statistics.hh revision 9863:9483739f83ee
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 // The following functions are specific to vectors. If you use them 341 // in a non vector context, you will get a nice compiler error! 342 343 /** 344 * Set the subfield name for the given index, and marks this stat to print 345 * at the end of simulation. 346 * @param index The subfield index. 347 * @param name The new name of the subfield. 348 * @return A reference to this stat. 349 */ 350 Derived & 351 subname(off_type index, const std::string &name) 352 { 353 Derived &self = this->self(); 354 Info *info = self.info(); 355 356 std::vector<std::string> &subn = info->subnames; 357 if (subn.size() <= index) 358 subn.resize(index + 1); 359 subn[index] = name; 360 return self; 361 } 362 363 // The following functions are specific to 2d vectors. If you use 364 // them in a non vector context, you will get a nice compiler 365 // error because info doesn't have the right variables. 366 367 /** 368 * Set the subfield description for the given index and marks this stat to 369 * print at the end of simulation. 370 * @param index The subfield index. 371 * @param desc The new description of the subfield 372 * @return A reference to this stat. 373 */ 374 Derived & 375 subdesc(off_type index, const std::string &desc) 376 { 377 Info *info = this->info(); 378 379 std::vector<std::string> &subd = info->subdescs; 380 if (subd.size() <= index) 381 subd.resize(index + 1); 382 subd[index] = desc; 383 384 return this->self(); 385 } 386 387 void 388 prepare() 389 { 390 Derived &self = this->self(); 391 Info *info = this->info(); 392 393 size_t size = self.size(); 394 for (off_type i = 0; i < size; ++i) 395 self.data(i)->prepare(info); 396 } 397 398 void 399 reset() 400 { 401 Derived &self = this->self(); 402 Info *info = this->info(); 403 404 size_t size = self.size(); 405 for (off_type i = 0; i < size; ++i) 406 self.data(i)->reset(info); 407 } 408}; 409 410template <class Derived, template <class> class InfoProxyType> 411class DataWrapVec2d : public DataWrapVec<Derived, InfoProxyType> 412{ 413 public: 414 typedef InfoProxyType<Derived> Info; 415 416 /** 417 * @warning This makes the assumption that if you're gonna subnames a 2d 418 * vector, you're subnaming across all y 419 */ 420 Derived & 421 ysubnames(const char **names) 422 { 423 Derived &self = this->self(); 424 Info *info = this->info(); 425 426 info->y_subnames.resize(self.y); 427 for (off_type i = 0; i < self.y; ++i) 428 info->y_subnames[i] = names[i]; 429 return self; 430 } 431 432 Derived & 433 ysubname(off_type index, const std::string &subname) 434 { 435 Derived &self = this->self(); 436 Info *info = this->info(); 437 438 assert(index < self.y); 439 info->y_subnames.resize(self.y); 440 info->y_subnames[index] = subname.c_str(); 441 return self; 442 } 443 444 std::string 445 ysubname(off_type i) const 446 { 447 return this->info()->y_subnames[i]; 448 } 449 450}; 451 452////////////////////////////////////////////////////////////////////// 453// 454// Simple Statistics 455// 456////////////////////////////////////////////////////////////////////// 457 458/** 459 * Templatized storage and interface for a simple scalar stat. 460 */ 461class StatStor 462{ 463 private: 464 /** The statistic value. */ 465 Counter data; 466 467 public: 468 struct Params : public StorageParams {}; 469 470 public: 471 /** 472 * Builds this storage element and calls the base constructor of the 473 * datatype. 474 */ 475 StatStor(Info *info) 476 : data(Counter()) 477 { } 478 479 /** 480 * The the stat to the given value. 481 * @param val The new value. 482 */ 483 void set(Counter val) { data = val; } 484 /** 485 * Increment the stat by the given value. 486 * @param val The new value. 487 */ 488 void inc(Counter val) { data += val; } 489 /** 490 * Decrement the stat by the given value. 491 * @param val The new value. 492 */ 493 void dec(Counter val) { data -= val; } 494 /** 495 * Return the value of this stat as its base type. 496 * @return The value of this stat. 497 */ 498 Counter value() const { return data; } 499 /** 500 * Return the value of this stat as a result type. 501 * @return The value of this stat. 502 */ 503 Result result() const { return (Result)data; } 504 /** 505 * Prepare stat data for dumping or serialization 506 */ 507 void prepare(Info *info) { } 508 /** 509 * Reset stat value to default 510 */ 511 void reset(Info *info) { data = Counter(); } 512 513 /** 514 * @return true if zero value 515 */ 516 bool zero() const { return data == Counter(); } 517}; 518 519/** 520 * Templatized storage and interface to a per-tick average stat. This keeps 521 * a current count and updates a total (count * ticks) when this count 522 * changes. This allows the quick calculation of a per tick count of the item 523 * being watched. This is good for keeping track of residencies in structures 524 * among other things. 525 */ 526class AvgStor 527{ 528 private: 529 /** The current count. */ 530 Counter current; 531 /** The tick of the last reset */ 532 Tick lastReset; 533 /** The total count for all tick. */ 534 mutable Result total; 535 /** The tick that current last changed. */ 536 mutable Tick last; 537 538 public: 539 struct Params : public StorageParams {}; 540 541 public: 542 /** 543 * Build and initializes this stat storage. 544 */ 545 AvgStor(Info *info) 546 : current(0), lastReset(0), total(0), last(0) 547 { } 548 549 /** 550 * Set the current count to the one provided, update the total and last 551 * set values. 552 * @param val The new count. 553 */ 554 void 555 set(Counter val) 556 { 557 total += current * (curTick() - last); 558 last = curTick(); 559 current = val; 560 } 561 562 /** 563 * Increment the current count by the provided value, calls set. 564 * @param val The amount to increment. 565 */ 566 void inc(Counter val) { set(current + val); } 567 568 /** 569 * Deccrement the current count by the provided value, calls set. 570 * @param val The amount to decrement. 571 */ 572 void dec(Counter val) { set(current - val); } 573 574 /** 575 * Return the current count. 576 * @return The current count. 577 */ 578 Counter value() const { return current; } 579 580 /** 581 * Return the current average. 582 * @return The current average. 583 */ 584 Result 585 result() const 586 { 587 assert(last == curTick()); 588 return (Result)(total + current) / (Result)(curTick() - lastReset + 1); 589 } 590 591 /** 592 * @return true if zero value 593 */ 594 bool zero() const { return total == 0.0; } 595 596 /** 597 * Prepare stat data for dumping or serialization 598 */ 599 void 600 prepare(Info *info) 601 { 602 total += current * (curTick() - last); 603 last = curTick(); 604 } 605 606 /** 607 * Reset stat value to default 608 */ 609 void 610 reset(Info *info) 611 { 612 total = 0.0; 613 last = curTick(); 614 lastReset = curTick(); 615 } 616 617}; 618 619/** 620 * Implementation of a scalar stat. The type of stat is determined by the 621 * Storage template. 622 */ 623template <class Derived, class Stor> 624class ScalarBase : public DataWrap<Derived, ScalarInfoProxy> 625{ 626 public: 627 typedef Stor Storage; 628 typedef typename Stor::Params Params; 629 630 protected: 631 /** The storage of this stat. */ 632 char storage[sizeof(Storage)] __attribute__ ((aligned (8))); 633 634 protected: 635 /** 636 * Retrieve the storage. 637 * @param index The vector index to access. 638 * @return The storage object at the given index. 639 */ 640 Storage * 641 data() 642 { 643 return reinterpret_cast<Storage *>(storage); 644 } 645 646 /** 647 * Retrieve a const pointer to the storage. 648 * for the given index. 649 * @param index The vector index to access. 650 * @return A const pointer to the storage object at the given index. 651 */ 652 const Storage * 653 data() const 654 { 655 return reinterpret_cast<const Storage *>(storage); 656 } 657 658 void 659 doInit() 660 { 661 new (storage) Storage(this->info()); 662 this->setInit(); 663 } 664 665 public: 666 /** 667 * Return the current value of this stat as its base type. 668 * @return The current value. 669 */ 670 Counter value() const { return data()->value(); } 671 672 public: 673 ScalarBase() 674 { 675 this->doInit(); 676 } 677 678 public: 679 // Common operators for stats 680 /** 681 * Increment the stat by 1. This calls the associated storage object inc 682 * function. 683 */ 684 void operator++() { data()->inc(1); } 685 /** 686 * Decrement the stat by 1. This calls the associated storage object dec 687 * function. 688 */ 689 void operator--() { data()->dec(1); } 690 691 /** Increment the stat by 1. */ 692 void operator++(int) { ++*this; } 693 /** Decrement the stat by 1. */ 694 void operator--(int) { --*this; } 695 696 /** 697 * Set the data value to the given value. This calls the associated storage 698 * object set function. 699 * @param v The new value. 700 */ 701 template <typename U> 702 void operator=(const U &v) { data()->set(v); } 703 704 /** 705 * Increment the stat by the given value. This calls the associated 706 * storage object inc function. 707 * @param v The value to add. 708 */ 709 template <typename U> 710 void operator+=(const U &v) { data()->inc(v); } 711 712 /** 713 * Decrement the stat by the given value. This calls the associated 714 * storage object dec function. 715 * @param v The value to substract. 716 */ 717 template <typename U> 718 void operator-=(const U &v) { data()->dec(v); } 719 720 /** 721 * Return the number of elements, always 1 for a scalar. 722 * @return 1. 723 */ 724 size_type size() const { return 1; } 725 726 Counter value() { return data()->value(); } 727 728 Result result() { return data()->result(); } 729 730 Result total() { return result(); } 731 732 bool zero() { return result() == 0.0; } 733 734 void reset() { data()->reset(this->info()); } 735 void prepare() { data()->prepare(this->info()); } 736}; 737 738class ProxyInfo : public ScalarInfo 739{ 740 public: 741 std::string str() const { return to_string(value()); } 742 size_type size() const { return 1; } 743 bool check() const { return true; } 744 void prepare() { } 745 void reset() { } 746 bool zero() const { return value() == 0; } 747 748 void visit(Output &visitor) { visitor.visit(*this); } 749}; 750 751template <class T> 752class ValueProxy : public ProxyInfo 753{ 754 private: 755 T *scalar; 756 757 public: 758 ValueProxy(T &val) : scalar(&val) {} 759 Counter value() const { return *scalar; } 760 Result result() const { return *scalar; } 761 Result total() const { return *scalar; } 762}; 763 764template <class T> 765class FunctorProxy : public ProxyInfo 766{ 767 private: 768 T *functor; 769 770 public: 771 FunctorProxy(T &func) : functor(&func) {} 772 Counter value() const { return (*functor)(); } 773 Result result() const { return (*functor)(); } 774 Result total() const { return (*functor)(); } 775}; 776 777template <class Derived> 778class ValueBase : public DataWrap<Derived, ScalarInfoProxy> 779{ 780 private: 781 ProxyInfo *proxy; 782 783 public: 784 ValueBase() : proxy(NULL) { } 785 ~ValueBase() { if (proxy) delete proxy; } 786 787 template <class T> 788 Derived & 789 scalar(T &value) 790 { 791 proxy = new ValueProxy<T>(value); 792 this->setInit(); 793 return this->self(); 794 } 795 796 template <class T> 797 Derived & 798 functor(T &func) 799 { 800 proxy = new FunctorProxy<T>(func); 801 this->setInit(); 802 return this->self(); 803 } 804 805 Counter value() { return proxy->value(); } 806 Result result() const { return proxy->result(); } 807 Result total() const { return proxy->total(); }; 808 size_type size() const { return proxy->size(); } 809 810 std::string str() const { return proxy->str(); } 811 bool zero() const { return proxy->zero(); } 812 bool check() const { return proxy != NULL; } 813 void prepare() { } 814 void reset() { } 815}; 816 817////////////////////////////////////////////////////////////////////// 818// 819// Vector Statistics 820// 821////////////////////////////////////////////////////////////////////// 822 823/** 824 * A proxy class to access the stat at a given index in a VectorBase stat. 825 * Behaves like a ScalarBase. 826 */ 827template <class Stat> 828class ScalarProxy 829{ 830 private: 831 /** Pointer to the parent Vector. */ 832 Stat &stat; 833 834 /** The index to access in the parent VectorBase. */ 835 off_type index; 836 837 public: 838 /** 839 * Return the current value of this stat as its base type. 840 * @return The current value. 841 */ 842 Counter value() const { return stat.data(index)->value(); } 843 844 /** 845 * Return the current value of this statas a result type. 846 * @return The current value. 847 */ 848 Result result() const { return stat.data(index)->result(); } 849 850 public: 851 /** 852 * Create and initialize this proxy, do not register it with the database. 853 * @param i The index to access. 854 */ 855 ScalarProxy(Stat &s, off_type i) 856 : stat(s), index(i) 857 { 858 } 859 860 /** 861 * Create a copy of the provided ScalarProxy. 862 * @param sp The proxy to copy. 863 */ 864 ScalarProxy(const ScalarProxy &sp) 865 : stat(sp.stat), index(sp.index) 866 {} 867 868 /** 869 * Set this proxy equal to the provided one. 870 * @param sp The proxy to copy. 871 * @return A reference to this proxy. 872 */ 873 const ScalarProxy & 874 operator=(const ScalarProxy &sp) 875 { 876 stat = sp.stat; 877 index = sp.index; 878 return *this; 879 } 880 881 public: 882 // Common operators for stats 883 /** 884 * Increment the stat by 1. This calls the associated storage object inc 885 * function. 886 */ 887 void operator++() { stat.data(index)->inc(1); } 888 /** 889 * Decrement the stat by 1. This calls the associated storage object dec 890 * function. 891 */ 892 void operator--() { stat.data(index)->dec(1); } 893 894 /** Increment the stat by 1. */ 895 void operator++(int) { ++*this; } 896 /** Decrement the stat by 1. */ 897 void operator--(int) { --*this; } 898 899 /** 900 * Set the data value to the given value. This calls the associated storage 901 * object set function. 902 * @param v The new value. 903 */ 904 template <typename U> 905 void 906 operator=(const U &v) 907 { 908 stat.data(index)->set(v); 909 } 910 911 /** 912 * Increment the stat by the given value. This calls the associated 913 * storage object inc function. 914 * @param v The value to add. 915 */ 916 template <typename U> 917 void 918 operator+=(const U &v) 919 { 920 stat.data(index)->inc(v); 921 } 922 923 /** 924 * Decrement the stat by the given value. This calls the associated 925 * storage object dec function. 926 * @param v The value to substract. 927 */ 928 template <typename U> 929 void 930 operator-=(const U &v) 931 { 932 stat.data(index)->dec(v); 933 } 934 935 /** 936 * Return the number of elements, always 1 for a scalar. 937 * @return 1. 938 */ 939 size_type size() const { return 1; } 940 941 public: 942 std::string 943 str() const 944 { 945 return csprintf("%s[%d]", stat.info()->name, index); 946 } 947}; 948 949/** 950 * Implementation of a vector of stats. The type of stat is determined by the 951 * Storage class. @sa ScalarBase 952 */ 953template <class Derived, class Stor> 954class VectorBase : public DataWrapVec<Derived, VectorInfoProxy> 955{ 956 public: 957 typedef Stor Storage; 958 typedef typename Stor::Params Params; 959 960 /** Proxy type */ 961 typedef ScalarProxy<Derived> Proxy; 962 friend class ScalarProxy<Derived>; 963 friend class DataWrapVec<Derived, VectorInfoProxy>; 964 965 protected: 966 /** The storage of this stat. */ 967 Storage *storage; 968 size_type _size; 969 970 protected: 971 /** 972 * Retrieve the storage. 973 * @param index The vector index to access. 974 * @return The storage object at the given index. 975 */ 976 Storage *data(off_type index) { return &storage[index]; } 977 978 /** 979 * Retrieve a const pointer to the storage. 980 * @param index The vector index to access. 981 * @return A const pointer to the storage object at the given index. 982 */ 983 const Storage *data(off_type index) const { return &storage[index]; } 984 985 void 986 doInit(size_type s) 987 { 988 assert(s > 0 && "size must be positive!"); 989 assert(!storage && "already initialized"); 990 _size = s; 991 992 char *ptr = new char[_size * sizeof(Storage)]; 993 storage = reinterpret_cast<Storage *>(ptr); 994 995 for (off_type i = 0; i < _size; ++i) 996 new (&storage[i]) Storage(this->info()); 997 998 this->setInit(); 999 } 1000 1001 public: 1002 void 1003 value(VCounter &vec) const 1004 { 1005 vec.resize(size()); 1006 for (off_type i = 0; i < size(); ++i) 1007 vec[i] = data(i)->value(); 1008 } 1009 1010 /** 1011 * Copy the values to a local vector and return a reference to it. 1012 * @return A reference to a vector of the stat values. 1013 */ 1014 void 1015 result(VResult &vec) const 1016 { 1017 vec.resize(size()); 1018 for (off_type i = 0; i < size(); ++i) 1019 vec[i] = data(i)->result(); 1020 } 1021 1022 /** 1023 * Return a total of all entries in this vector. 1024 * @return The total of all vector entries. 1025 */ 1026 Result 1027 total() const 1028 { 1029 Result total = 0.0; 1030 for (off_type i = 0; i < size(); ++i) 1031 total += data(i)->result(); 1032 return total; 1033 } 1034 1035 /** 1036 * @return the number of elements in this vector. 1037 */ 1038 size_type size() const { return _size; } 1039 1040 bool 1041 zero() const 1042 { 1043 for (off_type i = 0; i < size(); ++i) 1044 if (data(i)->zero()) 1045 return false; 1046 return true; 1047 } 1048 1049 bool 1050 check() const 1051 { 1052 return storage != NULL; 1053 } 1054 1055 public: 1056 VectorBase() 1057 : storage(NULL) 1058 {} 1059 1060 ~VectorBase() 1061 { 1062 if (!storage) 1063 return; 1064 1065 for (off_type i = 0; i < _size; ++i) 1066 data(i)->~Storage(); 1067 delete [] reinterpret_cast<char *>(storage); 1068 } 1069 1070 /** 1071 * Set this vector to have the given size. 1072 * @param size The new size. 1073 * @return A reference to this stat. 1074 */ 1075 Derived & 1076 init(size_type size) 1077 { 1078 Derived &self = this->self(); 1079 self.doInit(size); 1080 return self; 1081 } 1082 1083 /** 1084 * Return a reference (ScalarProxy) to the stat at the given index. 1085 * @param index The vector index to access. 1086 * @return A reference of the stat. 1087 */ 1088 Proxy 1089 operator[](off_type index) 1090 { 1091 assert (index >= 0 && index < size()); 1092 return Proxy(this->self(), index); 1093 } 1094}; 1095 1096template <class Stat> 1097class VectorProxy 1098{ 1099 private: 1100 Stat &stat; 1101 off_type offset; 1102 size_type len; 1103 1104 private: 1105 mutable VResult vec; 1106 1107 typename Stat::Storage * 1108 data(off_type index) 1109 { 1110 assert(index < len); 1111 return stat.data(offset + index); 1112 } 1113 1114 const typename Stat::Storage * 1115 data(off_type index) const 1116 { 1117 assert(index < len); 1118 return stat.data(offset + index); 1119 } 1120 1121 public: 1122 const VResult & 1123 result() const 1124 { 1125 vec.resize(size()); 1126 1127 for (off_type i = 0; i < size(); ++i) 1128 vec[i] = data(i)->result(); 1129 1130 return vec; 1131 } 1132 1133 Result 1134 total() const 1135 { 1136 Result total = 0.0; 1137 for (off_type i = 0; i < size(); ++i) 1138 total += data(i)->result(); 1139 return total; 1140 } 1141 1142 public: 1143 VectorProxy(Stat &s, off_type o, size_type l) 1144 : stat(s), offset(o), len(l) 1145 { 1146 } 1147 1148 VectorProxy(const VectorProxy &sp) 1149 : stat(sp.stat), offset(sp.offset), len(sp.len) 1150 { 1151 } 1152 1153 const VectorProxy & 1154 operator=(const VectorProxy &sp) 1155 { 1156 stat = sp.stat; 1157 offset = sp.offset; 1158 len = sp.len; 1159 return *this; 1160 } 1161 1162 ScalarProxy<Stat> 1163 operator[](off_type index) 1164 { 1165 assert (index >= 0 && index < size()); 1166 return ScalarProxy<Stat>(stat, offset + index); 1167 } 1168 1169 size_type size() const { return len; } 1170}; 1171 1172template <class Derived, class Stor> 1173class Vector2dBase : public DataWrapVec2d<Derived, Vector2dInfoProxy> 1174{ 1175 public: 1176 typedef Vector2dInfoProxy<Derived> Info; 1177 typedef Stor Storage; 1178 typedef typename Stor::Params Params; 1179 typedef VectorProxy<Derived> Proxy; 1180 friend class ScalarProxy<Derived>; 1181 friend class VectorProxy<Derived>; 1182 friend class DataWrapVec<Derived, Vector2dInfoProxy>; 1183 friend class DataWrapVec2d<Derived, Vector2dInfoProxy>; 1184 1185 protected: 1186 size_type x; 1187 size_type y; 1188 size_type _size; 1189 Storage *storage; 1190 1191 protected: 1192 Storage *data(off_type index) { return &storage[index]; } 1193 const Storage *data(off_type index) const { return &storage[index]; } 1194 1195 public: 1196 Vector2dBase() 1197 : storage(NULL) 1198 {} 1199 1200 ~Vector2dBase() 1201 { 1202 if (!storage) 1203 return; 1204 1205 for (off_type i = 0; i < _size; ++i) 1206 data(i)->~Storage(); 1207 delete [] reinterpret_cast<char *>(storage); 1208 } 1209 1210 Derived & 1211 init(size_type _x, size_type _y) 1212 { 1213 assert(_x > 0 && _y > 0 && "sizes must be positive!"); 1214 assert(!storage && "already initialized"); 1215 1216 Derived &self = this->self(); 1217 Info *info = this->info(); 1218 1219 x = _x; 1220 y = _y; 1221 info->x = _x; 1222 info->y = _y; 1223 _size = x * y; 1224 1225 char *ptr = new char[_size * sizeof(Storage)]; 1226 storage = reinterpret_cast<Storage *>(ptr); 1227 1228 for (off_type i = 0; i < _size; ++i) 1229 new (&storage[i]) Storage(info); 1230 1231 this->setInit(); 1232 1233 return self; 1234 } 1235 1236 Proxy 1237 operator[](off_type index) 1238 { 1239 off_type offset = index * y; 1240 assert (index >= 0 && offset + y <= size()); 1241 return Proxy(this->self(), offset, y); 1242 } 1243 1244 1245 size_type 1246 size() const 1247 { 1248 return _size; 1249 } 1250 1251 bool 1252 zero() const 1253 { 1254 return data(0)->zero(); 1255#if 0 1256 for (off_type i = 0; i < size(); ++i) 1257 if (!data(i)->zero()) 1258 return false; 1259 return true; 1260#endif 1261 } 1262 1263 void 1264 prepare() 1265 { 1266 Info *info = this->info(); 1267 size_type size = this->size(); 1268 1269 for (off_type i = 0; i < size; ++i) 1270 data(i)->prepare(info); 1271 1272 info->cvec.resize(size); 1273 for (off_type i = 0; i < size; ++i) 1274 info->cvec[i] = data(i)->value(); 1275 } 1276 1277 /** 1278 * Reset stat value to default 1279 */ 1280 void 1281 reset() 1282 { 1283 Info *info = this->info(); 1284 size_type size = this->size(); 1285 for (off_type i = 0; i < size; ++i) 1286 data(i)->reset(info); 1287 } 1288 1289 bool 1290 check() const 1291 { 1292 return storage != NULL; 1293 } 1294}; 1295 1296////////////////////////////////////////////////////////////////////// 1297// 1298// Non formula statistics 1299// 1300////////////////////////////////////////////////////////////////////// 1301/** The parameters for a distribution stat. */ 1302struct DistParams : public StorageParams 1303{ 1304 const DistType type; 1305 DistParams(DistType t) : type(t) {} 1306}; 1307 1308/** 1309 * Templatized storage and interface for a distrbution stat. 1310 */ 1311class DistStor 1312{ 1313 public: 1314 /** The parameters for a distribution stat. */ 1315 struct Params : public DistParams 1316 { 1317 /** The minimum value to track. */ 1318 Counter min; 1319 /** The maximum value to track. */ 1320 Counter max; 1321 /** The number of entries in each bucket. */ 1322 Counter bucket_size; 1323 /** The number of buckets. Equal to (max-min)/bucket_size. */ 1324 size_type buckets; 1325 1326 Params() : DistParams(Dist) {} 1327 }; 1328 1329 private: 1330 /** The minimum value to track. */ 1331 Counter min_track; 1332 /** The maximum value to track. */ 1333 Counter max_track; 1334 /** The number of entries in each bucket. */ 1335 Counter bucket_size; 1336 1337 /** The smallest value sampled. */ 1338 Counter min_val; 1339 /** The largest value sampled. */ 1340 Counter max_val; 1341 /** The number of values sampled less than min. */ 1342 Counter underflow; 1343 /** The number of values sampled more than max. */ 1344 Counter overflow; 1345 /** The current sum. */ 1346 Counter sum; 1347 /** The sum of squares. */ 1348 Counter squares; 1349 /** The number of samples. */ 1350 Counter samples; 1351 /** Counter for each bucket. */ 1352 VCounter cvec; 1353 1354 public: 1355 DistStor(Info *info) 1356 : cvec(safe_cast<const Params *>(info->storageParams)->buckets) 1357 { 1358 reset(info); 1359 } 1360 1361 /** 1362 * Add a value to the distribution for the given number of times. 1363 * @param val The value to add. 1364 * @param number The number of times to add the value. 1365 */ 1366 void 1367 sample(Counter val, int number) 1368 { 1369 if (val < min_track) 1370 underflow += number; 1371 else if (val > max_track) 1372 overflow += number; 1373 else { 1374 size_type index = 1375 (size_type)std::floor((val - min_track) / bucket_size); 1376 assert(index < size()); 1377 cvec[index] += number; 1378 } 1379 1380 if (val < min_val) 1381 min_val = val; 1382 1383 if (val > max_val) 1384 max_val = val; 1385 1386 sum += val * number; 1387 squares += val * val * number; 1388 samples += number; 1389 } 1390 1391 /** 1392 * Return the number of buckets in this distribution. 1393 * @return the number of buckets. 1394 */ 1395 size_type size() const { return cvec.size(); } 1396 1397 /** 1398 * Returns true if any calls to sample have been made. 1399 * @return True if any values have been sampled. 1400 */ 1401 bool 1402 zero() const 1403 { 1404 return samples == Counter(); 1405 } 1406 1407 void 1408 prepare(Info *info, DistData &data) 1409 { 1410 const Params *params = safe_cast<const Params *>(info->storageParams); 1411 1412 assert(params->type == Dist); 1413 data.type = params->type; 1414 data.min = params->min; 1415 data.max = params->max; 1416 data.bucket_size = params->bucket_size; 1417 1418 data.min_val = (min_val == CounterLimits::max()) ? 0 : min_val; 1419 data.max_val = (max_val == CounterLimits::min()) ? 0 : max_val; 1420 data.underflow = underflow; 1421 data.overflow = overflow; 1422 1423 data.cvec.resize(params->buckets); 1424 for (off_type i = 0; i < params->buckets; ++i) 1425 data.cvec[i] = cvec[i]; 1426 1427 data.sum = sum; 1428 data.squares = squares; 1429 data.samples = samples; 1430 } 1431 1432 /** 1433 * Reset stat value to default 1434 */ 1435 void 1436 reset(Info *info) 1437 { 1438 const Params *params = safe_cast<const Params *>(info->storageParams); 1439 min_track = params->min; 1440 max_track = params->max; 1441 bucket_size = params->bucket_size; 1442 1443 min_val = CounterLimits::max(); 1444 max_val = CounterLimits::min(); 1445 underflow = Counter(); 1446 overflow = Counter(); 1447 1448 size_type size = cvec.size(); 1449 for (off_type i = 0; i < size; ++i) 1450 cvec[i] = Counter(); 1451 1452 sum = Counter(); 1453 squares = Counter(); 1454 samples = Counter(); 1455 } 1456}; 1457 1458/** 1459 * Templatized storage and interface for a histogram stat. 1460 */ 1461class HistStor 1462{ 1463 public: 1464 /** The parameters for a distribution stat. */ 1465 struct Params : public DistParams 1466 { 1467 /** The number of buckets.. */ 1468 size_type buckets; 1469 1470 Params() : DistParams(Hist) {} 1471 }; 1472 1473 private: 1474 /** The minimum value to track. */ 1475 Counter min_bucket; 1476 /** The maximum value to track. */ 1477 Counter max_bucket; 1478 /** The number of entries in each bucket. */ 1479 Counter bucket_size; 1480 1481 /** The current sum. */ 1482 Counter sum; 1483 /** The sum of logarithm of each sample, used to compute geometric mean. */ 1484 Counter logs; 1485 /** The sum of squares. */ 1486 Counter squares; 1487 /** The number of samples. */ 1488 Counter samples; 1489 /** Counter for each bucket. */ 1490 VCounter cvec; 1491 1492 public: 1493 HistStor(Info *info) 1494 : cvec(safe_cast<const Params *>(info->storageParams)->buckets) 1495 { 1496 reset(info); 1497 } 1498 1499 void grow_up(); 1500 void grow_out(); 1501 void grow_convert(); 1502 1503 /** 1504 * Add a value to the distribution for the given number of times. 1505 * @param val The value to add. 1506 * @param number The number of times to add the value. 1507 */ 1508 void 1509 sample(Counter val, int number) 1510 { 1511 assert(min_bucket < max_bucket); 1512 if (val < min_bucket) { 1513 if (min_bucket == 0) 1514 grow_convert(); 1515 1516 while (val < min_bucket) 1517 grow_out(); 1518 } else if (val >= max_bucket + bucket_size) { 1519 if (min_bucket == 0) { 1520 while (val >= max_bucket + bucket_size) 1521 grow_up(); 1522 } else { 1523 while (val >= max_bucket + bucket_size) 1524 grow_out(); 1525 } 1526 } 1527 1528 size_type index = 1529 (int64_t)std::floor((val - min_bucket) / bucket_size); 1530 1531 assert(index >= 0 && index < size()); 1532 cvec[index] += number; 1533 1534 sum += val * number; 1535 squares += val * val * number; 1536 logs += log(val) * number; 1537 samples += number; 1538 } 1539 1540 /** 1541 * Return the number of buckets in this distribution. 1542 * @return the number of buckets. 1543 */ 1544 size_type size() const { return cvec.size(); } 1545 1546 /** 1547 * Returns true if any calls to sample have been made. 1548 * @return True if any values have been sampled. 1549 */ 1550 bool 1551 zero() const 1552 { 1553 return samples == Counter(); 1554 } 1555 1556 void 1557 prepare(Info *info, DistData &data) 1558 { 1559 const Params *params = safe_cast<const Params *>(info->storageParams); 1560 1561 assert(params->type == Hist); 1562 data.type = params->type; 1563 data.min = min_bucket; 1564 data.max = max_bucket + bucket_size - 1; 1565 data.bucket_size = bucket_size; 1566 1567 data.min_val = min_bucket; 1568 data.max_val = max_bucket; 1569 1570 int buckets = params->buckets; 1571 data.cvec.resize(buckets); 1572 for (off_type i = 0; i < buckets; ++i) 1573 data.cvec[i] = cvec[i]; 1574 1575 data.sum = sum; 1576 data.logs = logs; 1577 data.squares = squares; 1578 data.samples = samples; 1579 } 1580 1581 /** 1582 * Reset stat value to default 1583 */ 1584 void 1585 reset(Info *info) 1586 { 1587 const Params *params = safe_cast<const Params *>(info->storageParams); 1588 min_bucket = 0; 1589 max_bucket = params->buckets - 1; 1590 bucket_size = 1; 1591 1592 size_type size = cvec.size(); 1593 for (off_type i = 0; i < size; ++i) 1594 cvec[i] = Counter(); 1595 1596 sum = Counter(); 1597 squares = Counter(); 1598 samples = Counter(); 1599 logs = Counter(); 1600 } 1601}; 1602 1603/** 1604 * Templatized storage and interface for a distribution that calculates mean 1605 * and variance. 1606 */ 1607class SampleStor 1608{ 1609 public: 1610 struct Params : public DistParams 1611 { 1612 Params() : DistParams(Deviation) {} 1613 }; 1614 1615 private: 1616 /** The current sum. */ 1617 Counter sum; 1618 /** The sum of squares. */ 1619 Counter squares; 1620 /** The number of samples. */ 1621 Counter samples; 1622 1623 public: 1624 /** 1625 * Create and initialize this storage. 1626 */ 1627 SampleStor(Info *info) 1628 : sum(Counter()), squares(Counter()), samples(Counter()) 1629 { } 1630 1631 /** 1632 * Add a value the given number of times to this running average. 1633 * Update the running sum and sum of squares, increment the number of 1634 * values seen by the given number. 1635 * @param val The value to add. 1636 * @param number The number of times to add the value. 1637 */ 1638 void 1639 sample(Counter val, int number) 1640 { 1641 Counter value = val * number; 1642 sum += value; 1643 squares += value * value; 1644 samples += number; 1645 } 1646 1647 /** 1648 * Return the number of entries in this stat, 1 1649 * @return 1. 1650 */ 1651 size_type size() const { return 1; } 1652 1653 /** 1654 * Return true if no samples have been added. 1655 * @return True if no samples have been added. 1656 */ 1657 bool zero() const { return samples == Counter(); } 1658 1659 void 1660 prepare(Info *info, DistData &data) 1661 { 1662 const Params *params = safe_cast<const Params *>(info->storageParams); 1663 1664 assert(params->type == Deviation); 1665 data.type = params->type; 1666 data.sum = sum; 1667 data.squares = squares; 1668 data.samples = samples; 1669 } 1670 1671 /** 1672 * Reset stat value to default 1673 */ 1674 void 1675 reset(Info *info) 1676 { 1677 sum = Counter(); 1678 squares = Counter(); 1679 samples = Counter(); 1680 } 1681}; 1682 1683/** 1684 * Templatized storage for distribution that calculates per tick mean and 1685 * variance. 1686 */ 1687class AvgSampleStor 1688{ 1689 public: 1690 struct Params : public DistParams 1691 { 1692 Params() : DistParams(Deviation) {} 1693 }; 1694 1695 private: 1696 /** Current total. */ 1697 Counter sum; 1698 /** Current sum of squares. */ 1699 Counter squares; 1700 1701 public: 1702 /** 1703 * Create and initialize this storage. 1704 */ 1705 AvgSampleStor(Info *info) 1706 : sum(Counter()), squares(Counter()) 1707 {} 1708 1709 /** 1710 * Add a value to the distribution for the given number of times. 1711 * Update the running sum and sum of squares. 1712 * @param val The value to add. 1713 * @param number The number of times to add the value. 1714 */ 1715 void 1716 sample(Counter val, int number) 1717 { 1718 Counter value = val * number; 1719 sum += value; 1720 squares += value * value; 1721 } 1722 1723 /** 1724 * Return the number of entries, in this case 1. 1725 * @return 1. 1726 */ 1727 size_type size() const { return 1; } 1728 1729 /** 1730 * Return true if no samples have been added. 1731 * @return True if the sum is zero. 1732 */ 1733 bool zero() const { return sum == Counter(); } 1734 1735 void 1736 prepare(Info *info, DistData &data) 1737 { 1738 const Params *params = safe_cast<const Params *>(info->storageParams); 1739 1740 assert(params->type == Deviation); 1741 data.type = params->type; 1742 data.sum = sum; 1743 data.squares = squares; 1744 data.samples = curTick(); 1745 } 1746 1747 /** 1748 * Reset stat value to default 1749 */ 1750 void 1751 reset(Info *info) 1752 { 1753 sum = Counter(); 1754 squares = Counter(); 1755 } 1756}; 1757 1758/** 1759 * Implementation of a distribution stat. The type of distribution is 1760 * determined by the Storage template. @sa ScalarBase 1761 */ 1762template <class Derived, class Stor> 1763class DistBase : public DataWrap<Derived, DistInfoProxy> 1764{ 1765 public: 1766 typedef DistInfoProxy<Derived> Info; 1767 typedef Stor Storage; 1768 typedef typename Stor::Params Params; 1769 1770 protected: 1771 /** The storage for this stat. */ 1772 char storage[sizeof(Storage)] __attribute__ ((aligned (8))); 1773 1774 protected: 1775 /** 1776 * Retrieve the storage. 1777 * @return The storage object for this stat. 1778 */ 1779 Storage * 1780 data() 1781 { 1782 return reinterpret_cast<Storage *>(storage); 1783 } 1784 1785 /** 1786 * Retrieve a const pointer to the storage. 1787 * @return A const pointer to the storage object for this stat. 1788 */ 1789 const Storage * 1790 data() const 1791 { 1792 return reinterpret_cast<const Storage *>(storage); 1793 } 1794 1795 void 1796 doInit() 1797 { 1798 new (storage) Storage(this->info()); 1799 this->setInit(); 1800 } 1801 1802 public: 1803 DistBase() { } 1804 1805 /** 1806 * Add a value to the distribtion n times. Calls sample on the storage 1807 * class. 1808 * @param v The value to add. 1809 * @param n The number of times to add it, defaults to 1. 1810 */ 1811 template <typename U> 1812 void sample(const U &v, int n = 1) { data()->sample(v, n); } 1813 1814 /** 1815 * Return the number of entries in this stat. 1816 * @return The number of entries. 1817 */ 1818 size_type size() const { return data()->size(); } 1819 /** 1820 * Return true if no samples have been added. 1821 * @return True if there haven't been any samples. 1822 */ 1823 bool zero() const { return data()->zero(); } 1824 1825 void 1826 prepare() 1827 { 1828 Info *info = this->info(); 1829 data()->prepare(info, info->data); 1830 } 1831 1832 /** 1833 * Reset stat value to default 1834 */ 1835 void 1836 reset() 1837 { 1838 data()->reset(this->info()); 1839 } 1840}; 1841 1842template <class Stat> 1843class DistProxy; 1844 1845template <class Derived, class Stor> 1846class VectorDistBase : public DataWrapVec<Derived, VectorDistInfoProxy> 1847{ 1848 public: 1849 typedef VectorDistInfoProxy<Derived> Info; 1850 typedef Stor Storage; 1851 typedef typename Stor::Params Params; 1852 typedef DistProxy<Derived> Proxy; 1853 friend class DistProxy<Derived>; 1854 friend class DataWrapVec<Derived, VectorDistInfoProxy>; 1855 1856 protected: 1857 Storage *storage; 1858 size_type _size; 1859 1860 protected: 1861 Storage * 1862 data(off_type index) 1863 { 1864 return &storage[index]; 1865 } 1866 1867 const Storage * 1868 data(off_type index) const 1869 { 1870 return &storage[index]; 1871 } 1872 1873 void 1874 doInit(size_type s) 1875 { 1876 assert(s > 0 && "size must be positive!"); 1877 assert(!storage && "already initialized"); 1878 _size = s; 1879 1880 char *ptr = new char[_size * sizeof(Storage)]; 1881 storage = reinterpret_cast<Storage *>(ptr); 1882 1883 Info *info = this->info(); 1884 for (off_type i = 0; i < _size; ++i) 1885 new (&storage[i]) Storage(info); 1886 1887 this->setInit(); 1888 } 1889 1890 public: 1891 VectorDistBase() 1892 : storage(NULL) 1893 {} 1894 1895 ~VectorDistBase() 1896 { 1897 if (!storage) 1898 return ; 1899 1900 for (off_type i = 0; i < _size; ++i) 1901 data(i)->~Storage(); 1902 delete [] reinterpret_cast<char *>(storage); 1903 } 1904 1905 Proxy operator[](off_type index) 1906 { 1907 assert(index >= 0 && index < size()); 1908 return Proxy(this->self(), index); 1909 } 1910 1911 size_type 1912 size() const 1913 { 1914 return _size; 1915 } 1916 1917 bool 1918 zero() const 1919 { 1920 for (off_type i = 0; i < size(); ++i) 1921 if (!data(i)->zero()) 1922 return false; 1923 return true; 1924 } 1925 1926 void 1927 prepare() 1928 { 1929 Info *info = this->info(); 1930 size_type size = this->size(); 1931 info->data.resize(size); 1932 for (off_type i = 0; i < size; ++i) 1933 data(i)->prepare(info, info->data[i]); 1934 } 1935 1936 bool 1937 check() const 1938 { 1939 return storage != NULL; 1940 } 1941}; 1942 1943template <class Stat> 1944class DistProxy 1945{ 1946 private: 1947 Stat &stat; 1948 off_type index; 1949 1950 protected: 1951 typename Stat::Storage *data() { return stat.data(index); } 1952 const typename Stat::Storage *data() const { return stat.data(index); } 1953 1954 public: 1955 DistProxy(Stat &s, off_type i) 1956 : stat(s), index(i) 1957 {} 1958 1959 DistProxy(const DistProxy &sp) 1960 : stat(sp.stat), index(sp.index) 1961 {} 1962 1963 const DistProxy & 1964 operator=(const DistProxy &sp) 1965 { 1966 stat = sp.stat; 1967 index = sp.index; 1968 return *this; 1969 } 1970 1971 public: 1972 template <typename U> 1973 void 1974 sample(const U &v, int n = 1) 1975 { 1976 data()->sample(v, n); 1977 } 1978 1979 size_type 1980 size() const 1981 { 1982 return 1; 1983 } 1984 1985 bool 1986 zero() const 1987 { 1988 return data()->zero(); 1989 } 1990 1991 /** 1992 * Proxy has no state. Nothing to reset. 1993 */ 1994 void reset() { } 1995}; 1996 1997////////////////////////////////////////////////////////////////////// 1998// 1999// Formula Details 2000// 2001////////////////////////////////////////////////////////////////////// 2002 2003/** 2004 * Base class for formula statistic node. These nodes are used to build a tree 2005 * that represents the formula. 2006 */ 2007class Node : public RefCounted 2008{ 2009 public: 2010 /** 2011 * Return the number of nodes in the subtree starting at this node. 2012 * @return the number of nodes in this subtree. 2013 */ 2014 virtual size_type size() const = 0; 2015 /** 2016 * Return the result vector of this subtree. 2017 * @return The result vector of this subtree. 2018 */ 2019 virtual const VResult &result() const = 0; 2020 /** 2021 * Return the total of the result vector. 2022 * @return The total of the result vector. 2023 */ 2024 virtual Result total() const = 0; 2025 2026 /** 2027 * 2028 */ 2029 virtual std::string str() const = 0; 2030}; 2031 2032/** Reference counting pointer to a function Node. */ 2033typedef RefCountingPtr<Node> NodePtr; 2034 2035class ScalarStatNode : public Node 2036{ 2037 private: 2038 const ScalarInfo *data; 2039 mutable VResult vresult; 2040 2041 public: 2042 ScalarStatNode(const ScalarInfo *d) : data(d), vresult(1) {} 2043 2044 const VResult & 2045 result() const 2046 { 2047 vresult[0] = data->result(); 2048 return vresult; 2049 } 2050 2051 Result total() const { return data->result(); }; 2052 2053 size_type size() const { return 1; } 2054 2055 /** 2056 * 2057 */ 2058 std::string str() const { return data->name; } 2059}; 2060 2061template <class Stat> 2062class ScalarProxyNode : public Node 2063{ 2064 private: 2065 const ScalarProxy<Stat> proxy; 2066 mutable VResult vresult; 2067 2068 public: 2069 ScalarProxyNode(const ScalarProxy<Stat> &p) 2070 : proxy(p), vresult(1) 2071 { } 2072 2073 const VResult & 2074 result() const 2075 { 2076 vresult[0] = proxy.result(); 2077 return vresult; 2078 } 2079 2080 Result 2081 total() const 2082 { 2083 return proxy.result(); 2084 } 2085 2086 size_type 2087 size() const 2088 { 2089 return 1; 2090 } 2091 2092 /** 2093 * 2094 */ 2095 std::string 2096 str() const 2097 { 2098 return proxy.str(); 2099 } 2100}; 2101 2102class VectorStatNode : public Node 2103{ 2104 private: 2105 const VectorInfo *data; 2106 2107 public: 2108 VectorStatNode(const VectorInfo *d) : data(d) { } 2109 const VResult &result() const { return data->result(); } 2110 Result total() const { return data->total(); }; 2111 2112 size_type size() const { return data->size(); } 2113 2114 std::string str() const { return data->name; } 2115}; 2116 2117template <class T> 2118class ConstNode : public Node 2119{ 2120 private: 2121 VResult vresult; 2122 2123 public: 2124 ConstNode(T s) : vresult(1, (Result)s) {} 2125 const VResult &result() const { return vresult; } 2126 Result total() const { return vresult[0]; }; 2127 size_type size() const { return 1; } 2128 std::string str() const { return to_string(vresult[0]); } 2129}; 2130 2131template <class T> 2132class ConstVectorNode : public Node 2133{ 2134 private: 2135 VResult vresult; 2136 2137 public: 2138 ConstVectorNode(const T &s) : vresult(s.begin(), s.end()) {} 2139 const VResult &result() const { return vresult; } 2140 2141 Result 2142 total() const 2143 { 2144 size_type size = this->size(); 2145 Result tmp = 0; 2146 for (off_type i = 0; i < size; i++) 2147 tmp += vresult[i]; 2148 return tmp; 2149 } 2150 2151 size_type size() const { return vresult.size(); } 2152 std::string 2153 str() const 2154 { 2155 size_type size = this->size(); 2156 std::string tmp = "("; 2157 for (off_type i = 0; i < size; i++) 2158 tmp += csprintf("%s ",to_string(vresult[i])); 2159 tmp += ")"; 2160 return tmp; 2161 } 2162}; 2163 2164template <class Op> 2165struct OpString; 2166 2167template<> 2168struct OpString<std::plus<Result> > 2169{ 2170 static std::string str() { return "+"; } 2171}; 2172 2173template<> 2174struct OpString<std::minus<Result> > 2175{ 2176 static std::string str() { return "-"; } 2177}; 2178 2179template<> 2180struct OpString<std::multiplies<Result> > 2181{ 2182 static std::string str() { return "*"; } 2183}; 2184 2185template<> 2186struct OpString<std::divides<Result> > 2187{ 2188 static std::string str() { return "/"; } 2189}; 2190 2191template<> 2192struct OpString<std::modulus<Result> > 2193{ 2194 static std::string str() { return "%"; } 2195}; 2196 2197template<> 2198struct OpString<std::negate<Result> > 2199{ 2200 static std::string str() { return "-"; } 2201}; 2202 2203template <class Op> 2204class UnaryNode : public Node 2205{ 2206 public: 2207 NodePtr l; 2208 mutable VResult vresult; 2209 2210 public: 2211 UnaryNode(NodePtr &p) : l(p) {} 2212 2213 const VResult & 2214 result() const 2215 { 2216 const VResult &lvec = l->result(); 2217 size_type size = lvec.size(); 2218 2219 assert(size > 0); 2220 2221 vresult.resize(size); 2222 Op op; 2223 for (off_type i = 0; i < size; ++i) 2224 vresult[i] = op(lvec[i]); 2225 2226 return vresult; 2227 } 2228 2229 Result 2230 total() const 2231 { 2232 const VResult &vec = this->result(); 2233 Result total = 0.0; 2234 for (off_type i = 0; i < size(); i++) 2235 total += vec[i]; 2236 return total; 2237 } 2238 2239 size_type size() const { return l->size(); } 2240 2241 std::string 2242 str() const 2243 { 2244 return OpString<Op>::str() + l->str(); 2245 } 2246}; 2247 2248template <class Op> 2249class BinaryNode : public Node 2250{ 2251 public: 2252 NodePtr l; 2253 NodePtr r; 2254 mutable VResult vresult; 2255 2256 public: 2257 BinaryNode(NodePtr &a, NodePtr &b) : l(a), r(b) {} 2258 2259 const VResult & 2260 result() const 2261 { 2262 Op op; 2263 const VResult &lvec = l->result(); 2264 const VResult &rvec = r->result(); 2265 2266 assert(lvec.size() > 0 && rvec.size() > 0); 2267 2268 if (lvec.size() == 1 && rvec.size() == 1) { 2269 vresult.resize(1); 2270 vresult[0] = op(lvec[0], rvec[0]); 2271 } else if (lvec.size() == 1) { 2272 size_type size = rvec.size(); 2273 vresult.resize(size); 2274 for (off_type i = 0; i < size; ++i) 2275 vresult[i] = op(lvec[0], rvec[i]); 2276 } else if (rvec.size() == 1) { 2277 size_type size = lvec.size(); 2278 vresult.resize(size); 2279 for (off_type i = 0; i < size; ++i) 2280 vresult[i] = op(lvec[i], rvec[0]); 2281 } else if (rvec.size() == lvec.size()) { 2282 size_type size = rvec.size(); 2283 vresult.resize(size); 2284 for (off_type i = 0; i < size; ++i) 2285 vresult[i] = op(lvec[i], rvec[i]); 2286 } 2287 2288 return vresult; 2289 } 2290 2291 Result 2292 total() const 2293 { 2294 const VResult &vec = this->result(); 2295 const VResult &lvec = l->result(); 2296 const VResult &rvec = r->result(); 2297 Result total = 0.0; 2298 Result lsum = 0.0; 2299 Result rsum = 0.0; 2300 Op op; 2301 2302 assert(lvec.size() > 0 && rvec.size() > 0); 2303 assert(lvec.size() == rvec.size() || 2304 lvec.size() == 1 || rvec.size() == 1); 2305 2306 /** If vectors are the same divide their sums (x0+x1)/(y0+y1) */ 2307 if (lvec.size() == rvec.size() && lvec.size() > 1) { 2308 for (off_type i = 0; i < size(); ++i) { 2309 lsum += lvec[i]; 2310 rsum += rvec[i]; 2311 } 2312 return op(lsum, rsum); 2313 } 2314 2315 /** Otherwise divide each item by the divisor */ 2316 for (off_type i = 0; i < size(); ++i) { 2317 total += vec[i]; 2318 } 2319 2320 return total; 2321 } 2322 2323 size_type 2324 size() const 2325 { 2326 size_type ls = l->size(); 2327 size_type rs = r->size(); 2328 if (ls == 1) { 2329 return rs; 2330 } else if (rs == 1) { 2331 return ls; 2332 } else { 2333 assert(ls == rs && "Node vector sizes are not equal"); 2334 return ls; 2335 } 2336 } 2337 2338 std::string 2339 str() const 2340 { 2341 return csprintf("(%s %s %s)", l->str(), OpString<Op>::str(), r->str()); 2342 } 2343}; 2344 2345template <class Op> 2346class SumNode : public Node 2347{ 2348 public: 2349 NodePtr l; 2350 mutable VResult vresult; 2351 2352 public: 2353 SumNode(NodePtr &p) : l(p), vresult(1) {} 2354 2355 const VResult & 2356 result() const 2357 { 2358 const VResult &lvec = l->result(); 2359 size_type size = lvec.size(); 2360 assert(size > 0); 2361 2362 vresult[0] = 0.0; 2363 2364 Op op; 2365 for (off_type i = 0; i < size; ++i) 2366 vresult[0] = op(vresult[0], lvec[i]); 2367 2368 return vresult; 2369 } 2370 2371 Result 2372 total() const 2373 { 2374 const VResult &lvec = l->result(); 2375 size_type size = lvec.size(); 2376 assert(size > 0); 2377 2378 Result result = 0.0; 2379 2380 Op op; 2381 for (off_type i = 0; i < size; ++i) 2382 result = op(result, lvec[i]); 2383 2384 return result; 2385 } 2386 2387 size_type size() const { return 1; } 2388 2389 std::string 2390 str() const 2391 { 2392 return csprintf("total(%s)", l->str()); 2393 } 2394}; 2395 2396 2397////////////////////////////////////////////////////////////////////// 2398// 2399// Visible Statistics Types 2400// 2401////////////////////////////////////////////////////////////////////// 2402/** 2403 * @defgroup VisibleStats "Statistic Types" 2404 * These are the statistics that are used in the simulator. 2405 * @{ 2406 */ 2407 2408/** 2409 * This is a simple scalar statistic, like a counter. 2410 * @sa Stat, ScalarBase, StatStor 2411 */ 2412class Scalar : public ScalarBase<Scalar, StatStor> 2413{ 2414 public: 2415 using ScalarBase<Scalar, StatStor>::operator=; 2416}; 2417 2418/** 2419 * A stat that calculates the per tick average of a value. 2420 * @sa Stat, ScalarBase, AvgStor 2421 */ 2422class Average : public ScalarBase<Average, AvgStor> 2423{ 2424 public: 2425 using ScalarBase<Average, AvgStor>::operator=; 2426}; 2427 2428class Value : public ValueBase<Value> 2429{ 2430}; 2431 2432/** 2433 * A vector of scalar stats. 2434 * @sa Stat, VectorBase, StatStor 2435 */ 2436class Vector : public VectorBase<Vector, StatStor> 2437{ 2438}; 2439 2440/** 2441 * A vector of Average stats. 2442 * @sa Stat, VectorBase, AvgStor 2443 */ 2444class AverageVector : public VectorBase<AverageVector, AvgStor> 2445{ 2446}; 2447 2448/** 2449 * A 2-Dimensional vecto of scalar stats. 2450 * @sa Stat, Vector2dBase, StatStor 2451 */ 2452class Vector2d : public Vector2dBase<Vector2d, StatStor> 2453{ 2454}; 2455 2456/** 2457 * A simple distribution stat. 2458 * @sa Stat, DistBase, DistStor 2459 */ 2460class Distribution : public DistBase<Distribution, DistStor> 2461{ 2462 public: 2463 /** 2464 * Set the parameters of this distribution. @sa DistStor::Params 2465 * @param min The minimum value of the distribution. 2466 * @param max The maximum value of the distribution. 2467 * @param bkt The number of values in each bucket. 2468 * @return A reference to this distribution. 2469 */ 2470 Distribution & 2471 init(Counter min, Counter max, Counter bkt) 2472 { 2473 DistStor::Params *params = new DistStor::Params; 2474 params->min = min; 2475 params->max = max; 2476 params->bucket_size = bkt; 2477 params->buckets = (size_type)ceil((max - min + 1.0) / bkt); 2478 this->setParams(params); 2479 this->doInit(); 2480 return this->self(); 2481 } 2482}; 2483 2484/** 2485 * A simple histogram stat. 2486 * @sa Stat, DistBase, HistStor 2487 */ 2488class Histogram : public DistBase<Histogram, HistStor> 2489{ 2490 public: 2491 /** 2492 * Set the parameters of this histogram. @sa HistStor::Params 2493 * @param size The number of buckets in the histogram 2494 * @return A reference to this histogram. 2495 */ 2496 Histogram & 2497 init(size_type size) 2498 { 2499 HistStor::Params *params = new HistStor::Params; 2500 params->buckets = size; 2501 this->setParams(params); 2502 this->doInit(); 2503 return this->self(); 2504 } 2505}; 2506 2507/** 2508 * Calculates the mean and variance of all the samples. 2509 * @sa DistBase, SampleStor 2510 */ 2511class StandardDeviation : public DistBase<StandardDeviation, SampleStor> 2512{ 2513 public: 2514 /** 2515 * Construct and initialize this distribution. 2516 */ 2517 StandardDeviation() 2518 { 2519 SampleStor::Params *params = new SampleStor::Params; 2520 this->doInit(); 2521 this->setParams(params); 2522 } 2523}; 2524 2525/** 2526 * Calculates the per tick mean and variance of the samples. 2527 * @sa DistBase, AvgSampleStor 2528 */ 2529class AverageDeviation : public DistBase<AverageDeviation, AvgSampleStor> 2530{ 2531 public: 2532 /** 2533 * Construct and initialize this distribution. 2534 */ 2535 AverageDeviation() 2536 { 2537 AvgSampleStor::Params *params = new AvgSampleStor::Params; 2538 this->doInit(); 2539 this->setParams(params); 2540 } 2541}; 2542 2543/** 2544 * A vector of distributions. 2545 * @sa VectorDistBase, DistStor 2546 */ 2547class VectorDistribution : public VectorDistBase<VectorDistribution, DistStor> 2548{ 2549 public: 2550 /** 2551 * Initialize storage and parameters for this distribution. 2552 * @param size The size of the vector (the number of distributions). 2553 * @param min The minimum value of the distribution. 2554 * @param max The maximum value of the distribution. 2555 * @param bkt The number of values in each bucket. 2556 * @return A reference to this distribution. 2557 */ 2558 VectorDistribution & 2559 init(size_type size, Counter min, Counter max, Counter bkt) 2560 { 2561 DistStor::Params *params = new DistStor::Params; 2562 params->min = min; 2563 params->max = max; 2564 params->bucket_size = bkt; 2565 params->buckets = (size_type)ceil((max - min + 1.0) / bkt); 2566 this->setParams(params); 2567 this->doInit(size); 2568 return this->self(); 2569 } 2570}; 2571 2572/** 2573 * This is a vector of StandardDeviation stats. 2574 * @sa VectorDistBase, SampleStor 2575 */ 2576class VectorStandardDeviation 2577 : public VectorDistBase<VectorStandardDeviation, SampleStor> 2578{ 2579 public: 2580 /** 2581 * Initialize storage for this distribution. 2582 * @param size The size of the vector. 2583 * @return A reference to this distribution. 2584 */ 2585 VectorStandardDeviation & 2586 init(size_type size) 2587 { 2588 SampleStor::Params *params = new SampleStor::Params; 2589 this->doInit(size); 2590 this->setParams(params); 2591 return this->self(); 2592 } 2593}; 2594 2595/** 2596 * This is a vector of AverageDeviation stats. 2597 * @sa VectorDistBase, AvgSampleStor 2598 */ 2599class VectorAverageDeviation 2600 : public VectorDistBase<VectorAverageDeviation, AvgSampleStor> 2601{ 2602 public: 2603 /** 2604 * Initialize storage for this distribution. 2605 * @param size The size of the vector. 2606 * @return A reference to this distribution. 2607 */ 2608 VectorAverageDeviation & 2609 init(size_type size) 2610 { 2611 AvgSampleStor::Params *params = new AvgSampleStor::Params; 2612 this->doInit(size); 2613 this->setParams(params); 2614 return this->self(); 2615 } 2616}; 2617 2618template <class Stat> 2619class FormulaInfoProxy : public InfoProxy<Stat, FormulaInfo> 2620{ 2621 protected: 2622 mutable VResult vec; 2623 mutable VCounter cvec; 2624 2625 public: 2626 FormulaInfoProxy(Stat &stat) : InfoProxy<Stat, FormulaInfo>(stat) {} 2627 2628 size_type size() const { return this->s.size(); } 2629 2630 const VResult & 2631 result() const 2632 { 2633 this->s.result(vec); 2634 return vec; 2635 } 2636 Result total() const { return this->s.total(); } 2637 VCounter &value() const { return cvec; } 2638 2639 std::string str() const { return this->s.str(); } 2640}; 2641 2642template <class Stat> 2643class SparseHistInfoProxy : public InfoProxy<Stat, SparseHistInfo> 2644{ 2645 public: 2646 SparseHistInfoProxy(Stat &stat) : InfoProxy<Stat, SparseHistInfo>(stat) {} 2647}; 2648 2649/** 2650 * Implementation of a sparse histogram stat. The storage class is 2651 * determined by the Storage template. 2652 */ 2653template <class Derived, class Stor> 2654class SparseHistBase : public DataWrap<Derived, SparseHistInfoProxy> 2655{ 2656 public: 2657 typedef SparseHistInfoProxy<Derived> Info; 2658 typedef Stor Storage; 2659 typedef typename Stor::Params Params; 2660 2661 protected: 2662 /** The storage for this stat. */ 2663 char storage[sizeof(Storage)]; 2664 2665 protected: 2666 /** 2667 * Retrieve the storage. 2668 * @return The storage object for this stat. 2669 */ 2670 Storage * 2671 data() 2672 { 2673 return reinterpret_cast<Storage *>(storage); 2674 } 2675 2676 /** 2677 * Retrieve a const pointer to the storage. 2678 * @return A const pointer to the storage object for this stat. 2679 */ 2680 const Storage * 2681 data() const 2682 { 2683 return reinterpret_cast<const Storage *>(storage); 2684 } 2685 2686 void 2687 doInit() 2688 { 2689 new (storage) Storage(this->info()); 2690 this->setInit(); 2691 } 2692 2693 public: 2694 SparseHistBase() { } 2695 2696 /** 2697 * Add a value to the distribtion n times. Calls sample on the storage 2698 * class. 2699 * @param v The value to add. 2700 * @param n The number of times to add it, defaults to 1. 2701 */ 2702 template <typename U> 2703 void sample(const U &v, int n = 1) { data()->sample(v, n); } 2704 2705 /** 2706 * Return the number of entries in this stat. 2707 * @return The number of entries. 2708 */ 2709 size_type size() const { return data()->size(); } 2710 /** 2711 * Return true if no samples have been added. 2712 * @return True if there haven't been any samples. 2713 */ 2714 bool zero() const { return data()->zero(); } 2715 2716 void 2717 prepare() 2718 { 2719 Info *info = this->info(); 2720 data()->prepare(info, info->data); 2721 } 2722 2723 /** 2724 * Reset stat value to default 2725 */ 2726 void 2727 reset() 2728 { 2729 data()->reset(this->info()); 2730 } 2731}; 2732 2733/** 2734 * Templatized storage and interface for a sparse histogram stat. 2735 */ 2736class SparseHistStor 2737{ 2738 public: 2739 /** The parameters for a sparse histogram stat. */ 2740 struct Params : public DistParams 2741 { 2742 Params() : DistParams(Hist) {} 2743 }; 2744 2745 private: 2746 /** Counter for number of samples */ 2747 Counter samples; 2748 /** Counter for each bucket. */ 2749 MCounter cmap; 2750 2751 public: 2752 SparseHistStor(Info *info) 2753 { 2754 reset(info); 2755 } 2756 2757 /** 2758 * Add a value to the distribution for the given number of times. 2759 * @param val The value to add. 2760 * @param number The number of times to add the value. 2761 */ 2762 void 2763 sample(Counter val, int number) 2764 { 2765 cmap[val] += number; 2766 samples += number; 2767 } 2768 2769 /** 2770 * Return the number of buckets in this distribution. 2771 * @return the number of buckets. 2772 */ 2773 size_type size() const { return cmap.size(); } 2774 2775 /** 2776 * Returns true if any calls to sample have been made. 2777 * @return True if any values have been sampled. 2778 */ 2779 bool 2780 zero() const 2781 { 2782 return samples == Counter(); 2783 } 2784 2785 void 2786 prepare(Info *info, SparseHistData &data) 2787 { 2788 MCounter::iterator it; 2789 data.cmap.clear(); 2790 for (it = cmap.begin(); it != cmap.end(); it++) { 2791 data.cmap[(*it).first] = (*it).second; 2792 } 2793 2794 data.samples = samples; 2795 } 2796 2797 /** 2798 * Reset stat value to default 2799 */ 2800 void 2801 reset(Info *info) 2802 { 2803 cmap.clear(); 2804 samples = 0; 2805 } 2806}; 2807 2808class SparseHistogram : public SparseHistBase<SparseHistogram, SparseHistStor> 2809{ 2810 public: 2811 /** 2812 * Set the parameters of this histogram. @sa HistStor::Params 2813 * @param size The number of buckets in the histogram 2814 * @return A reference to this histogram. 2815 */ 2816 SparseHistogram & 2817 init(size_type size) 2818 { 2819 SparseHistStor::Params *params = new SparseHistStor::Params; 2820 this->setParams(params); 2821 this->doInit(); 2822 return this->self(); 2823 } 2824}; 2825 2826class Temp; 2827/** 2828 * A formula for statistics that is calculated when printed. A formula is 2829 * stored as a tree of Nodes that represent the equation to calculate. 2830 * @sa Stat, ScalarStat, VectorStat, Node, Temp 2831 */ 2832class Formula : public DataWrapVec<Formula, FormulaInfoProxy> 2833{ 2834 protected: 2835 /** The root of the tree which represents the Formula */ 2836 NodePtr root; 2837 friend class Temp; 2838 2839 public: 2840 /** 2841 * Create and initialize thie formula, and register it with the database. 2842 */ 2843 Formula(); 2844 2845 /** 2846 * Create a formula with the given root node, register it with the 2847 * database. 2848 * @param r The root of the expression tree. 2849 */ 2850 Formula(Temp r); 2851 2852 /** 2853 * Set an unitialized Formula to the given root. 2854 * @param r The root of the expression tree. 2855 * @return a reference to this formula. 2856 */ 2857 const Formula &operator=(Temp r); 2858 2859 /** 2860 * Add the given tree to the existing one. 2861 * @param r The root of the expression tree. 2862 * @return a reference to this formula. 2863 */ 2864 const Formula &operator+=(Temp r); 2865 2866 /** 2867 * Divide the existing tree by the given one. 2868 * @param r The root of the expression tree. 2869 * @return a reference to this formula. 2870 */ 2871 const Formula &operator/=(Temp r); 2872 2873 /** 2874 * Return the result of the Fomula in a vector. If there were no Vector 2875 * components to the Formula, then the vector is size 1. If there were, 2876 * like x/y with x being a vector of size 3, then the result returned will 2877 * be x[0]/y, x[1]/y, x[2]/y, respectively. 2878 * @return The result vector. 2879 */ 2880 void result(VResult &vec) const; 2881 2882 /** 2883 * Return the total Formula result. If there is a Vector 2884 * component to this Formula, then this is the result of the 2885 * Formula if the formula is applied after summing all the 2886 * components of the Vector. For example, if Formula is x/y where 2887 * x is size 3, then total() will return (x[1]+x[2]+x[3])/y. If 2888 * there is no Vector component, total() returns the same value as 2889 * the first entry in the VResult val() returns. 2890 * @return The total of the result vector. 2891 */ 2892 Result total() const; 2893 2894 /** 2895 * Return the number of elements in the tree. 2896 */ 2897 size_type size() const; 2898 2899 void prepare() { } 2900 2901 /** 2902 * Formulas don't need to be reset 2903 */ 2904 void reset(); 2905 2906 /** 2907 * 2908 */ 2909 bool zero() const; 2910 2911 std::string str() const; 2912}; 2913 2914class FormulaNode : public Node 2915{ 2916 private: 2917 const Formula &formula; 2918 mutable VResult vec; 2919 2920 public: 2921 FormulaNode(const Formula &f) : formula(f) {} 2922 2923 size_type size() const { return formula.size(); } 2924 const VResult &result() const { formula.result(vec); return vec; } 2925 Result total() const { return formula.total(); } 2926 2927 std::string str() const { return formula.str(); } 2928}; 2929 2930/** 2931 * Helper class to construct formula node trees. 2932 */ 2933class Temp 2934{ 2935 protected: 2936 /** 2937 * Pointer to a Node object. 2938 */ 2939 NodePtr node; 2940 2941 public: 2942 /** 2943 * Copy the given pointer to this class. 2944 * @param n A pointer to a Node object to copy. 2945 */ 2946 Temp(NodePtr n) : node(n) { } 2947 2948 /** 2949 * Return the node pointer. 2950 * @return the node pointer. 2951 */ 2952 operator NodePtr&() { return node; } 2953 2954 public: 2955 /** 2956 * Create a new ScalarStatNode. 2957 * @param s The ScalarStat to place in a node. 2958 */ 2959 Temp(const Scalar &s) 2960 : node(new ScalarStatNode(s.info())) 2961 { } 2962 2963 /** 2964 * Create a new ScalarStatNode. 2965 * @param s The ScalarStat to place in a node. 2966 */ 2967 Temp(const Value &s) 2968 : node(new ScalarStatNode(s.info())) 2969 { } 2970 2971 /** 2972 * Create a new ScalarStatNode. 2973 * @param s The ScalarStat to place in a node. 2974 */ 2975 Temp(const Average &s) 2976 : node(new ScalarStatNode(s.info())) 2977 { } 2978 2979 /** 2980 * Create a new VectorStatNode. 2981 * @param s The VectorStat to place in a node. 2982 */ 2983 Temp(const Vector &s) 2984 : node(new VectorStatNode(s.info())) 2985 { } 2986 2987 Temp(const AverageVector &s) 2988 : node(new VectorStatNode(s.info())) 2989 { } 2990 2991 /** 2992 * 2993 */ 2994 Temp(const Formula &f) 2995 : node(new FormulaNode(f)) 2996 { } 2997 2998 /** 2999 * Create a new ScalarProxyNode. 3000 * @param p The ScalarProxy to place in a node. 3001 */ 3002 template <class Stat> 3003 Temp(const ScalarProxy<Stat> &p) 3004 : node(new ScalarProxyNode<Stat>(p)) 3005 { } 3006 3007 /** 3008 * Create a ConstNode 3009 * @param value The value of the const node. 3010 */ 3011 Temp(signed char value) 3012 : node(new ConstNode<signed char>(value)) 3013 { } 3014 3015 /** 3016 * Create a ConstNode 3017 * @param value The value of the const node. 3018 */ 3019 Temp(unsigned char value) 3020 : node(new ConstNode<unsigned char>(value)) 3021 { } 3022 3023 /** 3024 * Create a ConstNode 3025 * @param value The value of the const node. 3026 */ 3027 Temp(signed short value) 3028 : node(new ConstNode<signed short>(value)) 3029 { } 3030 3031 /** 3032 * Create a ConstNode 3033 * @param value The value of the const node. 3034 */ 3035 Temp(unsigned short value) 3036 : node(new ConstNode<unsigned short>(value)) 3037 { } 3038 3039 /** 3040 * Create a ConstNode 3041 * @param value The value of the const node. 3042 */ 3043 Temp(signed int value) 3044 : node(new ConstNode<signed int>(value)) 3045 { } 3046 3047 /** 3048 * Create a ConstNode 3049 * @param value The value of the const node. 3050 */ 3051 Temp(unsigned int value) 3052 : node(new ConstNode<unsigned int>(value)) 3053 { } 3054 3055 /** 3056 * Create a ConstNode 3057 * @param value The value of the const node. 3058 */ 3059 Temp(signed long value) 3060 : node(new ConstNode<signed long>(value)) 3061 { } 3062 3063 /** 3064 * Create a ConstNode 3065 * @param value The value of the const node. 3066 */ 3067 Temp(unsigned long value) 3068 : node(new ConstNode<unsigned long>(value)) 3069 { } 3070 3071 /** 3072 * Create a ConstNode 3073 * @param value The value of the const node. 3074 */ 3075 Temp(signed long long value) 3076 : node(new ConstNode<signed long long>(value)) 3077 { } 3078 3079 /** 3080 * Create a ConstNode 3081 * @param value The value of the const node. 3082 */ 3083 Temp(unsigned long long value) 3084 : node(new ConstNode<unsigned long long>(value)) 3085 { } 3086 3087 /** 3088 * Create a ConstNode 3089 * @param value The value of the const node. 3090 */ 3091 Temp(float value) 3092 : node(new ConstNode<float>(value)) 3093 { } 3094 3095 /** 3096 * Create a ConstNode 3097 * @param value The value of the const node. 3098 */ 3099 Temp(double value) 3100 : node(new ConstNode<double>(value)) 3101 { } 3102}; 3103 3104 3105/** 3106 * @} 3107 */ 3108 3109inline Temp 3110operator+(Temp l, Temp r) 3111{ 3112 return NodePtr(new BinaryNode<std::plus<Result> >(l, r)); 3113} 3114 3115inline Temp 3116operator-(Temp l, Temp r) 3117{ 3118 return NodePtr(new BinaryNode<std::minus<Result> >(l, r)); 3119} 3120 3121inline Temp 3122operator*(Temp l, Temp r) 3123{ 3124 return NodePtr(new BinaryNode<std::multiplies<Result> >(l, r)); 3125} 3126 3127inline Temp 3128operator/(Temp l, Temp r) 3129{ 3130 return NodePtr(new BinaryNode<std::divides<Result> >(l, r)); 3131} 3132 3133inline Temp 3134operator-(Temp l) 3135{ 3136 return NodePtr(new UnaryNode<std::negate<Result> >(l)); 3137} 3138 3139template <typename T> 3140inline Temp 3141constant(T val) 3142{ 3143 return NodePtr(new ConstNode<T>(val)); 3144} 3145 3146template <typename T> 3147inline Temp 3148constantVector(T val) 3149{ 3150 return NodePtr(new ConstVectorNode<T>(val)); 3151} 3152 3153inline Temp 3154sum(Temp val) 3155{ 3156 return NodePtr(new SumNode<std::plus<Result> >(val)); 3157} 3158 3159/** Dump all statistics data to the registered outputs */ 3160void dump(); 3161void reset(); 3162void enable(); 3163bool enabled(); 3164 3165/** 3166 * Register a callback that should be called whenever statistics are 3167 * reset 3168 */ 3169void registerResetCallback(Callback *cb); 3170 3171/** 3172 * Register a callback that should be called whenever statistics are 3173 * about to be dumped 3174 */ 3175void registerDumpCallback(Callback *cb); 3176 3177std::list<Info *> &statsList(); 3178 3179typedef std::map<const void *, Info *> MapType; 3180MapType &statsMap(); 3181 3182typedef std::map<std::string, Info *> NameMapType; 3183NameMapType &nameMap(); 3184 3185bool validateStatName(const std::string &name); 3186 3187} // namespace Stats 3188 3189void debugDumpStats(); 3190 3191#endif // __BASE_STATISTICS_HH__ 3192