mathjs/lib/function/algebra/sparse/cs_permute.js

'use strict';

function factory (type) {

  var SparseMatrix = type.SparseMatrix;

  /**
   * Permutes a sparse matrix C = P * A * Q
   *
   * @param {Matrix}  a               The Matrix A
   * @param {Array}   pinv            The row permutation vector
   * @param {Array}   q               The column permutation vector
   * @param {boolean} values          Create a pattern matrix (false), values and pattern otherwise
   *
   * @return {Matrix}                 C = P * A * Q, null on error
   *
   * Reference: http://faculty.cse.tamu.edu/davis/publications.html
   */
  var cs_permute = function (a, pinv, q, values) {
    // a arrays
    var avalues = a._values;
    var aindex = a._index;
    var aptr = a._ptr;
    var asize = a._size;
    var adt = a._datatype;
    // rows & columns
    var m = asize[0];
    var n = asize[1];
    // c arrays
    var cvalues = values && a._values ? [] : null;
    var cindex = []; // (aptr[n]);
    var cptr = []; // (n + 1);
    // initialize vars
    var nz = 0;
    // loop columns    
    for (var k = 0; k < n; k++) {
      // column k of C is column q[k] of A
      cptr[k] = nz;
      // apply column permutation
      var j = q ? (q[k]) : k;
      // loop values in column j of A
      for (var t0 = aptr[j], t1 = aptr[j + 1], t = t0; t < t1; t++) {
        // row i of A is row pinv[i] of C
        var r = pinv ? pinv[aindex[t]] : aindex[t];
        // index
        cindex[nz] = r;
        // check we need to populate values
        if (cvalues) 
          cvalues[nz] = avalues[t];
        // increment number of nonzero elements
        nz++;
      }
    }
    // finalize the last column of C
    cptr[n] = nz;
    // return C matrix
    return new SparseMatrix({
      values: cvalues,
      index: cindex,
      ptr: cptr,
      size: [m, n],
      datatype: adt
    });
  };

  return cs_permute;
}

exports.name = 'cs_permute';
exports.path = 'sparse';
exports.factory = factory;