19529302360

Committed 20 Nov 2025 07:38AM UTC coverage: 79.387% (+0.2%) from 79.235%

Build # 19529302360

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push

github

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web-flow

Commit Message

Merge pull request #1360 from Schwarf/coverage/edge_scores

Add unit tests for class EdgeScoreAsWeight.

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13 of 16 new or added lines in 2 files covered. (81.25%)

29424 of 37064 relevant lines covered (79.39%)

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96.0

/networkit/cpp/edgescores/EdgeScore.cpp

/*
 * EdgeScore.cpp
 *
 *  Created on: 18.08.2015
 *      Author: Gerd Lindner
 */

#include <networkit/auxiliary/Log.hpp>
#include <networkit/edgescores/EdgeScore.hpp>

namespace NetworKit {

template <typename T>
EdgeScore<T>::EdgeScore(const Graph &G) : Algorithm(), G(&G), scoreData() {}

/** Compute the edge score. */
template <typename T>
void EdgeScore<T>::run() {
    // empty run method for edge scoring methods that do not require preprocessing but calculate
    // score(u,v) on the fly
    hasRun = true;
}

/** Get a vector containing the score for each edge in the graph.
 *
 * @return the edge scores calculated by @link run().
 */
template <typename T>
const std::vector<T> &EdgeScore<T>::scores() const {
    assureFinished();
    return scoreData;
}

/** Get the edge score of the edge with the given edge id.
 */
template <typename T>
T EdgeScore<T>::score(edgeid eid) {
    assureFinished();
    return scoreData[eid];
}

/** Get the edge score of the given edge.
 */
template <typename T>
T EdgeScore<T>::score(node u, node v) {
    return score(G->edgeId(u, v));
}

template <typename T>
Graph EdgeScore<T>::calculate(bool squared, edgeweight offset, edgeweight factor) const {
    assureFinished();

    if (!G->hasEdgeIds()) {
        throw std::runtime_error("Edges have not been indexed - call indexEdges first");
    }

    Graph result(*G, true, G->isDirected());

    if (squared) {
        G->parallelForEdges([&](node u, node v, edgeid eid) {
            const auto s = scoreData[eid];
            result.setWeight(u, v, offset + factor * s * s);
        });
    } else {
        G->parallelForEdges([&](node u, node v, edgeid eid) {
            result.setWeight(u, v, offset + factor * scoreData[eid]);
        });
    }
    return result;
}

template class EdgeScore<double>;
template class EdgeScore<count>;

} /* namespace NetworKit */

1	/*
2	* EdgeScore.cpp
3	*
4	* Created on: 18.08.2015
5	* Author: Gerd Lindner
6	*/
7
8	#include <networkit/auxiliary/Log.hpp>
9	#include <networkit/edgescores/EdgeScore.hpp>
10
11	namespace NetworKit {
12
13	template <typename T>
14	EdgeScore<T>::EdgeScore(const Graph &G) : Algorithm(), G(&G), scoreData() {}	104✔
15
16	/** Compute the edge score. */
17	template <typename T>
18	void EdgeScore<T>::run() {	2✔
19	// empty run method for edge scoring methods that do not require preprocessing but calculate
20	// score(u,v) on the fly
21	hasRun = true;	2✔
22	}	2✔
23
24	/** Get a vector containing the score for each edge in the graph.
25	*
26	* @return the edge scores calculated by @link run().
27	*/
28	template <typename T>
29	const std::vector<T> &EdgeScore<T>::scores() const {	78✔
30	assureFinished();	78✔
31	return scoreData;	76✔
32	}
33
34	/** Get the edge score of the edge with the given edge id.
35	*/
36	template <typename T>
37	T EdgeScore<T>::score(edgeid eid) {	20✔
38	assureFinished();	20✔
39	return scoreData[eid];	16✔
40	}
41
42	/** Get the edge score of the given edge.
43	*/
44	template <typename T>
45	T EdgeScore<T>::score(node u, node v) {	10✔
46	return score(G->edgeId(u, v));	10✔
47	}
48
49	template <typename T>
50	Graph EdgeScore<T>::calculate(bool squared, edgeweight offset, edgeweight factor) const {	10✔
51	assureFinished();	10✔
52
53	if (!G->hasEdgeIds()) {	8✔
54	throw std::runtime_error("Edges have not been indexed - call indexEdges first");	2✔
55	}
56
57	Graph result(*G, true, G->isDirected());	6✔
58
59	if (squared) {	6✔
60	G->parallelForEdges([&](node u, node v, edgeid eid) {	8✔
61	const auto s = scoreData[eid];	2✔
62	result.setWeight(u, v, offset + factor * s * s);	2✔
63	});
64	} else {
65	G->parallelForEdges([&](node u, node v, edgeid eid) {	12✔
66	result.setWeight(u, v, offset + factor * scoreData[eid]);	4✔
67	});
68	}
69	return result;	6✔
NEW 70	}	×
71
72	template class EdgeScore<double>;
73	template class EdgeScore<count>;
74
75	} /* namespace NetworKit */

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