Mercurial > jdk8-mips64-public > hotspot / file revision

 /*

  * Copyright 2001-2007 Sun Microsystems, Inc.  All Rights Reserved.

  * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.

  *

  * This code is free software; you can redistribute it and/or modify it

  * under the terms of the GNU General Public License version 2 only, as

  * published by the Free Software Foundation.

  *

  * This code is distributed in the hope that it will be useful, but WITHOUT

  * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or

  * FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License

  * version 2 for more details (a copy is included in the LICENSE file that

  * accompanied this code).

  *

  * You should have received a copy of the GNU General Public License version

  * 2 along with this work; if not, write to the Free Software Foundation,

  * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.

  *

  * Please contact Sun Microsystems, Inc., 4150 Network Circle, Santa Clara,

  * CA 95054 USA or visit www.sun.com if you need additional information or

  * have any questions.

  *

  */

 /**

  **  This file contains a few classes that represent number sequence,

  **  x1, x2, x3, ..., xN, and can calculate their avg, max, and sd.

  **

  **  Here's a quick description of the classes:

  **

  **    AbsSeq: abstract superclass

  **    NumberSeq: the sequence is assumed to be very long and the

  **      maximum, avg, sd, davg, and dsd are calculated over all its elements

  **    TruncatedSeq: this class keeps track of the last L elements

  **      of the sequence and calculates avg, max, and sd only over them

  **/

 #define DEFAULT_ALPHA_VALUE 0.7

 class AbsSeq {

 private:

   void init(double alpha);

 protected:

   int    _num; // the number of elements in the sequence

   double _sum; // the sum of the elements in the sequence

   double _sum_of_squares; // the sum of squares of the elements in the sequence

   double _davg; // decaying average

   double _dvariance; // decaying variance

   double _alpha; // factor for the decaying average / variance

   // This is what we divide with to get the average. In a standard

   // number sequence, this should just be the number of elements in it.

   virtual double total() const { return (double) _num; };

 public:

   AbsSeq(double alpha = DEFAULT_ALPHA_VALUE);

   virtual void add(double val); // adds a new element to the sequence

   void add(unsigned val) { add((double) val); }

   virtual double maximum() const = 0; // maximum element in the sequence

   virtual double last() const = 0; // last element added in the sequence

   // the number of elements in the sequence

   int num() const { return _num; }

   // the sum of the elements in the sequence

   double sum() const { return _sum; }

   double avg() const; // the average of the sequence

   double variance() const; // the variance of the sequence

   double sd() const; // the standard deviation of the sequence

   double davg() const; // decaying average

   double dvariance() const; // decaying variance

   double dsd() const; // decaying "standard deviation"

 };

 class NumberSeq: public AbsSeq {

 private:

   bool check_nums(NumberSeq* total, int n, NumberSeq** parts);

 protected:

   double _last;

   double _maximum; // keep track of maximum value

 public:

   NumberSeq(double alpha = DEFAULT_ALPHA_VALUE);

   NumberSeq(NumberSeq* total, int n_parts, NumberSeq** parts);

   virtual void add(double val);

   virtual double maximum() const { return _maximum; }

   virtual double last() const { return _last; }

 };

 class TruncatedSeq: public AbsSeq {

 private:

   enum PrivateConstants {

     DefaultSeqLength = 10

   };

   void init();

 protected:

   double *_sequence; // buffers the last L elements in the sequence

   int     _length; // this is L

   int     _next;   // oldest slot in the array, i.e. next to be overwritten

 public:

   // accepts a value for L

   TruncatedSeq(int length = DefaultSeqLength,

                double alpha = DEFAULT_ALPHA_VALUE);

   virtual void add(double val);

   virtual double maximum() const;

   virtual double last() const; // the last value added to the sequence

   double oldest() const; // the oldest valid value in the sequence

   double predict_next() const; // prediction based on linear regression

 };