statistics.hh revision 9554:406fbcf60223
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        data.cvec.resize(params->buckets);
1420        for (off_type i = 0; i < params->buckets; ++i)
1421            data.cvec[i] = cvec[i];
1422
1423        data.sum = sum;
1424        data.squares = squares;
1425        data.samples = samples;
1426    }
1427
1428    /**
1429     * Reset stat value to default
1430     */
1431    void
1432    reset(Info *info)
1433    {
1434        const Params *params = safe_cast<const Params *>(info->storageParams);
1435        min_track = params->min;
1436        max_track = params->max;
1437        bucket_size = params->bucket_size;
1438
1439        min_val = CounterLimits::max();
1440        max_val = CounterLimits::min();
1441        underflow = Counter();
1442        overflow = Counter();
1443
1444        size_type size = cvec.size();
1445        for (off_type i = 0; i < size; ++i)
1446            cvec[i] = Counter();
1447
1448        sum = Counter();
1449        squares = Counter();
1450        samples = Counter();
1451    }
1452};
1453
1454/**
1455 * Templatized storage and interface for a histogram stat.
1456 */
1457class HistStor
1458{
1459  public:
1460    /** The parameters for a distribution stat. */
1461    struct Params : public DistParams
1462    {
1463        /** The number of buckets.. */
1464        size_type buckets;
1465
1466        Params() : DistParams(Hist) {}
1467    };
1468
1469  private:
1470    /** The minimum value to track. */
1471    Counter min_bucket;
1472    /** The maximum value to track. */
1473    Counter max_bucket;
1474    /** The number of entries in each bucket. */
1475    Counter bucket_size;
1476
1477    /** The current sum. */
1478    Counter sum;
1479    /** The sum of logarithm of each sample, used to compute geometric mean. */
1480    Counter logs;
1481    /** The sum of squares. */
1482    Counter squares;
1483    /** The number of samples. */
1484    Counter samples;
1485    /** Counter for each bucket. */
1486    VCounter cvec;
1487
1488  public:
1489    HistStor(Info *info)
1490        : cvec(safe_cast<const Params *>(info->storageParams)->buckets)
1491    {
1492        reset(info);
1493    }
1494
1495    void grow_up();
1496    void grow_out();
1497    void grow_convert();
1498
1499    /**
1500     * Add a value to the distribution for the given number of times.
1501     * @param val The value to add.
1502     * @param number The number of times to add the value.
1503     */
1504    void
1505    sample(Counter val, int number)
1506    {
1507        assert(min_bucket < max_bucket);
1508        if (val < min_bucket) {
1509            if (min_bucket == 0)
1510                grow_convert();
1511
1512            while (val < min_bucket)
1513                grow_out();
1514        } else if (val >= max_bucket + bucket_size) {
1515            if (min_bucket == 0) {
1516                while (val >= max_bucket + bucket_size)
1517                    grow_up();
1518            } else {
1519                while (val >= max_bucket + bucket_size)
1520                    grow_out();
1521            }
1522        }
1523
1524        size_type index =
1525            (int64_t)std::floor((val - min_bucket) / bucket_size);
1526
1527        assert(index >= 0 && index < size());
1528        cvec[index] += number;
1529
1530        sum += val * number;
1531        squares += val * val * number;
1532        logs += log(val) * number;
1533        samples += number;
1534    }
1535
1536    /**
1537     * Return the number of buckets in this distribution.
1538     * @return the number of buckets.
1539     */
1540    size_type size() const { return cvec.size(); }
1541
1542    /**
1543     * Returns true if any calls to sample have been made.
1544     * @return True if any values have been sampled.
1545     */
1546    bool
1547    zero() const
1548    {
1549        return samples == Counter();
1550    }
1551
1552    void
1553    prepare(Info *info, DistData &data)
1554    {
1555        const Params *params = safe_cast<const Params *>(info->storageParams);
1556
1557        assert(params->type == Hist);
1558        data.type = params->type;
1559        data.min = min_bucket;
1560        data.max = max_bucket + bucket_size - 1;
1561        data.bucket_size = bucket_size;
1562
1563        data.min_val = min_bucket;
1564        data.max_val = max_bucket;
1565
1566        int buckets = params->buckets;
1567        data.cvec.resize(buckets);
1568        for (off_type i = 0; i < buckets; ++i)
1569            data.cvec[i] = cvec[i];
1570
1571        data.sum = sum;
1572        data.logs = logs;
1573        data.squares = squares;
1574        data.samples = samples;
1575    }
1576
1577    /**
1578     * Reset stat value to default
1579     */
1580    void
1581    reset(Info *info)
1582    {
1583        const Params *params = safe_cast<const Params *>(info->storageParams);
1584        min_bucket = 0;
1585        max_bucket = params->buckets - 1;
1586        bucket_size = 1;
1587
1588        size_type size = cvec.size();
1589        for (off_type i = 0; i < size; ++i)
1590            cvec[i] = Counter();
1591
1592        sum = Counter();
1593        squares = Counter();
1594        samples = Counter();
1595        logs = Counter();
1596    }
1597};
1598
1599/**
1600 * Templatized storage and interface for a distribution that calculates mean
1601 * and variance.
1602 */
1603class SampleStor
1604{
1605  public:
1606    struct Params : public DistParams
1607    {
1608        Params() : DistParams(Deviation) {}
1609    };
1610
1611  private:
1612    /** The current sum. */
1613    Counter sum;
1614    /** The sum of squares. */
1615    Counter squares;
1616    /** The number of samples. */
1617    Counter samples;
1618
1619  public:
1620    /**
1621     * Create and initialize this storage.
1622     */
1623    SampleStor(Info *info)
1624        : sum(Counter()), squares(Counter()), samples(Counter())
1625    { }
1626
1627    /**
1628     * Add a value the given number of times to this running average.
1629     * Update the running sum and sum of squares, increment the number of
1630     * values seen by the given number.
1631     * @param val The value to add.
1632     * @param number The number of times to add the value.
1633     */
1634    void
1635    sample(Counter val, int number)
1636    {
1637        Counter value = val * number;
1638        sum += value;
1639        squares += value * value;
1640        samples += number;
1641    }
1642
1643    /**
1644     * Return the number of entries in this stat, 1
1645     * @return 1.
1646     */
1647    size_type size() const { return 1; }
1648
1649    /**
1650     * Return true if no samples have been added.
1651     * @return True if no samples have been added.
1652     */
1653    bool zero() const { return samples == Counter(); }
1654
1655    void
1656    prepare(Info *info, DistData &data)
1657    {
1658        const Params *params = safe_cast<const Params *>(info->storageParams);
1659
1660        assert(params->type == Deviation);
1661        data.type = params->type;
1662        data.sum = sum;
1663        data.squares = squares;
1664        data.samples = samples;
1665    }
1666
1667    /**
1668     * Reset stat value to default
1669     */
1670    void
1671    reset(Info *info)
1672    {
1673        sum = Counter();
1674        squares = Counter();
1675        samples = Counter();
1676    }
1677};
1678
1679/**
1680 * Templatized storage for distribution that calculates per tick mean and
1681 * variance.
1682 */
1683class AvgSampleStor
1684{
1685  public:
1686    struct Params : public DistParams
1687    {
1688        Params() : DistParams(Deviation) {}
1689    };
1690
1691  private:
1692    /** Current total. */
1693    Counter sum;
1694    /** Current sum of squares. */
1695    Counter squares;
1696
1697  public:
1698    /**
1699     * Create and initialize this storage.
1700     */
1701    AvgSampleStor(Info *info)
1702        : sum(Counter()), squares(Counter())
1703    {}
1704
1705    /**
1706     * Add a value to the distribution for the given number of times.
1707     * Update the running sum and sum of squares.
1708     * @param val The value to add.
1709     * @param number The number of times to add the value.
1710     */
1711    void
1712    sample(Counter val, int number)
1713    {
1714        Counter value = val * number;
1715        sum += value;
1716        squares += value * value;
1717    }
1718
1719    /**
1720     * Return the number of entries, in this case 1.
1721     * @return 1.
1722     */
1723    size_type size() const { return 1; }
1724
1725    /**
1726     * Return true if no samples have been added.
1727     * @return True if the sum is zero.
1728     */
1729    bool zero() const { return sum == Counter(); }
1730
1731    void
1732    prepare(Info *info, DistData &data)
1733    {
1734        const Params *params = safe_cast<const Params *>(info->storageParams);
1735
1736        assert(params->type == Deviation);
1737        data.type = params->type;
1738        data.sum = sum;
1739        data.squares = squares;
1740        data.samples = curTick();
1741    }
1742
1743    /**
1744     * Reset stat value to default
1745     */
1746    void
1747    reset(Info *info)
1748    {
1749        sum = Counter();
1750        squares = Counter();
1751    }
1752};
1753
1754/**
1755 * Implementation of a distribution stat. The type of distribution is
1756 * determined by the Storage template. @sa ScalarBase
1757 */
1758template <class Derived, class Stor>
1759class DistBase : public DataWrap<Derived, DistInfoProxy>
1760{
1761  public:
1762    typedef DistInfoProxy<Derived> Info;
1763    typedef Stor Storage;
1764    typedef typename Stor::Params Params;
1765
1766  protected:
1767    /** The storage for this stat. */
1768    char storage[sizeof(Storage)] __attribute__ ((aligned (8)));
1769
1770  protected:
1771    /**
1772     * Retrieve the storage.
1773     * @return The storage object for this stat.
1774     */
1775    Storage *
1776    data()
1777    {
1778        return reinterpret_cast<Storage *>(storage);
1779    }
1780
1781    /**
1782     * Retrieve a const pointer to the storage.
1783     * @return A const pointer to the storage object for this stat.
1784     */
1785    const Storage *
1786    data() const
1787    {
1788        return reinterpret_cast<const Storage *>(storage);
1789    }
1790
1791    void
1792    doInit()
1793    {
1794        new (storage) Storage(this->info());
1795        this->setInit();
1796    }
1797
1798  public:
1799    DistBase() { }
1800
1801    /**
1802     * Add a value to the distribtion n times. Calls sample on the storage
1803     * class.
1804     * @param v The value to add.
1805     * @param n The number of times to add it, defaults to 1.
1806     */
1807    template <typename U>
1808    void sample(const U &v, int n = 1) { data()->sample(v, n); }
1809
1810    /**
1811     * Return the number of entries in this stat.
1812     * @return The number of entries.
1813     */
1814    size_type size() const { return data()->size(); }
1815    /**
1816     * Return true if no samples have been added.
1817     * @return True if there haven't been any samples.
1818     */
1819    bool zero() const { return data()->zero(); }
1820
1821    void
1822    prepare()
1823    {
1824        Info *info = this->info();
1825        data()->prepare(info, info->data);
1826    }
1827
1828    /**
1829     * Reset stat value to default
1830     */
1831    void
1832    reset()
1833    {
1834        data()->reset(this->info());
1835    }
1836};
1837
1838template <class Stat>
1839class DistProxy;
1840
1841template <class Derived, class Stor>
1842class VectorDistBase : public DataWrapVec<Derived, VectorDistInfoProxy>
1843{
1844  public:
1845    typedef VectorDistInfoProxy<Derived> Info;
1846    typedef Stor Storage;
1847    typedef typename Stor::Params Params;
1848    typedef DistProxy<Derived> Proxy;
1849    friend class DistProxy<Derived>;
1850    friend class DataWrapVec<Derived, VectorDistInfoProxy>;
1851
1852  protected:
1853    Storage *storage;
1854    size_type _size;
1855
1856  protected:
1857    Storage *
1858    data(off_type index)
1859    {
1860        return &storage[index];
1861    }
1862
1863    const Storage *
1864    data(off_type index) const
1865    {
1866        return &storage[index];
1867    }
1868
1869    void
1870    doInit(size_type s)
1871    {
1872        assert(s > 0 && "size must be positive!");
1873        assert(!storage && "already initialized");
1874        _size = s;
1875
1876        char *ptr = new char[_size * sizeof(Storage)];
1877        storage = reinterpret_cast<Storage *>(ptr);
1878
1879        Info *info = this->info();
1880        for (off_type i = 0; i < _size; ++i)
1881            new (&storage[i]) Storage(info);
1882
1883        this->setInit();
1884    }
1885
1886  public:
1887    VectorDistBase()
1888        : storage(NULL)
1889    {}
1890
1891    ~VectorDistBase()
1892    {
1893        if (!storage)
1894            return ;
1895
1896        for (off_type i = 0; i < _size; ++i)
1897            data(i)->~Storage();
1898        delete [] reinterpret_cast<char *>(storage);
1899    }
1900
1901    Proxy operator[](off_type index)
1902    {
1903        assert(index >= 0 && index < size());
1904        return Proxy(this->self(), index);
1905    }
1906
1907    size_type
1908    size() const
1909    {
1910        return _size;
1911    }
1912
1913    bool
1914    zero() const
1915    {
1916        for (off_type i = 0; i < size(); ++i)
1917            if (!data(i)->zero())
1918                return false;
1919        return true;
1920    }
1921
1922    void
1923    prepare()
1924    {
1925        Info *info = this->info();
1926        size_type size = this->size();
1927        info->data.resize(size);
1928        for (off_type i = 0; i < size; ++i)
1929            data(i)->prepare(info, info->data[i]);
1930    }
1931
1932    bool
1933    check() const
1934    {
1935        return storage != NULL;
1936    }
1937};
1938
1939template <class Stat>
1940class DistProxy
1941{
1942  private:
1943    Stat &stat;
1944    off_type index;
1945
1946  protected:
1947    typename Stat::Storage *data() { return stat.data(index); }
1948    const typename Stat::Storage *data() const { return stat.data(index); }
1949
1950  public:
1951    DistProxy(Stat &s, off_type i)
1952        : stat(s), index(i)
1953    {}
1954
1955    DistProxy(const DistProxy &sp)
1956        : stat(sp.stat), index(sp.index)
1957    {}
1958
1959    const DistProxy &
1960    operator=(const DistProxy &sp)
1961    {
1962        stat = sp.stat;
1963        index = sp.index;
1964        return *this;
1965    }
1966
1967  public:
1968    template <typename U>
1969    void
1970    sample(const U &v, int n = 1)
1971    {
1972        data()->sample(v, n);
1973    }
1974
1975    size_type
1976    size() const
1977    {
1978        return 1;
1979    }
1980
1981    bool
1982    zero() const
1983    {
1984        return data()->zero();
1985    }
1986
1987    /**
1988     * Proxy has no state.  Nothing to reset.
1989     */
1990    void reset() { }
1991};
1992
1993//////////////////////////////////////////////////////////////////////
1994//
1995//  Formula Details
1996//
1997//////////////////////////////////////////////////////////////////////
1998
1999/**
2000 * Base class for formula statistic node. These nodes are used to build a tree
2001 * that represents the formula.
2002 */
2003class Node : public RefCounted
2004{
2005  public:
2006    /**
2007     * Return the number of nodes in the subtree starting at this node.
2008     * @return the number of nodes in this subtree.
2009     */
2010    virtual size_type size() const = 0;
2011    /**
2012     * Return the result vector of this subtree.
2013     * @return The result vector of this subtree.
2014     */
2015    virtual const VResult &result() const = 0;
2016    /**
2017     * Return the total of the result vector.
2018     * @return The total of the result vector.
2019     */
2020    virtual Result total() const = 0;
2021
2022    /**
2023     *
2024     */
2025    virtual std::string str() const = 0;
2026};
2027
2028/** Reference counting pointer to a function Node. */
2029typedef RefCountingPtr<Node> NodePtr;
2030
2031class ScalarStatNode : public Node
2032{
2033  private:
2034    const ScalarInfo *data;
2035    mutable VResult vresult;
2036
2037  public:
2038    ScalarStatNode(const ScalarInfo *d) : data(d), vresult(1) {}
2039
2040    const VResult &
2041    result() const
2042    {
2043        vresult[0] = data->result();
2044        return vresult;
2045    }
2046
2047    Result total() const { return data->result(); };
2048
2049    size_type size() const { return 1; }
2050
2051    /**
2052     *
2053     */
2054    std::string str() const { return data->name; }
2055};
2056
2057template <class Stat>
2058class ScalarProxyNode : public Node
2059{
2060  private:
2061    const ScalarProxy<Stat> proxy;
2062    mutable VResult vresult;
2063
2064  public:
2065    ScalarProxyNode(const ScalarProxy<Stat> &p)
2066        : proxy(p), vresult(1)
2067    { }
2068
2069    const VResult &
2070    result() const
2071    {
2072        vresult[0] = proxy.result();
2073        return vresult;
2074    }
2075
2076    Result
2077    total() const
2078    {
2079        return proxy.result();
2080    }
2081
2082    size_type
2083    size() const
2084    {
2085        return 1;
2086    }
2087
2088    /**
2089     *
2090     */
2091    std::string
2092    str() const
2093    {
2094        return proxy.str();
2095    }
2096};
2097
2098class VectorStatNode : public Node
2099{
2100  private:
2101    const VectorInfo *data;
2102
2103  public:
2104    VectorStatNode(const VectorInfo *d) : data(d) { }
2105    const VResult &result() const { return data->result(); }
2106    Result total() const { return data->total(); };
2107
2108    size_type size() const { return data->size(); }
2109
2110    std::string str() const { return data->name; }
2111};
2112
2113template <class T>
2114class ConstNode : public Node
2115{
2116  private:
2117    VResult vresult;
2118
2119  public:
2120    ConstNode(T s) : vresult(1, (Result)s) {}
2121    const VResult &result() const { return vresult; }
2122    Result total() const { return vresult[0]; };
2123    size_type size() const { return 1; }
2124    std::string str() const { return to_string(vresult[0]); }
2125};
2126
2127template <class T>
2128class ConstVectorNode : public Node
2129{
2130  private:
2131    VResult vresult;
2132
2133  public:
2134    ConstVectorNode(const T &s) : vresult(s.begin(), s.end()) {}
2135    const VResult &result() const { return vresult; }
2136
2137    Result
2138    total() const
2139    {
2140        size_type size = this->size();
2141        Result tmp = 0;
2142        for (off_type i = 0; i < size; i++)
2143            tmp += vresult[i];
2144        return tmp;
2145    }
2146
2147    size_type size() const { return vresult.size(); }
2148    std::string
2149    str() const
2150    {
2151        size_type size = this->size();
2152        std::string tmp = "(";
2153        for (off_type i = 0; i < size; i++)
2154            tmp += csprintf("%s ",to_string(vresult[i]));
2155        tmp += ")";
2156        return tmp;
2157    }
2158};
2159
2160template <class Op>
2161struct OpString;
2162
2163template<>
2164struct OpString<std::plus<Result> >
2165{
2166    static std::string str() { return "+"; }
2167};
2168
2169template<>
2170struct OpString<std::minus<Result> >
2171{
2172    static std::string str() { return "-"; }
2173};
2174
2175template<>
2176struct OpString<std::multiplies<Result> >
2177{
2178    static std::string str() { return "*"; }
2179};
2180
2181template<>
2182struct OpString<std::divides<Result> >
2183{
2184    static std::string str() { return "/"; }
2185};
2186
2187template<>
2188struct OpString<std::modulus<Result> >
2189{
2190    static std::string str() { return "%"; }
2191};
2192
2193template<>
2194struct OpString<std::negate<Result> >
2195{
2196    static std::string str() { return "-"; }
2197};
2198
2199template <class Op>
2200class UnaryNode : public Node
2201{
2202  public:
2203    NodePtr l;
2204    mutable VResult vresult;
2205
2206  public:
2207    UnaryNode(NodePtr &p) : l(p) {}
2208
2209    const VResult &
2210    result() const
2211    {
2212        const VResult &lvec = l->result();
2213        size_type size = lvec.size();
2214
2215        assert(size > 0);
2216
2217        vresult.resize(size);
2218        Op op;
2219        for (off_type i = 0; i < size; ++i)
2220            vresult[i] = op(lvec[i]);
2221
2222        return vresult;
2223    }
2224
2225    Result
2226    total() const
2227    {
2228        const VResult &vec = this->result();
2229        Result total = 0.0;
2230        for (off_type i = 0; i < size(); i++)
2231            total += vec[i];
2232        return total;
2233    }
2234
2235    size_type size() const { return l->size(); }
2236
2237    std::string
2238    str() const
2239    {
2240        return OpString<Op>::str() + l->str();
2241    }
2242};
2243
2244template <class Op>
2245class BinaryNode : public Node
2246{
2247  public:
2248    NodePtr l;
2249    NodePtr r;
2250    mutable VResult vresult;
2251
2252  public:
2253    BinaryNode(NodePtr &a, NodePtr &b) : l(a), r(b) {}
2254
2255    const VResult &
2256    result() const
2257    {
2258        Op op;
2259        const VResult &lvec = l->result();
2260        const VResult &rvec = r->result();
2261
2262        assert(lvec.size() > 0 && rvec.size() > 0);
2263
2264        if (lvec.size() == 1 && rvec.size() == 1) {
2265            vresult.resize(1);
2266            vresult[0] = op(lvec[0], rvec[0]);
2267        } else if (lvec.size() == 1) {
2268            size_type size = rvec.size();
2269            vresult.resize(size);
2270            for (off_type i = 0; i < size; ++i)
2271                vresult[i] = op(lvec[0], rvec[i]);
2272        } else if (rvec.size() == 1) {
2273            size_type size = lvec.size();
2274            vresult.resize(size);
2275            for (off_type i = 0; i < size; ++i)
2276                vresult[i] = op(lvec[i], rvec[0]);
2277        } else if (rvec.size() == lvec.size()) {
2278            size_type size = rvec.size();
2279            vresult.resize(size);
2280            for (off_type i = 0; i < size; ++i)
2281                vresult[i] = op(lvec[i], rvec[i]);
2282        }
2283
2284        return vresult;
2285    }
2286
2287    Result
2288    total() const
2289    {
2290        const VResult &vec = this->result();
2291        const VResult &lvec = l->result();
2292        const VResult &rvec = r->result();
2293        Result total = 0.0;
2294        Result lsum = 0.0;
2295        Result rsum = 0.0;
2296        Op op;
2297
2298        assert(lvec.size() > 0 && rvec.size() > 0);
2299        assert(lvec.size() == rvec.size() ||
2300               lvec.size() == 1 || rvec.size() == 1);
2301
2302        /** If vectors are the same divide their sums (x0+x1)/(y0+y1) */
2303        if (lvec.size() == rvec.size() && lvec.size() > 1) {
2304            for (off_type i = 0; i < size(); ++i) {
2305                lsum += lvec[i];
2306                rsum += rvec[i];
2307            }
2308            return op(lsum, rsum);
2309        }
2310
2311        /** Otherwise divide each item by the divisor */
2312        for (off_type i = 0; i < size(); ++i) {
2313            total += vec[i];
2314        }
2315
2316        return total;
2317    }
2318
2319    size_type
2320    size() const
2321    {
2322        size_type ls = l->size();
2323        size_type rs = r->size();
2324        if (ls == 1) {
2325            return rs;
2326        } else if (rs == 1) {
2327            return ls;
2328        } else {
2329            assert(ls == rs && "Node vector sizes are not equal");
2330            return ls;
2331        }
2332    }
2333
2334    std::string
2335    str() const
2336    {
2337        return csprintf("(%s %s %s)", l->str(), OpString<Op>::str(), r->str());
2338    }
2339};
2340
2341template <class Op>
2342class SumNode : public Node
2343{
2344  public:
2345    NodePtr l;
2346    mutable VResult vresult;
2347
2348  public:
2349    SumNode(NodePtr &p) : l(p), vresult(1) {}
2350
2351    const VResult &
2352    result() const
2353    {
2354        const VResult &lvec = l->result();
2355        size_type size = lvec.size();
2356        assert(size > 0);
2357
2358        vresult[0] = 0.0;
2359
2360        Op op;
2361        for (off_type i = 0; i < size; ++i)
2362            vresult[0] = op(vresult[0], lvec[i]);
2363
2364        return vresult;
2365    }
2366
2367    Result
2368    total() const
2369    {
2370        const VResult &lvec = l->result();
2371        size_type size = lvec.size();
2372        assert(size > 0);
2373
2374        Result result = 0.0;
2375
2376        Op op;
2377        for (off_type i = 0; i < size; ++i)
2378            result = op(result, lvec[i]);
2379
2380        return result;
2381    }
2382
2383    size_type size() const { return 1; }
2384
2385    std::string
2386    str() const
2387    {
2388        return csprintf("total(%s)", l->str());
2389    }
2390};
2391
2392
2393//////////////////////////////////////////////////////////////////////
2394//
2395// Visible Statistics Types
2396//
2397//////////////////////////////////////////////////////////////////////
2398/**
2399 * @defgroup VisibleStats "Statistic Types"
2400 * These are the statistics that are used in the simulator.
2401 * @{
2402 */
2403
2404/**
2405 * This is a simple scalar statistic, like a counter.
2406 * @sa Stat, ScalarBase, StatStor
2407 */
2408class Scalar : public ScalarBase<Scalar, StatStor>
2409{
2410  public:
2411    using ScalarBase<Scalar, StatStor>::operator=;
2412};
2413
2414/**
2415 * A stat that calculates the per tick average of a value.
2416 * @sa Stat, ScalarBase, AvgStor
2417 */
2418class Average : public ScalarBase<Average, AvgStor>
2419{
2420  public:
2421    using ScalarBase<Average, AvgStor>::operator=;
2422};
2423
2424class Value : public ValueBase<Value>
2425{
2426};
2427
2428/**
2429 * A vector of scalar stats.
2430 * @sa Stat, VectorBase, StatStor
2431 */
2432class Vector : public VectorBase<Vector, StatStor>
2433{
2434};
2435
2436/**
2437 * A vector of Average stats.
2438 * @sa Stat, VectorBase, AvgStor
2439 */
2440class AverageVector : public VectorBase<AverageVector, AvgStor>
2441{
2442};
2443
2444/**
2445 * A 2-Dimensional vecto of scalar stats.
2446 * @sa Stat, Vector2dBase, StatStor
2447 */
2448class Vector2d : public Vector2dBase<Vector2d, StatStor>
2449{
2450};
2451
2452/**
2453 * A simple distribution stat.
2454 * @sa Stat, DistBase, DistStor
2455 */
2456class Distribution : public DistBase<Distribution, DistStor>
2457{
2458  public:
2459    /**
2460     * Set the parameters of this distribution. @sa DistStor::Params
2461     * @param min The minimum value of the distribution.
2462     * @param max The maximum value of the distribution.
2463     * @param bkt The number of values in each bucket.
2464     * @return A reference to this distribution.
2465     */
2466    Distribution &
2467    init(Counter min, Counter max, Counter bkt)
2468    {
2469        DistStor::Params *params = new DistStor::Params;
2470        params->min = min;
2471        params->max = max;
2472        params->bucket_size = bkt;
2473        params->buckets = (size_type)ceil((max - min + 1.0) / bkt);
2474        this->setParams(params);
2475        this->doInit();
2476        return this->self();
2477    }
2478};
2479
2480/**
2481 * A simple histogram stat.
2482 * @sa Stat, DistBase, HistStor
2483 */
2484class Histogram : public DistBase<Histogram, HistStor>
2485{
2486  public:
2487    /**
2488     * Set the parameters of this histogram. @sa HistStor::Params
2489     * @param size The number of buckets in the histogram
2490     * @return A reference to this histogram.
2491     */
2492    Histogram &
2493    init(size_type size)
2494    {
2495        HistStor::Params *params = new HistStor::Params;
2496        params->buckets = size;
2497        this->setParams(params);
2498        this->doInit();
2499        return this->self();
2500    }
2501};
2502
2503/**
2504 * Calculates the mean and variance of all the samples.
2505 * @sa DistBase, SampleStor
2506 */
2507class StandardDeviation : public DistBase<StandardDeviation, SampleStor>
2508{
2509  public:
2510    /**
2511     * Construct and initialize this distribution.
2512     */
2513    StandardDeviation()
2514    {
2515        SampleStor::Params *params = new SampleStor::Params;
2516        this->doInit();
2517        this->setParams(params);
2518    }
2519};
2520
2521/**
2522 * Calculates the per tick mean and variance of the samples.
2523 * @sa DistBase, AvgSampleStor
2524 */
2525class AverageDeviation : public DistBase<AverageDeviation, AvgSampleStor>
2526{
2527  public:
2528    /**
2529     * Construct and initialize this distribution.
2530     */
2531    AverageDeviation()
2532    {
2533        AvgSampleStor::Params *params = new AvgSampleStor::Params;
2534        this->doInit();
2535        this->setParams(params);
2536    }
2537};
2538
2539/**
2540 * A vector of distributions.
2541 * @sa VectorDistBase, DistStor
2542 */
2543class VectorDistribution : public VectorDistBase<VectorDistribution, DistStor>
2544{
2545  public:
2546    /**
2547     * Initialize storage and parameters for this distribution.
2548     * @param size The size of the vector (the number of distributions).
2549     * @param min The minimum value of the distribution.
2550     * @param max The maximum value of the distribution.
2551     * @param bkt The number of values in each bucket.
2552     * @return A reference to this distribution.
2553     */
2554    VectorDistribution &
2555    init(size_type size, Counter min, Counter max, Counter bkt)
2556    {
2557        DistStor::Params *params = new DistStor::Params;
2558        params->min = min;
2559        params->max = max;
2560        params->bucket_size = bkt;
2561        params->buckets = (size_type)ceil((max - min + 1.0) / bkt);
2562        this->setParams(params);
2563        this->doInit(size);
2564        return this->self();
2565    }
2566};
2567
2568/**
2569 * This is a vector of StandardDeviation stats.
2570 * @sa VectorDistBase, SampleStor
2571 */
2572class VectorStandardDeviation
2573    : public VectorDistBase<VectorStandardDeviation, SampleStor>
2574{
2575  public:
2576    /**
2577     * Initialize storage for this distribution.
2578     * @param size The size of the vector.
2579     * @return A reference to this distribution.
2580     */
2581    VectorStandardDeviation &
2582    init(size_type size)
2583    {
2584        SampleStor::Params *params = new SampleStor::Params;
2585        this->doInit(size);
2586        this->setParams(params);
2587        return this->self();
2588    }
2589};
2590
2591/**
2592 * This is a vector of AverageDeviation stats.
2593 * @sa VectorDistBase, AvgSampleStor
2594 */
2595class VectorAverageDeviation
2596    : public VectorDistBase<VectorAverageDeviation, AvgSampleStor>
2597{
2598  public:
2599    /**
2600     * Initialize storage for this distribution.
2601     * @param size The size of the vector.
2602     * @return A reference to this distribution.
2603     */
2604    VectorAverageDeviation &
2605    init(size_type size)
2606    {
2607        AvgSampleStor::Params *params = new AvgSampleStor::Params;
2608        this->doInit(size);
2609        this->setParams(params);
2610        return this->self();
2611    }
2612};
2613
2614template <class Stat>
2615class FormulaInfoProxy : public InfoProxy<Stat, FormulaInfo>
2616{
2617  protected:
2618    mutable VResult vec;
2619    mutable VCounter cvec;
2620
2621  public:
2622    FormulaInfoProxy(Stat &stat) : InfoProxy<Stat, FormulaInfo>(stat) {}
2623
2624    size_type size() const { return this->s.size(); }
2625
2626    const VResult &
2627    result() const
2628    {
2629        this->s.result(vec);
2630        return vec;
2631    }
2632    Result total() const { return this->s.total(); }
2633    VCounter &value() const { return cvec; }
2634
2635    std::string str() const { return this->s.str(); }
2636};
2637
2638template <class Stat>
2639class SparseHistInfoProxy : public InfoProxy<Stat, SparseHistInfo>
2640{
2641  public:
2642    SparseHistInfoProxy(Stat &stat) : InfoProxy<Stat, SparseHistInfo>(stat) {}
2643};
2644
2645/**
2646 * Implementation of a sparse histogram stat. The storage class is
2647 * determined by the Storage template.
2648 */
2649template <class Derived, class Stor>
2650class SparseHistBase : public DataWrap<Derived, SparseHistInfoProxy>
2651{
2652  public:
2653    typedef SparseHistInfoProxy<Derived> Info;
2654    typedef Stor Storage;
2655    typedef typename Stor::Params Params;
2656
2657  protected:
2658    /** The storage for this stat. */
2659    char storage[sizeof(Storage)];
2660
2661  protected:
2662    /**
2663     * Retrieve the storage.
2664     * @return The storage object for this stat.
2665     */
2666    Storage *
2667    data()
2668    {
2669        return reinterpret_cast<Storage *>(storage);
2670    }
2671
2672    /**
2673     * Retrieve a const pointer to the storage.
2674     * @return A const pointer to the storage object for this stat.
2675     */
2676    const Storage *
2677    data() const
2678    {
2679        return reinterpret_cast<const Storage *>(storage);
2680    }
2681
2682    void
2683    doInit()
2684    {
2685        new (storage) Storage(this->info());
2686        this->setInit();
2687    }
2688
2689  public:
2690    SparseHistBase() { }
2691
2692    /**
2693     * Add a value to the distribtion n times. Calls sample on the storage
2694     * class.
2695     * @param v The value to add.
2696     * @param n The number of times to add it, defaults to 1.
2697     */
2698    template <typename U>
2699    void sample(const U &v, int n = 1) { data()->sample(v, n); }
2700
2701    /**
2702     * Return the number of entries in this stat.
2703     * @return The number of entries.
2704     */
2705    size_type size() const { return data()->size(); }
2706    /**
2707     * Return true if no samples have been added.
2708     * @return True if there haven't been any samples.
2709     */
2710    bool zero() const { return data()->zero(); }
2711
2712    void
2713    prepare()
2714    {
2715        Info *info = this->info();
2716        data()->prepare(info, info->data);
2717    }
2718
2719    /**
2720     * Reset stat value to default
2721     */
2722    void
2723    reset()
2724    {
2725        data()->reset(this->info());
2726    }
2727};
2728
2729/**
2730 * Templatized storage and interface for a sparse histogram stat.
2731 */
2732class SparseHistStor
2733{
2734  public:
2735    /** The parameters for a sparse histogram stat. */
2736    struct Params : public DistParams
2737    {
2738        Params() : DistParams(Hist) {}
2739    };
2740
2741  private:
2742    /** Counter for number of samples */
2743    Counter samples;
2744    /** Counter for each bucket. */
2745    MCounter cmap;
2746
2747  public:
2748    SparseHistStor(Info *info)
2749    {
2750        reset(info);
2751    }
2752
2753    /**
2754     * Add a value to the distribution for the given number of times.
2755     * @param val The value to add.
2756     * @param number The number of times to add the value.
2757     */
2758    void
2759    sample(Counter val, int number)
2760    {
2761        cmap[val] += number;
2762        samples += number;
2763    }
2764
2765    /**
2766     * Return the number of buckets in this distribution.
2767     * @return the number of buckets.
2768     */
2769    size_type size() const { return cmap.size(); }
2770
2771    /**
2772     * Returns true if any calls to sample have been made.
2773     * @return True if any values have been sampled.
2774     */
2775    bool
2776    zero() const
2777    {
2778        return samples == Counter();
2779    }
2780
2781    void
2782    prepare(Info *info, SparseHistData &data)
2783    {
2784        MCounter::iterator it;
2785        data.cmap.clear();
2786        for (it = cmap.begin(); it != cmap.end(); it++) {
2787            data.cmap[(*it).first] = (*it).second;
2788        }
2789
2790        data.samples = samples;
2791    }
2792
2793    /**
2794     * Reset stat value to default
2795     */
2796    void
2797    reset(Info *info)
2798    {
2799        cmap.clear();
2800        samples = 0;
2801    }
2802};
2803
2804class SparseHistogram : public SparseHistBase<SparseHistogram, SparseHistStor>
2805{
2806  public:
2807    /**
2808     * Set the parameters of this histogram. @sa HistStor::Params
2809     * @param size The number of buckets in the histogram
2810     * @return A reference to this histogram.
2811     */
2812    SparseHistogram &
2813    init(size_type size)
2814    {
2815        SparseHistStor::Params *params = new SparseHistStor::Params;
2816        this->setParams(params);
2817        this->doInit();
2818        return this->self();
2819    }
2820};
2821
2822class Temp;
2823/**
2824 * A formula for statistics that is calculated when printed. A formula is
2825 * stored as a tree of Nodes that represent the equation to calculate.
2826 * @sa Stat, ScalarStat, VectorStat, Node, Temp
2827 */
2828class Formula : public DataWrapVec<Formula, FormulaInfoProxy>
2829{
2830  protected:
2831    /** The root of the tree which represents the Formula */
2832    NodePtr root;
2833    friend class Temp;
2834
2835  public:
2836    /**
2837     * Create and initialize thie formula, and register it with the database.
2838     */
2839    Formula();
2840
2841    /**
2842     * Create a formula with the given root node, register it with the
2843     * database.
2844     * @param r The root of the expression tree.
2845     */
2846    Formula(Temp r);
2847
2848    /**
2849     * Set an unitialized Formula to the given root.
2850     * @param r The root of the expression tree.
2851     * @return a reference to this formula.
2852     */
2853    const Formula &operator=(Temp r);
2854
2855    /**
2856     * Add the given tree to the existing one.
2857     * @param r The root of the expression tree.
2858     * @return a reference to this formula.
2859     */
2860    const Formula &operator+=(Temp r);
2861    /**
2862     * Return the result of the Fomula in a vector.  If there were no Vector
2863     * components to the Formula, then the vector is size 1.  If there were,
2864     * like x/y with x being a vector of size 3, then the result returned will
2865     * be x[0]/y, x[1]/y, x[2]/y, respectively.
2866     * @return The result vector.
2867     */
2868    void result(VResult &vec) const;
2869
2870    /**
2871     * Return the total Formula result.  If there is a Vector
2872     * component to this Formula, then this is the result of the
2873     * Formula if the formula is applied after summing all the
2874     * components of the Vector.  For example, if Formula is x/y where
2875     * x is size 3, then total() will return (x[1]+x[2]+x[3])/y.  If
2876     * there is no Vector component, total() returns the same value as
2877     * the first entry in the VResult val() returns.
2878     * @return The total of the result vector.
2879     */
2880    Result total() const;
2881
2882    /**
2883     * Return the number of elements in the tree.
2884     */
2885    size_type size() const;
2886
2887    void prepare() { }
2888
2889    /**
2890     * Formulas don't need to be reset
2891     */
2892    void reset();
2893
2894    /**
2895     *
2896     */
2897    bool zero() const;
2898
2899    std::string str() const;
2900};
2901
2902class FormulaNode : public Node
2903{
2904  private:
2905    const Formula &formula;
2906    mutable VResult vec;
2907
2908  public:
2909    FormulaNode(const Formula &f) : formula(f) {}
2910
2911    size_type size() const { return formula.size(); }
2912    const VResult &result() const { formula.result(vec); return vec; }
2913    Result total() const { return formula.total(); }
2914
2915    std::string str() const { return formula.str(); }
2916};
2917
2918/**
2919 * Helper class to construct formula node trees.
2920 */
2921class Temp
2922{
2923  protected:
2924    /**
2925     * Pointer to a Node object.
2926     */
2927    NodePtr node;
2928
2929  public:
2930    /**
2931     * Copy the given pointer to this class.
2932     * @param n A pointer to a Node object to copy.
2933     */
2934    Temp(NodePtr n) : node(n) { }
2935
2936    /**
2937     * Return the node pointer.
2938     * @return the node pointer.
2939     */
2940    operator NodePtr&() { return node; }
2941
2942  public:
2943    /**
2944     * Create a new ScalarStatNode.
2945     * @param s The ScalarStat to place in a node.
2946     */
2947    Temp(const Scalar &s)
2948        : node(new ScalarStatNode(s.info()))
2949    { }
2950
2951    /**
2952     * Create a new ScalarStatNode.
2953     * @param s The ScalarStat to place in a node.
2954     */
2955    Temp(const Value &s)
2956        : node(new ScalarStatNode(s.info()))
2957    { }
2958
2959    /**
2960     * Create a new ScalarStatNode.
2961     * @param s The ScalarStat to place in a node.
2962     */
2963    Temp(const Average &s)
2964        : node(new ScalarStatNode(s.info()))
2965    { }
2966
2967    /**
2968     * Create a new VectorStatNode.
2969     * @param s The VectorStat to place in a node.
2970     */
2971    Temp(const Vector &s)
2972        : node(new VectorStatNode(s.info()))
2973    { }
2974
2975    Temp(const AverageVector &s)
2976        : node(new VectorStatNode(s.info()))
2977    { }
2978
2979    /**
2980     *
2981     */
2982    Temp(const Formula &f)
2983        : node(new FormulaNode(f))
2984    { }
2985
2986    /**
2987     * Create a new ScalarProxyNode.
2988     * @param p The ScalarProxy to place in a node.
2989     */
2990    template <class Stat>
2991    Temp(const ScalarProxy<Stat> &p)
2992        : node(new ScalarProxyNode<Stat>(p))
2993    { }
2994
2995    /**
2996     * Create a ConstNode
2997     * @param value The value of the const node.
2998     */
2999    Temp(signed char value)
3000        : node(new ConstNode<signed char>(value))
3001    { }
3002
3003    /**
3004     * Create a ConstNode
3005     * @param value The value of the const node.
3006     */
3007    Temp(unsigned char value)
3008        : node(new ConstNode<unsigned char>(value))
3009    { }
3010
3011    /**
3012     * Create a ConstNode
3013     * @param value The value of the const node.
3014     */
3015    Temp(signed short value)
3016        : node(new ConstNode<signed short>(value))
3017    { }
3018
3019    /**
3020     * Create a ConstNode
3021     * @param value The value of the const node.
3022     */
3023    Temp(unsigned short value)
3024        : node(new ConstNode<unsigned short>(value))
3025    { }
3026
3027    /**
3028     * Create a ConstNode
3029     * @param value The value of the const node.
3030     */
3031    Temp(signed int value)
3032        : node(new ConstNode<signed int>(value))
3033    { }
3034
3035    /**
3036     * Create a ConstNode
3037     * @param value The value of the const node.
3038     */
3039    Temp(unsigned int value)
3040        : node(new ConstNode<unsigned int>(value))
3041    { }
3042
3043    /**
3044     * Create a ConstNode
3045     * @param value The value of the const node.
3046     */
3047    Temp(signed long value)
3048        : node(new ConstNode<signed long>(value))
3049    { }
3050
3051    /**
3052     * Create a ConstNode
3053     * @param value The value of the const node.
3054     */
3055    Temp(unsigned long value)
3056        : node(new ConstNode<unsigned long>(value))
3057    { }
3058
3059    /**
3060     * Create a ConstNode
3061     * @param value The value of the const node.
3062     */
3063    Temp(signed long long value)
3064        : node(new ConstNode<signed long long>(value))
3065    { }
3066
3067    /**
3068     * Create a ConstNode
3069     * @param value The value of the const node.
3070     */
3071    Temp(unsigned long long value)
3072        : node(new ConstNode<unsigned long long>(value))
3073    { }
3074
3075    /**
3076     * Create a ConstNode
3077     * @param value The value of the const node.
3078     */
3079    Temp(float value)
3080        : node(new ConstNode<float>(value))
3081    { }
3082
3083    /**
3084     * Create a ConstNode
3085     * @param value The value of the const node.
3086     */
3087    Temp(double value)
3088        : node(new ConstNode<double>(value))
3089    { }
3090};
3091
3092
3093/**
3094 * @}
3095 */
3096
3097inline Temp
3098operator+(Temp l, Temp r)
3099{
3100    return NodePtr(new BinaryNode<std::plus<Result> >(l, r));
3101}
3102
3103inline Temp
3104operator-(Temp l, Temp r)
3105{
3106    return NodePtr(new BinaryNode<std::minus<Result> >(l, r));
3107}
3108
3109inline Temp
3110operator*(Temp l, Temp r)
3111{
3112    return NodePtr(new BinaryNode<std::multiplies<Result> >(l, r));
3113}
3114
3115inline Temp
3116operator/(Temp l, Temp r)
3117{
3118    return NodePtr(new BinaryNode<std::divides<Result> >(l, r));
3119}
3120
3121inline Temp
3122operator-(Temp l)
3123{
3124    return NodePtr(new UnaryNode<std::negate<Result> >(l));
3125}
3126
3127template <typename T>
3128inline Temp
3129constant(T val)
3130{
3131    return NodePtr(new ConstNode<T>(val));
3132}
3133
3134template <typename T>
3135inline Temp
3136constantVector(T val)
3137{
3138    return NodePtr(new ConstVectorNode<T>(val));
3139}
3140
3141inline Temp
3142sum(Temp val)
3143{
3144    return NodePtr(new SumNode<std::plus<Result> >(val));
3145}
3146
3147/** Dump all statistics data to the registered outputs */
3148void dump();
3149void reset();
3150void enable();
3151bool enabled();
3152
3153/**
3154 * Register a callback that should be called whenever statistics are
3155 * reset
3156 */
3157void registerResetCallback(Callback *cb);
3158
3159/**
3160 * Register a callback that should be called whenever statistics are
3161 * about to be dumped
3162 */
3163void registerDumpCallback(Callback *cb);
3164
3165std::list<Info *> &statsList();
3166
3167typedef std::map<const void *, Info *> MapType;
3168MapType &statsMap();
3169
3170typedef std::map<std::string, Info *> NameMapType;
3171NameMapType &nameMap();
3172
3173bool validateStatName(const std::string &name);
3174
3175} // namespace Stats
3176
3177void debugDumpStats();
3178
3179#endif // __BASE_STATISTICS_HH__
3180