1/* 2 3 Part of CLP(R) (Constraint Logic Programming over Reals) 4 5 Author: Leslie De Koninck 6 E-mail: Leslie.DeKoninck@cs.kuleuven.be 7 WWW: http://www.swi-prolog.org 8 http://www.ai.univie.ac.at/cgi-bin/tr-online?number+95-09 9 Copyright (C): 2004, K.U. Leuven and 10 1992-1995, Austrian Research Institute for 11 Artificial Intelligence (OFAI), 12 Vienna, Austria 13 14 This software is part of Leslie De Koninck's master thesis, supervised 15 by Bart Demoen and daily advisor Tom Schrijvers. It is based on CLP(Q,R) 16 by Christian Holzbaur for SICStus Prolog and distributed under the 17 license details below with permission from all mentioned authors. 18 19 This program is free software; you can redistribute it and/or 20 modify it under the terms of the GNU General Public License 21 as published by the Free Software Foundation; either version 2 22 of the License, or (at your option) any later version. 23 24 This program is distributed in the hope that it will be useful, 25 but WITHOUT ANY WARRANTY; without even the implied warranty of 26 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 27 GNU General Public License for more details. 28 29 You should have received a copy of the GNU Lesser General Public 30 License along with this library; if not, write to the Free Software 31 Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA 32 33 As a special exception, if you link this library with other files, 34 compiled with a Free Software compiler, to produce an executable, this 35 library does not by itself cause the resulting executable to be covered 36 by the GNU General Public License. This exception does not however 37 invalidate any other reasons why the executable file might be covered by 38 the GNU General Public License. 39*/ 40 41:- module(itf_r, 42 [ 43 do_checks/8 44 ]). 45:- use_module(library(apply), [maplist/2]). 46:- use_module(bv_r, 47 [ 48 deref/2, 49 detach_bounds_vlv/5, 50 solve/1, 51 solve_ord_x/3 52 ]). 53:- use_module(nf_r, 54 [ 55 nf/2 56 ]). 57:- use_module(store_r, 58 [ 59 add_linear_11/3, 60 indep/2, 61 nf_coeff_of/3 62 ]). 63:- use_module('../clpqr/class', 64 [ 65 class_drop/2 66 ]). 67:- use_module(library(error), [type_error/2]). 68 69do_checks(Y,Ty,St,Li,Or,Cl,No,Later) :- 70 numbers_only(Y), 71 verify_nonzero(No,Y), 72 verify_type(Ty,St,Y,Later,[]), 73 verify_lin(Or,Cl,Li,Y), 74 maplist(call,Later). 75 76numbers_only(Y) :- 77 ( var(Y) 78 -> true 79 ; integer(Y) 80 -> true 81 ; float(Y) 82 -> true 83 ; type_error(real, Y) 84 ). 85 86% verify_nonzero(Nonzero,Y) 87% 88% if Nonzero = nonzero, then verify that Y is not zero 89% (if possible, otherwise set Y to be nonzero) 90 91verify_nonzero(nonzero,Y) :- 92 ( var(Y) 93 -> ( get_attr(Y,clpqr_itf,Att) 94 -> setarg(8,Att,nonzero) 95 ; put_attr(Y,clpqr_itf,t(clpr,n,n,n,n,n,n,nonzero,n,n,n)) 96 ) 97 ; ( Y < -1.0e-10 98 -> true 99 ; Y > 1.0e-10 100 ) 101 ). 102verify_nonzero(n,_). % X is not nonzero 103 104% verify_type(type(Type),strictness(Strict),Y,[OL|OLT],OLT) 105% 106% if possible verifies whether Y satisfies the type and strictness of X 107% if not possible to verify, then returns the constraints that follow from 108% the type and strictness 109 110verify_type(type(Type),strictness(Strict),Y) --> 111 verify_type2(Y,Type,Strict). 112verify_type(n,n,_) --> []. 113 114verify_type2(Y,TypeX,StrictX) --> 115 {var(Y)}, 116 !, 117 verify_type_var(TypeX,Y,StrictX). 118verify_type2(Y,TypeX,StrictX) --> 119 {verify_type_nonvar(TypeX,Y,StrictX)}. 120 121% verify_type_nonvar(Type,Nonvar,Strictness) 122% 123% verifies whether the type and strictness are satisfied with the Nonvar 124 125verify_type_nonvar(t_none,_,_). 126verify_type_nonvar(t_l(L),Value,S) :- ilb(S,L,Value). 127verify_type_nonvar(t_u(U),Value,S) :- iub(S,U,Value). 128verify_type_nonvar(t_lu(L,U),Value,S) :- 129 ilb(S,L,Value), 130 iub(S,U,Value). 131verify_type_nonvar(t_L(L),Value,S) :- ilb(S,L,Value). 132verify_type_nonvar(t_U(U),Value,S) :- iub(S,U,Value). 133verify_type_nonvar(t_Lu(L,U),Value,S) :- 134 ilb(S,L,Value), 135 iub(S,U,Value). 136verify_type_nonvar(t_lU(L,U),Value,S) :- 137 ilb(S,L,Value), 138 iub(S,U,Value). 139 140% ilb(Strict,Lower,Value) & iub(Strict,Upper,Value) 141% 142% check whether Value is satisfiable with the given lower/upper bound and 143% strictness. 144% strictness is encoded as follows: 145% 2 = strict lower bound 146% 1 = strict upper bound 147% 3 = strict lower and upper bound 148% 0 = no strict bounds 149 150ilb(S,L,V) :- 151 S /\ 2 =:= 0, 152 !, 153 L - V < 1.0e-10. % non-strict 154ilb(_,L,V) :- L - V < -1.0e-10. % strict 155 156iub(S,U,V) :- 157 S /\ 1 =:= 0, 158 !, 159 V - U < 1.0e-10. % non-strict 160iub(_,U,V) :- V - U < -1.0e-10. % strict 161 162% 163% Running some goals after X=Y simplifies the coding. It should be possible 164% to run the goals here and taking care not to put_atts/2 on X ... 165% 166 167% verify_type_var(Type,Var,Strictness,[OutList|OutListTail],OutListTail) 168% 169% returns the inequalities following from a type and strictness satisfaction 170% test with Var 171 172verify_type_var(t_none,_,_) --> []. 173verify_type_var(t_l(L),Y,S) --> llb(S,L,Y). 174verify_type_var(t_u(U),Y,S) --> lub(S,U,Y). 175verify_type_var(t_lu(L,U),Y,S) --> 176 llb(S,L,Y), 177 lub(S,U,Y). 178verify_type_var(t_L(L),Y,S) --> llb(S,L,Y). 179verify_type_var(t_U(U),Y,S) --> lub(S,U,Y). 180verify_type_var(t_Lu(L,U),Y,S) --> 181 llb(S,L,Y), 182 lub(S,U,Y). 183verify_type_var(t_lU(L,U),Y,S) --> 184 llb(S,L,Y), 185 lub(S,U,Y). 186 187% llb(Strict,Lower,Value,[OL|OLT],OLT) and lub(Strict,Upper,Value,[OL|OLT],OLT) 188% 189% returns the inequalities following from the lower and upper bounds and the 190% strictness see also lb and ub 191llb(S,L,V) --> 192 {S /\ 2 =:= 0}, 193 !, 194 [clpr:{L =< V}]. 195llb(_,L,V) --> [clpr:{L < V}]. 196 197lub(S,U,V) --> 198 {S /\ 1 =:= 0}, 199 !, 200 [clpr:{V =< U}]. 201lub(_,U,V) --> [clpr:{V < U}]. 202 203% 204% We used to drop X from the class/basis to avoid trouble with subsequent 205% put_atts/2 on X. Now we could let these dead but harmless updates happen. 206% In R however, exported bindings might conflict, e.g. 0 \== 0.0 207% 208% If X is indep and we do _not_ solve for it, we are in deep shit 209% because the ordering is violated. 210% 211verify_lin(order(OrdX),class(Class),lin(LinX),Y) :- 212 !, 213 ( indep(LinX,OrdX) 214 -> detach_bounds_vlv(OrdX,LinX,Class,Y,NewLinX), 215 % if there were bounds, they are requeued already 216 class_drop(Class,Y), 217 nf(-Y,NfY), 218 deref(NfY,LinY), 219 add_linear_11(NewLinX,LinY,Lind), 220 ( nf_coeff_of(Lind,OrdX,_) 221 -> % X is element of Lind 222 solve_ord_x(Lind,OrdX,Class) 223 ; solve(Lind) % X is gone, can safely solve Lind 224 ) 225 ; class_drop(Class,Y), 226 nf(-Y,NfY), 227 deref(NfY,LinY), 228 add_linear_11(LinX,LinY,Lind), 229 solve(Lind) 230 ). 231verify_lin(_,_,_,_)