IO: Fix bug in DMA Device where receiving a snoop on DMA port would cause a panic.
[gem5.git] / src / base / statistics.hh
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
73 class Callback;
74
75 /** The current simulated tick. */
76 extern Tick curTick();
77
78 /* A namespace for all of the Statistics */
79 namespace Stats {
80
81 template <class Stat, class Base>
82 class 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
101 template <class Stat>
102 class 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
112 template <class Stat>
113 class 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
141 template <class Stat>
142 class DistInfoProxy : public InfoProxy<Stat, DistInfo>
143 {
144 public:
145 DistInfoProxy(Stat &stat) : InfoProxy<Stat, DistInfo>(stat) {}
146 };
147
148 template <class Stat>
149 class 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
157 template <class Stat>
158 class Vector2dInfoProxy : public InfoProxy<Stat, Vector2dInfo>
159 {
160 public:
161 Vector2dInfoProxy(Stat &stat) : InfoProxy<Stat, Vector2dInfo>(stat) {}
162 };
163
164 struct StorageParams
165 {
166 virtual ~StorageParams();
167 };
168
169 class 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
204 template <class Derived, template <class> class InfoProxyType>
205 class 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
328 template <class Derived, template <class> class InfoProxyType>
329 class 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
404 template <class Derived, template <class> class InfoProxyType>
405 class 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 */
455 class 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 */
520 class 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 */
617 template <class Derived, class Stor>
618 class 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
732 class 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
745 template <class T>
746 class 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
758 template <class T>
759 class 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
771 template <class Derived>
772 class 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 */
821 template <class Stat>
822 class 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 */
947 template <class Derived, class Stor>
948 class 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
1090 template <class Stat>
1091 class 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
1166 template <class Derived, class Stor>
1167 class Vector2dBase : public DataWrapVec2d<Derived, Vector2dInfoProxy>
1168 {
1169 public:
1170 typedef Vector2dInfoProxy<Derived> Info;
1171 typedef Stor Storage;
1172 typedef typename Stor::Params Params;
1173 typedef VectorProxy<Derived> Proxy;
1174 friend class ScalarProxy<Derived>;
1175 friend class VectorProxy<Derived>;
1176 friend class DataWrapVec<Derived, Vector2dInfoProxy>;
1177 friend class DataWrapVec2d<Derived, Vector2dInfoProxy>;
1178
1179 protected:
1180 size_type x;
1181 size_type y;
1182 size_type _size;
1183 Storage *storage;
1184
1185 protected:
1186 Storage *data(off_type index) { return &storage[index]; }
1187 const Storage *data(off_type index) const { return &storage[index]; }
1188
1189 public:
1190 Vector2dBase()
1191 : storage(NULL)
1192 {}
1193
1194 ~Vector2dBase()
1195 {
1196 if (!storage)
1197 return;
1198
1199 for (off_type i = 0; i < _size; ++i)
1200 data(i)->~Storage();
1201 delete [] reinterpret_cast<char *>(storage);
1202 }
1203
1204 Derived &
1205 init(size_type _x, size_type _y)
1206 {
1207 assert(_x > 0 && _y > 0 && "sizes must be positive!");
1208 assert(!storage && "already initialized");
1209
1210 Derived &self = this->self();
1211 Info *info = this->info();
1212
1213 x = _x;
1214 y = _y;
1215 info->x = _x;
1216 info->y = _y;
1217 _size = x * y;
1218
1219 char *ptr = new char[_size * sizeof(Storage)];
1220 storage = reinterpret_cast<Storage *>(ptr);
1221
1222 for (off_type i = 0; i < _size; ++i)
1223 new (&storage[i]) Storage(info);
1224
1225 this->setInit();
1226
1227 return self;
1228 }
1229
1230 Proxy
1231 operator[](off_type index)
1232 {
1233 off_type offset = index * y;
1234 assert (index >= 0 && offset + index < size());
1235 return Proxy(this->self(), offset, y);
1236 }
1237
1238
1239 size_type
1240 size() const
1241 {
1242 return _size;
1243 }
1244
1245 bool
1246 zero() const
1247 {
1248 return data(0)->zero();
1249 #if 0
1250 for (off_type i = 0; i < size(); ++i)
1251 if (!data(i)->zero())
1252 return false;
1253 return true;
1254 #endif
1255 }
1256
1257 void
1258 prepare()
1259 {
1260 Info *info = this->info();
1261 size_type size = this->size();
1262
1263 for (off_type i = 0; i < size; ++i)
1264 data(i)->prepare(info);
1265
1266 info->cvec.resize(size);
1267 for (off_type i = 0; i < size; ++i)
1268 info->cvec[i] = data(i)->value();
1269 }
1270
1271 /**
1272 * Reset stat value to default
1273 */
1274 void
1275 reset()
1276 {
1277 Info *info = this->info();
1278 size_type size = this->size();
1279 for (off_type i = 0; i < size; ++i)
1280 data(i)->reset(info);
1281 }
1282
1283 bool
1284 check() const
1285 {
1286 return storage != NULL;
1287 }
1288 };
1289
1290 //////////////////////////////////////////////////////////////////////
1291 //
1292 // Non formula statistics
1293 //
1294 //////////////////////////////////////////////////////////////////////
1295 /** The parameters for a distribution stat. */
1296 struct 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 */
1305 class DistStor
1306 {
1307 public:
1308 /** The parameters for a distribution stat. */
1309 struct Params : public DistParams
1310 {
1311 /** The minimum value to track. */
1312 Counter min;
1313 /** The maximum value to track. */
1314 Counter max;
1315 /** The number of entries in each bucket. */
1316 Counter bucket_size;
1317 /** The number of buckets. Equal to (max-min)/bucket_size. */
1318 size_type buckets;
1319
1320 Params() : DistParams(Dist) {}
1321 };
1322
1323 private:
1324 /** The minimum value to track. */
1325 Counter min_track;
1326 /** The maximum value to track. */
1327 Counter max_track;
1328 /** The number of entries in each bucket. */
1329 Counter bucket_size;
1330 /** The number of buckets. Equal to (max-min)/bucket_size. */
1331 size_type buckets;
1332
1333 /** The smallest value sampled. */
1334 Counter min_val;
1335 /** The largest value sampled. */
1336 Counter max_val;
1337 /** The number of values sampled less than min. */
1338 Counter underflow;
1339 /** The number of values sampled more than max. */
1340 Counter overflow;
1341 /** The current sum. */
1342 Counter sum;
1343 /** The sum of squares. */
1344 Counter squares;
1345 /** The number of samples. */
1346 Counter samples;
1347 /** Counter for each bucket. */
1348 VCounter cvec;
1349
1350 public:
1351 DistStor(Info *info)
1352 : cvec(safe_cast<const Params *>(info->storageParams)->buckets)
1353 {
1354 reset(info);
1355 }
1356
1357 /**
1358 * Add a value to the distribution for the given number of times.
1359 * @param val The value to add.
1360 * @param number The number of times to add the value.
1361 */
1362 void
1363 sample(Counter val, int number)
1364 {
1365 if (val < min_track)
1366 underflow += number;
1367 else if (val > max_track)
1368 overflow += number;
1369 else {
1370 size_type index =
1371 (size_type)std::floor((val - min_track) / bucket_size);
1372 assert(index < size());
1373 cvec[index] += number;
1374 }
1375
1376 if (val < min_val)
1377 min_val = val;
1378
1379 if (val > max_val)
1380 max_val = val;
1381
1382 sum += val * number;
1383 squares += val * val * number;
1384 samples += number;
1385 }
1386
1387 /**
1388 * Return the number of buckets in this distribution.
1389 * @return the number of buckets.
1390 */
1391 size_type size() const { return cvec.size(); }
1392
1393 /**
1394 * Returns true if any calls to sample have been made.
1395 * @return True if any values have been sampled.
1396 */
1397 bool
1398 zero() const
1399 {
1400 return samples == Counter();
1401 }
1402
1403 void
1404 prepare(Info *info, DistData &data)
1405 {
1406 const Params *params = safe_cast<const Params *>(info->storageParams);
1407
1408 assert(params->type == Dist);
1409 data.type = params->type;
1410 data.min = params->min;
1411 data.max = params->max;
1412 data.bucket_size = params->bucket_size;
1413
1414 data.min_val = (min_val == CounterLimits::max()) ? 0 : min_val;
1415 data.max_val = (max_val == CounterLimits::min()) ? 0 : max_val;
1416 data.underflow = underflow;
1417 data.overflow = overflow;
1418
1419 size_type buckets = params->buckets;
1420 data.cvec.resize(buckets);
1421 for (off_type i = 0; i < buckets; ++i)
1422 data.cvec[i] = cvec[i];
1423
1424 data.sum = sum;
1425 data.squares = squares;
1426 data.samples = samples;
1427 }
1428
1429 /**
1430 * Reset stat value to default
1431 */
1432 void
1433 reset(Info *info)
1434 {
1435 const Params *params = safe_cast<const Params *>(info->storageParams);
1436 min_track = params->min;
1437 max_track = params->max;
1438 bucket_size = params->bucket_size;
1439
1440 min_val = CounterLimits::max();
1441 max_val = CounterLimits::min();
1442 underflow = Counter();
1443 overflow = Counter();
1444
1445 size_type size = cvec.size();
1446 for (off_type i = 0; i < size; ++i)
1447 cvec[i] = Counter();
1448
1449 sum = Counter();
1450 squares = Counter();
1451 samples = Counter();
1452 }
1453 };
1454
1455 /**
1456 * Templatized storage and interface for a histogram stat.
1457 */
1458 class HistStor
1459 {
1460 public:
1461 /** The parameters for a distribution stat. */
1462 struct Params : public DistParams
1463 {
1464 /** The number of buckets.. */
1465 size_type buckets;
1466
1467 Params() : DistParams(Hist) {}
1468 };
1469
1470 private:
1471 /** The minimum value to track. */
1472 Counter min_bucket;
1473 /** The maximum value to track. */
1474 Counter max_bucket;
1475 /** The number of entries in each bucket. */
1476 Counter bucket_size;
1477
1478 /** The current sum. */
1479 Counter sum;
1480 /** The sum of squares. */
1481 Counter squares;
1482 /** The number of samples. */
1483 Counter samples;
1484 /** Counter for each bucket. */
1485 VCounter cvec;
1486
1487 public:
1488 HistStor(Info *info)
1489 : cvec(safe_cast<const Params *>(info->storageParams)->buckets)
1490 {
1491 reset(info);
1492 }
1493
1494 void grow_up();
1495 void grow_out();
1496 void grow_convert();
1497
1498 /**
1499 * Add a value to the distribution for the given number of times.
1500 * @param val The value to add.
1501 * @param number The number of times to add the value.
1502 */
1503 void
1504 sample(Counter val, int number)
1505 {
1506 assert(min_bucket < max_bucket);
1507 if (val < min_bucket) {
1508 if (min_bucket == 0)
1509 grow_convert();
1510
1511 while (val < min_bucket)
1512 grow_out();
1513 } else if (val >= max_bucket + bucket_size) {
1514 if (min_bucket == 0) {
1515 while (val >= max_bucket + bucket_size)
1516 grow_up();
1517 } else {
1518 while (val >= max_bucket + bucket_size)
1519 grow_out();
1520 }
1521 }
1522
1523 size_type index =
1524 (int64_t)std::floor((val - min_bucket) / bucket_size);
1525
1526 assert(index >= 0 && index < size());
1527 cvec[index] += number;
1528
1529 sum += val * number;
1530 squares += val * val * number;
1531 samples += number;
1532 }
1533
1534 /**
1535 * Return the number of buckets in this distribution.
1536 * @return the number of buckets.
1537 */
1538 size_type size() const { return cvec.size(); }
1539
1540 /**
1541 * Returns true if any calls to sample have been made.
1542 * @return True if any values have been sampled.
1543 */
1544 bool
1545 zero() const
1546 {
1547 return samples == Counter();
1548 }
1549
1550 void
1551 prepare(Info *info, DistData &data)
1552 {
1553 const Params *params = safe_cast<const Params *>(info->storageParams);
1554
1555 assert(params->type == Hist);
1556 data.type = params->type;
1557 data.min = min_bucket;
1558 data.max = max_bucket + bucket_size - 1;
1559 data.bucket_size = bucket_size;
1560
1561 data.min_val = min_bucket;
1562 data.max_val = max_bucket;
1563
1564 int buckets = params->buckets;
1565 data.cvec.resize(buckets);
1566 for (off_type i = 0; i < buckets; ++i)
1567 data.cvec[i] = cvec[i];
1568
1569 data.sum = sum;
1570 data.squares = squares;
1571 data.samples = samples;
1572 }
1573
1574 /**
1575 * Reset stat value to default
1576 */
1577 void
1578 reset(Info *info)
1579 {
1580 const Params *params = safe_cast<const Params *>(info->storageParams);
1581 min_bucket = 0;
1582 max_bucket = params->buckets - 1;
1583 bucket_size = 1;
1584
1585 size_type size = cvec.size();
1586 for (off_type i = 0; i < size; ++i)
1587 cvec[i] = Counter();
1588
1589 sum = Counter();
1590 squares = Counter();
1591 samples = Counter();
1592 }
1593 };
1594
1595 /**
1596 * Templatized storage and interface for a distribution that calculates mean
1597 * and variance.
1598 */
1599 class SampleStor
1600 {
1601 public:
1602 struct Params : public DistParams
1603 {
1604 Params() : DistParams(Deviation) {}
1605 };
1606
1607 private:
1608 /** The current sum. */
1609 Counter sum;
1610 /** The sum of squares. */
1611 Counter squares;
1612 /** The number of samples. */
1613 Counter samples;
1614
1615 public:
1616 /**
1617 * Create and initialize this storage.
1618 */
1619 SampleStor(Info *info)
1620 : sum(Counter()), squares(Counter()), samples(Counter())
1621 { }
1622
1623 /**
1624 * Add a value the given number of times to this running average.
1625 * Update the running sum and sum of squares, increment the number of
1626 * values seen by the given number.
1627 * @param val The value to add.
1628 * @param number The number of times to add the value.
1629 */
1630 void
1631 sample(Counter val, int number)
1632 {
1633 Counter value = val * number;
1634 sum += value;
1635 squares += value * value;
1636 samples += number;
1637 }
1638
1639 /**
1640 * Return the number of entries in this stat, 1
1641 * @return 1.
1642 */
1643 size_type size() const { return 1; }
1644
1645 /**
1646 * Return true if no samples have been added.
1647 * @return True if no samples have been added.
1648 */
1649 bool zero() const { return samples == Counter(); }
1650
1651 void
1652 prepare(Info *info, DistData &data)
1653 {
1654 const Params *params = safe_cast<const Params *>(info->storageParams);
1655
1656 assert(params->type == Deviation);
1657 data.type = params->type;
1658 data.sum = sum;
1659 data.squares = squares;
1660 data.samples = samples;
1661 }
1662
1663 /**
1664 * Reset stat value to default
1665 */
1666 void
1667 reset(Info *info)
1668 {
1669 sum = Counter();
1670 squares = Counter();
1671 samples = Counter();
1672 }
1673 };
1674
1675 /**
1676 * Templatized storage for distribution that calculates per tick mean and
1677 * variance.
1678 */
1679 class AvgSampleStor
1680 {
1681 public:
1682 struct Params : public DistParams
1683 {
1684 Params() : DistParams(Deviation) {}
1685 };
1686
1687 private:
1688 /** Current total. */
1689 Counter sum;
1690 /** Current sum of squares. */
1691 Counter squares;
1692
1693 public:
1694 /**
1695 * Create and initialize this storage.
1696 */
1697 AvgSampleStor(Info *info)
1698 : sum(Counter()), squares(Counter())
1699 {}
1700
1701 /**
1702 * Add a value to the distribution for the given number of times.
1703 * Update the running sum and sum of squares.
1704 * @param val The value to add.
1705 * @param number The number of times to add the value.
1706 */
1707 void
1708 sample(Counter val, int number)
1709 {
1710 Counter value = val * number;
1711 sum += value;
1712 squares += value * value;
1713 }
1714
1715 /**
1716 * Return the number of entries, in this case 1.
1717 * @return 1.
1718 */
1719 size_type size() const { return 1; }
1720
1721 /**
1722 * Return true if no samples have been added.
1723 * @return True if the sum is zero.
1724 */
1725 bool zero() const { return sum == Counter(); }
1726
1727 void
1728 prepare(Info *info, DistData &data)
1729 {
1730 const Params *params = safe_cast<const Params *>(info->storageParams);
1731
1732 assert(params->type == Deviation);
1733 data.type = params->type;
1734 data.sum = sum;
1735 data.squares = squares;
1736 data.samples = curTick();
1737 }
1738
1739 /**
1740 * Reset stat value to default
1741 */
1742 void
1743 reset(Info *info)
1744 {
1745 sum = Counter();
1746 squares = Counter();
1747 }
1748 };
1749
1750 /**
1751 * Implementation of a distribution stat. The type of distribution is
1752 * determined by the Storage template. @sa ScalarBase
1753 */
1754 template <class Derived, class Stor>
1755 class DistBase : public DataWrap<Derived, DistInfoProxy>
1756 {
1757 public:
1758 typedef DistInfoProxy<Derived> Info;
1759 typedef Stor Storage;
1760 typedef typename Stor::Params Params;
1761
1762 protected:
1763 /** The storage for this stat. */
1764 char storage[sizeof(Storage)] __attribute__ ((aligned (8)));
1765
1766 protected:
1767 /**
1768 * Retrieve the storage.
1769 * @return The storage object for this stat.
1770 */
1771 Storage *
1772 data()
1773 {
1774 return reinterpret_cast<Storage *>(storage);
1775 }
1776
1777 /**
1778 * Retrieve a const pointer to the storage.
1779 * @return A const pointer to the storage object for this stat.
1780 */
1781 const Storage *
1782 data() const
1783 {
1784 return reinterpret_cast<const Storage *>(storage);
1785 }
1786
1787 void
1788 doInit()
1789 {
1790 new (storage) Storage(this->info());
1791 this->setInit();
1792 }
1793
1794 public:
1795 DistBase() { }
1796
1797 /**
1798 * Add a value to the distribtion n times. Calls sample on the storage
1799 * class.
1800 * @param v The value to add.
1801 * @param n The number of times to add it, defaults to 1.
1802 */
1803 template <typename U>
1804 void sample(const U &v, int n = 1) { data()->sample(v, n); }
1805
1806 /**
1807 * Return the number of entries in this stat.
1808 * @return The number of entries.
1809 */
1810 size_type size() const { return data()->size(); }
1811 /**
1812 * Return true if no samples have been added.
1813 * @return True if there haven't been any samples.
1814 */
1815 bool zero() const { return data()->zero(); }
1816
1817 void
1818 prepare()
1819 {
1820 Info *info = this->info();
1821 data()->prepare(info, info->data);
1822 }
1823
1824 /**
1825 * Reset stat value to default
1826 */
1827 void
1828 reset()
1829 {
1830 data()->reset(this->info());
1831 }
1832 };
1833
1834 template <class Stat>
1835 class DistProxy;
1836
1837 template <class Derived, class Stor>
1838 class VectorDistBase : public DataWrapVec<Derived, VectorDistInfoProxy>
1839 {
1840 public:
1841 typedef VectorDistInfoProxy<Derived> Info;
1842 typedef Stor Storage;
1843 typedef typename Stor::Params Params;
1844 typedef DistProxy<Derived> Proxy;
1845 friend class DistProxy<Derived>;
1846 friend class DataWrapVec<Derived, VectorDistInfoProxy>;
1847
1848 protected:
1849 Storage *storage;
1850 size_type _size;
1851
1852 protected:
1853 Storage *
1854 data(off_type index)
1855 {
1856 return &storage[index];
1857 }
1858
1859 const Storage *
1860 data(off_type index) const
1861 {
1862 return &storage[index];
1863 }
1864
1865 void
1866 doInit(size_type s)
1867 {
1868 assert(s > 0 && "size must be positive!");
1869 assert(!storage && "already initialized");
1870 _size = s;
1871
1872 char *ptr = new char[_size * sizeof(Storage)];
1873 storage = reinterpret_cast<Storage *>(ptr);
1874
1875 Info *info = this->info();
1876 for (off_type i = 0; i < _size; ++i)
1877 new (&storage[i]) Storage(info);
1878
1879 this->setInit();
1880 }
1881
1882 public:
1883 VectorDistBase()
1884 : storage(NULL)
1885 {}
1886
1887 ~VectorDistBase()
1888 {
1889 if (!storage)
1890 return ;
1891
1892 for (off_type i = 0; i < _size; ++i)
1893 data(i)->~Storage();
1894 delete [] reinterpret_cast<char *>(storage);
1895 }
1896
1897 Proxy operator[](off_type index)
1898 {
1899 assert(index >= 0 && index < size());
1900 return Proxy(this->self(), index);
1901 }
1902
1903 size_type
1904 size() const
1905 {
1906 return _size;
1907 }
1908
1909 bool
1910 zero() const
1911 {
1912 for (off_type i = 0; i < size(); ++i)
1913 if (!data(i)->zero())
1914 return false;
1915 return true;
1916 }
1917
1918 void
1919 prepare()
1920 {
1921 Info *info = this->info();
1922 size_type size = this->size();
1923 info->data.resize(size);
1924 for (off_type i = 0; i < size; ++i)
1925 data(i)->prepare(info, info->data[i]);
1926 }
1927
1928 bool
1929 check() const
1930 {
1931 return storage != NULL;
1932 }
1933 };
1934
1935 template <class Stat>
1936 class DistProxy
1937 {
1938 private:
1939 Stat &stat;
1940 off_type index;
1941
1942 protected:
1943 typename Stat::Storage *data() { return stat.data(index); }
1944 const typename Stat::Storage *data() const { return stat.data(index); }
1945
1946 public:
1947 DistProxy(Stat &s, off_type i)
1948 : stat(s), index(i)
1949 {}
1950
1951 DistProxy(const DistProxy &sp)
1952 : stat(sp.stat), index(sp.index)
1953 {}
1954
1955 const DistProxy &
1956 operator=(const DistProxy &sp)
1957 {
1958 stat = sp.stat;
1959 index = sp.index;
1960 return *this;
1961 }
1962
1963 public:
1964 template <typename U>
1965 void
1966 sample(const U &v, int n = 1)
1967 {
1968 data()->sample(v, n);
1969 }
1970
1971 size_type
1972 size() const
1973 {
1974 return 1;
1975 }
1976
1977 bool
1978 zero() const
1979 {
1980 return data()->zero();
1981 }
1982
1983 /**
1984 * Proxy has no state. Nothing to reset.
1985 */
1986 void reset() { }
1987 };
1988
1989 //////////////////////////////////////////////////////////////////////
1990 //
1991 // Formula Details
1992 //
1993 //////////////////////////////////////////////////////////////////////
1994
1995 /**
1996 * Base class for formula statistic node. These nodes are used to build a tree
1997 * that represents the formula.
1998 */
1999 class Node : public RefCounted
2000 {
2001 public:
2002 /**
2003 * Return the number of nodes in the subtree starting at this node.
2004 * @return the number of nodes in this subtree.
2005 */
2006 virtual size_type size() const = 0;
2007 /**
2008 * Return the result vector of this subtree.
2009 * @return The result vector of this subtree.
2010 */
2011 virtual const VResult &result() const = 0;
2012 /**
2013 * Return the total of the result vector.
2014 * @return The total of the result vector.
2015 */
2016 virtual Result total() const = 0;
2017
2018 /**
2019 *
2020 */
2021 virtual std::string str() const = 0;
2022 };
2023
2024 /** Reference counting pointer to a function Node. */
2025 typedef RefCountingPtr<Node> NodePtr;
2026
2027 class ScalarStatNode : public Node
2028 {
2029 private:
2030 const ScalarInfo *data;
2031 mutable VResult vresult;
2032
2033 public:
2034 ScalarStatNode(const ScalarInfo *d) : data(d), vresult(1) {}
2035
2036 const VResult &
2037 result() const
2038 {
2039 vresult[0] = data->result();
2040 return vresult;
2041 }
2042
2043 Result total() const { return data->result(); };
2044
2045 size_type size() const { return 1; }
2046
2047 /**
2048 *
2049 */
2050 std::string str() const { return data->name; }
2051 };
2052
2053 template <class Stat>
2054 class ScalarProxyNode : public Node
2055 {
2056 private:
2057 const ScalarProxy<Stat> proxy;
2058 mutable VResult vresult;
2059
2060 public:
2061 ScalarProxyNode(const ScalarProxy<Stat> &p)
2062 : proxy(p), vresult(1)
2063 { }
2064
2065 const VResult &
2066 result() const
2067 {
2068 vresult[0] = proxy.result();
2069 return vresult;
2070 }
2071
2072 Result
2073 total() const
2074 {
2075 return proxy.result();
2076 }
2077
2078 size_type
2079 size() const
2080 {
2081 return 1;
2082 }
2083
2084 /**
2085 *
2086 */
2087 std::string
2088 str() const
2089 {
2090 return proxy.str();
2091 }
2092 };
2093
2094 class VectorStatNode : public Node
2095 {
2096 private:
2097 const VectorInfo *data;
2098
2099 public:
2100 VectorStatNode(const VectorInfo *d) : data(d) { }
2101 const VResult &result() const { return data->result(); }
2102 Result total() const { return data->total(); };
2103
2104 size_type size() const { return data->size(); }
2105
2106 std::string str() const { return data->name; }
2107 };
2108
2109 template <class T>
2110 class ConstNode : public Node
2111 {
2112 private:
2113 VResult vresult;
2114
2115 public:
2116 ConstNode(T s) : vresult(1, (Result)s) {}
2117 const VResult &result() const { return vresult; }
2118 Result total() const { return vresult[0]; };
2119 size_type size() const { return 1; }
2120 std::string str() const { return to_string(vresult[0]); }
2121 };
2122
2123 template <class T>
2124 class ConstVectorNode : public Node
2125 {
2126 private:
2127 VResult vresult;
2128
2129 public:
2130 ConstVectorNode(const T &s) : vresult(s.begin(), s.end()) {}
2131 const VResult &result() const { return vresult; }
2132
2133 Result
2134 total() const
2135 {
2136 size_type size = this->size();
2137 Result tmp = 0;
2138 for (off_type i = 0; i < size; i++)
2139 tmp += vresult[i];
2140 return tmp;
2141 }
2142
2143 size_type size() const { return vresult.size(); }
2144 std::string
2145 str() const
2146 {
2147 size_type size = this->size();
2148 std::string tmp = "(";
2149 for (off_type i = 0; i < size; i++)
2150 tmp += csprintf("%s ",to_string(vresult[i]));
2151 tmp += ")";
2152 return tmp;
2153 }
2154 };
2155
2156 template <class Op>
2157 struct OpString;
2158
2159 template<>
2160 struct OpString<std::plus<Result> >
2161 {
2162 static std::string str() { return "+"; }
2163 };
2164
2165 template<>
2166 struct OpString<std::minus<Result> >
2167 {
2168 static std::string str() { return "-"; }
2169 };
2170
2171 template<>
2172 struct OpString<std::multiplies<Result> >
2173 {
2174 static std::string str() { return "*"; }
2175 };
2176
2177 template<>
2178 struct OpString<std::divides<Result> >
2179 {
2180 static std::string str() { return "/"; }
2181 };
2182
2183 template<>
2184 struct OpString<std::modulus<Result> >
2185 {
2186 static std::string str() { return "%"; }
2187 };
2188
2189 template<>
2190 struct OpString<std::negate<Result> >
2191 {
2192 static std::string str() { return "-"; }
2193 };
2194
2195 template <class Op>
2196 class UnaryNode : public Node
2197 {
2198 public:
2199 NodePtr l;
2200 mutable VResult vresult;
2201
2202 public:
2203 UnaryNode(NodePtr &p) : l(p) {}
2204
2205 const VResult &
2206 result() const
2207 {
2208 const VResult &lvec = l->result();
2209 size_type size = lvec.size();
2210
2211 assert(size > 0);
2212
2213 vresult.resize(size);
2214 Op op;
2215 for (off_type i = 0; i < size; ++i)
2216 vresult[i] = op(lvec[i]);
2217
2218 return vresult;
2219 }
2220
2221 Result
2222 total() const
2223 {
2224 const VResult &vec = this->result();
2225 Result total = 0.0;
2226 for (off_type i = 0; i < size(); i++)
2227 total += vec[i];
2228 return total;
2229 }
2230
2231 size_type size() const { return l->size(); }
2232
2233 std::string
2234 str() const
2235 {
2236 return OpString<Op>::str() + l->str();
2237 }
2238 };
2239
2240 template <class Op>
2241 class BinaryNode : public Node
2242 {
2243 public:
2244 NodePtr l;
2245 NodePtr r;
2246 mutable VResult vresult;
2247
2248 public:
2249 BinaryNode(NodePtr &a, NodePtr &b) : l(a), r(b) {}
2250
2251 const VResult &
2252 result() const
2253 {
2254 Op op;
2255 const VResult &lvec = l->result();
2256 const VResult &rvec = r->result();
2257
2258 assert(lvec.size() > 0 && rvec.size() > 0);
2259
2260 if (lvec.size() == 1 && rvec.size() == 1) {
2261 vresult.resize(1);
2262 vresult[0] = op(lvec[0], rvec[0]);
2263 } else if (lvec.size() == 1) {
2264 size_type size = rvec.size();
2265 vresult.resize(size);
2266 for (off_type i = 0; i < size; ++i)
2267 vresult[i] = op(lvec[0], rvec[i]);
2268 } else if (rvec.size() == 1) {
2269 size_type size = lvec.size();
2270 vresult.resize(size);
2271 for (off_type i = 0; i < size; ++i)
2272 vresult[i] = op(lvec[i], rvec[0]);
2273 } else if (rvec.size() == lvec.size()) {
2274 size_type size = rvec.size();
2275 vresult.resize(size);
2276 for (off_type i = 0; i < size; ++i)
2277 vresult[i] = op(lvec[i], rvec[i]);
2278 }
2279
2280 return vresult;
2281 }
2282
2283 Result
2284 total() const
2285 {
2286 const VResult &vec = this->result();
2287 Result total = 0.0;
2288 for (off_type i = 0; i < size(); i++)
2289 total += vec[i];
2290 return total;
2291 }
2292
2293 size_type
2294 size() const
2295 {
2296 size_type ls = l->size();
2297 size_type rs = r->size();
2298 if (ls == 1) {
2299 return rs;
2300 } else if (rs == 1) {
2301 return ls;
2302 } else {
2303 assert(ls == rs && "Node vector sizes are not equal");
2304 return ls;
2305 }
2306 }
2307
2308 std::string
2309 str() const
2310 {
2311 return csprintf("(%s %s %s)", l->str(), OpString<Op>::str(), r->str());
2312 }
2313 };
2314
2315 template <class Op>
2316 class SumNode : public Node
2317 {
2318 public:
2319 NodePtr l;
2320 mutable VResult vresult;
2321
2322 public:
2323 SumNode(NodePtr &p) : l(p), vresult(1) {}
2324
2325 const VResult &
2326 result() const
2327 {
2328 const VResult &lvec = l->result();
2329 size_type size = lvec.size();
2330 assert(size > 0);
2331
2332 vresult[0] = 0.0;
2333
2334 Op op;
2335 for (off_type i = 0; i < size; ++i)
2336 vresult[0] = op(vresult[0], lvec[i]);
2337
2338 return vresult;
2339 }
2340
2341 Result
2342 total() const
2343 {
2344 const VResult &lvec = l->result();
2345 size_type size = lvec.size();
2346 assert(size > 0);
2347
2348 Result vresult = 0.0;
2349
2350 Op op;
2351 for (off_type i = 0; i < size; ++i)
2352 vresult = op(vresult, lvec[i]);
2353
2354 return vresult;
2355 }
2356
2357 size_type size() const { return 1; }
2358
2359 std::string
2360 str() const
2361 {
2362 return csprintf("total(%s)", l->str());
2363 }
2364 };
2365
2366
2367 //////////////////////////////////////////////////////////////////////
2368 //
2369 // Visible Statistics Types
2370 //
2371 //////////////////////////////////////////////////////////////////////
2372 /**
2373 * @defgroup VisibleStats "Statistic Types"
2374 * These are the statistics that are used in the simulator.
2375 * @{
2376 */
2377
2378 /**
2379 * This is a simple scalar statistic, like a counter.
2380 * @sa Stat, ScalarBase, StatStor
2381 */
2382 class Scalar : public ScalarBase<Scalar, StatStor>
2383 {
2384 public:
2385 using ScalarBase<Scalar, StatStor>::operator=;
2386 };
2387
2388 /**
2389 * A stat that calculates the per tick average of a value.
2390 * @sa Stat, ScalarBase, AvgStor
2391 */
2392 class Average : public ScalarBase<Average, AvgStor>
2393 {
2394 public:
2395 using ScalarBase<Average, AvgStor>::operator=;
2396 };
2397
2398 class Value : public ValueBase<Value>
2399 {
2400 };
2401
2402 /**
2403 * A vector of scalar stats.
2404 * @sa Stat, VectorBase, StatStor
2405 */
2406 class Vector : public VectorBase<Vector, StatStor>
2407 {
2408 };
2409
2410 /**
2411 * A vector of Average stats.
2412 * @sa Stat, VectorBase, AvgStor
2413 */
2414 class AverageVector : public VectorBase<AverageVector, AvgStor>
2415 {
2416 };
2417
2418 /**
2419 * A 2-Dimensional vecto of scalar stats.
2420 * @sa Stat, Vector2dBase, StatStor
2421 */
2422 class Vector2d : public Vector2dBase<Vector2d, StatStor>
2423 {
2424 };
2425
2426 /**
2427 * A simple distribution stat.
2428 * @sa Stat, DistBase, DistStor
2429 */
2430 class Distribution : public DistBase<Distribution, DistStor>
2431 {
2432 public:
2433 /**
2434 * Set the parameters of this distribution. @sa DistStor::Params
2435 * @param min The minimum value of the distribution.
2436 * @param max The maximum value of the distribution.
2437 * @param bkt The number of values in each bucket.
2438 * @return A reference to this distribution.
2439 */
2440 Distribution &
2441 init(Counter min, Counter max, Counter bkt)
2442 {
2443 DistStor::Params *params = new DistStor::Params;
2444 params->min = min;
2445 params->max = max;
2446 params->bucket_size = bkt;
2447 params->buckets = (size_type)ceil((max - min + 1.0) / bkt);
2448 this->setParams(params);
2449 this->doInit();
2450 return this->self();
2451 }
2452 };
2453
2454 /**
2455 * A simple histogram stat.
2456 * @sa Stat, DistBase, HistStor
2457 */
2458 class Histogram : public DistBase<Histogram, HistStor>
2459 {
2460 public:
2461 /**
2462 * Set the parameters of this histogram. @sa HistStor::Params
2463 * @param size The number of buckets in the histogram
2464 * @return A reference to this histogram.
2465 */
2466 Histogram &
2467 init(size_type size)
2468 {
2469 HistStor::Params *params = new HistStor::Params;
2470 params->buckets = size;
2471 this->setParams(params);
2472 this->doInit();
2473 return this->self();
2474 }
2475 };
2476
2477 /**
2478 * Calculates the mean and variance of all the samples.
2479 * @sa DistBase, SampleStor
2480 */
2481 class StandardDeviation : public DistBase<StandardDeviation, SampleStor>
2482 {
2483 public:
2484 /**
2485 * Construct and initialize this distribution.
2486 */
2487 StandardDeviation()
2488 {
2489 SampleStor::Params *params = new SampleStor::Params;
2490 this->doInit();
2491 this->setParams(params);
2492 }
2493 };
2494
2495 /**
2496 * Calculates the per tick mean and variance of the samples.
2497 * @sa DistBase, AvgSampleStor
2498 */
2499 class AverageDeviation : public DistBase<AverageDeviation, AvgSampleStor>
2500 {
2501 public:
2502 /**
2503 * Construct and initialize this distribution.
2504 */
2505 AverageDeviation()
2506 {
2507 AvgSampleStor::Params *params = new AvgSampleStor::Params;
2508 this->doInit();
2509 this->setParams(params);
2510 }
2511 };
2512
2513 /**
2514 * A vector of distributions.
2515 * @sa VectorDistBase, DistStor
2516 */
2517 class VectorDistribution : public VectorDistBase<VectorDistribution, DistStor>
2518 {
2519 public:
2520 /**
2521 * Initialize storage and parameters for this distribution.
2522 * @param size The size of the vector (the number of distributions).
2523 * @param min The minimum value of the distribution.
2524 * @param max The maximum value of the distribution.
2525 * @param bkt The number of values in each bucket.
2526 * @return A reference to this distribution.
2527 */
2528 VectorDistribution &
2529 init(size_type size, Counter min, Counter max, Counter bkt)
2530 {
2531 DistStor::Params *params = new DistStor::Params;
2532 params->min = min;
2533 params->max = max;
2534 params->bucket_size = bkt;
2535 params->buckets = (size_type)ceil((max - min + 1.0) / bkt);
2536 this->setParams(params);
2537 this->doInit(size);
2538 return this->self();
2539 }
2540 };
2541
2542 /**
2543 * This is a vector of StandardDeviation stats.
2544 * @sa VectorDistBase, SampleStor
2545 */
2546 class VectorStandardDeviation
2547 : public VectorDistBase<VectorStandardDeviation, SampleStor>
2548 {
2549 public:
2550 /**
2551 * Initialize storage for this distribution.
2552 * @param size The size of the vector.
2553 * @return A reference to this distribution.
2554 */
2555 VectorStandardDeviation &
2556 init(size_type size)
2557 {
2558 SampleStor::Params *params = new SampleStor::Params;
2559 this->doInit(size);
2560 this->setParams(params);
2561 return this->self();
2562 }
2563 };
2564
2565 /**
2566 * This is a vector of AverageDeviation stats.
2567 * @sa VectorDistBase, AvgSampleStor
2568 */
2569 class VectorAverageDeviation
2570 : public VectorDistBase<VectorAverageDeviation, AvgSampleStor>
2571 {
2572 public:
2573 /**
2574 * Initialize storage for this distribution.
2575 * @param size The size of the vector.
2576 * @return A reference to this distribution.
2577 */
2578 VectorAverageDeviation &
2579 init(size_type size)
2580 {
2581 AvgSampleStor::Params *params = new AvgSampleStor::Params;
2582 this->doInit(size);
2583 this->setParams(params);
2584 return this->self();
2585 }
2586 };
2587
2588 template <class Stat>
2589 class FormulaInfoProxy : public InfoProxy<Stat, FormulaInfo>
2590 {
2591 protected:
2592 mutable VResult vec;
2593 mutable VCounter cvec;
2594
2595 public:
2596 FormulaInfoProxy(Stat &stat) : InfoProxy<Stat, FormulaInfo>(stat) {}
2597
2598 size_type size() const { return this->s.size(); }
2599
2600 const VResult &
2601 result() const
2602 {
2603 this->s.result(vec);
2604 return vec;
2605 }
2606 Result total() const { return this->s.total(); }
2607 VCounter &value() const { return cvec; }
2608
2609 std::string str() const { return this->s.str(); }
2610 };
2611
2612 template <class Stat>
2613 class SparseHistInfoProxy : public InfoProxy<Stat, SparseHistInfo>
2614 {
2615 public:
2616 SparseHistInfoProxy(Stat &stat) : InfoProxy<Stat, SparseHistInfo>(stat) {}
2617 };
2618
2619 /**
2620 * Implementation of a sparse histogram stat. The storage class is
2621 * determined by the Storage template.
2622 */
2623 template <class Derived, class Stor>
2624 class SparseHistBase : public DataWrap<Derived, SparseHistInfoProxy>
2625 {
2626 public:
2627 typedef SparseHistInfoProxy<Derived> Info;
2628 typedef Stor Storage;
2629 typedef typename Stor::Params Params;
2630
2631 protected:
2632 /** The storage for this stat. */
2633 char storage[sizeof(Storage)];
2634
2635 protected:
2636 /**
2637 * Retrieve the storage.
2638 * @return The storage object for this stat.
2639 */
2640 Storage *
2641 data()
2642 {
2643 return reinterpret_cast<Storage *>(storage);
2644 }
2645
2646 /**
2647 * Retrieve a const pointer to the storage.
2648 * @return A const pointer to the storage object for this stat.
2649 */
2650 const Storage *
2651 data() const
2652 {
2653 return reinterpret_cast<const Storage *>(storage);
2654 }
2655
2656 void
2657 doInit()
2658 {
2659 new (storage) Storage(this->info());
2660 this->setInit();
2661 }
2662
2663 public:
2664 SparseHistBase() { }
2665
2666 /**
2667 * Add a value to the distribtion n times. Calls sample on the storage
2668 * class.
2669 * @param v The value to add.
2670 * @param n The number of times to add it, defaults to 1.
2671 */
2672 template <typename U>
2673 void sample(const U &v, int n = 1) { data()->sample(v, n); }
2674
2675 /**
2676 * Return the number of entries in this stat.
2677 * @return The number of entries.
2678 */
2679 size_type size() const { return data()->size(); }
2680 /**
2681 * Return true if no samples have been added.
2682 * @return True if there haven't been any samples.
2683 */
2684 bool zero() const { return data()->zero(); }
2685
2686 void
2687 prepare()
2688 {
2689 Info *info = this->info();
2690 data()->prepare(info, info->data);
2691 }
2692
2693 /**
2694 * Reset stat value to default
2695 */
2696 void
2697 reset()
2698 {
2699 data()->reset(this->info());
2700 }
2701 };
2702
2703 /**
2704 * Templatized storage and interface for a sparse histogram stat.
2705 */
2706 class SparseHistStor
2707 {
2708 public:
2709 /** The parameters for a sparse histogram stat. */
2710 struct Params : public DistParams
2711 {
2712 Params() : DistParams(Hist) {}
2713 };
2714
2715 private:
2716 /** Counter for number of samples */
2717 Counter samples;
2718 /** Counter for each bucket. */
2719 MCounter cmap;
2720
2721 public:
2722 SparseHistStor(Info *info)
2723 {
2724 reset(info);
2725 }
2726
2727 /**
2728 * Add a value to the distribution for the given number of times.
2729 * @param val The value to add.
2730 * @param number The number of times to add the value.
2731 */
2732 void
2733 sample(Counter val, int number)
2734 {
2735 cmap[val] += number;
2736 samples += number;
2737 }
2738
2739 /**
2740 * Return the number of buckets in this distribution.
2741 * @return the number of buckets.
2742 */
2743 size_type size() const { return cmap.size(); }
2744
2745 /**
2746 * Returns true if any calls to sample have been made.
2747 * @return True if any values have been sampled.
2748 */
2749 bool
2750 zero() const
2751 {
2752 return samples == Counter();
2753 }
2754
2755 void
2756 prepare(Info *info, SparseHistData &data)
2757 {
2758 MCounter::iterator it;
2759 data.cmap.clear();
2760 for (it = cmap.begin(); it != cmap.end(); it++) {
2761 data.cmap[(*it).first] = (*it).second;
2762 }
2763
2764 data.samples = samples;
2765 }
2766
2767 /**
2768 * Reset stat value to default
2769 */
2770 void
2771 reset(Info *info)
2772 {
2773 cmap.clear();
2774 samples = 0;
2775 }
2776 };
2777
2778 class SparseHistogram : public SparseHistBase<SparseHistogram, SparseHistStor>
2779 {
2780 public:
2781 /**
2782 * Set the parameters of this histogram. @sa HistStor::Params
2783 * @param size The number of buckets in the histogram
2784 * @return A reference to this histogram.
2785 */
2786 SparseHistogram &
2787 init(size_type size)
2788 {
2789 SparseHistStor::Params *params = new SparseHistStor::Params;
2790 this->setParams(params);
2791 this->doInit();
2792 return this->self();
2793 }
2794 };
2795
2796 class Temp;
2797 /**
2798 * A formula for statistics that is calculated when printed. A formula is
2799 * stored as a tree of Nodes that represent the equation to calculate.
2800 * @sa Stat, ScalarStat, VectorStat, Node, Temp
2801 */
2802 class Formula : public DataWrapVec<Formula, FormulaInfoProxy>
2803 {
2804 protected:
2805 /** The root of the tree which represents the Formula */
2806 NodePtr root;
2807 friend class Temp;
2808
2809 public:
2810 /**
2811 * Create and initialize thie formula, and register it with the database.
2812 */
2813 Formula();
2814
2815 /**
2816 * Create a formula with the given root node, register it with the
2817 * database.
2818 * @param r The root of the expression tree.
2819 */
2820 Formula(Temp r);
2821
2822 /**
2823 * Set an unitialized Formula to the given root.
2824 * @param r The root of the expression tree.
2825 * @return a reference to this formula.
2826 */
2827 const Formula &operator=(Temp r);
2828
2829 /**
2830 * Add the given tree to the existing one.
2831 * @param r The root of the expression tree.
2832 * @return a reference to this formula.
2833 */
2834 const Formula &operator+=(Temp r);
2835 /**
2836 * Return the result of the Fomula in a vector. If there were no Vector
2837 * components to the Formula, then the vector is size 1. If there were,
2838 * like x/y with x being a vector of size 3, then the result returned will
2839 * be x[0]/y, x[1]/y, x[2]/y, respectively.
2840 * @return The result vector.
2841 */
2842 void result(VResult &vec) const;
2843
2844 /**
2845 * Return the total Formula result. If there is a Vector
2846 * component to this Formula, then this is the result of the
2847 * Formula if the formula is applied after summing all the
2848 * components of the Vector. For example, if Formula is x/y where
2849 * x is size 3, then total() will return (x[1]+x[2]+x[3])/y. If
2850 * there is no Vector component, total() returns the same value as
2851 * the first entry in the VResult val() returns.
2852 * @return The total of the result vector.
2853 */
2854 Result total() const;
2855
2856 /**
2857 * Return the number of elements in the tree.
2858 */
2859 size_type size() const;
2860
2861 void prepare() { }
2862
2863 /**
2864 * Formulas don't need to be reset
2865 */
2866 void reset();
2867
2868 /**
2869 *
2870 */
2871 bool zero() const;
2872
2873 std::string str() const;
2874 };
2875
2876 class FormulaNode : public Node
2877 {
2878 private:
2879 const Formula &formula;
2880 mutable VResult vec;
2881
2882 public:
2883 FormulaNode(const Formula &f) : formula(f) {}
2884
2885 size_type size() const { return formula.size(); }
2886 const VResult &result() const { formula.result(vec); return vec; }
2887 Result total() const { return formula.total(); }
2888
2889 std::string str() const { return formula.str(); }
2890 };
2891
2892 /**
2893 * Helper class to construct formula node trees.
2894 */
2895 class Temp
2896 {
2897 protected:
2898 /**
2899 * Pointer to a Node object.
2900 */
2901 NodePtr node;
2902
2903 public:
2904 /**
2905 * Copy the given pointer to this class.
2906 * @param n A pointer to a Node object to copy.
2907 */
2908 Temp(NodePtr n) : node(n) { }
2909
2910 /**
2911 * Return the node pointer.
2912 * @return the node pointer.
2913 */
2914 operator NodePtr&() { return node; }
2915
2916 public:
2917 /**
2918 * Create a new ScalarStatNode.
2919 * @param s The ScalarStat to place in a node.
2920 */
2921 Temp(const Scalar &s)
2922 : node(new ScalarStatNode(s.info()))
2923 { }
2924
2925 /**
2926 * Create a new ScalarStatNode.
2927 * @param s The ScalarStat to place in a node.
2928 */
2929 Temp(const Value &s)
2930 : node(new ScalarStatNode(s.info()))
2931 { }
2932
2933 /**
2934 * Create a new ScalarStatNode.
2935 * @param s The ScalarStat to place in a node.
2936 */
2937 Temp(const Average &s)
2938 : node(new ScalarStatNode(s.info()))
2939 { }
2940
2941 /**
2942 * Create a new VectorStatNode.
2943 * @param s The VectorStat to place in a node.
2944 */
2945 Temp(const Vector &s)
2946 : node(new VectorStatNode(s.info()))
2947 { }
2948
2949 Temp(const AverageVector &s)
2950 : node(new VectorStatNode(s.info()))
2951 { }
2952
2953 /**
2954 *
2955 */
2956 Temp(const Formula &f)
2957 : node(new FormulaNode(f))
2958 { }
2959
2960 /**
2961 * Create a new ScalarProxyNode.
2962 * @param p The ScalarProxy to place in a node.
2963 */
2964 template <class Stat>
2965 Temp(const ScalarProxy<Stat> &p)
2966 : node(new ScalarProxyNode<Stat>(p))
2967 { }
2968
2969 /**
2970 * Create a ConstNode
2971 * @param value The value of the const node.
2972 */
2973 Temp(signed char value)
2974 : node(new ConstNode<signed char>(value))
2975 { }
2976
2977 /**
2978 * Create a ConstNode
2979 * @param value The value of the const node.
2980 */
2981 Temp(unsigned char value)
2982 : node(new ConstNode<unsigned char>(value))
2983 { }
2984
2985 /**
2986 * Create a ConstNode
2987 * @param value The value of the const node.
2988 */
2989 Temp(signed short value)
2990 : node(new ConstNode<signed short>(value))
2991 { }
2992
2993 /**
2994 * Create a ConstNode
2995 * @param value The value of the const node.
2996 */
2997 Temp(unsigned short value)
2998 : node(new ConstNode<unsigned short>(value))
2999 { }
3000
3001 /**
3002 * Create a ConstNode
3003 * @param value The value of the const node.
3004 */
3005 Temp(signed int value)
3006 : node(new ConstNode<signed int>(value))
3007 { }
3008
3009 /**
3010 * Create a ConstNode
3011 * @param value The value of the const node.
3012 */
3013 Temp(unsigned int value)
3014 : node(new ConstNode<unsigned int>(value))
3015 { }
3016
3017 /**
3018 * Create a ConstNode
3019 * @param value The value of the const node.
3020 */
3021 Temp(signed long value)
3022 : node(new ConstNode<signed long>(value))
3023 { }
3024
3025 /**
3026 * Create a ConstNode
3027 * @param value The value of the const node.
3028 */
3029 Temp(unsigned long value)
3030 : node(new ConstNode<unsigned long>(value))
3031 { }
3032
3033 /**
3034 * Create a ConstNode
3035 * @param value The value of the const node.
3036 */
3037 Temp(signed long long value)
3038 : node(new ConstNode<signed long long>(value))
3039 { }
3040
3041 /**
3042 * Create a ConstNode
3043 * @param value The value of the const node.
3044 */
3045 Temp(unsigned long long value)
3046 : node(new ConstNode<unsigned long long>(value))
3047 { }
3048
3049 /**
3050 * Create a ConstNode
3051 * @param value The value of the const node.
3052 */
3053 Temp(float value)
3054 : node(new ConstNode<float>(value))
3055 { }
3056
3057 /**
3058 * Create a ConstNode
3059 * @param value The value of the const node.
3060 */
3061 Temp(double value)
3062 : node(new ConstNode<double>(value))
3063 { }
3064 };
3065
3066
3067 /**
3068 * @}
3069 */
3070
3071 inline Temp
3072 operator+(Temp l, Temp r)
3073 {
3074 return NodePtr(new BinaryNode<std::plus<Result> >(l, r));
3075 }
3076
3077 inline Temp
3078 operator-(Temp l, Temp r)
3079 {
3080 return NodePtr(new BinaryNode<std::minus<Result> >(l, r));
3081 }
3082
3083 inline Temp
3084 operator*(Temp l, Temp r)
3085 {
3086 return NodePtr(new BinaryNode<std::multiplies<Result> >(l, r));
3087 }
3088
3089 inline Temp
3090 operator/(Temp l, Temp r)
3091 {
3092 return NodePtr(new BinaryNode<std::divides<Result> >(l, r));
3093 }
3094
3095 inline Temp
3096 operator-(Temp l)
3097 {
3098 return NodePtr(new UnaryNode<std::negate<Result> >(l));
3099 }
3100
3101 template <typename T>
3102 inline Temp
3103 constant(T val)
3104 {
3105 return NodePtr(new ConstNode<T>(val));
3106 }
3107
3108 template <typename T>
3109 inline Temp
3110 constantVector(T val)
3111 {
3112 return NodePtr(new ConstVectorNode<T>(val));
3113 }
3114
3115 inline Temp
3116 sum(Temp val)
3117 {
3118 return NodePtr(new SumNode<std::plus<Result> >(val));
3119 }
3120
3121 /** Dump all statistics data to the registered outputs */
3122 void dump();
3123 void reset();
3124
3125 /**
3126 * Register a callback that should be called whenever statistics are
3127 * reset
3128 */
3129 void registerResetCallback(Callback *cb);
3130
3131 std::list<Info *> &statsList();
3132
3133 } // namespace Stats
3134
3135 #endif // __BASE_STATISTICS_HH__