statistics.hh revision 8514:57c96df312a1
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    // The following functions are specific to vectors.  If you use them
335    // in a non vector context, you will get a nice compiler error!
336
337    /**
338     * Set the subfield name for the given index, and marks this stat to print
339     * at the end of simulation.
340     * @param index The subfield index.
341     * @param name The new name of the subfield.
342     * @return A reference to this stat.
343     */
344    Derived &
345    subname(off_type index, const std::string &name)
346    {
347        Derived &self = this->self();
348        Info *info = self.info();
349
350        std::vector<std::string> &subn = info->subnames;
351        if (subn.size() <= index)
352            subn.resize(index + 1);
353        subn[index] = name;
354        return self;
355    }
356
357    // The following functions are specific to 2d vectors.  If you use
358    // them in a non vector context, you will get a nice compiler
359    // error because info doesn't have the right variables.
360
361    /**
362     * Set the subfield description for the given index and marks this stat to
363     * print at the end of simulation.
364     * @param index The subfield index.
365     * @param desc The new description of the subfield
366     * @return A reference to this stat.
367     */
368    Derived &
369    subdesc(off_type index, const std::string &desc)
370    {
371        Info *info = this->info();
372
373        std::vector<std::string> &subd = info->subdescs;
374        if (subd.size() <= index)
375            subd.resize(index + 1);
376        subd[index] = desc;
377
378        return this->self();
379    }
380
381    void
382    prepare()
383    {
384        Derived &self = this->self();
385        Info *info = this->info();
386
387        size_t size = self.size();
388        for (off_type i = 0; i < size; ++i)
389            self.data(i)->prepare(info);
390    }
391
392    void
393    reset()
394    {
395        Derived &self = this->self();
396        Info *info = this->info();
397
398        size_t size = self.size();
399        for (off_type i = 0; i < size; ++i)
400            self.data(i)->reset(info);
401    }
402};
403
404template <class Derived, template <class> class InfoProxyType>
405class DataWrapVec2d : public DataWrapVec<Derived, InfoProxyType>
406{
407  public:
408    typedef InfoProxyType<Derived> Info;
409
410    /**
411     * @warning This makes the assumption that if you're gonna subnames a 2d
412     * vector, you're subnaming across all y
413     */
414    Derived &
415    ysubnames(const char **names)
416    {
417        Derived &self = this->self();
418        Info *info = this->info();
419
420        info->y_subnames.resize(self.y);
421        for (off_type i = 0; i < self.y; ++i)
422            info->y_subnames[i] = names[i];
423        return self;
424    }
425
426    Derived &
427    ysubname(off_type index, const std::string &subname)
428    {
429        Derived &self = this->self();
430        Info *info = this->info();
431
432        assert(index < self.y);
433        info->y_subnames.resize(self.y);
434        info->y_subnames[index] = subname.c_str();
435        return self;
436    }
437
438    std::string
439    ysubname(off_type i) const
440    {
441        return this->info()->y_subnames[i];
442    }
443
444};
445
446//////////////////////////////////////////////////////////////////////
447//
448// Simple Statistics
449//
450//////////////////////////////////////////////////////////////////////
451
452/**
453 * Templatized storage and interface for a simple scalar stat.
454 */
455class StatStor
456{
457  private:
458    /** The statistic value. */
459    Counter data;
460
461  public:
462    struct Params : public StorageParams {};
463
464  public:
465    /**
466     * Builds this storage element and calls the base constructor of the
467     * datatype.
468     */
469    StatStor(Info *info)
470        : data(Counter())
471    { }
472
473    /**
474     * The the stat to the given value.
475     * @param val The new value.
476     */
477    void set(Counter val) { data = val; }
478    /**
479     * Increment the stat by the given value.
480     * @param val The new value.
481     */
482    void inc(Counter val) { data += val; }
483    /**
484     * Decrement the stat by the given value.
485     * @param val The new value.
486     */
487    void dec(Counter val) { data -= val; }
488    /**
489     * Return the value of this stat as its base type.
490     * @return The value of this stat.
491     */
492    Counter value() const { return data; }
493    /**
494     * Return the value of this stat as a result type.
495     * @return The value of this stat.
496     */
497    Result result() const { return (Result)data; }
498    /**
499     * Prepare stat data for dumping or serialization
500     */
501    void prepare(Info *info) { }
502    /**
503     * Reset stat value to default
504     */
505    void reset(Info *info) { data = Counter(); }
506
507    /**
508     * @return true if zero value
509     */
510    bool zero() const { return data == Counter(); }
511};
512
513/**
514 * Templatized storage and interface to a per-tick average stat. This keeps
515 * a current count and updates a total (count * ticks) when this count
516 * changes. This allows the quick calculation of a per tick count of the item
517 * being watched. This is good for keeping track of residencies in structures
518 * among other things.
519 */
520class AvgStor
521{
522  private:
523    /** The current count. */
524    Counter current;
525    /** The tick of the last reset */
526    Tick lastReset;
527    /** The total count for all tick. */
528    mutable Result total;
529    /** The tick that current last changed. */
530    mutable Tick last;
531
532  public:
533    struct Params : public StorageParams {};
534
535  public:
536    /**
537     * Build and initializes this stat storage.
538     */
539    AvgStor(Info *info)
540        : current(0), lastReset(0), total(0), last(0)
541    { }
542
543    /**
544     * Set the current count to the one provided, update the total and last
545     * set values.
546     * @param val The new count.
547     */
548    void
549    set(Counter val)
550    {
551        total += current * (curTick() - last);
552        last = curTick();
553        current = val;
554    }
555
556    /**
557     * Increment the current count by the provided value, calls set.
558     * @param val The amount to increment.
559     */
560    void inc(Counter val) { set(current + val); }
561
562    /**
563     * Deccrement the current count by the provided value, calls set.
564     * @param val The amount to decrement.
565     */
566    void dec(Counter val) { set(current - val); }
567
568    /**
569     * Return the current count.
570     * @return The current count.
571     */
572    Counter value() const { return current; }
573
574    /**
575     * Return the current average.
576     * @return The current average.
577     */
578    Result
579    result() const
580    {
581        assert(last == curTick());
582        return (Result)(total + current) / (Result)(curTick() - lastReset + 1);
583    }
584
585    /**
586     * @return true if zero value
587     */
588    bool zero() const { return total == 0.0; }
589
590    /**
591     * Prepare stat data for dumping or serialization
592     */
593    void
594    prepare(Info *info)
595    {
596        total += current * (curTick() - last);
597        last = curTick();
598    }
599
600    /**
601     * Reset stat value to default
602     */
603    void
604    reset(Info *info)
605    {
606        total = 0.0;
607        last = curTick();
608        lastReset = curTick();
609    }
610
611};
612
613/**
614 * Implementation of a scalar stat. The type of stat is determined by the
615 * Storage template.
616 */
617template <class Derived, class Stor>
618class ScalarBase : public DataWrap<Derived, ScalarInfoProxy>
619{
620  public:
621    typedef Stor Storage;
622    typedef typename Stor::Params Params;
623
624  protected:
625    /** The storage of this stat. */
626    char storage[sizeof(Storage)] __attribute__ ((aligned (8)));
627
628  protected:
629    /**
630     * Retrieve the storage.
631     * @param index The vector index to access.
632     * @return The storage object at the given index.
633     */
634    Storage *
635    data()
636    {
637        return reinterpret_cast<Storage *>(storage);
638    }
639
640    /**
641     * Retrieve a const pointer to the storage.
642     * for the given index.
643     * @param index The vector index to access.
644     * @return A const pointer to the storage object at the given index.
645     */
646    const Storage *
647    data() const
648    {
649        return reinterpret_cast<const Storage *>(storage);
650    }
651
652    void
653    doInit()
654    {
655        new (storage) Storage(this->info());
656        this->setInit();
657    }
658
659  public:
660    /**
661     * Return the current value of this stat as its base type.
662     * @return The current value.
663     */
664    Counter value() const { return data()->value(); }
665
666  public:
667    ScalarBase()
668    {
669        this->doInit();
670    }
671
672  public:
673    // Common operators for stats
674    /**
675     * Increment the stat by 1. This calls the associated storage object inc
676     * function.
677     */
678    void operator++() { data()->inc(1); }
679    /**
680     * Decrement the stat by 1. This calls the associated storage object dec
681     * function.
682     */
683    void operator--() { data()->dec(1); }
684
685    /** Increment the stat by 1. */
686    void operator++(int) { ++*this; }
687    /** Decrement the stat by 1. */
688    void operator--(int) { --*this; }
689
690    /**
691     * Set the data value to the given value. This calls the associated storage
692     * object set function.
693     * @param v The new value.
694     */
695    template <typename U>
696    void operator=(const U &v) { data()->set(v); }
697
698    /**
699     * Increment the stat by the given value. This calls the associated
700     * storage object inc function.
701     * @param v The value to add.
702     */
703    template <typename U>
704    void operator+=(const U &v) { data()->inc(v); }
705
706    /**
707     * Decrement the stat by the given value. This calls the associated
708     * storage object dec function.
709     * @param v The value to substract.
710     */
711    template <typename U>
712    void operator-=(const U &v) { data()->dec(v); }
713
714    /**
715     * Return the number of elements, always 1 for a scalar.
716     * @return 1.
717     */
718    size_type size() const { return 1; }
719
720    Counter value() { return data()->value(); }
721
722    Result result() { return data()->result(); }
723
724    Result total() { return result(); }
725
726    bool zero() { return result() == 0.0; }
727
728    void reset() { data()->reset(this->info()); }
729    void prepare() { data()->prepare(this->info()); }
730};
731
732class ProxyInfo : public ScalarInfo
733{
734  public:
735    std::string str() const { return to_string(value()); }
736    size_type size() const { return 1; }
737    bool check() const { return true; }
738    void prepare() { }
739    void reset() { }
740    bool zero() const { return value() == 0; }
741
742    void visit(Output &visitor) { visitor.visit(*this); }
743};
744
745template <class T>
746class ValueProxy : public ProxyInfo
747{
748  private:
749    T *scalar;
750
751  public:
752    ValueProxy(T &val) : scalar(&val) {}
753    Counter value() const { return *scalar; }
754    Result result() const { return *scalar; }
755    Result total() const { return *scalar; }
756};
757
758template <class T>
759class FunctorProxy : public ProxyInfo
760{
761  private:
762    T *functor;
763
764  public:
765    FunctorProxy(T &func) : functor(&func) {}
766    Counter value() const { return (*functor)(); }
767    Result result() const { return (*functor)(); }
768    Result total() const { return (*functor)(); }
769};
770
771template <class Derived>
772class ValueBase : public DataWrap<Derived, ScalarInfoProxy>
773{
774  private:
775    ProxyInfo *proxy;
776
777  public:
778    ValueBase() : proxy(NULL) { }
779    ~ValueBase() { if (proxy) delete proxy; }
780
781    template <class T>
782    Derived &
783    scalar(T &value)
784    {
785        proxy = new ValueProxy<T>(value);
786        this->setInit();
787        return this->self();
788    }
789
790    template <class T>
791    Derived &
792    functor(T &func)
793    {
794        proxy = new FunctorProxy<T>(func);
795        this->setInit();
796        return this->self();
797    }
798
799    Counter value() { return proxy->value(); }
800    Result result() const { return proxy->result(); }
801    Result total() const { return proxy->total(); };
802    size_type size() const { return proxy->size(); }
803
804    std::string str() const { return proxy->str(); }
805    bool zero() const { return proxy->zero(); }
806    bool check() const { return proxy != NULL; }
807    void prepare() { }
808    void reset() { }
809};
810
811//////////////////////////////////////////////////////////////////////
812//
813// Vector Statistics
814//
815//////////////////////////////////////////////////////////////////////
816
817/**
818 * A proxy class to access the stat at a given index in a VectorBase stat.
819 * Behaves like a ScalarBase.
820 */
821template <class Stat>
822class ScalarProxy
823{
824  private:
825    /** Pointer to the parent Vector. */
826    Stat &stat;
827
828    /** The index to access in the parent VectorBase. */
829    off_type index;
830
831  public:
832    /**
833     * Return the current value of this stat as its base type.
834     * @return The current value.
835     */
836    Counter value() const { return stat.data(index)->value(); }
837
838    /**
839     * Return the current value of this statas a result type.
840     * @return The current value.
841     */
842    Result result() const { return stat.data(index)->result(); }
843
844  public:
845    /**
846     * Create and initialize this proxy, do not register it with the database.
847     * @param i The index to access.
848     */
849    ScalarProxy(Stat &s, off_type i)
850        : stat(s), index(i)
851    {
852    }
853
854    /**
855     * Create a copy of the provided ScalarProxy.
856     * @param sp The proxy to copy.
857     */
858    ScalarProxy(const ScalarProxy &sp)
859        : stat(sp.stat), index(sp.index)
860    {}
861
862    /**
863     * Set this proxy equal to the provided one.
864     * @param sp The proxy to copy.
865     * @return A reference to this proxy.
866     */
867    const ScalarProxy &
868    operator=(const ScalarProxy &sp)
869    {
870        stat = sp.stat;
871        index = sp.index;
872        return *this;
873    }
874
875  public:
876    // Common operators for stats
877    /**
878     * Increment the stat by 1. This calls the associated storage object inc
879     * function.
880     */
881    void operator++() { stat.data(index)->inc(1); }
882    /**
883     * Decrement the stat by 1. This calls the associated storage object dec
884     * function.
885     */
886    void operator--() { stat.data(index)->dec(1); }
887
888    /** Increment the stat by 1. */
889    void operator++(int) { ++*this; }
890    /** Decrement the stat by 1. */
891    void operator--(int) { --*this; }
892
893    /**
894     * Set the data value to the given value. This calls the associated storage
895     * object set function.
896     * @param v The new value.
897     */
898    template <typename U>
899    void
900    operator=(const U &v)
901    {
902        stat.data(index)->set(v);
903    }
904
905    /**
906     * Increment the stat by the given value. This calls the associated
907     * storage object inc function.
908     * @param v The value to add.
909     */
910    template <typename U>
911    void
912    operator+=(const U &v)
913    {
914        stat.data(index)->inc(v);
915    }
916
917    /**
918     * Decrement the stat by the given value. This calls the associated
919     * storage object dec function.
920     * @param v The value to substract.
921     */
922    template <typename U>
923    void
924    operator-=(const U &v)
925    {
926        stat.data(index)->dec(v);
927    }
928
929    /**
930     * Return the number of elements, always 1 for a scalar.
931     * @return 1.
932     */
933    size_type size() const { return 1; }
934
935  public:
936    std::string
937    str() const
938    {
939        return csprintf("%s[%d]", stat.info()->name, index);
940    }
941};
942
943/**
944 * Implementation of a vector of stats. The type of stat is determined by the
945 * Storage class. @sa ScalarBase
946 */
947template <class Derived, class Stor>
948class VectorBase : public DataWrapVec<Derived, VectorInfoProxy>
949{
950  public:
951    typedef Stor Storage;
952    typedef typename Stor::Params Params;
953
954    /** Proxy type */
955    typedef ScalarProxy<Derived> Proxy;
956    friend class ScalarProxy<Derived>;
957    friend class DataWrapVec<Derived, VectorInfoProxy>;
958
959  protected:
960    /** The storage of this stat. */
961    Storage *storage;
962    size_type _size;
963
964  protected:
965    /**
966     * Retrieve the storage.
967     * @param index The vector index to access.
968     * @return The storage object at the given index.
969     */
970    Storage *data(off_type index) { return &storage[index]; }
971
972    /**
973     * Retrieve a const pointer to the storage.
974     * @param index The vector index to access.
975     * @return A const pointer to the storage object at the given index.
976     */
977    const Storage *data(off_type index) const { return &storage[index]; }
978
979    void
980    doInit(size_type s)
981    {
982        assert(s > 0 && "size must be positive!");
983        assert(!storage && "already initialized");
984        _size = s;
985
986        char *ptr = new char[_size * sizeof(Storage)];
987        storage = reinterpret_cast<Storage *>(ptr);
988
989        for (off_type i = 0; i < _size; ++i)
990            new (&storage[i]) Storage(this->info());
991
992        this->setInit();
993    }
994
995  public:
996    void
997    value(VCounter &vec) const
998    {
999        vec.resize(size());
1000        for (off_type i = 0; i < size(); ++i)
1001            vec[i] = data(i)->value();
1002    }
1003
1004    /**
1005     * Copy the values to a local vector and return a reference to it.
1006     * @return A reference to a vector of the stat values.
1007     */
1008    void
1009    result(VResult &vec) const
1010    {
1011        vec.resize(size());
1012        for (off_type i = 0; i < size(); ++i)
1013            vec[i] = data(i)->result();
1014    }
1015
1016    /**
1017     * Return a total of all entries in this vector.
1018     * @return The total of all vector entries.
1019     */
1020    Result
1021    total() const
1022    {
1023        Result total = 0.0;
1024        for (off_type i = 0; i < size(); ++i)
1025            total += data(i)->result();
1026        return total;
1027    }
1028
1029    /**
1030     * @return the number of elements in this vector.
1031     */
1032    size_type size() const { return _size; }
1033
1034    bool
1035    zero() const
1036    {
1037        for (off_type i = 0; i < size(); ++i)
1038            if (data(i)->zero())
1039                return false;
1040        return true;
1041    }
1042
1043    bool
1044    check() const
1045    {
1046        return storage != NULL;
1047    }
1048
1049  public:
1050    VectorBase()
1051        : storage(NULL)
1052    {}
1053
1054    ~VectorBase()
1055    {
1056        if (!storage)
1057            return;
1058
1059        for (off_type i = 0; i < _size; ++i)
1060            data(i)->~Storage();
1061        delete [] reinterpret_cast<char *>(storage);
1062    }
1063
1064    /**
1065     * Set this vector to have the given size.
1066     * @param size The new size.
1067     * @return A reference to this stat.
1068     */
1069    Derived &
1070    init(size_type size)
1071    {
1072        Derived &self = this->self();
1073        self.doInit(size);
1074        return self;
1075    }
1076
1077    /**
1078     * Return a reference (ScalarProxy) to the stat at the given index.
1079     * @param index The vector index to access.
1080     * @return A reference of the stat.
1081     */
1082    Proxy
1083    operator[](off_type index)
1084    {
1085        assert (index >= 0 && index < size());
1086        return Proxy(this->self(), index);
1087    }
1088};
1089
1090template <class Stat>
1091class VectorProxy
1092{
1093  private:
1094    Stat &stat;
1095    off_type offset;
1096    size_type len;
1097
1098  private:
1099    mutable VResult vec;
1100
1101    typename Stat::Storage *
1102    data(off_type index)
1103    {
1104        assert(index < len);
1105        return stat.data(offset + index);
1106    }
1107
1108    const typename Stat::Storage *
1109    data(off_type index) const
1110    {
1111        assert(index < len);
1112        return stat.data(offset + index);
1113    }
1114
1115  public:
1116    const VResult &
1117    result() const
1118    {
1119        vec.resize(size());
1120
1121        for (off_type i = 0; i < size(); ++i)
1122            vec[i] = data(i)->result();
1123
1124        return vec;
1125    }
1126
1127    Result
1128    total() const
1129    {
1130        Result total = 0.0;
1131        for (off_type i = 0; i < size(); ++i)
1132            total += data(i)->result();
1133        return total;
1134    }
1135
1136  public:
1137    VectorProxy(Stat &s, off_type o, size_type l)
1138        : stat(s), offset(o), len(l)
1139    {
1140    }
1141
1142    VectorProxy(const VectorProxy &sp)
1143        : stat(sp.stat), offset(sp.offset), len(sp.len)
1144    {
1145    }
1146
1147    const VectorProxy &
1148    operator=(const VectorProxy &sp)
1149    {
1150        stat = sp.stat;
1151        offset = sp.offset;
1152        len = sp.len;
1153        return *this;
1154    }
1155
1156    ScalarProxy<Stat>
1157    operator[](off_type index)
1158    {
1159        assert (index >= 0 && index < size());
1160        return ScalarProxy<Stat>(stat, offset + index);
1161    }
1162
1163    size_type size() const { return len; }
1164};
1165
1166template <class Derived, class Stor>
1167class Vector2dBase : public DataWrapVec2d<Derived, Vector2dInfoProxy>
1168{
1169  public:
1170    typedef Vector2dInfoProxy<Derived> Info;
1171    typedef Stor Storage;
1172    typedef typename Stor::Params Params;
1173    typedef VectorProxy<Derived> Proxy;
1174    friend class ScalarProxy<Derived>;
1175    friend class VectorProxy<Derived>;
1176    friend class DataWrapVec<Derived, Vector2dInfoProxy>;
1177    friend class DataWrapVec2d<Derived, Vector2dInfoProxy>;
1178
1179  protected:
1180    size_type x;
1181    size_type y;
1182    size_type _size;
1183    Storage *storage;
1184
1185  protected:
1186    Storage *data(off_type index) { return &storage[index]; }
1187    const Storage *data(off_type index) const { return &storage[index]; }
1188
1189  public:
1190    Vector2dBase()
1191        : storage(NULL)
1192    {}
1193
1194    ~Vector2dBase()
1195    {
1196        if (!storage)
1197            return;
1198
1199        for (off_type i = 0; i < _size; ++i)
1200            data(i)->~Storage();
1201        delete [] reinterpret_cast<char *>(storage);
1202    }
1203
1204    Derived &
1205    init(size_type _x, size_type _y)
1206    {
1207        assert(_x > 0 && _y > 0 && "sizes must be positive!");
1208        assert(!storage && "already initialized");
1209
1210        Derived &self = this->self();
1211        Info *info = this->info();
1212
1213        x = _x;
1214        y = _y;
1215        info->x = _x;
1216        info->y = _y;
1217        _size = x * y;
1218
1219        char *ptr = new char[_size * sizeof(Storage)];
1220        storage = reinterpret_cast<Storage *>(ptr);
1221
1222        for (off_type i = 0; i < _size; ++i)
1223            new (&storage[i]) Storage(info);
1224
1225        this->setInit();
1226
1227        return self;
1228    }
1229
1230    Proxy
1231    operator[](off_type index)
1232    {
1233        off_type offset = index * y;
1234        assert (index >= 0 && offset + index < size());
1235        return Proxy(this->self(), offset, y);
1236    }
1237
1238
1239    size_type
1240    size() const
1241    {
1242        return _size;
1243    }
1244
1245    bool
1246    zero() const
1247    {
1248        return data(0)->zero();
1249#if 0
1250        for (off_type i = 0; i < size(); ++i)
1251            if (!data(i)->zero())
1252                return false;
1253        return true;
1254#endif
1255    }
1256
1257    void
1258    prepare()
1259    {
1260        Info *info = this->info();
1261        size_type size = this->size();
1262
1263        for (off_type i = 0; i < size; ++i)
1264            data(i)->prepare(info);
1265
1266        info->cvec.resize(size);
1267        for (off_type i = 0; i < size; ++i)
1268            info->cvec[i] = data(i)->value();
1269    }
1270
1271    /**
1272     * Reset stat value to default
1273     */
1274    void
1275    reset()
1276    {
1277        Info *info = this->info();
1278        size_type size = this->size();
1279        for (off_type i = 0; i < size; ++i)
1280            data(i)->reset(info);
1281    }
1282
1283    bool
1284    check() const
1285    {
1286        return storage != NULL;
1287    }
1288};
1289
1290//////////////////////////////////////////////////////////////////////
1291//
1292// Non formula statistics
1293//
1294//////////////////////////////////////////////////////////////////////
1295/** The parameters for a distribution stat. */
1296struct DistParams : public StorageParams
1297{
1298    const DistType type;
1299    DistParams(DistType t) : type(t) {}
1300};
1301
1302/**
1303 * Templatized storage and interface for a distrbution stat.
1304 */
1305class DistStor
1306{
1307  public:
1308    /** The parameters for a distribution stat. */
1309    struct Params : public DistParams
1310    {
1311        /** The minimum value to track. */
1312        Counter min;
1313        /** The maximum value to track. */
1314        Counter max;
1315        /** The number of entries in each bucket. */
1316        Counter bucket_size;
1317        /** The number of buckets. Equal to (max-min)/bucket_size. */
1318        size_type buckets;
1319
1320        Params() : DistParams(Dist) {}
1321    };
1322
1323  private:
1324    /** The minimum value to track. */
1325    Counter min_track;
1326    /** The maximum value to track. */
1327    Counter max_track;
1328    /** The number of entries in each bucket. */
1329    Counter bucket_size;
1330    /** The number of buckets. Equal to (max-min)/bucket_size. */
1331    size_type buckets;
1332
1333    /** The smallest value sampled. */
1334    Counter min_val;
1335    /** The largest value sampled. */
1336    Counter max_val;
1337    /** The number of values sampled less than min. */
1338    Counter underflow;
1339    /** The number of values sampled more than max. */
1340    Counter overflow;
1341    /** The current sum. */
1342    Counter sum;
1343    /** The sum of squares. */
1344    Counter squares;
1345    /** The number of samples. */
1346    Counter samples;
1347    /** Counter for each bucket. */
1348    VCounter cvec;
1349
1350  public:
1351    DistStor(Info *info)
1352        : cvec(safe_cast<const Params *>(info->storageParams)->buckets)
1353    {
1354        reset(info);
1355    }
1356
1357    /**
1358     * Add a value to the distribution for the given number of times.
1359     * @param val The value to add.
1360     * @param number The number of times to add the value.
1361     */
1362    void
1363    sample(Counter val, int number)
1364    {
1365        if (val < min_track)
1366            underflow += number;
1367        else if (val > max_track)
1368            overflow += number;
1369        else {
1370            size_type index =
1371                (size_type)std::floor((val - min_track) / bucket_size);
1372            assert(index < size());
1373            cvec[index] += number;
1374        }
1375
1376        if (val < min_val)
1377            min_val = val;
1378
1379        if (val > max_val)
1380            max_val = val;
1381
1382        sum += val * number;
1383        squares += val * val * number;
1384        samples += number;
1385    }
1386
1387    /**
1388     * Return the number of buckets in this distribution.
1389     * @return the number of buckets.
1390     */
1391    size_type size() const { return cvec.size(); }
1392
1393    /**
1394     * Returns true if any calls to sample have been made.
1395     * @return True if any values have been sampled.
1396     */
1397    bool
1398    zero() const
1399    {
1400        return samples == Counter();
1401    }
1402
1403    void
1404    prepare(Info *info, DistData &data)
1405    {
1406        const Params *params = safe_cast<const Params *>(info->storageParams);
1407
1408        assert(params->type == Dist);
1409        data.type = params->type;
1410        data.min = params->min;
1411        data.max = params->max;
1412        data.bucket_size = params->bucket_size;
1413
1414        data.min_val = (min_val == CounterLimits::max()) ? 0 : min_val;
1415        data.max_val = (max_val == CounterLimits::min()) ? 0 : max_val;
1416        data.underflow = underflow;
1417        data.overflow = overflow;
1418
1419        size_type buckets = params->buckets;
1420        data.cvec.resize(buckets);
1421        for (off_type i = 0; i < buckets; ++i)
1422            data.cvec[i] = cvec[i];
1423
1424        data.sum = sum;
1425        data.squares = squares;
1426        data.samples = samples;
1427    }
1428
1429    /**
1430     * Reset stat value to default
1431     */
1432    void
1433    reset(Info *info)
1434    {
1435        const Params *params = safe_cast<const Params *>(info->storageParams);
1436        min_track = params->min;
1437        max_track = params->max;
1438        bucket_size = params->bucket_size;
1439
1440        min_val = CounterLimits::max();
1441        max_val = CounterLimits::min();
1442        underflow = Counter();
1443        overflow = Counter();
1444
1445        size_type size = cvec.size();
1446        for (off_type i = 0; i < size; ++i)
1447            cvec[i] = Counter();
1448
1449        sum = Counter();
1450        squares = Counter();
1451        samples = Counter();
1452    }
1453};
1454
1455/**
1456 * Templatized storage and interface for a histogram stat.
1457 */
1458class HistStor
1459{
1460  public:
1461    /** The parameters for a distribution stat. */
1462    struct Params : public DistParams
1463    {
1464        /** The number of buckets.. */
1465        size_type buckets;
1466
1467        Params() : DistParams(Hist) {}
1468    };
1469
1470  private:
1471    /** The minimum value to track. */
1472    Counter min_bucket;
1473    /** The maximum value to track. */
1474    Counter max_bucket;
1475    /** The number of entries in each bucket. */
1476    Counter bucket_size;
1477
1478    /** The current sum. */
1479    Counter sum;
1480    /** The sum of squares. */
1481    Counter squares;
1482    /** The number of samples. */
1483    Counter samples;
1484    /** Counter for each bucket. */
1485    VCounter cvec;
1486
1487  public:
1488    HistStor(Info *info)
1489        : cvec(safe_cast<const Params *>(info->storageParams)->buckets)
1490    {
1491        reset(info);
1492    }
1493
1494    void grow_up();
1495    void grow_out();
1496    void grow_convert();
1497
1498    /**
1499     * Add a value to the distribution for the given number of times.
1500     * @param val The value to add.
1501     * @param number The number of times to add the value.
1502     */
1503    void
1504    sample(Counter val, int number)
1505    {
1506        assert(min_bucket < max_bucket);
1507        if (val < min_bucket) {
1508            if (min_bucket == 0)
1509                grow_convert();
1510
1511            while (val < min_bucket)
1512                grow_out();
1513        } else if (val >= max_bucket + bucket_size) {
1514            if (min_bucket == 0) {
1515                while (val >= max_bucket + bucket_size)
1516                    grow_up();
1517            } else {
1518                while (val >= max_bucket + bucket_size)
1519                    grow_out();
1520            }
1521        }
1522
1523        size_type index =
1524            (int64_t)std::floor((val - min_bucket) / bucket_size);
1525
1526        assert(index >= 0 && index < size());
1527        cvec[index] += number;
1528
1529        sum += val * number;
1530        squares += val * val * number;
1531        samples += number;
1532    }
1533
1534    /**
1535     * Return the number of buckets in this distribution.
1536     * @return the number of buckets.
1537     */
1538    size_type size() const { return cvec.size(); }
1539
1540    /**
1541     * Returns true if any calls to sample have been made.
1542     * @return True if any values have been sampled.
1543     */
1544    bool
1545    zero() const
1546    {
1547        return samples == Counter();
1548    }
1549
1550    void
1551    prepare(Info *info, DistData &data)
1552    {
1553        const Params *params = safe_cast<const Params *>(info->storageParams);
1554
1555        assert(params->type == Hist);
1556        data.type = params->type;
1557        data.min = min_bucket;
1558        data.max = max_bucket + bucket_size - 1;
1559        data.bucket_size = bucket_size;
1560
1561        data.min_val = min_bucket;
1562        data.max_val = max_bucket;
1563
1564        int buckets = params->buckets;
1565        data.cvec.resize(buckets);
1566        for (off_type i = 0; i < buckets; ++i)
1567            data.cvec[i] = cvec[i];
1568
1569        data.sum = sum;
1570        data.squares = squares;
1571        data.samples = samples;
1572    }
1573
1574    /**
1575     * Reset stat value to default
1576     */
1577    void
1578    reset(Info *info)
1579    {
1580        const Params *params = safe_cast<const Params *>(info->storageParams);
1581        min_bucket = 0;
1582        max_bucket = params->buckets - 1;
1583        bucket_size = 1;
1584
1585        size_type size = cvec.size();
1586        for (off_type i = 0; i < size; ++i)
1587            cvec[i] = Counter();
1588
1589        sum = Counter();
1590        squares = Counter();
1591        samples = Counter();
1592    }
1593};
1594
1595/**
1596 * Templatized storage and interface for a distribution that calculates mean
1597 * and variance.
1598 */
1599class SampleStor
1600{
1601  public:
1602    struct Params : public DistParams
1603    {
1604        Params() : DistParams(Deviation) {}
1605    };
1606
1607  private:
1608    /** The current sum. */
1609    Counter sum;
1610    /** The sum of squares. */
1611    Counter squares;
1612    /** The number of samples. */
1613    Counter samples;
1614
1615  public:
1616    /**
1617     * Create and initialize this storage.
1618     */
1619    SampleStor(Info *info)
1620        : sum(Counter()), squares(Counter()), samples(Counter())
1621    { }
1622
1623    /**
1624     * Add a value the given number of times to this running average.
1625     * Update the running sum and sum of squares, increment the number of
1626     * values seen by the given number.
1627     * @param val The value to add.
1628     * @param number The number of times to add the value.
1629     */
1630    void
1631    sample(Counter val, int number)
1632    {
1633        Counter value = val * number;
1634        sum += value;
1635        squares += value * value;
1636        samples += number;
1637    }
1638
1639    /**
1640     * Return the number of entries in this stat, 1
1641     * @return 1.
1642     */
1643    size_type size() const { return 1; }
1644
1645    /**
1646     * Return true if no samples have been added.
1647     * @return True if no samples have been added.
1648     */
1649    bool zero() const { return samples == Counter(); }
1650
1651    void
1652    prepare(Info *info, DistData &data)
1653    {
1654        const Params *params = safe_cast<const Params *>(info->storageParams);
1655
1656        assert(params->type == Deviation);
1657        data.type = params->type;
1658        data.sum = sum;
1659        data.squares = squares;
1660        data.samples = samples;
1661    }
1662
1663    /**
1664     * Reset stat value to default
1665     */
1666    void
1667    reset(Info *info)
1668    {
1669        sum = Counter();
1670        squares = Counter();
1671        samples = Counter();
1672    }
1673};
1674
1675/**
1676 * Templatized storage for distribution that calculates per tick mean and
1677 * variance.
1678 */
1679class AvgSampleStor
1680{
1681  public:
1682    struct Params : public DistParams
1683    {
1684        Params() : DistParams(Deviation) {}
1685    };
1686
1687  private:
1688    /** Current total. */
1689    Counter sum;
1690    /** Current sum of squares. */
1691    Counter squares;
1692
1693  public:
1694    /**
1695     * Create and initialize this storage.
1696     */
1697    AvgSampleStor(Info *info)
1698        : sum(Counter()), squares(Counter())
1699    {}
1700
1701    /**
1702     * Add a value to the distribution for the given number of times.
1703     * Update the running sum and sum of squares.
1704     * @param val The value to add.
1705     * @param number The number of times to add the value.
1706     */
1707    void
1708    sample(Counter val, int number)
1709    {
1710        Counter value = val * number;
1711        sum += value;
1712        squares += value * value;
1713    }
1714
1715    /**
1716     * Return the number of entries, in this case 1.
1717     * @return 1.
1718     */
1719    size_type size() const { return 1; }
1720
1721    /**
1722     * Return true if no samples have been added.
1723     * @return True if the sum is zero.
1724     */
1725    bool zero() const { return sum == Counter(); }
1726
1727    void
1728    prepare(Info *info, DistData &data)
1729    {
1730        const Params *params = safe_cast<const Params *>(info->storageParams);
1731
1732        assert(params->type == Deviation);
1733        data.type = params->type;
1734        data.sum = sum;
1735        data.squares = squares;
1736        data.samples = curTick();
1737    }
1738
1739    /**
1740     * Reset stat value to default
1741     */
1742    void
1743    reset(Info *info)
1744    {
1745        sum = Counter();
1746        squares = Counter();
1747    }
1748};
1749
1750/**
1751 * Implementation of a distribution stat. The type of distribution is
1752 * determined by the Storage template. @sa ScalarBase
1753 */
1754template <class Derived, class Stor>
1755class DistBase : public DataWrap<Derived, DistInfoProxy>
1756{
1757  public:
1758    typedef DistInfoProxy<Derived> Info;
1759    typedef Stor Storage;
1760    typedef typename Stor::Params Params;
1761
1762  protected:
1763    /** The storage for this stat. */
1764    char storage[sizeof(Storage)] __attribute__ ((aligned (8)));
1765
1766  protected:
1767    /**
1768     * Retrieve the storage.
1769     * @return The storage object for this stat.
1770     */
1771    Storage *
1772    data()
1773    {
1774        return reinterpret_cast<Storage *>(storage);
1775    }
1776
1777    /**
1778     * Retrieve a const pointer to the storage.
1779     * @return A const pointer to the storage object for this stat.
1780     */
1781    const Storage *
1782    data() const
1783    {
1784        return reinterpret_cast<const Storage *>(storage);
1785    }
1786
1787    void
1788    doInit()
1789    {
1790        new (storage) Storage(this->info());
1791        this->setInit();
1792    }
1793
1794  public:
1795    DistBase() { }
1796
1797    /**
1798     * Add a value to the distribtion n times. Calls sample on the storage
1799     * class.
1800     * @param v The value to add.
1801     * @param n The number of times to add it, defaults to 1.
1802     */
1803    template <typename U>
1804    void sample(const U &v, int n = 1) { data()->sample(v, n); }
1805
1806    /**
1807     * Return the number of entries in this stat.
1808     * @return The number of entries.
1809     */
1810    size_type size() const { return data()->size(); }
1811    /**
1812     * Return true if no samples have been added.
1813     * @return True if there haven't been any samples.
1814     */
1815    bool zero() const { return data()->zero(); }
1816
1817    void
1818    prepare()
1819    {
1820        Info *info = this->info();
1821        data()->prepare(info, info->data);
1822    }
1823
1824    /**
1825     * Reset stat value to default
1826     */
1827    void
1828    reset()
1829    {
1830        data()->reset(this->info());
1831    }
1832};
1833
1834template <class Stat>
1835class DistProxy;
1836
1837template <class Derived, class Stor>
1838class VectorDistBase : public DataWrapVec<Derived, VectorDistInfoProxy>
1839{
1840  public:
1841    typedef VectorDistInfoProxy<Derived> Info;
1842    typedef Stor Storage;
1843    typedef typename Stor::Params Params;
1844    typedef DistProxy<Derived> Proxy;
1845    friend class DistProxy<Derived>;
1846    friend class DataWrapVec<Derived, VectorDistInfoProxy>;
1847
1848  protected:
1849    Storage *storage;
1850    size_type _size;
1851
1852  protected:
1853    Storage *
1854    data(off_type index)
1855    {
1856        return &storage[index];
1857    }
1858
1859    const Storage *
1860    data(off_type index) const
1861    {
1862        return &storage[index];
1863    }
1864
1865    void
1866    doInit(size_type s)
1867    {
1868        assert(s > 0 && "size must be positive!");
1869        assert(!storage && "already initialized");
1870        _size = s;
1871
1872        char *ptr = new char[_size * sizeof(Storage)];
1873        storage = reinterpret_cast<Storage *>(ptr);
1874
1875        Info *info = this->info();
1876        for (off_type i = 0; i < _size; ++i)
1877            new (&storage[i]) Storage(info);
1878
1879        this->setInit();
1880    }
1881
1882  public:
1883    VectorDistBase()
1884        : storage(NULL)
1885    {}
1886
1887    ~VectorDistBase()
1888    {
1889        if (!storage)
1890            return ;
1891
1892        for (off_type i = 0; i < _size; ++i)
1893            data(i)->~Storage();
1894        delete [] reinterpret_cast<char *>(storage);
1895    }
1896
1897    Proxy operator[](off_type index)
1898    {
1899        assert(index >= 0 && index < size());
1900        return Proxy(this->self(), index);
1901    }
1902
1903    size_type
1904    size() const
1905    {
1906        return _size;
1907    }
1908
1909    bool
1910    zero() const
1911    {
1912        for (off_type i = 0; i < size(); ++i)
1913            if (!data(i)->zero())
1914                return false;
1915        return true;
1916    }
1917
1918    void
1919    prepare()
1920    {
1921        Info *info = this->info();
1922        size_type size = this->size();
1923        info->data.resize(size);
1924        for (off_type i = 0; i < size; ++i)
1925            data(i)->prepare(info, info->data[i]);
1926    }
1927
1928    bool
1929    check() const
1930    {
1931        return storage != NULL;
1932    }
1933};
1934
1935template <class Stat>
1936class DistProxy
1937{
1938  private:
1939    Stat &stat;
1940    off_type index;
1941
1942  protected:
1943    typename Stat::Storage *data() { return stat.data(index); }
1944    const typename Stat::Storage *data() const { return stat.data(index); }
1945
1946  public:
1947    DistProxy(Stat &s, off_type i)
1948        : stat(s), index(i)
1949    {}
1950
1951    DistProxy(const DistProxy &sp)
1952        : stat(sp.stat), index(sp.index)
1953    {}
1954
1955    const DistProxy &
1956    operator=(const DistProxy &sp)
1957    {
1958        stat = sp.stat;
1959        index = sp.index;
1960        return *this;
1961    }
1962
1963  public:
1964    template <typename U>
1965    void
1966    sample(const U &v, int n = 1)
1967    {
1968        data()->sample(v, n);
1969    }
1970
1971    size_type
1972    size() const
1973    {
1974        return 1;
1975    }
1976
1977    bool
1978    zero() const
1979    {
1980        return data()->zero();
1981    }
1982
1983    /**
1984     * Proxy has no state.  Nothing to reset.
1985     */
1986    void reset() { }
1987};
1988
1989//////////////////////////////////////////////////////////////////////
1990//
1991//  Formula Details
1992//
1993//////////////////////////////////////////////////////////////////////
1994
1995/**
1996 * Base class for formula statistic node. These nodes are used to build a tree
1997 * that represents the formula.
1998 */
1999class Node : public RefCounted
2000{
2001  public:
2002    /**
2003     * Return the number of nodes in the subtree starting at this node.
2004     * @return the number of nodes in this subtree.
2005     */
2006    virtual size_type size() const = 0;
2007    /**
2008     * Return the result vector of this subtree.
2009     * @return The result vector of this subtree.
2010     */
2011    virtual const VResult &result() const = 0;
2012    /**
2013     * Return the total of the result vector.
2014     * @return The total of the result vector.
2015     */
2016    virtual Result total() const = 0;
2017
2018    /**
2019     *
2020     */
2021    virtual std::string str() const = 0;
2022};
2023
2024/** Reference counting pointer to a function Node. */
2025typedef RefCountingPtr<Node> NodePtr;
2026
2027class ScalarStatNode : public Node
2028{
2029  private:
2030    const ScalarInfo *data;
2031    mutable VResult vresult;
2032
2033  public:
2034    ScalarStatNode(const ScalarInfo *d) : data(d), vresult(1) {}
2035
2036    const VResult &
2037    result() const
2038    {
2039        vresult[0] = data->result();
2040        return vresult;
2041    }
2042
2043    Result total() const { return data->result(); };
2044
2045    size_type size() const { return 1; }
2046
2047    /**
2048     *
2049     */
2050    std::string str() const { return data->name; }
2051};
2052
2053template <class Stat>
2054class ScalarProxyNode : public Node
2055{
2056  private:
2057    const ScalarProxy<Stat> proxy;
2058    mutable VResult vresult;
2059
2060  public:
2061    ScalarProxyNode(const ScalarProxy<Stat> &p)
2062        : proxy(p), vresult(1)
2063    { }
2064
2065    const VResult &
2066    result() const
2067    {
2068        vresult[0] = proxy.result();
2069        return vresult;
2070    }
2071
2072    Result
2073    total() const
2074    {
2075        return proxy.result();
2076    }
2077
2078    size_type
2079    size() const
2080    {
2081        return 1;
2082    }
2083
2084    /**
2085     *
2086     */
2087    std::string
2088    str() const
2089    {
2090        return proxy.str();
2091    }
2092};
2093
2094class VectorStatNode : public Node
2095{
2096  private:
2097    const VectorInfo *data;
2098
2099  public:
2100    VectorStatNode(const VectorInfo *d) : data(d) { }
2101    const VResult &result() const { return data->result(); }
2102    Result total() const { return data->total(); };
2103
2104    size_type size() const { return data->size(); }
2105
2106    std::string str() const { return data->name; }
2107};
2108
2109template <class T>
2110class ConstNode : public Node
2111{
2112  private:
2113    VResult vresult;
2114
2115  public:
2116    ConstNode(T s) : vresult(1, (Result)s) {}
2117    const VResult &result() const { return vresult; }
2118    Result total() const { return vresult[0]; };
2119    size_type size() const { return 1; }
2120    std::string str() const { return to_string(vresult[0]); }
2121};
2122
2123template <class T>
2124class ConstVectorNode : public Node
2125{
2126  private:
2127    VResult vresult;
2128
2129  public:
2130    ConstVectorNode(const T &s) : vresult(s.begin(), s.end()) {}
2131    const VResult &result() const { return vresult; }
2132
2133    Result
2134    total() const
2135    {
2136        size_type size = this->size();
2137        Result tmp = 0;
2138        for (off_type i = 0; i < size; i++)
2139            tmp += vresult[i];
2140        return tmp;
2141    }
2142
2143    size_type size() const { return vresult.size(); }
2144    std::string
2145    str() const
2146    {
2147        size_type size = this->size();
2148        std::string tmp = "(";
2149        for (off_type i = 0; i < size; i++)
2150            tmp += csprintf("%s ",to_string(vresult[i]));
2151        tmp += ")";
2152        return tmp;
2153    }
2154};
2155
2156template <class Op>
2157struct OpString;
2158
2159template<>
2160struct OpString<std::plus<Result> >
2161{
2162    static std::string str() { return "+"; }
2163};
2164
2165template<>
2166struct OpString<std::minus<Result> >
2167{
2168    static std::string str() { return "-"; }
2169};
2170
2171template<>
2172struct OpString<std::multiplies<Result> >
2173{
2174    static std::string str() { return "*"; }
2175};
2176
2177template<>
2178struct OpString<std::divides<Result> >
2179{
2180    static std::string str() { return "/"; }
2181};
2182
2183template<>
2184struct OpString<std::modulus<Result> >
2185{
2186    static std::string str() { return "%"; }
2187};
2188
2189template<>
2190struct OpString<std::negate<Result> >
2191{
2192    static std::string str() { return "-"; }
2193};
2194
2195template <class Op>
2196class UnaryNode : public Node
2197{
2198  public:
2199    NodePtr l;
2200    mutable VResult vresult;
2201
2202  public:
2203    UnaryNode(NodePtr &p) : l(p) {}
2204
2205    const VResult &
2206    result() const
2207    {
2208        const VResult &lvec = l->result();
2209        size_type size = lvec.size();
2210
2211        assert(size > 0);
2212
2213        vresult.resize(size);
2214        Op op;
2215        for (off_type i = 0; i < size; ++i)
2216            vresult[i] = op(lvec[i]);
2217
2218        return vresult;
2219    }
2220
2221    Result
2222    total() const
2223    {
2224        const VResult &vec = this->result();
2225        Result total = 0.0;
2226        for (off_type i = 0; i < size(); i++)
2227            total += vec[i];
2228        return total;
2229    }
2230
2231    size_type size() const { return l->size(); }
2232
2233    std::string
2234    str() const
2235    {
2236        return OpString<Op>::str() + l->str();
2237    }
2238};
2239
2240template <class Op>
2241class BinaryNode : public Node
2242{
2243  public:
2244    NodePtr l;
2245    NodePtr r;
2246    mutable VResult vresult;
2247
2248  public:
2249    BinaryNode(NodePtr &a, NodePtr &b) : l(a), r(b) {}
2250
2251    const VResult &
2252    result() const
2253    {
2254        Op op;
2255        const VResult &lvec = l->result();
2256        const VResult &rvec = r->result();
2257
2258        assert(lvec.size() > 0 && rvec.size() > 0);
2259
2260        if (lvec.size() == 1 && rvec.size() == 1) {
2261            vresult.resize(1);
2262            vresult[0] = op(lvec[0], rvec[0]);
2263        } else if (lvec.size() == 1) {
2264            size_type size = rvec.size();
2265            vresult.resize(size);
2266            for (off_type i = 0; i < size; ++i)
2267                vresult[i] = op(lvec[0], rvec[i]);
2268        } else if (rvec.size() == 1) {
2269            size_type size = lvec.size();
2270            vresult.resize(size);
2271            for (off_type i = 0; i < size; ++i)
2272                vresult[i] = op(lvec[i], rvec[0]);
2273        } else if (rvec.size() == lvec.size()) {
2274            size_type size = rvec.size();
2275            vresult.resize(size);
2276            for (off_type i = 0; i < size; ++i)
2277                vresult[i] = op(lvec[i], rvec[i]);
2278        }
2279
2280        return vresult;
2281    }
2282
2283    Result
2284    total() const
2285    {
2286        const VResult &vec = this->result();
2287        Result total = 0.0;
2288        for (off_type i = 0; i < size(); i++)
2289            total += vec[i];
2290        return total;
2291    }
2292
2293    size_type
2294    size() const
2295    {
2296        size_type ls = l->size();
2297        size_type rs = r->size();
2298        if (ls == 1) {
2299            return rs;
2300        } else if (rs == 1) {
2301            return ls;
2302        } else {
2303            assert(ls == rs && "Node vector sizes are not equal");
2304            return ls;
2305        }
2306    }
2307
2308    std::string
2309    str() const
2310    {
2311        return csprintf("(%s %s %s)", l->str(), OpString<Op>::str(), r->str());
2312    }
2313};
2314
2315template <class Op>
2316class SumNode : public Node
2317{
2318  public:
2319    NodePtr l;
2320    mutable VResult vresult;
2321
2322  public:
2323    SumNode(NodePtr &p) : l(p), vresult(1) {}
2324
2325    const VResult &
2326    result() const
2327    {
2328        const VResult &lvec = l->result();
2329        size_type size = lvec.size();
2330        assert(size > 0);
2331
2332        vresult[0] = 0.0;
2333
2334        Op op;
2335        for (off_type i = 0; i < size; ++i)
2336            vresult[0] = op(vresult[0], lvec[i]);
2337
2338        return vresult;
2339    }
2340
2341    Result
2342    total() const
2343    {
2344        const VResult &lvec = l->result();
2345        size_type size = lvec.size();
2346        assert(size > 0);
2347
2348        Result vresult = 0.0;
2349
2350        Op op;
2351        for (off_type i = 0; i < size; ++i)
2352            vresult = op(vresult, lvec[i]);
2353
2354        return vresult;
2355    }
2356
2357    size_type size() const { return 1; }
2358
2359    std::string
2360    str() const
2361    {
2362        return csprintf("total(%s)", l->str());
2363    }
2364};
2365
2366
2367//////////////////////////////////////////////////////////////////////
2368//
2369// Visible Statistics Types
2370//
2371//////////////////////////////////////////////////////////////////////
2372/**
2373 * @defgroup VisibleStats "Statistic Types"
2374 * These are the statistics that are used in the simulator.
2375 * @{
2376 */
2377
2378/**
2379 * This is a simple scalar statistic, like a counter.
2380 * @sa Stat, ScalarBase, StatStor
2381 */
2382class Scalar : public ScalarBase<Scalar, StatStor>
2383{
2384  public:
2385    using ScalarBase<Scalar, StatStor>::operator=;
2386};
2387
2388/**
2389 * A stat that calculates the per tick average of a value.
2390 * @sa Stat, ScalarBase, AvgStor
2391 */
2392class Average : public ScalarBase<Average, AvgStor>
2393{
2394  public:
2395    using ScalarBase<Average, AvgStor>::operator=;
2396};
2397
2398class Value : public ValueBase<Value>
2399{
2400};
2401
2402/**
2403 * A vector of scalar stats.
2404 * @sa Stat, VectorBase, StatStor
2405 */
2406class Vector : public VectorBase<Vector, StatStor>
2407{
2408};
2409
2410/**
2411 * A vector of Average stats.
2412 * @sa Stat, VectorBase, AvgStor
2413 */
2414class AverageVector : public VectorBase<AverageVector, AvgStor>
2415{
2416};
2417
2418/**
2419 * A 2-Dimensional vecto of scalar stats.
2420 * @sa Stat, Vector2dBase, StatStor
2421 */
2422class Vector2d : public Vector2dBase<Vector2d, StatStor>
2423{
2424};
2425
2426/**
2427 * A simple distribution stat.
2428 * @sa Stat, DistBase, DistStor
2429 */
2430class Distribution : public DistBase<Distribution, DistStor>
2431{
2432  public:
2433    /**
2434     * Set the parameters of this distribution. @sa DistStor::Params
2435     * @param min The minimum value of the distribution.
2436     * @param max The maximum value of the distribution.
2437     * @param bkt The number of values in each bucket.
2438     * @return A reference to this distribution.
2439     */
2440    Distribution &
2441    init(Counter min, Counter max, Counter bkt)
2442    {
2443        DistStor::Params *params = new DistStor::Params;
2444        params->min = min;
2445        params->max = max;
2446        params->bucket_size = bkt;
2447        params->buckets = (size_type)ceil((max - min + 1.0) / bkt);
2448        this->setParams(params);
2449        this->doInit();
2450        return this->self();
2451    }
2452};
2453
2454/**
2455 * A simple histogram stat.
2456 * @sa Stat, DistBase, HistStor
2457 */
2458class Histogram : public DistBase<Histogram, HistStor>
2459{
2460  public:
2461    /**
2462     * Set the parameters of this histogram. @sa HistStor::Params
2463     * @param size The number of buckets in the histogram
2464     * @return A reference to this histogram.
2465     */
2466    Histogram &
2467    init(size_type size)
2468    {
2469        HistStor::Params *params = new HistStor::Params;
2470        params->buckets = size;
2471        this->setParams(params);
2472        this->doInit();
2473        return this->self();
2474    }
2475};
2476
2477/**
2478 * Calculates the mean and variance of all the samples.
2479 * @sa DistBase, SampleStor
2480 */
2481class StandardDeviation : public DistBase<StandardDeviation, SampleStor>
2482{
2483  public:
2484    /**
2485     * Construct and initialize this distribution.
2486     */
2487    StandardDeviation()
2488    {
2489        SampleStor::Params *params = new SampleStor::Params;
2490        this->doInit();
2491        this->setParams(params);
2492    }
2493};
2494
2495/**
2496 * Calculates the per tick mean and variance of the samples.
2497 * @sa DistBase, AvgSampleStor
2498 */
2499class AverageDeviation : public DistBase<AverageDeviation, AvgSampleStor>
2500{
2501  public:
2502    /**
2503     * Construct and initialize this distribution.
2504     */
2505    AverageDeviation()
2506    {
2507        AvgSampleStor::Params *params = new AvgSampleStor::Params;
2508        this->doInit();
2509        this->setParams(params);
2510    }
2511};
2512
2513/**
2514 * A vector of distributions.
2515 * @sa VectorDistBase, DistStor
2516 */
2517class VectorDistribution : public VectorDistBase<VectorDistribution, DistStor>
2518{
2519  public:
2520    /**
2521     * Initialize storage and parameters for this distribution.
2522     * @param size The size of the vector (the number of distributions).
2523     * @param min The minimum value of the distribution.
2524     * @param max The maximum value of the distribution.
2525     * @param bkt The number of values in each bucket.
2526     * @return A reference to this distribution.
2527     */
2528    VectorDistribution &
2529    init(size_type size, Counter min, Counter max, Counter bkt)
2530    {
2531        DistStor::Params *params = new DistStor::Params;
2532        params->min = min;
2533        params->max = max;
2534        params->bucket_size = bkt;
2535        params->buckets = (size_type)ceil((max - min + 1.0) / bkt);
2536        this->setParams(params);
2537        this->doInit(size);
2538        return this->self();
2539    }
2540};
2541
2542/**
2543 * This is a vector of StandardDeviation stats.
2544 * @sa VectorDistBase, SampleStor
2545 */
2546class VectorStandardDeviation
2547    : public VectorDistBase<VectorStandardDeviation, SampleStor>
2548{
2549  public:
2550    /**
2551     * Initialize storage for this distribution.
2552     * @param size The size of the vector.
2553     * @return A reference to this distribution.
2554     */
2555    VectorStandardDeviation &
2556    init(size_type size)
2557    {
2558        SampleStor::Params *params = new SampleStor::Params;
2559        this->doInit(size);
2560        this->setParams(params);
2561        return this->self();
2562    }
2563};
2564
2565/**
2566 * This is a vector of AverageDeviation stats.
2567 * @sa VectorDistBase, AvgSampleStor
2568 */
2569class VectorAverageDeviation
2570    : public VectorDistBase<VectorAverageDeviation, AvgSampleStor>
2571{
2572  public:
2573    /**
2574     * Initialize storage for this distribution.
2575     * @param size The size of the vector.
2576     * @return A reference to this distribution.
2577     */
2578    VectorAverageDeviation &
2579    init(size_type size)
2580    {
2581        AvgSampleStor::Params *params = new AvgSampleStor::Params;
2582        this->doInit(size);
2583        this->setParams(params);
2584        return this->self();
2585    }
2586};
2587
2588template <class Stat>
2589class FormulaInfoProxy : public InfoProxy<Stat, FormulaInfo>
2590{
2591  protected:
2592    mutable VResult vec;
2593    mutable VCounter cvec;
2594
2595  public:
2596    FormulaInfoProxy(Stat &stat) : InfoProxy<Stat, FormulaInfo>(stat) {}
2597
2598    size_type size() const { return this->s.size(); }
2599
2600    const VResult &
2601    result() const
2602    {
2603        this->s.result(vec);
2604        return vec;
2605    }
2606    Result total() const { return this->s.total(); }
2607    VCounter &value() const { return cvec; }
2608
2609    std::string str() const { return this->s.str(); }
2610};
2611
2612template <class Stat>
2613class SparseHistInfoProxy : public InfoProxy<Stat, SparseHistInfo>
2614{
2615  public:
2616    SparseHistInfoProxy(Stat &stat) : InfoProxy<Stat, SparseHistInfo>(stat) {}
2617};
2618
2619/**
2620 * Implementation of a sparse histogram stat. The storage class is
2621 * determined by the Storage template.
2622 */
2623template <class Derived, class Stor>
2624class SparseHistBase : public DataWrap<Derived, SparseHistInfoProxy>
2625{
2626  public:
2627    typedef SparseHistInfoProxy<Derived> Info;
2628    typedef Stor Storage;
2629    typedef typename Stor::Params Params;
2630
2631  protected:
2632    /** The storage for this stat. */
2633    char storage[sizeof(Storage)];
2634
2635  protected:
2636    /**
2637     * Retrieve the storage.
2638     * @return The storage object for this stat.
2639     */
2640    Storage *
2641    data()
2642    {
2643        return reinterpret_cast<Storage *>(storage);
2644    }
2645
2646    /**
2647     * Retrieve a const pointer to the storage.
2648     * @return A const pointer to the storage object for this stat.
2649     */
2650    const Storage *
2651    data() const
2652    {
2653        return reinterpret_cast<const Storage *>(storage);
2654    }
2655
2656    void
2657    doInit()
2658    {
2659        new (storage) Storage(this->info());
2660        this->setInit();
2661    }
2662
2663  public:
2664    SparseHistBase() { }
2665
2666    /**
2667     * Add a value to the distribtion n times. Calls sample on the storage
2668     * class.
2669     * @param v The value to add.
2670     * @param n The number of times to add it, defaults to 1.
2671     */
2672    template <typename U>
2673    void sample(const U &v, int n = 1) { data()->sample(v, n); }
2674
2675    /**
2676     * Return the number of entries in this stat.
2677     * @return The number of entries.
2678     */
2679    size_type size() const { return data()->size(); }
2680    /**
2681     * Return true if no samples have been added.
2682     * @return True if there haven't been any samples.
2683     */
2684    bool zero() const { return data()->zero(); }
2685
2686    void
2687    prepare()
2688    {
2689        Info *info = this->info();
2690        data()->prepare(info, info->data);
2691    }
2692
2693    /**
2694     * Reset stat value to default
2695     */
2696    void
2697    reset()
2698    {
2699        data()->reset(this->info());
2700    }
2701};
2702
2703/**
2704 * Templatized storage and interface for a sparse histogram stat.
2705 */
2706class SparseHistStor
2707{
2708  public:
2709    /** The parameters for a sparse histogram stat. */
2710    struct Params : public DistParams
2711    {
2712        Params() : DistParams(Hist) {}
2713    };
2714
2715  private:
2716    /** Counter for number of samples */
2717    Counter samples;
2718    /** Counter for each bucket. */
2719    MCounter cmap;
2720
2721  public:
2722    SparseHistStor(Info *info)
2723    {
2724        reset(info);
2725    }
2726
2727    /**
2728     * Add a value to the distribution for the given number of times.
2729     * @param val The value to add.
2730     * @param number The number of times to add the value.
2731     */
2732    void
2733    sample(Counter val, int number)
2734    {
2735        cmap[val] += number;
2736        samples += number;
2737    }
2738
2739    /**
2740     * Return the number of buckets in this distribution.
2741     * @return the number of buckets.
2742     */
2743    size_type size() const { return cmap.size(); }
2744
2745    /**
2746     * Returns true if any calls to sample have been made.
2747     * @return True if any values have been sampled.
2748     */
2749    bool
2750    zero() const
2751    {
2752        return samples == Counter();
2753    }
2754
2755    void
2756    prepare(Info *info, SparseHistData &data)
2757    {
2758        MCounter::iterator it;
2759        data.cmap.clear();
2760        for (it = cmap.begin(); it != cmap.end(); it++) {
2761            data.cmap[(*it).first] = (*it).second;
2762        }
2763
2764        data.samples = samples;
2765    }
2766
2767    /**
2768     * Reset stat value to default
2769     */
2770    void
2771    reset(Info *info)
2772    {
2773        cmap.clear();
2774        samples = 0;
2775    }
2776};
2777
2778class SparseHistogram : public SparseHistBase<SparseHistogram, SparseHistStor>
2779{
2780  public:
2781    /**
2782     * Set the parameters of this histogram. @sa HistStor::Params
2783     * @param size The number of buckets in the histogram
2784     * @return A reference to this histogram.
2785     */
2786    SparseHistogram &
2787    init(size_type size)
2788    {
2789        SparseHistStor::Params *params = new SparseHistStor::Params;
2790        this->setParams(params);
2791        this->doInit();
2792        return this->self();
2793    }
2794};
2795
2796class Temp;
2797/**
2798 * A formula for statistics that is calculated when printed. A formula is
2799 * stored as a tree of Nodes that represent the equation to calculate.
2800 * @sa Stat, ScalarStat, VectorStat, Node, Temp
2801 */
2802class Formula : public DataWrapVec<Formula, FormulaInfoProxy>
2803{
2804  protected:
2805    /** The root of the tree which represents the Formula */
2806    NodePtr root;
2807    friend class Temp;
2808
2809  public:
2810    /**
2811     * Create and initialize thie formula, and register it with the database.
2812     */
2813    Formula();
2814
2815    /**
2816     * Create a formula with the given root node, register it with the
2817     * database.
2818     * @param r The root of the expression tree.
2819     */
2820    Formula(Temp r);
2821
2822    /**
2823     * Set an unitialized Formula to the given root.
2824     * @param r The root of the expression tree.
2825     * @return a reference to this formula.
2826     */
2827    const Formula &operator=(Temp r);
2828
2829    /**
2830     * Add the given tree to the existing one.
2831     * @param r The root of the expression tree.
2832     * @return a reference to this formula.
2833     */
2834    const Formula &operator+=(Temp r);
2835    /**
2836     * Return the result of the Fomula in a vector.  If there were no Vector
2837     * components to the Formula, then the vector is size 1.  If there were,
2838     * like x/y with x being a vector of size 3, then the result returned will
2839     * be x[0]/y, x[1]/y, x[2]/y, respectively.
2840     * @return The result vector.
2841     */
2842    void result(VResult &vec) const;
2843
2844    /**
2845     * Return the total Formula result.  If there is a Vector
2846     * component to this Formula, then this is the result of the
2847     * Formula if the formula is applied after summing all the
2848     * components of the Vector.  For example, if Formula is x/y where
2849     * x is size 3, then total() will return (x[1]+x[2]+x[3])/y.  If
2850     * there is no Vector component, total() returns the same value as
2851     * the first entry in the VResult val() returns.
2852     * @return The total of the result vector.
2853     */
2854    Result total() const;
2855
2856    /**
2857     * Return the number of elements in the tree.
2858     */
2859    size_type size() const;
2860
2861    void prepare() { }
2862
2863    /**
2864     * Formulas don't need to be reset
2865     */
2866    void reset();
2867
2868    /**
2869     *
2870     */
2871    bool zero() const;
2872
2873    std::string str() const;
2874};
2875
2876class FormulaNode : public Node
2877{
2878  private:
2879    const Formula &formula;
2880    mutable VResult vec;
2881
2882  public:
2883    FormulaNode(const Formula &f) : formula(f) {}
2884
2885    size_type size() const { return formula.size(); }
2886    const VResult &result() const { formula.result(vec); return vec; }
2887    Result total() const { return formula.total(); }
2888
2889    std::string str() const { return formula.str(); }
2890};
2891
2892/**
2893 * Helper class to construct formula node trees.
2894 */
2895class Temp
2896{
2897  protected:
2898    /**
2899     * Pointer to a Node object.
2900     */
2901    NodePtr node;
2902
2903  public:
2904    /**
2905     * Copy the given pointer to this class.
2906     * @param n A pointer to a Node object to copy.
2907     */
2908    Temp(NodePtr n) : node(n) { }
2909
2910    /**
2911     * Return the node pointer.
2912     * @return the node pointer.
2913     */
2914    operator NodePtr&() { return node; }
2915
2916  public:
2917    /**
2918     * Create a new ScalarStatNode.
2919     * @param s The ScalarStat to place in a node.
2920     */
2921    Temp(const Scalar &s)
2922        : node(new ScalarStatNode(s.info()))
2923    { }
2924
2925    /**
2926     * Create a new ScalarStatNode.
2927     * @param s The ScalarStat to place in a node.
2928     */
2929    Temp(const Value &s)
2930        : node(new ScalarStatNode(s.info()))
2931    { }
2932
2933    /**
2934     * Create a new ScalarStatNode.
2935     * @param s The ScalarStat to place in a node.
2936     */
2937    Temp(const Average &s)
2938        : node(new ScalarStatNode(s.info()))
2939    { }
2940
2941    /**
2942     * Create a new VectorStatNode.
2943     * @param s The VectorStat to place in a node.
2944     */
2945    Temp(const Vector &s)
2946        : node(new VectorStatNode(s.info()))
2947    { }
2948
2949    Temp(const AverageVector &s)
2950        : node(new VectorStatNode(s.info()))
2951    { }
2952
2953    /**
2954     *
2955     */
2956    Temp(const Formula &f)
2957        : node(new FormulaNode(f))
2958    { }
2959
2960    /**
2961     * Create a new ScalarProxyNode.
2962     * @param p The ScalarProxy to place in a node.
2963     */
2964    template <class Stat>
2965    Temp(const ScalarProxy<Stat> &p)
2966        : node(new ScalarProxyNode<Stat>(p))
2967    { }
2968
2969    /**
2970     * Create a ConstNode
2971     * @param value The value of the const node.
2972     */
2973    Temp(signed char value)
2974        : node(new ConstNode<signed char>(value))
2975    { }
2976
2977    /**
2978     * Create a ConstNode
2979     * @param value The value of the const node.
2980     */
2981    Temp(unsigned char value)
2982        : node(new ConstNode<unsigned char>(value))
2983    { }
2984
2985    /**
2986     * Create a ConstNode
2987     * @param value The value of the const node.
2988     */
2989    Temp(signed short value)
2990        : node(new ConstNode<signed short>(value))
2991    { }
2992
2993    /**
2994     * Create a ConstNode
2995     * @param value The value of the const node.
2996     */
2997    Temp(unsigned short value)
2998        : node(new ConstNode<unsigned short>(value))
2999    { }
3000
3001    /**
3002     * Create a ConstNode
3003     * @param value The value of the const node.
3004     */
3005    Temp(signed int value)
3006        : node(new ConstNode<signed int>(value))
3007    { }
3008
3009    /**
3010     * Create a ConstNode
3011     * @param value The value of the const node.
3012     */
3013    Temp(unsigned int value)
3014        : node(new ConstNode<unsigned int>(value))
3015    { }
3016
3017    /**
3018     * Create a ConstNode
3019     * @param value The value of the const node.
3020     */
3021    Temp(signed long value)
3022        : node(new ConstNode<signed long>(value))
3023    { }
3024
3025    /**
3026     * Create a ConstNode
3027     * @param value The value of the const node.
3028     */
3029    Temp(unsigned long value)
3030        : node(new ConstNode<unsigned long>(value))
3031    { }
3032
3033    /**
3034     * Create a ConstNode
3035     * @param value The value of the const node.
3036     */
3037    Temp(signed long long value)
3038        : node(new ConstNode<signed long long>(value))
3039    { }
3040
3041    /**
3042     * Create a ConstNode
3043     * @param value The value of the const node.
3044     */
3045    Temp(unsigned long long value)
3046        : node(new ConstNode<unsigned long long>(value))
3047    { }
3048
3049    /**
3050     * Create a ConstNode
3051     * @param value The value of the const node.
3052     */
3053    Temp(float value)
3054        : node(new ConstNode<float>(value))
3055    { }
3056
3057    /**
3058     * Create a ConstNode
3059     * @param value The value of the const node.
3060     */
3061    Temp(double value)
3062        : node(new ConstNode<double>(value))
3063    { }
3064};
3065
3066
3067/**
3068 * @}
3069 */
3070
3071inline Temp
3072operator+(Temp l, Temp r)
3073{
3074    return NodePtr(new BinaryNode<std::plus<Result> >(l, r));
3075}
3076
3077inline Temp
3078operator-(Temp l, Temp r)
3079{
3080    return NodePtr(new BinaryNode<std::minus<Result> >(l, r));
3081}
3082
3083inline Temp
3084operator*(Temp l, Temp r)
3085{
3086    return NodePtr(new BinaryNode<std::multiplies<Result> >(l, r));
3087}
3088
3089inline Temp
3090operator/(Temp l, Temp r)
3091{
3092    return NodePtr(new BinaryNode<std::divides<Result> >(l, r));
3093}
3094
3095inline Temp
3096operator-(Temp l)
3097{
3098    return NodePtr(new UnaryNode<std::negate<Result> >(l));
3099}
3100
3101template <typename T>
3102inline Temp
3103constant(T val)
3104{
3105    return NodePtr(new ConstNode<T>(val));
3106}
3107
3108template <typename T>
3109inline Temp
3110constantVector(T val)
3111{
3112    return NodePtr(new ConstVectorNode<T>(val));
3113}
3114
3115inline Temp
3116sum(Temp val)
3117{
3118    return NodePtr(new SumNode<std::plus<Result> >(val));
3119}
3120
3121/** Dump all statistics data to the registered outputs */
3122void dump();
3123void reset();
3124
3125/**
3126 * Register a callback that should be called whenever statistics are
3127 * reset
3128 */
3129void registerResetCallback(Callback *cb);
3130
3131std::list<Info *> &statsList();
3132
3133} // namespace Stats
3134
3135#endif // __BASE_STATISTICS_HH__
3136