mathjs/lib/type/matrix/DenseMatrix.js

"use strict";

Object.defineProperty(exports, "__esModule", {
  value: true
});
exports.createDenseMatrixClass = void 0;

var _is = require("../../utils/is");

var _array = require("../../utils/array");

var _string = require("../../utils/string");

var _number = require("../../utils/number");

var _object = require("../../utils/object");

var _DimensionError = require("../../error/DimensionError");

var _factory = require("../../utils/factory");

var name = 'DenseMatrix';
var dependencies = ['Matrix'];
var createDenseMatrixClass = /* #__PURE__ */(0, _factory.factory)(name, dependencies, function (_ref) {
  var Matrix = _ref.Matrix;

  /**
   * Dense Matrix implementation. A regular, dense matrix, supporting multi-dimensional matrices. This is the default matrix type.
   * @class DenseMatrix
   */
  function DenseMatrix(data, datatype) {
    if (!(this instanceof DenseMatrix)) {
      throw new SyntaxError('Constructor must be called with the new operator');
    }

    if (datatype && !(0, _is.isString)(datatype)) {
      throw new Error('Invalid datatype: ' + datatype);
    }

    if ((0, _is.isMatrix)(data)) {
      // check data is a DenseMatrix
      if (data.type === 'DenseMatrix') {
        // clone data & size
        this._data = (0, _object.clone)(data._data);
        this._size = (0, _object.clone)(data._size);
        this._datatype = datatype || data._datatype;
      } else {
        // build data from existing matrix
        this._data = data.toArray();
        this._size = data.size();
        this._datatype = datatype || data._datatype;
      }
    } else if (data && (0, _is.isArray)(data.data) && (0, _is.isArray)(data.size)) {
      // initialize fields from JSON representation
      this._data = data.data;
      this._size = data.size; // verify the dimensions of the array

      (0, _array.validate)(this._data, this._size);
      this._datatype = datatype || data.datatype;
    } else if ((0, _is.isArray)(data)) {
      // replace nested Matrices with Arrays
      this._data = preprocess(data); // get the dimensions of the array

      this._size = (0, _array.arraySize)(this._data); // verify the dimensions of the array, TODO: compute size while processing array

      (0, _array.validate)(this._data, this._size); // data type unknown

      this._datatype = datatype;
    } else if (data) {
      // unsupported type
      throw new TypeError('Unsupported type of data (' + (0, _is.typeOf)(data) + ')');
    } else {
      // nothing provided
      this._data = [];
      this._size = [0];
      this._datatype = datatype;
    }
  }

  DenseMatrix.prototype = new Matrix();
  /**
   * Create a new DenseMatrix
   */

  DenseMatrix.prototype.createDenseMatrix = function (data, datatype) {
    return new DenseMatrix(data, datatype);
  };
  /**
   * Attach type information
   */


  DenseMatrix.prototype.type = 'DenseMatrix';
  DenseMatrix.prototype.isDenseMatrix = true;
  /**
   * Get the matrix type
   *
   * Usage:
   *    const matrixType = matrix.getDataType()  // retrieves the matrix type
   *
   * @memberOf DenseMatrix
   * @return {string}   type information; if multiple types are found from the Matrix, it will return "mixed"
   */

  DenseMatrix.prototype.getDataType = function () {
    return (0, _array.getArrayDataType)(this._data, _is.typeOf);
  };
  /**
   * Get the storage format used by the matrix.
   *
   * Usage:
   *     const format = matrix.storage()  // retrieve storage format
   *
   * @memberof DenseMatrix
   * @return {string}           The storage format.
   */


  DenseMatrix.prototype.storage = function () {
    return 'dense';
  };
  /**
   * Get the datatype of the data stored in the matrix.
   *
   * Usage:
   *     const format = matrix.datatype()   // retrieve matrix datatype
   *
   * @memberof DenseMatrix
   * @return {string}           The datatype.
   */


  DenseMatrix.prototype.datatype = function () {
    return this._datatype;
  };
  /**
   * Create a new DenseMatrix
   * @memberof DenseMatrix
   * @param {Array} data
   * @param {string} [datatype]
   */


  DenseMatrix.prototype.create = function (data, datatype) {
    return new DenseMatrix(data, datatype);
  };
  /**
   * Get a subset of the matrix, or replace a subset of the matrix.
   *
   * Usage:
   *     const subset = matrix.subset(index)               // retrieve subset
   *     const value = matrix.subset(index, replacement)   // replace subset
   *
   * @memberof DenseMatrix
   * @param {Index} index
   * @param {Array | Matrix | *} [replacement]
   * @param {*} [defaultValue=0]      Default value, filled in on new entries when
   *                                  the matrix is resized. If not provided,
   *                                  new matrix elements will be filled with zeros.
   */


  DenseMatrix.prototype.subset = function (index, replacement, defaultValue) {
    switch (arguments.length) {
      case 1:
        return _get(this, index);
      // intentional fall through

      case 2:
      case 3:
        return _set(this, index, replacement, defaultValue);

      default:
        throw new SyntaxError('Wrong number of arguments');
    }
  };
  /**
   * Get a single element from the matrix.
   * @memberof DenseMatrix
   * @param {number[]} index   Zero-based index
   * @return {*} value
   */


  DenseMatrix.prototype.get = function (index) {
    if (!(0, _is.isArray)(index)) {
      throw new TypeError('Array expected');
    }

    if (index.length !== this._size.length) {
      throw new _DimensionError.DimensionError(index.length, this._size.length);
    } // check index


    for (var x = 0; x < index.length; x++) {
      (0, _array.validateIndex)(index[x], this._size[x]);
    }

    var data = this._data;

    for (var i = 0, ii = index.length; i < ii; i++) {
      var indexI = index[i];
      (0, _array.validateIndex)(indexI, data.length);
      data = data[indexI];
    }

    return data;
  };
  /**
   * Replace a single element in the matrix.
   * @memberof DenseMatrix
   * @param {number[]} index   Zero-based index
   * @param {*} value
   * @param {*} [defaultValue]        Default value, filled in on new entries when
   *                                  the matrix is resized. If not provided,
   *                                  new matrix elements will be left undefined.
   * @return {DenseMatrix} self
   */


  DenseMatrix.prototype.set = function (index, value, defaultValue) {
    if (!(0, _is.isArray)(index)) {
      throw new TypeError('Array expected');
    }

    if (index.length < this._size.length) {
      throw new _DimensionError.DimensionError(index.length, this._size.length, '<');
    }

    var i, ii, indexI; // enlarge matrix when needed

    var size = index.map(function (i) {
      return i + 1;
    });

    _fit(this, size, defaultValue); // traverse over the dimensions


    var data = this._data;

    for (i = 0, ii = index.length - 1; i < ii; i++) {
      indexI = index[i];
      (0, _array.validateIndex)(indexI, data.length);
      data = data[indexI];
    } // set new value


    indexI = index[index.length - 1];
    (0, _array.validateIndex)(indexI, data.length);
    data[indexI] = value;
    return this;
  };
  /**
   * Get a submatrix of this matrix
   * @memberof DenseMatrix
   * @param {DenseMatrix} matrix
   * @param {Index} index   Zero-based index
   * @private
   */


  function _get(matrix, index) {
    if (!(0, _is.isIndex)(index)) {
      throw new TypeError('Invalid index');
    }

    var isScalar = index.isScalar();

    if (isScalar) {
      // return a scalar
      return matrix.get(index.min());
    } else {
      // validate dimensions
      var size = index.size();

      if (size.length !== matrix._size.length) {
        throw new _DimensionError.DimensionError(size.length, matrix._size.length);
      } // validate if any of the ranges in the index is out of range


      var min = index.min();
      var max = index.max();

      for (var i = 0, ii = matrix._size.length; i < ii; i++) {
        (0, _array.validateIndex)(min[i], matrix._size[i]);
        (0, _array.validateIndex)(max[i], matrix._size[i]);
      } // retrieve submatrix
      // TODO: more efficient when creating an empty matrix and setting _data and _size manually


      return new DenseMatrix(_getSubmatrix(matrix._data, index, size.length, 0), matrix._datatype);
    }
  }
  /**
   * Recursively get a submatrix of a multi dimensional matrix.
   * Index is not checked for correct number or length of dimensions.
   * @memberof DenseMatrix
   * @param {Array} data
   * @param {Index} index
   * @param {number} dims   Total number of dimensions
   * @param {number} dim    Current dimension
   * @return {Array} submatrix
   * @private
   */


  function _getSubmatrix(data, index, dims, dim) {
    var last = dim === dims - 1;
    var range = index.dimension(dim);

    if (last) {
      return range.map(function (i) {
        (0, _array.validateIndex)(i, data.length);
        return data[i];
      }).valueOf();
    } else {
      return range.map(function (i) {
        (0, _array.validateIndex)(i, data.length);
        var child = data[i];
        return _getSubmatrix(child, index, dims, dim + 1);
      }).valueOf();
    }
  }
  /**
   * Replace a submatrix in this matrix
   * Indexes are zero-based.
   * @memberof DenseMatrix
   * @param {DenseMatrix} matrix
   * @param {Index} index
   * @param {DenseMatrix | Array | *} submatrix
   * @param {*} defaultValue          Default value, filled in on new entries when
   *                                  the matrix is resized.
   * @return {DenseMatrix} matrix
   * @private
   */


  function _set(matrix, index, submatrix, defaultValue) {
    if (!index || index.isIndex !== true) {
      throw new TypeError('Invalid index');
    } // get index size and check whether the index contains a single value


    var iSize = index.size();
    var isScalar = index.isScalar(); // calculate the size of the submatrix, and convert it into an Array if needed

    var sSize;

    if ((0, _is.isMatrix)(submatrix)) {
      sSize = submatrix.size();
      submatrix = submatrix.valueOf();
    } else {
      sSize = (0, _array.arraySize)(submatrix);
    }

    if (isScalar) {
      // set a scalar
      // check whether submatrix is a scalar
      if (sSize.length !== 0) {
        throw new TypeError('Scalar expected');
      }

      matrix.set(index.min(), submatrix, defaultValue);
    } else {
      // set a submatrix
      // validate dimensions
      if (iSize.length < matrix._size.length) {
        throw new _DimensionError.DimensionError(iSize.length, matrix._size.length, '<');
      }

      if (sSize.length < iSize.length) {
        // calculate number of missing outer dimensions
        var i = 0;
        var outer = 0;

        while (iSize[i] === 1 && sSize[i] === 1) {
          i++;
        }

        while (iSize[i] === 1) {
          outer++;
          i++;
        } // unsqueeze both outer and inner dimensions


        submatrix = (0, _array.unsqueeze)(submatrix, iSize.length, outer, sSize);
      } // check whether the size of the submatrix matches the index size


      if (!(0, _object.deepStrictEqual)(iSize, sSize)) {
        throw new _DimensionError.DimensionError(iSize, sSize, '>');
      } // enlarge matrix when needed


      var size = index.max().map(function (i) {
        return i + 1;
      });

      _fit(matrix, size, defaultValue); // insert the sub matrix


      var dims = iSize.length;
      var dim = 0;

      _setSubmatrix(matrix._data, index, submatrix, dims, dim);
    }

    return matrix;
  }
  /**
   * Replace a submatrix of a multi dimensional matrix.
   * @memberof DenseMatrix
   * @param {Array} data
   * @param {Index} index
   * @param {Array} submatrix
   * @param {number} dims   Total number of dimensions
   * @param {number} dim
   * @private
   */


  function _setSubmatrix(data, index, submatrix, dims, dim) {
    var last = dim === dims - 1;
    var range = index.dimension(dim);

    if (last) {
      range.forEach(function (dataIndex, subIndex) {
        (0, _array.validateIndex)(dataIndex);
        data[dataIndex] = submatrix[subIndex[0]];
      });
    } else {
      range.forEach(function (dataIndex, subIndex) {
        (0, _array.validateIndex)(dataIndex);

        _setSubmatrix(data[dataIndex], index, submatrix[subIndex[0]], dims, dim + 1);
      });
    }
  }
  /**
   * Resize the matrix to the given size. Returns a copy of the matrix when
   * `copy=true`, otherwise return the matrix itself (resize in place).
   *
   * @memberof DenseMatrix
   * @param {number[] || Matrix} size The new size the matrix should have.
   * @param {*} [defaultValue=0]      Default value, filled in on new entries.
   *                                  If not provided, the matrix elements will
   *                                  be filled with zeros.
   * @param {boolean} [copy]          Return a resized copy of the matrix
   *
   * @return {Matrix}                 The resized matrix
   */


  DenseMatrix.prototype.resize = function (size, defaultValue, copy) {
    // validate arguments
    if (!(0, _is.isCollection)(size)) {
      throw new TypeError('Array or Matrix expected');
    } // SparseMatrix input is always 2d, flatten this into 1d if it's indeed a vector


    var sizeArray = size.valueOf().map(function (value) {
      return Array.isArray(value) && value.length === 1 ? value[0] : value;
    }); // matrix to resize

    var m = copy ? this.clone() : this; // resize matrix

    return _resize(m, sizeArray, defaultValue);
  };

  function _resize(matrix, size, defaultValue) {
    // check size
    if (size.length === 0) {
      // first value in matrix
      var v = matrix._data; // go deep

      while ((0, _is.isArray)(v)) {
        v = v[0];
      }

      return v;
    } // resize matrix


    matrix._size = size.slice(0); // copy the array

    matrix._data = (0, _array.resize)(matrix._data, matrix._size, defaultValue); // return matrix

    return matrix;
  }
  /**
   * Reshape the matrix to the given size. Returns a copy of the matrix when
   * `copy=true`, otherwise return the matrix itself (reshape in place).
   *
   * NOTE: This might be better suited to copy by default, instead of modifying
   *       in place. For now, it operates in place to remain consistent with
   *       resize().
   *
   * @memberof DenseMatrix
   * @param {number[]} size           The new size the matrix should have.
   * @param {boolean} [copy]          Return a reshaped copy of the matrix
   *
   * @return {Matrix}                 The reshaped matrix
   */


  DenseMatrix.prototype.reshape = function (size, copy) {
    var m = copy ? this.clone() : this;
    m._data = (0, _array.reshape)(m._data, size);
    m._size = size.slice(0);
    return m;
  };
  /**
   * Enlarge the matrix when it is smaller than given size.
   * If the matrix is larger or equal sized, nothing is done.
   * @memberof DenseMatrix
   * @param {DenseMatrix} matrix           The matrix to be resized
   * @param {number[]} size
   * @param {*} defaultValue          Default value, filled in on new entries.
   * @private
   */


  function _fit(matrix, size, defaultValue) {
    var // copy the array
    newSize = matrix._size.slice(0);

    var changed = false; // add dimensions when needed

    while (newSize.length < size.length) {
      newSize.push(0);
      changed = true;
    } // enlarge size when needed


    for (var i = 0, ii = size.length; i < ii; i++) {
      if (size[i] > newSize[i]) {
        newSize[i] = size[i];
        changed = true;
      }
    }

    if (changed) {
      // resize only when size is changed
      _resize(matrix, newSize, defaultValue);
    }
  }
  /**
   * Create a clone of the matrix
   * @memberof DenseMatrix
   * @return {DenseMatrix} clone
   */


  DenseMatrix.prototype.clone = function () {
    var m = new DenseMatrix({
      data: (0, _object.clone)(this._data),
      size: (0, _object.clone)(this._size),
      datatype: this._datatype
    });
    return m;
  };
  /**
   * Retrieve the size of the matrix.
   * @memberof DenseMatrix
   * @returns {number[]} size
   */


  DenseMatrix.prototype.size = function () {
    return this._size.slice(0); // return a clone of _size
  };
  /**
   * Create a new matrix with the results of the callback function executed on
   * each entry of the matrix.
   * @memberof DenseMatrix
   * @param {Function} callback   The callback function is invoked with three
   *                              parameters: the value of the element, the index
   *                              of the element, and the Matrix being traversed.
   *
   * @return {DenseMatrix} matrix
   */


  DenseMatrix.prototype.map = function (callback) {
    // matrix instance
    var me = this;

    var recurse = function recurse(value, index) {
      if ((0, _is.isArray)(value)) {
        return value.map(function (child, i) {
          return recurse(child, index.concat(i));
        });
      } else {
        return callback(value, index, me);
      }
    }; // determine the new datatype when the original matrix has datatype defined
    // TODO: should be done in matrix constructor instead


    var data = recurse(this._data, []);
    var datatype = this._datatype !== undefined ? (0, _array.getArrayDataType)(data, _is.typeOf) : undefined;
    return new DenseMatrix(data, datatype);
  };
  /**
   * Execute a callback function on each entry of the matrix.
   * @memberof DenseMatrix
   * @param {Function} callback   The callback function is invoked with three
   *                              parameters: the value of the element, the index
   *                              of the element, and the Matrix being traversed.
   */


  DenseMatrix.prototype.forEach = function (callback) {
    // matrix instance
    var me = this;

    var recurse = function recurse(value, index) {
      if ((0, _is.isArray)(value)) {
        value.forEach(function (child, i) {
          recurse(child, index.concat(i));
        });
      } else {
        callback(value, index, me);
      }
    };

    recurse(this._data, []);
  };
  /**
   * Create an Array with a copy of the data of the DenseMatrix
   * @memberof DenseMatrix
   * @returns {Array} array
   */


  DenseMatrix.prototype.toArray = function () {
    return (0, _object.clone)(this._data);
  };
  /**
   * Get the primitive value of the DenseMatrix: a multidimensional array
   * @memberof DenseMatrix
   * @returns {Array} array
   */


  DenseMatrix.prototype.valueOf = function () {
    return this._data;
  };
  /**
   * Get a string representation of the matrix, with optional formatting options.
   * @memberof DenseMatrix
   * @param {Object | number | Function} [options]  Formatting options. See
   *                                                lib/utils/number:format for a
   *                                                description of the available
   *                                                options.
   * @returns {string} str
   */


  DenseMatrix.prototype.format = function (options) {
    return (0, _string.format)(this._data, options);
  };
  /**
   * Get a string representation of the matrix
   * @memberof DenseMatrix
   * @returns {string} str
   */


  DenseMatrix.prototype.toString = function () {
    return (0, _string.format)(this._data);
  };
  /**
   * Get a JSON representation of the matrix
   * @memberof DenseMatrix
   * @returns {Object}
   */


  DenseMatrix.prototype.toJSON = function () {
    return {
      mathjs: 'DenseMatrix',
      data: this._data,
      size: this._size,
      datatype: this._datatype
    };
  };
  /**
   * Get the kth Matrix diagonal.
   *
   * @memberof DenseMatrix
   * @param {number | BigNumber} [k=0]     The kth diagonal where the vector will retrieved.
   *
   * @returns {Matrix}                     The matrix with the diagonal values.
   */


  DenseMatrix.prototype.diagonal = function (k) {
    // validate k if any
    if (k) {
      // convert BigNumber to a number
      if ((0, _is.isBigNumber)(k)) {
        k = k.toNumber();
      } // is must be an integer


      if (!(0, _is.isNumber)(k) || !(0, _number.isInteger)(k)) {
        throw new TypeError('The parameter k must be an integer number');
      }
    } else {
      // default value
      k = 0;
    }

    var kSuper = k > 0 ? k : 0;
    var kSub = k < 0 ? -k : 0; // rows & columns

    var rows = this._size[0];
    var columns = this._size[1]; // number diagonal values

    var n = Math.min(rows - kSub, columns - kSuper); // x is a matrix get diagonal from matrix

    var data = []; // loop rows

    for (var i = 0; i < n; i++) {
      data[i] = this._data[i + kSub][i + kSuper];
    } // create DenseMatrix


    return new DenseMatrix({
      data: data,
      size: [n],
      datatype: this._datatype
    });
  };
  /**
   * Create a diagonal matrix.
   *
   * @memberof DenseMatrix
   * @param {Array} size                     The matrix size.
   * @param {number | Matrix | Array } value The values for the diagonal.
   * @param {number | BigNumber} [k=0]       The kth diagonal where the vector will be filled in.
   * @param {number} [defaultValue]          The default value for non-diagonal
   * @param {string} [datatype]              The datatype for the diagonal
   *
   * @returns {DenseMatrix}
   */


  DenseMatrix.diagonal = function (size, value, k, defaultValue) {
    if (!(0, _is.isArray)(size)) {
      throw new TypeError('Array expected, size parameter');
    }

    if (size.length !== 2) {
      throw new Error('Only two dimensions matrix are supported');
    } // map size & validate


    size = size.map(function (s) {
      // check it is a big number
      if ((0, _is.isBigNumber)(s)) {
        // convert it
        s = s.toNumber();
      } // validate arguments


      if (!(0, _is.isNumber)(s) || !(0, _number.isInteger)(s) || s < 1) {
        throw new Error('Size values must be positive integers');
      }

      return s;
    }); // validate k if any

    if (k) {
      // convert BigNumber to a number
      if ((0, _is.isBigNumber)(k)) {
        k = k.toNumber();
      } // is must be an integer


      if (!(0, _is.isNumber)(k) || !(0, _number.isInteger)(k)) {
        throw new TypeError('The parameter k must be an integer number');
      }
    } else {
      // default value
      k = 0;
    }

    var kSuper = k > 0 ? k : 0;
    var kSub = k < 0 ? -k : 0; // rows and columns

    var rows = size[0];
    var columns = size[1]; // number of non-zero items

    var n = Math.min(rows - kSub, columns - kSuper); // value extraction function

    var _value; // check value


    if ((0, _is.isArray)(value)) {
      // validate array
      if (value.length !== n) {
        // number of values in array must be n
        throw new Error('Invalid value array length');
      } // define function


      _value = function _value(i) {
        // return value @ i
        return value[i];
      };
    } else if ((0, _is.isMatrix)(value)) {
      // matrix size
      var ms = value.size(); // validate matrix

      if (ms.length !== 1 || ms[0] !== n) {
        // number of values in array must be n
        throw new Error('Invalid matrix length');
      } // define function


      _value = function _value(i) {
        // return value @ i
        return value.get([i]);
      };
    } else {
      // define function
      _value = function _value() {
        // return value
        return value;
      };
    } // discover default value if needed


    if (!defaultValue) {
      // check first value in array
      defaultValue = (0, _is.isBigNumber)(_value(0)) ? _value(0).mul(0) // trick to create a BigNumber with value zero
      : 0;
    } // empty array


    var data = []; // check we need to resize array

    if (size.length > 0) {
      // resize array
      data = (0, _array.resize)(data, size, defaultValue); // fill diagonal

      for (var d = 0; d < n; d++) {
        data[d + kSub][d + kSuper] = _value(d);
      }
    } // create DenseMatrix


    return new DenseMatrix({
      data: data,
      size: [rows, columns]
    });
  };
  /**
   * Generate a matrix from a JSON object
   * @memberof DenseMatrix
   * @param {Object} json  An object structured like
   *                       `{"mathjs": "DenseMatrix", data: [], size: []}`,
   *                       where mathjs is optional
   * @returns {DenseMatrix}
   */


  DenseMatrix.fromJSON = function (json) {
    return new DenseMatrix(json);
  };
  /**
   * Swap rows i and j in Matrix.
   *
   * @memberof DenseMatrix
   * @param {number} i       Matrix row index 1
   * @param {number} j       Matrix row index 2
   *
   * @return {Matrix}        The matrix reference
   */


  DenseMatrix.prototype.swapRows = function (i, j) {
    // check index
    if (!(0, _is.isNumber)(i) || !(0, _number.isInteger)(i) || !(0, _is.isNumber)(j) || !(0, _number.isInteger)(j)) {
      throw new Error('Row index must be positive integers');
    } // check dimensions


    if (this._size.length !== 2) {
      throw new Error('Only two dimensional matrix is supported');
    } // validate index


    (0, _array.validateIndex)(i, this._size[0]);
    (0, _array.validateIndex)(j, this._size[0]); // swap rows

    DenseMatrix._swapRows(i, j, this._data); // return current instance


    return this;
  };
  /**
   * Swap rows i and j in Dense Matrix data structure.
   *
   * @param {number} i       Matrix row index 1
   * @param {number} j       Matrix row index 2
   * @param {Array} data     Matrix data
   */


  DenseMatrix._swapRows = function (i, j, data) {
    // swap values i <-> j
    var vi = data[i];
    data[i] = data[j];
    data[j] = vi;
  };
  /**
   * Preprocess data, which can be an Array or DenseMatrix with nested Arrays and
   * Matrices. Replaces all nested Matrices with Arrays
   * @memberof DenseMatrix
   * @param {Array} data
   * @return {Array} data
   */


  function preprocess(data) {
    for (var i = 0, ii = data.length; i < ii; i++) {
      var elem = data[i];

      if ((0, _is.isArray)(elem)) {
        data[i] = preprocess(elem);
      } else if (elem && elem.isMatrix === true) {
        data[i] = preprocess(elem.valueOf());
      }
    }

    return data;
  }

  return DenseMatrix;
}, {
  isClass: true
});
exports.createDenseMatrixClass = createDenseMatrixClass;