chainy/node_modules/markov-chains/dist/markov-chains.js

'use strict';

Object.defineProperty(exports, "__esModule", {
  value: true
});

var _slicedToArray = function () { function sliceIterator(arr, i) { var _arr = []; var _n = true; var _d = false; var _e = undefined; try { for (var _i = arr[Symbol.iterator](), _s; !(_n = (_s = _i.next()).done); _n = true) { _arr.push(_s.value); if (i && _arr.length === i) break; } } catch (err) { _d = true; _e = err; } finally { try { if (!_n && _i["return"]) _i["return"](); } finally { if (_d) throw _e; } } return _arr; } return function (arr, i) { if (Array.isArray(arr)) { return arr; } else if (Symbol.iterator in Object(arr)) { return sliceIterator(arr, i); } else { throw new TypeError("Invalid attempt to destructure non-iterable instance"); } }; }();

var _createClass = function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ("value" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; }();

var _javascriptStringify = require('javascript-stringify');

var _javascriptStringify2 = _interopRequireDefault(_javascriptStringify);

function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; }

function _toConsumableArray(arr) { if (Array.isArray(arr)) { for (var i = 0, arr2 = Array(arr.length); i < arr.length; i++) { arr2[i] = arr[i]; } return arr2; } else { return Array.from(arr); } }

function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } }

/**
 * Constants used to pad states from the beginning and end of a corpus
 */
var BEGIN = '@@MARKOV_CHAIN_BEGIN';
var END = '@@MARKOV_CHAIN_END';

/**
 * The default state size
 */
var DEFAULT_STATE_SIZE = 1;

// ============================================================================

/**
 * A Markov chain representing processes that have both beginnings and ends.
 * For example: Sentences.
 */

var Chain = function () {
  function Chain(corpusOrModel) {
    var _ref = arguments.length <= 1 || arguments[1] === undefined ? {} : arguments[1];

    var _ref$stateSize = _ref.stateSize;
    var stateSize = _ref$stateSize === undefined ? DEFAULT_STATE_SIZE : _ref$stateSize;

    _classCallCheck(this, Chain);

    this.stateSize = stateSize;

    if (corpusOrModel instanceof Map) {
      this.model = corpusOrModel;
    } else {
      this.model = Chain.build(corpusOrModel, { stateSize: stateSize });
    }
  }

  /**
   * Creates a Map of Maps where the keys of the outer Map represent all
   * possible states, and point to the inner Map. The inner Maps represent all
   * possibilities for the 'next' item in the chain, along with the count of
   * times it appears.
   */


  _createClass(Chain, [{
    key: 'toJSON',


    /**
     * Converts the model to a 2D array, which can then be serialized by
     * JSON.stringify
     */
    value: function toJSON() {
      var serialized = [];

      var _iteratorNormalCompletion = true;
      var _didIteratorError = false;
      var _iteratorError = undefined;

      try {
        for (var _iterator = this.model[Symbol.iterator](), _step; !(_iteratorNormalCompletion = (_step = _iterator.next()).done); _iteratorNormalCompletion = true) {
          var _step$value = _slicedToArray(_step.value, 2);

          var state = _step$value[0];
          var follow = _step$value[1];

          serialized.push([state, [].concat(_toConsumableArray(follow))]);
        }
      } catch (err) {
        _didIteratorError = true;
        _iteratorError = err;
      } finally {
        try {
          if (!_iteratorNormalCompletion && _iterator.return) {
            _iterator.return();
          }
        } finally {
          if (_didIteratorError) {
            throw _iteratorError;
          }
        }
      }

      return serialized;
    }

    /**
     * Given a state, chooses the next item at random, with a bias towards next
     * states with higher weights
     */

  }, {
    key: 'move',
    value: function move(fromState) {
      var stateKey = createStateKey(fromState);
      var state = this.model.get(stateKey);

      if (!state) {
        return undefined;
      }

      var choices = [];
      var weights = [];

      state.forEach(function (follow) {
        choices.push(follow.value);
        weights.push(follow.count);
      });

      var cumulativeDistribution = weights.reduce(function (cumWeights, currWeight) {
        var sum = last(cumWeights) || 0;
        return [].concat(_toConsumableArray(cumWeights), [sum + currWeight]);
      }, []);

      var r = Math.random() * last(cumulativeDistribution);
      var randomIndex = bisect(cumulativeDistribution, r);

      var nextMove = choices[randomIndex];

      return nextMove;
    }

    /**
     * Generates successive items until the chain reaches the END state
     */

  }, {
    key: 'generate',
    value: function* generate() {
      var beginState = arguments.length <= 0 || arguments[0] === undefined ? createBeginState(this.stateSize) : arguments[0];

      var state = beginState;

      for (;;) {
        var step = this.move(state);

        if (step === undefined || step === END) {
          break;
        } else {
          yield step;
          state = [].concat(_toConsumableArray(state.slice(1)), [step]);
        }
      }
    }

    /**
     * Performs a single run of the Markov model, optionally starting from the
     * provided `beginState`
     */

  }, {
    key: 'walk',
    value: function walk(beginState) {
      var steps = [];

      var _iteratorNormalCompletion2 = true;
      var _didIteratorError2 = false;
      var _iteratorError2 = undefined;

      try {
        for (var _iterator2 = this.generate(beginState)[Symbol.iterator](), _step2; !(_iteratorNormalCompletion2 = (_step2 = _iterator2.next()).done); _iteratorNormalCompletion2 = true) {
          var step = _step2.value;

          steps.push(step);
        }
      } catch (err) {
        _didIteratorError2 = true;
        _iteratorError2 = err;
      } finally {
        try {
          if (!_iteratorNormalCompletion2 && _iterator2.return) {
            _iterator2.return();
          }
        } finally {
          if (_didIteratorError2) {
            throw _iteratorError2;
          }
        }
      }

      return steps;
    }
  }], [{
    key: 'build',
    value: function build(corpus) {
      var _ref2 = arguments.length <= 1 || arguments[1] === undefined ? {} : arguments[1];

      var _ref2$stateSize = _ref2.stateSize;
      var stateSize = _ref2$stateSize === undefined ? DEFAULT_STATE_SIZE : _ref2$stateSize;

      if (!Array.isArray(corpus)) {
        throw new Error('Corpus must be a List or an Array');
      }

      var model = new Map();

      corpus.forEach(function (run) {
        if (!Array.isArray(run)) {
          throw new Error('Invalid run in corpus: Must be an array');
        }

        var paddedRun = [].concat(_toConsumableArray(createBeginState(stateSize)), _toConsumableArray(run), [END]);

        // add one to original run size to account for END state
        for (var ngramStart = 0; ngramStart < run.length + 1; ngramStart++) {
          var ngramEnd = ngramStart + stateSize;

          var stateKey = createStateKey(paddedRun.slice(ngramStart, ngramEnd));
          var follow = paddedRun[ngramEnd];
          var followKey = (0, _javascriptStringify2.default)(follow);

          if (!model.has(stateKey)) {
            model.set(stateKey, new Map());
          }

          var stateMap = model.get(stateKey);

          if (!stateMap.has(followKey)) {
            stateMap.set(followKey, { value: follow, count: 0 });
          }

          var followMap = stateMap.get(followKey);
          followMap.count += 1;
        }
      });

      return model;
    }

    /**
     * Creates a Chain instance by hydrating the model from a JSON string
     */

  }, {
    key: 'fromJSON',
    value: function fromJSON(jsonData) {
      var getStateSize = function getStateSize(stateKey) {
        return JSON.parse(stateKey).length;
      };

      var stateSize = void 0;

      var states = JSON.parse(jsonData).map(function (_ref3) {
        var _ref4 = _slicedToArray(_ref3, 2);

        var stateKey = _ref4[0];
        var follow = _ref4[1];

        var currentStateSize = getStateSize(stateKey);

        // Ensure that each state in the chain has a consistent size
        if (!stateSize) {
          stateSize = currentStateSize;
        } else if (currentStateSize !== stateSize) {
          throw new Error('Inconsistent state size. ' + ('Expected ' + stateSize + ' but got ' + currentStateSize + ' (' + stateKey + ').'));
        }

        var followMap = new Map();

        // Clone the `followData` object so that the garbage collector doesn't
        // keep the temporary hydrated states array laying around because the new
        // chain references objects it contains.
        var _iteratorNormalCompletion3 = true;
        var _didIteratorError3 = false;
        var _iteratorError3 = undefined;

        try {
          for (var _iterator3 = follow[Symbol.iterator](), _step3; !(_iteratorNormalCompletion3 = (_step3 = _iterator3.next()).done); _iteratorNormalCompletion3 = true) {
            var _step3$value = _slicedToArray(_step3.value, 2);

            var followKey = _step3$value[0];
            var followData = _step3$value[1];

            followMap.set(followKey, Object.assign({}, followData));
          }
        } catch (err) {
          _didIteratorError3 = true;
          _iteratorError3 = err;
        } finally {
          try {
            if (!_iteratorNormalCompletion3 && _iterator3.return) {
              _iterator3.return();
            }
          } finally {
            if (_didIteratorError3) {
              throw _iteratorError3;
            }
          }
        }

        return [stateKey, followMap];
      });

      return new Chain(new Map(states), { stateSize: stateSize });
    }
  }]);

  return Chain;
}();

// ============================================================================

/**
 * Creates a state that can be used to look up transitions in the model
 */


exports.default = Chain;
function createStateKey(fromState) {
  // When the `stateSize` is one, it can seem a bit silly to have to pass in an
  // array with a single item. To make things simpler to use, we therefore
  // convert any single, non-array argument to arrays.
  var state = Array.isArray(fromState) ? fromState : [fromState];

  // Using `JSON.stringify` here allows us to programmatically determine the
  // original `stateSize` when we restore a chain from JSON. If we were to use
  // `serialize`, the stateKey array would be surrounded by single quotes, and
  // would therefore need to be parsed by `eval` in order to determine the
  // original state size. Using JSON.parse is a lot safer than using `eval`.
  return JSON.stringify(state.map(_javascriptStringify2.default));
}

/**
 * Creates inital `BEGIN` states to use for padding at the beginning of runs
 */
function createBeginState(stateSize) {
  var beginStates = new Array(stateSize);

  for (var i = 0; i < stateSize; i++) {
    beginStates[i] = BEGIN;
  }

  return beginStates;
}

/**
 * Gets the last item in an array
 */
function last(arr) {
  return arr[arr.length - 1];
}

/**
 * A port of Python's `bisect.bisect_right`, similar to lodash's `sortedIndex`
 */
function bisect(list, num) {
  var high = arguments.length <= 2 || arguments[2] === undefined ? list.length : arguments[2];

  var currLow = 0;
  var currHigh = high;

  while (currLow < currHigh) {
    var mid = Math.floor((currLow + currHigh) / 2);
    if (num < list[mid]) {
      currHigh = mid;
    } else {
      currLow = mid + 1;
    }
  }

  return currLow;
}