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Diffstat (limited to 'Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/src/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/distance/KSDistance.xtend')
-rw-r--r-- | Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/src/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/distance/KSDistance.xtend | 47 |
1 files changed, 47 insertions, 0 deletions
diff --git a/Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/src/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/distance/KSDistance.xtend b/Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/src/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/distance/KSDistance.xtend new file mode 100644 index 00000000..1fb21529 --- /dev/null +++ b/Metrics/Metrics-Calculation/ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator/src/ca/mcgill/ecse/dslreasoner/realistic/metrics/calculator/distance/KSDistance.xtend | |||
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1 | package ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.distance | ||
2 | |||
3 | import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.app.Domain | ||
4 | import java.util.List | ||
5 | import org.apache.commons.math3.stat.inference.KolmogorovSmirnovTest | ||
6 | import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.io.RepMetricsReader | ||
7 | |||
8 | class KSDistance { | ||
9 | var static ksTester = new KolmogorovSmirnovTest(); | ||
10 | var double[] mpcSamples; | ||
11 | var double[] naSamples; | ||
12 | var double[] outDegreeSamples; | ||
13 | |||
14 | new(Domain d){ | ||
15 | var metrics = RepMetricsReader.read(d); | ||
16 | mpcSamples = metrics.mpcSamples; | ||
17 | naSamples = metrics.naSamples.stream.mapToDouble([it]).toArray(); | ||
18 | outDegreeSamples = metrics.outDegreeSamples.stream.mapToDouble([it]).toArray(); | ||
19 | } | ||
20 | |||
21 | def double mpcDistance(List<Double> samples){ | ||
22 | // map list to array | ||
23 | var arr = samples.stream.mapToDouble([it]).toArray(); | ||
24 | |||
25 | //if the size of array is smaller than 2, ks distance cannot be performed, simply return 1 | ||
26 | if(arr.size < 2) return 1; | ||
27 | return ksTester.kolmogorovSmirnovStatistic(mpcSamples, arr); | ||
28 | } | ||
29 | |||
30 | def double naDistance(List<Double> samples){ | ||
31 | // map list to array | ||
32 | var arr = samples.stream.mapToDouble([it]).toArray(); | ||
33 | |||
34 | //if the size of array is smaller than 2, ks distance cannot be performed, simply return 1 | ||
35 | if(arr.size < 2) return 1; | ||
36 | return ksTester.kolmogorovSmirnovStatistic(naSamples as double[], arr); | ||
37 | } | ||
38 | |||
39 | def double outDegreeDistance(List<Double> samples){ | ||
40 | // map list to array | ||
41 | var arr = samples.stream.mapToDouble([it]).toArray(); | ||
42 | |||
43 | //if the size of array is smaller than 2, ks distance cannot be performed, simply return 1 | ||
44 | if(arr.size < 2) return 1; | ||
45 | return ksTester.kolmogorovSmirnovStatistic(outDegreeSamples, arr); | ||
46 | } | ||
47 | } \ No newline at end of file | ||