statistics.hh revision 9865:cc5797147e1c
1/*
2 * Copyright (c) 2003-2005 The Regents of The University of Michigan
3 * All rights reserved.
4 *
5 * Redistribution and use in source and binary forms, with or without
6 * modification, are permitted provided that the following conditions are
7 * met: redistributions of source code must retain the above copyright
8 * notice, this list of conditions and the following disclaimer;
9 * redistributions in binary form must reproduce the above copyright
10 * notice, this list of conditions and the following disclaimer in the
11 * documentation and/or other materials provided with the distribution;
12 * neither the name of the copyright holders nor the names of its
13 * contributors may be used to endorse or promote products derived from
14 * this software without specific prior written permission.
15 *
16 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
17 * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
18 * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
19 * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
20 * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
21 * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
22 * LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
23 * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
24 * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
25 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
26 * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
27 *
28 * Authors: Nathan Binkert
29 */
30
31/** @file
32 * Declaration of Statistics objects.
33 */
34
35/**
36* @todo
37*
38* Generalized N-dimensinal vector
39* documentation
40* key stats
41* interval stats
42*   -- these both can use the same function that prints out a
43*   specific set of stats
44* VectorStandardDeviation totals
45* Document Namespaces
46*/
47#ifndef __BASE_STATISTICS_HH__
48#define __BASE_STATISTICS_HH__
49
50#include <algorithm>
51#include <cassert>
52#ifdef __SUNPRO_CC
53#include <math.h>
54#endif
55#include <cmath>
56#include <functional>
57#include <iosfwd>
58#include <list>
59#include <map>
60#include <string>
61#include <vector>
62
63#include "base/stats/info.hh"
64#include "base/stats/output.hh"
65#include "base/stats/types.hh"
66#include "base/cast.hh"
67#include "base/cprintf.hh"
68#include "base/intmath.hh"
69#include "base/refcnt.hh"
70#include "base/str.hh"
71#include "base/types.hh"
72
73class Callback;
74
75/** The current simulated tick. */
76extern Tick curTick();
77
78/* A namespace for all of the Statistics */
79namespace Stats {
80
81template <class Stat, class Base>
82class InfoProxy : public Base
83{
84  protected:
85    Stat &s;
86
87  public:
88    InfoProxy(Stat &stat) : s(stat) {}
89
90    bool check() const { return s.check(); }
91    void prepare() { s.prepare(); }
92    void reset() { s.reset(); }
93    void
94    visit(Output &visitor)
95    {
96        visitor.visit(*static_cast<Base *>(this));
97    }
98    bool zero() const { return s.zero(); }
99};
100
101template <class Stat>
102class ScalarInfoProxy : public InfoProxy<Stat, ScalarInfo>
103{
104  public:
105    ScalarInfoProxy(Stat &stat) : InfoProxy<Stat, ScalarInfo>(stat) {}
106
107    Counter value() const { return this->s.value(); }
108    Result result() const { return this->s.result(); }
109    Result total() const { return this->s.total(); }
110};
111
112template <class Stat>
113class VectorInfoProxy : public InfoProxy<Stat, VectorInfo>
114{
115  protected:
116    mutable VCounter cvec;
117    mutable VResult rvec;
118
119  public:
120    VectorInfoProxy(Stat &stat) : InfoProxy<Stat, VectorInfo>(stat) {}
121
122    size_type size() const { return this->s.size(); }
123
124    VCounter &
125    value() const
126    {
127        this->s.value(cvec);
128        return cvec;
129    }
130
131    const VResult &
132    result() const
133    {
134        this->s.result(rvec);
135        return rvec;
136    }
137
138    Result total() const { return this->s.total(); }
139};
140
141template <class Stat>
142class DistInfoProxy : public InfoProxy<Stat, DistInfo>
143{
144  public:
145    DistInfoProxy(Stat &stat) : InfoProxy<Stat, DistInfo>(stat) {}
146};
147
148template <class Stat>
149class VectorDistInfoProxy : public InfoProxy<Stat, VectorDistInfo>
150{
151  public:
152    VectorDistInfoProxy(Stat &stat) : InfoProxy<Stat, VectorDistInfo>(stat) {}
153
154    size_type size() const { return this->s.size(); }
155};
156
157template <class Stat>
158class Vector2dInfoProxy : public InfoProxy<Stat, Vector2dInfo>
159{
160  public:
161    Vector2dInfoProxy(Stat &stat) : InfoProxy<Stat, Vector2dInfo>(stat) {}
162};
163
164struct StorageParams
165{
166    virtual ~StorageParams();
167};
168
169class InfoAccess
170{
171  protected:
172    /** Set up an info class for this statistic */
173    void setInfo(Info *info);
174    /** Save Storage class parameters if any */
175    void setParams(const StorageParams *params);
176    /** Save Storage class parameters if any */
177    void setInit();
178
179    /** Grab the information class for this statistic */
180    Info *info();
181    /** Grab the information class for this statistic */
182    const Info *info() const;
183
184  public:
185    /**
186     * Reset the stat to the default state.
187     */
188    void reset() { }
189
190    /**
191     * @return true if this stat has a value and satisfies its
192     * requirement as a prereq
193     */
194    bool zero() const { return true; }
195
196    /**
197     * Check that this stat has been set up properly and is ready for
198     * use
199     * @return true for success
200     */
201    bool check() const { return true; }
202};
203
204template <class Derived, template <class> class InfoProxyType>
205class DataWrap : public InfoAccess
206{
207  public:
208    typedef InfoProxyType<Derived> Info;
209
210  protected:
211    Derived &self() { return *static_cast<Derived *>(this); }
212
213  protected:
214    Info *
215    info()
216    {
217        return safe_cast<Info *>(InfoAccess::info());
218    }
219
220  public:
221    const Info *
222    info() const
223    {
224        return safe_cast<const Info *>(InfoAccess::info());
225    }
226
227  protected:
228    /**
229     * Copy constructor, copies are not allowed.
230     */
231    DataWrap(const DataWrap &stat);
232
233    /**
234     * Can't copy stats.
235     */
236    void operator=(const DataWrap &);
237
238  public:
239    DataWrap()
240    {
241        this->setInfo(new Info(self()));
242    }
243
244    /**
245     * Set the name and marks this stat to print at the end of simulation.
246     * @param name The new name.
247     * @return A reference to this stat.
248     */
249    Derived &
250    name(const std::string &name)
251    {
252        Info *info = this->info();
253        info->setName(name);
254        info->flags.set(display);
255        return this->self();
256    }
257    const std::string &name() const { return this->info()->name; }
258
259    /**
260     * Set the character(s) used between the name and vector number
261     * on vectors, dist, etc.
262     * @param _sep The new separator string
263     * @return A reference to this stat.
264     */
265    Derived &
266    setSeparator(const std::string &_sep)
267    {
268      this->info()->setSeparator(_sep);
269      return this->self();
270    }
271    const std::string &setSeparator() const
272    {
273      return this->info()->separatorString;
274    }
275
276    /**
277     * Set the description and marks this stat to print at the end of
278     * simulation.
279     * @param desc The new description.
280     * @return A reference to this stat.
281     */
282    Derived &
283    desc(const std::string &_desc)
284    {
285        this->info()->desc = _desc;
286        return this->self();
287    }
288
289    /**
290     * Set the precision and marks this stat to print at the end of simulation.
291     * @param _precision The new precision
292     * @return A reference to this stat.
293     */
294    Derived &
295    precision(int _precision)
296    {
297        this->info()->precision = _precision;
298        return this->self();
299    }
300
301    /**
302     * Set the flags and marks this stat to print at the end of simulation.
303     * @param f The new flags.
304     * @return A reference to this stat.
305     */
306    Derived &
307    flags(Flags _flags)
308    {
309        this->info()->flags.set(_flags);
310        return this->self();
311    }
312
313    /**
314     * Set the prerequisite stat and marks this stat to print at the end of
315     * simulation.
316     * @param prereq The prerequisite stat.
317     * @return A reference to this stat.
318     */
319    template <class Stat>
320    Derived &
321    prereq(const Stat &prereq)
322    {
323        this->info()->prereq = prereq.info();
324        return this->self();
325    }
326};
327
328template <class Derived, template <class> class InfoProxyType>
329class DataWrapVec : public DataWrap<Derived, InfoProxyType>
330{
331  public:
332    typedef InfoProxyType<Derived> Info;
333
334    DataWrapVec()
335    {}
336
337    DataWrapVec(const DataWrapVec &ref)
338    {}
339
340    void operator=(const DataWrapVec &)
341    {}
342
343    // The following functions are specific to vectors.  If you use them
344    // in a non vector context, you will get a nice compiler error!
345
346    /**
347     * Set the subfield name for the given index, and marks this stat to print
348     * at the end of simulation.
349     * @param index The subfield index.
350     * @param name The new name of the subfield.
351     * @return A reference to this stat.
352     */
353    Derived &
354    subname(off_type index, const std::string &name)
355    {
356        Derived &self = this->self();
357        Info *info = self.info();
358
359        std::vector<std::string> &subn = info->subnames;
360        if (subn.size() <= index)
361            subn.resize(index + 1);
362        subn[index] = name;
363        return self;
364    }
365
366    // The following functions are specific to 2d vectors.  If you use
367    // them in a non vector context, you will get a nice compiler
368    // error because info doesn't have the right variables.
369
370    /**
371     * Set the subfield description for the given index and marks this stat to
372     * print at the end of simulation.
373     * @param index The subfield index.
374     * @param desc The new description of the subfield
375     * @return A reference to this stat.
376     */
377    Derived &
378    subdesc(off_type index, const std::string &desc)
379    {
380        Info *info = this->info();
381
382        std::vector<std::string> &subd = info->subdescs;
383        if (subd.size() <= index)
384            subd.resize(index + 1);
385        subd[index] = desc;
386
387        return this->self();
388    }
389
390    void
391    prepare()
392    {
393        Derived &self = this->self();
394        Info *info = this->info();
395
396        size_t size = self.size();
397        for (off_type i = 0; i < size; ++i)
398            self.data(i)->prepare(info);
399    }
400
401    void
402    reset()
403    {
404        Derived &self = this->self();
405        Info *info = this->info();
406
407        size_t size = self.size();
408        for (off_type i = 0; i < size; ++i)
409            self.data(i)->reset(info);
410    }
411};
412
413template <class Derived, template <class> class InfoProxyType>
414class DataWrapVec2d : public DataWrapVec<Derived, InfoProxyType>
415{
416  public:
417    typedef InfoProxyType<Derived> Info;
418
419    /**
420     * @warning This makes the assumption that if you're gonna subnames a 2d
421     * vector, you're subnaming across all y
422     */
423    Derived &
424    ysubnames(const char **names)
425    {
426        Derived &self = this->self();
427        Info *info = this->info();
428
429        info->y_subnames.resize(self.y);
430        for (off_type i = 0; i < self.y; ++i)
431            info->y_subnames[i] = names[i];
432        return self;
433    }
434
435    Derived &
436    ysubname(off_type index, const std::string &subname)
437    {
438        Derived &self = this->self();
439        Info *info = this->info();
440
441        assert(index < self.y);
442        info->y_subnames.resize(self.y);
443        info->y_subnames[index] = subname.c_str();
444        return self;
445    }
446
447    std::string
448    ysubname(off_type i) const
449    {
450        return this->info()->y_subnames[i];
451    }
452
453};
454
455//////////////////////////////////////////////////////////////////////
456//
457// Simple Statistics
458//
459//////////////////////////////////////////////////////////////////////
460
461/**
462 * Templatized storage and interface for a simple scalar stat.
463 */
464class StatStor
465{
466  private:
467    /** The statistic value. */
468    Counter data;
469
470  public:
471    struct Params : public StorageParams {};
472
473  public:
474    /**
475     * Builds this storage element and calls the base constructor of the
476     * datatype.
477     */
478    StatStor(Info *info)
479        : data(Counter())
480    { }
481
482    /**
483     * The the stat to the given value.
484     * @param val The new value.
485     */
486    void set(Counter val) { data = val; }
487    /**
488     * Increment the stat by the given value.
489     * @param val The new value.
490     */
491    void inc(Counter val) { data += val; }
492    /**
493     * Decrement the stat by the given value.
494     * @param val The new value.
495     */
496    void dec(Counter val) { data -= val; }
497    /**
498     * Return the value of this stat as its base type.
499     * @return The value of this stat.
500     */
501    Counter value() const { return data; }
502    /**
503     * Return the value of this stat as a result type.
504     * @return The value of this stat.
505     */
506    Result result() const { return (Result)data; }
507    /**
508     * Prepare stat data for dumping or serialization
509     */
510    void prepare(Info *info) { }
511    /**
512     * Reset stat value to default
513     */
514    void reset(Info *info) { data = Counter(); }
515
516    /**
517     * @return true if zero value
518     */
519    bool zero() const { return data == Counter(); }
520};
521
522/**
523 * Templatized storage and interface to a per-tick average stat. This keeps
524 * a current count and updates a total (count * ticks) when this count
525 * changes. This allows the quick calculation of a per tick count of the item
526 * being watched. This is good for keeping track of residencies in structures
527 * among other things.
528 */
529class AvgStor
530{
531  private:
532    /** The current count. */
533    Counter current;
534    /** The tick of the last reset */
535    Tick lastReset;
536    /** The total count for all tick. */
537    mutable Result total;
538    /** The tick that current last changed. */
539    mutable Tick last;
540
541  public:
542    struct Params : public StorageParams {};
543
544  public:
545    /**
546     * Build and initializes this stat storage.
547     */
548    AvgStor(Info *info)
549        : current(0), lastReset(0), total(0), last(0)
550    { }
551
552    /**
553     * Set the current count to the one provided, update the total and last
554     * set values.
555     * @param val The new count.
556     */
557    void
558    set(Counter val)
559    {
560        total += current * (curTick() - last);
561        last = curTick();
562        current = val;
563    }
564
565    /**
566     * Increment the current count by the provided value, calls set.
567     * @param val The amount to increment.
568     */
569    void inc(Counter val) { set(current + val); }
570
571    /**
572     * Deccrement the current count by the provided value, calls set.
573     * @param val The amount to decrement.
574     */
575    void dec(Counter val) { set(current - val); }
576
577    /**
578     * Return the current count.
579     * @return The current count.
580     */
581    Counter value() const { return current; }
582
583    /**
584     * Return the current average.
585     * @return The current average.
586     */
587    Result
588    result() const
589    {
590        assert(last == curTick());
591        return (Result)(total + current) / (Result)(curTick() - lastReset + 1);
592    }
593
594    /**
595     * @return true if zero value
596     */
597    bool zero() const { return total == 0.0; }
598
599    /**
600     * Prepare stat data for dumping or serialization
601     */
602    void
603    prepare(Info *info)
604    {
605        total += current * (curTick() - last);
606        last = curTick();
607    }
608
609    /**
610     * Reset stat value to default
611     */
612    void
613    reset(Info *info)
614    {
615        total = 0.0;
616        last = curTick();
617        lastReset = curTick();
618    }
619
620};
621
622/**
623 * Implementation of a scalar stat. The type of stat is determined by the
624 * Storage template.
625 */
626template <class Derived, class Stor>
627class ScalarBase : public DataWrap<Derived, ScalarInfoProxy>
628{
629  public:
630    typedef Stor Storage;
631    typedef typename Stor::Params Params;
632
633  protected:
634    /** The storage of this stat. */
635    char storage[sizeof(Storage)] __attribute__ ((aligned (8)));
636
637  protected:
638    /**
639     * Retrieve the storage.
640     * @param index The vector index to access.
641     * @return The storage object at the given index.
642     */
643    Storage *
644    data()
645    {
646        return reinterpret_cast<Storage *>(storage);
647    }
648
649    /**
650     * Retrieve a const pointer to the storage.
651     * for the given index.
652     * @param index The vector index to access.
653     * @return A const pointer to the storage object at the given index.
654     */
655    const Storage *
656    data() const
657    {
658        return reinterpret_cast<const Storage *>(storage);
659    }
660
661    void
662    doInit()
663    {
664        new (storage) Storage(this->info());
665        this->setInit();
666    }
667
668  public:
669    /**
670     * Return the current value of this stat as its base type.
671     * @return The current value.
672     */
673    Counter value() const { return data()->value(); }
674
675  public:
676    ScalarBase()
677    {
678        this->doInit();
679    }
680
681  public:
682    // Common operators for stats
683    /**
684     * Increment the stat by 1. This calls the associated storage object inc
685     * function.
686     */
687    void operator++() { data()->inc(1); }
688    /**
689     * Decrement the stat by 1. This calls the associated storage object dec
690     * function.
691     */
692    void operator--() { data()->dec(1); }
693
694    /** Increment the stat by 1. */
695    void operator++(int) { ++*this; }
696    /** Decrement the stat by 1. */
697    void operator--(int) { --*this; }
698
699    /**
700     * Set the data value to the given value. This calls the associated storage
701     * object set function.
702     * @param v The new value.
703     */
704    template <typename U>
705    void operator=(const U &v) { data()->set(v); }
706
707    /**
708     * Increment the stat by the given value. This calls the associated
709     * storage object inc function.
710     * @param v The value to add.
711     */
712    template <typename U>
713    void operator+=(const U &v) { data()->inc(v); }
714
715    /**
716     * Decrement the stat by the given value. This calls the associated
717     * storage object dec function.
718     * @param v The value to substract.
719     */
720    template <typename U>
721    void operator-=(const U &v) { data()->dec(v); }
722
723    /**
724     * Return the number of elements, always 1 for a scalar.
725     * @return 1.
726     */
727    size_type size() const { return 1; }
728
729    Counter value() { return data()->value(); }
730
731    Result result() { return data()->result(); }
732
733    Result total() { return result(); }
734
735    bool zero() { return result() == 0.0; }
736
737    void reset() { data()->reset(this->info()); }
738    void prepare() { data()->prepare(this->info()); }
739};
740
741class ProxyInfo : public ScalarInfo
742{
743  public:
744    std::string str() const { return to_string(value()); }
745    size_type size() const { return 1; }
746    bool check() const { return true; }
747    void prepare() { }
748    void reset() { }
749    bool zero() const { return value() == 0; }
750
751    void visit(Output &visitor) { visitor.visit(*this); }
752};
753
754template <class T>
755class ValueProxy : public ProxyInfo
756{
757  private:
758    T *scalar;
759
760  public:
761    ValueProxy(T &val) : scalar(&val) {}
762    Counter value() const { return *scalar; }
763    Result result() const { return *scalar; }
764    Result total() const { return *scalar; }
765};
766
767template <class T>
768class FunctorProxy : public ProxyInfo
769{
770  private:
771    T *functor;
772
773  public:
774    FunctorProxy(T &func) : functor(&func) {}
775    Counter value() const { return (*functor)(); }
776    Result result() const { return (*functor)(); }
777    Result total() const { return (*functor)(); }
778};
779
780template <class Derived>
781class ValueBase : public DataWrap<Derived, ScalarInfoProxy>
782{
783  private:
784    ProxyInfo *proxy;
785
786  public:
787    ValueBase() : proxy(NULL) { }
788    ~ValueBase() { if (proxy) delete proxy; }
789
790    template <class T>
791    Derived &
792    scalar(T &value)
793    {
794        proxy = new ValueProxy<T>(value);
795        this->setInit();
796        return this->self();
797    }
798
799    template <class T>
800    Derived &
801    functor(T &func)
802    {
803        proxy = new FunctorProxy<T>(func);
804        this->setInit();
805        return this->self();
806    }
807
808    Counter value() { return proxy->value(); }
809    Result result() const { return proxy->result(); }
810    Result total() const { return proxy->total(); };
811    size_type size() const { return proxy->size(); }
812
813    std::string str() const { return proxy->str(); }
814    bool zero() const { return proxy->zero(); }
815    bool check() const { return proxy != NULL; }
816    void prepare() { }
817    void reset() { }
818};
819
820//////////////////////////////////////////////////////////////////////
821//
822// Vector Statistics
823//
824//////////////////////////////////////////////////////////////////////
825
826/**
827 * A proxy class to access the stat at a given index in a VectorBase stat.
828 * Behaves like a ScalarBase.
829 */
830template <class Stat>
831class ScalarProxy
832{
833  private:
834    /** Pointer to the parent Vector. */
835    Stat &stat;
836
837    /** The index to access in the parent VectorBase. */
838    off_type index;
839
840  public:
841    /**
842     * Return the current value of this stat as its base type.
843     * @return The current value.
844     */
845    Counter value() const { return stat.data(index)->value(); }
846
847    /**
848     * Return the current value of this statas a result type.
849     * @return The current value.
850     */
851    Result result() const { return stat.data(index)->result(); }
852
853  public:
854    /**
855     * Create and initialize this proxy, do not register it with the database.
856     * @param i The index to access.
857     */
858    ScalarProxy(Stat &s, off_type i)
859        : stat(s), index(i)
860    {
861    }
862
863    /**
864     * Create a copy of the provided ScalarProxy.
865     * @param sp The proxy to copy.
866     */
867    ScalarProxy(const ScalarProxy &sp)
868        : stat(sp.stat), index(sp.index)
869    {}
870
871    /**
872     * Set this proxy equal to the provided one.
873     * @param sp The proxy to copy.
874     * @return A reference to this proxy.
875     */
876    const ScalarProxy &
877    operator=(const ScalarProxy &sp)
878    {
879        stat = sp.stat;
880        index = sp.index;
881        return *this;
882    }
883
884  public:
885    // Common operators for stats
886    /**
887     * Increment the stat by 1. This calls the associated storage object inc
888     * function.
889     */
890    void operator++() { stat.data(index)->inc(1); }
891    /**
892     * Decrement the stat by 1. This calls the associated storage object dec
893     * function.
894     */
895    void operator--() { stat.data(index)->dec(1); }
896
897    /** Increment the stat by 1. */
898    void operator++(int) { ++*this; }
899    /** Decrement the stat by 1. */
900    void operator--(int) { --*this; }
901
902    /**
903     * Set the data value to the given value. This calls the associated storage
904     * object set function.
905     * @param v The new value.
906     */
907    template <typename U>
908    void
909    operator=(const U &v)
910    {
911        stat.data(index)->set(v);
912    }
913
914    /**
915     * Increment the stat by the given value. This calls the associated
916     * storage object inc function.
917     * @param v The value to add.
918     */
919    template <typename U>
920    void
921    operator+=(const U &v)
922    {
923        stat.data(index)->inc(v);
924    }
925
926    /**
927     * Decrement the stat by the given value. This calls the associated
928     * storage object dec function.
929     * @param v The value to substract.
930     */
931    template <typename U>
932    void
933    operator-=(const U &v)
934    {
935        stat.data(index)->dec(v);
936    }
937
938    /**
939     * Return the number of elements, always 1 for a scalar.
940     * @return 1.
941     */
942    size_type size() const { return 1; }
943
944  public:
945    std::string
946    str() const
947    {
948        return csprintf("%s[%d]", stat.info()->name, index);
949    }
950};
951
952/**
953 * Implementation of a vector of stats. The type of stat is determined by the
954 * Storage class. @sa ScalarBase
955 */
956template <class Derived, class Stor>
957class VectorBase : public DataWrapVec<Derived, VectorInfoProxy>
958{
959  public:
960    typedef Stor Storage;
961    typedef typename Stor::Params Params;
962
963    /** Proxy type */
964    typedef ScalarProxy<Derived> Proxy;
965    friend class ScalarProxy<Derived>;
966    friend class DataWrapVec<Derived, VectorInfoProxy>;
967
968  protected:
969    /** The storage of this stat. */
970    Storage *storage;
971    size_type _size;
972
973  protected:
974    /**
975     * Retrieve the storage.
976     * @param index The vector index to access.
977     * @return The storage object at the given index.
978     */
979    Storage *data(off_type index) { return &storage[index]; }
980
981    /**
982     * Retrieve a const pointer to the storage.
983     * @param index The vector index to access.
984     * @return A const pointer to the storage object at the given index.
985     */
986    const Storage *data(off_type index) const { return &storage[index]; }
987
988    void
989    doInit(size_type s)
990    {
991        assert(s > 0 && "size must be positive!");
992        assert(!storage && "already initialized");
993        _size = s;
994
995        char *ptr = new char[_size * sizeof(Storage)];
996        storage = reinterpret_cast<Storage *>(ptr);
997
998        for (off_type i = 0; i < _size; ++i)
999            new (&storage[i]) Storage(this->info());
1000
1001        this->setInit();
1002    }
1003
1004  public:
1005    void
1006    value(VCounter &vec) const
1007    {
1008        vec.resize(size());
1009        for (off_type i = 0; i < size(); ++i)
1010            vec[i] = data(i)->value();
1011    }
1012
1013    /**
1014     * Copy the values to a local vector and return a reference to it.
1015     * @return A reference to a vector of the stat values.
1016     */
1017    void
1018    result(VResult &vec) const
1019    {
1020        vec.resize(size());
1021        for (off_type i = 0; i < size(); ++i)
1022            vec[i] = data(i)->result();
1023    }
1024
1025    /**
1026     * Return a total of all entries in this vector.
1027     * @return The total of all vector entries.
1028     */
1029    Result
1030    total() const
1031    {
1032        Result total = 0.0;
1033        for (off_type i = 0; i < size(); ++i)
1034            total += data(i)->result();
1035        return total;
1036    }
1037
1038    /**
1039     * @return the number of elements in this vector.
1040     */
1041    size_type size() const { return _size; }
1042
1043    bool
1044    zero() const
1045    {
1046        for (off_type i = 0; i < size(); ++i)
1047            if (data(i)->zero())
1048                return false;
1049        return true;
1050    }
1051
1052    bool
1053    check() const
1054    {
1055        return storage != NULL;
1056    }
1057
1058  public:
1059    VectorBase()
1060        : storage(NULL)
1061    {}
1062
1063    ~VectorBase()
1064    {
1065        if (!storage)
1066            return;
1067
1068        for (off_type i = 0; i < _size; ++i)
1069            data(i)->~Storage();
1070        delete [] reinterpret_cast<char *>(storage);
1071    }
1072
1073    /**
1074     * Set this vector to have the given size.
1075     * @param size The new size.
1076     * @return A reference to this stat.
1077     */
1078    Derived &
1079    init(size_type size)
1080    {
1081        Derived &self = this->self();
1082        self.doInit(size);
1083        return self;
1084    }
1085
1086    /**
1087     * Return a reference (ScalarProxy) to the stat at the given index.
1088     * @param index The vector index to access.
1089     * @return A reference of the stat.
1090     */
1091    Proxy
1092    operator[](off_type index)
1093    {
1094        assert (index >= 0 && index < size());
1095        return Proxy(this->self(), index);
1096    }
1097};
1098
1099template <class Stat>
1100class VectorProxy
1101{
1102  private:
1103    Stat &stat;
1104    off_type offset;
1105    size_type len;
1106
1107  private:
1108    mutable VResult vec;
1109
1110    typename Stat::Storage *
1111    data(off_type index)
1112    {
1113        assert(index < len);
1114        return stat.data(offset + index);
1115    }
1116
1117    const typename Stat::Storage *
1118    data(off_type index) const
1119    {
1120        assert(index < len);
1121        return stat.data(offset + index);
1122    }
1123
1124  public:
1125    const VResult &
1126    result() const
1127    {
1128        vec.resize(size());
1129
1130        for (off_type i = 0; i < size(); ++i)
1131            vec[i] = data(i)->result();
1132
1133        return vec;
1134    }
1135
1136    Result
1137    total() const
1138    {
1139        Result total = 0.0;
1140        for (off_type i = 0; i < size(); ++i)
1141            total += data(i)->result();
1142        return total;
1143    }
1144
1145  public:
1146    VectorProxy(Stat &s, off_type o, size_type l)
1147        : stat(s), offset(o), len(l)
1148    {
1149    }
1150
1151    VectorProxy(const VectorProxy &sp)
1152        : stat(sp.stat), offset(sp.offset), len(sp.len)
1153    {
1154    }
1155
1156    const VectorProxy &
1157    operator=(const VectorProxy &sp)
1158    {
1159        stat = sp.stat;
1160        offset = sp.offset;
1161        len = sp.len;
1162        return *this;
1163    }
1164
1165    ScalarProxy<Stat>
1166    operator[](off_type index)
1167    {
1168        assert (index >= 0 && index < size());
1169        return ScalarProxy<Stat>(stat, offset + index);
1170    }
1171
1172    size_type size() const { return len; }
1173};
1174
1175template <class Derived, class Stor>
1176class Vector2dBase : public DataWrapVec2d<Derived, Vector2dInfoProxy>
1177{
1178  public:
1179    typedef Vector2dInfoProxy<Derived> Info;
1180    typedef Stor Storage;
1181    typedef typename Stor::Params Params;
1182    typedef VectorProxy<Derived> Proxy;
1183    friend class ScalarProxy<Derived>;
1184    friend class VectorProxy<Derived>;
1185    friend class DataWrapVec<Derived, Vector2dInfoProxy>;
1186    friend class DataWrapVec2d<Derived, Vector2dInfoProxy>;
1187
1188  protected:
1189    size_type x;
1190    size_type y;
1191    size_type _size;
1192    Storage *storage;
1193
1194  protected:
1195    Storage *data(off_type index) { return &storage[index]; }
1196    const Storage *data(off_type index) const { return &storage[index]; }
1197
1198  public:
1199    Vector2dBase()
1200        : storage(NULL)
1201    {}
1202
1203    ~Vector2dBase()
1204    {
1205        if (!storage)
1206            return;
1207
1208        for (off_type i = 0; i < _size; ++i)
1209            data(i)->~Storage();
1210        delete [] reinterpret_cast<char *>(storage);
1211    }
1212
1213    Derived &
1214    init(size_type _x, size_type _y)
1215    {
1216        assert(_x > 0 && _y > 0 && "sizes must be positive!");
1217        assert(!storage && "already initialized");
1218
1219        Derived &self = this->self();
1220        Info *info = this->info();
1221
1222        x = _x;
1223        y = _y;
1224        info->x = _x;
1225        info->y = _y;
1226        _size = x * y;
1227
1228        char *ptr = new char[_size * sizeof(Storage)];
1229        storage = reinterpret_cast<Storage *>(ptr);
1230
1231        for (off_type i = 0; i < _size; ++i)
1232            new (&storage[i]) Storage(info);
1233
1234        this->setInit();
1235
1236        return self;
1237    }
1238
1239    Proxy
1240    operator[](off_type index)
1241    {
1242        off_type offset = index * y;
1243        assert (index >= 0 && offset + y <= size());
1244        return Proxy(this->self(), offset, y);
1245    }
1246
1247
1248    size_type
1249    size() const
1250    {
1251        return _size;
1252    }
1253
1254    bool
1255    zero() const
1256    {
1257        return data(0)->zero();
1258#if 0
1259        for (off_type i = 0; i < size(); ++i)
1260            if (!data(i)->zero())
1261                return false;
1262        return true;
1263#endif
1264    }
1265
1266    void
1267    prepare()
1268    {
1269        Info *info = this->info();
1270        size_type size = this->size();
1271
1272        for (off_type i = 0; i < size; ++i)
1273            data(i)->prepare(info);
1274
1275        info->cvec.resize(size);
1276        for (off_type i = 0; i < size; ++i)
1277            info->cvec[i] = data(i)->value();
1278    }
1279
1280    /**
1281     * Reset stat value to default
1282     */
1283    void
1284    reset()
1285    {
1286        Info *info = this->info();
1287        size_type size = this->size();
1288        for (off_type i = 0; i < size; ++i)
1289            data(i)->reset(info);
1290    }
1291
1292    bool
1293    check() const
1294    {
1295        return storage != NULL;
1296    }
1297};
1298
1299//////////////////////////////////////////////////////////////////////
1300//
1301// Non formula statistics
1302//
1303//////////////////////////////////////////////////////////////////////
1304/** The parameters for a distribution stat. */
1305struct DistParams : public StorageParams
1306{
1307    const DistType type;
1308    DistParams(DistType t) : type(t) {}
1309};
1310
1311/**
1312 * Templatized storage and interface for a distrbution stat.
1313 */
1314class DistStor
1315{
1316  public:
1317    /** The parameters for a distribution stat. */
1318    struct Params : public DistParams
1319    {
1320        /** The minimum value to track. */
1321        Counter min;
1322        /** The maximum value to track. */
1323        Counter max;
1324        /** The number of entries in each bucket. */
1325        Counter bucket_size;
1326        /** The number of buckets. Equal to (max-min)/bucket_size. */
1327        size_type buckets;
1328
1329        Params() : DistParams(Dist) {}
1330    };
1331
1332  private:
1333    /** The minimum value to track. */
1334    Counter min_track;
1335    /** The maximum value to track. */
1336    Counter max_track;
1337    /** The number of entries in each bucket. */
1338    Counter bucket_size;
1339
1340    /** The smallest value sampled. */
1341    Counter min_val;
1342    /** The largest value sampled. */
1343    Counter max_val;
1344    /** The number of values sampled less than min. */
1345    Counter underflow;
1346    /** The number of values sampled more than max. */
1347    Counter overflow;
1348    /** The current sum. */
1349    Counter sum;
1350    /** The sum of squares. */
1351    Counter squares;
1352    /** The number of samples. */
1353    Counter samples;
1354    /** Counter for each bucket. */
1355    VCounter cvec;
1356
1357  public:
1358    DistStor(Info *info)
1359        : cvec(safe_cast<const Params *>(info->storageParams)->buckets)
1360    {
1361        reset(info);
1362    }
1363
1364    /**
1365     * Add a value to the distribution for the given number of times.
1366     * @param val The value to add.
1367     * @param number The number of times to add the value.
1368     */
1369    void
1370    sample(Counter val, int number)
1371    {
1372        if (val < min_track)
1373            underflow += number;
1374        else if (val > max_track)
1375            overflow += number;
1376        else {
1377            size_type index =
1378                (size_type)std::floor((val - min_track) / bucket_size);
1379            assert(index < size());
1380            cvec[index] += number;
1381        }
1382
1383        if (val < min_val)
1384            min_val = val;
1385
1386        if (val > max_val)
1387            max_val = val;
1388
1389        sum += val * number;
1390        squares += val * val * number;
1391        samples += number;
1392    }
1393
1394    /**
1395     * Return the number of buckets in this distribution.
1396     * @return the number of buckets.
1397     */
1398    size_type size() const { return cvec.size(); }
1399
1400    /**
1401     * Returns true if any calls to sample have been made.
1402     * @return True if any values have been sampled.
1403     */
1404    bool
1405    zero() const
1406    {
1407        return samples == Counter();
1408    }
1409
1410    void
1411    prepare(Info *info, DistData &data)
1412    {
1413        const Params *params = safe_cast<const Params *>(info->storageParams);
1414
1415        assert(params->type == Dist);
1416        data.type = params->type;
1417        data.min = params->min;
1418        data.max = params->max;
1419        data.bucket_size = params->bucket_size;
1420
1421        data.min_val = (min_val == CounterLimits::max()) ? 0 : min_val;
1422        data.max_val = (max_val == CounterLimits::min()) ? 0 : max_val;
1423        data.underflow = underflow;
1424        data.overflow = overflow;
1425
1426        data.cvec.resize(params->buckets);
1427        for (off_type i = 0; i < params->buckets; ++i)
1428            data.cvec[i] = cvec[i];
1429
1430        data.sum = sum;
1431        data.squares = squares;
1432        data.samples = samples;
1433    }
1434
1435    /**
1436     * Reset stat value to default
1437     */
1438    void
1439    reset(Info *info)
1440    {
1441        const Params *params = safe_cast<const Params *>(info->storageParams);
1442        min_track = params->min;
1443        max_track = params->max;
1444        bucket_size = params->bucket_size;
1445
1446        min_val = CounterLimits::max();
1447        max_val = CounterLimits::min();
1448        underflow = Counter();
1449        overflow = Counter();
1450
1451        size_type size = cvec.size();
1452        for (off_type i = 0; i < size; ++i)
1453            cvec[i] = Counter();
1454
1455        sum = Counter();
1456        squares = Counter();
1457        samples = Counter();
1458    }
1459};
1460
1461/**
1462 * Templatized storage and interface for a histogram stat.
1463 */
1464class HistStor
1465{
1466  public:
1467    /** The parameters for a distribution stat. */
1468    struct Params : public DistParams
1469    {
1470        /** The number of buckets.. */
1471        size_type buckets;
1472
1473        Params() : DistParams(Hist) {}
1474    };
1475
1476  private:
1477    /** The minimum value to track. */
1478    Counter min_bucket;
1479    /** The maximum value to track. */
1480    Counter max_bucket;
1481    /** The number of entries in each bucket. */
1482    Counter bucket_size;
1483
1484    /** The current sum. */
1485    Counter sum;
1486    /** The sum of logarithm of each sample, used to compute geometric mean. */
1487    Counter logs;
1488    /** The sum of squares. */
1489    Counter squares;
1490    /** The number of samples. */
1491    Counter samples;
1492    /** Counter for each bucket. */
1493    VCounter cvec;
1494
1495  public:
1496    HistStor(Info *info)
1497        : cvec(safe_cast<const Params *>(info->storageParams)->buckets)
1498    {
1499        reset(info);
1500    }
1501
1502    void grow_up();
1503    void grow_out();
1504    void grow_convert();
1505
1506    /**
1507     * Add a value to the distribution for the given number of times.
1508     * @param val The value to add.
1509     * @param number The number of times to add the value.
1510     */
1511    void
1512    sample(Counter val, int number)
1513    {
1514        assert(min_bucket < max_bucket);
1515        if (val < min_bucket) {
1516            if (min_bucket == 0)
1517                grow_convert();
1518
1519            while (val < min_bucket)
1520                grow_out();
1521        } else if (val >= max_bucket + bucket_size) {
1522            if (min_bucket == 0) {
1523                while (val >= max_bucket + bucket_size)
1524                    grow_up();
1525            } else {
1526                while (val >= max_bucket + bucket_size)
1527                    grow_out();
1528            }
1529        }
1530
1531        size_type index =
1532            (int64_t)std::floor((val - min_bucket) / bucket_size);
1533
1534        assert(index >= 0 && index < size());
1535        cvec[index] += number;
1536
1537        sum += val * number;
1538        squares += val * val * number;
1539        logs += log(val) * number;
1540        samples += number;
1541    }
1542
1543    /**
1544     * Return the number of buckets in this distribution.
1545     * @return the number of buckets.
1546     */
1547    size_type size() const { return cvec.size(); }
1548
1549    /**
1550     * Returns true if any calls to sample have been made.
1551     * @return True if any values have been sampled.
1552     */
1553    bool
1554    zero() const
1555    {
1556        return samples == Counter();
1557    }
1558
1559    void
1560    prepare(Info *info, DistData &data)
1561    {
1562        const Params *params = safe_cast<const Params *>(info->storageParams);
1563
1564        assert(params->type == Hist);
1565        data.type = params->type;
1566        data.min = min_bucket;
1567        data.max = max_bucket + bucket_size - 1;
1568        data.bucket_size = bucket_size;
1569
1570        data.min_val = min_bucket;
1571        data.max_val = max_bucket;
1572
1573        int buckets = params->buckets;
1574        data.cvec.resize(buckets);
1575        for (off_type i = 0; i < buckets; ++i)
1576            data.cvec[i] = cvec[i];
1577
1578        data.sum = sum;
1579        data.logs = logs;
1580        data.squares = squares;
1581        data.samples = samples;
1582    }
1583
1584    /**
1585     * Reset stat value to default
1586     */
1587    void
1588    reset(Info *info)
1589    {
1590        const Params *params = safe_cast<const Params *>(info->storageParams);
1591        min_bucket = 0;
1592        max_bucket = params->buckets - 1;
1593        bucket_size = 1;
1594
1595        size_type size = cvec.size();
1596        for (off_type i = 0; i < size; ++i)
1597            cvec[i] = Counter();
1598
1599        sum = Counter();
1600        squares = Counter();
1601        samples = Counter();
1602        logs = Counter();
1603    }
1604};
1605
1606/**
1607 * Templatized storage and interface for a distribution that calculates mean
1608 * and variance.
1609 */
1610class SampleStor
1611{
1612  public:
1613    struct Params : public DistParams
1614    {
1615        Params() : DistParams(Deviation) {}
1616    };
1617
1618  private:
1619    /** The current sum. */
1620    Counter sum;
1621    /** The sum of squares. */
1622    Counter squares;
1623    /** The number of samples. */
1624    Counter samples;
1625
1626  public:
1627    /**
1628     * Create and initialize this storage.
1629     */
1630    SampleStor(Info *info)
1631        : sum(Counter()), squares(Counter()), samples(Counter())
1632    { }
1633
1634    /**
1635     * Add a value the given number of times to this running average.
1636     * Update the running sum and sum of squares, increment the number of
1637     * values seen by the given number.
1638     * @param val The value to add.
1639     * @param number The number of times to add the value.
1640     */
1641    void
1642    sample(Counter val, int number)
1643    {
1644        Counter value = val * number;
1645        sum += value;
1646        squares += value * value;
1647        samples += number;
1648    }
1649
1650    /**
1651     * Return the number of entries in this stat, 1
1652     * @return 1.
1653     */
1654    size_type size() const { return 1; }
1655
1656    /**
1657     * Return true if no samples have been added.
1658     * @return True if no samples have been added.
1659     */
1660    bool zero() const { return samples == Counter(); }
1661
1662    void
1663    prepare(Info *info, DistData &data)
1664    {
1665        const Params *params = safe_cast<const Params *>(info->storageParams);
1666
1667        assert(params->type == Deviation);
1668        data.type = params->type;
1669        data.sum = sum;
1670        data.squares = squares;
1671        data.samples = samples;
1672    }
1673
1674    /**
1675     * Reset stat value to default
1676     */
1677    void
1678    reset(Info *info)
1679    {
1680        sum = Counter();
1681        squares = Counter();
1682        samples = Counter();
1683    }
1684};
1685
1686/**
1687 * Templatized storage for distribution that calculates per tick mean and
1688 * variance.
1689 */
1690class AvgSampleStor
1691{
1692  public:
1693    struct Params : public DistParams
1694    {
1695        Params() : DistParams(Deviation) {}
1696    };
1697
1698  private:
1699    /** Current total. */
1700    Counter sum;
1701    /** Current sum of squares. */
1702    Counter squares;
1703
1704  public:
1705    /**
1706     * Create and initialize this storage.
1707     */
1708    AvgSampleStor(Info *info)
1709        : sum(Counter()), squares(Counter())
1710    {}
1711
1712    /**
1713     * Add a value to the distribution for the given number of times.
1714     * Update the running sum and sum of squares.
1715     * @param val The value to add.
1716     * @param number The number of times to add the value.
1717     */
1718    void
1719    sample(Counter val, int number)
1720    {
1721        Counter value = val * number;
1722        sum += value;
1723        squares += value * value;
1724    }
1725
1726    /**
1727     * Return the number of entries, in this case 1.
1728     * @return 1.
1729     */
1730    size_type size() const { return 1; }
1731
1732    /**
1733     * Return true if no samples have been added.
1734     * @return True if the sum is zero.
1735     */
1736    bool zero() const { return sum == Counter(); }
1737
1738    void
1739    prepare(Info *info, DistData &data)
1740    {
1741        const Params *params = safe_cast<const Params *>(info->storageParams);
1742
1743        assert(params->type == Deviation);
1744        data.type = params->type;
1745        data.sum = sum;
1746        data.squares = squares;
1747        data.samples = curTick();
1748    }
1749
1750    /**
1751     * Reset stat value to default
1752     */
1753    void
1754    reset(Info *info)
1755    {
1756        sum = Counter();
1757        squares = Counter();
1758    }
1759};
1760
1761/**
1762 * Implementation of a distribution stat. The type of distribution is
1763 * determined by the Storage template. @sa ScalarBase
1764 */
1765template <class Derived, class Stor>
1766class DistBase : public DataWrap<Derived, DistInfoProxy>
1767{
1768  public:
1769    typedef DistInfoProxy<Derived> Info;
1770    typedef Stor Storage;
1771    typedef typename Stor::Params Params;
1772
1773  protected:
1774    /** The storage for this stat. */
1775    char storage[sizeof(Storage)] __attribute__ ((aligned (8)));
1776
1777  protected:
1778    /**
1779     * Retrieve the storage.
1780     * @return The storage object for this stat.
1781     */
1782    Storage *
1783    data()
1784    {
1785        return reinterpret_cast<Storage *>(storage);
1786    }
1787
1788    /**
1789     * Retrieve a const pointer to the storage.
1790     * @return A const pointer to the storage object for this stat.
1791     */
1792    const Storage *
1793    data() const
1794    {
1795        return reinterpret_cast<const Storage *>(storage);
1796    }
1797
1798    void
1799    doInit()
1800    {
1801        new (storage) Storage(this->info());
1802        this->setInit();
1803    }
1804
1805  public:
1806    DistBase() { }
1807
1808    /**
1809     * Add a value to the distribtion n times. Calls sample on the storage
1810     * class.
1811     * @param v The value to add.
1812     * @param n The number of times to add it, defaults to 1.
1813     */
1814    template <typename U>
1815    void sample(const U &v, int n = 1) { data()->sample(v, n); }
1816
1817    /**
1818     * Return the number of entries in this stat.
1819     * @return The number of entries.
1820     */
1821    size_type size() const { return data()->size(); }
1822    /**
1823     * Return true if no samples have been added.
1824     * @return True if there haven't been any samples.
1825     */
1826    bool zero() const { return data()->zero(); }
1827
1828    void
1829    prepare()
1830    {
1831        Info *info = this->info();
1832        data()->prepare(info, info->data);
1833    }
1834
1835    /**
1836     * Reset stat value to default
1837     */
1838    void
1839    reset()
1840    {
1841        data()->reset(this->info());
1842    }
1843};
1844
1845template <class Stat>
1846class DistProxy;
1847
1848template <class Derived, class Stor>
1849class VectorDistBase : public DataWrapVec<Derived, VectorDistInfoProxy>
1850{
1851  public:
1852    typedef VectorDistInfoProxy<Derived> Info;
1853    typedef Stor Storage;
1854    typedef typename Stor::Params Params;
1855    typedef DistProxy<Derived> Proxy;
1856    friend class DistProxy<Derived>;
1857    friend class DataWrapVec<Derived, VectorDistInfoProxy>;
1858
1859  protected:
1860    Storage *storage;
1861    size_type _size;
1862
1863  protected:
1864    Storage *
1865    data(off_type index)
1866    {
1867        return &storage[index];
1868    }
1869
1870    const Storage *
1871    data(off_type index) const
1872    {
1873        return &storage[index];
1874    }
1875
1876    void
1877    doInit(size_type s)
1878    {
1879        assert(s > 0 && "size must be positive!");
1880        assert(!storage && "already initialized");
1881        _size = s;
1882
1883        char *ptr = new char[_size * sizeof(Storage)];
1884        storage = reinterpret_cast<Storage *>(ptr);
1885
1886        Info *info = this->info();
1887        for (off_type i = 0; i < _size; ++i)
1888            new (&storage[i]) Storage(info);
1889
1890        this->setInit();
1891    }
1892
1893  public:
1894    VectorDistBase()
1895        : storage(NULL)
1896    {}
1897
1898    ~VectorDistBase()
1899    {
1900        if (!storage)
1901            return ;
1902
1903        for (off_type i = 0; i < _size; ++i)
1904            data(i)->~Storage();
1905        delete [] reinterpret_cast<char *>(storage);
1906    }
1907
1908    Proxy operator[](off_type index)
1909    {
1910        assert(index >= 0 && index < size());
1911        return Proxy(this->self(), index);
1912    }
1913
1914    size_type
1915    size() const
1916    {
1917        return _size;
1918    }
1919
1920    bool
1921    zero() const
1922    {
1923        for (off_type i = 0; i < size(); ++i)
1924            if (!data(i)->zero())
1925                return false;
1926        return true;
1927    }
1928
1929    void
1930    prepare()
1931    {
1932        Info *info = this->info();
1933        size_type size = this->size();
1934        info->data.resize(size);
1935        for (off_type i = 0; i < size; ++i)
1936            data(i)->prepare(info, info->data[i]);
1937    }
1938
1939    bool
1940    check() const
1941    {
1942        return storage != NULL;
1943    }
1944};
1945
1946template <class Stat>
1947class DistProxy
1948{
1949  private:
1950    Stat &stat;
1951    off_type index;
1952
1953  protected:
1954    typename Stat::Storage *data() { return stat.data(index); }
1955    const typename Stat::Storage *data() const { return stat.data(index); }
1956
1957  public:
1958    DistProxy(Stat &s, off_type i)
1959        : stat(s), index(i)
1960    {}
1961
1962    DistProxy(const DistProxy &sp)
1963        : stat(sp.stat), index(sp.index)
1964    {}
1965
1966    const DistProxy &
1967    operator=(const DistProxy &sp)
1968    {
1969        stat = sp.stat;
1970        index = sp.index;
1971        return *this;
1972    }
1973
1974  public:
1975    template <typename U>
1976    void
1977    sample(const U &v, int n = 1)
1978    {
1979        data()->sample(v, n);
1980    }
1981
1982    size_type
1983    size() const
1984    {
1985        return 1;
1986    }
1987
1988    bool
1989    zero() const
1990    {
1991        return data()->zero();
1992    }
1993
1994    /**
1995     * Proxy has no state.  Nothing to reset.
1996     */
1997    void reset() { }
1998};
1999
2000//////////////////////////////////////////////////////////////////////
2001//
2002//  Formula Details
2003//
2004//////////////////////////////////////////////////////////////////////
2005
2006/**
2007 * Base class for formula statistic node. These nodes are used to build a tree
2008 * that represents the formula.
2009 */
2010class Node : public RefCounted
2011{
2012  public:
2013    /**
2014     * Return the number of nodes in the subtree starting at this node.
2015     * @return the number of nodes in this subtree.
2016     */
2017    virtual size_type size() const = 0;
2018    /**
2019     * Return the result vector of this subtree.
2020     * @return The result vector of this subtree.
2021     */
2022    virtual const VResult &result() const = 0;
2023    /**
2024     * Return the total of the result vector.
2025     * @return The total of the result vector.
2026     */
2027    virtual Result total() const = 0;
2028
2029    /**
2030     *
2031     */
2032    virtual std::string str() const = 0;
2033};
2034
2035/** Reference counting pointer to a function Node. */
2036typedef RefCountingPtr<Node> NodePtr;
2037
2038class ScalarStatNode : public Node
2039{
2040  private:
2041    const ScalarInfo *data;
2042    mutable VResult vresult;
2043
2044  public:
2045    ScalarStatNode(const ScalarInfo *d) : data(d), vresult(1) {}
2046
2047    const VResult &
2048    result() const
2049    {
2050        vresult[0] = data->result();
2051        return vresult;
2052    }
2053
2054    Result total() const { return data->result(); };
2055
2056    size_type size() const { return 1; }
2057
2058    /**
2059     *
2060     */
2061    std::string str() const { return data->name; }
2062};
2063
2064template <class Stat>
2065class ScalarProxyNode : public Node
2066{
2067  private:
2068    const ScalarProxy<Stat> proxy;
2069    mutable VResult vresult;
2070
2071  public:
2072    ScalarProxyNode(const ScalarProxy<Stat> &p)
2073        : proxy(p), vresult(1)
2074    { }
2075
2076    const VResult &
2077    result() const
2078    {
2079        vresult[0] = proxy.result();
2080        return vresult;
2081    }
2082
2083    Result
2084    total() const
2085    {
2086        return proxy.result();
2087    }
2088
2089    size_type
2090    size() const
2091    {
2092        return 1;
2093    }
2094
2095    /**
2096     *
2097     */
2098    std::string
2099    str() const
2100    {
2101        return proxy.str();
2102    }
2103};
2104
2105class VectorStatNode : public Node
2106{
2107  private:
2108    const VectorInfo *data;
2109
2110  public:
2111    VectorStatNode(const VectorInfo *d) : data(d) { }
2112    const VResult &result() const { return data->result(); }
2113    Result total() const { return data->total(); };
2114
2115    size_type size() const { return data->size(); }
2116
2117    std::string str() const { return data->name; }
2118};
2119
2120template <class T>
2121class ConstNode : public Node
2122{
2123  private:
2124    VResult vresult;
2125
2126  public:
2127    ConstNode(T s) : vresult(1, (Result)s) {}
2128    const VResult &result() const { return vresult; }
2129    Result total() const { return vresult[0]; };
2130    size_type size() const { return 1; }
2131    std::string str() const { return to_string(vresult[0]); }
2132};
2133
2134template <class T>
2135class ConstVectorNode : public Node
2136{
2137  private:
2138    VResult vresult;
2139
2140  public:
2141    ConstVectorNode(const T &s) : vresult(s.begin(), s.end()) {}
2142    const VResult &result() const { return vresult; }
2143
2144    Result
2145    total() const
2146    {
2147        size_type size = this->size();
2148        Result tmp = 0;
2149        for (off_type i = 0; i < size; i++)
2150            tmp += vresult[i];
2151        return tmp;
2152    }
2153
2154    size_type size() const { return vresult.size(); }
2155    std::string
2156    str() const
2157    {
2158        size_type size = this->size();
2159        std::string tmp = "(";
2160        for (off_type i = 0; i < size; i++)
2161            tmp += csprintf("%s ",to_string(vresult[i]));
2162        tmp += ")";
2163        return tmp;
2164    }
2165};
2166
2167template <class Op>
2168struct OpString;
2169
2170template<>
2171struct OpString<std::plus<Result> >
2172{
2173    static std::string str() { return "+"; }
2174};
2175
2176template<>
2177struct OpString<std::minus<Result> >
2178{
2179    static std::string str() { return "-"; }
2180};
2181
2182template<>
2183struct OpString<std::multiplies<Result> >
2184{
2185    static std::string str() { return "*"; }
2186};
2187
2188template<>
2189struct OpString<std::divides<Result> >
2190{
2191    static std::string str() { return "/"; }
2192};
2193
2194template<>
2195struct OpString<std::modulus<Result> >
2196{
2197    static std::string str() { return "%"; }
2198};
2199
2200template<>
2201struct OpString<std::negate<Result> >
2202{
2203    static std::string str() { return "-"; }
2204};
2205
2206template <class Op>
2207class UnaryNode : public Node
2208{
2209  public:
2210    NodePtr l;
2211    mutable VResult vresult;
2212
2213  public:
2214    UnaryNode(NodePtr &p) : l(p) {}
2215
2216    const VResult &
2217    result() const
2218    {
2219        const VResult &lvec = l->result();
2220        size_type size = lvec.size();
2221
2222        assert(size > 0);
2223
2224        vresult.resize(size);
2225        Op op;
2226        for (off_type i = 0; i < size; ++i)
2227            vresult[i] = op(lvec[i]);
2228
2229        return vresult;
2230    }
2231
2232    Result
2233    total() const
2234    {
2235        const VResult &vec = this->result();
2236        Result total = 0.0;
2237        for (off_type i = 0; i < size(); i++)
2238            total += vec[i];
2239        return total;
2240    }
2241
2242    size_type size() const { return l->size(); }
2243
2244    std::string
2245    str() const
2246    {
2247        return OpString<Op>::str() + l->str();
2248    }
2249};
2250
2251template <class Op>
2252class BinaryNode : public Node
2253{
2254  public:
2255    NodePtr l;
2256    NodePtr r;
2257    mutable VResult vresult;
2258
2259  public:
2260    BinaryNode(NodePtr &a, NodePtr &b) : l(a), r(b) {}
2261
2262    const VResult &
2263    result() const
2264    {
2265        Op op;
2266        const VResult &lvec = l->result();
2267        const VResult &rvec = r->result();
2268
2269        assert(lvec.size() > 0 && rvec.size() > 0);
2270
2271        if (lvec.size() == 1 && rvec.size() == 1) {
2272            vresult.resize(1);
2273            vresult[0] = op(lvec[0], rvec[0]);
2274        } else if (lvec.size() == 1) {
2275            size_type size = rvec.size();
2276            vresult.resize(size);
2277            for (off_type i = 0; i < size; ++i)
2278                vresult[i] = op(lvec[0], rvec[i]);
2279        } else if (rvec.size() == 1) {
2280            size_type size = lvec.size();
2281            vresult.resize(size);
2282            for (off_type i = 0; i < size; ++i)
2283                vresult[i] = op(lvec[i], rvec[0]);
2284        } else if (rvec.size() == lvec.size()) {
2285            size_type size = rvec.size();
2286            vresult.resize(size);
2287            for (off_type i = 0; i < size; ++i)
2288                vresult[i] = op(lvec[i], rvec[i]);
2289        }
2290
2291        return vresult;
2292    }
2293
2294    Result
2295    total() const
2296    {
2297        const VResult &vec = this->result();
2298        const VResult &lvec = l->result();
2299        const VResult &rvec = r->result();
2300        Result total = 0.0;
2301        Result lsum = 0.0;
2302        Result rsum = 0.0;
2303        Op op;
2304
2305        assert(lvec.size() > 0 && rvec.size() > 0);
2306        assert(lvec.size() == rvec.size() ||
2307               lvec.size() == 1 || rvec.size() == 1);
2308
2309        /** If vectors are the same divide their sums (x0+x1)/(y0+y1) */
2310        if (lvec.size() == rvec.size() && lvec.size() > 1) {
2311            for (off_type i = 0; i < size(); ++i) {
2312                lsum += lvec[i];
2313                rsum += rvec[i];
2314            }
2315            return op(lsum, rsum);
2316        }
2317
2318        /** Otherwise divide each item by the divisor */
2319        for (off_type i = 0; i < size(); ++i) {
2320            total += vec[i];
2321        }
2322
2323        return total;
2324    }
2325
2326    size_type
2327    size() const
2328    {
2329        size_type ls = l->size();
2330        size_type rs = r->size();
2331        if (ls == 1) {
2332            return rs;
2333        } else if (rs == 1) {
2334            return ls;
2335        } else {
2336            assert(ls == rs && "Node vector sizes are not equal");
2337            return ls;
2338        }
2339    }
2340
2341    std::string
2342    str() const
2343    {
2344        return csprintf("(%s %s %s)", l->str(), OpString<Op>::str(), r->str());
2345    }
2346};
2347
2348template <class Op>
2349class SumNode : public Node
2350{
2351  public:
2352    NodePtr l;
2353    mutable VResult vresult;
2354
2355  public:
2356    SumNode(NodePtr &p) : l(p), vresult(1) {}
2357
2358    const VResult &
2359    result() const
2360    {
2361        const VResult &lvec = l->result();
2362        size_type size = lvec.size();
2363        assert(size > 0);
2364
2365        vresult[0] = 0.0;
2366
2367        Op op;
2368        for (off_type i = 0; i < size; ++i)
2369            vresult[0] = op(vresult[0], lvec[i]);
2370
2371        return vresult;
2372    }
2373
2374    Result
2375    total() const
2376    {
2377        const VResult &lvec = l->result();
2378        size_type size = lvec.size();
2379        assert(size > 0);
2380
2381        Result result = 0.0;
2382
2383        Op op;
2384        for (off_type i = 0; i < size; ++i)
2385            result = op(result, lvec[i]);
2386
2387        return result;
2388    }
2389
2390    size_type size() const { return 1; }
2391
2392    std::string
2393    str() const
2394    {
2395        return csprintf("total(%s)", l->str());
2396    }
2397};
2398
2399
2400//////////////////////////////////////////////////////////////////////
2401//
2402// Visible Statistics Types
2403//
2404//////////////////////////////////////////////////////////////////////
2405/**
2406 * @defgroup VisibleStats "Statistic Types"
2407 * These are the statistics that are used in the simulator.
2408 * @{
2409 */
2410
2411/**
2412 * This is a simple scalar statistic, like a counter.
2413 * @sa Stat, ScalarBase, StatStor
2414 */
2415class Scalar : public ScalarBase<Scalar, StatStor>
2416{
2417  public:
2418    using ScalarBase<Scalar, StatStor>::operator=;
2419};
2420
2421/**
2422 * A stat that calculates the per tick average of a value.
2423 * @sa Stat, ScalarBase, AvgStor
2424 */
2425class Average : public ScalarBase<Average, AvgStor>
2426{
2427  public:
2428    using ScalarBase<Average, AvgStor>::operator=;
2429};
2430
2431class Value : public ValueBase<Value>
2432{
2433};
2434
2435/**
2436 * A vector of scalar stats.
2437 * @sa Stat, VectorBase, StatStor
2438 */
2439class Vector : public VectorBase<Vector, StatStor>
2440{
2441};
2442
2443/**
2444 * A vector of Average stats.
2445 * @sa Stat, VectorBase, AvgStor
2446 */
2447class AverageVector : public VectorBase<AverageVector, AvgStor>
2448{
2449};
2450
2451/**
2452 * A 2-Dimensional vecto of scalar stats.
2453 * @sa Stat, Vector2dBase, StatStor
2454 */
2455class Vector2d : public Vector2dBase<Vector2d, StatStor>
2456{
2457};
2458
2459/**
2460 * A simple distribution stat.
2461 * @sa Stat, DistBase, DistStor
2462 */
2463class Distribution : public DistBase<Distribution, DistStor>
2464{
2465  public:
2466    /**
2467     * Set the parameters of this distribution. @sa DistStor::Params
2468     * @param min The minimum value of the distribution.
2469     * @param max The maximum value of the distribution.
2470     * @param bkt The number of values in each bucket.
2471     * @return A reference to this distribution.
2472     */
2473    Distribution &
2474    init(Counter min, Counter max, Counter bkt)
2475    {
2476        DistStor::Params *params = new DistStor::Params;
2477        params->min = min;
2478        params->max = max;
2479        params->bucket_size = bkt;
2480        params->buckets = (size_type)ceil((max - min + 1.0) / bkt);
2481        this->setParams(params);
2482        this->doInit();
2483        return this->self();
2484    }
2485};
2486
2487/**
2488 * A simple histogram stat.
2489 * @sa Stat, DistBase, HistStor
2490 */
2491class Histogram : public DistBase<Histogram, HistStor>
2492{
2493  public:
2494    /**
2495     * Set the parameters of this histogram. @sa HistStor::Params
2496     * @param size The number of buckets in the histogram
2497     * @return A reference to this histogram.
2498     */
2499    Histogram &
2500    init(size_type size)
2501    {
2502        HistStor::Params *params = new HistStor::Params;
2503        params->buckets = size;
2504        this->setParams(params);
2505        this->doInit();
2506        return this->self();
2507    }
2508};
2509
2510/**
2511 * Calculates the mean and variance of all the samples.
2512 * @sa DistBase, SampleStor
2513 */
2514class StandardDeviation : public DistBase<StandardDeviation, SampleStor>
2515{
2516  public:
2517    /**
2518     * Construct and initialize this distribution.
2519     */
2520    StandardDeviation()
2521    {
2522        SampleStor::Params *params = new SampleStor::Params;
2523        this->doInit();
2524        this->setParams(params);
2525    }
2526};
2527
2528/**
2529 * Calculates the per tick mean and variance of the samples.
2530 * @sa DistBase, AvgSampleStor
2531 */
2532class AverageDeviation : public DistBase<AverageDeviation, AvgSampleStor>
2533{
2534  public:
2535    /**
2536     * Construct and initialize this distribution.
2537     */
2538    AverageDeviation()
2539    {
2540        AvgSampleStor::Params *params = new AvgSampleStor::Params;
2541        this->doInit();
2542        this->setParams(params);
2543    }
2544};
2545
2546/**
2547 * A vector of distributions.
2548 * @sa VectorDistBase, DistStor
2549 */
2550class VectorDistribution : public VectorDistBase<VectorDistribution, DistStor>
2551{
2552  public:
2553    /**
2554     * Initialize storage and parameters for this distribution.
2555     * @param size The size of the vector (the number of distributions).
2556     * @param min The minimum value of the distribution.
2557     * @param max The maximum value of the distribution.
2558     * @param bkt The number of values in each bucket.
2559     * @return A reference to this distribution.
2560     */
2561    VectorDistribution &
2562    init(size_type size, Counter min, Counter max, Counter bkt)
2563    {
2564        DistStor::Params *params = new DistStor::Params;
2565        params->min = min;
2566        params->max = max;
2567        params->bucket_size = bkt;
2568        params->buckets = (size_type)ceil((max - min + 1.0) / bkt);
2569        this->setParams(params);
2570        this->doInit(size);
2571        return this->self();
2572    }
2573};
2574
2575/**
2576 * This is a vector of StandardDeviation stats.
2577 * @sa VectorDistBase, SampleStor
2578 */
2579class VectorStandardDeviation
2580    : public VectorDistBase<VectorStandardDeviation, SampleStor>
2581{
2582  public:
2583    /**
2584     * Initialize storage for this distribution.
2585     * @param size The size of the vector.
2586     * @return A reference to this distribution.
2587     */
2588    VectorStandardDeviation &
2589    init(size_type size)
2590    {
2591        SampleStor::Params *params = new SampleStor::Params;
2592        this->doInit(size);
2593        this->setParams(params);
2594        return this->self();
2595    }
2596};
2597
2598/**
2599 * This is a vector of AverageDeviation stats.
2600 * @sa VectorDistBase, AvgSampleStor
2601 */
2602class VectorAverageDeviation
2603    : public VectorDistBase<VectorAverageDeviation, AvgSampleStor>
2604{
2605  public:
2606    /**
2607     * Initialize storage for this distribution.
2608     * @param size The size of the vector.
2609     * @return A reference to this distribution.
2610     */
2611    VectorAverageDeviation &
2612    init(size_type size)
2613    {
2614        AvgSampleStor::Params *params = new AvgSampleStor::Params;
2615        this->doInit(size);
2616        this->setParams(params);
2617        return this->self();
2618    }
2619};
2620
2621template <class Stat>
2622class FormulaInfoProxy : public InfoProxy<Stat, FormulaInfo>
2623{
2624  protected:
2625    mutable VResult vec;
2626    mutable VCounter cvec;
2627
2628  public:
2629    FormulaInfoProxy(Stat &stat) : InfoProxy<Stat, FormulaInfo>(stat) {}
2630
2631    size_type size() const { return this->s.size(); }
2632
2633    const VResult &
2634    result() const
2635    {
2636        this->s.result(vec);
2637        return vec;
2638    }
2639    Result total() const { return this->s.total(); }
2640    VCounter &value() const { return cvec; }
2641
2642    std::string str() const { return this->s.str(); }
2643};
2644
2645template <class Stat>
2646class SparseHistInfoProxy : public InfoProxy<Stat, SparseHistInfo>
2647{
2648  public:
2649    SparseHistInfoProxy(Stat &stat) : InfoProxy<Stat, SparseHistInfo>(stat) {}
2650};
2651
2652/**
2653 * Implementation of a sparse histogram stat. The storage class is
2654 * determined by the Storage template.
2655 */
2656template <class Derived, class Stor>
2657class SparseHistBase : public DataWrap<Derived, SparseHistInfoProxy>
2658{
2659  public:
2660    typedef SparseHistInfoProxy<Derived> Info;
2661    typedef Stor Storage;
2662    typedef typename Stor::Params Params;
2663
2664  protected:
2665    /** The storage for this stat. */
2666    char storage[sizeof(Storage)];
2667
2668  protected:
2669    /**
2670     * Retrieve the storage.
2671     * @return The storage object for this stat.
2672     */
2673    Storage *
2674    data()
2675    {
2676        return reinterpret_cast<Storage *>(storage);
2677    }
2678
2679    /**
2680     * Retrieve a const pointer to the storage.
2681     * @return A const pointer to the storage object for this stat.
2682     */
2683    const Storage *
2684    data() const
2685    {
2686        return reinterpret_cast<const Storage *>(storage);
2687    }
2688
2689    void
2690    doInit()
2691    {
2692        new (storage) Storage(this->info());
2693        this->setInit();
2694    }
2695
2696  public:
2697    SparseHistBase() { }
2698
2699    /**
2700     * Add a value to the distribtion n times. Calls sample on the storage
2701     * class.
2702     * @param v The value to add.
2703     * @param n The number of times to add it, defaults to 1.
2704     */
2705    template <typename U>
2706    void sample(const U &v, int n = 1) { data()->sample(v, n); }
2707
2708    /**
2709     * Return the number of entries in this stat.
2710     * @return The number of entries.
2711     */
2712    size_type size() const { return data()->size(); }
2713    /**
2714     * Return true if no samples have been added.
2715     * @return True if there haven't been any samples.
2716     */
2717    bool zero() const { return data()->zero(); }
2718
2719    void
2720    prepare()
2721    {
2722        Info *info = this->info();
2723        data()->prepare(info, info->data);
2724    }
2725
2726    /**
2727     * Reset stat value to default
2728     */
2729    void
2730    reset()
2731    {
2732        data()->reset(this->info());
2733    }
2734};
2735
2736/**
2737 * Templatized storage and interface for a sparse histogram stat.
2738 */
2739class SparseHistStor
2740{
2741  public:
2742    /** The parameters for a sparse histogram stat. */
2743    struct Params : public DistParams
2744    {
2745        Params() : DistParams(Hist) {}
2746    };
2747
2748  private:
2749    /** Counter for number of samples */
2750    Counter samples;
2751    /** Counter for each bucket. */
2752    MCounter cmap;
2753
2754  public:
2755    SparseHistStor(Info *info)
2756    {
2757        reset(info);
2758    }
2759
2760    /**
2761     * Add a value to the distribution for the given number of times.
2762     * @param val The value to add.
2763     * @param number The number of times to add the value.
2764     */
2765    void
2766    sample(Counter val, int number)
2767    {
2768        cmap[val] += number;
2769        samples += number;
2770    }
2771
2772    /**
2773     * Return the number of buckets in this distribution.
2774     * @return the number of buckets.
2775     */
2776    size_type size() const { return cmap.size(); }
2777
2778    /**
2779     * Returns true if any calls to sample have been made.
2780     * @return True if any values have been sampled.
2781     */
2782    bool
2783    zero() const
2784    {
2785        return samples == Counter();
2786    }
2787
2788    void
2789    prepare(Info *info, SparseHistData &data)
2790    {
2791        MCounter::iterator it;
2792        data.cmap.clear();
2793        for (it = cmap.begin(); it != cmap.end(); it++) {
2794            data.cmap[(*it).first] = (*it).second;
2795        }
2796
2797        data.samples = samples;
2798    }
2799
2800    /**
2801     * Reset stat value to default
2802     */
2803    void
2804    reset(Info *info)
2805    {
2806        cmap.clear();
2807        samples = 0;
2808    }
2809};
2810
2811class SparseHistogram : public SparseHistBase<SparseHistogram, SparseHistStor>
2812{
2813  public:
2814    /**
2815     * Set the parameters of this histogram. @sa HistStor::Params
2816     * @param size The number of buckets in the histogram
2817     * @return A reference to this histogram.
2818     */
2819    SparseHistogram &
2820    init(size_type size)
2821    {
2822        SparseHistStor::Params *params = new SparseHistStor::Params;
2823        this->setParams(params);
2824        this->doInit();
2825        return this->self();
2826    }
2827};
2828
2829class Temp;
2830/**
2831 * A formula for statistics that is calculated when printed. A formula is
2832 * stored as a tree of Nodes that represent the equation to calculate.
2833 * @sa Stat, ScalarStat, VectorStat, Node, Temp
2834 */
2835class Formula : public DataWrapVec<Formula, FormulaInfoProxy>
2836{
2837  protected:
2838    /** The root of the tree which represents the Formula */
2839    NodePtr root;
2840    friend class Temp;
2841
2842  public:
2843    /**
2844     * Create and initialize thie formula, and register it with the database.
2845     */
2846    Formula();
2847
2848    /**
2849     * Create a formula with the given root node, register it with the
2850     * database.
2851     * @param r The root of the expression tree.
2852     */
2853    Formula(Temp r);
2854
2855    /**
2856     * Set an unitialized Formula to the given root.
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    /**
2863     * Add the given tree to the existing one.
2864     * @param r The root of the expression tree.
2865     * @return a reference to this formula.
2866     */
2867    const Formula &operator+=(Temp r);
2868
2869    /**
2870     * Divide the existing tree by the given one.
2871     * @param r The root of the expression tree.
2872     * @return a reference to this formula.
2873     */
2874    const Formula &operator/=(Temp r);
2875
2876    /**
2877     * Return the result of the Fomula in a vector.  If there were no Vector
2878     * components to the Formula, then the vector is size 1.  If there were,
2879     * like x/y with x being a vector of size 3, then the result returned will
2880     * be x[0]/y, x[1]/y, x[2]/y, respectively.
2881     * @return The result vector.
2882     */
2883    void result(VResult &vec) const;
2884
2885    /**
2886     * Return the total Formula result.  If there is a Vector
2887     * component to this Formula, then this is the result of the
2888     * Formula if the formula is applied after summing all the
2889     * components of the Vector.  For example, if Formula is x/y where
2890     * x is size 3, then total() will return (x[1]+x[2]+x[3])/y.  If
2891     * there is no Vector component, total() returns the same value as
2892     * the first entry in the VResult val() returns.
2893     * @return The total of the result vector.
2894     */
2895    Result total() const;
2896
2897    /**
2898     * Return the number of elements in the tree.
2899     */
2900    size_type size() const;
2901
2902    void prepare() { }
2903
2904    /**
2905     * Formulas don't need to be reset
2906     */
2907    void reset();
2908
2909    /**
2910     *
2911     */
2912    bool zero() const;
2913
2914    std::string str() const;
2915};
2916
2917class FormulaNode : public Node
2918{
2919  private:
2920    const Formula &formula;
2921    mutable VResult vec;
2922
2923  public:
2924    FormulaNode(const Formula &f) : formula(f) {}
2925
2926    size_type size() const { return formula.size(); }
2927    const VResult &result() const { formula.result(vec); return vec; }
2928    Result total() const { return formula.total(); }
2929
2930    std::string str() const { return formula.str(); }
2931};
2932
2933/**
2934 * Helper class to construct formula node trees.
2935 */
2936class Temp
2937{
2938  protected:
2939    /**
2940     * Pointer to a Node object.
2941     */
2942    NodePtr node;
2943
2944  public:
2945    /**
2946     * Copy the given pointer to this class.
2947     * @param n A pointer to a Node object to copy.
2948     */
2949    Temp(NodePtr n) : node(n) { }
2950
2951    /**
2952     * Return the node pointer.
2953     * @return the node pointer.
2954     */
2955    operator NodePtr&() { return node; }
2956
2957  public:
2958    /**
2959     * Create a new ScalarStatNode.
2960     * @param s The ScalarStat to place in a node.
2961     */
2962    Temp(const Scalar &s)
2963        : node(new ScalarStatNode(s.info()))
2964    { }
2965
2966    /**
2967     * Create a new ScalarStatNode.
2968     * @param s The ScalarStat to place in a node.
2969     */
2970    Temp(const Value &s)
2971        : node(new ScalarStatNode(s.info()))
2972    { }
2973
2974    /**
2975     * Create a new ScalarStatNode.
2976     * @param s The ScalarStat to place in a node.
2977     */
2978    Temp(const Average &s)
2979        : node(new ScalarStatNode(s.info()))
2980    { }
2981
2982    /**
2983     * Create a new VectorStatNode.
2984     * @param s The VectorStat to place in a node.
2985     */
2986    Temp(const Vector &s)
2987        : node(new VectorStatNode(s.info()))
2988    { }
2989
2990    Temp(const AverageVector &s)
2991        : node(new VectorStatNode(s.info()))
2992    { }
2993
2994    /**
2995     *
2996     */
2997    Temp(const Formula &f)
2998        : node(new FormulaNode(f))
2999    { }
3000
3001    /**
3002     * Create a new ScalarProxyNode.
3003     * @param p The ScalarProxy to place in a node.
3004     */
3005    template <class Stat>
3006    Temp(const ScalarProxy<Stat> &p)
3007        : node(new ScalarProxyNode<Stat>(p))
3008    { }
3009
3010    /**
3011     * Create a ConstNode
3012     * @param value The value of the const node.
3013     */
3014    Temp(signed char value)
3015        : node(new ConstNode<signed char>(value))
3016    { }
3017
3018    /**
3019     * Create a ConstNode
3020     * @param value The value of the const node.
3021     */
3022    Temp(unsigned char value)
3023        : node(new ConstNode<unsigned char>(value))
3024    { }
3025
3026    /**
3027     * Create a ConstNode
3028     * @param value The value of the const node.
3029     */
3030    Temp(signed short value)
3031        : node(new ConstNode<signed short>(value))
3032    { }
3033
3034    /**
3035     * Create a ConstNode
3036     * @param value The value of the const node.
3037     */
3038    Temp(unsigned short value)
3039        : node(new ConstNode<unsigned short>(value))
3040    { }
3041
3042    /**
3043     * Create a ConstNode
3044     * @param value The value of the const node.
3045     */
3046    Temp(signed int value)
3047        : node(new ConstNode<signed int>(value))
3048    { }
3049
3050    /**
3051     * Create a ConstNode
3052     * @param value The value of the const node.
3053     */
3054    Temp(unsigned int value)
3055        : node(new ConstNode<unsigned int>(value))
3056    { }
3057
3058    /**
3059     * Create a ConstNode
3060     * @param value The value of the const node.
3061     */
3062    Temp(signed long value)
3063        : node(new ConstNode<signed long>(value))
3064    { }
3065
3066    /**
3067     * Create a ConstNode
3068     * @param value The value of the const node.
3069     */
3070    Temp(unsigned long value)
3071        : node(new ConstNode<unsigned long>(value))
3072    { }
3073
3074    /**
3075     * Create a ConstNode
3076     * @param value The value of the const node.
3077     */
3078    Temp(signed long long value)
3079        : node(new ConstNode<signed long long>(value))
3080    { }
3081
3082    /**
3083     * Create a ConstNode
3084     * @param value The value of the const node.
3085     */
3086    Temp(unsigned long long value)
3087        : node(new ConstNode<unsigned long long>(value))
3088    { }
3089
3090    /**
3091     * Create a ConstNode
3092     * @param value The value of the const node.
3093     */
3094    Temp(float value)
3095        : node(new ConstNode<float>(value))
3096    { }
3097
3098    /**
3099     * Create a ConstNode
3100     * @param value The value of the const node.
3101     */
3102    Temp(double value)
3103        : node(new ConstNode<double>(value))
3104    { }
3105};
3106
3107
3108/**
3109 * @}
3110 */
3111
3112inline Temp
3113operator+(Temp l, Temp r)
3114{
3115    return NodePtr(new BinaryNode<std::plus<Result> >(l, r));
3116}
3117
3118inline Temp
3119operator-(Temp l, Temp r)
3120{
3121    return NodePtr(new BinaryNode<std::minus<Result> >(l, r));
3122}
3123
3124inline Temp
3125operator*(Temp l, Temp r)
3126{
3127    return NodePtr(new BinaryNode<std::multiplies<Result> >(l, r));
3128}
3129
3130inline Temp
3131operator/(Temp l, Temp r)
3132{
3133    return NodePtr(new BinaryNode<std::divides<Result> >(l, r));
3134}
3135
3136inline Temp
3137operator-(Temp l)
3138{
3139    return NodePtr(new UnaryNode<std::negate<Result> >(l));
3140}
3141
3142template <typename T>
3143inline Temp
3144constant(T val)
3145{
3146    return NodePtr(new ConstNode<T>(val));
3147}
3148
3149template <typename T>
3150inline Temp
3151constantVector(T val)
3152{
3153    return NodePtr(new ConstVectorNode<T>(val));
3154}
3155
3156inline Temp
3157sum(Temp val)
3158{
3159    return NodePtr(new SumNode<std::plus<Result> >(val));
3160}
3161
3162/** Dump all statistics data to the registered outputs */
3163void dump();
3164void reset();
3165void enable();
3166bool enabled();
3167
3168/**
3169 * Register a callback that should be called whenever statistics are
3170 * reset
3171 */
3172void registerResetCallback(Callback *cb);
3173
3174/**
3175 * Register a callback that should be called whenever statistics are
3176 * about to be dumped
3177 */
3178void registerDumpCallback(Callback *cb);
3179
3180std::list<Info *> &statsList();
3181
3182typedef std::map<const void *, Info *> MapType;
3183MapType &statsMap();
3184
3185typedef std::map<std::string, Info *> NameMapType;
3186NameMapType &nameMap();
3187
3188bool validateStatName(const std::string &name);
3189
3190} // namespace Stats
3191
3192void debugDumpStats();
3193
3194#endif // __BASE_STATISTICS_HH__
3195