This is a tutorial that documents GiNaC @value{VERSION}, an open
framework for symbolic computation within the C++ programming language.
-Copyright (C) 1999-2015 Johannes Gutenberg University Mainz, Germany
+Copyright (C) 1999-2016 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{} 1999-2015 Johannes Gutenberg University Mainz, Germany
+Copyright @copyright{} 1999-2016 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{} 1999-2015 Johannes Gutenberg
+language is Copyright @copyright{} 1999-2016 Johannes Gutenberg
University Mainz, Germany.
This program is free software; you can redistribute it and/or
@uref{http://pkg-config.freedesktop.org}.
Last but not least, the CLN library
is used extensively and needs to be installed on your system.
-Please get it from @uref{ftp://ftpthep.physik.uni-mainz.de/pub/gnu/}
-(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.
+Please get it from @uref{http://www.ginac.de/CLN/} (it is licensed under
+the 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.
@node Configuration, Building GiNaC, Prerequisites, Installation
of the non-commutative classes. The drawback is that to work with other than
the built-in algebras you have to implement new classes yourself. Both
symbols and user-defined functions can be specified as being non-commutative.
+For symbols, this is done by subclassing class symbol; for functions,
+by explicitly setting the return type (@pxref{Symbolic functions}).
@cindex @code{return_type()}
@cindex @code{return_type_tinfo()}
Note that the call @code{clifford_unit(mu, minkmetric())} creates
something very close to @code{dirac_gamma(mu)}, although
@code{dirac_gamma} have more efficient simplification mechanism.
-@cindex @code{clifford::get_metric()}
+@cindex @code{get_metric()}
The method @code{clifford::get_metric()} returns a metric defining this
Clifford number.
@item @code{log(x)}
@tab natural logarithm
@cindex @code{log()}
+@item @code{eta(x,y)}
+@tab Eta function: @code{eta(x,y) = log(x*y) - log(x) - log(y)}
+@cindex @code{eta()}
@item @code{Li2(x)}
@tab dilogarithm
@cindex @code{Li2()}
table["x"] = x+log(y)+1;
parser reader(table);
ex e = reader("5*x^3 - x^2");
- // e = 5*(x+log(y)+1)^3 + (x+log(y)+1)^2
+ // e = 5*(x+log(y)+1)^3 - (x+log(y)+1)^2
@}
@end example
parser reader;
ex e = reader("2*x+sin(y)");
symtab table = reader.get_syms();
- symbol x = reader["x"];
- symbol y = reader["y"];
+ symbol x = ex_to<symbol>(table["x"]);
+ symbol y = ex_to<symbol>(table["y"]);
@}
@end example
@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.
+directory. You can also export additional compiler flags via the $CXXFLAGS
+variable:
+
+@example
+setenv("CXXFLAGS", "-O3 -fomit-frame-pointer -ffast-math", 1);
+compile_ex(...);
+@end example
@subsection Archiving
@cindex @code{archive} (class)
case the function has more than one parameter, and its main application
is for correct handling of the chain rule.
+Derivatives of some functions, for example @code{abs()} and
+@code{Order()}, could not be evaluated through the chain rule. In such
+cases the full derivative may be specified as shown for @code{Order()}:
+
+@example
+static ex Order_expl_derivative(const ex & arg, const symbol & s)
+@{
+ return Order(arg.diff(s));
+@}
+@end example
+
+That is, we need to supply a procedure, which returns the expression of
+derivative with respect to the variable @code{s} for the argument
+@code{arg}. This procedure need to be registered with the function
+through the option @code{expl_derivative_func} (see the next
+Subsection). In contrast, a partial derivative, e.g. as was defined for
+@code{cos()} above, needs to be registered through the option
+@code{derivative_func}.
+
An implementation of the series expansion is not needed for @code{cos()} as
it doesn't have any poles and GiNaC can do Taylor expansion by itself (as
long as it knows what the derivative of @code{cos()} is). @code{tan()}, on
eval_func(<C++ function>)
evalf_func(<C++ function>)
derivative_func(<C++ function>)
+expl_derivative_func(<C++ function>)
series_func(<C++ function>)
conjugate_func(<C++ function>)
@end example
These specify the C++ functions that implement symbolic evaluation,
-numeric evaluation, partial derivatives, and series expansion, respectively.
-They correspond to the GiNaC methods @code{eval()}, @code{evalf()},
-@code{diff()} and @code{series()}.
+numeric evaluation, partial derivatives, explicit derivative, and series
+expansion, respectively. They correspond to the GiNaC methods
+@code{eval()}, @code{evalf()}, @code{diff()} and @code{series()}.
The @code{eval_func()} function needs to use @code{.hold()} if no further
automatic evaluation is desired or possible.
git://www.ginac.de / ginac.git / blobdiff