PlotGenerator.kt.mj 6.34 KB
Newer Older
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
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
fun generateScalingPlot(logs: List<ParEpLog>, graphs: Array<String>, k: Int, allowedNumberOfCores: Array<Int>, filename: String, aspect: (ParEpLog) -> Double) {
    println(string)

    val filtered = logs.filter { it.graphName in graphs && it.numberOfCores in allowedNumberOfCores && it.k == k }
    val runtimes = filtered.groupBy { Pair(it.graphName, it.numberOfCores) }
            .mapValues { (_, values) -> values.map(aspect).average() }

    File(filename).bufferedWriter().use {
        for (graph in graphs) {
            for (numberOfCores in allowedNumberOfCores) {
                val key = Pair(graph, numberOfCores)
                val runtime = runtimes[key]
                if (runtime != null) {
                    it.write(string_string_string)
                } else {
                    println(string)
                }
            }
        }
    }
}

fun generateTwoPlots(db: Db, algorithms: Array<String>, graphs: Array<String>, ks: Array<Int>, filename: String, aspect: (Log) -> Double) {
    println(string)

    val filtered = db.filter {
        it.algorithm in algorithms && it.graphName in graphs && it.k in ks
    }

    data class Point(val algorithm: String, val x: Int, val y: Double)
    val points = ArrayList<Point>()

    val instanceNames = graphs
            .flatMap { graph -> ks.map { k -> Pair(graph, k) } }
            .sortedBy { (graph, k) -> dimensions[graph]!![string]!! }

    var x = 0
    for ((graph, k) in instanceNames) {
            val instances = filtered
                    .filter { it.graphName == graph && it.k == k }
                    .groupBy { it.algorithm }
            val values = instances.mapValues { (_, values) -> values.map(aspect).average() }

            for (algorithm in algorithms) {
                points.add(Point(algorithm, x, values[algorithm]!!))
            }
        ++x
    }

    File(filename).bufferedWriter().use {
        for ((algorithm, x, y) in points) {
            it.write(string)
            it.newLine()
        }
    }
}

fun generateSinglePlot(db: Db, algorithms: Array<String>, graphs: Array<String>, ks: Array<Int>, filename: String) {
    println(string)

    data class Point(val algorithm: String, val x: Double, val y: Double)
    val points = ArrayList<Point>()

    val filtered = db.filter {
        it.algorithm in algorithms && it.graphName in graphs && it.k in ks
    }

    for (graph in graphs) {
        for (k in ks) {
            val instances = filtered
                    .filter { it.graphName == graph && it.k == k }
                    .groupBy { it.algorithm }
            val cuts = instances.mapValues { (_, values) -> values.map { it.vertexCut }.average() }
            val bestCut = cuts.map { (_, cut) -> cut }.min() as Double

            val runtimes = instances.mapValues { (_, values) -> values.map { it.time }.average() }
            val bestRuntime = runtimes.map { (_, runtime) -> runtime }.min() as Double

            for (algorithm in algorithms) {
                val cut = cuts[algorithm]
                if (cut == null) {
                    println(string)
                    continue
                }
                val runtime = runtimes[algorithm]!!

                points.add(Point(algorithm, runtime / bestRuntime, 1 - (bestCut / cut)))
            }
        }
    }

    File(filename).bufferedWriter().use {
        for ((algorithm, x, y) in points) {
            it.write(string)
            it.newLine()
        }
    }
}

fun generatePerformancePlot(db: Db, algorithms: Array<String>, graphs: Array<String>, ks: Array<Int>, filename: String, aspect: (Log) -> Double) {
    println(string)

    val performanceValues = HashMap<String, MutableList<Double>>().apply {
        algorithms.forEach { this/*@*/apply[it] = ArrayList() }
    }
    val filtered = db.filter { it.algorithm in algorithms && it.graphName in graphs && it.k in ks }

    for (graph in graphs) {
        for (k in ks) {
            val values = filtered.filter { it.graphName == graph && it.k == k }
                    .groupBy { it.algorithm }
                    .mapValues { (_, values) -> values.map(aspect).average() }
            val best = values.map { (_, average) -> average }.min()
            if (best == null) {
                println(string)
                continue
            }

            for (algorithm in algorithms) {
                val value = values[algorithm]
                if (value != null) {
                    if (value == 0.0) {
                        throw Exception(string)
                    }
                    performanceValues[algorithm]!!.add(1.0 - best / value)
                    if (algorithm in arrayOf(string)) {
                        println(string)
                    }
                } else {
                    performanceValues[algorithm]!!.add(1.0)
                }
            }
        }
    }

    performanceValues.forEach { (_, values) -> values.sortDescending() }

    File(filename).bufferedWriter().use { writer ->
        for (algorithm in algorithms) {
            var i = 1
            performanceValues[algorithm]?.forEach {
                writer.write(string)
                writer.newLine()
                ++i
            }
        }
    }
}

class PerformancePlotGenerator {

    private val records = HashMap<String, ArrayList<Double>>()

    fun add(algorithm: String, performance: Double) = records.getOrPut(algorithm) { ArrayList() }.add(performance)

    fun generate(writer: Writer) {
        val (maxLengthAlgorithm, maxLength) = records
                .mapValues { (_, v) -> v.size }
                .maxBy { (_, v) -> v }!!
        val (minLengthAlgorithm, minLength) = records
                .mapValues { (_, v) -> v.size }
                .minBy { (_, v) -> v }!!

        if (minLength != maxLength) {
            println(string)
        }

        for (i in 0 until maxLength) {
            val notNull = records.filter { (_, v) -> v.size > i }
            val best = notNull.map { (_, v) -> v[i] }.min()!!
            val values = notNull.mapValues { (_, v) -> 1.0 - best / v[i] }
            values.forEach { (k, v) -> records[k]?.let { it[i] = v } }
        }

        records.forEach { (_, v) -> v.sort() }
        for (i in 0 until maxLength) {
            val notNull = records.filter { (_, v) -> v.size > i }
            val values = notNull.mapValues { (_, v) -> v[i] }
            values.forEach { (k, v) -> writer.write(string) }
        }

    }
}