markdown-flow-ui
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A React UI library for rendering markdown with interactive flow components, typewriter effects, and plugin support
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{"version":3,"file":"layout-VtjyAaGP.mjs","sources":["../node_modules/lodash-es/_flatRest.js","../node_modules/lodash-es/cloneDeep.js","../node_modules/lodash-es/forIn.js","../node_modules/lodash-es/forOwn.js","../node_modules/lodash-es/_baseGt.js","../node_modules/lodash-es/mapValues.js","../node_modules/lodash-es/max.js","../node_modules/lodash-es/minBy.js","../node_modules/lodash-es/_baseSortBy.js","../node_modules/lodash-es/_compareAscending.js","../node_modules/lodash-es/_compareMultiple.js","../node_modules/lodash-es/_baseOrderBy.js","../node_modules/lodash-es/_basePick.js","../node_modules/lodash-es/pick.js","../node_modules/lodash-es/_baseRange.js","../node_modules/lodash-es/_createRange.js","../node_modules/lodash-es/range.js","../node_modules/lodash-es/sortBy.js","../node_modules/lodash-es/uniqueId.js","../node_modules/lodash-es/_baseZipObject.js","../node_modules/lodash-es/zipObject.js","../node_modules/dagre-d3-es/src/dagre/data/list.js","../node_modules/dagre-d3-es/src/dagre/greedy-fas.js","../node_modules/dagre-d3-es/src/dagre/acyclic.js","../node_modules/dagre-d3-es/src/dagre/util.js","../node_modules/dagre-d3-es/src/dagre/add-border-segments.js","../node_modules/dagre-d3-es/src/dagre/coordinate-system.js","../node_modules/dagre-d3-es/src/dagre/normalize.js","../node_modules/dagre-d3-es/src/dagre/rank/util.js","../node_modules/dagre-d3-es/src/dagre/rank/feasible-tree.js","../node_modules/dagre-d3-es/src/graphlib/alg/topsort.js","../node_modules/dagre-d3-es/src/graphlib/alg/dfs.js","../node_modules/dagre-d3-es/src/graphlib/alg/postorder.js","../node_modules/dagre-d3-es/src/graphlib/alg/preorder.js","../node_modules/dagre-d3-es/src/dagre/rank/network-simplex.js","../node_modules/dagre-d3-es/src/dagre/rank/index.js","../node_modules/dagre-d3-es/src/dagre/nesting-graph.js","../node_modules/dagre-d3-es/src/dagre/order/add-subgraph-constraints.js","../node_modules/dagre-d3-es/src/dagre/order/build-layer-graph.js","../node_modules/dagre-d3-es/src/dagre/order/cross-count.js","../node_modules/dagre-d3-es/src/dagre/order/init-order.js","../node_modules/dagre-d3-es/src/dagre/order/barycenter.js","../node_modules/dagre-d3-es/src/dagre/order/resolve-conflicts.js","../node_modules/dagre-d3-es/src/dagre/order/sort.js","../node_modules/dagre-d3-es/src/dagre/order/sort-subgraph.js","../node_modules/dagre-d3-es/src/dagre/order/index.js","../node_modules/dagre-d3-es/src/dagre/parent-dummy-chains.js","../node_modules/dagre-d3-es/src/dagre/position/bk.js","../node_modules/dagre-d3-es/src/dagre/position/index.js","../node_modules/dagre-d3-es/src/dagre/layout.js"],"sourcesContent":["import flatten from './flatten.js';\nimport overRest from './_overRest.js';\nimport setToString from './_setToString.js';\n\n/**\n * A specialized version of `baseRest` which flattens the rest array.\n *\n * @private\n * @param {Function} func The function to apply a rest parameter to.\n * @returns {Function} Returns the new function.\n */\nfunction flatRest(func) {\n return setToString(overRest(func, undefined, flatten), func + '');\n}\n\nexport default flatRest;\n","import baseClone from './_baseClone.js';\n\n/** Used to compose bitmasks for cloning. */\nvar CLONE_DEEP_FLAG = 1,\n CLONE_SYMBOLS_FLAG = 4;\n\n/**\n * This method is like `_.clone` except that it recursively clones `value`.\n *\n * @static\n * @memberOf _\n * @since 1.0.0\n * @category Lang\n * @param {*} value The value to recursively clone.\n * @returns {*} Returns the deep cloned value.\n * @see _.clone\n * @example\n *\n * var objects = [{ 'a': 1 }, { 'b': 2 }];\n *\n * var deep = _.cloneDeep(objects);\n * console.log(deep[0] === objects[0]);\n * // => false\n */\nfunction cloneDeep(value) {\n return baseClone(value, CLONE_DEEP_FLAG | CLONE_SYMBOLS_FLAG);\n}\n\nexport default cloneDeep;\n","import baseFor from './_baseFor.js';\nimport castFunction from './_castFunction.js';\nimport keysIn from './keysIn.js';\n\n/**\n * Iterates over own and inherited enumerable string keyed properties of an\n * object and invokes `iteratee` for each property. The iteratee is invoked\n * with three arguments: (value, key, object). Iteratee functions may exit\n * iteration early by explicitly returning `false`.\n *\n * @static\n * @memberOf _\n * @since 0.3.0\n * @category Object\n * @param {Object} object The object to iterate over.\n * @param {Function} [iteratee=_.identity] The function invoked per iteration.\n * @returns {Object} Returns `object`.\n * @see _.forInRight\n * @example\n *\n * function Foo() {\n * this.a = 1;\n * this.b = 2;\n * }\n *\n * Foo.prototype.c = 3;\n *\n * _.forIn(new Foo, function(value, key) {\n * console.log(key);\n * });\n * // => Logs 'a', 'b', then 'c' (iteration order is not guaranteed).\n */\nfunction forIn(object, iteratee) {\n return object == null\n ? object\n : baseFor(object, castFunction(iteratee), keysIn);\n}\n\nexport default forIn;\n","import baseForOwn from './_baseForOwn.js';\nimport castFunction from './_castFunction.js';\n\n/**\n * Iterates over own enumerable string keyed properties of an object and\n * invokes `iteratee` for each property. The iteratee is invoked with three\n * arguments: (value, key, object). Iteratee functions may exit iteration\n * early by explicitly returning `false`.\n *\n * @static\n * @memberOf _\n * @since 0.3.0\n * @category Object\n * @param {Object} object The object to iterate over.\n * @param {Function} [iteratee=_.identity] The function invoked per iteration.\n * @returns {Object} Returns `object`.\n * @see _.forOwnRight\n * @example\n *\n * function Foo() {\n * this.a = 1;\n * this.b = 2;\n * }\n *\n * Foo.prototype.c = 3;\n *\n * _.forOwn(new Foo, function(value, key) {\n * console.log(key);\n * });\n * // => Logs 'a' then 'b' (iteration order is not guaranteed).\n */\nfunction forOwn(object, iteratee) {\n return object && baseForOwn(object, castFunction(iteratee));\n}\n\nexport default forOwn;\n","/**\n * The base implementation of `_.gt` which doesn't coerce arguments.\n *\n * @private\n * @param {*} value The value to compare.\n * @param {*} other The other value to compare.\n * @returns {boolean} Returns `true` if `value` is greater than `other`,\n * else `false`.\n */\nfunction baseGt(value, other) {\n return value > other;\n}\n\nexport default baseGt;\n","import baseAssignValue from './_baseAssignValue.js';\nimport baseForOwn from './_baseForOwn.js';\nimport baseIteratee from './_baseIteratee.js';\n\n/**\n * Creates an object with the same keys as `object` and values generated\n * by running each own enumerable string keyed property of `object` thru\n * `iteratee`. The iteratee is invoked with three arguments:\n * (value, key, object).\n *\n * @static\n * @memberOf _\n * @since 2.4.0\n * @category Object\n * @param {Object} object The object to iterate over.\n * @param {Function} [iteratee=_.identity] The function invoked per iteration.\n * @returns {Object} Returns the new mapped object.\n * @see _.mapKeys\n * @example\n *\n * var users = {\n * 'fred': { 'user': 'fred', 'age': 40 },\n * 'pebbles': { 'user': 'pebbles', 'age': 1 }\n * };\n *\n * _.mapValues(users, function(o) { return o.age; });\n * // => { 'fred': 40, 'pebbles': 1 } (iteration order is not guaranteed)\n *\n * // The `_.property` iteratee shorthand.\n * _.mapValues(users, 'age');\n * // => { 'fred': 40, 'pebbles': 1 } (iteration order is not guaranteed)\n */\nfunction mapValues(object, iteratee) {\n var result = {};\n iteratee = baseIteratee(iteratee, 3);\n\n baseForOwn(object, function(value, key, object) {\n baseAssignValue(result, key, iteratee(value, key, object));\n });\n return result;\n}\n\nexport default mapValues;\n","import baseExtremum from './_baseExtremum.js';\nimport baseGt from './_baseGt.js';\nimport identity from './identity.js';\n\n/**\n * Computes the maximum value of `array`. If `array` is empty or falsey,\n * `undefined` is returned.\n *\n * @static\n * @since 0.1.0\n * @memberOf _\n * @category Math\n * @param {Array} array The array to iterate over.\n * @returns {*} Returns the maximum value.\n * @example\n *\n * _.max([4, 2, 8, 6]);\n * // => 8\n *\n * _.max([]);\n * // => undefined\n */\nfunction max(array) {\n return (array && array.length)\n ? baseExtremum(array, identity, baseGt)\n : undefined;\n}\n\nexport default max;\n","import baseExtremum from './_baseExtremum.js';\nimport baseIteratee from './_baseIteratee.js';\nimport baseLt from './_baseLt.js';\n\n/**\n * This method is like `_.min` except that it accepts `iteratee` which is\n * invoked for each element in `array` to generate the criterion by which\n * the value is ranked. The iteratee is invoked with one argument: (value).\n *\n * @static\n * @memberOf _\n * @since 4.0.0\n * @category Math\n * @param {Array} array The array to iterate over.\n * @param {Function} [iteratee=_.identity] The iteratee invoked per element.\n * @returns {*} Returns the minimum value.\n * @example\n *\n * var objects = [{ 'n': 1 }, { 'n': 2 }];\n *\n * _.minBy(objects, function(o) { return o.n; });\n * // => { 'n': 1 }\n *\n * // The `_.property` iteratee shorthand.\n * _.minBy(objects, 'n');\n * // => { 'n': 1 }\n */\nfunction minBy(array, iteratee) {\n return (array && array.length)\n ? baseExtremum(array, baseIteratee(iteratee, 2), baseLt)\n : undefined;\n}\n\nexport default minBy;\n","/**\n * The base implementation of `_.sortBy` which uses `comparer` to define the\n * sort order of `array` and replaces criteria objects with their corresponding\n * values.\n *\n * @private\n * @param {Array} array The array to sort.\n * @param {Function} comparer The function to define sort order.\n * @returns {Array} Returns `array`.\n */\nfunction baseSortBy(array, comparer) {\n var length = array.length;\n\n array.sort(comparer);\n while (length--) {\n array[length] = array[length].value;\n }\n return array;\n}\n\nexport default baseSortBy;\n","import isSymbol from './isSymbol.js';\n\n/**\n * Compares values to sort them in ascending order.\n *\n * @private\n * @param {*} value The value to compare.\n * @param {*} other The other value to compare.\n * @returns {number} Returns the sort order indicator for `value`.\n */\nfunction compareAscending(value, other) {\n if (value !== other) {\n var valIsDefined = value !== undefined,\n valIsNull = value === null,\n valIsReflexive = value === value,\n valIsSymbol = isSymbol(value);\n\n var othIsDefined = other !== undefined,\n othIsNull = other === null,\n othIsReflexive = other === other,\n othIsSymbol = isSymbol(other);\n\n if ((!othIsNull && !othIsSymbol && !valIsSymbol && value > other) ||\n (valIsSymbol && othIsDefined && othIsReflexive && !othIsNull && !othIsSymbol) ||\n (valIsNull && othIsDefined && othIsReflexive) ||\n (!valIsDefined && othIsReflexive) ||\n !valIsReflexive) {\n return 1;\n }\n if ((!valIsNull && !valIsSymbol && !othIsSymbol && value < other) ||\n (othIsSymbol && valIsDefined && valIsReflexive && !valIsNull && !valIsSymbol) ||\n (othIsNull && valIsDefined && valIsReflexive) ||\n (!othIsDefined && valIsReflexive) ||\n !othIsReflexive) {\n return -1;\n }\n }\n return 0;\n}\n\nexport default compareAscending;\n","import compareAscending from './_compareAscending.js';\n\n/**\n * Used by `_.orderBy` to compare multiple properties of a value to another\n * and stable sort them.\n *\n * If `orders` is unspecified, all values are sorted in ascending order. Otherwise,\n * specify an order of \"desc\" for descending or \"asc\" for ascending sort order\n * of corresponding values.\n *\n * @private\n * @param {Object} object The object to compare.\n * @param {Object} other The other object to compare.\n * @param {boolean[]|string[]} orders The order to sort by for each property.\n * @returns {number} Returns the sort order indicator for `object`.\n */\nfunction compareMultiple(object, other, orders) {\n var index = -1,\n objCriteria = object.criteria,\n othCriteria = other.criteria,\n length = objCriteria.length,\n ordersLength = orders.length;\n\n while (++index < length) {\n var result = compareAscending(objCriteria[index], othCriteria[index]);\n if (result) {\n if (index >= ordersLength) {\n return result;\n }\n var order = orders[index];\n return result * (order == 'desc' ? -1 : 1);\n }\n }\n // Fixes an `Array#sort` bug in the JS engine embedded in Adobe applications\n // that causes it, under certain circumstances, to provide the same value for\n // `object` and `other`. See https://github.com/jashkenas/underscore/pull/1247\n // for more details.\n //\n // This also ensures a stable sort in V8 and other engines.\n // See https://bugs.chromium.org/p/v8/issues/detail?id=90 for more details.\n return object.index - other.index;\n}\n\nexport default compareMultiple;\n","import arrayMap from './_arrayMap.js';\nimport baseGet from './_baseGet.js';\nimport baseIteratee from './_baseIteratee.js';\nimport baseMap from './_baseMap.js';\nimport baseSortBy from './_baseSortBy.js';\nimport baseUnary from './_baseUnary.js';\nimport compareMultiple from './_compareMultiple.js';\nimport identity from './identity.js';\nimport isArray from './isArray.js';\n\n/**\n * The base implementation of `_.orderBy` without param guards.\n *\n * @private\n * @param {Array|Object} collection The collection to iterate over.\n * @param {Function[]|Object[]|string[]} iteratees The iteratees to sort by.\n * @param {string[]} orders The sort orders of `iteratees`.\n * @returns {Array} Returns the new sorted array.\n */\nfunction baseOrderBy(collection, iteratees, orders) {\n if (iteratees.length) {\n iteratees = arrayMap(iteratees, function(iteratee) {\n if (isArray(iteratee)) {\n return function(value) {\n return baseGet(value, iteratee.length === 1 ? iteratee[0] : iteratee);\n }\n }\n return iteratee;\n });\n } else {\n iteratees = [identity];\n }\n\n var index = -1;\n iteratees = arrayMap(iteratees, baseUnary(baseIteratee));\n\n var result = baseMap(collection, function(value, key, collection) {\n var criteria = arrayMap(iteratees, function(iteratee) {\n return iteratee(value);\n });\n return { 'criteria': criteria, 'index': ++index, 'value': value };\n });\n\n return baseSortBy(result, function(object, other) {\n return compareMultiple(object, other, orders);\n });\n}\n\nexport default baseOrderBy;\n","import basePickBy from './_basePickBy.js';\nimport hasIn from './hasIn.js';\n\n/**\n * The base implementation of `_.pick` without support for individual\n * property identifiers.\n *\n * @private\n * @param {Object} object The source object.\n * @param {string[]} paths The property paths to pick.\n * @returns {Object} Returns the new object.\n */\nfunction basePick(object, paths) {\n return basePickBy(object, paths, function(value, path) {\n return hasIn(object, path);\n });\n}\n\nexport default basePick;\n","import basePick from './_basePick.js';\nimport flatRest from './_flatRest.js';\n\n/**\n * Creates an object composed of the picked `object` properties.\n *\n * @static\n * @since 0.1.0\n * @memberOf _\n * @category Object\n * @param {Object} object The source object.\n * @param {...(string|string[])} [paths] The property paths to pick.\n * @returns {Object} Returns the new object.\n * @example\n *\n * var object = { 'a': 1, 'b': '2', 'c': 3 };\n *\n * _.pick(object, ['a', 'c']);\n * // => { 'a': 1, 'c': 3 }\n */\nvar pick = flatRest(function(object, paths) {\n return object == null ? {} : basePick(object, paths);\n});\n\nexport default pick;\n","/* Built-in method references for those with the same name as other `lodash` methods. */\nvar nativeCeil = Math.ceil,\n nativeMax = Math.max;\n\n/**\n * The base implementation of `_.range` and `_.rangeRight` which doesn't\n * coerce arguments.\n *\n * @private\n * @param {number} start The start of the range.\n * @param {number} end The end of the range.\n * @param {number} step The value to increment or decrement by.\n * @param {boolean} [fromRight] Specify iterating from right to left.\n * @returns {Array} Returns the range of numbers.\n */\nfunction baseRange(start, end, step, fromRight) {\n var index = -1,\n length = nativeMax(nativeCeil((end - start) / (step || 1)), 0),\n result = Array(length);\n\n while (length--) {\n result[fromRight ? length : ++index] = start;\n start += step;\n }\n return result;\n}\n\nexport default baseRange;\n","import baseRange from './_baseRange.js';\nimport isIterateeCall from './_isIterateeCall.js';\nimport toFinite from './toFinite.js';\n\n/**\n * Creates a `_.range` or `_.rangeRight` function.\n *\n * @private\n * @param {boolean} [fromRight] Specify iterating from right to left.\n * @returns {Function} Returns the new range function.\n */\nfunction createRange(fromRight) {\n return function(start, end, step) {\n if (step && typeof step != 'number' && isIterateeCall(start, end, step)) {\n end = step = undefined;\n }\n // Ensure the sign of `-0` is preserved.\n start = toFinite(start);\n if (end === undefined) {\n end = start;\n start = 0;\n } else {\n end = toFinite(end);\n }\n step = step === undefined ? (start < end ? 1 : -1) : toFinite(step);\n return baseRange(start, end, step, fromRight);\n };\n}\n\nexport default createRange;\n","import createRange from './_createRange.js';\n\n/**\n * Creates an array of numbers (positive and/or negative) progressing from\n * `start` up to, but not including, `end`. A step of `-1` is used if a negative\n * `start` is specified without an `end` or `step`. If `end` is not specified,\n * it's set to `start` with `start` then set to `0`.\n *\n * **Note:** JavaScript follows the IEEE-754 standard for resolving\n * floating-point values which can produce unexpected results.\n *\n * @static\n * @since 0.1.0\n * @memberOf _\n * @category Util\n * @param {number} [start=0] The start of the range.\n * @param {number} end The end of the range.\n * @param {number} [step=1] The value to increment or decrement by.\n * @returns {Array} Returns the range of numbers.\n * @see _.inRange, _.rangeRight\n * @example\n *\n * _.range(4);\n * // => [0, 1, 2, 3]\n *\n * _.range(-4);\n * // => [0, -1, -2, -3]\n *\n * _.range(1, 5);\n * // => [1, 2, 3, 4]\n *\n * _.range(0, 20, 5);\n * // => [0, 5, 10, 15]\n *\n * _.range(0, -4, -1);\n * // => [0, -1, -2, -3]\n *\n * _.range(1, 4, 0);\n * // => [1, 1, 1]\n *\n * _.range(0);\n * // => []\n */\nvar range = createRange();\n\nexport default range;\n","import baseFlatten from './_baseFlatten.js';\nimport baseOrderBy from './_baseOrderBy.js';\nimport baseRest from './_baseRest.js';\nimport isIterateeCall from './_isIterateeCall.js';\n\n/**\n * Creates an array of elements, sorted in ascending order by the results of\n * running each element in a collection thru each iteratee. This method\n * performs a stable sort, that is, it preserves the original sort order of\n * equal elements. The iteratees are invoked with one argument: (value).\n *\n * @static\n * @memberOf _\n * @since 0.1.0\n * @category Collection\n * @param {Array|Object} collection The collection to iterate over.\n * @param {...(Function|Function[])} [iteratees=[_.identity]]\n * The iteratees to sort by.\n * @returns {Array} Returns the new sorted array.\n * @example\n *\n * var users = [\n * { 'user': 'fred', 'age': 48 },\n * { 'user': 'barney', 'age': 36 },\n * { 'user': 'fred', 'age': 30 },\n * { 'user': 'barney', 'age': 34 }\n * ];\n *\n * _.sortBy(users, [function(o) { return o.user; }]);\n * // => objects for [['barney', 36], ['barney', 34], ['fred', 48], ['fred', 30]]\n *\n * _.sortBy(users, ['user', 'age']);\n * // => objects for [['barney', 34], ['barney', 36], ['fred', 30], ['fred', 48]]\n */\nvar sortBy = baseRest(function(collection, iteratees) {\n if (collection == null) {\n return [];\n }\n var length = iteratees.length;\n if (length > 1 && isIterateeCall(collection, iteratees[0], iteratees[1])) {\n iteratees = [];\n } else if (length > 2 && isIterateeCall(iteratees[0], iteratees[1], iteratees[2])) {\n iteratees = [iteratees[0]];\n }\n return baseOrderBy(collection, baseFlatten(iteratees, 1), []);\n});\n\nexport default sortBy;\n","import toString from './toString.js';\n\n/** Used to generate unique IDs. */\nvar idCounter = 0;\n\n/**\n * Generates a unique ID. If `prefix` is given, the ID is appended to it.\n *\n * @static\n * @since 0.1.0\n * @memberOf _\n * @category Util\n * @param {string} [prefix=''] The value to prefix the ID with.\n * @returns {string} Returns the unique ID.\n * @example\n *\n * _.uniqueId('contact_');\n * // => 'contact_104'\n *\n * _.uniqueId();\n * // => '105'\n */\nfunction uniqueId(prefix) {\n var id = ++idCounter;\n return toString(prefix) + id;\n}\n\nexport default uniqueId;\n","/**\n * This base implementation of `_.zipObject` which assigns values using `assignFunc`.\n *\n * @private\n * @param {Array} props The property identifiers.\n * @param {Array} values The property values.\n * @param {Function} assignFunc The function to assign values.\n * @returns {Object} Returns the new object.\n */\nfunction baseZipObject(props, values, assignFunc) {\n var index = -1,\n length = props.length,\n valsLength = values.length,\n result = {};\n\n while (++index < length) {\n var value = index < valsLength ? values[index] : undefined;\n assignFunc(result, props[index], value);\n }\n return result;\n}\n\nexport default baseZipObject;\n","import assignValue from './_assignValue.js';\nimport baseZipObject from './_baseZipObject.js';\n\n/**\n * This method is like `_.fromPairs` except that it accepts two arrays,\n * one of property identifiers and one of corresponding values.\n *\n * @static\n * @memberOf _\n * @since 0.4.0\n * @category Array\n * @param {Array} [props=[]] The property identifiers.\n * @param {Array} [values=[]] The property values.\n * @returns {Object} Returns the new object.\n * @example\n *\n * _.zipObject(['a', 'b'], [1, 2]);\n * // => { 'a': 1, 'b': 2 }\n */\nfunction zipObject(props, values) {\n return baseZipObject(props || [], values || [], assignValue);\n}\n\nexport default zipObject;\n","/*\n * Simple doubly linked list implementation derived from Cormen, et al.,\n * \"Introduction to Algorithms\".\n */\n\nexport { List };\n\nclass List {\n constructor() {\n var sentinel = {};\n sentinel._next = sentinel._prev = sentinel;\n this._sentinel = sentinel;\n }\n dequeue() {\n var sentinel = this._sentinel;\n var entry = sentinel._prev;\n if (entry !== sentinel) {\n unlink(entry);\n return entry;\n }\n }\n enqueue(entry) {\n var sentinel = this._sentinel;\n if (entry._prev && entry._next) {\n unlink(entry);\n }\n entry._next = sentinel._next;\n sentinel._next._prev = entry;\n sentinel._next = entry;\n entry._prev = sentinel;\n }\n toString() {\n var strs = [];\n var sentinel = this._sentinel;\n var curr = sentinel._prev;\n while (curr !== sentinel) {\n strs.push(JSON.stringify(curr, filterOutLinks));\n curr = curr._prev;\n }\n return '[' + strs.join(', ') + ']';\n }\n}\n\nfunction unlink(entry) {\n entry._prev._next = entry._next;\n entry._next._prev = entry._prev;\n delete entry._next;\n delete entry._prev;\n}\n\nfunction filterOutLinks(k, v) {\n if (k !== '_next' && k !== '_prev') {\n return v;\n }\n}\n","import * as _ from 'lodash-es';\nimport { Graph } from '../graphlib/index.js';\nimport { List } from './data/list.js';\n\n/*\n * A greedy heuristic for finding a feedback arc set for a graph. A feedback\n * arc set is a set of edges that can be removed to make a graph acyclic.\n * The algorithm comes from: P. Eades, X. Lin, and W. F. Smyth, \"A fast and\n * effective heuristic for the feedback arc set problem.\" This implementation\n * adjusts that from the paper to allow for weighted edges.\n */\nexport { greedyFAS };\n\nvar DEFAULT_WEIGHT_FN = _.constant(1);\n\nfunction greedyFAS(g, weightFn) {\n if (g.nodeCount() <= 1) {\n return [];\n }\n var state = buildState(g, weightFn || DEFAULT_WEIGHT_FN);\n var results = doGreedyFAS(state.graph, state.buckets, state.zeroIdx);\n\n // Expand multi-edges\n return _.flatten(\n _.map(results, function (e) {\n return g.outEdges(e.v, e.w);\n }),\n );\n}\n\nfunction doGreedyFAS(g, buckets, zeroIdx) {\n var results = [];\n var sources = buckets[buckets.length - 1];\n var sinks = buckets[0];\n\n var entry;\n while (g.nodeCount()) {\n while ((entry = sinks.dequeue())) {\n removeNode(g, buckets, zeroIdx, entry);\n }\n while ((entry = sources.dequeue())) {\n removeNode(g, buckets, zeroIdx, entry);\n }\n if (g.nodeCount()) {\n for (var i = buckets.length - 2; i > 0; --i) {\n entry = buckets[i].dequeue();\n if (entry) {\n results = results.concat(removeNode(g, buckets, zeroIdx, entry, true));\n break;\n }\n }\n }\n }\n\n return results;\n}\n\nfunction removeNode(g, buckets, zeroIdx, entry, collectPredecessors) {\n var results = collectPredecessors ? [] : undefined;\n\n _.forEach(g.inEdges(entry.v), function (edge) {\n var weight = g.edge(edge);\n var uEntry = g.node(edge.v);\n\n if (collectPredecessors) {\n results.push({ v: edge.v, w: edge.w });\n }\n\n uEntry.out -= weight;\n assignBucket(buckets, zeroIdx, uEntry);\n });\n\n _.forEach(g.outEdges(entry.v), function (edge) {\n var weight = g.edge(edge);\n var w = edge.w;\n var wEntry = g.node(w);\n wEntry['in'] -= weight;\n assignBucket(buckets, zeroIdx, wEntry);\n });\n\n g.removeNode(entry.v);\n\n return results;\n}\n\nfunction buildState(g, weightFn) {\n var fasGraph = new Graph();\n var maxIn = 0;\n var maxOut = 0;\n\n _.forEach(g.nodes(), function (v) {\n fasGraph.setNode(v, { v: v, in: 0, out: 0 });\n });\n\n // Aggregate weights on nodes, but also sum the weights across multi-edges\n // into a single edge for the fasGraph.\n _.forEach(g.edges(), function (e) {\n var prevWeight = fasGraph.edge(e.v, e.w) || 0;\n var weight = weightFn(e);\n var edgeWeight = prevWeight + weight;\n fasGraph.setEdge(e.v, e.w, edgeWeight);\n maxOut = Math.max(maxOut, (fasGraph.node(e.v).out += weight));\n maxIn = Math.max(maxIn, (fasGraph.node(e.w)['in'] += weight));\n });\n\n var buckets = _.range(maxOut + maxIn + 3).map(function () {\n return new List();\n });\n var zeroIdx = maxIn + 1;\n\n _.forEach(fasGraph.nodes(), function (v) {\n assignBucket(buckets, zeroIdx, fasGraph.node(v));\n });\n\n return { graph: fasGraph, buckets: buckets, zeroIdx: zeroIdx };\n}\n\nfunction assignBucket(buckets, zeroIdx, entry) {\n if (!entry.out) {\n buckets[0].enqueue(entry);\n } else if (!entry['in']) {\n buckets[buckets.length - 1].enqueue(entry);\n } else {\n buckets[entry.out - entry['in'] + zeroIdx].enqueue(entry);\n }\n}\n","import * as _ from 'lodash-es';\nimport { greedyFAS } from './greedy-fas.js';\n\nexport { run, undo };\n\nfunction run(g) {\n var fas = g.graph().acyclicer === 'greedy' ? greedyFAS(g, weightFn(g)) : dfsFAS(g);\n _.forEach(fas, function (e) {\n var label = g.edge(e);\n g.removeEdge(e);\n label.forwardName = e.name;\n label.reversed = true;\n g.setEdge(e.w, e.v, label, _.uniqueId('rev'));\n });\n\n function weightFn(g) {\n return function (e) {\n return g.edge(e).weight;\n };\n }\n}\n\nfunction dfsFAS(g) {\n var fas = [];\n var stack = {};\n var visited = {};\n\n function dfs(v) {\n if (Object.prototype.hasOwnProperty.call(visited, v)) {\n return;\n }\n visited[v] = true;\n stack[v] = true;\n _.forEach(g.outEdges(v), function (e) {\n if (Object.prototype.hasOwnProperty.call(stack, e.w)) {\n fas.push(e);\n } else {\n dfs(e.w);\n }\n });\n delete stack[v];\n }\n\n _.forEach(g.nodes(), dfs);\n return fas;\n}\n\nfunction undo(g) {\n _.forEach(g.edges(), function (e) {\n var label = g.edge(e);\n if (label.reversed) {\n g.removeEdge(e);\n\n var forwardName = label.forwardName;\n delete label.reversed;\n delete label.forwardName;\n g.setEdge(e.w, e.v, label, forwardName);\n }\n });\n}\n","import * as _ from 'lodash-es';\nimport { Graph } from '../graphlib/index.js';\n\nexport {\n addDummyNode,\n simplify,\n asNonCompoundGraph,\n successorWeights,\n predecessorWeights,\n intersectRect,\n buildLayerMatrix,\n normalizeRanks,\n removeEmptyRanks,\n addBorderNode,\n maxRank,\n partition,\n time,\n notime,\n};\n\n/*\n * Adds a dummy node to the graph and return v.\n */\nfunction addDummyNode(g, type, attrs, name) {\n var v;\n do {\n v = _.uniqueId(name);\n } while (g.hasNode(v));\n\n attrs.dummy = type;\n g.setNode(v, attrs);\n return v;\n}\n\n/*\n * Returns a new graph with only simple edges. Handles aggregation of data\n * associated with multi-edges.\n */\nfunction simplify(g) {\n var simplified = new Graph().setGraph(g.graph());\n _.forEach(g.nodes(), function (v) {\n simplified.setNode(v, g.node(v));\n });\n _.forEach(g.edges(), function (e) {\n var simpleLabel = simplified.edge(e.v, e.w) || { weight: 0, minlen: 1 };\n var label = g.edge(e);\n simplified.setEdge(e.v, e.w, {\n weight: simpleLabel.weight + label.weight,\n minlen: Math.max(simpleLabel.minlen, label.minlen),\n });\n });\n return simplified;\n}\n\nfunction asNonCompoundGraph(g) {\n var simplified = new Graph({ multigraph: g.isMultigraph() }).setGraph(g.graph());\n _.forEach(g.nodes(), function (v) {\n if (!g.children(v).length) {\n simplified.setNode(v, g.node(v));\n }\n });\n _.forEach(g.edges(), function (e) {\n simplified.setEdge(e, g.edge(e));\n });\n return simplified;\n}\n\nfunction successorWeights(g) {\n var weightMap = _.map(g.nodes(), function (v) {\n var sucs = {};\n _.forEach(g.outEdges(v), function (e) {\n sucs[e.w] = (sucs[e.w] || 0) + g.edge(e).weight;\n });\n return sucs;\n });\n return _.zipObject(g.nodes(), weightMap);\n}\n\nfunction predecessorWeights(g) {\n var weightMap = _.map(g.nodes(), function (v) {\n var preds = {};\n _.forEach(g.inEdges(v), function (e) {\n preds[e.v] = (preds[e.v] || 0) + g.edge(e).weight;\n });\n return preds;\n });\n return _.zipObject(g.nodes(), weightMap);\n}\n\n/*\n * Finds where a line starting at point ({x, y}) would intersect a rectangle\n * ({x, y, width, height}) if it were pointing at the rectangle's center.\n */\nfunction intersectRect(rect, point) {\n var x = rect.x;\n var y = rect.y;\n\n // Rectangle intersection algorithm from:\n // http://math.stackexchange.com/questions/108113/find-edge-between-two-boxes\n var dx = point.x - x;\n var dy = point.y - y;\n var w = rect.width / 2;\n var h = rect.height / 2;\n\n if (!dx && !dy) {\n throw new Error('Not possible to find intersection inside of the rectangle');\n }\n\n var sx, sy;\n if (Math.abs(dy) * w > Math.abs(dx) * h) {\n // Intersection is top or bottom of rect.\n if (dy < 0) {\n h = -h;\n }\n sx = (h * dx) / dy;\n sy = h;\n } else {\n // Intersection is left or right of rect.\n if (dx < 0) {\n w = -w;\n }\n sx = w;\n sy = (w * dy) / dx;\n }\n\n return { x: x + sx, y: y + sy };\n}\n\n/*\n * Given a DAG with each node assigned \"rank\" and \"order\" properties, this\n * function will produce a matrix with the ids of each node.\n */\nfunction buildLayerMatrix(g) {\n var layering = _.map(_.range(maxRank(g) + 1), function () {\n return [];\n });\n _.forEach(g.nodes(), function (v) {\n var node = g.node(v);\n var rank = node.rank;\n if (!_.isUndefined(rank)) {\n layering[rank][node.order] = v;\n }\n });\n return layering;\n}\n\n/*\n * Adjusts the ranks for all nodes in the graph such that all nodes v have\n * rank(v) >= 0 and at least one node w has rank(w) = 0.\n */\nfunction normalizeRanks(g) {\n var min = _.min(\n _.map(g.nodes(), function (v) {\n return g.node(v).rank;\n }),\n );\n _.forEach(g.nodes(), function (v) {\n var node = g.node(v);\n if (_.has(node, 'rank')) {\n node.rank -= min;\n }\n });\n}\n\nfunction removeEmptyRanks(g) {\n // Ranks may not start at 0, so we need to offset them\n var offset = _.min(\n _.map(g.nodes(), function (v) {\n return g.node(v).rank;\n }),\n );\n\n var layers = [];\n _.forEach(g.nodes(), function (v) {\n var rank = g.node(v).rank - offset;\n if (!layers[rank]) {\n layers[rank] = [];\n }\n layers[rank].push(v);\n });\n\n var delta = 0;\n var nodeRankFactor = g.graph().nodeRankFactor;\n _.forEach(layers, function (vs, i) {\n if (_.isUndefined(vs) && i % nodeRankFactor !== 0) {\n --delta;\n } else if (delta) {\n _.forEach(vs, function (v) {\n g.node(v).rank += delta;\n });\n }\n });\n}\n\nfunction addBorderNode(g, prefix, rank, order) {\n var node = {\n width: 0,\n height: 0,\n };\n if (arguments.length >= 4) {\n node.rank = rank;\n node.order = order;\n }\n return addDummyNode(g, 'border', node, prefix);\n}\n\nfunction maxRank(g) {\n return _.max(\n _.map(g.nodes(), function (v) {\n var rank = g.node(v).rank;\n if (!_.isUndefined(rank)) {\n return rank;\n }\n }),\n );\n}\n\n/*\n * Partition a collection into two groups: `lhs` and `rhs`. If the supplied\n * function returns true for an entry it goes into `lhs`. Otherwise it goes\n * into `rhs.\n */\nfunction partition(collection, fn) {\n var result = { lhs: [], rhs: [] };\n _.forEach(collection, function (value) {\n if (fn(value)) {\n result.lhs.push(value);\n } else {\n result.rhs.push(value);\n }\n });\n return result;\n}\n\n/*\n * Returns a new function that wraps `fn` with a timer. The wrapper logs the\n * time it takes to execute the function.\n */\nfunction time(name, fn) {\n var start = _.now();\n try {\n return fn();\n } finally {\n console.log(name + ' time: ' + (_.now() - start) + 'ms');\n }\n}\n\nfunction notime(name, fn) {\n return fn();\n}\n","import * as _ from 'lodash-es';\nimport * as util from './util.js';\n\nexport { addBorderSegments };\n\nfunction addBorderSegments(g) {\n function dfs(v) {\n var children = g.children(v);\n var node = g.node(v);\n if (children.length) {\n _.forEach(children, dfs);\n }\n\n if (Object.prototype.hasOwnProperty.call(node, 'minRank')) {\n node.borderLeft = [];\n node.borderRight = [];\n for (var rank = node.minRank, maxRank = node.maxRank + 1; rank < maxRank; ++rank) {\n addBorderNode(g, 'borderLeft', '_bl', v, node, rank);\n addBorderNode(g, 'borderRight', '_br', v, node, rank);\n }\n }\n }\n\n _.forEach(g.children(), dfs);\n}\n\nfunction addBorderNode(g, prop, prefix, sg, sgNode, rank) {\n var label = { width: 0, height: 0, rank: rank, borderType: prop };\n var prev = sgNode[prop][rank - 1];\n var curr = util.addDummyNode(g, 'border', label, prefix);\n sgNode[prop][rank] = curr;\n g.setParent(curr, sg);\n if (prev) {\n g.setEdge(prev, curr, { weight: 1 });\n }\n}\n","import * as _ from 'lodash-es';\n\nexport { adjust, undo };\n\nfunction adjust(g) {\n var rankDir = g.graph().rankdir.toLowerCase();\n if (rankDir === 'lr' || rankDir === 'rl') {\n swapWidthHeight(g);\n }\n}\n\nfunction undo(g) {\n var rankDir = g.graph().rankdir.toLowerCase();\n if (rankDir === 'bt' || rankDir === 'rl') {\n reverseY(g);\n }\n\n if (rankDir === 'lr' || rankDir === 'rl') {\n swapXY(g);\n swapWidthHeight(g);\n }\n}\n\nfunction swapWidthHeight(g) {\n _.forEach(g.nodes(), function (v) {\n swapWidthHeightOne(g.node(v));\n });\n _.forEach(g.edges(), function (e) {\n swapWidthHeightOne(g.edge(e));\n });\n}\n\nfunction swapWidthHeightOne(attrs) {\n var w = attrs.width;\n attrs.width = attrs.height;\n attrs.height = w;\n}\n\nfunction reverseY(g) {\n _.forEach(g.nodes(), function (v) {\n reverseYOne(g.node(v));\n });\n\n _.forEach(g.edges(), function (e) {\n var edge = g.edge(e);\n _.forEach(edge.points, reverseYOne);\n if (Object.prototype.hasOwnProperty.call(edge, 'y')) {\n reverseYOne(edge);\n }\n });\n}\n\nfunction reverseYOne(attrs) {\n attrs.y = -attrs.y;\n}\n\nfunction swapXY(g) {\n _.forEach(g.nodes(), function (v) {\n swapXYOne(g.node(v));\n });\n\n _.forEach(g.edges(), function (e) {\n var edge = g.edge(e);\n _.forEach(edge.points, swapXYOne);\n if (Object.prototype.hasOwnProperty.call(edge, 'x')) {\n swapXYOne(edge);\n }\n });\n}\n\nfunction swapXYOne(attrs) {\n var x = attrs.x;\n attrs.x = attrs.y;\n attrs.y = x;\n}\n","/**\n * TypeScript type imports:\n *\n * @import { Graph } from '../graphlib/graph.js';\n */\nimport * as _ from 'lodash-es';\nimport * as util from './util.js';\n\nexport { run, undo };\n\n/*\n * Breaks any long edges in the graph into short segments that span 1 layer\n * each. This operation is undoable with the denormalize function.\n *\n * Pre-conditions:\n *\n * 1. The input graph is a DAG.\n * 2. Each node in the graph has a \"rank\" property.\n *\n * Post-condition:\n *\n * 1. All edges in the graph have a length of 1.\n * 2. Dummy nodes are added where edges have been split into segments.\n * 3. The graph is augmented with a \"dummyChains\" attribute which contains\n * the first dummy in each chain of dummy nodes produced.\n */\nfunction run(g) {\n g.graph().dummyChains = [];\n _.forEach(g.edges(), function (edge) {\n normalizeEdge(g, edge);\n });\n}\n\n/**\n * @param {Graph} g\n */\nfunction normalizeEdge(g, e) {\n var v = e.v;\n var vRank = g.node(v).rank;\n var w = e.w;\n var wRank = g.node(w).rank;\n var name = e.name;\n var edgeLabel = g.edge(e);\n var labelRank = edgeLabel.labelRank;\n\n if (wRank === vRank + 1) return;\n\n g.removeEdge(e);\n\n /**\n * @typedef {Object} Attrs\n * @property {number} width\n * @property {number} height\n * @property {ReturnType<Graph[\"node\"]>} edgeLabel\n * @property {any} edgeObj\n * @property {ReturnType<Graph[\"node\"]>[\"rank\"]} rank\n * @property {string} [dummy]\n * @property {ReturnType<Graph[\"node\"]>[\"labelpos\"]} [labelpos]\n */\n\n /** @type {Attrs | undefined} */\n var attrs = undefined;\n var dummy, i;\n for (i = 0, ++vRank; vRank < wRank; ++i, ++vRank) {\n edgeLabel.points = [];\n attrs = {\n width: 0,\n height: 0,\n edgeLabel: edgeLabel,\n edgeObj: e,\n rank: vRank,\n };\n dummy = util.addDummyNode(g, 'edge', attrs, '_d');\n if (vRank === labelRank) {\n attrs.width = edgeLabel.width;\n attrs.height = edgeLabel.height;\n attrs.dummy = 'edge-label';\n attrs.labelpos = edgeLabel.labelpos;\n }\n g.setEdge(v, dummy, { weight: edgeLabel.weight }, name);\n if (i === 0) {\n g.graph().dummyChains.push(dummy);\n }\n v = dummy;\n }\n\n g.setEdge(v, w, { weight: edgeLabel.weight }, name);\n}\n\nfunction undo(g) {\n _.forEach(g.graph().dummyChains, function (v) {\n var node = g.node(v);\n var origLabel = node.edgeLabel;\n var w;\n g.setEdge(node.edgeObj, origLabel);\n while (node.dummy) {\n w = g.successors(v)[0];\n g.removeNode(v);\n origLabel.points.push({ x: node.x, y: node.y });\n if (node.dummy === 'edge-label') {\n origLabel.x = node.x;\n origLabel.y = node.y;\n origLabel.width = node.width;\n origLabel.height = node.height;\n }\n v = w;\n node = g.node(v);\n }\n });\n}\n","import * as _ from 'lodash-es';\n\nexport { longestPath, slack };\n\n/*\n * Initializes ranks for the input graph using the longest path algorithm. This\n * algorithm scales well and is fast in practice, it yields rather poor\n * solutions. Nodes are pushed to the lowest layer possible, leaving the bottom\n * ranks wide and leaving edges longer than necessary. However, due to its\n * speed, this algorithm is good for getting an initial ranking that can be fed\n * into other algorithms.\n *\n * This algorithm does not normalize layers because it will be used by other\n * algorithms in most cases. If using this algorithm directly, be sure to\n * run normalize at the end.\n *\n * Pre-conditions:\n *\n * 1. Input graph is a DAG.\n * 2. Input graph node labels can be assigned properties.\n *\n * Post-conditions:\n *\n * 1. Each node will be assign an (unnormalized) \"rank\" property.\n */\nfunction longestPath(g) {\n var visited = {};\n\n function dfs(v) {\n var label = g.node(v);\n if (Object.prototype.hasOwnProperty.call(visited, v)) {\n return label.rank;\n }\n visited[v] = true;\n\n var rank = _.min(\n _.map(g.outEdges(v), function (e) {\n return dfs(e.w) - g.edge(e).minlen;\n }),\n );\n\n if (\n rank === Number.POSITIVE_INFINITY || // return value of _.map([]) for Lodash 3\n rank === undefined || // return value of _.map([]) for Lodash 4\n rank === null\n ) {\n // return value of _.map([null])\n rank = 0;\n }\n\n return (label.rank = rank);\n }\n\n _.forEach(g.sources(), dfs);\n}\n\n/*\n * Returns the amount of slack for the given edge. The slack is defined as the\n * difference between the length of the edge and its minimum length.\n */\nfunction slack(g, e) {\n return g.node(e.w).rank - g.node(e.v).rank - g.edge(e).minlen;\n}\n","import * as _ from 'lodash-es';\nimport { Graph } from '../../graphlib/index.js';\nimport { slack } from './util.js';\n\nexport { feasibleTree };\n\n/*\n * Constructs a spanning tree with tight edges and adjusted the input node's\n * ranks to achieve this. A tight edge is one that is has a length that matches\n * its \"minlen\" attribute.\n *\n * The basic structure for this function is derived from Gansner, et al., \"A\n * Technique for Drawing Directed Graphs.\"\n *\n * Pre-conditions:\n *\n * 1. Graph must be a DAG.\n * 2. Graph must be connected.\n * 3. Graph must have at least one node.\n * 5. Graph nodes must have been previously assigned a \"rank\" property that\n * respects the \"minlen\" property of incident edges.\n * 6. Graph edges must have a \"minlen\" property.\n *\n * Post-conditions:\n *\n * - Graph nodes will have their rank adjusted to ensure that all edges are\n * tight.\n *\n * Returns a tree (undirected graph) that is constructed using only \"tight\"\n * edges.\n */\nfunction feasibleTree(g) {\n var t = new Graph({ directed: false });\n\n // Choose arbitrary node from which to start our tree\n var start = g.nodes()[0];\n var size = g.nodeCount();\n t.setNode(start, {});\n\n var edge, delta;\n while (tightTree(t, g) < size) {\n edge = findMinSlackEdge(t, g);\n delta = t.hasNode(edge.v) ? slack(g, edge) : -slack(g, edge);\n shiftRanks(t, g, delta);\n }\n\n return t;\n}\n\n/*\n * Finds a maximal tree of tight edges and returns the number of nodes in the\n * tree.\n */\nfunction tightTree(t, g) {\n function dfs(v) {\n _.forEach(g.nodeEdges(v), function (e) {\n var edgeV = e.v,\n w = v === edgeV ? e.w : edgeV;\n if (!t.hasNode(w) && !slack(g, e)) {\n t.setNode(w, {});\n t.setEdge(v, w, {});\n dfs(w);\n }\n });\n }\n\n _.forEach(t.nodes(), dfs);\n return t.nodeCount();\n}\n\n/*\n * Finds the edge with the smallest slack that is incident on tree and returns\n * it.\n */\nfunction findMinSlackEdge(t, g) {\n return _.minBy(g.edges(), function (e) {\n if (t.hasNode(e.v) !== t.hasNode(e.w)) {\n return slack(g, e);\n }\n });\n}\n\nfunction shiftRanks(t, g, delta) {\n _.forEach(t.nodes(), function (v) {\n g.node(v).rank += delta;\n });\n}\n","import * as _ from 'lodash-es';\n\nexport { topsort, CycleException };\n\ntopsort.CycleException = CycleException;\n\nfunction topsort(g) {\n var visited = {};\n var stack = {};\n var results = [];\n\n function visit(node) {\n if (Object.prototype.hasOwnProperty.call(stack, node)) {\n throw new CycleException();\n }\n\n if (!Object.prototype.hasOwnProperty.call(visited, node)) {\n stack[node] = true;\n visited[node] = true;\n _.each(g.predecessors(node), visit);\n delete stack[node];\n results.push(node);\n }\n }\n\n _.each(g.sinks(), visit);\n\n if (_.size(visited) !== g.nodeCount()) {\n throw new CycleException();\n }\n\n return results;\n}\n\nfunction CycleException() {}\nCycleException.prototype = new Error(); // must be an instance of Error to pass testing\n","import * as _ from 'lodash-es';\n\nexport { dfs };\n\n/*\n * A helper that preforms a pre- or post-order traversal on the input graph\n * and returns the nodes in the order they were visited. If the graph is\n * undirected then this algorithm will navigate using neighbors. If the graph\n * is directed then this algorithm will navigate using successors.\n *\n * Order must be one of \"pre\" or \"post\".\n */\nfunction dfs(g, vs, order) {\n if (!_.isArray(vs)) {\n vs = [vs];\n }\n\n var navigation = (g.isDirected() ? g.successors : g.neighbors).bind(g);\n\n var acc = [];\n var visited = {};\n _.each(vs, function (v) {\n if (!g.hasNode(v)) {\n throw new Error('Graph does not have node: ' + v);\n }\n\n doDfs(g, v, order === 'post', visited, navigation, acc);\n });\n return acc;\n}\n\nfunction doDfs(g, v, postorder, visited, navigation, acc) {\n if (!Object.prototype.hasOwnProperty.call(visited, v)) {\n visited[v] = true;\n\n if (!postorder) {\n acc.push(v);\n }\n _.each(navigation(v), function (w) {\n doDfs(g, w, postorder, visited, navigation, acc);\n });\n if (postorder) {\n acc.push(v);\n }\n }\n}\n","import { dfs } from './dfs.js';\n\nexport { postorder };\n\nfunction postorder(g, vs) {\n return dfs(g, vs, 'post');\n}\n","import { dfs } from './dfs.js';\n\nexport { preorder };\n\nfunction preorder(g, vs) {\n return dfs(g, vs, 'pre');\n}\n","import * as _ from 'lodash-es';\nimport * as alg from '../../graphlib/alg/index.js';\nimport { simplify } from '../util.js';\nimport { feasibleTree } from './feasible-tree.js';\nimport { longestPath, slack } from './util.js';\n\nexport { networkSimplex };\n\n// Expose some internals for testing purposes\nnetworkSimplex.initLowLimValues = initLowLimValues;\nnetworkSimplex.initCutValues = initCutValues;\nnetworkSimplex.calcCutValue = calcCutValue;\nnetworkSimplex.leaveEdge = leaveEdge;\nnetworkSimplex.enterEdge = enterEdge;\nnetworkSimplex.exchangeEdges = exchangeEdges;\n\n/*\n * The network simplex algorithm assigns ranks to each node in the input graph\n * and iteratively improves the ranking to reduce the length of edges.\n *\n * Preconditions:\n *\n * 1. The input graph must be a DAG.\n * 2. All nodes in the graph must have an object value.\n * 3. All edges in the graph must have \"minlen\" and \"weight\" attributes.\n *\n * Postconditions:\n *\n * 1. All nodes in the graph will have an assigned \"rank\" attribute that has\n * been optimized by the network simplex algorithm. Ranks start at 0.\n *\n *\n * A rough sketch of the algorithm is as follows:\n *\n * 1. Assign initial ranks to each node. We use the longest path algorithm,\n * which assigns ranks to the lowest position possible. In general this\n * leads to very wide bottom ranks and unnecessarily long edges.\n * 2. Construct a feasible tight tree. A tight tree is one such that all\n * edges in the tree have no slack (difference between length of edge\n * and minlen for the edge). This by itself greatly improves the assigned\n * rankings by shorting edges.\n * 3. Iteratively find edges that have negative cut values. Generally a\n * negative cut value indicates that the edge could be removed and a new\n * tree edge could be added to produce a more compact graph.\n *\n * Much of the algorithms here are derived from Gansner, et al., \"A Technique\n * for Drawing Directed Graphs.\" The structure of the file roughly follows the\n * structure of the overall algorithm.\n */\nfunction networkSimplex(g) {\n g = simplify(g);\n longestPath(g);\n var t = feasibleTree(g);\n initLowLimValues(t);\n initCutValues(t, g);\n\n var e, f;\n while ((e = leaveEdge(t))) {\n f = enterEdge(t, g, e);\n exchangeEdges(t, g, e, f);\n }\n}\n\n/*\n * Initializes cut values for all edges in the tree.\n */\nfunction initCutValues(t, g) {\n var vs = alg.postorder(t, t.nodes());\n vs = vs.slice(0, vs.length - 1);\n _.forEach(vs, function (v) {\n assignCutValue(t, g, v);\n });\n}\n\nfunction assignCutValue(t, g, child) {\n var childLab = t.node(child);\n var parent = childLab.parent;\n t.edge(child, parent).cutvalue = calcCutValue(t, g, child);\n}\n\n/*\n * Given the tight tree, its graph, and a child in the graph calculate and\n * return the cut value for the edge between the child and its parent.\n */\nfunction calcCutValue(t, g, child) {\n var childLab = t.node(child);\n var parent = childLab.parent;\n // True if the child is on the tail end of the edge in the directed graph\n var childIsTail = true;\n // The graph's view of the tree edge we're inspecting\n var graphEdge = g.edge(child, parent);\n // The accumulated cut value for the edge between this node and its parent\n var cutValue = 0;\n\n if (!graphEdge) {\n childIsTail = false;\n graphEdge = g.edge(parent, child);\n }\n\n cutValue = graphEdge.weight;\n\n _.forEach(g.nodeEdges(child), function (e) {\n var isOutEdge = e.v === child,\n other = isOutEdge ? e.w : e.v;\n\n if (other !== parent) {\n var p