mathjs/lib/function/logical/xor.js

Math.js is an extensive math library for JavaScript and Node.js. It features a flexible expression parser with support for symbolic computation, comes with a large set of built-in functions and constants, and offers an integrated solution to work with dif

'use strict';

function factory(type, config, load, typed) {
  var latex = require('../../utils/latex');

  var matrix = load(require('../../type/matrix/function/matrix'));
  var algorithm03 = load(require('../../type/matrix/utils/algorithm03'));
  var algorithm07 = load(require('../../type/matrix/utils/algorithm07'));
  var algorithm12 = load(require('../../type/matrix/utils/algorithm12'));
  var algorithm13 = load(require('../../type/matrix/utils/algorithm13'));
  var algorithm14 = load(require('../../type/matrix/utils/algorithm14'));
  /**
   * Logical `xor`. Test whether one and only one value is defined with a nonzero/nonempty value.
   * For matrices, the function is evaluated element wise.
   *
   * Syntax:
   *
   *    math.xor(x, y)
   *
   * Examples:
   *
   *    math.xor(2, 4)   // returns false
   *
   *    a = [2, 0, 0]
   *    b = [2, 7, 0]
   *    c = 0
   *
   *    math.xor(a, b)   // returns [false, true, false]
   *    math.xor(a, c)   // returns [true, false, false]
   *
   * See also:
   *
   *    and, not, or
   *
   * @param  {number | BigNumber | Complex | Unit | Array | Matrix} x First value to check
   * @param  {number | BigNumber | Complex | Unit | Array | Matrix} y Second value to check
   * @return {boolean | Array | Matrix}
   *            Returns true when one and only one input is defined with a nonzero/nonempty value.
   */

  var xor = typed('xor', {
    'number, number': function numberNumber(x, y) {
      return !!x !== !!y;
    },
    'Complex, Complex': function ComplexComplex(x, y) {
      return (x.re !== 0 || x.im !== 0) !== (y.re !== 0 || y.im !== 0);
    },
    'BigNumber, BigNumber': function BigNumberBigNumber(x, y) {
      return (!x.isZero() && !x.isNaN()) !== (!y.isZero() && !y.isNaN());
    },
    'Unit, Unit': function UnitUnit(x, y) {
      return xor(x.value || 0, y.value || 0);
    },
    'SparseMatrix, SparseMatrix': function SparseMatrixSparseMatrix(x, y) {
      return algorithm07(x, y, xor);
    },
    'SparseMatrix, DenseMatrix': function SparseMatrixDenseMatrix(x, y) {
      return algorithm03(y, x, xor, true);
    },
    'DenseMatrix, SparseMatrix': function DenseMatrixSparseMatrix(x, y) {
      return algorithm03(x, y, xor, false);
    },
    'DenseMatrix, DenseMatrix': function DenseMatrixDenseMatrix(x, y) {
      return algorithm13(x, y, xor);
    },
    'Array, Array': function ArrayArray(x, y) {
      // use matrix implementation
      return xor(matrix(x), matrix(y)).valueOf();
    },
    'Array, Matrix': function ArrayMatrix(x, y) {
      // use matrix implementation
      return xor(matrix(x), y);
    },
    'Matrix, Array': function MatrixArray(x, y) {
      // use matrix implementation
      return xor(x, matrix(y));
    },
    'SparseMatrix, any': function SparseMatrixAny(x, y) {
      return algorithm12(x, y, xor, false);
    },
    'DenseMatrix, any': function DenseMatrixAny(x, y) {
      return algorithm14(x, y, xor, false);
    },
    'any, SparseMatrix': function anySparseMatrix(x, y) {
      return algorithm12(y, x, xor, true);
    },
    'any, DenseMatrix': function anyDenseMatrix(x, y) {
      return algorithm14(y, x, xor, true);
    },
    'Array, any': function ArrayAny(x, y) {
      // use matrix implementation
      return algorithm14(matrix(x), y, xor, false).valueOf();
    },
    'any, Array': function anyArray(x, y) {
      // use matrix implementation
      return algorithm14(matrix(y), x, xor, true).valueOf();
    }
  });
  xor.toTex = {
    2: "\\left(${args[0]}".concat(latex.operators['xor'], "${args[1]}\\right)")
  };
  return xor;
}

exports.name = 'xor';
exports.factory = factory;