial(mp);
+ cout << " = " << p << "\n with " << mp << 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;
+ exmap mr;
+ ex r = a.to_rational(mr);
+ cout << " = " << r << "\n with " << mr << endl;
// = -1/3*symbol4^(-1)*y+2*symbol4^(-1)*x
// with @{symbol4==sin(x)@}
@}
the maximal expansion. For example, for the exponent GiNaC firstly expands
the argument and then the function. For the logarithm and absolute value,
GiNaC uses the opposite order: firstly expands the function and then its
-argument. Of course, a user can fine-tune this behaviour by sequential
+argument. Of course, a user can fine-tune this behavior by sequential
calls of several @code{expand()} methods with desired flags.
@node Multiple polylogarithms, Complex expressions, Built-in functions, Methods and functions
@cindex ginac-excompiler
@code{compile_ex} uses the shell script @code{ginac-excompiler} to start the C
compiler and produce the object files. This shell script comes with GiNaC and
-will be installed together with GiNaC in the configured @code{$PREFIX/bin}
-directory. You can also export additional compiler flags via the $CXXFLAGS
-variable:
+will be installed together with GiNaC in the configured @code{$LIBEXECDIR}
+(typically @code{$PREFIX/libexec} or @code{$PREFIX/lib/ginac}). You can also
+export additional compiler flags via the @env{$CXXFLAGS} variable:
@example
setenv("CXXFLAGS", "-O3 -fomit-frame-pointer -ffast-math", 1);
git://www.ginac.de / ginac.git / blobdiff