statistics.hh revision 9557:8666e81607a6
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 + y <= 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
1331    /** The smallest value sampled. */
1332    Counter min_val;
1333    /** The largest value sampled. */
1334    Counter max_val;
1335    /** The number of values sampled less than min. */
1336    Counter underflow;
1337    /** The number of values sampled more than max. */
1338    Counter overflow;
1339    /** The current sum. */
1340    Counter sum;
1341    /** The sum of squares. */
1342    Counter squares;
1343    /** The number of samples. */
1344    Counter samples;
1345    /** Counter for each bucket. */
1346    VCounter cvec;
1347
1348  public:
1349    DistStor(Info *info)
1350        : cvec(safe_cast<const Params *>(info->storageParams)->buckets)
1351    {
1352        reset(info);
1353    }
1354
1355    /**
1356     * Add a value to the distribution for the given number of times.
1357     * @param val The value to add.
1358     * @param number The number of times to add the value.
1359     */
1360    void
1361    sample(Counter val, int number)
1362    {
1363        if (val < min_track)
1364            underflow += number;
1365        else if (val > max_track)
1366            overflow += number;
1367        else {
1368            size_type index =
1369                (size_type)std::floor((val - min_track) / bucket_size);
1370            assert(index < size());
1371            cvec[index] += number;
1372        }
1373
1374        if (val < min_val)
1375            min_val = val;
1376
1377        if (val > max_val)
1378            max_val = val;
1379
1380        sum += val * number;
1381        squares += val * val * number;
1382        samples += number;
1383    }
1384
1385    /**
1386     * Return the number of buckets in this distribution.
1387     * @return the number of buckets.
1388     */
1389    size_type size() const { return cvec.size(); }
1390
1391    /**
1392     * Returns true if any calls to sample have been made.
1393     * @return True if any values have been sampled.
1394     */
1395    bool
1396    zero() const
1397    {
1398        return samples == Counter();
1399    }
1400
1401    void
1402    prepare(Info *info, DistData &data)
1403    {
1404        const Params *params = safe_cast<const Params *>(info->storageParams);
1405
1406        assert(params->type == Dist);
1407        data.type = params->type;
1408        data.min = params->min;
1409        data.max = params->max;
1410        data.bucket_size = params->bucket_size;
1411
1412        data.min_val = (min_val == CounterLimits::max()) ? 0 : min_val;
1413        data.max_val = (max_val == CounterLimits::min()) ? 0 : max_val;
1414        data.underflow = underflow;
1415        data.overflow = overflow;
1416
1417        data.cvec.resize(params->buckets);
1418        for (off_type i = 0; i < params->buckets; ++i)
1419            data.cvec[i] = cvec[i];
1420
1421        data.sum = sum;
1422        data.squares = squares;
1423        data.samples = samples;
1424    }
1425
1426    /**
1427     * Reset stat value to default
1428     */
1429    void
1430    reset(Info *info)
1431    {
1432        const Params *params = safe_cast<const Params *>(info->storageParams);
1433        min_track = params->min;
1434        max_track = params->max;
1435        bucket_size = params->bucket_size;
1436
1437        min_val = CounterLimits::max();
1438        max_val = CounterLimits::min();
1439        underflow = Counter();
1440        overflow = Counter();
1441
1442        size_type size = cvec.size();
1443        for (off_type i = 0; i < size; ++i)
1444            cvec[i] = Counter();
1445
1446        sum = Counter();
1447        squares = Counter();
1448        samples = Counter();
1449    }
1450};
1451
1452/**
1453 * Templatized storage and interface for a histogram stat.
1454 */
1455class HistStor
1456{
1457  public:
1458    /** The parameters for a distribution stat. */
1459    struct Params : public DistParams
1460    {
1461        /** The number of buckets.. */
1462        size_type buckets;
1463
1464        Params() : DistParams(Hist) {}
1465    };
1466
1467  private:
1468    /** The minimum value to track. */
1469    Counter min_bucket;
1470    /** The maximum value to track. */
1471    Counter max_bucket;
1472    /** The number of entries in each bucket. */
1473    Counter bucket_size;
1474
1475    /** The current sum. */
1476    Counter sum;
1477    /** The sum of logarithm of each sample, used to compute geometric mean. */
1478    Counter logs;
1479    /** The sum of squares. */
1480    Counter squares;
1481    /** The number of samples. */
1482    Counter samples;
1483    /** Counter for each bucket. */
1484    VCounter cvec;
1485
1486  public:
1487    HistStor(Info *info)
1488        : cvec(safe_cast<const Params *>(info->storageParams)->buckets)
1489    {
1490        reset(info);
1491    }
1492
1493    void grow_up();
1494    void grow_out();
1495    void grow_convert();
1496
1497    /**
1498     * Add a value to the distribution for the given number of times.
1499     * @param val The value to add.
1500     * @param number The number of times to add the value.
1501     */
1502    void
1503    sample(Counter val, int number)
1504    {
1505        assert(min_bucket < max_bucket);
1506        if (val < min_bucket) {
1507            if (min_bucket == 0)
1508                grow_convert();
1509
1510            while (val < min_bucket)
1511                grow_out();
1512        } else if (val >= max_bucket + bucket_size) {
1513            if (min_bucket == 0) {
1514                while (val >= max_bucket + bucket_size)
1515                    grow_up();
1516            } else {
1517                while (val >= max_bucket + bucket_size)
1518                    grow_out();
1519            }
1520        }
1521
1522        size_type index =
1523            (int64_t)std::floor((val - min_bucket) / bucket_size);
1524
1525        assert(index >= 0 && index < size());
1526        cvec[index] += number;
1527
1528        sum += val * number;
1529        squares += val * val * number;
1530        logs += log(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.logs = logs;
1571        data.squares = squares;
1572        data.samples = samples;
1573    }
1574
1575    /**
1576     * Reset stat value to default
1577     */
1578    void
1579    reset(Info *info)
1580    {
1581        const Params *params = safe_cast<const Params *>(info->storageParams);
1582        min_bucket = 0;
1583        max_bucket = params->buckets - 1;
1584        bucket_size = 1;
1585
1586        size_type size = cvec.size();
1587        for (off_type i = 0; i < size; ++i)
1588            cvec[i] = Counter();
1589
1590        sum = Counter();
1591        squares = Counter();
1592        samples = Counter();
1593        logs = Counter();
1594    }
1595};
1596
1597/**
1598 * Templatized storage and interface for a distribution that calculates mean
1599 * and variance.
1600 */
1601class SampleStor
1602{
1603  public:
1604    struct Params : public DistParams
1605    {
1606        Params() : DistParams(Deviation) {}
1607    };
1608
1609  private:
1610    /** The current sum. */
1611    Counter sum;
1612    /** The sum of squares. */
1613    Counter squares;
1614    /** The number of samples. */
1615    Counter samples;
1616
1617  public:
1618    /**
1619     * Create and initialize this storage.
1620     */
1621    SampleStor(Info *info)
1622        : sum(Counter()), squares(Counter()), samples(Counter())
1623    { }
1624
1625    /**
1626     * Add a value the given number of times to this running average.
1627     * Update the running sum and sum of squares, increment the number of
1628     * values seen by the given number.
1629     * @param val The value to add.
1630     * @param number The number of times to add the value.
1631     */
1632    void
1633    sample(Counter val, int number)
1634    {
1635        Counter value = val * number;
1636        sum += value;
1637        squares += value * value;
1638        samples += number;
1639    }
1640
1641    /**
1642     * Return the number of entries in this stat, 1
1643     * @return 1.
1644     */
1645    size_type size() const { return 1; }
1646
1647    /**
1648     * Return true if no samples have been added.
1649     * @return True if no samples have been added.
1650     */
1651    bool zero() const { return samples == Counter(); }
1652
1653    void
1654    prepare(Info *info, DistData &data)
1655    {
1656        const Params *params = safe_cast<const Params *>(info->storageParams);
1657
1658        assert(params->type == Deviation);
1659        data.type = params->type;
1660        data.sum = sum;
1661        data.squares = squares;
1662        data.samples = samples;
1663    }
1664
1665    /**
1666     * Reset stat value to default
1667     */
1668    void
1669    reset(Info *info)
1670    {
1671        sum = Counter();
1672        squares = Counter();
1673        samples = Counter();
1674    }
1675};
1676
1677/**
1678 * Templatized storage for distribution that calculates per tick mean and
1679 * variance.
1680 */
1681class AvgSampleStor
1682{
1683  public:
1684    struct Params : public DistParams
1685    {
1686        Params() : DistParams(Deviation) {}
1687    };
1688
1689  private:
1690    /** Current total. */
1691    Counter sum;
1692    /** Current sum of squares. */
1693    Counter squares;
1694
1695  public:
1696    /**
1697     * Create and initialize this storage.
1698     */
1699    AvgSampleStor(Info *info)
1700        : sum(Counter()), squares(Counter())
1701    {}
1702
1703    /**
1704     * Add a value to the distribution for the given number of times.
1705     * Update the running sum and sum of squares.
1706     * @param val The value to add.
1707     * @param number The number of times to add the value.
1708     */
1709    void
1710    sample(Counter val, int number)
1711    {
1712        Counter value = val * number;
1713        sum += value;
1714        squares += value * value;
1715    }
1716
1717    /**
1718     * Return the number of entries, in this case 1.
1719     * @return 1.
1720     */
1721    size_type size() const { return 1; }
1722
1723    /**
1724     * Return true if no samples have been added.
1725     * @return True if the sum is zero.
1726     */
1727    bool zero() const { return sum == Counter(); }
1728
1729    void
1730    prepare(Info *info, DistData &data)
1731    {
1732        const Params *params = safe_cast<const Params *>(info->storageParams);
1733
1734        assert(params->type == Deviation);
1735        data.type = params->type;
1736        data.sum = sum;
1737        data.squares = squares;
1738        data.samples = curTick();
1739    }
1740
1741    /**
1742     * Reset stat value to default
1743     */
1744    void
1745    reset(Info *info)
1746    {
1747        sum = Counter();
1748        squares = Counter();
1749    }
1750};
1751
1752/**
1753 * Implementation of a distribution stat. The type of distribution is
1754 * determined by the Storage template. @sa ScalarBase
1755 */
1756template <class Derived, class Stor>
1757class DistBase : public DataWrap<Derived, DistInfoProxy>
1758{
1759  public:
1760    typedef DistInfoProxy<Derived> Info;
1761    typedef Stor Storage;
1762    typedef typename Stor::Params Params;
1763
1764  protected:
1765    /** The storage for this stat. */
1766    char storage[sizeof(Storage)] __attribute__ ((aligned (8)));
1767
1768  protected:
1769    /**
1770     * Retrieve the storage.
1771     * @return The storage object for this stat.
1772     */
1773    Storage *
1774    data()
1775    {
1776        return reinterpret_cast<Storage *>(storage);
1777    }
1778
1779    /**
1780     * Retrieve a const pointer to the storage.
1781     * @return A const pointer to the storage object for this stat.
1782     */
1783    const Storage *
1784    data() const
1785    {
1786        return reinterpret_cast<const Storage *>(storage);
1787    }
1788
1789    void
1790    doInit()
1791    {
1792        new (storage) Storage(this->info());
1793        this->setInit();
1794    }
1795
1796  public:
1797    DistBase() { }
1798
1799    /**
1800     * Add a value to the distribtion n times. Calls sample on the storage
1801     * class.
1802     * @param v The value to add.
1803     * @param n The number of times to add it, defaults to 1.
1804     */
1805    template <typename U>
1806    void sample(const U &v, int n = 1) { data()->sample(v, n); }
1807
1808    /**
1809     * Return the number of entries in this stat.
1810     * @return The number of entries.
1811     */
1812    size_type size() const { return data()->size(); }
1813    /**
1814     * Return true if no samples have been added.
1815     * @return True if there haven't been any samples.
1816     */
1817    bool zero() const { return data()->zero(); }
1818
1819    void
1820    prepare()
1821    {
1822        Info *info = this->info();
1823        data()->prepare(info, info->data);
1824    }
1825
1826    /**
1827     * Reset stat value to default
1828     */
1829    void
1830    reset()
1831    {
1832        data()->reset(this->info());
1833    }
1834};
1835
1836template <class Stat>
1837class DistProxy;
1838
1839template <class Derived, class Stor>
1840class VectorDistBase : public DataWrapVec<Derived, VectorDistInfoProxy>
1841{
1842  public:
1843    typedef VectorDistInfoProxy<Derived> Info;
1844    typedef Stor Storage;
1845    typedef typename Stor::Params Params;
1846    typedef DistProxy<Derived> Proxy;
1847    friend class DistProxy<Derived>;
1848    friend class DataWrapVec<Derived, VectorDistInfoProxy>;
1849
1850  protected:
1851    Storage *storage;
1852    size_type _size;
1853
1854  protected:
1855    Storage *
1856    data(off_type index)
1857    {
1858        return &storage[index];
1859    }
1860
1861    const Storage *
1862    data(off_type index) const
1863    {
1864        return &storage[index];
1865    }
1866
1867    void
1868    doInit(size_type s)
1869    {
1870        assert(s > 0 && "size must be positive!");
1871        assert(!storage && "already initialized");
1872        _size = s;
1873
1874        char *ptr = new char[_size * sizeof(Storage)];
1875        storage = reinterpret_cast<Storage *>(ptr);
1876
1877        Info *info = this->info();
1878        for (off_type i = 0; i < _size; ++i)
1879            new (&storage[i]) Storage(info);
1880
1881        this->setInit();
1882    }
1883
1884  public:
1885    VectorDistBase()
1886        : storage(NULL)
1887    {}
1888
1889    ~VectorDistBase()
1890    {
1891        if (!storage)
1892            return ;
1893
1894        for (off_type i = 0; i < _size; ++i)
1895            data(i)->~Storage();
1896        delete [] reinterpret_cast<char *>(storage);
1897    }
1898
1899    Proxy operator[](off_type index)
1900    {
1901        assert(index >= 0 && index < size());
1902        return Proxy(this->self(), index);
1903    }
1904
1905    size_type
1906    size() const
1907    {
1908        return _size;
1909    }
1910
1911    bool
1912    zero() const
1913    {
1914        for (off_type i = 0; i < size(); ++i)
1915            if (!data(i)->zero())
1916                return false;
1917        return true;
1918    }
1919
1920    void
1921    prepare()
1922    {
1923        Info *info = this->info();
1924        size_type size = this->size();
1925        info->data.resize(size);
1926        for (off_type i = 0; i < size; ++i)
1927            data(i)->prepare(info, info->data[i]);
1928    }
1929
1930    bool
1931    check() const
1932    {
1933        return storage != NULL;
1934    }
1935};
1936
1937template <class Stat>
1938class DistProxy
1939{
1940  private:
1941    Stat &stat;
1942    off_type index;
1943
1944  protected:
1945    typename Stat::Storage *data() { return stat.data(index); }
1946    const typename Stat::Storage *data() const { return stat.data(index); }
1947
1948  public:
1949    DistProxy(Stat &s, off_type i)
1950        : stat(s), index(i)
1951    {}
1952
1953    DistProxy(const DistProxy &sp)
1954        : stat(sp.stat), index(sp.index)
1955    {}
1956
1957    const DistProxy &
1958    operator=(const DistProxy &sp)
1959    {
1960        stat = sp.stat;
1961        index = sp.index;
1962        return *this;
1963    }
1964
1965  public:
1966    template <typename U>
1967    void
1968    sample(const U &v, int n = 1)
1969    {
1970        data()->sample(v, n);
1971    }
1972
1973    size_type
1974    size() const
1975    {
1976        return 1;
1977    }
1978
1979    bool
1980    zero() const
1981    {
1982        return data()->zero();
1983    }
1984
1985    /**
1986     * Proxy has no state.  Nothing to reset.
1987     */
1988    void reset() { }
1989};
1990
1991//////////////////////////////////////////////////////////////////////
1992//
1993//  Formula Details
1994//
1995//////////////////////////////////////////////////////////////////////
1996
1997/**
1998 * Base class for formula statistic node. These nodes are used to build a tree
1999 * that represents the formula.
2000 */
2001class Node : public RefCounted
2002{
2003  public:
2004    /**
2005     * Return the number of nodes in the subtree starting at this node.
2006     * @return the number of nodes in this subtree.
2007     */
2008    virtual size_type size() const = 0;
2009    /**
2010     * Return the result vector of this subtree.
2011     * @return The result vector of this subtree.
2012     */
2013    virtual const VResult &result() const = 0;
2014    /**
2015     * Return the total of the result vector.
2016     * @return The total of the result vector.
2017     */
2018    virtual Result total() const = 0;
2019
2020    /**
2021     *
2022     */
2023    virtual std::string str() const = 0;
2024};
2025
2026/** Reference counting pointer to a function Node. */
2027typedef RefCountingPtr<Node> NodePtr;
2028
2029class ScalarStatNode : public Node
2030{
2031  private:
2032    const ScalarInfo *data;
2033    mutable VResult vresult;
2034
2035  public:
2036    ScalarStatNode(const ScalarInfo *d) : data(d), vresult(1) {}
2037
2038    const VResult &
2039    result() const
2040    {
2041        vresult[0] = data->result();
2042        return vresult;
2043    }
2044
2045    Result total() const { return data->result(); };
2046
2047    size_type size() const { return 1; }
2048
2049    /**
2050     *
2051     */
2052    std::string str() const { return data->name; }
2053};
2054
2055template <class Stat>
2056class ScalarProxyNode : public Node
2057{
2058  private:
2059    const ScalarProxy<Stat> proxy;
2060    mutable VResult vresult;
2061
2062  public:
2063    ScalarProxyNode(const ScalarProxy<Stat> &p)
2064        : proxy(p), vresult(1)
2065    { }
2066
2067    const VResult &
2068    result() const
2069    {
2070        vresult[0] = proxy.result();
2071        return vresult;
2072    }
2073
2074    Result
2075    total() const
2076    {
2077        return proxy.result();
2078    }
2079
2080    size_type
2081    size() const
2082    {
2083        return 1;
2084    }
2085
2086    /**
2087     *
2088     */
2089    std::string
2090    str() const
2091    {
2092        return proxy.str();
2093    }
2094};
2095
2096class VectorStatNode : public Node
2097{
2098  private:
2099    const VectorInfo *data;
2100
2101  public:
2102    VectorStatNode(const VectorInfo *d) : data(d) { }
2103    const VResult &result() const { return data->result(); }
2104    Result total() const { return data->total(); };
2105
2106    size_type size() const { return data->size(); }
2107
2108    std::string str() const { return data->name; }
2109};
2110
2111template <class T>
2112class ConstNode : public Node
2113{
2114  private:
2115    VResult vresult;
2116
2117  public:
2118    ConstNode(T s) : vresult(1, (Result)s) {}
2119    const VResult &result() const { return vresult; }
2120    Result total() const { return vresult[0]; };
2121    size_type size() const { return 1; }
2122    std::string str() const { return to_string(vresult[0]); }
2123};
2124
2125template <class T>
2126class ConstVectorNode : public Node
2127{
2128  private:
2129    VResult vresult;
2130
2131  public:
2132    ConstVectorNode(const T &s) : vresult(s.begin(), s.end()) {}
2133    const VResult &result() const { return vresult; }
2134
2135    Result
2136    total() const
2137    {
2138        size_type size = this->size();
2139        Result tmp = 0;
2140        for (off_type i = 0; i < size; i++)
2141            tmp += vresult[i];
2142        return tmp;
2143    }
2144
2145    size_type size() const { return vresult.size(); }
2146    std::string
2147    str() const
2148    {
2149        size_type size = this->size();
2150        std::string tmp = "(";
2151        for (off_type i = 0; i < size; i++)
2152            tmp += csprintf("%s ",to_string(vresult[i]));
2153        tmp += ")";
2154        return tmp;
2155    }
2156};
2157
2158template <class Op>
2159struct OpString;
2160
2161template<>
2162struct OpString<std::plus<Result> >
2163{
2164    static std::string str() { return "+"; }
2165};
2166
2167template<>
2168struct OpString<std::minus<Result> >
2169{
2170    static std::string str() { return "-"; }
2171};
2172
2173template<>
2174struct OpString<std::multiplies<Result> >
2175{
2176    static std::string str() { return "*"; }
2177};
2178
2179template<>
2180struct OpString<std::divides<Result> >
2181{
2182    static std::string str() { return "/"; }
2183};
2184
2185template<>
2186struct OpString<std::modulus<Result> >
2187{
2188    static std::string str() { return "%"; }
2189};
2190
2191template<>
2192struct OpString<std::negate<Result> >
2193{
2194    static std::string str() { return "-"; }
2195};
2196
2197template <class Op>
2198class UnaryNode : public Node
2199{
2200  public:
2201    NodePtr l;
2202    mutable VResult vresult;
2203
2204  public:
2205    UnaryNode(NodePtr &p) : l(p) {}
2206
2207    const VResult &
2208    result() const
2209    {
2210        const VResult &lvec = l->result();
2211        size_type size = lvec.size();
2212
2213        assert(size > 0);
2214
2215        vresult.resize(size);
2216        Op op;
2217        for (off_type i = 0; i < size; ++i)
2218            vresult[i] = op(lvec[i]);
2219
2220        return vresult;
2221    }
2222
2223    Result
2224    total() const
2225    {
2226        const VResult &vec = this->result();
2227        Result total = 0.0;
2228        for (off_type i = 0; i < size(); i++)
2229            total += vec[i];
2230        return total;
2231    }
2232
2233    size_type size() const { return l->size(); }
2234
2235    std::string
2236    str() const
2237    {
2238        return OpString<Op>::str() + l->str();
2239    }
2240};
2241
2242template <class Op>
2243class BinaryNode : public Node
2244{
2245  public:
2246    NodePtr l;
2247    NodePtr r;
2248    mutable VResult vresult;
2249
2250  public:
2251    BinaryNode(NodePtr &a, NodePtr &b) : l(a), r(b) {}
2252
2253    const VResult &
2254    result() const
2255    {
2256        Op op;
2257        const VResult &lvec = l->result();
2258        const VResult &rvec = r->result();
2259
2260        assert(lvec.size() > 0 && rvec.size() > 0);
2261
2262        if (lvec.size() == 1 && rvec.size() == 1) {
2263            vresult.resize(1);
2264            vresult[0] = op(lvec[0], rvec[0]);
2265        } else if (lvec.size() == 1) {
2266            size_type size = rvec.size();
2267            vresult.resize(size);
2268            for (off_type i = 0; i < size; ++i)
2269                vresult[i] = op(lvec[0], rvec[i]);
2270        } else if (rvec.size() == 1) {
2271            size_type size = lvec.size();
2272            vresult.resize(size);
2273            for (off_type i = 0; i < size; ++i)
2274                vresult[i] = op(lvec[i], rvec[0]);
2275        } else if (rvec.size() == lvec.size()) {
2276            size_type size = rvec.size();
2277            vresult.resize(size);
2278            for (off_type i = 0; i < size; ++i)
2279                vresult[i] = op(lvec[i], rvec[i]);
2280        }
2281
2282        return vresult;
2283    }
2284
2285    Result
2286    total() const
2287    {
2288        const VResult &vec = this->result();
2289        const VResult &lvec = l->result();
2290        const VResult &rvec = r->result();
2291        Result total = 0.0;
2292        Result lsum = 0.0;
2293        Result rsum = 0.0;
2294        Op op;
2295
2296        assert(lvec.size() > 0 && rvec.size() > 0);
2297        assert(lvec.size() == rvec.size() ||
2298               lvec.size() == 1 || rvec.size() == 1);
2299
2300        /** If vectors are the same divide their sums (x0+x1)/(y0+y1) */
2301        if (lvec.size() == rvec.size() && lvec.size() > 1) {
2302            for (off_type i = 0; i < size(); ++i) {
2303                lsum += lvec[i];
2304                rsum += rvec[i];
2305            }
2306            return op(lsum, rsum);
2307        }
2308
2309        /** Otherwise divide each item by the divisor */
2310        for (off_type i = 0; i < size(); ++i) {
2311            total += vec[i];
2312        }
2313
2314        return total;
2315    }
2316
2317    size_type
2318    size() const
2319    {
2320        size_type ls = l->size();
2321        size_type rs = r->size();
2322        if (ls == 1) {
2323            return rs;
2324        } else if (rs == 1) {
2325            return ls;
2326        } else {
2327            assert(ls == rs && "Node vector sizes are not equal");
2328            return ls;
2329        }
2330    }
2331
2332    std::string
2333    str() const
2334    {
2335        return csprintf("(%s %s %s)", l->str(), OpString<Op>::str(), r->str());
2336    }
2337};
2338
2339template <class Op>
2340class SumNode : public Node
2341{
2342  public:
2343    NodePtr l;
2344    mutable VResult vresult;
2345
2346  public:
2347    SumNode(NodePtr &p) : l(p), vresult(1) {}
2348
2349    const VResult &
2350    result() const
2351    {
2352        const VResult &lvec = l->result();
2353        size_type size = lvec.size();
2354        assert(size > 0);
2355
2356        vresult[0] = 0.0;
2357
2358        Op op;
2359        for (off_type i = 0; i < size; ++i)
2360            vresult[0] = op(vresult[0], lvec[i]);
2361
2362        return vresult;
2363    }
2364
2365    Result
2366    total() const
2367    {
2368        const VResult &lvec = l->result();
2369        size_type size = lvec.size();
2370        assert(size > 0);
2371
2372        Result result = 0.0;
2373
2374        Op op;
2375        for (off_type i = 0; i < size; ++i)
2376            result = op(result, lvec[i]);
2377
2378        return result;
2379    }
2380
2381    size_type size() const { return 1; }
2382
2383    std::string
2384    str() const
2385    {
2386        return csprintf("total(%s)", l->str());
2387    }
2388};
2389
2390
2391//////////////////////////////////////////////////////////////////////
2392//
2393// Visible Statistics Types
2394//
2395//////////////////////////////////////////////////////////////////////
2396/**
2397 * @defgroup VisibleStats "Statistic Types"
2398 * These are the statistics that are used in the simulator.
2399 * @{
2400 */
2401
2402/**
2403 * This is a simple scalar statistic, like a counter.
2404 * @sa Stat, ScalarBase, StatStor
2405 */
2406class Scalar : public ScalarBase<Scalar, StatStor>
2407{
2408  public:
2409    using ScalarBase<Scalar, StatStor>::operator=;
2410};
2411
2412/**
2413 * A stat that calculates the per tick average of a value.
2414 * @sa Stat, ScalarBase, AvgStor
2415 */
2416class Average : public ScalarBase<Average, AvgStor>
2417{
2418  public:
2419    using ScalarBase<Average, AvgStor>::operator=;
2420};
2421
2422class Value : public ValueBase<Value>
2423{
2424};
2425
2426/**
2427 * A vector of scalar stats.
2428 * @sa Stat, VectorBase, StatStor
2429 */
2430class Vector : public VectorBase<Vector, StatStor>
2431{
2432};
2433
2434/**
2435 * A vector of Average stats.
2436 * @sa Stat, VectorBase, AvgStor
2437 */
2438class AverageVector : public VectorBase<AverageVector, AvgStor>
2439{
2440};
2441
2442/**
2443 * A 2-Dimensional vecto of scalar stats.
2444 * @sa Stat, Vector2dBase, StatStor
2445 */
2446class Vector2d : public Vector2dBase<Vector2d, StatStor>
2447{
2448};
2449
2450/**
2451 * A simple distribution stat.
2452 * @sa Stat, DistBase, DistStor
2453 */
2454class Distribution : public DistBase<Distribution, DistStor>
2455{
2456  public:
2457    /**
2458     * Set the parameters of this distribution. @sa DistStor::Params
2459     * @param min The minimum value of the distribution.
2460     * @param max The maximum value of the distribution.
2461     * @param bkt The number of values in each bucket.
2462     * @return A reference to this distribution.
2463     */
2464    Distribution &
2465    init(Counter min, Counter max, Counter bkt)
2466    {
2467        DistStor::Params *params = new DistStor::Params;
2468        params->min = min;
2469        params->max = max;
2470        params->bucket_size = bkt;
2471        params->buckets = (size_type)ceil((max - min + 1.0) / bkt);
2472        this->setParams(params);
2473        this->doInit();
2474        return this->self();
2475    }
2476};
2477
2478/**
2479 * A simple histogram stat.
2480 * @sa Stat, DistBase, HistStor
2481 */
2482class Histogram : public DistBase<Histogram, HistStor>
2483{
2484  public:
2485    /**
2486     * Set the parameters of this histogram. @sa HistStor::Params
2487     * @param size The number of buckets in the histogram
2488     * @return A reference to this histogram.
2489     */
2490    Histogram &
2491    init(size_type size)
2492    {
2493        HistStor::Params *params = new HistStor::Params;
2494        params->buckets = size;
2495        this->setParams(params);
2496        this->doInit();
2497        return this->self();
2498    }
2499};
2500
2501/**
2502 * Calculates the mean and variance of all the samples.
2503 * @sa DistBase, SampleStor
2504 */
2505class StandardDeviation : public DistBase<StandardDeviation, SampleStor>
2506{
2507  public:
2508    /**
2509     * Construct and initialize this distribution.
2510     */
2511    StandardDeviation()
2512    {
2513        SampleStor::Params *params = new SampleStor::Params;
2514        this->doInit();
2515        this->setParams(params);
2516    }
2517};
2518
2519/**
2520 * Calculates the per tick mean and variance of the samples.
2521 * @sa DistBase, AvgSampleStor
2522 */
2523class AverageDeviation : public DistBase<AverageDeviation, AvgSampleStor>
2524{
2525  public:
2526    /**
2527     * Construct and initialize this distribution.
2528     */
2529    AverageDeviation()
2530    {
2531        AvgSampleStor::Params *params = new AvgSampleStor::Params;
2532        this->doInit();
2533        this->setParams(params);
2534    }
2535};
2536
2537/**
2538 * A vector of distributions.
2539 * @sa VectorDistBase, DistStor
2540 */
2541class VectorDistribution : public VectorDistBase<VectorDistribution, DistStor>
2542{
2543  public:
2544    /**
2545     * Initialize storage and parameters for this distribution.
2546     * @param size The size of the vector (the number of distributions).
2547     * @param min The minimum value of the distribution.
2548     * @param max The maximum value of the distribution.
2549     * @param bkt The number of values in each bucket.
2550     * @return A reference to this distribution.
2551     */
2552    VectorDistribution &
2553    init(size_type size, Counter min, Counter max, Counter bkt)
2554    {
2555        DistStor::Params *params = new DistStor::Params;
2556        params->min = min;
2557        params->max = max;
2558        params->bucket_size = bkt;
2559        params->buckets = (size_type)ceil((max - min + 1.0) / bkt);
2560        this->setParams(params);
2561        this->doInit(size);
2562        return this->self();
2563    }
2564};
2565
2566/**
2567 * This is a vector of StandardDeviation stats.
2568 * @sa VectorDistBase, SampleStor
2569 */
2570class VectorStandardDeviation
2571    : public VectorDistBase<VectorStandardDeviation, SampleStor>
2572{
2573  public:
2574    /**
2575     * Initialize storage for this distribution.
2576     * @param size The size of the vector.
2577     * @return A reference to this distribution.
2578     */
2579    VectorStandardDeviation &
2580    init(size_type size)
2581    {
2582        SampleStor::Params *params = new SampleStor::Params;
2583        this->doInit(size);
2584        this->setParams(params);
2585        return this->self();
2586    }
2587};
2588
2589/**
2590 * This is a vector of AverageDeviation stats.
2591 * @sa VectorDistBase, AvgSampleStor
2592 */
2593class VectorAverageDeviation
2594    : public VectorDistBase<VectorAverageDeviation, AvgSampleStor>
2595{
2596  public:
2597    /**
2598     * Initialize storage for this distribution.
2599     * @param size The size of the vector.
2600     * @return A reference to this distribution.
2601     */
2602    VectorAverageDeviation &
2603    init(size_type size)
2604    {
2605        AvgSampleStor::Params *params = new AvgSampleStor::Params;
2606        this->doInit(size);
2607        this->setParams(params);
2608        return this->self();
2609    }
2610};
2611
2612template <class Stat>
2613class FormulaInfoProxy : public InfoProxy<Stat, FormulaInfo>
2614{
2615  protected:
2616    mutable VResult vec;
2617    mutable VCounter cvec;
2618
2619  public:
2620    FormulaInfoProxy(Stat &stat) : InfoProxy<Stat, FormulaInfo>(stat) {}
2621
2622    size_type size() const { return this->s.size(); }
2623
2624    const VResult &
2625    result() const
2626    {
2627        this->s.result(vec);
2628        return vec;
2629    }
2630    Result total() const { return this->s.total(); }
2631    VCounter &value() const { return cvec; }
2632
2633    std::string str() const { return this->s.str(); }
2634};
2635
2636template <class Stat>
2637class SparseHistInfoProxy : public InfoProxy<Stat, SparseHistInfo>
2638{
2639  public:
2640    SparseHistInfoProxy(Stat &stat) : InfoProxy<Stat, SparseHistInfo>(stat) {}
2641};
2642
2643/**
2644 * Implementation of a sparse histogram stat. The storage class is
2645 * determined by the Storage template.
2646 */
2647template <class Derived, class Stor>
2648class SparseHistBase : public DataWrap<Derived, SparseHistInfoProxy>
2649{
2650  public:
2651    typedef SparseHistInfoProxy<Derived> Info;
2652    typedef Stor Storage;
2653    typedef typename Stor::Params Params;
2654
2655  protected:
2656    /** The storage for this stat. */
2657    char storage[sizeof(Storage)];
2658
2659  protected:
2660    /**
2661     * Retrieve the storage.
2662     * @return The storage object for this stat.
2663     */
2664    Storage *
2665    data()
2666    {
2667        return reinterpret_cast<Storage *>(storage);
2668    }
2669
2670    /**
2671     * Retrieve a const pointer to the storage.
2672     * @return A const pointer to the storage object for this stat.
2673     */
2674    const Storage *
2675    data() const
2676    {
2677        return reinterpret_cast<const Storage *>(storage);
2678    }
2679
2680    void
2681    doInit()
2682    {
2683        new (storage) Storage(this->info());
2684        this->setInit();
2685    }
2686
2687  public:
2688    SparseHistBase() { }
2689
2690    /**
2691     * Add a value to the distribtion n times. Calls sample on the storage
2692     * class.
2693     * @param v The value to add.
2694     * @param n The number of times to add it, defaults to 1.
2695     */
2696    template <typename U>
2697    void sample(const U &v, int n = 1) { data()->sample(v, n); }
2698
2699    /**
2700     * Return the number of entries in this stat.
2701     * @return The number of entries.
2702     */
2703    size_type size() const { return data()->size(); }
2704    /**
2705     * Return true if no samples have been added.
2706     * @return True if there haven't been any samples.
2707     */
2708    bool zero() const { return data()->zero(); }
2709
2710    void
2711    prepare()
2712    {
2713        Info *info = this->info();
2714        data()->prepare(info, info->data);
2715    }
2716
2717    /**
2718     * Reset stat value to default
2719     */
2720    void
2721    reset()
2722    {
2723        data()->reset(this->info());
2724    }
2725};
2726
2727/**
2728 * Templatized storage and interface for a sparse histogram stat.
2729 */
2730class SparseHistStor
2731{
2732  public:
2733    /** The parameters for a sparse histogram stat. */
2734    struct Params : public DistParams
2735    {
2736        Params() : DistParams(Hist) {}
2737    };
2738
2739  private:
2740    /** Counter for number of samples */
2741    Counter samples;
2742    /** Counter for each bucket. */
2743    MCounter cmap;
2744
2745  public:
2746    SparseHistStor(Info *info)
2747    {
2748        reset(info);
2749    }
2750
2751    /**
2752     * Add a value to the distribution for the given number of times.
2753     * @param val The value to add.
2754     * @param number The number of times to add the value.
2755     */
2756    void
2757    sample(Counter val, int number)
2758    {
2759        cmap[val] += number;
2760        samples += number;
2761    }
2762
2763    /**
2764     * Return the number of buckets in this distribution.
2765     * @return the number of buckets.
2766     */
2767    size_type size() const { return cmap.size(); }
2768
2769    /**
2770     * Returns true if any calls to sample have been made.
2771     * @return True if any values have been sampled.
2772     */
2773    bool
2774    zero() const
2775    {
2776        return samples == Counter();
2777    }
2778
2779    void
2780    prepare(Info *info, SparseHistData &data)
2781    {
2782        MCounter::iterator it;
2783        data.cmap.clear();
2784        for (it = cmap.begin(); it != cmap.end(); it++) {
2785            data.cmap[(*it).first] = (*it).second;
2786        }
2787
2788        data.samples = samples;
2789    }
2790
2791    /**
2792     * Reset stat value to default
2793     */
2794    void
2795    reset(Info *info)
2796    {
2797        cmap.clear();
2798        samples = 0;
2799    }
2800};
2801
2802class SparseHistogram : public SparseHistBase<SparseHistogram, SparseHistStor>
2803{
2804  public:
2805    /**
2806     * Set the parameters of this histogram. @sa HistStor::Params
2807     * @param size The number of buckets in the histogram
2808     * @return A reference to this histogram.
2809     */
2810    SparseHistogram &
2811    init(size_type size)
2812    {
2813        SparseHistStor::Params *params = new SparseHistStor::Params;
2814        this->setParams(params);
2815        this->doInit();
2816        return this->self();
2817    }
2818};
2819
2820class Temp;
2821/**
2822 * A formula for statistics that is calculated when printed. A formula is
2823 * stored as a tree of Nodes that represent the equation to calculate.
2824 * @sa Stat, ScalarStat, VectorStat, Node, Temp
2825 */
2826class Formula : public DataWrapVec<Formula, FormulaInfoProxy>
2827{
2828  protected:
2829    /** The root of the tree which represents the Formula */
2830    NodePtr root;
2831    friend class Temp;
2832
2833  public:
2834    /**
2835     * Create and initialize thie formula, and register it with the database.
2836     */
2837    Formula();
2838
2839    /**
2840     * Create a formula with the given root node, register it with the
2841     * database.
2842     * @param r The root of the expression tree.
2843     */
2844    Formula(Temp r);
2845
2846    /**
2847     * Set an unitialized Formula to the given root.
2848     * @param r The root of the expression tree.
2849     * @return a reference to this formula.
2850     */
2851    const Formula &operator=(Temp r);
2852
2853    /**
2854     * Add the given tree to the existing one.
2855     * @param r The root of the expression tree.
2856     * @return a reference to this formula.
2857     */
2858    const Formula &operator+=(Temp r);
2859    /**
2860     * Return the result of the Fomula in a vector.  If there were no Vector
2861     * components to the Formula, then the vector is size 1.  If there were,
2862     * like x/y with x being a vector of size 3, then the result returned will
2863     * be x[0]/y, x[1]/y, x[2]/y, respectively.
2864     * @return The result vector.
2865     */
2866    void result(VResult &vec) const;
2867
2868    /**
2869     * Return the total Formula result.  If there is a Vector
2870     * component to this Formula, then this is the result of the
2871     * Formula if the formula is applied after summing all the
2872     * components of the Vector.  For example, if Formula is x/y where
2873     * x is size 3, then total() will return (x[1]+x[2]+x[3])/y.  If
2874     * there is no Vector component, total() returns the same value as
2875     * the first entry in the VResult val() returns.
2876     * @return The total of the result vector.
2877     */
2878    Result total() const;
2879
2880    /**
2881     * Return the number of elements in the tree.
2882     */
2883    size_type size() const;
2884
2885    void prepare() { }
2886
2887    /**
2888     * Formulas don't need to be reset
2889     */
2890    void reset();
2891
2892    /**
2893     *
2894     */
2895    bool zero() const;
2896
2897    std::string str() const;
2898};
2899
2900class FormulaNode : public Node
2901{
2902  private:
2903    const Formula &formula;
2904    mutable VResult vec;
2905
2906  public:
2907    FormulaNode(const Formula &f) : formula(f) {}
2908
2909    size_type size() const { return formula.size(); }
2910    const VResult &result() const { formula.result(vec); return vec; }
2911    Result total() const { return formula.total(); }
2912
2913    std::string str() const { return formula.str(); }
2914};
2915
2916/**
2917 * Helper class to construct formula node trees.
2918 */
2919class Temp
2920{
2921  protected:
2922    /**
2923     * Pointer to a Node object.
2924     */
2925    NodePtr node;
2926
2927  public:
2928    /**
2929     * Copy the given pointer to this class.
2930     * @param n A pointer to a Node object to copy.
2931     */
2932    Temp(NodePtr n) : node(n) { }
2933
2934    /**
2935     * Return the node pointer.
2936     * @return the node pointer.
2937     */
2938    operator NodePtr&() { return node; }
2939
2940  public:
2941    /**
2942     * Create a new ScalarStatNode.
2943     * @param s The ScalarStat to place in a node.
2944     */
2945    Temp(const Scalar &s)
2946        : node(new ScalarStatNode(s.info()))
2947    { }
2948
2949    /**
2950     * Create a new ScalarStatNode.
2951     * @param s The ScalarStat to place in a node.
2952     */
2953    Temp(const Value &s)
2954        : node(new ScalarStatNode(s.info()))
2955    { }
2956
2957    /**
2958     * Create a new ScalarStatNode.
2959     * @param s The ScalarStat to place in a node.
2960     */
2961    Temp(const Average &s)
2962        : node(new ScalarStatNode(s.info()))
2963    { }
2964
2965    /**
2966     * Create a new VectorStatNode.
2967     * @param s The VectorStat to place in a node.
2968     */
2969    Temp(const Vector &s)
2970        : node(new VectorStatNode(s.info()))
2971    { }
2972
2973    Temp(const AverageVector &s)
2974        : node(new VectorStatNode(s.info()))
2975    { }
2976
2977    /**
2978     *
2979     */
2980    Temp(const Formula &f)
2981        : node(new FormulaNode(f))
2982    { }
2983
2984    /**
2985     * Create a new ScalarProxyNode.
2986     * @param p The ScalarProxy to place in a node.
2987     */
2988    template <class Stat>
2989    Temp(const ScalarProxy<Stat> &p)
2990        : node(new ScalarProxyNode<Stat>(p))
2991    { }
2992
2993    /**
2994     * Create a ConstNode
2995     * @param value The value of the const node.
2996     */
2997    Temp(signed char value)
2998        : node(new ConstNode<signed char>(value))
2999    { }
3000
3001    /**
3002     * Create a ConstNode
3003     * @param value The value of the const node.
3004     */
3005    Temp(unsigned char value)
3006        : node(new ConstNode<unsigned char>(value))
3007    { }
3008
3009    /**
3010     * Create a ConstNode
3011     * @param value The value of the const node.
3012     */
3013    Temp(signed short value)
3014        : node(new ConstNode<signed short>(value))
3015    { }
3016
3017    /**
3018     * Create a ConstNode
3019     * @param value The value of the const node.
3020     */
3021    Temp(unsigned short value)
3022        : node(new ConstNode<unsigned short>(value))
3023    { }
3024
3025    /**
3026     * Create a ConstNode
3027     * @param value The value of the const node.
3028     */
3029    Temp(signed int value)
3030        : node(new ConstNode<signed int>(value))
3031    { }
3032
3033    /**
3034     * Create a ConstNode
3035     * @param value The value of the const node.
3036     */
3037    Temp(unsigned int value)
3038        : node(new ConstNode<unsigned int>(value))
3039    { }
3040
3041    /**
3042     * Create a ConstNode
3043     * @param value The value of the const node.
3044     */
3045    Temp(signed long value)
3046        : node(new ConstNode<signed long>(value))
3047    { }
3048
3049    /**
3050     * Create a ConstNode
3051     * @param value The value of the const node.
3052     */
3053    Temp(unsigned long value)
3054        : node(new ConstNode<unsigned long>(value))
3055    { }
3056
3057    /**
3058     * Create a ConstNode
3059     * @param value The value of the const node.
3060     */
3061    Temp(signed long long value)
3062        : node(new ConstNode<signed long long>(value))
3063    { }
3064
3065    /**
3066     * Create a ConstNode
3067     * @param value The value of the const node.
3068     */
3069    Temp(unsigned long long value)
3070        : node(new ConstNode<unsigned long long>(value))
3071    { }
3072
3073    /**
3074     * Create a ConstNode
3075     * @param value The value of the const node.
3076     */
3077    Temp(float value)
3078        : node(new ConstNode<float>(value))
3079    { }
3080
3081    /**
3082     * Create a ConstNode
3083     * @param value The value of the const node.
3084     */
3085    Temp(double value)
3086        : node(new ConstNode<double>(value))
3087    { }
3088};
3089
3090
3091/**
3092 * @}
3093 */
3094
3095inline Temp
3096operator+(Temp l, Temp r)
3097{
3098    return NodePtr(new BinaryNode<std::plus<Result> >(l, r));
3099}
3100
3101inline Temp
3102operator-(Temp l, Temp r)
3103{
3104    return NodePtr(new BinaryNode<std::minus<Result> >(l, r));
3105}
3106
3107inline Temp
3108operator*(Temp l, Temp r)
3109{
3110    return NodePtr(new BinaryNode<std::multiplies<Result> >(l, r));
3111}
3112
3113inline Temp
3114operator/(Temp l, Temp r)
3115{
3116    return NodePtr(new BinaryNode<std::divides<Result> >(l, r));
3117}
3118
3119inline Temp
3120operator-(Temp l)
3121{
3122    return NodePtr(new UnaryNode<std::negate<Result> >(l));
3123}
3124
3125template <typename T>
3126inline Temp
3127constant(T val)
3128{
3129    return NodePtr(new ConstNode<T>(val));
3130}
3131
3132template <typename T>
3133inline Temp
3134constantVector(T val)
3135{
3136    return NodePtr(new ConstVectorNode<T>(val));
3137}
3138
3139inline Temp
3140sum(Temp val)
3141{
3142    return NodePtr(new SumNode<std::plus<Result> >(val));
3143}
3144
3145/** Dump all statistics data to the registered outputs */
3146void dump();
3147void reset();
3148void enable();
3149bool enabled();
3150
3151/**
3152 * Register a callback that should be called whenever statistics are
3153 * reset
3154 */
3155void registerResetCallback(Callback *cb);
3156
3157/**
3158 * Register a callback that should be called whenever statistics are
3159 * about to be dumped
3160 */
3161void registerDumpCallback(Callback *cb);
3162
3163std::list<Info *> &statsList();
3164
3165typedef std::map<const void *, Info *> MapType;
3166MapType &statsMap();
3167
3168typedef std::map<std::string, Info *> NameMapType;
3169NameMapType &nameMap();
3170
3171bool validateStatName(const std::string &name);
3172
3173} // namespace Stats
3174
3175void debugDumpStats();
3176
3177#endif // __BASE_STATISTICS_HH__
3178