statistics.hh revision 9863:9483739f83ee
1/*
2 * Copyright (c) 2003-2005 The Regents of The University of Michigan
3 * All rights reserved.
4 *
5 * Redistribution and use in source and binary forms, with or without
6 * modification, are permitted provided that the following conditions are
7 * met: redistributions of source code must retain the above copyright
8 * notice, this list of conditions and the following disclaimer;
9 * redistributions in binary form must reproduce the above copyright
10 * notice, this list of conditions and the following disclaimer in the
11 * documentation and/or other materials provided with the distribution;
12 * neither the name of the copyright holders nor the names of its
13 * contributors may be used to endorse or promote products derived from
14 * this software without specific prior written permission.
15 *
16 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
17 * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
18 * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
19 * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
20 * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
21 * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
22 * LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
23 * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
24 * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
25 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
26 * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
27 *
28 * Authors: Nathan Binkert
29 */
30
31/** @file
32 * Declaration of Statistics objects.
33 */
34
35/**
36* @todo
37*
38* Generalized N-dimensinal vector
39* documentation
40* key stats
41* interval stats
42*   -- these both can use the same function that prints out a
43*   specific set of stats
44* VectorStandardDeviation totals
45* Document Namespaces
46*/
47#ifndef __BASE_STATISTICS_HH__
48#define __BASE_STATISTICS_HH__
49
50#include <algorithm>
51#include <cassert>
52#ifdef __SUNPRO_CC
53#include <math.h>
54#endif
55#include <cmath>
56#include <functional>
57#include <iosfwd>
58#include <list>
59#include <map>
60#include <string>
61#include <vector>
62
63#include "base/stats/info.hh"
64#include "base/stats/output.hh"
65#include "base/stats/types.hh"
66#include "base/cast.hh"
67#include "base/cprintf.hh"
68#include "base/intmath.hh"
69#include "base/refcnt.hh"
70#include "base/str.hh"
71#include "base/types.hh"
72
73class Callback;
74
75/** The current simulated tick. */
76extern Tick curTick();
77
78/* A namespace for all of the Statistics */
79namespace Stats {
80
81template <class Stat, class Base>
82class InfoProxy : public Base
83{
84  protected:
85    Stat &s;
86
87  public:
88    InfoProxy(Stat &stat) : s(stat) {}
89
90    bool check() const { return s.check(); }
91    void prepare() { s.prepare(); }
92    void reset() { s.reset(); }
93    void
94    visit(Output &visitor)
95    {
96        visitor.visit(*static_cast<Base *>(this));
97    }
98    bool zero() const { return s.zero(); }
99};
100
101template <class Stat>
102class ScalarInfoProxy : public InfoProxy<Stat, ScalarInfo>
103{
104  public:
105    ScalarInfoProxy(Stat &stat) : InfoProxy<Stat, ScalarInfo>(stat) {}
106
107    Counter value() const { return this->s.value(); }
108    Result result() const { return this->s.result(); }
109    Result total() const { return this->s.total(); }
110};
111
112template <class Stat>
113class VectorInfoProxy : public InfoProxy<Stat, VectorInfo>
114{
115  protected:
116    mutable VCounter cvec;
117    mutable VResult rvec;
118
119  public:
120    VectorInfoProxy(Stat &stat) : InfoProxy<Stat, VectorInfo>(stat) {}
121
122    size_type size() const { return this->s.size(); }
123
124    VCounter &
125    value() const
126    {
127        this->s.value(cvec);
128        return cvec;
129    }
130
131    const VResult &
132    result() const
133    {
134        this->s.result(rvec);
135        return rvec;
136    }
137
138    Result total() const { return this->s.total(); }
139};
140
141template <class Stat>
142class DistInfoProxy : public InfoProxy<Stat, DistInfo>
143{
144  public:
145    DistInfoProxy(Stat &stat) : InfoProxy<Stat, DistInfo>(stat) {}
146};
147
148template <class Stat>
149class VectorDistInfoProxy : public InfoProxy<Stat, VectorDistInfo>
150{
151  public:
152    VectorDistInfoProxy(Stat &stat) : InfoProxy<Stat, VectorDistInfo>(stat) {}
153
154    size_type size() const { return this->s.size(); }
155};
156
157template <class Stat>
158class Vector2dInfoProxy : public InfoProxy<Stat, Vector2dInfo>
159{
160  public:
161    Vector2dInfoProxy(Stat &stat) : InfoProxy<Stat, Vector2dInfo>(stat) {}
162};
163
164struct StorageParams
165{
166    virtual ~StorageParams();
167};
168
169class InfoAccess
170{
171  protected:
172    /** Set up an info class for this statistic */
173    void setInfo(Info *info);
174    /** Save Storage class parameters if any */
175    void setParams(const StorageParams *params);
176    /** Save Storage class parameters if any */
177    void setInit();
178
179    /** Grab the information class for this statistic */
180    Info *info();
181    /** Grab the information class for this statistic */
182    const Info *info() const;
183
184  public:
185    /**
186     * Reset the stat to the default state.
187     */
188    void reset() { }
189
190    /**
191     * @return true if this stat has a value and satisfies its
192     * requirement as a prereq
193     */
194    bool zero() const { return true; }
195
196    /**
197     * Check that this stat has been set up properly and is ready for
198     * use
199     * @return true for success
200     */
201    bool check() const { return true; }
202};
203
204template <class Derived, template <class> class InfoProxyType>
205class DataWrap : public InfoAccess
206{
207  public:
208    typedef InfoProxyType<Derived> Info;
209
210  protected:
211    Derived &self() { return *static_cast<Derived *>(this); }
212
213  protected:
214    Info *
215    info()
216    {
217        return safe_cast<Info *>(InfoAccess::info());
218    }
219
220  public:
221    const Info *
222    info() const
223    {
224        return safe_cast<const Info *>(InfoAccess::info());
225    }
226
227  protected:
228    /**
229     * Copy constructor, copies are not allowed.
230     */
231    DataWrap(const DataWrap &stat);
232
233    /**
234     * Can't copy stats.
235     */
236    void operator=(const DataWrap &);
237
238  public:
239    DataWrap()
240    {
241        this->setInfo(new Info(self()));
242    }
243
244    /**
245     * Set the name and marks this stat to print at the end of simulation.
246     * @param name The new name.
247     * @return A reference to this stat.
248     */
249    Derived &
250    name(const std::string &name)
251    {
252        Info *info = this->info();
253        info->setName(name);
254        info->flags.set(display);
255        return this->self();
256    }
257    const std::string &name() const { return this->info()->name; }
258
259    /**
260     * Set the character(s) used between the name and vector number
261     * on vectors, dist, etc.
262     * @param _sep The new separator string
263     * @return A reference to this stat.
264     */
265    Derived &
266    setSeparator(const std::string &_sep)
267    {
268      this->info()->setSeparator(_sep);
269      return this->self();
270    }
271    const std::string &setSeparator() const
272    {
273      return this->info()->separatorString;
274    }
275
276    /**
277     * Set the description and marks this stat to print at the end of
278     * simulation.
279     * @param desc The new description.
280     * @return A reference to this stat.
281     */
282    Derived &
283    desc(const std::string &_desc)
284    {
285        this->info()->desc = _desc;
286        return this->self();
287    }
288
289    /**
290     * Set the precision and marks this stat to print at the end of simulation.
291     * @param _precision The new precision
292     * @return A reference to this stat.
293     */
294    Derived &
295    precision(int _precision)
296    {
297        this->info()->precision = _precision;
298        return this->self();
299    }
300
301    /**
302     * Set the flags and marks this stat to print at the end of simulation.
303     * @param f The new flags.
304     * @return A reference to this stat.
305     */
306    Derived &
307    flags(Flags _flags)
308    {
309        this->info()->flags.set(_flags);
310        return this->self();
311    }
312
313    /**
314     * Set the prerequisite stat and marks this stat to print at the end of
315     * simulation.
316     * @param prereq The prerequisite stat.
317     * @return A reference to this stat.
318     */
319    template <class Stat>
320    Derived &
321    prereq(const Stat &prereq)
322    {
323        this->info()->prereq = prereq.info();
324        return this->self();
325    }
326};
327
328template <class Derived, template <class> class InfoProxyType>
329class DataWrapVec : public DataWrap<Derived, InfoProxyType>
330{
331  public:
332    typedef InfoProxyType<Derived> Info;
333
334    DataWrapVec()
335    {}
336
337    DataWrapVec(const DataWrapVec &ref)
338    {}
339
340    // The following functions are specific to vectors.  If you use them
341    // in a non vector context, you will get a nice compiler error!
342
343    /**
344     * Set the subfield name for the given index, and marks this stat to print
345     * at the end of simulation.
346     * @param index The subfield index.
347     * @param name The new name of the subfield.
348     * @return A reference to this stat.
349     */
350    Derived &
351    subname(off_type index, const std::string &name)
352    {
353        Derived &self = this->self();
354        Info *info = self.info();
355
356        std::vector<std::string> &subn = info->subnames;
357        if (subn.size() <= index)
358            subn.resize(index + 1);
359        subn[index] = name;
360        return self;
361    }
362
363    // The following functions are specific to 2d vectors.  If you use
364    // them in a non vector context, you will get a nice compiler
365    // error because info doesn't have the right variables.
366
367    /**
368     * Set the subfield description for the given index and marks this stat to
369     * print at the end of simulation.
370     * @param index The subfield index.
371     * @param desc The new description of the subfield
372     * @return A reference to this stat.
373     */
374    Derived &
375    subdesc(off_type index, const std::string &desc)
376    {
377        Info *info = this->info();
378
379        std::vector<std::string> &subd = info->subdescs;
380        if (subd.size() <= index)
381            subd.resize(index + 1);
382        subd[index] = desc;
383
384        return this->self();
385    }
386
387    void
388    prepare()
389    {
390        Derived &self = this->self();
391        Info *info = this->info();
392
393        size_t size = self.size();
394        for (off_type i = 0; i < size; ++i)
395            self.data(i)->prepare(info);
396    }
397
398    void
399    reset()
400    {
401        Derived &self = this->self();
402        Info *info = this->info();
403
404        size_t size = self.size();
405        for (off_type i = 0; i < size; ++i)
406            self.data(i)->reset(info);
407    }
408};
409
410template <class Derived, template <class> class InfoProxyType>
411class DataWrapVec2d : public DataWrapVec<Derived, InfoProxyType>
412{
413  public:
414    typedef InfoProxyType<Derived> Info;
415
416    /**
417     * @warning This makes the assumption that if you're gonna subnames a 2d
418     * vector, you're subnaming across all y
419     */
420    Derived &
421    ysubnames(const char **names)
422    {
423        Derived &self = this->self();
424        Info *info = this->info();
425
426        info->y_subnames.resize(self.y);
427        for (off_type i = 0; i < self.y; ++i)
428            info->y_subnames[i] = names[i];
429        return self;
430    }
431
432    Derived &
433    ysubname(off_type index, const std::string &subname)
434    {
435        Derived &self = this->self();
436        Info *info = this->info();
437
438        assert(index < self.y);
439        info->y_subnames.resize(self.y);
440        info->y_subnames[index] = subname.c_str();
441        return self;
442    }
443
444    std::string
445    ysubname(off_type i) const
446    {
447        return this->info()->y_subnames[i];
448    }
449
450};
451
452//////////////////////////////////////////////////////////////////////
453//
454// Simple Statistics
455//
456//////////////////////////////////////////////////////////////////////
457
458/**
459 * Templatized storage and interface for a simple scalar stat.
460 */
461class StatStor
462{
463  private:
464    /** The statistic value. */
465    Counter data;
466
467  public:
468    struct Params : public StorageParams {};
469
470  public:
471    /**
472     * Builds this storage element and calls the base constructor of the
473     * datatype.
474     */
475    StatStor(Info *info)
476        : data(Counter())
477    { }
478
479    /**
480     * The the stat to the given value.
481     * @param val The new value.
482     */
483    void set(Counter val) { data = val; }
484    /**
485     * Increment the stat by the given value.
486     * @param val The new value.
487     */
488    void inc(Counter val) { data += val; }
489    /**
490     * Decrement the stat by the given value.
491     * @param val The new value.
492     */
493    void dec(Counter val) { data -= val; }
494    /**
495     * Return the value of this stat as its base type.
496     * @return The value of this stat.
497     */
498    Counter value() const { return data; }
499    /**
500     * Return the value of this stat as a result type.
501     * @return The value of this stat.
502     */
503    Result result() const { return (Result)data; }
504    /**
505     * Prepare stat data for dumping or serialization
506     */
507    void prepare(Info *info) { }
508    /**
509     * Reset stat value to default
510     */
511    void reset(Info *info) { data = Counter(); }
512
513    /**
514     * @return true if zero value
515     */
516    bool zero() const { return data == Counter(); }
517};
518
519/**
520 * Templatized storage and interface to a per-tick average stat. This keeps
521 * a current count and updates a total (count * ticks) when this count
522 * changes. This allows the quick calculation of a per tick count of the item
523 * being watched. This is good for keeping track of residencies in structures
524 * among other things.
525 */
526class AvgStor
527{
528  private:
529    /** The current count. */
530    Counter current;
531    /** The tick of the last reset */
532    Tick lastReset;
533    /** The total count for all tick. */
534    mutable Result total;
535    /** The tick that current last changed. */
536    mutable Tick last;
537
538  public:
539    struct Params : public StorageParams {};
540
541  public:
542    /**
543     * Build and initializes this stat storage.
544     */
545    AvgStor(Info *info)
546        : current(0), lastReset(0), total(0), last(0)
547    { }
548
549    /**
550     * Set the current count to the one provided, update the total and last
551     * set values.
552     * @param val The new count.
553     */
554    void
555    set(Counter val)
556    {
557        total += current * (curTick() - last);
558        last = curTick();
559        current = val;
560    }
561
562    /**
563     * Increment the current count by the provided value, calls set.
564     * @param val The amount to increment.
565     */
566    void inc(Counter val) { set(current + val); }
567
568    /**
569     * Deccrement the current count by the provided value, calls set.
570     * @param val The amount to decrement.
571     */
572    void dec(Counter val) { set(current - val); }
573
574    /**
575     * Return the current count.
576     * @return The current count.
577     */
578    Counter value() const { return current; }
579
580    /**
581     * Return the current average.
582     * @return The current average.
583     */
584    Result
585    result() const
586    {
587        assert(last == curTick());
588        return (Result)(total + current) / (Result)(curTick() - lastReset + 1);
589    }
590
591    /**
592     * @return true if zero value
593     */
594    bool zero() const { return total == 0.0; }
595
596    /**
597     * Prepare stat data for dumping or serialization
598     */
599    void
600    prepare(Info *info)
601    {
602        total += current * (curTick() - last);
603        last = curTick();
604    }
605
606    /**
607     * Reset stat value to default
608     */
609    void
610    reset(Info *info)
611    {
612        total = 0.0;
613        last = curTick();
614        lastReset = curTick();
615    }
616
617};
618
619/**
620 * Implementation of a scalar stat. The type of stat is determined by the
621 * Storage template.
622 */
623template <class Derived, class Stor>
624class ScalarBase : public DataWrap<Derived, ScalarInfoProxy>
625{
626  public:
627    typedef Stor Storage;
628    typedef typename Stor::Params Params;
629
630  protected:
631    /** The storage of this stat. */
632    char storage[sizeof(Storage)] __attribute__ ((aligned (8)));
633
634  protected:
635    /**
636     * Retrieve the storage.
637     * @param index The vector index to access.
638     * @return The storage object at the given index.
639     */
640    Storage *
641    data()
642    {
643        return reinterpret_cast<Storage *>(storage);
644    }
645
646    /**
647     * Retrieve a const pointer to the storage.
648     * for the given index.
649     * @param index The vector index to access.
650     * @return A const pointer to the storage object at the given index.
651     */
652    const Storage *
653    data() const
654    {
655        return reinterpret_cast<const Storage *>(storage);
656    }
657
658    void
659    doInit()
660    {
661        new (storage) Storage(this->info());
662        this->setInit();
663    }
664
665  public:
666    /**
667     * Return the current value of this stat as its base type.
668     * @return The current value.
669     */
670    Counter value() const { return data()->value(); }
671
672  public:
673    ScalarBase()
674    {
675        this->doInit();
676    }
677
678  public:
679    // Common operators for stats
680    /**
681     * Increment the stat by 1. This calls the associated storage object inc
682     * function.
683     */
684    void operator++() { data()->inc(1); }
685    /**
686     * Decrement the stat by 1. This calls the associated storage object dec
687     * function.
688     */
689    void operator--() { data()->dec(1); }
690
691    /** Increment the stat by 1. */
692    void operator++(int) { ++*this; }
693    /** Decrement the stat by 1. */
694    void operator--(int) { --*this; }
695
696    /**
697     * Set the data value to the given value. This calls the associated storage
698     * object set function.
699     * @param v The new value.
700     */
701    template <typename U>
702    void operator=(const U &v) { data()->set(v); }
703
704    /**
705     * Increment the stat by the given value. This calls the associated
706     * storage object inc function.
707     * @param v The value to add.
708     */
709    template <typename U>
710    void operator+=(const U &v) { data()->inc(v); }
711
712    /**
713     * Decrement the stat by the given value. This calls the associated
714     * storage object dec function.
715     * @param v The value to substract.
716     */
717    template <typename U>
718    void operator-=(const U &v) { data()->dec(v); }
719
720    /**
721     * Return the number of elements, always 1 for a scalar.
722     * @return 1.
723     */
724    size_type size() const { return 1; }
725
726    Counter value() { return data()->value(); }
727
728    Result result() { return data()->result(); }
729
730    Result total() { return result(); }
731
732    bool zero() { return result() == 0.0; }
733
734    void reset() { data()->reset(this->info()); }
735    void prepare() { data()->prepare(this->info()); }
736};
737
738class ProxyInfo : public ScalarInfo
739{
740  public:
741    std::string str() const { return to_string(value()); }
742    size_type size() const { return 1; }
743    bool check() const { return true; }
744    void prepare() { }
745    void reset() { }
746    bool zero() const { return value() == 0; }
747
748    void visit(Output &visitor) { visitor.visit(*this); }
749};
750
751template <class T>
752class ValueProxy : public ProxyInfo
753{
754  private:
755    T *scalar;
756
757  public:
758    ValueProxy(T &val) : scalar(&val) {}
759    Counter value() const { return *scalar; }
760    Result result() const { return *scalar; }
761    Result total() const { return *scalar; }
762};
763
764template <class T>
765class FunctorProxy : public ProxyInfo
766{
767  private:
768    T *functor;
769
770  public:
771    FunctorProxy(T &func) : functor(&func) {}
772    Counter value() const { return (*functor)(); }
773    Result result() const { return (*functor)(); }
774    Result total() const { return (*functor)(); }
775};
776
777template <class Derived>
778class ValueBase : public DataWrap<Derived, ScalarInfoProxy>
779{
780  private:
781    ProxyInfo *proxy;
782
783  public:
784    ValueBase() : proxy(NULL) { }
785    ~ValueBase() { if (proxy) delete proxy; }
786
787    template <class T>
788    Derived &
789    scalar(T &value)
790    {
791        proxy = new ValueProxy<T>(value);
792        this->setInit();
793        return this->self();
794    }
795
796    template <class T>
797    Derived &
798    functor(T &func)
799    {
800        proxy = new FunctorProxy<T>(func);
801        this->setInit();
802        return this->self();
803    }
804
805    Counter value() { return proxy->value(); }
806    Result result() const { return proxy->result(); }
807    Result total() const { return proxy->total(); };
808    size_type size() const { return proxy->size(); }
809
810    std::string str() const { return proxy->str(); }
811    bool zero() const { return proxy->zero(); }
812    bool check() const { return proxy != NULL; }
813    void prepare() { }
814    void reset() { }
815};
816
817//////////////////////////////////////////////////////////////////////
818//
819// Vector Statistics
820//
821//////////////////////////////////////////////////////////////////////
822
823/**
824 * A proxy class to access the stat at a given index in a VectorBase stat.
825 * Behaves like a ScalarBase.
826 */
827template <class Stat>
828class ScalarProxy
829{
830  private:
831    /** Pointer to the parent Vector. */
832    Stat &stat;
833
834    /** The index to access in the parent VectorBase. */
835    off_type index;
836
837  public:
838    /**
839     * Return the current value of this stat as its base type.
840     * @return The current value.
841     */
842    Counter value() const { return stat.data(index)->value(); }
843
844    /**
845     * Return the current value of this statas a result type.
846     * @return The current value.
847     */
848    Result result() const { return stat.data(index)->result(); }
849
850  public:
851    /**
852     * Create and initialize this proxy, do not register it with the database.
853     * @param i The index to access.
854     */
855    ScalarProxy(Stat &s, off_type i)
856        : stat(s), index(i)
857    {
858    }
859
860    /**
861     * Create a copy of the provided ScalarProxy.
862     * @param sp The proxy to copy.
863     */
864    ScalarProxy(const ScalarProxy &sp)
865        : stat(sp.stat), index(sp.index)
866    {}
867
868    /**
869     * Set this proxy equal to the provided one.
870     * @param sp The proxy to copy.
871     * @return A reference to this proxy.
872     */
873    const ScalarProxy &
874    operator=(const ScalarProxy &sp)
875    {
876        stat = sp.stat;
877        index = sp.index;
878        return *this;
879    }
880
881  public:
882    // Common operators for stats
883    /**
884     * Increment the stat by 1. This calls the associated storage object inc
885     * function.
886     */
887    void operator++() { stat.data(index)->inc(1); }
888    /**
889     * Decrement the stat by 1. This calls the associated storage object dec
890     * function.
891     */
892    void operator--() { stat.data(index)->dec(1); }
893
894    /** Increment the stat by 1. */
895    void operator++(int) { ++*this; }
896    /** Decrement the stat by 1. */
897    void operator--(int) { --*this; }
898
899    /**
900     * Set the data value to the given value. This calls the associated storage
901     * object set function.
902     * @param v The new value.
903     */
904    template <typename U>
905    void
906    operator=(const U &v)
907    {
908        stat.data(index)->set(v);
909    }
910
911    /**
912     * Increment the stat by the given value. This calls the associated
913     * storage object inc function.
914     * @param v The value to add.
915     */
916    template <typename U>
917    void
918    operator+=(const U &v)
919    {
920        stat.data(index)->inc(v);
921    }
922
923    /**
924     * Decrement the stat by the given value. This calls the associated
925     * storage object dec function.
926     * @param v The value to substract.
927     */
928    template <typename U>
929    void
930    operator-=(const U &v)
931    {
932        stat.data(index)->dec(v);
933    }
934
935    /**
936     * Return the number of elements, always 1 for a scalar.
937     * @return 1.
938     */
939    size_type size() const { return 1; }
940
941  public:
942    std::string
943    str() const
944    {
945        return csprintf("%s[%d]", stat.info()->name, index);
946    }
947};
948
949/**
950 * Implementation of a vector of stats. The type of stat is determined by the
951 * Storage class. @sa ScalarBase
952 */
953template <class Derived, class Stor>
954class VectorBase : public DataWrapVec<Derived, VectorInfoProxy>
955{
956  public:
957    typedef Stor Storage;
958    typedef typename Stor::Params Params;
959
960    /** Proxy type */
961    typedef ScalarProxy<Derived> Proxy;
962    friend class ScalarProxy<Derived>;
963    friend class DataWrapVec<Derived, VectorInfoProxy>;
964
965  protected:
966    /** The storage of this stat. */
967    Storage *storage;
968    size_type _size;
969
970  protected:
971    /**
972     * Retrieve the storage.
973     * @param index The vector index to access.
974     * @return The storage object at the given index.
975     */
976    Storage *data(off_type index) { return &storage[index]; }
977
978    /**
979     * Retrieve a const pointer to the storage.
980     * @param index The vector index to access.
981     * @return A const pointer to the storage object at the given index.
982     */
983    const Storage *data(off_type index) const { return &storage[index]; }
984
985    void
986    doInit(size_type s)
987    {
988        assert(s > 0 && "size must be positive!");
989        assert(!storage && "already initialized");
990        _size = s;
991
992        char *ptr = new char[_size * sizeof(Storage)];
993        storage = reinterpret_cast<Storage *>(ptr);
994
995        for (off_type i = 0; i < _size; ++i)
996            new (&storage[i]) Storage(this->info());
997
998        this->setInit();
999    }
1000
1001  public:
1002    void
1003    value(VCounter &vec) const
1004    {
1005        vec.resize(size());
1006        for (off_type i = 0; i < size(); ++i)
1007            vec[i] = data(i)->value();
1008    }
1009
1010    /**
1011     * Copy the values to a local vector and return a reference to it.
1012     * @return A reference to a vector of the stat values.
1013     */
1014    void
1015    result(VResult &vec) const
1016    {
1017        vec.resize(size());
1018        for (off_type i = 0; i < size(); ++i)
1019            vec[i] = data(i)->result();
1020    }
1021
1022    /**
1023     * Return a total of all entries in this vector.
1024     * @return The total of all vector entries.
1025     */
1026    Result
1027    total() const
1028    {
1029        Result total = 0.0;
1030        for (off_type i = 0; i < size(); ++i)
1031            total += data(i)->result();
1032        return total;
1033    }
1034
1035    /**
1036     * @return the number of elements in this vector.
1037     */
1038    size_type size() const { return _size; }
1039
1040    bool
1041    zero() const
1042    {
1043        for (off_type i = 0; i < size(); ++i)
1044            if (data(i)->zero())
1045                return false;
1046        return true;
1047    }
1048
1049    bool
1050    check() const
1051    {
1052        return storage != NULL;
1053    }
1054
1055  public:
1056    VectorBase()
1057        : storage(NULL)
1058    {}
1059
1060    ~VectorBase()
1061    {
1062        if (!storage)
1063            return;
1064
1065        for (off_type i = 0; i < _size; ++i)
1066            data(i)->~Storage();
1067        delete [] reinterpret_cast<char *>(storage);
1068    }
1069
1070    /**
1071     * Set this vector to have the given size.
1072     * @param size The new size.
1073     * @return A reference to this stat.
1074     */
1075    Derived &
1076    init(size_type size)
1077    {
1078        Derived &self = this->self();
1079        self.doInit(size);
1080        return self;
1081    }
1082
1083    /**
1084     * Return a reference (ScalarProxy) to the stat at the given index.
1085     * @param index The vector index to access.
1086     * @return A reference of the stat.
1087     */
1088    Proxy
1089    operator[](off_type index)
1090    {
1091        assert (index >= 0 && index < size());
1092        return Proxy(this->self(), index);
1093    }
1094};
1095
1096template <class Stat>
1097class VectorProxy
1098{
1099  private:
1100    Stat &stat;
1101    off_type offset;
1102    size_type len;
1103
1104  private:
1105    mutable VResult vec;
1106
1107    typename Stat::Storage *
1108    data(off_type index)
1109    {
1110        assert(index < len);
1111        return stat.data(offset + index);
1112    }
1113
1114    const typename Stat::Storage *
1115    data(off_type index) const
1116    {
1117        assert(index < len);
1118        return stat.data(offset + index);
1119    }
1120
1121  public:
1122    const VResult &
1123    result() const
1124    {
1125        vec.resize(size());
1126
1127        for (off_type i = 0; i < size(); ++i)
1128            vec[i] = data(i)->result();
1129
1130        return vec;
1131    }
1132
1133    Result
1134    total() const
1135    {
1136        Result total = 0.0;
1137        for (off_type i = 0; i < size(); ++i)
1138            total += data(i)->result();
1139        return total;
1140    }
1141
1142  public:
1143    VectorProxy(Stat &s, off_type o, size_type l)
1144        : stat(s), offset(o), len(l)
1145    {
1146    }
1147
1148    VectorProxy(const VectorProxy &sp)
1149        : stat(sp.stat), offset(sp.offset), len(sp.len)
1150    {
1151    }
1152
1153    const VectorProxy &
1154    operator=(const VectorProxy &sp)
1155    {
1156        stat = sp.stat;
1157        offset = sp.offset;
1158        len = sp.len;
1159        return *this;
1160    }
1161
1162    ScalarProxy<Stat>
1163    operator[](off_type index)
1164    {
1165        assert (index >= 0 && index < size());
1166        return ScalarProxy<Stat>(stat, offset + index);
1167    }
1168
1169    size_type size() const { return len; }
1170};
1171
1172template <class Derived, class Stor>
1173class Vector2dBase : public DataWrapVec2d<Derived, Vector2dInfoProxy>
1174{
1175  public:
1176    typedef Vector2dInfoProxy<Derived> Info;
1177    typedef Stor Storage;
1178    typedef typename Stor::Params Params;
1179    typedef VectorProxy<Derived> Proxy;
1180    friend class ScalarProxy<Derived>;
1181    friend class VectorProxy<Derived>;
1182    friend class DataWrapVec<Derived, Vector2dInfoProxy>;
1183    friend class DataWrapVec2d<Derived, Vector2dInfoProxy>;
1184
1185  protected:
1186    size_type x;
1187    size_type y;
1188    size_type _size;
1189    Storage *storage;
1190
1191  protected:
1192    Storage *data(off_type index) { return &storage[index]; }
1193    const Storage *data(off_type index) const { return &storage[index]; }
1194
1195  public:
1196    Vector2dBase()
1197        : storage(NULL)
1198    {}
1199
1200    ~Vector2dBase()
1201    {
1202        if (!storage)
1203            return;
1204
1205        for (off_type i = 0; i < _size; ++i)
1206            data(i)->~Storage();
1207        delete [] reinterpret_cast<char *>(storage);
1208    }
1209
1210    Derived &
1211    init(size_type _x, size_type _y)
1212    {
1213        assert(_x > 0 && _y > 0 && "sizes must be positive!");
1214        assert(!storage && "already initialized");
1215
1216        Derived &self = this->self();
1217        Info *info = this->info();
1218
1219        x = _x;
1220        y = _y;
1221        info->x = _x;
1222        info->y = _y;
1223        _size = x * y;
1224
1225        char *ptr = new char[_size * sizeof(Storage)];
1226        storage = reinterpret_cast<Storage *>(ptr);
1227
1228        for (off_type i = 0; i < _size; ++i)
1229            new (&storage[i]) Storage(info);
1230
1231        this->setInit();
1232
1233        return self;
1234    }
1235
1236    Proxy
1237    operator[](off_type index)
1238    {
1239        off_type offset = index * y;
1240        assert (index >= 0 && offset + y <= size());
1241        return Proxy(this->self(), offset, y);
1242    }
1243
1244
1245    size_type
1246    size() const
1247    {
1248        return _size;
1249    }
1250
1251    bool
1252    zero() const
1253    {
1254        return data(0)->zero();
1255#if 0
1256        for (off_type i = 0; i < size(); ++i)
1257            if (!data(i)->zero())
1258                return false;
1259        return true;
1260#endif
1261    }
1262
1263    void
1264    prepare()
1265    {
1266        Info *info = this->info();
1267        size_type size = this->size();
1268
1269        for (off_type i = 0; i < size; ++i)
1270            data(i)->prepare(info);
1271
1272        info->cvec.resize(size);
1273        for (off_type i = 0; i < size; ++i)
1274            info->cvec[i] = data(i)->value();
1275    }
1276
1277    /**
1278     * Reset stat value to default
1279     */
1280    void
1281    reset()
1282    {
1283        Info *info = this->info();
1284        size_type size = this->size();
1285        for (off_type i = 0; i < size; ++i)
1286            data(i)->reset(info);
1287    }
1288
1289    bool
1290    check() const
1291    {
1292        return storage != NULL;
1293    }
1294};
1295
1296//////////////////////////////////////////////////////////////////////
1297//
1298// Non formula statistics
1299//
1300//////////////////////////////////////////////////////////////////////
1301/** The parameters for a distribution stat. */
1302struct DistParams : public StorageParams
1303{
1304    const DistType type;
1305    DistParams(DistType t) : type(t) {}
1306};
1307
1308/**
1309 * Templatized storage and interface for a distrbution stat.
1310 */
1311class DistStor
1312{
1313  public:
1314    /** The parameters for a distribution stat. */
1315    struct Params : public DistParams
1316    {
1317        /** The minimum value to track. */
1318        Counter min;
1319        /** The maximum value to track. */
1320        Counter max;
1321        /** The number of entries in each bucket. */
1322        Counter bucket_size;
1323        /** The number of buckets. Equal to (max-min)/bucket_size. */
1324        size_type buckets;
1325
1326        Params() : DistParams(Dist) {}
1327    };
1328
1329  private:
1330    /** The minimum value to track. */
1331    Counter min_track;
1332    /** The maximum value to track. */
1333    Counter max_track;
1334    /** The number of entries in each bucket. */
1335    Counter bucket_size;
1336
1337    /** The smallest value sampled. */
1338    Counter min_val;
1339    /** The largest value sampled. */
1340    Counter max_val;
1341    /** The number of values sampled less than min. */
1342    Counter underflow;
1343    /** The number of values sampled more than max. */
1344    Counter overflow;
1345    /** The current sum. */
1346    Counter sum;
1347    /** The sum of squares. */
1348    Counter squares;
1349    /** The number of samples. */
1350    Counter samples;
1351    /** Counter for each bucket. */
1352    VCounter cvec;
1353
1354  public:
1355    DistStor(Info *info)
1356        : cvec(safe_cast<const Params *>(info->storageParams)->buckets)
1357    {
1358        reset(info);
1359    }
1360
1361    /**
1362     * Add a value to the distribution for the given number of times.
1363     * @param val The value to add.
1364     * @param number The number of times to add the value.
1365     */
1366    void
1367    sample(Counter val, int number)
1368    {
1369        if (val < min_track)
1370            underflow += number;
1371        else if (val > max_track)
1372            overflow += number;
1373        else {
1374            size_type index =
1375                (size_type)std::floor((val - min_track) / bucket_size);
1376            assert(index < size());
1377            cvec[index] += number;
1378        }
1379
1380        if (val < min_val)
1381            min_val = val;
1382
1383        if (val > max_val)
1384            max_val = val;
1385
1386        sum += val * number;
1387        squares += val * val * number;
1388        samples += number;
1389    }
1390
1391    /**
1392     * Return the number of buckets in this distribution.
1393     * @return the number of buckets.
1394     */
1395    size_type size() const { return cvec.size(); }
1396
1397    /**
1398     * Returns true if any calls to sample have been made.
1399     * @return True if any values have been sampled.
1400     */
1401    bool
1402    zero() const
1403    {
1404        return samples == Counter();
1405    }
1406
1407    void
1408    prepare(Info *info, DistData &data)
1409    {
1410        const Params *params = safe_cast<const Params *>(info->storageParams);
1411
1412        assert(params->type == Dist);
1413        data.type = params->type;
1414        data.min = params->min;
1415        data.max = params->max;
1416        data.bucket_size = params->bucket_size;
1417
1418        data.min_val = (min_val == CounterLimits::max()) ? 0 : min_val;
1419        data.max_val = (max_val == CounterLimits::min()) ? 0 : max_val;
1420        data.underflow = underflow;
1421        data.overflow = overflow;
1422
1423        data.cvec.resize(params->buckets);
1424        for (off_type i = 0; i < params->buckets; ++i)
1425            data.cvec[i] = cvec[i];
1426
1427        data.sum = sum;
1428        data.squares = squares;
1429        data.samples = samples;
1430    }
1431
1432    /**
1433     * Reset stat value to default
1434     */
1435    void
1436    reset(Info *info)
1437    {
1438        const Params *params = safe_cast<const Params *>(info->storageParams);
1439        min_track = params->min;
1440        max_track = params->max;
1441        bucket_size = params->bucket_size;
1442
1443        min_val = CounterLimits::max();
1444        max_val = CounterLimits::min();
1445        underflow = Counter();
1446        overflow = Counter();
1447
1448        size_type size = cvec.size();
1449        for (off_type i = 0; i < size; ++i)
1450            cvec[i] = Counter();
1451
1452        sum = Counter();
1453        squares = Counter();
1454        samples = Counter();
1455    }
1456};
1457
1458/**
1459 * Templatized storage and interface for a histogram stat.
1460 */
1461class HistStor
1462{
1463  public:
1464    /** The parameters for a distribution stat. */
1465    struct Params : public DistParams
1466    {
1467        /** The number of buckets.. */
1468        size_type buckets;
1469
1470        Params() : DistParams(Hist) {}
1471    };
1472
1473  private:
1474    /** The minimum value to track. */
1475    Counter min_bucket;
1476    /** The maximum value to track. */
1477    Counter max_bucket;
1478    /** The number of entries in each bucket. */
1479    Counter bucket_size;
1480
1481    /** The current sum. */
1482    Counter sum;
1483    /** The sum of logarithm of each sample, used to compute geometric mean. */
1484    Counter logs;
1485    /** The sum of squares. */
1486    Counter squares;
1487    /** The number of samples. */
1488    Counter samples;
1489    /** Counter for each bucket. */
1490    VCounter cvec;
1491
1492  public:
1493    HistStor(Info *info)
1494        : cvec(safe_cast<const Params *>(info->storageParams)->buckets)
1495    {
1496        reset(info);
1497    }
1498
1499    void grow_up();
1500    void grow_out();
1501    void grow_convert();
1502
1503    /**
1504     * Add a value to the distribution for the given number of times.
1505     * @param val The value to add.
1506     * @param number The number of times to add the value.
1507     */
1508    void
1509    sample(Counter val, int number)
1510    {
1511        assert(min_bucket < max_bucket);
1512        if (val < min_bucket) {
1513            if (min_bucket == 0)
1514                grow_convert();
1515
1516            while (val < min_bucket)
1517                grow_out();
1518        } else if (val >= max_bucket + bucket_size) {
1519            if (min_bucket == 0) {
1520                while (val >= max_bucket + bucket_size)
1521                    grow_up();
1522            } else {
1523                while (val >= max_bucket + bucket_size)
1524                    grow_out();
1525            }
1526        }
1527
1528        size_type index =
1529            (int64_t)std::floor((val - min_bucket) / bucket_size);
1530
1531        assert(index >= 0 && index < size());
1532        cvec[index] += number;
1533
1534        sum += val * number;
1535        squares += val * val * number;
1536        logs += log(val) * number;
1537        samples += number;
1538    }
1539
1540    /**
1541     * Return the number of buckets in this distribution.
1542     * @return the number of buckets.
1543     */
1544    size_type size() const { return cvec.size(); }
1545
1546    /**
1547     * Returns true if any calls to sample have been made.
1548     * @return True if any values have been sampled.
1549     */
1550    bool
1551    zero() const
1552    {
1553        return samples == Counter();
1554    }
1555
1556    void
1557    prepare(Info *info, DistData &data)
1558    {
1559        const Params *params = safe_cast<const Params *>(info->storageParams);
1560
1561        assert(params->type == Hist);
1562        data.type = params->type;
1563        data.min = min_bucket;
1564        data.max = max_bucket + bucket_size - 1;
1565        data.bucket_size = bucket_size;
1566
1567        data.min_val = min_bucket;
1568        data.max_val = max_bucket;
1569
1570        int buckets = params->buckets;
1571        data.cvec.resize(buckets);
1572        for (off_type i = 0; i < buckets; ++i)
1573            data.cvec[i] = cvec[i];
1574
1575        data.sum = sum;
1576        data.logs = logs;
1577        data.squares = squares;
1578        data.samples = samples;
1579    }
1580
1581    /**
1582     * Reset stat value to default
1583     */
1584    void
1585    reset(Info *info)
1586    {
1587        const Params *params = safe_cast<const Params *>(info->storageParams);
1588        min_bucket = 0;
1589        max_bucket = params->buckets - 1;
1590        bucket_size = 1;
1591
1592        size_type size = cvec.size();
1593        for (off_type i = 0; i < size; ++i)
1594            cvec[i] = Counter();
1595
1596        sum = Counter();
1597        squares = Counter();
1598        samples = Counter();
1599        logs = Counter();
1600    }
1601};
1602
1603/**
1604 * Templatized storage and interface for a distribution that calculates mean
1605 * and variance.
1606 */
1607class SampleStor
1608{
1609  public:
1610    struct Params : public DistParams
1611    {
1612        Params() : DistParams(Deviation) {}
1613    };
1614
1615  private:
1616    /** The current sum. */
1617    Counter sum;
1618    /** The sum of squares. */
1619    Counter squares;
1620    /** The number of samples. */
1621    Counter samples;
1622
1623  public:
1624    /**
1625     * Create and initialize this storage.
1626     */
1627    SampleStor(Info *info)
1628        : sum(Counter()), squares(Counter()), samples(Counter())
1629    { }
1630
1631    /**
1632     * Add a value the given number of times to this running average.
1633     * Update the running sum and sum of squares, increment the number of
1634     * values seen by the given number.
1635     * @param val The value to add.
1636     * @param number The number of times to add the value.
1637     */
1638    void
1639    sample(Counter val, int number)
1640    {
1641        Counter value = val * number;
1642        sum += value;
1643        squares += value * value;
1644        samples += number;
1645    }
1646
1647    /**
1648     * Return the number of entries in this stat, 1
1649     * @return 1.
1650     */
1651    size_type size() const { return 1; }
1652
1653    /**
1654     * Return true if no samples have been added.
1655     * @return True if no samples have been added.
1656     */
1657    bool zero() const { return samples == Counter(); }
1658
1659    void
1660    prepare(Info *info, DistData &data)
1661    {
1662        const Params *params = safe_cast<const Params *>(info->storageParams);
1663
1664        assert(params->type == Deviation);
1665        data.type = params->type;
1666        data.sum = sum;
1667        data.squares = squares;
1668        data.samples = samples;
1669    }
1670
1671    /**
1672     * Reset stat value to default
1673     */
1674    void
1675    reset(Info *info)
1676    {
1677        sum = Counter();
1678        squares = Counter();
1679        samples = Counter();
1680    }
1681};
1682
1683/**
1684 * Templatized storage for distribution that calculates per tick mean and
1685 * variance.
1686 */
1687class AvgSampleStor
1688{
1689  public:
1690    struct Params : public DistParams
1691    {
1692        Params() : DistParams(Deviation) {}
1693    };
1694
1695  private:
1696    /** Current total. */
1697    Counter sum;
1698    /** Current sum of squares. */
1699    Counter squares;
1700
1701  public:
1702    /**
1703     * Create and initialize this storage.
1704     */
1705    AvgSampleStor(Info *info)
1706        : sum(Counter()), squares(Counter())
1707    {}
1708
1709    /**
1710     * Add a value to the distribution for the given number of times.
1711     * Update the running sum and sum of squares.
1712     * @param val The value to add.
1713     * @param number The number of times to add the value.
1714     */
1715    void
1716    sample(Counter val, int number)
1717    {
1718        Counter value = val * number;
1719        sum += value;
1720        squares += value * value;
1721    }
1722
1723    /**
1724     * Return the number of entries, in this case 1.
1725     * @return 1.
1726     */
1727    size_type size() const { return 1; }
1728
1729    /**
1730     * Return true if no samples have been added.
1731     * @return True if the sum is zero.
1732     */
1733    bool zero() const { return sum == Counter(); }
1734
1735    void
1736    prepare(Info *info, DistData &data)
1737    {
1738        const Params *params = safe_cast<const Params *>(info->storageParams);
1739
1740        assert(params->type == Deviation);
1741        data.type = params->type;
1742        data.sum = sum;
1743        data.squares = squares;
1744        data.samples = curTick();
1745    }
1746
1747    /**
1748     * Reset stat value to default
1749     */
1750    void
1751    reset(Info *info)
1752    {
1753        sum = Counter();
1754        squares = Counter();
1755    }
1756};
1757
1758/**
1759 * Implementation of a distribution stat. The type of distribution is
1760 * determined by the Storage template. @sa ScalarBase
1761 */
1762template <class Derived, class Stor>
1763class DistBase : public DataWrap<Derived, DistInfoProxy>
1764{
1765  public:
1766    typedef DistInfoProxy<Derived> Info;
1767    typedef Stor Storage;
1768    typedef typename Stor::Params Params;
1769
1770  protected:
1771    /** The storage for this stat. */
1772    char storage[sizeof(Storage)] __attribute__ ((aligned (8)));
1773
1774  protected:
1775    /**
1776     * Retrieve the storage.
1777     * @return The storage object for this stat.
1778     */
1779    Storage *
1780    data()
1781    {
1782        return reinterpret_cast<Storage *>(storage);
1783    }
1784
1785    /**
1786     * Retrieve a const pointer to the storage.
1787     * @return A const pointer to the storage object for this stat.
1788     */
1789    const Storage *
1790    data() const
1791    {
1792        return reinterpret_cast<const Storage *>(storage);
1793    }
1794
1795    void
1796    doInit()
1797    {
1798        new (storage) Storage(this->info());
1799        this->setInit();
1800    }
1801
1802  public:
1803    DistBase() { }
1804
1805    /**
1806     * Add a value to the distribtion n times. Calls sample on the storage
1807     * class.
1808     * @param v The value to add.
1809     * @param n The number of times to add it, defaults to 1.
1810     */
1811    template <typename U>
1812    void sample(const U &v, int n = 1) { data()->sample(v, n); }
1813
1814    /**
1815     * Return the number of entries in this stat.
1816     * @return The number of entries.
1817     */
1818    size_type size() const { return data()->size(); }
1819    /**
1820     * Return true if no samples have been added.
1821     * @return True if there haven't been any samples.
1822     */
1823    bool zero() const { return data()->zero(); }
1824
1825    void
1826    prepare()
1827    {
1828        Info *info = this->info();
1829        data()->prepare(info, info->data);
1830    }
1831
1832    /**
1833     * Reset stat value to default
1834     */
1835    void
1836    reset()
1837    {
1838        data()->reset(this->info());
1839    }
1840};
1841
1842template <class Stat>
1843class DistProxy;
1844
1845template <class Derived, class Stor>
1846class VectorDistBase : public DataWrapVec<Derived, VectorDistInfoProxy>
1847{
1848  public:
1849    typedef VectorDistInfoProxy<Derived> Info;
1850    typedef Stor Storage;
1851    typedef typename Stor::Params Params;
1852    typedef DistProxy<Derived> Proxy;
1853    friend class DistProxy<Derived>;
1854    friend class DataWrapVec<Derived, VectorDistInfoProxy>;
1855
1856  protected:
1857    Storage *storage;
1858    size_type _size;
1859
1860  protected:
1861    Storage *
1862    data(off_type index)
1863    {
1864        return &storage[index];
1865    }
1866
1867    const Storage *
1868    data(off_type index) const
1869    {
1870        return &storage[index];
1871    }
1872
1873    void
1874    doInit(size_type s)
1875    {
1876        assert(s > 0 && "size must be positive!");
1877        assert(!storage && "already initialized");
1878        _size = s;
1879
1880        char *ptr = new char[_size * sizeof(Storage)];
1881        storage = reinterpret_cast<Storage *>(ptr);
1882
1883        Info *info = this->info();
1884        for (off_type i = 0; i < _size; ++i)
1885            new (&storage[i]) Storage(info);
1886
1887        this->setInit();
1888    }
1889
1890  public:
1891    VectorDistBase()
1892        : storage(NULL)
1893    {}
1894
1895    ~VectorDistBase()
1896    {
1897        if (!storage)
1898            return ;
1899
1900        for (off_type i = 0; i < _size; ++i)
1901            data(i)->~Storage();
1902        delete [] reinterpret_cast<char *>(storage);
1903    }
1904
1905    Proxy operator[](off_type index)
1906    {
1907        assert(index >= 0 && index < size());
1908        return Proxy(this->self(), index);
1909    }
1910
1911    size_type
1912    size() const
1913    {
1914        return _size;
1915    }
1916
1917    bool
1918    zero() const
1919    {
1920        for (off_type i = 0; i < size(); ++i)
1921            if (!data(i)->zero())
1922                return false;
1923        return true;
1924    }
1925
1926    void
1927    prepare()
1928    {
1929        Info *info = this->info();
1930        size_type size = this->size();
1931        info->data.resize(size);
1932        for (off_type i = 0; i < size; ++i)
1933            data(i)->prepare(info, info->data[i]);
1934    }
1935
1936    bool
1937    check() const
1938    {
1939        return storage != NULL;
1940    }
1941};
1942
1943template <class Stat>
1944class DistProxy
1945{
1946  private:
1947    Stat &stat;
1948    off_type index;
1949
1950  protected:
1951    typename Stat::Storage *data() { return stat.data(index); }
1952    const typename Stat::Storage *data() const { return stat.data(index); }
1953
1954  public:
1955    DistProxy(Stat &s, off_type i)
1956        : stat(s), index(i)
1957    {}
1958
1959    DistProxy(const DistProxy &sp)
1960        : stat(sp.stat), index(sp.index)
1961    {}
1962
1963    const DistProxy &
1964    operator=(const DistProxy &sp)
1965    {
1966        stat = sp.stat;
1967        index = sp.index;
1968        return *this;
1969    }
1970
1971  public:
1972    template <typename U>
1973    void
1974    sample(const U &v, int n = 1)
1975    {
1976        data()->sample(v, n);
1977    }
1978
1979    size_type
1980    size() const
1981    {
1982        return 1;
1983    }
1984
1985    bool
1986    zero() const
1987    {
1988        return data()->zero();
1989    }
1990
1991    /**
1992     * Proxy has no state.  Nothing to reset.
1993     */
1994    void reset() { }
1995};
1996
1997//////////////////////////////////////////////////////////////////////
1998//
1999//  Formula Details
2000//
2001//////////////////////////////////////////////////////////////////////
2002
2003/**
2004 * Base class for formula statistic node. These nodes are used to build a tree
2005 * that represents the formula.
2006 */
2007class Node : public RefCounted
2008{
2009  public:
2010    /**
2011     * Return the number of nodes in the subtree starting at this node.
2012     * @return the number of nodes in this subtree.
2013     */
2014    virtual size_type size() const = 0;
2015    /**
2016     * Return the result vector of this subtree.
2017     * @return The result vector of this subtree.
2018     */
2019    virtual const VResult &result() const = 0;
2020    /**
2021     * Return the total of the result vector.
2022     * @return The total of the result vector.
2023     */
2024    virtual Result total() const = 0;
2025
2026    /**
2027     *
2028     */
2029    virtual std::string str() const = 0;
2030};
2031
2032/** Reference counting pointer to a function Node. */
2033typedef RefCountingPtr<Node> NodePtr;
2034
2035class ScalarStatNode : public Node
2036{
2037  private:
2038    const ScalarInfo *data;
2039    mutable VResult vresult;
2040
2041  public:
2042    ScalarStatNode(const ScalarInfo *d) : data(d), vresult(1) {}
2043
2044    const VResult &
2045    result() const
2046    {
2047        vresult[0] = data->result();
2048        return vresult;
2049    }
2050
2051    Result total() const { return data->result(); };
2052
2053    size_type size() const { return 1; }
2054
2055    /**
2056     *
2057     */
2058    std::string str() const { return data->name; }
2059};
2060
2061template <class Stat>
2062class ScalarProxyNode : public Node
2063{
2064  private:
2065    const ScalarProxy<Stat> proxy;
2066    mutable VResult vresult;
2067
2068  public:
2069    ScalarProxyNode(const ScalarProxy<Stat> &p)
2070        : proxy(p), vresult(1)
2071    { }
2072
2073    const VResult &
2074    result() const
2075    {
2076        vresult[0] = proxy.result();
2077        return vresult;
2078    }
2079
2080    Result
2081    total() const
2082    {
2083        return proxy.result();
2084    }
2085
2086    size_type
2087    size() const
2088    {
2089        return 1;
2090    }
2091
2092    /**
2093     *
2094     */
2095    std::string
2096    str() const
2097    {
2098        return proxy.str();
2099    }
2100};
2101
2102class VectorStatNode : public Node
2103{
2104  private:
2105    const VectorInfo *data;
2106
2107  public:
2108    VectorStatNode(const VectorInfo *d) : data(d) { }
2109    const VResult &result() const { return data->result(); }
2110    Result total() const { return data->total(); };
2111
2112    size_type size() const { return data->size(); }
2113
2114    std::string str() const { return data->name; }
2115};
2116
2117template <class T>
2118class ConstNode : public Node
2119{
2120  private:
2121    VResult vresult;
2122
2123  public:
2124    ConstNode(T s) : vresult(1, (Result)s) {}
2125    const VResult &result() const { return vresult; }
2126    Result total() const { return vresult[0]; };
2127    size_type size() const { return 1; }
2128    std::string str() const { return to_string(vresult[0]); }
2129};
2130
2131template <class T>
2132class ConstVectorNode : public Node
2133{
2134  private:
2135    VResult vresult;
2136
2137  public:
2138    ConstVectorNode(const T &s) : vresult(s.begin(), s.end()) {}
2139    const VResult &result() const { return vresult; }
2140
2141    Result
2142    total() const
2143    {
2144        size_type size = this->size();
2145        Result tmp = 0;
2146        for (off_type i = 0; i < size; i++)
2147            tmp += vresult[i];
2148        return tmp;
2149    }
2150
2151    size_type size() const { return vresult.size(); }
2152    std::string
2153    str() const
2154    {
2155        size_type size = this->size();
2156        std::string tmp = "(";
2157        for (off_type i = 0; i < size; i++)
2158            tmp += csprintf("%s ",to_string(vresult[i]));
2159        tmp += ")";
2160        return tmp;
2161    }
2162};
2163
2164template <class Op>
2165struct OpString;
2166
2167template<>
2168struct OpString<std::plus<Result> >
2169{
2170    static std::string str() { return "+"; }
2171};
2172
2173template<>
2174struct OpString<std::minus<Result> >
2175{
2176    static std::string str() { return "-"; }
2177};
2178
2179template<>
2180struct OpString<std::multiplies<Result> >
2181{
2182    static std::string str() { return "*"; }
2183};
2184
2185template<>
2186struct OpString<std::divides<Result> >
2187{
2188    static std::string str() { return "/"; }
2189};
2190
2191template<>
2192struct OpString<std::modulus<Result> >
2193{
2194    static std::string str() { return "%"; }
2195};
2196
2197template<>
2198struct OpString<std::negate<Result> >
2199{
2200    static std::string str() { return "-"; }
2201};
2202
2203template <class Op>
2204class UnaryNode : public Node
2205{
2206  public:
2207    NodePtr l;
2208    mutable VResult vresult;
2209
2210  public:
2211    UnaryNode(NodePtr &p) : l(p) {}
2212
2213    const VResult &
2214    result() const
2215    {
2216        const VResult &lvec = l->result();
2217        size_type size = lvec.size();
2218
2219        assert(size > 0);
2220
2221        vresult.resize(size);
2222        Op op;
2223        for (off_type i = 0; i < size; ++i)
2224            vresult[i] = op(lvec[i]);
2225
2226        return vresult;
2227    }
2228
2229    Result
2230    total() const
2231    {
2232        const VResult &vec = this->result();
2233        Result total = 0.0;
2234        for (off_type i = 0; i < size(); i++)
2235            total += vec[i];
2236        return total;
2237    }
2238
2239    size_type size() const { return l->size(); }
2240
2241    std::string
2242    str() const
2243    {
2244        return OpString<Op>::str() + l->str();
2245    }
2246};
2247
2248template <class Op>
2249class BinaryNode : public Node
2250{
2251  public:
2252    NodePtr l;
2253    NodePtr r;
2254    mutable VResult vresult;
2255
2256  public:
2257    BinaryNode(NodePtr &a, NodePtr &b) : l(a), r(b) {}
2258
2259    const VResult &
2260    result() const
2261    {
2262        Op op;
2263        const VResult &lvec = l->result();
2264        const VResult &rvec = r->result();
2265
2266        assert(lvec.size() > 0 && rvec.size() > 0);
2267
2268        if (lvec.size() == 1 && rvec.size() == 1) {
2269            vresult.resize(1);
2270            vresult[0] = op(lvec[0], rvec[0]);
2271        } else if (lvec.size() == 1) {
2272            size_type size = rvec.size();
2273            vresult.resize(size);
2274            for (off_type i = 0; i < size; ++i)
2275                vresult[i] = op(lvec[0], rvec[i]);
2276        } else if (rvec.size() == 1) {
2277            size_type size = lvec.size();
2278            vresult.resize(size);
2279            for (off_type i = 0; i < size; ++i)
2280                vresult[i] = op(lvec[i], rvec[0]);
2281        } else if (rvec.size() == lvec.size()) {
2282            size_type size = rvec.size();
2283            vresult.resize(size);
2284            for (off_type i = 0; i < size; ++i)
2285                vresult[i] = op(lvec[i], rvec[i]);
2286        }
2287
2288        return vresult;
2289    }
2290
2291    Result
2292    total() const
2293    {
2294        const VResult &vec = this->result();
2295        const VResult &lvec = l->result();
2296        const VResult &rvec = r->result();
2297        Result total = 0.0;
2298        Result lsum = 0.0;
2299        Result rsum = 0.0;
2300        Op op;
2301
2302        assert(lvec.size() > 0 && rvec.size() > 0);
2303        assert(lvec.size() == rvec.size() ||
2304               lvec.size() == 1 || rvec.size() == 1);
2305
2306        /** If vectors are the same divide their sums (x0+x1)/(y0+y1) */
2307        if (lvec.size() == rvec.size() && lvec.size() > 1) {
2308            for (off_type i = 0; i < size(); ++i) {
2309                lsum += lvec[i];
2310                rsum += rvec[i];
2311            }
2312            return op(lsum, rsum);
2313        }
2314
2315        /** Otherwise divide each item by the divisor */
2316        for (off_type i = 0; i < size(); ++i) {
2317            total += vec[i];
2318        }
2319
2320        return total;
2321    }
2322
2323    size_type
2324    size() const
2325    {
2326        size_type ls = l->size();
2327        size_type rs = r->size();
2328        if (ls == 1) {
2329            return rs;
2330        } else if (rs == 1) {
2331            return ls;
2332        } else {
2333            assert(ls == rs && "Node vector sizes are not equal");
2334            return ls;
2335        }
2336    }
2337
2338    std::string
2339    str() const
2340    {
2341        return csprintf("(%s %s %s)", l->str(), OpString<Op>::str(), r->str());
2342    }
2343};
2344
2345template <class Op>
2346class SumNode : public Node
2347{
2348  public:
2349    NodePtr l;
2350    mutable VResult vresult;
2351
2352  public:
2353    SumNode(NodePtr &p) : l(p), vresult(1) {}
2354
2355    const VResult &
2356    result() const
2357    {
2358        const VResult &lvec = l->result();
2359        size_type size = lvec.size();
2360        assert(size > 0);
2361
2362        vresult[0] = 0.0;
2363
2364        Op op;
2365        for (off_type i = 0; i < size; ++i)
2366            vresult[0] = op(vresult[0], lvec[i]);
2367
2368        return vresult;
2369    }
2370
2371    Result
2372    total() const
2373    {
2374        const VResult &lvec = l->result();
2375        size_type size = lvec.size();
2376        assert(size > 0);
2377
2378        Result result = 0.0;
2379
2380        Op op;
2381        for (off_type i = 0; i < size; ++i)
2382            result = op(result, lvec[i]);
2383
2384        return result;
2385    }
2386
2387    size_type size() const { return 1; }
2388
2389    std::string
2390    str() const
2391    {
2392        return csprintf("total(%s)", l->str());
2393    }
2394};
2395
2396
2397//////////////////////////////////////////////////////////////////////
2398//
2399// Visible Statistics Types
2400//
2401//////////////////////////////////////////////////////////////////////
2402/**
2403 * @defgroup VisibleStats "Statistic Types"
2404 * These are the statistics that are used in the simulator.
2405 * @{
2406 */
2407
2408/**
2409 * This is a simple scalar statistic, like a counter.
2410 * @sa Stat, ScalarBase, StatStor
2411 */
2412class Scalar : public ScalarBase<Scalar, StatStor>
2413{
2414  public:
2415    using ScalarBase<Scalar, StatStor>::operator=;
2416};
2417
2418/**
2419 * A stat that calculates the per tick average of a value.
2420 * @sa Stat, ScalarBase, AvgStor
2421 */
2422class Average : public ScalarBase<Average, AvgStor>
2423{
2424  public:
2425    using ScalarBase<Average, AvgStor>::operator=;
2426};
2427
2428class Value : public ValueBase<Value>
2429{
2430};
2431
2432/**
2433 * A vector of scalar stats.
2434 * @sa Stat, VectorBase, StatStor
2435 */
2436class Vector : public VectorBase<Vector, StatStor>
2437{
2438};
2439
2440/**
2441 * A vector of Average stats.
2442 * @sa Stat, VectorBase, AvgStor
2443 */
2444class AverageVector : public VectorBase<AverageVector, AvgStor>
2445{
2446};
2447
2448/**
2449 * A 2-Dimensional vecto of scalar stats.
2450 * @sa Stat, Vector2dBase, StatStor
2451 */
2452class Vector2d : public Vector2dBase<Vector2d, StatStor>
2453{
2454};
2455
2456/**
2457 * A simple distribution stat.
2458 * @sa Stat, DistBase, DistStor
2459 */
2460class Distribution : public DistBase<Distribution, DistStor>
2461{
2462  public:
2463    /**
2464     * Set the parameters of this distribution. @sa DistStor::Params
2465     * @param min The minimum value of the distribution.
2466     * @param max The maximum value of the distribution.
2467     * @param bkt The number of values in each bucket.
2468     * @return A reference to this distribution.
2469     */
2470    Distribution &
2471    init(Counter min, Counter max, Counter bkt)
2472    {
2473        DistStor::Params *params = new DistStor::Params;
2474        params->min = min;
2475        params->max = max;
2476        params->bucket_size = bkt;
2477        params->buckets = (size_type)ceil((max - min + 1.0) / bkt);
2478        this->setParams(params);
2479        this->doInit();
2480        return this->self();
2481    }
2482};
2483
2484/**
2485 * A simple histogram stat.
2486 * @sa Stat, DistBase, HistStor
2487 */
2488class Histogram : public DistBase<Histogram, HistStor>
2489{
2490  public:
2491    /**
2492     * Set the parameters of this histogram. @sa HistStor::Params
2493     * @param size The number of buckets in the histogram
2494     * @return A reference to this histogram.
2495     */
2496    Histogram &
2497    init(size_type size)
2498    {
2499        HistStor::Params *params = new HistStor::Params;
2500        params->buckets = size;
2501        this->setParams(params);
2502        this->doInit();
2503        return this->self();
2504    }
2505};
2506
2507/**
2508 * Calculates the mean and variance of all the samples.
2509 * @sa DistBase, SampleStor
2510 */
2511class StandardDeviation : public DistBase<StandardDeviation, SampleStor>
2512{
2513  public:
2514    /**
2515     * Construct and initialize this distribution.
2516     */
2517    StandardDeviation()
2518    {
2519        SampleStor::Params *params = new SampleStor::Params;
2520        this->doInit();
2521        this->setParams(params);
2522    }
2523};
2524
2525/**
2526 * Calculates the per tick mean and variance of the samples.
2527 * @sa DistBase, AvgSampleStor
2528 */
2529class AverageDeviation : public DistBase<AverageDeviation, AvgSampleStor>
2530{
2531  public:
2532    /**
2533     * Construct and initialize this distribution.
2534     */
2535    AverageDeviation()
2536    {
2537        AvgSampleStor::Params *params = new AvgSampleStor::Params;
2538        this->doInit();
2539        this->setParams(params);
2540    }
2541};
2542
2543/**
2544 * A vector of distributions.
2545 * @sa VectorDistBase, DistStor
2546 */
2547class VectorDistribution : public VectorDistBase<VectorDistribution, DistStor>
2548{
2549  public:
2550    /**
2551     * Initialize storage and parameters for this distribution.
2552     * @param size The size of the vector (the number of distributions).
2553     * @param min The minimum value of the distribution.
2554     * @param max The maximum value of the distribution.
2555     * @param bkt The number of values in each bucket.
2556     * @return A reference to this distribution.
2557     */
2558    VectorDistribution &
2559    init(size_type size, Counter min, Counter max, Counter bkt)
2560    {
2561        DistStor::Params *params = new DistStor::Params;
2562        params->min = min;
2563        params->max = max;
2564        params->bucket_size = bkt;
2565        params->buckets = (size_type)ceil((max - min + 1.0) / bkt);
2566        this->setParams(params);
2567        this->doInit(size);
2568        return this->self();
2569    }
2570};
2571
2572/**
2573 * This is a vector of StandardDeviation stats.
2574 * @sa VectorDistBase, SampleStor
2575 */
2576class VectorStandardDeviation
2577    : public VectorDistBase<VectorStandardDeviation, SampleStor>
2578{
2579  public:
2580    /**
2581     * Initialize storage for this distribution.
2582     * @param size The size of the vector.
2583     * @return A reference to this distribution.
2584     */
2585    VectorStandardDeviation &
2586    init(size_type size)
2587    {
2588        SampleStor::Params *params = new SampleStor::Params;
2589        this->doInit(size);
2590        this->setParams(params);
2591        return this->self();
2592    }
2593};
2594
2595/**
2596 * This is a vector of AverageDeviation stats.
2597 * @sa VectorDistBase, AvgSampleStor
2598 */
2599class VectorAverageDeviation
2600    : public VectorDistBase<VectorAverageDeviation, AvgSampleStor>
2601{
2602  public:
2603    /**
2604     * Initialize storage for this distribution.
2605     * @param size The size of the vector.
2606     * @return A reference to this distribution.
2607     */
2608    VectorAverageDeviation &
2609    init(size_type size)
2610    {
2611        AvgSampleStor::Params *params = new AvgSampleStor::Params;
2612        this->doInit(size);
2613        this->setParams(params);
2614        return this->self();
2615    }
2616};
2617
2618template <class Stat>
2619class FormulaInfoProxy : public InfoProxy<Stat, FormulaInfo>
2620{
2621  protected:
2622    mutable VResult vec;
2623    mutable VCounter cvec;
2624
2625  public:
2626    FormulaInfoProxy(Stat &stat) : InfoProxy<Stat, FormulaInfo>(stat) {}
2627
2628    size_type size() const { return this->s.size(); }
2629
2630    const VResult &
2631    result() const
2632    {
2633        this->s.result(vec);
2634        return vec;
2635    }
2636    Result total() const { return this->s.total(); }
2637    VCounter &value() const { return cvec; }
2638
2639    std::string str() const { return this->s.str(); }
2640};
2641
2642template <class Stat>
2643class SparseHistInfoProxy : public InfoProxy<Stat, SparseHistInfo>
2644{
2645  public:
2646    SparseHistInfoProxy(Stat &stat) : InfoProxy<Stat, SparseHistInfo>(stat) {}
2647};
2648
2649/**
2650 * Implementation of a sparse histogram stat. The storage class is
2651 * determined by the Storage template.
2652 */
2653template <class Derived, class Stor>
2654class SparseHistBase : public DataWrap<Derived, SparseHistInfoProxy>
2655{
2656  public:
2657    typedef SparseHistInfoProxy<Derived> Info;
2658    typedef Stor Storage;
2659    typedef typename Stor::Params Params;
2660
2661  protected:
2662    /** The storage for this stat. */
2663    char storage[sizeof(Storage)];
2664
2665  protected:
2666    /**
2667     * Retrieve the storage.
2668     * @return The storage object for this stat.
2669     */
2670    Storage *
2671    data()
2672    {
2673        return reinterpret_cast<Storage *>(storage);
2674    }
2675
2676    /**
2677     * Retrieve a const pointer to the storage.
2678     * @return A const pointer to the storage object for this stat.
2679     */
2680    const Storage *
2681    data() const
2682    {
2683        return reinterpret_cast<const Storage *>(storage);
2684    }
2685
2686    void
2687    doInit()
2688    {
2689        new (storage) Storage(this->info());
2690        this->setInit();
2691    }
2692
2693  public:
2694    SparseHistBase() { }
2695
2696    /**
2697     * Add a value to the distribtion n times. Calls sample on the storage
2698     * class.
2699     * @param v The value to add.
2700     * @param n The number of times to add it, defaults to 1.
2701     */
2702    template <typename U>
2703    void sample(const U &v, int n = 1) { data()->sample(v, n); }
2704
2705    /**
2706     * Return the number of entries in this stat.
2707     * @return The number of entries.
2708     */
2709    size_type size() const { return data()->size(); }
2710    /**
2711     * Return true if no samples have been added.
2712     * @return True if there haven't been any samples.
2713     */
2714    bool zero() const { return data()->zero(); }
2715
2716    void
2717    prepare()
2718    {
2719        Info *info = this->info();
2720        data()->prepare(info, info->data);
2721    }
2722
2723    /**
2724     * Reset stat value to default
2725     */
2726    void
2727    reset()
2728    {
2729        data()->reset(this->info());
2730    }
2731};
2732
2733/**
2734 * Templatized storage and interface for a sparse histogram stat.
2735 */
2736class SparseHistStor
2737{
2738  public:
2739    /** The parameters for a sparse histogram stat. */
2740    struct Params : public DistParams
2741    {
2742        Params() : DistParams(Hist) {}
2743    };
2744
2745  private:
2746    /** Counter for number of samples */
2747    Counter samples;
2748    /** Counter for each bucket. */
2749    MCounter cmap;
2750
2751  public:
2752    SparseHistStor(Info *info)
2753    {
2754        reset(info);
2755    }
2756
2757    /**
2758     * Add a value to the distribution for the given number of times.
2759     * @param val The value to add.
2760     * @param number The number of times to add the value.
2761     */
2762    void
2763    sample(Counter val, int number)
2764    {
2765        cmap[val] += number;
2766        samples += number;
2767    }
2768
2769    /**
2770     * Return the number of buckets in this distribution.
2771     * @return the number of buckets.
2772     */
2773    size_type size() const { return cmap.size(); }
2774
2775    /**
2776     * Returns true if any calls to sample have been made.
2777     * @return True if any values have been sampled.
2778     */
2779    bool
2780    zero() const
2781    {
2782        return samples == Counter();
2783    }
2784
2785    void
2786    prepare(Info *info, SparseHistData &data)
2787    {
2788        MCounter::iterator it;
2789        data.cmap.clear();
2790        for (it = cmap.begin(); it != cmap.end(); it++) {
2791            data.cmap[(*it).first] = (*it).second;
2792        }
2793
2794        data.samples = samples;
2795    }
2796
2797    /**
2798     * Reset stat value to default
2799     */
2800    void
2801    reset(Info *info)
2802    {
2803        cmap.clear();
2804        samples = 0;
2805    }
2806};
2807
2808class SparseHistogram : public SparseHistBase<SparseHistogram, SparseHistStor>
2809{
2810  public:
2811    /**
2812     * Set the parameters of this histogram. @sa HistStor::Params
2813     * @param size The number of buckets in the histogram
2814     * @return A reference to this histogram.
2815     */
2816    SparseHistogram &
2817    init(size_type size)
2818    {
2819        SparseHistStor::Params *params = new SparseHistStor::Params;
2820        this->setParams(params);
2821        this->doInit();
2822        return this->self();
2823    }
2824};
2825
2826class Temp;
2827/**
2828 * A formula for statistics that is calculated when printed. A formula is
2829 * stored as a tree of Nodes that represent the equation to calculate.
2830 * @sa Stat, ScalarStat, VectorStat, Node, Temp
2831 */
2832class Formula : public DataWrapVec<Formula, FormulaInfoProxy>
2833{
2834  protected:
2835    /** The root of the tree which represents the Formula */
2836    NodePtr root;
2837    friend class Temp;
2838
2839  public:
2840    /**
2841     * Create and initialize thie formula, and register it with the database.
2842     */
2843    Formula();
2844
2845    /**
2846     * Create a formula with the given root node, register it with the
2847     * database.
2848     * @param r The root of the expression tree.
2849     */
2850    Formula(Temp r);
2851
2852    /**
2853     * Set an unitialized Formula to the given root.
2854     * @param r The root of the expression tree.
2855     * @return a reference to this formula.
2856     */
2857    const Formula &operator=(Temp r);
2858
2859    /**
2860     * Add the given tree to the existing one.
2861     * @param r The root of the expression tree.
2862     * @return a reference to this formula.
2863     */
2864    const Formula &operator+=(Temp r);
2865
2866    /**
2867     * Divide the existing tree by the given one.
2868     * @param r The root of the expression tree.
2869     * @return a reference to this formula.
2870     */
2871    const Formula &operator/=(Temp r);
2872
2873    /**
2874     * Return the result of the Fomula in a vector.  If there were no Vector
2875     * components to the Formula, then the vector is size 1.  If there were,
2876     * like x/y with x being a vector of size 3, then the result returned will
2877     * be x[0]/y, x[1]/y, x[2]/y, respectively.
2878     * @return The result vector.
2879     */
2880    void result(VResult &vec) const;
2881
2882    /**
2883     * Return the total Formula result.  If there is a Vector
2884     * component to this Formula, then this is the result of the
2885     * Formula if the formula is applied after summing all the
2886     * components of the Vector.  For example, if Formula is x/y where
2887     * x is size 3, then total() will return (x[1]+x[2]+x[3])/y.  If
2888     * there is no Vector component, total() returns the same value as
2889     * the first entry in the VResult val() returns.
2890     * @return The total of the result vector.
2891     */
2892    Result total() const;
2893
2894    /**
2895     * Return the number of elements in the tree.
2896     */
2897    size_type size() const;
2898
2899    void prepare() { }
2900
2901    /**
2902     * Formulas don't need to be reset
2903     */
2904    void reset();
2905
2906    /**
2907     *
2908     */
2909    bool zero() const;
2910
2911    std::string str() const;
2912};
2913
2914class FormulaNode : public Node
2915{
2916  private:
2917    const Formula &formula;
2918    mutable VResult vec;
2919
2920  public:
2921    FormulaNode(const Formula &f) : formula(f) {}
2922
2923    size_type size() const { return formula.size(); }
2924    const VResult &result() const { formula.result(vec); return vec; }
2925    Result total() const { return formula.total(); }
2926
2927    std::string str() const { return formula.str(); }
2928};
2929
2930/**
2931 * Helper class to construct formula node trees.
2932 */
2933class Temp
2934{
2935  protected:
2936    /**
2937     * Pointer to a Node object.
2938     */
2939    NodePtr node;
2940
2941  public:
2942    /**
2943     * Copy the given pointer to this class.
2944     * @param n A pointer to a Node object to copy.
2945     */
2946    Temp(NodePtr n) : node(n) { }
2947
2948    /**
2949     * Return the node pointer.
2950     * @return the node pointer.
2951     */
2952    operator NodePtr&() { return node; }
2953
2954  public:
2955    /**
2956     * Create a new ScalarStatNode.
2957     * @param s The ScalarStat to place in a node.
2958     */
2959    Temp(const Scalar &s)
2960        : node(new ScalarStatNode(s.info()))
2961    { }
2962
2963    /**
2964     * Create a new ScalarStatNode.
2965     * @param s The ScalarStat to place in a node.
2966     */
2967    Temp(const Value &s)
2968        : node(new ScalarStatNode(s.info()))
2969    { }
2970
2971    /**
2972     * Create a new ScalarStatNode.
2973     * @param s The ScalarStat to place in a node.
2974     */
2975    Temp(const Average &s)
2976        : node(new ScalarStatNode(s.info()))
2977    { }
2978
2979    /**
2980     * Create a new VectorStatNode.
2981     * @param s The VectorStat to place in a node.
2982     */
2983    Temp(const Vector &s)
2984        : node(new VectorStatNode(s.info()))
2985    { }
2986
2987    Temp(const AverageVector &s)
2988        : node(new VectorStatNode(s.info()))
2989    { }
2990
2991    /**
2992     *
2993     */
2994    Temp(const Formula &f)
2995        : node(new FormulaNode(f))
2996    { }
2997
2998    /**
2999     * Create a new ScalarProxyNode.
3000     * @param p The ScalarProxy to place in a node.
3001     */
3002    template <class Stat>
3003    Temp(const ScalarProxy<Stat> &p)
3004        : node(new ScalarProxyNode<Stat>(p))
3005    { }
3006
3007    /**
3008     * Create a ConstNode
3009     * @param value The value of the const node.
3010     */
3011    Temp(signed char value)
3012        : node(new ConstNode<signed char>(value))
3013    { }
3014
3015    /**
3016     * Create a ConstNode
3017     * @param value The value of the const node.
3018     */
3019    Temp(unsigned char value)
3020        : node(new ConstNode<unsigned char>(value))
3021    { }
3022
3023    /**
3024     * Create a ConstNode
3025     * @param value The value of the const node.
3026     */
3027    Temp(signed short value)
3028        : node(new ConstNode<signed short>(value))
3029    { }
3030
3031    /**
3032     * Create a ConstNode
3033     * @param value The value of the const node.
3034     */
3035    Temp(unsigned short value)
3036        : node(new ConstNode<unsigned short>(value))
3037    { }
3038
3039    /**
3040     * Create a ConstNode
3041     * @param value The value of the const node.
3042     */
3043    Temp(signed int value)
3044        : node(new ConstNode<signed int>(value))
3045    { }
3046
3047    /**
3048     * Create a ConstNode
3049     * @param value The value of the const node.
3050     */
3051    Temp(unsigned int value)
3052        : node(new ConstNode<unsigned int>(value))
3053    { }
3054
3055    /**
3056     * Create a ConstNode
3057     * @param value The value of the const node.
3058     */
3059    Temp(signed long value)
3060        : node(new ConstNode<signed long>(value))
3061    { }
3062
3063    /**
3064     * Create a ConstNode
3065     * @param value The value of the const node.
3066     */
3067    Temp(unsigned long value)
3068        : node(new ConstNode<unsigned long>(value))
3069    { }
3070
3071    /**
3072     * Create a ConstNode
3073     * @param value The value of the const node.
3074     */
3075    Temp(signed long long value)
3076        : node(new ConstNode<signed long long>(value))
3077    { }
3078
3079    /**
3080     * Create a ConstNode
3081     * @param value The value of the const node.
3082     */
3083    Temp(unsigned long long value)
3084        : node(new ConstNode<unsigned long long>(value))
3085    { }
3086
3087    /**
3088     * Create a ConstNode
3089     * @param value The value of the const node.
3090     */
3091    Temp(float value)
3092        : node(new ConstNode<float>(value))
3093    { }
3094
3095    /**
3096     * Create a ConstNode
3097     * @param value The value of the const node.
3098     */
3099    Temp(double value)
3100        : node(new ConstNode<double>(value))
3101    { }
3102};
3103
3104
3105/**
3106 * @}
3107 */
3108
3109inline Temp
3110operator+(Temp l, Temp r)
3111{
3112    return NodePtr(new BinaryNode<std::plus<Result> >(l, r));
3113}
3114
3115inline Temp
3116operator-(Temp l, Temp r)
3117{
3118    return NodePtr(new BinaryNode<std::minus<Result> >(l, r));
3119}
3120
3121inline Temp
3122operator*(Temp l, Temp r)
3123{
3124    return NodePtr(new BinaryNode<std::multiplies<Result> >(l, r));
3125}
3126
3127inline Temp
3128operator/(Temp l, Temp r)
3129{
3130    return NodePtr(new BinaryNode<std::divides<Result> >(l, r));
3131}
3132
3133inline Temp
3134operator-(Temp l)
3135{
3136    return NodePtr(new UnaryNode<std::negate<Result> >(l));
3137}
3138
3139template <typename T>
3140inline Temp
3141constant(T val)
3142{
3143    return NodePtr(new ConstNode<T>(val));
3144}
3145
3146template <typename T>
3147inline Temp
3148constantVector(T val)
3149{
3150    return NodePtr(new ConstVectorNode<T>(val));
3151}
3152
3153inline Temp
3154sum(Temp val)
3155{
3156    return NodePtr(new SumNode<std::plus<Result> >(val));
3157}
3158
3159/** Dump all statistics data to the registered outputs */
3160void dump();
3161void reset();
3162void enable();
3163bool enabled();
3164
3165/**
3166 * Register a callback that should be called whenever statistics are
3167 * reset
3168 */
3169void registerResetCallback(Callback *cb);
3170
3171/**
3172 * Register a callback that should be called whenever statistics are
3173 * about to be dumped
3174 */
3175void registerDumpCallback(Callback *cb);
3176
3177std::list<Info *> &statsList();
3178
3179typedef std::map<const void *, Info *> MapType;
3180MapType &statsMap();
3181
3182typedef std::map<std::string, Info *> NameMapType;
3183NameMapType &nameMap();
3184
3185bool validateStatName(const std::string &name);
3186
3187} // namespace Stats
3188
3189void debugDumpStats();
3190
3191#endif // __BASE_STATISTICS_HH__
3192