blob: f9923a6303e403f77fbcb0433a788fc46696cdde (
plain) (
blame)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
|
package ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.graph;
import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.graph.GraphStatistic;
import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.metrics.EdgeTypeMetric;
import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.metrics.Metric;
import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.metrics.MetricSampleGroup;
import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.metrics.MultiplexParticipationCoefficientMetric;
import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.metrics.NodeActivityMetric;
import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.metrics.NodeTypeMetric;
import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.metrics.OutDegreeMetric;
import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.metrics.TypedOutDegree;
import java.util.ArrayList;
import java.util.Collection;
import java.util.HashMap;
import java.util.List;
import org.eclipse.xtext.xbase.lib.Conversions;
@SuppressWarnings("all")
public abstract class Graph {
protected final static String META_MODEL_HEADER = "Meta Mode";
protected final static String NUM_NODE_HEADER = "Number Of Nodes";
protected final static String NUM_EDGE_TYPE_HEADER = "Number of Edge types";
protected final static String STATE_ID_HEADER = "State Id";
protected final GraphStatistic statistic = new GraphStatistic();
protected List<Metric> metrics;
protected String name = "";
protected String metaModel = "";
/**
* evaluate all metrics for this model
* return the result as a two dimentional list
*/
public ArrayList<ArrayList<String>> evaluateAllMetrics() {
final ArrayList<ArrayList<String>> result = new ArrayList<ArrayList<String>>();
this.setBasicInformation(result);
for (final Metric metric : this.metrics) {
{
final String[][] datas = metric.evaluate(this.statistic);
for (final String[] row : datas) {
ArrayList<String> _arrayList = new ArrayList<String>((Collection<? extends String>)Conversions.doWrapArray(row));
result.add(_arrayList);
}
}
}
return result;
}
public MetricSampleGroup evaluateAllMetricsToSamples() {
MetricSampleGroup sample = new MetricSampleGroup();
for (final Metric metric : this.metrics) {
if ((metric instanceof MultiplexParticipationCoefficientMetric)) {
Object _evaluateSamples = ((MultiplexParticipationCoefficientMetric)metric).evaluateSamples(this.statistic);
sample.mpcSamples = ((ArrayList<Double>) _evaluateSamples);
} else {
if ((metric instanceof NodeActivityMetric)) {
Object _evaluateSamples_1 = ((NodeActivityMetric)metric).evaluateSamples(this.statistic);
sample.naSamples = ((ArrayList<Double>) _evaluateSamples_1);
} else {
if ((metric instanceof OutDegreeMetric)) {
Object _evaluateSamples_2 = ((OutDegreeMetric)metric).evaluateSamples(this.statistic);
sample.outDegreeSamples = ((ArrayList<Double>) _evaluateSamples_2);
} else {
if ((metric instanceof TypedOutDegree)) {
Object _evaluateSamples_3 = ((TypedOutDegree)metric).evaluateSamples(this.statistic);
sample.typedOutDegreeSamples = ((HashMap<String, List<Integer>>) _evaluateSamples_3);
} else {
if ((metric instanceof NodeTypeMetric)) {
Object _evaluateSamples_4 = ((NodeTypeMetric)metric).evaluateSamples(this.statistic);
sample.nodeTypeSamples = ((HashMap<String, Double>) _evaluateSamples_4);
} else {
if ((metric instanceof EdgeTypeMetric)) {
Object _evaluateSamples_5 = ((EdgeTypeMetric)metric).evaluateSamples(this.statistic);
sample.edgeTypeSamples = ((HashMap<String, Double>) _evaluateSamples_5);
}
}
}
}
}
}
}
return sample;
}
public abstract void setBasicInformation(final ArrayList<ArrayList<String>> result);
public abstract GraphStatistic getStatistic();
public abstract String getName();
}
|
