3 * Collection of all flags used through the GiNaC framework. */
6 * GiNaC Copyright (C) 1999-2003 Johannes Gutenberg University Mainz, Germany
8 * This program is free software; you can redistribute it and/or modify
9 * it under the terms of the GNU General Public License as published by
10 * the Free Software Foundation; either version 2 of the License, or
11 * (at your option) any later version.
13 * This program is distributed in the hope that it will be useful,
14 * but WITHOUT ANY WARRANTY; without even the implied warranty of
15 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
16 * GNU General Public License for more details.
18 * You should have received a copy of the GNU General Public License
19 * along with this program; if not, write to the Free Software
20 * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
23 #ifndef __GINAC_FLAGS_H__
24 #define __GINAC_FLAGS_H__
28 /** Flags to control the behavior of expand(). */
29 class expand_options {
32 expand_trigonometric = 0x0001,
33 expand_indexed = 0x0002,
34 expand_function_args = 0x0004
38 /** Flags to control the behavior of subs(). */
42 subs_no_pattern = 0x0001,
43 subs_algebraic = 0x0002
47 /** Flags to control series expansion. */
48 class series_options {
51 /** Suppress branch cuts in series expansion. Branch cuts manifest
52 * themselves as step functions, if this option is not passed. If
53 * it is passed and expansion at a point on a cut is performed, then
54 * the analytic continuation of the function is expanded. */
55 suppress_branchcut = 0x0001
59 /** Switch to control algorithm for determinant computation. */
60 class determinant_algo {
63 /** Let the system choose. A heuristics is applied for automatic
64 * determination of a suitable algorithm. */
66 /** Gauss elimination. If \f$m_{i,j}^{(0)}\f$ are the entries of the
67 * original matrix, then the matrix is transformed into triangular
68 * form by applying the rules
70 * m_{i,j}^{(k+1)} = m_{i,j}^{(k)} - m_{i,k}^{(k)} m_{k,j}^{(k)} / m_{k,k}^{(k)}
72 * The determinant is then just the product of diagonal elements.
73 * Choose this algorithm only for purely numerical matrices. */
75 /** Division-free elimination. This is a modification of Gauss
76 * elimination where the division by the pivot element is not
77 * carried out. If \f$m_{i,j}^{(0)}\f$ are the entries of the
78 * original matrix, then the matrix is transformed into triangular
79 * form by applying the rules
81 * m_{i,j}^{(k+1)} = m_{i,j}^{(k)} m_{k,k}^{(k)} - m_{i,k}^{(k)} m_{k,j}^{(k)}
83 * The determinant can later be computed by inspecting the diagonal
84 * elements only. This algorithm is only there for the purpose of
85 * cross-checks. It is never fast. */
87 /** Laplace elimination. This is plain recursive elimination along
88 * minors although multiple minors are avoided by the algorithm.
89 * Although the algorithm is exponential in complexity it is
90 * frequently the fastest one when the matrix is populated by
91 * complicated symbolic expressions. */
93 /** Bareiss fraction-free elimination. This is a modification of
94 * Gauss elimination where the division by the pivot element is
95 * <EM>delayed</EM> until it can be carried out without computing
96 * GCDs. If \f$m_{i,j}^{(0)}\f$ are the entries of the original
97 * matrix, then the matrix is transformed into triangular form by
100 * m_{i,j}^{(k+1)} = (m_{i,j}^{(k)} m_{k,k}^{(k)} - m_{i,k}^{(k)} m_{k,j}^{(k)}) / m_{k-1,k-1}^{(k-1)}
102 * (We have set \f$m_{-1,-1}^{(-1)}=1\f$ in order to avoid a case
103 * distinction in above formula.) It can be shown that nothing more
104 * than polynomial long division is needed for carrying out the
105 * division. The determinant can then be read of from the lower
106 * right entry. This algorithm is rarely fast for computing
112 /** Switch to control algorithm for linear system solving. */
116 /** Let the system choose. A heuristics is applied for automatic
117 * determination of a suitable algorithm. */
119 /** Gauss elimination. If \f$m_{i,j}^{(0)}\f$ are the entries of the
120 * original matrix, then the matrix is transformed into triangular
121 * form by applying the rules
123 * m_{i,j}^{(k+1)} = m_{i,j}^{(k)} - m_{i,k}^{(k)} m_{k,j}^{(k)} / m_{k,k}^{(k)}
125 * This algorithm is well-suited for numerical matrices but generally
126 * suffers from the expensive division (and computation of GCDs) at
129 /** Division-free elimination. This is a modification of Gauss
130 * elimination where the division by the pivot element is not
131 * carried out. If \f$m_{i,j}^{(0)}\f$ are the entries of the
132 * original matrix, then the matrix is transformed into triangular
133 * form by applying the rules
135 * m_{i,j}^{(k+1)} = m_{i,j}^{(k)} m_{k,k}^{(k)} - m_{i,k}^{(k)} m_{k,j}^{(k)}
137 * This algorithm is only there for the purpose of cross-checks.
138 * It suffers from exponential intermediate expression swell. Use it
139 * only for small systems. */
141 /** Bareiss fraction-free elimination. This is a modification of
142 * Gauss elimination where the division by the pivot element is
143 * <EM>delayed</EM> until it can be carried out without computing
144 * GCDs. If \f$m_{i,j}^{(0)}\f$ are the entries of the original
145 * matrix, then the matrix is transformed into triangular form by
148 * m_{i,j}^{(k+1)} = (m_{i,j}^{(k)} m_{k,k}^{(k)} - m_{i,k}^{(k)} m_{k,j}^{(k)}) / m_{k-1,k-1}^{(k-1)}
150 * (We have set \f$m_{-1,-1}^{(-1)}=1\f$ in order to avoid a case
151 * distinction in above formula.) It can be shown that nothing more
152 * than polynomial long division is needed for carrying out the
153 * division. This is generally the fastest algorithm for solving
154 * linear systems. In contrast to division-free elimination it only
155 * has a linear expression swell. For two-dimensional systems, the
156 * two algorithms are equivalent, however. */
161 /** Flags to store information about the state of an object.
162 * @see basic::flags */
166 dynallocated = 0x0001, ///< Heap-allocated (i.e. created by new if we want to be clever and bypass the stack, @see ex::construct_from_basic() )
167 evaluated = 0x0002, ///< .eval() has already done its job
168 expanded = 0x0004, ///< .expand(0) has already done its job (other expand() options ignore this flag)
169 hash_calculated = 0x0008 ///< .calchash() has already done its job
173 /** Possible attributes an object can have. */
177 // answered by class numeric
194 // answered by class relation
199 relation_less_or_equal,
201 relation_greater_or_equal,
203 // answered by class symbol
206 // answered by class lst
209 // answered by class exprseq
212 // answered by classes numeric, symbol, add, mul, power
217 crational_polynomial,
221 // answered by class indexed
222 indexed, // class can carry indices
223 has_indices, // object has at least one index
225 // answered by class idx
235 noncommutative_composite
239 /** Strategies how to clean up the function remember cache.
240 * @see remember_table */
241 class remember_strategies {
244 delete_never, ///< Let table grow undefinitely
245 delete_lru, ///< Least recently used
246 delete_lfu, ///< Least frequently used
247 delete_cyclic ///< First (oldest) one in list
253 #endif // ndef __GINAC_FLAGS_H__