analysis/org.eclipse.tracecompass.analysis.timing.core/src/org/eclipse/tracecompass/internal/analysis/timing/core/callgraph/AggregatedCalledFunctionStatistics.java

   1 /*******************************************************************************
   2  * Copyright (c) 2016 Ericsson
   3  *
   4  * All rights reserved. This program and the accompanying materials are
   5  * made available under the terms of the Eclipse Public License v1.0 which
   6  * accompanies this distribution, and is available at
   7  * http://www.eclipse.org/legal/epl-v10.html
   8  *******************************************************************************/
   9
  10 package org.eclipse.tracecompass.internal.analysis.timing.core.callgraph;
  11
  12 import org.eclipse.tracecompass.analysis.timing.core.segmentstore.statistics.SegmentStoreStatistics;
  13 import org.eclipse.tracecompass.segmentstore.core.BasicSegment;
  14
  15 /**
  16  * Class to calculate statistics for an aggregated function.
  17  *
  18  * @author Sonia Farrah
  19  */
  20 public class AggregatedCalledFunctionStatistics extends SegmentStoreStatistics {
  21
  22     /**
  23      * The maximum self time
  24      */
  25     private long fMaxSelfTime;
  26     /**
  27      * The minimum duration
  28      */
  29     private long fMinSelfTime;
  30     /**
  31      * The average self time
  32      */
  33     private double fSelfTimeAverage;
  34     /**
  35      * The variance of the self time
  36      */
  37     private double fVariance;
  38
  39     /**
  40      * Constructor
  41      *
  42      * @param duration
  43      *            The function's duration
  44      * @param selfTime
  45      *            The function's self time
  46      */
  47     public AggregatedCalledFunctionStatistics(long duration, long selfTime) {
  48         fMaxSelfTime = selfTime;
  49         fMinSelfTime = selfTime;
  50         fVariance = 0.0;
  51         update(new BasicSegment(0, duration));
  52     }
  53
  54     /**
  55      * Update the statistics, this is used while merging nodes for the
  56      * aggregation tree.
  57      *
  58      * @param duration
  59      *            The function to be merged duration
  60      * @param selfTime
  61      *            The function to be merged self time
  62      */
  63     public void update(long duration, long selfTime) {
  64         update(new BasicSegment(0, duration));
  65         if (fMaxSelfTime < selfTime) {
  66             fMaxSelfTime = selfTime;
  67         }
  68         if (fMinSelfTime > selfTime) {
  69             fMinSelfTime = selfTime;
  70         }
  71         double delta = selfTime - fSelfTimeAverage;
  72         fSelfTimeAverage += delta / getNbSegments();
  73         fVariance += delta * (selfTime - fSelfTimeAverage);
  74     }
  75
  76     /**
  77      * Get the maximum self time
  78      *
  79      * @return The maximum self time
  80      */
  81     public long getMaxSelfTime() {
  82         return fMaxSelfTime;
  83     }
  84
  85     /**
  86      * Get the minimum self time
  87      *
  88      * @return The minimum self time
  89      */
  90     public long getMinSelfTime() {
  91         return fMinSelfTime;
  92     }
  93
  94     /**
  95      * Get the average self time
  96      *
  97      * @return The average self time
  98      */
  99     public double getAverageSelfTime() {
 100         return fSelfTimeAverage;
 101     }
 102
 103     /**
 104      * Get the standard deviation of the self time
 105      *
 106      * @return The standard deviation of the self time
 107      */
 108     public double getStdDevSelfTime() {
 109         long nbSegments = getNbSegments();
 110         return nbSegments > 2 ? Math.sqrt(fVariance / (nbSegments - 1)) : Double.NaN;
 111     }
 112
 113     /**
 114      * Initialize the maximum and minimum self time
 115      *
 116      * @param selfTime
 117      *            Self time
 118      */
 119     public void initializeMaxMinSelfTime(long selfTime) {
 120         fMaxSelfTime = selfTime;
 121         fMinSelfTime = selfTime;
 122         fSelfTimeAverage = selfTime;
 123     }
 124 }