text: /*
  Copyright (c) since 2015, Tel Aviv University and Software Modeling Lab
  
  All rights reserved.
  
  Redistribution and use in source and binary forms, with or without
  modification, are permitted provided that the following conditions are met:
      * Redistributions of source code must retain the above copyright
        notice, this list of conditions and the following disclaimer.
      * Redistributions in binary form must reproduce the above copyright
        notice, this list of conditions and the following disclaimer in the
        documentation and/or other materials provided with the distribution.
      * Neither the name of Tel Aviv University and Software Modeling Lab nor the
        names of its contributors may be used to endorse or promote products
        derived from this software without specific prior written permission.
  
  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
  ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
  WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
  DISCLAIMED. IN NO EVENT SHALL Tel Aviv University and Software Modeling Lab 
  BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR 
  CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE 
  GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) 
  HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT 
  LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT 
  OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 
  */
  
  /**
    @file
  
    @ingroup cudd
  
    @brief Functions to read in a matrix
  
    @see cudd_addHarwell.c
  
    @author Fabio Somenzi
  
    @copyright@parblock
    Copyright (c) 1995-2015, Regents of the University of Colorado
  
    All rights reserved.
  
    Redistribution and use in source and binary forms, with or without
    modification, are permitted provided that the following conditions
    are met:
  
    Redistributions of source code must retain the above copyright
    notice, this list of conditions and the following disclaimer.
  
    Redistributions in binary form must reproduce the above copyright
    notice, this list of conditions and the following disclaimer in the
    documentation and/or other materials provided with the distribution.
  
    Neither the name of the University of Colorado nor the names of its
    contributors may be used to endorse or promote products derived from
    this software without specific prior written permission.
  
    THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
    "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
    LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
    FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
    COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
    INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
    BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
    LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
    CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
    LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
    ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
    POSSIBILITY OF SUCH DAMAGE.
    @endparblock
  
  */
  
  #include "../util/util.h"
  #include "cuddInt.h"
  
  
  /*---------------------------------------------------------------------------*/
  /* Constant declarations                                                     */
  /*---------------------------------------------------------------------------*/
  
  
  /*---------------------------------------------------------------------------*/
  /* Stucture declarations                                                     */
  /*---------------------------------------------------------------------------*/
  
  
  /*---------------------------------------------------------------------------*/
  /* Type declarations                                                         */
  /*---------------------------------------------------------------------------*/
  
  
  /*---------------------------------------------------------------------------*/
  /* Variable declarations                                                     */
  /*---------------------------------------------------------------------------*/
  
  
  /*---------------------------------------------------------------------------*/
  /* Macro declarations                                                        */
  /*---------------------------------------------------------------------------*/
  
  /** \cond */
  
  /*---------------------------------------------------------------------------*/
  /* Static function prototypes                                                */
  /*---------------------------------------------------------------------------*/
  
  /** \endcond */
  
  
  /*---------------------------------------------------------------------------*/
  /* Definition of exported functions                                          */
  /*---------------------------------------------------------------------------*/
  
  
  /**
    @brief Reads in a sparse matrix.
  
    @details Reads in a sparse matrix specified in a simple format.
    The first line of the input contains the numbers of rows and columns.
    The remaining lines contain the elements of the matrix, one per line.
    Given a background value
    (specified by the background field of the manager), only the values
    different from it are explicitly listed.  Each foreground element is
    described by two integers, i.e., the row and column number, and a
    real number, i.e., the value.<p>
    Cudd_addRead produces an %ADD that depends on two sets of variables: x
    and y.  The x variables (x\[0\] ... x\[nx-1\]) encode the row index and
    the y variables (y\[0\] ... y\[ny-1\]) encode the column index.
    x\[0\] and y\[0\] are the most significant bits in the indices.
    The variables may already exist or may be created by the function.
    The index of x\[i\] is bx+i*sx, and the index of y\[i\] is by+i*sy.<p>
    On input, nx and ny hold the numbers
    of row and column variables already in existence. On output, they
    hold the numbers of row and column variables actually used by the
    matrix. When Cudd_addRead creates the variable arrays,
    the index of x\[i\] is bx+i*sx, and the index of y\[i\] is by+i*sy.
    When some variables already exist Cudd_addRead expects the indices
    of the existing x variables to be bx+i*sx, and the indices of the
    existing y variables to be by+i*sy.<p>
    m and n are set to the numbers of rows and columns of the
    matrix.  Their values on input are immaterial.
    The %ADD for the sparse matrix is returned in E, and its reference
    count is > 0.
  
    @return 1 in case of success; 0 otherwise.
  
    @sideeffect nx and ny are set to the numbers of row and column
    variables. m and n are set to the numbers of rows and columns. x and y
    are possibly extended to represent the array of row and column
    variables. Similarly for xn and yn_, which hold on return from
    Cudd_addRead the complements of the row and column variables.
  
    @see Cudd_addHarwell Cudd_bddRead
  
  */
  int
  Cudd_addRead(
    FILE * fp /**< input file pointer */,
    DdManager * dd /**< %DD manager */,
    DdNode ** E /**< characteristic function of the graph */,
    DdNode *** x /**< array of row variables */,
    DdNode *** y /**< array of column variables */,
    DdNode *** xn /**< array of complemented row variables */,
    DdNode *** yn_ /**< array of complemented column variables */,
    int * nx /**< number or row variables */,
    int * ny /**< number or column variables */,
    int * m /**< number of rows */,
    int * n /**< number of columns */,
    int  bx /**< first index of row variables */,
    int  sx /**< step of row variables */,
    int  by /**< first index of column variables */,
    int  sy /**< step of column variables */)
  {
      DdNode *one, *zero;
      DdNode *w, *neW;
      DdNode *minterm1;
      int u, v, err, i, nv;
      int lnx, lny;
      CUDD_VALUE_TYPE val;
      DdNode **lx, **ly, **lxn, **lyn;
  
      one = DD_ONE(dd);
      zero = DD_ZERO(dd);
  
      err = fscanf(fp, "%d %d", &u, &v);
      if (err == EOF) {
  	return(0);
      } else if (err != 2) {
  	return(0);
      }
  
      *m = u;
      /* Compute the number of x variables. */
      lx = *x; lxn = *xn;
      u--; 	/* row and column numbers start from 0 */
      for (lnx=0; u > 0; lnx++) {
  	u >>= 1;
      }
      /* Here we rely on the fact that REALLOC of a null pointer is
      ** translates to an ALLOC.
      */
      if (lnx > *nx) {
  	*x = lx = REALLOC(DdNode *, *x, lnx);
  	if (lx == NULL) {
  	    dd->errorCode = CUDD_MEMORY_OUT;
  	    return(0);
  	}
  	*xn = lxn =  REALLOC(DdNode *, *xn, lnx);
  	if (lxn == NULL) {
  	    dd->errorCode = CUDD_MEMORY_OUT;
  	    return(0);
  	}
      }
  
      *n = v;
      /* Compute the number of y variables. */
      ly = *y; lyn = *yn_;
      v--; 	/* row and column numbers start from 0 */
      for (lny=0; v > 0; lny++) {
  	v >>= 1;
      }
      /* Here we rely on the fact that REALLOC of a null pointer is
      ** translates to an ALLOC.
      */
      if (lny > *ny) {
  	*y = ly = REALLOC(DdNode *, *y, lny);
  	if (ly == NULL) {
  	    dd->errorCode = CUDD_MEMORY_OUT;
  	    return(0);
  	}
  	*yn_ = lyn =  REALLOC(DdNode *, *yn_, lny);
  	if (lyn == NULL) {
  	    dd->errorCode = CUDD_MEMORY_OUT;
  	    return(0);
  	}
      }
  
      /* Create all new variables. */
      for (i = *nx, nv = bx + (*nx) * sx; i < lnx; i++, nv += sx) {
  	do {
  	    dd->reordered = 0;
  	    lx[i] = cuddUniqueInter(dd, nv, one, zero);
  	} while (dd->reordered == 1);
  	if (lx[i] == NULL) {
              if (dd->errorCode == CUDD_TIMEOUT_EXPIRED && dd->timeoutHandler) {
                  dd->timeoutHandler(dd, dd->tohArg);
              }
              return(0);
          }
          cuddRef(lx[i]);
  	do {
  	    dd->reordered = 0;
  	    lxn[i] = cuddUniqueInter(dd, nv, zero, one);
  	} while (dd->reordered == 1);
  	if (lxn[i] == NULL) {
              if (dd->errorCode == CUDD_TIMEOUT_EXPIRED && dd->timeoutHandler) {
                  dd->timeoutHandler(dd, dd->tohArg);
              }
              return(0);
          }
          cuddRef(lxn[i]);
      }
      for (i = *ny, nv = by + (*ny) * sy; i < lny; i++, nv += sy) {
  	do {
  	    dd->reordered = 0;
  	    ly[i] = cuddUniqueInter(dd, nv, one, zero);
  	} while (dd->reordered == 1);
  	if (ly[i] == NULL) {
              if (dd->errorCode == CUDD_TIMEOUT_EXPIRED && dd->timeoutHandler) {
                  dd->timeoutHandler(dd, dd->tohArg);
              }
              return(0);
          }
  	cuddRef(ly[i]);
  	do {
  	    dd->reordered = 0;
  	    lyn[i] = cuddUniqueInter(dd, nv, zero, one);
  	} while (dd->reordered == 1);
  	if (lyn[i] == NULL) {
              if (dd->errorCode == CUDD_TIMEOUT_EXPIRED && dd->timeoutHandler) {
                  dd->timeoutHandler(dd, dd->tohArg);
              }
              return(0);
          }
  	cuddRef(lyn[i]);
      }
      *nx = lnx;
      *ny = lny;
  
      *E = dd->background; /* this call will never cause reordering */
      cuddRef(*E);
  
      while (! feof(fp)) {
  	err = fscanf(fp, "%d %d %lf", &u, &v, &val);
  	if (err == EOF) {
  	    break;
  	} else if (err != 3) {
  	    return(0);
  	} else if (u >= *m || v >= *n || u < 0 || v < 0) {
  	    return(0);
  	}
   
  	minterm1 = one; cuddRef(minterm1);
  
  	/* Build minterm1 corresponding to this arc */
  	for (i = lnx - 1; i>=0; i--) {
  	    if (u & 1) {
  		w = Cudd_addApply(dd, Cudd_addTimes, minterm1, lx[i]);
  	    } else {
  		w = Cudd_addApply(dd, Cudd_addTimes, minterm1, lxn[i]);
  	    }
  	    if (w == NULL) {
  		Cudd_RecursiveDeref(dd, minterm1);
  		return(0);
  	    }
  	    cuddRef(w);
  	    Cudd_RecursiveDeref(dd, minterm1);
  	    minterm1 = w;
  	    u >>= 1;
  	}
  	for (i = lny - 1; i>=0; i--) {
  	    if (v & 1) {
  		w = Cudd_addApply(dd, Cudd_addTimes, minterm1, ly[i]);
  	    } else {
  		w = Cudd_addApply(dd, Cudd_addTimes, minterm1, lyn[i]);
  	    }
  	    if (w == NULL) {
  		Cudd_RecursiveDeref(dd, minterm1);
  		return(0);
  	    }
  	    cuddRef(w);
  	    Cudd_RecursiveDeref(dd, minterm1);
  	    minterm1 = w;
  	    v >>= 1;
  	}
  	/* Create new constant node if necessary.
  	** This call will never cause reordering.
  	*/
  	neW = cuddUniqueConst(dd, val);
  	if (neW == NULL) {
  	    Cudd_RecursiveDeref(dd, minterm1);
  	    return(0);
  	}
      	cuddRef(neW);
  
  	w = Cudd_addIte(dd, minterm1, neW, *E);
  	if (w == NULL) {
  	    Cudd_RecursiveDeref(dd, minterm1);
  	    Cudd_RecursiveDeref(dd, neW);
  	    return(0);
  	}
  	cuddRef(w);
  	Cudd_RecursiveDeref(dd, minterm1);
  	Cudd_RecursiveDeref(dd, neW);
  	Cudd_RecursiveDeref(dd, *E);
  	*E = w;
      }
      return(1);
  
  } /* end of Cudd_addRead */
  
  
  /**
    @brief Reads in a graph (without labels) given as a list of arcs.
  
    @details Reads in a graph (without labels) given as an adjacency
    matrix.  The first line of the input contains the numbers of rows and
    columns of the adjacency matrix. The remaining lines contain the arcs
    of the graph, one per line. Each arc is described by two integers,
    i.e., the row and column number, or the indices of the two endpoints.
    Cudd_bddRead produces a %BDD that depends on two sets of variables: x
    and y.  The x variables (x\[0\] ... x\[nx-1\]) encode
    the row index and the y variables (y\[0\] ... y\[ny-1\]) encode the
    column index. x\[0\] and y\[0\] are the most significant bits in the
    indices.
    The variables may already exist or may be created by the function.
    The index of x\[i\] is bx+i*sx, and the index of y\[i\] is by+i*sy.<p>
    On input, nx and ny hold the numbers of row and column variables already
    in existence. On output, they hold the numbers of row and column
    variables actually used by the matrix. When Cudd_bddRead creates the
    variable arrays, the index of x\[i\] is bx+i*sx, and the index of
    y\[i\] is by+i*sy. When some variables already exist, Cudd_bddRead
    expects the indices of the existing x variables to be bx+i*sx, and the
    indices of the existing y variables to be by+i*sy.<p>
    m and n are set to the numbers of rows and columns of the
    matrix.  Their values on input are immaterial.  The %BDD for the graph
    is returned in E, and its reference count is > 0.
  
    @return 1 in case of success; 0 otherwise.
  
    @sideeffect nx and ny are set to the numbers of row and column
    variables. m and n are set to the numbers of rows and columns. x and y
    are possibly extended to represent the array of row and column
    variables.
  
    @see Cudd_addHarwell Cudd_addRead
  
  */
  int
  Cudd_bddRead(
    FILE * fp /**< input file pointer */,
    DdManager * dd /**< DD manager */,
    DdNode ** E /**< characteristic function of the graph */,
    DdNode *** x /**< array of row variables */,
    DdNode *** y /**< array of column variables */,
    int * nx /**< number or row variables */,
    int * ny /**< number or column variables */,
    int * m /**< number of rows */,
    int * n /**< number of columns */,
    int  bx /**< first index of row variables */,
    int  sx /**< step of row variables */,
    int  by /**< first index of column variables */,
    int  sy /**< step of column variables */)
  {
      DdNode *one, *zero;
      DdNode *w;
      DdNode *minterm1;
      int u, v, err, i, nv;
      int lnx, lny;
      DdNode **lx, **ly;
  
      one = DD_ONE(dd);
      zero = Cudd_Not(one);
  
      err = fscanf(fp, "%d %d", &u, &v);
      if (err == EOF) {
  	return(0);
      } else if (err != 2) {
  	return(0);
      }
  
      *m = u;
      /* Compute the number of x variables. */
      lx = *x;
      u--; 	/* row and column numbers start from 0 */
      for (lnx=0; u > 0; lnx++) {
  	u >>= 1;
      }
      if (lnx > *nx) {
  	*x = lx = REALLOC(DdNode *, *x, lnx);
  	if (lx == NULL) {
  	    dd->errorCode = CUDD_MEMORY_OUT;
  	    return(0);
  	}
      }
  
      *n = v;
      /* Compute the number of y variables. */
      ly = *y;
      v--; 	/* row and column numbers start from 0 */
      for (lny=0; v > 0; lny++) {
  	v >>= 1;
      }
      if (lny > *ny) {
  	*y = ly = REALLOC(DdNode *, *y, lny);
  	if (ly == NULL) {
  	    dd->errorCode = CUDD_MEMORY_OUT;
  	    return(0);
  	}
      }
  
      /* Create all new variables. */
      for (i = *nx, nv = bx + (*nx) * sx; i < lnx; i++, nv += sx) {
  	do {
  	    dd->reordered = 0;
  	    lx[i] = cuddUniqueInter(dd, nv, one, zero);
  	} while (dd->reordered == 1);
  	if (lx[i] == NULL) {
              if (dd->errorCode == CUDD_TIMEOUT_EXPIRED && dd->timeoutHandler) {
                  dd->timeoutHandler(dd, dd->tohArg);
              }
              return(0);
          }
          cuddRef(lx[i]);
      }
      for (i = *ny, nv = by + (*ny) * sy; i < lny; i++, nv += sy) {
  	do {
  	    dd->reordered = 0;
  	    ly[i] = cuddUniqueInter(dd, nv, one, zero);
  	} while (dd->reordered == 1);
  	if (ly[i] == NULL) {
              if (dd->errorCode == CUDD_TIMEOUT_EXPIRED && dd->timeoutHandler) {
                  dd->timeoutHandler(dd, dd->tohArg);
              }
              return(0);
          }
  	cuddRef(ly[i]);
      }
      *nx = lnx;
      *ny = lny;
  
      *E = zero; /* this call will never cause reordering */
      cuddRef(*E);
  
      while (! feof(fp)) {
  	err = fscanf(fp, "%d %d", &u, &v);
  	if (err == EOF) {
  	    break;
  	} else if (err != 2) {
  	    return(0);
  	} else if (u >= *m || v >= *n || u < 0 || v < 0) {
  	    return(0);
  	}
   
  	minterm1 = one; cuddRef(minterm1);
  
  	/* Build minterm1 corresponding to this arc. */
  	for (i = lnx - 1; i>=0; i--) {
  	    if (u & 1) {
  		w = Cudd_bddAnd(dd, minterm1, lx[i]);
  	    } else {
  		w = Cudd_bddAnd(dd, minterm1, Cudd_Not(lx[i]));
  	    }
  	    if (w == NULL) {
  		Cudd_RecursiveDeref(dd, minterm1);
  		return(0);
  	    }
  	    cuddRef(w);
  	    Cudd_RecursiveDeref(dd,minterm1);
  	    minterm1 = w;
  	    u >>= 1;
  	}
  	for (i = lny - 1; i>=0; i--) {
  	    if (v & 1) {
  		w = Cudd_bddAnd(dd, minterm1, ly[i]);
  	    } else {
  		w = Cudd_bddAnd(dd, minterm1, Cudd_Not(ly[i]));
  	    }
  	    if (w == NULL) {
  		Cudd_RecursiveDeref(dd, minterm1);
  		return(0);
  	    }
  	    cuddRef(w);
  	    Cudd_RecursiveDeref(dd, minterm1);
  	    minterm1 = w;
  	    v >>= 1;
  	}
  
  	w = Cudd_bddAnd(dd, Cudd_Not(minterm1), Cudd_Not(*E));
  	if (w == NULL) {
  	    Cudd_RecursiveDeref(dd, minterm1);
  	    return(0);
  	}
  	w = Cudd_Not(w);
  	cuddRef(w);
  	Cudd_RecursiveDeref(dd, minterm1);
  	Cudd_RecursiveDeref(dd, *E);
  	*E = w;
      }
      return(1);
  
  } /* end of Cudd_bddRead */
  
  /*---------------------------------------------------------------------------*/
  /* Definition of internal functions                                          */
  /*---------------------------------------------------------------------------*/
  
  
  /*---------------------------------------------------------------------------*/
  /* Definition of static functions                                            */
  /*---------------------------------------------------------------------------*/
  
  