| 1 | /**CFile*********************************************************************** | 
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| 2 |  | 
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| 3 |   FileName    [cuddRead.c] | 
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| 4 |  | 
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| 5 |   PackageName [cudd] | 
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| 6 |  | 
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| 7 |   Synopsis    [Functions to read in a matrix] | 
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| 8 |  | 
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| 9 |   Description [External procedures included in this module: | 
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| 10 |                 <ul> | 
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| 11 |                 <li> Cudd_addRead() | 
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| 12 |                 <li> Cudd_bddRead() | 
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| 13 |                 </ul>] | 
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| 14 |  | 
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| 15 |   SeeAlso     [cudd_addHarwell.c] | 
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| 16 |  | 
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| 17 |   Author      [Fabio Somenzi] | 
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| 18 |  | 
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| 19 |   Copyright   [Copyright (c) 1995-2004, Regents of the University of Colorado | 
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| 20 |  | 
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| 21 |   All rights reserved. | 
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| 22 |  | 
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| 23 |   Redistribution and use in source and binary forms, with or without | 
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| 24 |   modification, are permitted provided that the following conditions | 
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| 25 |   are met: | 
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| 26 |  | 
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| 27 |   Redistributions of source code must retain the above copyright | 
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| 28 |   notice, this list of conditions and the following disclaimer. | 
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| 29 |  | 
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| 30 |   Redistributions in binary form must reproduce the above copyright | 
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| 31 |   notice, this list of conditions and the following disclaimer in the | 
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| 32 |   documentation and/or other materials provided with the distribution. | 
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| 33 |  | 
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| 34 |   Neither the name of the University of Colorado nor the names of its | 
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| 35 |   contributors may be used to endorse or promote products derived from | 
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| 36 |   this software without specific prior written permission. | 
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| 37 |  | 
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| 38 |   THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS | 
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| 39 |   "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT | 
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| 40 |   LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS | 
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| 41 |   FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE | 
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| 42 |   COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, | 
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| 43 |   INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, | 
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| 44 |   BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; | 
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| 45 |   LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER | 
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| 46 |   CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT | 
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| 47 |   LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN | 
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| 48 |   ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE | 
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| 49 |   POSSIBILITY OF SUCH DAMAGE.] | 
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| 50 |  | 
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| 51 | ******************************************************************************/ | 
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| 52 |  | 
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| 53 | #include "util.h" | 
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| 54 | #include "cuddInt.h" | 
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| 55 |  | 
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| 56 |  | 
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| 57 | /*---------------------------------------------------------------------------*/ | 
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| 58 | /* Constant declarations                                                     */ | 
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| 59 | /*---------------------------------------------------------------------------*/ | 
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| 60 |  | 
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| 61 |  | 
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| 62 | /*---------------------------------------------------------------------------*/ | 
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| 63 | /* Stucture declarations                                                     */ | 
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| 64 | /*---------------------------------------------------------------------------*/ | 
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| 65 |  | 
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| 66 |  | 
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| 67 | /*---------------------------------------------------------------------------*/ | 
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| 68 | /* Type declarations                                                         */ | 
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| 69 | /*---------------------------------------------------------------------------*/ | 
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| 70 |  | 
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| 71 |  | 
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| 72 | /*---------------------------------------------------------------------------*/ | 
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| 73 | /* Variable declarations                                                     */ | 
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| 74 | /*---------------------------------------------------------------------------*/ | 
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| 75 |  | 
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| 76 | #ifndef lint | 
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| 77 | static char rcsid[] DD_UNUSED = "$Id: cuddRead.c,v 1.6 2004/08/13 18:04:50 fabio Exp $"; | 
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| 78 | #endif | 
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| 79 |  | 
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| 80 | /*---------------------------------------------------------------------------*/ | 
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| 81 | /* Macro declarations                                                        */ | 
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| 82 | /*---------------------------------------------------------------------------*/ | 
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| 83 |  | 
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| 84 |  | 
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| 85 | /**AutomaticStart*************************************************************/ | 
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| 86 |  | 
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| 87 | /*---------------------------------------------------------------------------*/ | 
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| 88 | /* Static function prototypes                                                */ | 
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| 89 | /*---------------------------------------------------------------------------*/ | 
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| 90 |  | 
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| 91 |  | 
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| 92 | /**AutomaticEnd***************************************************************/ | 
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| 93 |  | 
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| 94 |  | 
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| 95 | /*---------------------------------------------------------------------------*/ | 
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| 96 | /* Definition of exported functions                                          */ | 
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| 97 | /*---------------------------------------------------------------------------*/ | 
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| 98 |  | 
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| 99 |  | 
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| 100 | /**Function******************************************************************** | 
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| 101 |  | 
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| 102 |   Synopsis    [Reads in a sparse matrix.] | 
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| 103 |  | 
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| 104 |   Description [Reads in a sparse matrix specified in a simple format. | 
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| 105 |   The first line of the input contains the numbers of rows and columns. | 
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| 106 |   The remaining lines contain the elements of the matrix, one per line. | 
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| 107 |   Given a background value | 
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| 108 |   (specified by the background field of the manager), only the values | 
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| 109 |   different from it are explicitly listed.  Each foreground element is | 
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| 110 |   described by two integers, i.e., the row and column number, and a | 
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| 111 |   real number, i.e., the value.<p> | 
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| 112 |   Cudd_addRead produces an ADD that depends on two sets of variables: x | 
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| 113 |   and y.  The x variables (x\[0\] ... x\[nx-1\]) encode the row index and | 
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| 114 |   the y variables (y\[0\] ... y\[ny-1\]) encode the column index. | 
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| 115 |   x\[0\] and y\[0\] are the most significant bits in the indices. | 
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| 116 |   The variables may already exist or may be created by the function. | 
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| 117 |   The index of x\[i\] is bx+i*sx, and the index of y\[i\] is by+i*sy.<p> | 
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| 118 |   On input, nx and ny hold the numbers | 
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| 119 |   of row and column variables already in existence. On output, they | 
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| 120 |   hold the numbers of row and column variables actually used by the | 
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| 121 |   matrix. When Cudd_addRead creates the variable arrays, | 
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| 122 |   the index of x\[i\] is bx+i*sx, and the index of y\[i\] is by+i*sy. | 
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| 123 |   When some variables already exist Cudd_addRead expects the indices | 
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| 124 |   of the existing x variables to be bx+i*sx, and the indices of the | 
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| 125 |   existing y variables to be by+i*sy.<p> | 
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| 126 |   m and n are set to the numbers of rows and columns of the | 
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| 127 |   matrix.  Their values on input are immaterial. | 
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| 128 |   The ADD for the | 
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| 129 |   sparse matrix is returned in E, and its reference count is > 0. | 
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| 130 |   Cudd_addRead returns 1 in case of success; 0 otherwise.] | 
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| 131 |  | 
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| 132 |   SideEffects [nx and ny are set to the numbers of row and column | 
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| 133 |   variables. m and n are set to the numbers of rows and columns. x and y | 
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| 134 |   are possibly extended to represent the array of row and column | 
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| 135 |   variables. Similarly for xn and yn_, which hold on return from | 
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| 136 |   Cudd_addRead the complements of the row and column variables.] | 
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| 137 |  | 
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| 138 |   SeeAlso     [Cudd_addHarwell Cudd_bddRead] | 
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| 139 |  | 
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| 140 | ******************************************************************************/ | 
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| 141 | int | 
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| 142 | Cudd_addRead( | 
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| 143 |   FILE * fp /* input file pointer */, | 
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| 144 |   DdManager * dd /* DD manager */, | 
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| 145 |   DdNode ** E /* characteristic function of the graph */, | 
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| 146 |   DdNode *** x /* array of row variables */, | 
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| 147 |   DdNode *** y /* array of column variables */, | 
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| 148 |   DdNode *** xn /* array of complemented row variables */, | 
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| 149 |   DdNode *** yn_ /* array of complemented column variables */, | 
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| 150 |   int * nx /* number or row variables */, | 
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| 151 |   int * ny /* number or column variables */, | 
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| 152 |   int * m /* number of rows */, | 
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| 153 |   int * n /* number of columns */, | 
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| 154 |   int  bx /* first index of row variables */, | 
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| 155 |   int  sx /* step of row variables */, | 
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| 156 |   int  by /* first index of column variables */, | 
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| 157 |   int  sy /* step of column variables */) | 
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| 158 | { | 
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| 159 |     DdNode *one, *zero; | 
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| 160 |     DdNode *w, *neW; | 
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| 161 |     DdNode *minterm1; | 
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| 162 |     int u, v, err, i, nv; | 
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| 163 |     int lnx, lny; | 
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| 164 |     CUDD_VALUE_TYPE val; | 
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| 165 |     DdNode **lx, **ly, **lxn, **lyn; | 
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| 166 |  | 
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| 167 |     one = DD_ONE(dd); | 
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| 168 |     zero = DD_ZERO(dd); | 
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| 169 |  | 
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| 170 |     err = fscanf(fp, "%d %d", &u, &v); | 
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| 171 |     if (err == EOF) { | 
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| 172 |         return(0); | 
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| 173 |     } else if (err != 2) { | 
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| 174 |         return(0); | 
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| 175 |     } | 
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| 176 |  | 
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| 177 |     *m = u; | 
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| 178 |     /* Compute the number of x variables. */ | 
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| 179 |     lx = *x; lxn = *xn; | 
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| 180 |     u--;        /* row and column numbers start from 0 */ | 
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| 181 |     for (lnx=0; u > 0; lnx++) { | 
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| 182 |         u >>= 1; | 
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| 183 |     } | 
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| 184 |     /* Here we rely on the fact that REALLOC of a null pointer is | 
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| 185 |     ** translates to an ALLOC. | 
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| 186 |     */ | 
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| 187 |     if (lnx > *nx) { | 
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| 188 |         *x = lx = REALLOC(DdNode *, *x, lnx); | 
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| 189 |         if (lx == NULL) { | 
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| 190 |             dd->errorCode = CUDD_MEMORY_OUT; | 
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| 191 |             return(0); | 
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| 192 |         } | 
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| 193 |         *xn = lxn =  REALLOC(DdNode *, *xn, lnx); | 
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| 194 |         if (lxn == NULL) { | 
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| 195 |             dd->errorCode = CUDD_MEMORY_OUT; | 
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| 196 |             return(0); | 
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| 197 |         } | 
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| 198 |     } | 
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| 199 |  | 
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| 200 |     *n = v; | 
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| 201 |     /* Compute the number of y variables. */ | 
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| 202 |     ly = *y; lyn = *yn_; | 
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| 203 |     v--;        /* row and column numbers start from 0 */ | 
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| 204 |     for (lny=0; v > 0; lny++) { | 
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| 205 |         v >>= 1; | 
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| 206 |     } | 
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| 207 |     /* Here we rely on the fact that REALLOC of a null pointer is | 
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| 208 |     ** translates to an ALLOC. | 
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| 209 |     */ | 
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| 210 |     if (lny > *ny) { | 
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| 211 |         *y = ly = REALLOC(DdNode *, *y, lny); | 
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| 212 |         if (ly == NULL) { | 
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| 213 |             dd->errorCode = CUDD_MEMORY_OUT; | 
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| 214 |             return(0); | 
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| 215 |         } | 
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| 216 |         *yn_ = lyn =  REALLOC(DdNode *, *yn_, lny); | 
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| 217 |         if (lyn == NULL) { | 
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| 218 |             dd->errorCode = CUDD_MEMORY_OUT; | 
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| 219 |             return(0); | 
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| 220 |         } | 
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| 221 |     } | 
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| 222 |  | 
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| 223 |     /* Create all new variables. */ | 
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| 224 |     for (i = *nx, nv = bx + (*nx) * sx; i < lnx; i++, nv += sx) { | 
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| 225 |         do { | 
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| 226 |             dd->reordered = 0; | 
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| 227 |             lx[i] = cuddUniqueInter(dd, nv, one, zero); | 
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| 228 |         } while (dd->reordered == 1); | 
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| 229 |         if (lx[i] == NULL) return(0); | 
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| 230 |         cuddRef(lx[i]); | 
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| 231 |         do { | 
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| 232 |             dd->reordered = 0; | 
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| 233 |             lxn[i] = cuddUniqueInter(dd, nv, zero, one); | 
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| 234 |         } while (dd->reordered == 1); | 
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| 235 |         if (lxn[i] == NULL) return(0); | 
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| 236 |         cuddRef(lxn[i]); | 
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| 237 |     } | 
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| 238 |     for (i = *ny, nv = by + (*ny) * sy; i < lny; i++, nv += sy) { | 
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| 239 |         do { | 
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| 240 |             dd->reordered = 0; | 
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| 241 |             ly[i] = cuddUniqueInter(dd, nv, one, zero); | 
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| 242 |         } while (dd->reordered == 1); | 
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| 243 |         if (ly[i] == NULL) return(0); | 
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| 244 |         cuddRef(ly[i]); | 
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| 245 |         do { | 
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| 246 |             dd->reordered = 0; | 
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| 247 |             lyn[i] = cuddUniqueInter(dd, nv, zero, one); | 
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| 248 |         } while (dd->reordered == 1); | 
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| 249 |         if (lyn[i] == NULL) return(0); | 
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| 250 |         cuddRef(lyn[i]); | 
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| 251 |     } | 
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| 252 |     *nx = lnx; | 
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| 253 |     *ny = lny; | 
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| 254 |  | 
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| 255 |     *E = dd->background; /* this call will never cause reordering */ | 
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| 256 |     cuddRef(*E); | 
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| 257 |  | 
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| 258 |     while (! feof(fp)) { | 
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| 259 |         err = fscanf(fp, "%d %d %lf", &u, &v, &val); | 
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| 260 |         if (err == EOF) { | 
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| 261 |             break; | 
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| 262 |         } else if (err != 3) { | 
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| 263 |             return(0); | 
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| 264 |         } else if (u >= *m || v >= *n || u < 0 || v < 0) { | 
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| 265 |             return(0); | 
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| 266 |         } | 
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| 267 |   | 
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| 268 |         minterm1 = one; cuddRef(minterm1); | 
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| 269 |  | 
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| 270 |         /* Build minterm1 corresponding to this arc */ | 
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| 271 |         for (i = lnx - 1; i>=0; i--) { | 
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| 272 |             if (u & 1) { | 
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| 273 |                 w = Cudd_addApply(dd, Cudd_addTimes, minterm1, lx[i]); | 
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| 274 |             } else { | 
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| 275 |                 w = Cudd_addApply(dd, Cudd_addTimes, minterm1, lxn[i]); | 
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| 276 |             } | 
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| 277 |             if (w == NULL) { | 
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| 278 |                 Cudd_RecursiveDeref(dd, minterm1); | 
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| 279 |                 return(0); | 
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| 280 |             } | 
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| 281 |             cuddRef(w); | 
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| 282 |             Cudd_RecursiveDeref(dd, minterm1); | 
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| 283 |             minterm1 = w; | 
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| 284 |             u >>= 1; | 
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| 285 |         } | 
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| 286 |         for (i = lny - 1; i>=0; i--) { | 
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| 287 |             if (v & 1) { | 
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| 288 |                 w = Cudd_addApply(dd, Cudd_addTimes, minterm1, ly[i]); | 
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| 289 |             } else { | 
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| 290 |                 w = Cudd_addApply(dd, Cudd_addTimes, minterm1, lyn[i]); | 
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| 291 |             } | 
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| 292 |             if (w == NULL) { | 
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| 293 |                 Cudd_RecursiveDeref(dd, minterm1); | 
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| 294 |                 return(0); | 
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| 295 |             } | 
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| 296 |             cuddRef(w); | 
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| 297 |             Cudd_RecursiveDeref(dd, minterm1); | 
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| 298 |             minterm1 = w; | 
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| 299 |             v >>= 1; | 
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| 300 |         } | 
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| 301 |         /* Create new constant node if necessary. | 
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| 302 |         ** This call will never cause reordering. | 
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| 303 |         */ | 
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| 304 |         neW = cuddUniqueConst(dd, val); | 
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| 305 |         if (neW == NULL) { | 
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| 306 |             Cudd_RecursiveDeref(dd, minterm1); | 
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| 307 |             return(0); | 
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| 308 |         } | 
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| 309 |         cuddRef(neW); | 
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| 310 |  | 
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| 311 |         w = Cudd_addIte(dd, minterm1, neW, *E); | 
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| 312 |         if (w == NULL) { | 
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| 313 |             Cudd_RecursiveDeref(dd, minterm1); | 
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| 314 |             Cudd_RecursiveDeref(dd, neW); | 
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| 315 |             return(0); | 
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| 316 |         } | 
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| 317 |         cuddRef(w); | 
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| 318 |         Cudd_RecursiveDeref(dd, minterm1); | 
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| 319 |         Cudd_RecursiveDeref(dd, neW); | 
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| 320 |         Cudd_RecursiveDeref(dd, *E); | 
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| 321 |         *E = w; | 
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| 322 |     } | 
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| 323 |     return(1); | 
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| 324 |  | 
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| 325 | } /* end of Cudd_addRead */ | 
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| 326 |  | 
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| 327 |  | 
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| 328 | /**Function******************************************************************** | 
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| 329 |  | 
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| 330 |   Synopsis    [Reads in a graph (without labels) given as a list of arcs.] | 
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| 331 |  | 
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| 332 |   Description [Reads in a graph (without labels) given as an adjacency | 
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| 333 |   matrix.  The first line of the input contains the numbers of rows and | 
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| 334 |   columns of the adjacency matrix. The remaining lines contain the arcs | 
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| 335 |   of the graph, one per line. Each arc is described by two integers, | 
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| 336 |   i.e., the row and column number, or the indices of the two endpoints. | 
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| 337 |   Cudd_bddRead produces a BDD that depends on two sets of variables: x | 
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| 338 |   and y.  The x variables (x\[0\] ... x\[nx-1\]) encode | 
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| 339 |   the row index and the y variables (y\[0\] ... y\[ny-1\]) encode the | 
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| 340 |   column index. x\[0\] and y\[0\] are the most significant bits in the | 
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| 341 |   indices. | 
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| 342 |   The variables may already exist or may be created by the function. | 
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| 343 |   The index of x\[i\] is bx+i*sx, and the index of y\[i\] is by+i*sy.<p> | 
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| 344 |   On input, nx and ny hold the numbers of row and column variables already | 
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| 345 |   in existence. On output, they hold the numbers of row and column | 
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| 346 |   variables actually used by the matrix. When Cudd_bddRead creates the | 
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| 347 |   variable arrays, the index of x\[i\] is bx+i*sx, and the index of | 
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| 348 |   y\[i\] is by+i*sy. When some variables already exist, Cudd_bddRead | 
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| 349 |   expects the indices of the existing x variables to be bx+i*sx, and the | 
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| 350 |   indices of the existing y variables to be by+i*sy.<p> | 
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| 351 |   m and n are set to the numbers of rows and columns of the | 
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| 352 |   matrix.  Their values on input are immaterial.  The BDD for the graph | 
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| 353 |   is returned in E, and its reference count is > 0. Cudd_bddRead returns | 
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| 354 |   1 in case of success; 0 otherwise.] | 
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| 355 |  | 
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| 356 |   SideEffects [nx and ny are set to the numbers of row and column | 
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| 357 |   variables. m and n are set to the numbers of rows and columns. x and y | 
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| 358 |   are possibly extended to represent the array of row and column | 
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| 359 |   variables.] | 
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| 360 |  | 
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| 361 |   SeeAlso     [Cudd_addHarwell Cudd_addRead] | 
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| 362 |  | 
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| 363 | ******************************************************************************/ | 
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| 364 | int | 
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| 365 | Cudd_bddRead( | 
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| 366 |   FILE * fp /* input file pointer */, | 
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| 367 |   DdManager * dd /* DD manager */, | 
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| 368 |   DdNode ** E /* characteristic function of the graph */, | 
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| 369 |   DdNode *** x /* array of row variables */, | 
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| 370 |   DdNode *** y /* array of column variables */, | 
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| 371 |   int * nx /* number or row variables */, | 
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| 372 |   int * ny /* number or column variables */, | 
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| 373 |   int * m /* number of rows */, | 
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| 374 |   int * n /* number of columns */, | 
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| 375 |   int  bx /* first index of row variables */, | 
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| 376 |   int  sx /* step of row variables */, | 
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| 377 |   int  by /* first index of column variables */, | 
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| 378 |   int  sy /* step of column variables */) | 
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| 379 | { | 
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| 380 |     DdNode *one, *zero; | 
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| 381 |     DdNode *w; | 
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| 382 |     DdNode *minterm1; | 
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| 383 |     int u, v, err, i, nv; | 
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| 384 |     int lnx, lny; | 
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| 385 |     DdNode **lx, **ly; | 
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| 386 |  | 
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| 387 |     one = DD_ONE(dd); | 
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| 388 |     zero = Cudd_Not(one); | 
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| 389 |  | 
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| 390 |     err = fscanf(fp, "%d %d", &u, &v); | 
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| 391 |     if (err == EOF) { | 
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| 392 |         return(0); | 
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| 393 |     } else if (err != 2) { | 
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| 394 |         return(0); | 
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| 395 |     } | 
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| 396 |  | 
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| 397 |     *m = u; | 
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| 398 |     /* Compute the number of x variables. */ | 
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| 399 |     lx = *x; | 
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| 400 |     u--;        /* row and column numbers start from 0 */ | 
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| 401 |     for (lnx=0; u > 0; lnx++) { | 
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| 402 |         u >>= 1; | 
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| 403 |     } | 
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| 404 |     if (lnx > *nx) { | 
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| 405 |         *x = lx = REALLOC(DdNode *, *x, lnx); | 
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| 406 |         if (lx == NULL) { | 
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| 407 |             dd->errorCode = CUDD_MEMORY_OUT; | 
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| 408 |             return(0); | 
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| 409 |         } | 
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| 410 |     } | 
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| 411 |  | 
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| 412 |     *n = v; | 
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| 413 |     /* Compute the number of y variables. */ | 
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| 414 |     ly = *y; | 
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| 415 |     v--;        /* row and column numbers start from 0 */ | 
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| 416 |     for (lny=0; v > 0; lny++) { | 
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| 417 |         v >>= 1; | 
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| 418 |     } | 
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| 419 |     if (lny > *ny) { | 
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| 420 |         *y = ly = REALLOC(DdNode *, *y, lny); | 
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| 421 |         if (ly == NULL) { | 
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| 422 |             dd->errorCode = CUDD_MEMORY_OUT; | 
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| 423 |             return(0); | 
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| 424 |         } | 
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| 425 |     } | 
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| 426 |  | 
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| 427 |     /* Create all new variables. */ | 
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| 428 |     for (i = *nx, nv = bx + (*nx) * sx; i < lnx; i++, nv += sx) { | 
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| 429 |         do { | 
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| 430 |             dd->reordered = 0; | 
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| 431 |             lx[i] = cuddUniqueInter(dd, nv, one, zero); | 
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| 432 |         } while (dd->reordered == 1); | 
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| 433 |         if (lx[i] == NULL) return(0); | 
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| 434 |         cuddRef(lx[i]); | 
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| 435 |     } | 
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| 436 |     for (i = *ny, nv = by + (*ny) * sy; i < lny; i++, nv += sy) { | 
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| 437 |         do { | 
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| 438 |             dd->reordered = 0; | 
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| 439 |             ly[i] = cuddUniqueInter(dd, nv, one, zero); | 
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| 440 |         } while (dd->reordered == 1); | 
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| 441 |         if (ly[i] == NULL) return(0); | 
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| 442 |         cuddRef(ly[i]); | 
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| 443 |     } | 
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| 444 |     *nx = lnx; | 
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| 445 |     *ny = lny; | 
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| 446 |  | 
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| 447 |     *E = zero; /* this call will never cause reordering */ | 
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| 448 |     cuddRef(*E); | 
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| 449 |  | 
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| 450 |     while (! feof(fp)) { | 
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| 451 |         err = fscanf(fp, "%d %d", &u, &v); | 
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| 452 |         if (err == EOF) { | 
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| 453 |             break; | 
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| 454 |         } else if (err != 2) { | 
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| 455 |             return(0); | 
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| 456 |         } else if (u >= *m || v >= *n || u < 0 || v < 0) { | 
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| 457 |             return(0); | 
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| 458 |         } | 
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| 459 |   | 
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| 460 |         minterm1 = one; cuddRef(minterm1); | 
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| 461 |  | 
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| 462 |         /* Build minterm1 corresponding to this arc. */ | 
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| 463 |         for (i = lnx - 1; i>=0; i--) { | 
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| 464 |             if (u & 1) { | 
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| 465 |                 w = Cudd_bddAnd(dd, minterm1, lx[i]); | 
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| 466 |             } else { | 
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| 467 |                 w = Cudd_bddAnd(dd, minterm1, Cudd_Not(lx[i])); | 
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| 468 |             } | 
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| 469 |             if (w == NULL) { | 
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| 470 |                 Cudd_RecursiveDeref(dd, minterm1); | 
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| 471 |                 return(0); | 
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| 472 |             } | 
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| 473 |             cuddRef(w); | 
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| 474 |             Cudd_RecursiveDeref(dd,minterm1); | 
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| 475 |             minterm1 = w; | 
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| 476 |             u >>= 1; | 
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| 477 |         } | 
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| 478 |         for (i = lny - 1; i>=0; i--) { | 
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| 479 |             if (v & 1) { | 
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| 480 |                 w = Cudd_bddAnd(dd, minterm1, ly[i]); | 
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| 481 |             } else { | 
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| 482 |                 w = Cudd_bddAnd(dd, minterm1, Cudd_Not(ly[i])); | 
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| 483 |             } | 
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| 484 |             if (w == NULL) { | 
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| 485 |                 Cudd_RecursiveDeref(dd, minterm1); | 
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| 486 |                 return(0); | 
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| 487 |             } | 
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| 488 |             cuddRef(w); | 
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| 489 |             Cudd_RecursiveDeref(dd, minterm1); | 
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| 490 |             minterm1 = w; | 
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| 491 |             v >>= 1; | 
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| 492 |         } | 
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| 493 |  | 
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| 494 |         w = Cudd_bddAnd(dd, Cudd_Not(minterm1), Cudd_Not(*E)); | 
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| 495 |         if (w == NULL) { | 
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| 496 |             Cudd_RecursiveDeref(dd, minterm1); | 
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| 497 |             return(0); | 
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| 498 |         } | 
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| 499 |         w = Cudd_Not(w); | 
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| 500 |         cuddRef(w); | 
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| 501 |         Cudd_RecursiveDeref(dd, minterm1); | 
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| 502 |         Cudd_RecursiveDeref(dd, *E); | 
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| 503 |         *E = w; | 
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| 504 |     } | 
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| 505 |     return(1); | 
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| 506 |  | 
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| 507 | } /* end of Cudd_bddRead */ | 
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| 508 |  | 
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| 509 | /*---------------------------------------------------------------------------*/ | 
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| 510 | /* Definition of internal functions                                          */ | 
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| 511 | /*---------------------------------------------------------------------------*/ | 
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| 512 |  | 
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| 513 |  | 
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| 514 | /*---------------------------------------------------------------------------*/ | 
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| 515 | /* Definition of static functions                                            */ | 
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| 516 | /*---------------------------------------------------------------------------*/ | 
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| 517 |  | 
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