import {density} from 'graphology-metrics';
import density from 'graphology-metrics/density';

// Passing a graph instance
const d = density(graph);

// Passing the graph's order & size
const d = density(order, size);

// Or to force the kind of density being computed
import {
  mixedDensity,
  directedDensity,
  undirectedDensity,
  multiMixedDensity,
  multiDirectedDensity,
  multiUndirectedDensity
} from 'graphology-metric/density';

const d = undirectedDensity(mixedGraph);

import {diameter} from 'graphology-metrics';
// Alternatively, to load only the relevant code:
import diameter from 'graphology-metrics/diameter';

const graph = new Graph();
graph.addNode('1');
graph.addNode('2');
graph.addNode('3');
graph.addUndirectedEdge(1, 2);
graph.addUndirectedEdge(2, 3);

diameter(graph);
>>> 2

import extent from 'graphology-metrics/extent';

// Retrieving a single node attribute's extent
extent(graph, 'size');
>>> [1, 34]

// Retrieving multiple node attributes' extents
extent(graph, ['x', 'y']);
>>> {x: [-4, 3], y: [-34, 56]}

// For edges
extent.edgeExtent(graph, 'weight');
>>> [0, 5.7]

import {modularity} from 'graphology-metrics';
// Alternatively, to load only the relevant code:
import modularity from 'graphology-metrics/modularity';

// Simplest way
const Q = modularity(graph);

// If the partition is not given by node attributes
const Q = modularity(graph, {
  communities: {1: 0, 2: 0, 3: 1, 4: 1, 5: 1}
});

import {weightedSize} from 'graphology-metrics';
// Alternatively, to load only the relevant code:
import weightedSize from 'graphology-metrics/weighted-size';

const graph = new Graph();
graph.mergeEdge(1, 2, {weight: 3});
graph.mergeEdge(1, 2, {weight: 1});

// Simplest way
weightedSize(graph);
>>> 4

// With custom weight attribute
weightedSize(graph, 'myWeightAttribute');
>>> 4

import betweennessCentrality from 'graphology-metrics/centrality/betweenness';

// To compute centrality for every node:
const centrality = betweennessCentrality(graph);

// To compute weighted betweenness centrality
const centrality = betweennessCentrality(graph, {weighted: true});

// To directly map the result onto nodes' attributes (`betweennessCentrality`):
betweennessCentrality.assign(graph);

// To directly map the result onto a custom attribute:
betweennessCentrality.assign(graph, {attributes: {centrality: 'myCentrality'}});

import closenessCentrality from 'graphology-metrics/centrality/closeness';

// To compute the eigenvector centrality and return the score per node:
const scores = closenessCentrality(graph);

// To directly map the result to nodes' attributes:
closenessCentrality.assign(graph);

// Note that you can also pass options to customize the algorithm:
const p = closenessCentrality(graph, {wassermanFaust: true});

import degreeCentrality from 'graphology-metrics/centrality/degree';
// Or to load more specific functions:
import {
  degreeCentrality,
  inDegreeCentrality,
  outDegreeCentrality
} from 'graphology-metrics/centrality/degree';

// To compute degree centrality for every node:
const centrality = degreeCentrality(graph);

// To directly map the result onto nodes' attributes (`degreeCentrality`):
degreeCentrality.assign(graph);

// To directly map the result onto a custom attribute:
degreeCentrality.assign(graph, {attributes: {centrality: 'myCentrality'}});

import eigenvectorCentrality from 'graphology-metrics/centrality/eigenvector';

// To compute the eigenvector centrality and return the score per node:
const scores = eigenvectorCentrality(graph);

// To directly map the result to nodes' attributes:
eigenvectorCentrality.assign(graph);

// Note that you can also pass options to customize the algorithm:
const p = eigenvectorCentrality(graph, {tolerance: 1e-3, weighted: false});

import hits from 'graphology-metrics/centrality/hits';

// To compute and return the result as 'hubs' & 'authorities':
const {hubs, authorities} = hits(graph);

// To directly map the result to nodes' attributes:
hits.assign(graph);

// Note that you can also pass options to customize the algorithm:
const {hubs, authorities} = hits(graph, {normalize: false});

import pagerank from 'graphology-metrics/centrality/pagerank';

// To compute pagerank and return the score per node:
const scores = pagerank(graph);

// To directly map the result to nodes' attributes:
pagerank.assign(graph);

// Note that you can also pass options to customize the algorithm:
const p = pagerank(graph, {alpha: 0.9, weighted: false});

import weightedDegree from 'graphology-metrics/weighted-degree';
// Or to load more specific functions:
import {
  weightedDegree,
  weightedInDegree,
  weightedOutDegree
} from 'graphology-metrics/weighted-degree';

// To compute weighted degree of a single node
weightedDegree(graph, 'A');

// To compute weighted degree of every node
const weightedDegrees = weightedDegree(graph);

// To compute normalized weighted degree, i.e. weighted degree will be
// divided by the node's relevant degree
weightedDegree(graph, 'A', {normalized: true});

// To directly map the result onto node attributes
weightedDegree.assign(graph);

import degree from 'graphology-metrics/degree';

import degree, {
  inDegree,
  outDegree,
  undirectedDegree,
  directedDegree,
  allDegree
} from 'graphology-metrics/degree';

// To extract degree information for every node
const degrees = degree(graph);
>>> {node1: 34, node2: 45, ...}

// To extract only in degree information for every node
const inDegrees = inDegree(graph);

// To extract full degree breakdown for every node
const degrees = allDegree(graph);
>>> { // Assuming the graph is directed
  node1: {
    inDegree: 2,
    outDegree: 36
  },
  ...
}

// To map degree information to node attributes
degree.assign(graph);
graph.getNodeAttribute(node, 'degree');
>>> 45

// To map only degree & in degree to node attributes
allDegree.assign(graph, {types: ['degree', 'inDegree']});

// To map only degree & in degree with different names
allDegree(
  graph,
  {
    attributes: {
      inDegree: 'in',
      outDegree: 'out'
    },
    types: ['inDegree', 'outDegree']
  }
)
>>> {
  1: {in: 1, out: 1},
  ...
}

import {eccentricity} from 'graphology-metrics';
// Alternatively, to load only the relevant code:
import eccentricity from 'graphology-metrics/eccentricity';

graph.addNode('1');
graph.addNode('2');
graph.addNode('3');
graph.addNode('4');
graph.addUndirectedEdge(1, 2);
graph.addUndirectedEdge(2, 3);
graph.addUndirectedEdge(3, 1);
graph.addUndirectedEdge(3, 4);

eccentricity(graph, 3) >> 1;

import modalities from 'graphology-metrics/modalities';

// Retrieving the 'type' attribute's modalities
const info = modalities(graph, 'type');
>>> {
  value1: {
    nodes: 34,
    internalEdges: 277,
    internalDensity: 0.03,
    externalEdges: 45,
    externalDensity: 0.05,
    inboundEdges: 67,
    inboundDensity: 0.07,
    outboundEdges: 124,
    outboundDensity: 0.003
  },
  ...
}

// Retrieving modalities info for several attributes at once
const info = modalities(graph, ['type', 'lang']);
>>> {
  type: {...},
  lang: {...}
}

import edgeUniformity from 'graphology-metrics/layout-quality/edge-uniformity';

edgeUniformity(graph);
>>> ~1.132

import neighborhoodPreservation from 'graphology-metrics/layout-quality/neighborhood-preservation';

neighborhoodPreservation(graph);
// >>> 0.456

import stress from 'graphology-metrics/layout-quality/stress';

stress(graph);
// >>> ~24510.2914