statistics.hh revision 9054:4c0f7e5ae72a
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    /** 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 logarithm of each sample, used to compute geometric mean. */
1481    Counter logs;
1482    /** The sum of squares. */
1483    Counter squares;
1484    /** The number of samples. */
1485    Counter samples;
1486    /** Counter for each bucket. */
1487    VCounter cvec;
1488
1489  public:
1490    HistStor(Info *info)
1491        : cvec(safe_cast<const Params *>(info->storageParams)->buckets)
1492    {
1493        reset(info);
1494    }
1495
1496    void grow_up();
1497    void grow_out();
1498    void grow_convert();
1499
1500    /**
1501     * Add a value to the distribution for the given number of times.
1502     * @param val The value to add.
1503     * @param number The number of times to add the value.
1504     */
1505    void
1506    sample(Counter val, int number)
1507    {
1508        assert(min_bucket < max_bucket);
1509        if (val < min_bucket) {
1510            if (min_bucket == 0)
1511                grow_convert();
1512
1513            while (val < min_bucket)
1514                grow_out();
1515        } else if (val >= max_bucket + bucket_size) {
1516            if (min_bucket == 0) {
1517                while (val >= max_bucket + bucket_size)
1518                    grow_up();
1519            } else {
1520                while (val >= max_bucket + bucket_size)
1521                    grow_out();
1522            }
1523        }
1524
1525        size_type index =
1526            (int64_t)std::floor((val - min_bucket) / bucket_size);
1527
1528        assert(index >= 0 && index < size());
1529        cvec[index] += number;
1530
1531        sum += val * number;
1532        squares += val * val * number;
1533        logs += log(val) * number;
1534        samples += number;
1535    }
1536
1537    /**
1538     * Return the number of buckets in this distribution.
1539     * @return the number of buckets.
1540     */
1541    size_type size() const { return cvec.size(); }
1542
1543    /**
1544     * Returns true if any calls to sample have been made.
1545     * @return True if any values have been sampled.
1546     */
1547    bool
1548    zero() const
1549    {
1550        return samples == Counter();
1551    }
1552
1553    void
1554    prepare(Info *info, DistData &data)
1555    {
1556        const Params *params = safe_cast<const Params *>(info->storageParams);
1557
1558        assert(params->type == Hist);
1559        data.type = params->type;
1560        data.min = min_bucket;
1561        data.max = max_bucket + bucket_size - 1;
1562        data.bucket_size = bucket_size;
1563
1564        data.min_val = min_bucket;
1565        data.max_val = max_bucket;
1566
1567        int buckets = params->buckets;
1568        data.cvec.resize(buckets);
1569        for (off_type i = 0; i < buckets; ++i)
1570            data.cvec[i] = cvec[i];
1571
1572        data.sum = sum;
1573        data.logs = logs;
1574        data.squares = squares;
1575        data.samples = samples;
1576    }
1577
1578    /**
1579     * Reset stat value to default
1580     */
1581    void
1582    reset(Info *info)
1583    {
1584        const Params *params = safe_cast<const Params *>(info->storageParams);
1585        min_bucket = 0;
1586        max_bucket = params->buckets - 1;
1587        bucket_size = 1;
1588
1589        size_type size = cvec.size();
1590        for (off_type i = 0; i < size; ++i)
1591            cvec[i] = Counter();
1592
1593        sum = Counter();
1594        squares = Counter();
1595        samples = Counter();
1596        logs = Counter();
1597    }
1598};
1599
1600/**
1601 * Templatized storage and interface for a distribution that calculates mean
1602 * and variance.
1603 */
1604class SampleStor
1605{
1606  public:
1607    struct Params : public DistParams
1608    {
1609        Params() : DistParams(Deviation) {}
1610    };
1611
1612  private:
1613    /** The current sum. */
1614    Counter sum;
1615    /** The sum of squares. */
1616    Counter squares;
1617    /** The number of samples. */
1618    Counter samples;
1619
1620  public:
1621    /**
1622     * Create and initialize this storage.
1623     */
1624    SampleStor(Info *info)
1625        : sum(Counter()), squares(Counter()), samples(Counter())
1626    { }
1627
1628    /**
1629     * Add a value the given number of times to this running average.
1630     * Update the running sum and sum of squares, increment the number of
1631     * values seen by the given number.
1632     * @param val The value to add.
1633     * @param number The number of times to add the value.
1634     */
1635    void
1636    sample(Counter val, int number)
1637    {
1638        Counter value = val * number;
1639        sum += value;
1640        squares += value * value;
1641        samples += number;
1642    }
1643
1644    /**
1645     * Return the number of entries in this stat, 1
1646     * @return 1.
1647     */
1648    size_type size() const { return 1; }
1649
1650    /**
1651     * Return true if no samples have been added.
1652     * @return True if no samples have been added.
1653     */
1654    bool zero() const { return samples == Counter(); }
1655
1656    void
1657    prepare(Info *info, DistData &data)
1658    {
1659        const Params *params = safe_cast<const Params *>(info->storageParams);
1660
1661        assert(params->type == Deviation);
1662        data.type = params->type;
1663        data.sum = sum;
1664        data.squares = squares;
1665        data.samples = samples;
1666    }
1667
1668    /**
1669     * Reset stat value to default
1670     */
1671    void
1672    reset(Info *info)
1673    {
1674        sum = Counter();
1675        squares = Counter();
1676        samples = Counter();
1677    }
1678};
1679
1680/**
1681 * Templatized storage for distribution that calculates per tick mean and
1682 * variance.
1683 */
1684class AvgSampleStor
1685{
1686  public:
1687    struct Params : public DistParams
1688    {
1689        Params() : DistParams(Deviation) {}
1690    };
1691
1692  private:
1693    /** Current total. */
1694    Counter sum;
1695    /** Current sum of squares. */
1696    Counter squares;
1697
1698  public:
1699    /**
1700     * Create and initialize this storage.
1701     */
1702    AvgSampleStor(Info *info)
1703        : sum(Counter()), squares(Counter())
1704    {}
1705
1706    /**
1707     * Add a value to the distribution for the given number of times.
1708     * Update the running sum and sum of squares.
1709     * @param val The value to add.
1710     * @param number The number of times to add the value.
1711     */
1712    void
1713    sample(Counter val, int number)
1714    {
1715        Counter value = val * number;
1716        sum += value;
1717        squares += value * value;
1718    }
1719
1720    /**
1721     * Return the number of entries, in this case 1.
1722     * @return 1.
1723     */
1724    size_type size() const { return 1; }
1725
1726    /**
1727     * Return true if no samples have been added.
1728     * @return True if the sum is zero.
1729     */
1730    bool zero() const { return sum == Counter(); }
1731
1732    void
1733    prepare(Info *info, DistData &data)
1734    {
1735        const Params *params = safe_cast<const Params *>(info->storageParams);
1736
1737        assert(params->type == Deviation);
1738        data.type = params->type;
1739        data.sum = sum;
1740        data.squares = squares;
1741        data.samples = curTick();
1742    }
1743
1744    /**
1745     * Reset stat value to default
1746     */
1747    void
1748    reset(Info *info)
1749    {
1750        sum = Counter();
1751        squares = Counter();
1752    }
1753};
1754
1755/**
1756 * Implementation of a distribution stat. The type of distribution is
1757 * determined by the Storage template. @sa ScalarBase
1758 */
1759template <class Derived, class Stor>
1760class DistBase : public DataWrap<Derived, DistInfoProxy>
1761{
1762  public:
1763    typedef DistInfoProxy<Derived> Info;
1764    typedef Stor Storage;
1765    typedef typename Stor::Params Params;
1766
1767  protected:
1768    /** The storage for this stat. */
1769    char storage[sizeof(Storage)] __attribute__ ((aligned (8)));
1770
1771  protected:
1772    /**
1773     * Retrieve the storage.
1774     * @return The storage object for this stat.
1775     */
1776    Storage *
1777    data()
1778    {
1779        return reinterpret_cast<Storage *>(storage);
1780    }
1781
1782    /**
1783     * Retrieve a const pointer to the storage.
1784     * @return A const pointer to the storage object for this stat.
1785     */
1786    const Storage *
1787    data() const
1788    {
1789        return reinterpret_cast<const Storage *>(storage);
1790    }
1791
1792    void
1793    doInit()
1794    {
1795        new (storage) Storage(this->info());
1796        this->setInit();
1797    }
1798
1799  public:
1800    DistBase() { }
1801
1802    /**
1803     * Add a value to the distribtion n times. Calls sample on the storage
1804     * class.
1805     * @param v The value to add.
1806     * @param n The number of times to add it, defaults to 1.
1807     */
1808    template <typename U>
1809    void sample(const U &v, int n = 1) { data()->sample(v, n); }
1810
1811    /**
1812     * Return the number of entries in this stat.
1813     * @return The number of entries.
1814     */
1815    size_type size() const { return data()->size(); }
1816    /**
1817     * Return true if no samples have been added.
1818     * @return True if there haven't been any samples.
1819     */
1820    bool zero() const { return data()->zero(); }
1821
1822    void
1823    prepare()
1824    {
1825        Info *info = this->info();
1826        data()->prepare(info, info->data);
1827    }
1828
1829    /**
1830     * Reset stat value to default
1831     */
1832    void
1833    reset()
1834    {
1835        data()->reset(this->info());
1836    }
1837};
1838
1839template <class Stat>
1840class DistProxy;
1841
1842template <class Derived, class Stor>
1843class VectorDistBase : public DataWrapVec<Derived, VectorDistInfoProxy>
1844{
1845  public:
1846    typedef VectorDistInfoProxy<Derived> Info;
1847    typedef Stor Storage;
1848    typedef typename Stor::Params Params;
1849    typedef DistProxy<Derived> Proxy;
1850    friend class DistProxy<Derived>;
1851    friend class DataWrapVec<Derived, VectorDistInfoProxy>;
1852
1853  protected:
1854    Storage *storage;
1855    size_type _size;
1856
1857  protected:
1858    Storage *
1859    data(off_type index)
1860    {
1861        return &storage[index];
1862    }
1863
1864    const Storage *
1865    data(off_type index) const
1866    {
1867        return &storage[index];
1868    }
1869
1870    void
1871    doInit(size_type s)
1872    {
1873        assert(s > 0 && "size must be positive!");
1874        assert(!storage && "already initialized");
1875        _size = s;
1876
1877        char *ptr = new char[_size * sizeof(Storage)];
1878        storage = reinterpret_cast<Storage *>(ptr);
1879
1880        Info *info = this->info();
1881        for (off_type i = 0; i < _size; ++i)
1882            new (&storage[i]) Storage(info);
1883
1884        this->setInit();
1885    }
1886
1887  public:
1888    VectorDistBase()
1889        : storage(NULL)
1890    {}
1891
1892    ~VectorDistBase()
1893    {
1894        if (!storage)
1895            return ;
1896
1897        for (off_type i = 0; i < _size; ++i)
1898            data(i)->~Storage();
1899        delete [] reinterpret_cast<char *>(storage);
1900    }
1901
1902    Proxy operator[](off_type index)
1903    {
1904        assert(index >= 0 && index < size());
1905        return Proxy(this->self(), index);
1906    }
1907
1908    size_type
1909    size() const
1910    {
1911        return _size;
1912    }
1913
1914    bool
1915    zero() const
1916    {
1917        for (off_type i = 0; i < size(); ++i)
1918            if (!data(i)->zero())
1919                return false;
1920        return true;
1921    }
1922
1923    void
1924    prepare()
1925    {
1926        Info *info = this->info();
1927        size_type size = this->size();
1928        info->data.resize(size);
1929        for (off_type i = 0; i < size; ++i)
1930            data(i)->prepare(info, info->data[i]);
1931    }
1932
1933    bool
1934    check() const
1935    {
1936        return storage != NULL;
1937    }
1938};
1939
1940template <class Stat>
1941class DistProxy
1942{
1943  private:
1944    Stat &stat;
1945    off_type index;
1946
1947  protected:
1948    typename Stat::Storage *data() { return stat.data(index); }
1949    const typename Stat::Storage *data() const { return stat.data(index); }
1950
1951  public:
1952    DistProxy(Stat &s, off_type i)
1953        : stat(s), index(i)
1954    {}
1955
1956    DistProxy(const DistProxy &sp)
1957        : stat(sp.stat), index(sp.index)
1958    {}
1959
1960    const DistProxy &
1961    operator=(const DistProxy &sp)
1962    {
1963        stat = sp.stat;
1964        index = sp.index;
1965        return *this;
1966    }
1967
1968  public:
1969    template <typename U>
1970    void
1971    sample(const U &v, int n = 1)
1972    {
1973        data()->sample(v, n);
1974    }
1975
1976    size_type
1977    size() const
1978    {
1979        return 1;
1980    }
1981
1982    bool
1983    zero() const
1984    {
1985        return data()->zero();
1986    }
1987
1988    /**
1989     * Proxy has no state.  Nothing to reset.
1990     */
1991    void reset() { }
1992};
1993
1994//////////////////////////////////////////////////////////////////////
1995//
1996//  Formula Details
1997//
1998//////////////////////////////////////////////////////////////////////
1999
2000/**
2001 * Base class for formula statistic node. These nodes are used to build a tree
2002 * that represents the formula.
2003 */
2004class Node : public RefCounted
2005{
2006  public:
2007    /**
2008     * Return the number of nodes in the subtree starting at this node.
2009     * @return the number of nodes in this subtree.
2010     */
2011    virtual size_type size() const = 0;
2012    /**
2013     * Return the result vector of this subtree.
2014     * @return The result vector of this subtree.
2015     */
2016    virtual const VResult &result() const = 0;
2017    /**
2018     * Return the total of the result vector.
2019     * @return The total of the result vector.
2020     */
2021    virtual Result total() const = 0;
2022
2023    /**
2024     *
2025     */
2026    virtual std::string str() const = 0;
2027};
2028
2029/** Reference counting pointer to a function Node. */
2030typedef RefCountingPtr<Node> NodePtr;
2031
2032class ScalarStatNode : public Node
2033{
2034  private:
2035    const ScalarInfo *data;
2036    mutable VResult vresult;
2037
2038  public:
2039    ScalarStatNode(const ScalarInfo *d) : data(d), vresult(1) {}
2040
2041    const VResult &
2042    result() const
2043    {
2044        vresult[0] = data->result();
2045        return vresult;
2046    }
2047
2048    Result total() const { return data->result(); };
2049
2050    size_type size() const { return 1; }
2051
2052    /**
2053     *
2054     */
2055    std::string str() const { return data->name; }
2056};
2057
2058template <class Stat>
2059class ScalarProxyNode : public Node
2060{
2061  private:
2062    const ScalarProxy<Stat> proxy;
2063    mutable VResult vresult;
2064
2065  public:
2066    ScalarProxyNode(const ScalarProxy<Stat> &p)
2067        : proxy(p), vresult(1)
2068    { }
2069
2070    const VResult &
2071    result() const
2072    {
2073        vresult[0] = proxy.result();
2074        return vresult;
2075    }
2076
2077    Result
2078    total() const
2079    {
2080        return proxy.result();
2081    }
2082
2083    size_type
2084    size() const
2085    {
2086        return 1;
2087    }
2088
2089    /**
2090     *
2091     */
2092    std::string
2093    str() const
2094    {
2095        return proxy.str();
2096    }
2097};
2098
2099class VectorStatNode : public Node
2100{
2101  private:
2102    const VectorInfo *data;
2103
2104  public:
2105    VectorStatNode(const VectorInfo *d) : data(d) { }
2106    const VResult &result() const { return data->result(); }
2107    Result total() const { return data->total(); };
2108
2109    size_type size() const { return data->size(); }
2110
2111    std::string str() const { return data->name; }
2112};
2113
2114template <class T>
2115class ConstNode : public Node
2116{
2117  private:
2118    VResult vresult;
2119
2120  public:
2121    ConstNode(T s) : vresult(1, (Result)s) {}
2122    const VResult &result() const { return vresult; }
2123    Result total() const { return vresult[0]; };
2124    size_type size() const { return 1; }
2125    std::string str() const { return to_string(vresult[0]); }
2126};
2127
2128template <class T>
2129class ConstVectorNode : public Node
2130{
2131  private:
2132    VResult vresult;
2133
2134  public:
2135    ConstVectorNode(const T &s) : vresult(s.begin(), s.end()) {}
2136    const VResult &result() const { return vresult; }
2137
2138    Result
2139    total() const
2140    {
2141        size_type size = this->size();
2142        Result tmp = 0;
2143        for (off_type i = 0; i < size; i++)
2144            tmp += vresult[i];
2145        return tmp;
2146    }
2147
2148    size_type size() const { return vresult.size(); }
2149    std::string
2150    str() const
2151    {
2152        size_type size = this->size();
2153        std::string tmp = "(";
2154        for (off_type i = 0; i < size; i++)
2155            tmp += csprintf("%s ",to_string(vresult[i]));
2156        tmp += ")";
2157        return tmp;
2158    }
2159};
2160
2161template <class Op>
2162struct OpString;
2163
2164template<>
2165struct OpString<std::plus<Result> >
2166{
2167    static std::string str() { return "+"; }
2168};
2169
2170template<>
2171struct OpString<std::minus<Result> >
2172{
2173    static std::string str() { return "-"; }
2174};
2175
2176template<>
2177struct OpString<std::multiplies<Result> >
2178{
2179    static std::string str() { return "*"; }
2180};
2181
2182template<>
2183struct OpString<std::divides<Result> >
2184{
2185    static std::string str() { return "/"; }
2186};
2187
2188template<>
2189struct OpString<std::modulus<Result> >
2190{
2191    static std::string str() { return "%"; }
2192};
2193
2194template<>
2195struct OpString<std::negate<Result> >
2196{
2197    static std::string str() { return "-"; }
2198};
2199
2200template <class Op>
2201class UnaryNode : public Node
2202{
2203  public:
2204    NodePtr l;
2205    mutable VResult vresult;
2206
2207  public:
2208    UnaryNode(NodePtr &p) : l(p) {}
2209
2210    const VResult &
2211    result() const
2212    {
2213        const VResult &lvec = l->result();
2214        size_type size = lvec.size();
2215
2216        assert(size > 0);
2217
2218        vresult.resize(size);
2219        Op op;
2220        for (off_type i = 0; i < size; ++i)
2221            vresult[i] = op(lvec[i]);
2222
2223        return vresult;
2224    }
2225
2226    Result
2227    total() const
2228    {
2229        const VResult &vec = this->result();
2230        Result total = 0.0;
2231        for (off_type i = 0; i < size(); i++)
2232            total += vec[i];
2233        return total;
2234    }
2235
2236    size_type size() const { return l->size(); }
2237
2238    std::string
2239    str() const
2240    {
2241        return OpString<Op>::str() + l->str();
2242    }
2243};
2244
2245template <class Op>
2246class BinaryNode : public Node
2247{
2248  public:
2249    NodePtr l;
2250    NodePtr r;
2251    mutable VResult vresult;
2252
2253  public:
2254    BinaryNode(NodePtr &a, NodePtr &b) : l(a), r(b) {}
2255
2256    const VResult &
2257    result() const
2258    {
2259        Op op;
2260        const VResult &lvec = l->result();
2261        const VResult &rvec = r->result();
2262
2263        assert(lvec.size() > 0 && rvec.size() > 0);
2264
2265        if (lvec.size() == 1 && rvec.size() == 1) {
2266            vresult.resize(1);
2267            vresult[0] = op(lvec[0], rvec[0]);
2268        } else if (lvec.size() == 1) {
2269            size_type size = rvec.size();
2270            vresult.resize(size);
2271            for (off_type i = 0; i < size; ++i)
2272                vresult[i] = op(lvec[0], rvec[i]);
2273        } else if (rvec.size() == 1) {
2274            size_type size = lvec.size();
2275            vresult.resize(size);
2276            for (off_type i = 0; i < size; ++i)
2277                vresult[i] = op(lvec[i], rvec[0]);
2278        } else if (rvec.size() == lvec.size()) {
2279            size_type size = rvec.size();
2280            vresult.resize(size);
2281            for (off_type i = 0; i < size; ++i)
2282                vresult[i] = op(lvec[i], rvec[i]);
2283        }
2284
2285        return vresult;
2286    }
2287
2288    Result
2289    total() const
2290    {
2291        const VResult &vec = this->result();
2292        const VResult &lvec = l->result();
2293        const VResult &rvec = r->result();
2294        Result total = 0.0;
2295        Result lsum = 0.0;
2296        Result rsum = 0.0;
2297        Op op;
2298
2299        assert(lvec.size() > 0 && rvec.size() > 0);
2300        assert(lvec.size() == rvec.size() ||
2301               lvec.size() == 1 || rvec.size() == 1);
2302
2303        /** If vectors are the same divide their sums (x0+x1)/(y0+y1) */
2304        if (lvec.size() == rvec.size() && lvec.size() > 1) {
2305            for (off_type i = 0; i < size(); ++i) {
2306                lsum += lvec[i];
2307                rsum += rvec[i];
2308            }
2309            return op(lsum, rsum);
2310        }
2311
2312        /** Otherwise divide each item by the divisor */
2313        for (off_type i = 0; i < size(); ++i) {
2314            total += vec[i];
2315        }
2316
2317        return total;
2318    }
2319
2320    size_type
2321    size() const
2322    {
2323        size_type ls = l->size();
2324        size_type rs = r->size();
2325        if (ls == 1) {
2326            return rs;
2327        } else if (rs == 1) {
2328            return ls;
2329        } else {
2330            assert(ls == rs && "Node vector sizes are not equal");
2331            return ls;
2332        }
2333    }
2334
2335    std::string
2336    str() const
2337    {
2338        return csprintf("(%s %s %s)", l->str(), OpString<Op>::str(), r->str());
2339    }
2340};
2341
2342template <class Op>
2343class SumNode : public Node
2344{
2345  public:
2346    NodePtr l;
2347    mutable VResult vresult;
2348
2349  public:
2350    SumNode(NodePtr &p) : l(p), vresult(1) {}
2351
2352    const VResult &
2353    result() const
2354    {
2355        const VResult &lvec = l->result();
2356        size_type size = lvec.size();
2357        assert(size > 0);
2358
2359        vresult[0] = 0.0;
2360
2361        Op op;
2362        for (off_type i = 0; i < size; ++i)
2363            vresult[0] = op(vresult[0], lvec[i]);
2364
2365        return vresult;
2366    }
2367
2368    Result
2369    total() const
2370    {
2371        const VResult &lvec = l->result();
2372        size_type size = lvec.size();
2373        assert(size > 0);
2374
2375        Result vresult = 0.0;
2376
2377        Op op;
2378        for (off_type i = 0; i < size; ++i)
2379            vresult = op(vresult, lvec[i]);
2380
2381        return vresult;
2382    }
2383
2384    size_type size() const { return 1; }
2385
2386    std::string
2387    str() const
2388    {
2389        return csprintf("total(%s)", l->str());
2390    }
2391};
2392
2393
2394//////////////////////////////////////////////////////////////////////
2395//
2396// Visible Statistics Types
2397//
2398//////////////////////////////////////////////////////////////////////
2399/**
2400 * @defgroup VisibleStats "Statistic Types"
2401 * These are the statistics that are used in the simulator.
2402 * @{
2403 */
2404
2405/**
2406 * This is a simple scalar statistic, like a counter.
2407 * @sa Stat, ScalarBase, StatStor
2408 */
2409class Scalar : public ScalarBase<Scalar, StatStor>
2410{
2411  public:
2412    using ScalarBase<Scalar, StatStor>::operator=;
2413};
2414
2415/**
2416 * A stat that calculates the per tick average of a value.
2417 * @sa Stat, ScalarBase, AvgStor
2418 */
2419class Average : public ScalarBase<Average, AvgStor>
2420{
2421  public:
2422    using ScalarBase<Average, AvgStor>::operator=;
2423};
2424
2425class Value : public ValueBase<Value>
2426{
2427};
2428
2429/**
2430 * A vector of scalar stats.
2431 * @sa Stat, VectorBase, StatStor
2432 */
2433class Vector : public VectorBase<Vector, StatStor>
2434{
2435};
2436
2437/**
2438 * A vector of Average stats.
2439 * @sa Stat, VectorBase, AvgStor
2440 */
2441class AverageVector : public VectorBase<AverageVector, AvgStor>
2442{
2443};
2444
2445/**
2446 * A 2-Dimensional vecto of scalar stats.
2447 * @sa Stat, Vector2dBase, StatStor
2448 */
2449class Vector2d : public Vector2dBase<Vector2d, StatStor>
2450{
2451};
2452
2453/**
2454 * A simple distribution stat.
2455 * @sa Stat, DistBase, DistStor
2456 */
2457class Distribution : public DistBase<Distribution, DistStor>
2458{
2459  public:
2460    /**
2461     * Set the parameters of this distribution. @sa DistStor::Params
2462     * @param min The minimum value of the distribution.
2463     * @param max The maximum value of the distribution.
2464     * @param bkt The number of values in each bucket.
2465     * @return A reference to this distribution.
2466     */
2467    Distribution &
2468    init(Counter min, Counter max, Counter bkt)
2469    {
2470        DistStor::Params *params = new DistStor::Params;
2471        params->min = min;
2472        params->max = max;
2473        params->bucket_size = bkt;
2474        params->buckets = (size_type)ceil((max - min + 1.0) / bkt);
2475        this->setParams(params);
2476        this->doInit();
2477        return this->self();
2478    }
2479};
2480
2481/**
2482 * A simple histogram stat.
2483 * @sa Stat, DistBase, HistStor
2484 */
2485class Histogram : public DistBase<Histogram, HistStor>
2486{
2487  public:
2488    /**
2489     * Set the parameters of this histogram. @sa HistStor::Params
2490     * @param size The number of buckets in the histogram
2491     * @return A reference to this histogram.
2492     */
2493    Histogram &
2494    init(size_type size)
2495    {
2496        HistStor::Params *params = new HistStor::Params;
2497        params->buckets = size;
2498        this->setParams(params);
2499        this->doInit();
2500        return this->self();
2501    }
2502};
2503
2504/**
2505 * Calculates the mean and variance of all the samples.
2506 * @sa DistBase, SampleStor
2507 */
2508class StandardDeviation : public DistBase<StandardDeviation, SampleStor>
2509{
2510  public:
2511    /**
2512     * Construct and initialize this distribution.
2513     */
2514    StandardDeviation()
2515    {
2516        SampleStor::Params *params = new SampleStor::Params;
2517        this->doInit();
2518        this->setParams(params);
2519    }
2520};
2521
2522/**
2523 * Calculates the per tick mean and variance of the samples.
2524 * @sa DistBase, AvgSampleStor
2525 */
2526class AverageDeviation : public DistBase<AverageDeviation, AvgSampleStor>
2527{
2528  public:
2529    /**
2530     * Construct and initialize this distribution.
2531     */
2532    AverageDeviation()
2533    {
2534        AvgSampleStor::Params *params = new AvgSampleStor::Params;
2535        this->doInit();
2536        this->setParams(params);
2537    }
2538};
2539
2540/**
2541 * A vector of distributions.
2542 * @sa VectorDistBase, DistStor
2543 */
2544class VectorDistribution : public VectorDistBase<VectorDistribution, DistStor>
2545{
2546  public:
2547    /**
2548     * Initialize storage and parameters for this distribution.
2549     * @param size The size of the vector (the number of distributions).
2550     * @param min The minimum value of the distribution.
2551     * @param max The maximum value of the distribution.
2552     * @param bkt The number of values in each bucket.
2553     * @return A reference to this distribution.
2554     */
2555    VectorDistribution &
2556    init(size_type size, Counter min, Counter max, Counter bkt)
2557    {
2558        DistStor::Params *params = new DistStor::Params;
2559        params->min = min;
2560        params->max = max;
2561        params->bucket_size = bkt;
2562        params->buckets = (size_type)ceil((max - min + 1.0) / bkt);
2563        this->setParams(params);
2564        this->doInit(size);
2565        return this->self();
2566    }
2567};
2568
2569/**
2570 * This is a vector of StandardDeviation stats.
2571 * @sa VectorDistBase, SampleStor
2572 */
2573class VectorStandardDeviation
2574    : public VectorDistBase<VectorStandardDeviation, SampleStor>
2575{
2576  public:
2577    /**
2578     * Initialize storage for this distribution.
2579     * @param size The size of the vector.
2580     * @return A reference to this distribution.
2581     */
2582    VectorStandardDeviation &
2583    init(size_type size)
2584    {
2585        SampleStor::Params *params = new SampleStor::Params;
2586        this->doInit(size);
2587        this->setParams(params);
2588        return this->self();
2589    }
2590};
2591
2592/**
2593 * This is a vector of AverageDeviation stats.
2594 * @sa VectorDistBase, AvgSampleStor
2595 */
2596class VectorAverageDeviation
2597    : public VectorDistBase<VectorAverageDeviation, AvgSampleStor>
2598{
2599  public:
2600    /**
2601     * Initialize storage for this distribution.
2602     * @param size The size of the vector.
2603     * @return A reference to this distribution.
2604     */
2605    VectorAverageDeviation &
2606    init(size_type size)
2607    {
2608        AvgSampleStor::Params *params = new AvgSampleStor::Params;
2609        this->doInit(size);
2610        this->setParams(params);
2611        return this->self();
2612    }
2613};
2614
2615template <class Stat>
2616class FormulaInfoProxy : public InfoProxy<Stat, FormulaInfo>
2617{
2618  protected:
2619    mutable VResult vec;
2620    mutable VCounter cvec;
2621
2622  public:
2623    FormulaInfoProxy(Stat &stat) : InfoProxy<Stat, FormulaInfo>(stat) {}
2624
2625    size_type size() const { return this->s.size(); }
2626
2627    const VResult &
2628    result() const
2629    {
2630        this->s.result(vec);
2631        return vec;
2632    }
2633    Result total() const { return this->s.total(); }
2634    VCounter &value() const { return cvec; }
2635
2636    std::string str() const { return this->s.str(); }
2637};
2638
2639template <class Stat>
2640class SparseHistInfoProxy : public InfoProxy<Stat, SparseHistInfo>
2641{
2642  public:
2643    SparseHistInfoProxy(Stat &stat) : InfoProxy<Stat, SparseHistInfo>(stat) {}
2644};
2645
2646/**
2647 * Implementation of a sparse histogram stat. The storage class is
2648 * determined by the Storage template.
2649 */
2650template <class Derived, class Stor>
2651class SparseHistBase : public DataWrap<Derived, SparseHistInfoProxy>
2652{
2653  public:
2654    typedef SparseHistInfoProxy<Derived> Info;
2655    typedef Stor Storage;
2656    typedef typename Stor::Params Params;
2657
2658  protected:
2659    /** The storage for this stat. */
2660    char storage[sizeof(Storage)];
2661
2662  protected:
2663    /**
2664     * Retrieve the storage.
2665     * @return The storage object for this stat.
2666     */
2667    Storage *
2668    data()
2669    {
2670        return reinterpret_cast<Storage *>(storage);
2671    }
2672
2673    /**
2674     * Retrieve a const pointer to the storage.
2675     * @return A const pointer to the storage object for this stat.
2676     */
2677    const Storage *
2678    data() const
2679    {
2680        return reinterpret_cast<const Storage *>(storage);
2681    }
2682
2683    void
2684    doInit()
2685    {
2686        new (storage) Storage(this->info());
2687        this->setInit();
2688    }
2689
2690  public:
2691    SparseHistBase() { }
2692
2693    /**
2694     * Add a value to the distribtion n times. Calls sample on the storage
2695     * class.
2696     * @param v The value to add.
2697     * @param n The number of times to add it, defaults to 1.
2698     */
2699    template <typename U>
2700    void sample(const U &v, int n = 1) { data()->sample(v, n); }
2701
2702    /**
2703     * Return the number of entries in this stat.
2704     * @return The number of entries.
2705     */
2706    size_type size() const { return data()->size(); }
2707    /**
2708     * Return true if no samples have been added.
2709     * @return True if there haven't been any samples.
2710     */
2711    bool zero() const { return data()->zero(); }
2712
2713    void
2714    prepare()
2715    {
2716        Info *info = this->info();
2717        data()->prepare(info, info->data);
2718    }
2719
2720    /**
2721     * Reset stat value to default
2722     */
2723    void
2724    reset()
2725    {
2726        data()->reset(this->info());
2727    }
2728};
2729
2730/**
2731 * Templatized storage and interface for a sparse histogram stat.
2732 */
2733class SparseHistStor
2734{
2735  public:
2736    /** The parameters for a sparse histogram stat. */
2737    struct Params : public DistParams
2738    {
2739        Params() : DistParams(Hist) {}
2740    };
2741
2742  private:
2743    /** Counter for number of samples */
2744    Counter samples;
2745    /** Counter for each bucket. */
2746    MCounter cmap;
2747
2748  public:
2749    SparseHistStor(Info *info)
2750    {
2751        reset(info);
2752    }
2753
2754    /**
2755     * Add a value to the distribution for the given number of times.
2756     * @param val The value to add.
2757     * @param number The number of times to add the value.
2758     */
2759    void
2760    sample(Counter val, int number)
2761    {
2762        cmap[val] += number;
2763        samples += number;
2764    }
2765
2766    /**
2767     * Return the number of buckets in this distribution.
2768     * @return the number of buckets.
2769     */
2770    size_type size() const { return cmap.size(); }
2771
2772    /**
2773     * Returns true if any calls to sample have been made.
2774     * @return True if any values have been sampled.
2775     */
2776    bool
2777    zero() const
2778    {
2779        return samples == Counter();
2780    }
2781
2782    void
2783    prepare(Info *info, SparseHistData &data)
2784    {
2785        MCounter::iterator it;
2786        data.cmap.clear();
2787        for (it = cmap.begin(); it != cmap.end(); it++) {
2788            data.cmap[(*it).first] = (*it).second;
2789        }
2790
2791        data.samples = samples;
2792    }
2793
2794    /**
2795     * Reset stat value to default
2796     */
2797    void
2798    reset(Info *info)
2799    {
2800        cmap.clear();
2801        samples = 0;
2802    }
2803};
2804
2805class SparseHistogram : public SparseHistBase<SparseHistogram, SparseHistStor>
2806{
2807  public:
2808    /**
2809     * Set the parameters of this histogram. @sa HistStor::Params
2810     * @param size The number of buckets in the histogram
2811     * @return A reference to this histogram.
2812     */
2813    SparseHistogram &
2814    init(size_type size)
2815    {
2816        SparseHistStor::Params *params = new SparseHistStor::Params;
2817        this->setParams(params);
2818        this->doInit();
2819        return this->self();
2820    }
2821};
2822
2823class Temp;
2824/**
2825 * A formula for statistics that is calculated when printed. A formula is
2826 * stored as a tree of Nodes that represent the equation to calculate.
2827 * @sa Stat, ScalarStat, VectorStat, Node, Temp
2828 */
2829class Formula : public DataWrapVec<Formula, FormulaInfoProxy>
2830{
2831  protected:
2832    /** The root of the tree which represents the Formula */
2833    NodePtr root;
2834    friend class Temp;
2835
2836  public:
2837    /**
2838     * Create and initialize thie formula, and register it with the database.
2839     */
2840    Formula();
2841
2842    /**
2843     * Create a formula with the given root node, register it with the
2844     * database.
2845     * @param r The root of the expression tree.
2846     */
2847    Formula(Temp r);
2848
2849    /**
2850     * Set an unitialized Formula to the given root.
2851     * @param r The root of the expression tree.
2852     * @return a reference to this formula.
2853     */
2854    const Formula &operator=(Temp r);
2855
2856    /**
2857     * Add the given tree to the existing one.
2858     * @param r The root of the expression tree.
2859     * @return a reference to this formula.
2860     */
2861    const Formula &operator+=(Temp r);
2862    /**
2863     * Return the result of the Fomula in a vector.  If there were no Vector
2864     * components to the Formula, then the vector is size 1.  If there were,
2865     * like x/y with x being a vector of size 3, then the result returned will
2866     * be x[0]/y, x[1]/y, x[2]/y, respectively.
2867     * @return The result vector.
2868     */
2869    void result(VResult &vec) const;
2870
2871    /**
2872     * Return the total Formula result.  If there is a Vector
2873     * component to this Formula, then this is the result of the
2874     * Formula if the formula is applied after summing all the
2875     * components of the Vector.  For example, if Formula is x/y where
2876     * x is size 3, then total() will return (x[1]+x[2]+x[3])/y.  If
2877     * there is no Vector component, total() returns the same value as
2878     * the first entry in the VResult val() returns.
2879     * @return The total of the result vector.
2880     */
2881    Result total() const;
2882
2883    /**
2884     * Return the number of elements in the tree.
2885     */
2886    size_type size() const;
2887
2888    void prepare() { }
2889
2890    /**
2891     * Formulas don't need to be reset
2892     */
2893    void reset();
2894
2895    /**
2896     *
2897     */
2898    bool zero() const;
2899
2900    std::string str() const;
2901};
2902
2903class FormulaNode : public Node
2904{
2905  private:
2906    const Formula &formula;
2907    mutable VResult vec;
2908
2909  public:
2910    FormulaNode(const Formula &f) : formula(f) {}
2911
2912    size_type size() const { return formula.size(); }
2913    const VResult &result() const { formula.result(vec); return vec; }
2914    Result total() const { return formula.total(); }
2915
2916    std::string str() const { return formula.str(); }
2917};
2918
2919/**
2920 * Helper class to construct formula node trees.
2921 */
2922class Temp
2923{
2924  protected:
2925    /**
2926     * Pointer to a Node object.
2927     */
2928    NodePtr node;
2929
2930  public:
2931    /**
2932     * Copy the given pointer to this class.
2933     * @param n A pointer to a Node object to copy.
2934     */
2935    Temp(NodePtr n) : node(n) { }
2936
2937    /**
2938     * Return the node pointer.
2939     * @return the node pointer.
2940     */
2941    operator NodePtr&() { return node; }
2942
2943  public:
2944    /**
2945     * Create a new ScalarStatNode.
2946     * @param s The ScalarStat to place in a node.
2947     */
2948    Temp(const Scalar &s)
2949        : node(new ScalarStatNode(s.info()))
2950    { }
2951
2952    /**
2953     * Create a new ScalarStatNode.
2954     * @param s The ScalarStat to place in a node.
2955     */
2956    Temp(const Value &s)
2957        : node(new ScalarStatNode(s.info()))
2958    { }
2959
2960    /**
2961     * Create a new ScalarStatNode.
2962     * @param s The ScalarStat to place in a node.
2963     */
2964    Temp(const Average &s)
2965        : node(new ScalarStatNode(s.info()))
2966    { }
2967
2968    /**
2969     * Create a new VectorStatNode.
2970     * @param s The VectorStat to place in a node.
2971     */
2972    Temp(const Vector &s)
2973        : node(new VectorStatNode(s.info()))
2974    { }
2975
2976    Temp(const AverageVector &s)
2977        : node(new VectorStatNode(s.info()))
2978    { }
2979
2980    /**
2981     *
2982     */
2983    Temp(const Formula &f)
2984        : node(new FormulaNode(f))
2985    { }
2986
2987    /**
2988     * Create a new ScalarProxyNode.
2989     * @param p The ScalarProxy to place in a node.
2990     */
2991    template <class Stat>
2992    Temp(const ScalarProxy<Stat> &p)
2993        : node(new ScalarProxyNode<Stat>(p))
2994    { }
2995
2996    /**
2997     * Create a ConstNode
2998     * @param value The value of the const node.
2999     */
3000    Temp(signed char value)
3001        : node(new ConstNode<signed char>(value))
3002    { }
3003
3004    /**
3005     * Create a ConstNode
3006     * @param value The value of the const node.
3007     */
3008    Temp(unsigned char value)
3009        : node(new ConstNode<unsigned char>(value))
3010    { }
3011
3012    /**
3013     * Create a ConstNode
3014     * @param value The value of the const node.
3015     */
3016    Temp(signed short value)
3017        : node(new ConstNode<signed short>(value))
3018    { }
3019
3020    /**
3021     * Create a ConstNode
3022     * @param value The value of the const node.
3023     */
3024    Temp(unsigned short value)
3025        : node(new ConstNode<unsigned short>(value))
3026    { }
3027
3028    /**
3029     * Create a ConstNode
3030     * @param value The value of the const node.
3031     */
3032    Temp(signed int value)
3033        : node(new ConstNode<signed int>(value))
3034    { }
3035
3036    /**
3037     * Create a ConstNode
3038     * @param value The value of the const node.
3039     */
3040    Temp(unsigned int value)
3041        : node(new ConstNode<unsigned int>(value))
3042    { }
3043
3044    /**
3045     * Create a ConstNode
3046     * @param value The value of the const node.
3047     */
3048    Temp(signed long value)
3049        : node(new ConstNode<signed long>(value))
3050    { }
3051
3052    /**
3053     * Create a ConstNode
3054     * @param value The value of the const node.
3055     */
3056    Temp(unsigned long value)
3057        : node(new ConstNode<unsigned long>(value))
3058    { }
3059
3060    /**
3061     * Create a ConstNode
3062     * @param value The value of the const node.
3063     */
3064    Temp(signed long long value)
3065        : node(new ConstNode<signed long long>(value))
3066    { }
3067
3068    /**
3069     * Create a ConstNode
3070     * @param value The value of the const node.
3071     */
3072    Temp(unsigned long long value)
3073        : node(new ConstNode<unsigned long long>(value))
3074    { }
3075
3076    /**
3077     * Create a ConstNode
3078     * @param value The value of the const node.
3079     */
3080    Temp(float value)
3081        : node(new ConstNode<float>(value))
3082    { }
3083
3084    /**
3085     * Create a ConstNode
3086     * @param value The value of the const node.
3087     */
3088    Temp(double value)
3089        : node(new ConstNode<double>(value))
3090    { }
3091};
3092
3093
3094/**
3095 * @}
3096 */
3097
3098inline Temp
3099operator+(Temp l, Temp r)
3100{
3101    return NodePtr(new BinaryNode<std::plus<Result> >(l, r));
3102}
3103
3104inline Temp
3105operator-(Temp l, Temp r)
3106{
3107    return NodePtr(new BinaryNode<std::minus<Result> >(l, r));
3108}
3109
3110inline Temp
3111operator*(Temp l, Temp r)
3112{
3113    return NodePtr(new BinaryNode<std::multiplies<Result> >(l, r));
3114}
3115
3116inline Temp
3117operator/(Temp l, Temp r)
3118{
3119    return NodePtr(new BinaryNode<std::divides<Result> >(l, r));
3120}
3121
3122inline Temp
3123operator-(Temp l)
3124{
3125    return NodePtr(new UnaryNode<std::negate<Result> >(l));
3126}
3127
3128template <typename T>
3129inline Temp
3130constant(T val)
3131{
3132    return NodePtr(new ConstNode<T>(val));
3133}
3134
3135template <typename T>
3136inline Temp
3137constantVector(T val)
3138{
3139    return NodePtr(new ConstVectorNode<T>(val));
3140}
3141
3142inline Temp
3143sum(Temp val)
3144{
3145    return NodePtr(new SumNode<std::plus<Result> >(val));
3146}
3147
3148/** Dump all statistics data to the registered outputs */
3149void dump();
3150void reset();
3151void enable();
3152bool enabled();
3153
3154/**
3155 * Register a callback that should be called whenever statistics are
3156 * reset
3157 */
3158void registerResetCallback(Callback *cb);
3159
3160/**
3161 * Register a callback that should be called whenever statistics are
3162 * about to be dumped
3163 */
3164void registerDumpCallback(Callback *cb);
3165
3166std::list<Info *> &statsList();
3167
3168} // namespace Stats
3169
3170#endif // __BASE_STATISTICS_HH__
3171