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
| 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
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334 // The following functions are specific to vectors. If you use them 335 // in a non vector context, you will get a nice compiler error! 336 337 /** 338 * Set the subfield name for the given index, and marks this stat to print 339 * at the end of simulation. 340 * @param index The subfield index. 341 * @param name The new name of the subfield. 342 * @return A reference to this stat. 343 */ 344 Derived & 345 subname(off_type index, const std::string &name) 346 { 347 Derived &self = this->self(); 348 Info *info = self.info(); 349 350 std::vector<std::string> &subn = info->subnames; 351 if (subn.size() <= index) 352 subn.resize(index + 1); 353 subn[index] = name; 354 return self; 355 } 356 357 // The following functions are specific to 2d vectors. If you use 358 // them in a non vector context, you will get a nice compiler 359 // error because info doesn't have the right variables. 360 361 /** 362 * Set the subfield description for the given index and marks this stat to 363 * print at the end of simulation. 364 * @param index The subfield index. 365 * @param desc The new description of the subfield 366 * @return A reference to this stat. 367 */ 368 Derived & 369 subdesc(off_type index, const std::string &desc) 370 { 371 Info *info = this->info(); 372 373 std::vector<std::string> &subd = info->subdescs; 374 if (subd.size() <= index) 375 subd.resize(index + 1); 376 subd[index] = desc; 377 378 return this->self(); 379 } 380 381 void 382 prepare() 383 { 384 Derived &self = this->self(); 385 Info *info = this->info(); 386 387 size_t size = self.size(); 388 for (off_type i = 0; i < size; ++i) 389 self.data(i)->prepare(info); 390 } 391 392 void 393 reset() 394 { 395 Derived &self = this->self(); 396 Info *info = this->info(); 397 398 size_t size = self.size(); 399 for (off_type i = 0; i < size; ++i) 400 self.data(i)->reset(info); 401 } 402}; 403 404template <class Derived, template <class> class InfoProxyType> 405class DataWrapVec2d : public DataWrapVec<Derived, InfoProxyType> 406{ 407 public: 408 typedef InfoProxyType<Derived> Info; 409 410 /** 411 * @warning This makes the assumption that if you're gonna subnames a 2d 412 * vector, you're subnaming across all y 413 */ 414 Derived & 415 ysubnames(const char **names) 416 { 417 Derived &self = this->self(); 418 Info *info = this->info(); 419 420 info->y_subnames.resize(self.y); 421 for (off_type i = 0; i < self.y; ++i) 422 info->y_subnames[i] = names[i]; 423 return self; 424 } 425 426 Derived & 427 ysubname(off_type index, const std::string &subname) 428 { 429 Derived &self = this->self(); 430 Info *info = this->info(); 431 432 assert(index < self.y); 433 info->y_subnames.resize(self.y); 434 info->y_subnames[index] = subname.c_str(); 435 return self; 436 } 437 438 std::string 439 ysubname(off_type i) const 440 { 441 return this->info()->y_subnames[i]; 442 } 443 444}; 445 446////////////////////////////////////////////////////////////////////// 447// 448// Simple Statistics 449// 450////////////////////////////////////////////////////////////////////// 451 452/** 453 * Templatized storage and interface for a simple scalar stat. 454 */ 455class StatStor 456{ 457 private: 458 /** The statistic value. */ 459 Counter data; 460 461 public: 462 struct Params : public StorageParams {}; 463 464 public: 465 /** 466 * Builds this storage element and calls the base constructor of the 467 * datatype. 468 */ 469 StatStor(Info *info) 470 : data(Counter()) 471 { } 472 473 /** 474 * The the stat to the given value. 475 * @param val The new value. 476 */ 477 void set(Counter val) { data = val; } 478 /** 479 * Increment the stat by the given value. 480 * @param val The new value. 481 */ 482 void inc(Counter val) { data += val; } 483 /** 484 * Decrement the stat by the given value. 485 * @param val The new value. 486 */ 487 void dec(Counter val) { data -= val; } 488 /** 489 * Return the value of this stat as its base type. 490 * @return The value of this stat. 491 */ 492 Counter value() const { return data; } 493 /** 494 * Return the value of this stat as a result type. 495 * @return The value of this stat. 496 */ 497 Result result() const { return (Result)data; } 498 /** 499 * Prepare stat data for dumping or serialization 500 */ 501 void prepare(Info *info) { } 502 /** 503 * Reset stat value to default 504 */ 505 void reset(Info *info) { data = Counter(); } 506 507 /** 508 * @return true if zero value 509 */ 510 bool zero() const { return data == Counter(); } 511}; 512 513/** 514 * Templatized storage and interface to a per-tick average stat. This keeps 515 * a current count and updates a total (count * ticks) when this count 516 * changes. This allows the quick calculation of a per tick count of the item 517 * being watched. This is good for keeping track of residencies in structures 518 * among other things. 519 */ 520class AvgStor 521{ 522 private: 523 /** The current count. */ 524 Counter current; 525 /** The tick of the last reset */ 526 Tick lastReset; 527 /** The total count for all tick. */ 528 mutable Result total; 529 /** The tick that current last changed. */ 530 mutable Tick last; 531 532 public: 533 struct Params : public StorageParams {}; 534 535 public: 536 /** 537 * Build and initializes this stat storage. 538 */ 539 AvgStor(Info *info) 540 : current(0), lastReset(0), total(0), last(0) 541 { } 542 543 /** 544 * Set the current count to the one provided, update the total and last 545 * set values. 546 * @param val The new count. 547 */ 548 void 549 set(Counter val) 550 { 551 total += current * (curTick() - last); 552 last = curTick(); 553 current = val; 554 } 555 556 /** 557 * Increment the current count by the provided value, calls set. 558 * @param val The amount to increment. 559 */ 560 void inc(Counter val) { set(current + val); } 561 562 /** 563 * Deccrement the current count by the provided value, calls set. 564 * @param val The amount to decrement. 565 */ 566 void dec(Counter val) { set(current - val); } 567 568 /** 569 * Return the current count. 570 * @return The current count. 571 */ 572 Counter value() const { return current; } 573 574 /** 575 * Return the current average. 576 * @return The current average. 577 */ 578 Result 579 result() const 580 { 581 assert(last == curTick()); 582 return (Result)(total + current) / (Result)(curTick() - lastReset + 1); 583 } 584 585 /** 586 * @return true if zero value 587 */ 588 bool zero() const { return total == 0.0; } 589 590 /** 591 * Prepare stat data for dumping or serialization 592 */ 593 void 594 prepare(Info *info) 595 { 596 total += current * (curTick() - last); 597 last = curTick(); 598 } 599 600 /** 601 * Reset stat value to default 602 */ 603 void 604 reset(Info *info) 605 { 606 total = 0.0; 607 last = curTick(); 608 lastReset = curTick(); 609 } 610 611}; 612 613/** 614 * Implementation of a scalar stat. The type of stat is determined by the 615 * Storage template. 616 */ 617template <class Derived, class Stor> 618class ScalarBase : public DataWrap<Derived, ScalarInfoProxy> 619{ 620 public: 621 typedef Stor Storage; 622 typedef typename Stor::Params Params; 623 624 protected: 625 /** The storage of this stat. */ 626 char storage[sizeof(Storage)] __attribute__ ((aligned (8))); 627 628 protected: 629 /** 630 * Retrieve the storage. 631 * @param index The vector index to access. 632 * @return The storage object at the given index. 633 */ 634 Storage * 635 data() 636 { 637 return reinterpret_cast<Storage *>(storage); 638 } 639 640 /** 641 * Retrieve a const pointer to the storage. 642 * for the given index. 643 * @param index The vector index to access. 644 * @return A const pointer to the storage object at the given index. 645 */ 646 const Storage * 647 data() const 648 { 649 return reinterpret_cast<const Storage *>(storage); 650 } 651 652 void 653 doInit() 654 { 655 new (storage) Storage(this->info()); 656 this->setInit(); 657 } 658 659 public: 660 /** 661 * Return the current value of this stat as its base type. 662 * @return The current value. 663 */ 664 Counter value() const { return data()->value(); } 665 666 public: 667 ScalarBase() 668 { 669 this->doInit(); 670 } 671 672 public: 673 // Common operators for stats 674 /** 675 * Increment the stat by 1. This calls the associated storage object inc 676 * function. 677 */ 678 void operator++() { data()->inc(1); } 679 /** 680 * Decrement the stat by 1. This calls the associated storage object dec 681 * function. 682 */ 683 void operator--() { data()->dec(1); } 684 685 /** Increment the stat by 1. */ 686 void operator++(int) { ++*this; } 687 /** Decrement the stat by 1. */ 688 void operator--(int) { --*this; } 689 690 /** 691 * Set the data value to the given value. This calls the associated storage 692 * object set function. 693 * @param v The new value. 694 */ 695 template <typename U> 696 void operator=(const U &v) { data()->set(v); } 697 698 /** 699 * Increment the stat by the given value. This calls the associated 700 * storage object inc function. 701 * @param v The value to add. 702 */ 703 template <typename U> 704 void operator+=(const U &v) { data()->inc(v); } 705 706 /** 707 * Decrement the stat by the given value. This calls the associated 708 * storage object dec function. 709 * @param v The value to substract. 710 */ 711 template <typename U> 712 void operator-=(const U &v) { data()->dec(v); } 713 714 /** 715 * Return the number of elements, always 1 for a scalar. 716 * @return 1. 717 */ 718 size_type size() const { return 1; } 719 720 Counter value() { return data()->value(); } 721 722 Result result() { return data()->result(); } 723 724 Result total() { return result(); } 725 726 bool zero() { return result() == 0.0; } 727 728 void reset() { data()->reset(this->info()); } 729 void prepare() { data()->prepare(this->info()); } 730}; 731 732class ProxyInfo : public ScalarInfo 733{ 734 public: 735 std::string str() const { return to_string(value()); } 736 size_type size() const { return 1; } 737 bool check() const { return true; } 738 void prepare() { } 739 void reset() { } 740 bool zero() const { return value() == 0; } 741 742 void visit(Output &visitor) { visitor.visit(*this); } 743}; 744 745template <class T> 746class ValueProxy : public ProxyInfo 747{ 748 private: 749 T *scalar; 750 751 public: 752 ValueProxy(T &val) : scalar(&val) {} 753 Counter value() const { return *scalar; } 754 Result result() const { return *scalar; } 755 Result total() const { return *scalar; } 756}; 757 758template <class T> 759class FunctorProxy : public ProxyInfo 760{ 761 private: 762 T *functor; 763 764 public: 765 FunctorProxy(T &func) : functor(&func) {} 766 Counter value() const { return (*functor)(); } 767 Result result() const { return (*functor)(); } 768 Result total() const { return (*functor)(); } 769}; 770 771template <class Derived> 772class ValueBase : public DataWrap<Derived, ScalarInfoProxy> 773{ 774 private: 775 ProxyInfo *proxy; 776 777 public: 778 ValueBase() : proxy(NULL) { } 779 ~ValueBase() { if (proxy) delete proxy; } 780 781 template <class T> 782 Derived & 783 scalar(T &value) 784 { 785 proxy = new ValueProxy<T>(value); 786 this->setInit(); 787 return this->self(); 788 } 789 790 template <class T> 791 Derived & 792 functor(T &func) 793 { 794 proxy = new FunctorProxy<T>(func); 795 this->setInit(); 796 return this->self(); 797 } 798 799 Counter value() { return proxy->value(); } 800 Result result() const { return proxy->result(); } 801 Result total() const { return proxy->total(); }; 802 size_type size() const { return proxy->size(); } 803 804 std::string str() const { return proxy->str(); } 805 bool zero() const { return proxy->zero(); } 806 bool check() const { return proxy != NULL; } 807 void prepare() { } 808 void reset() { } 809}; 810 811////////////////////////////////////////////////////////////////////// 812// 813// Vector Statistics 814// 815////////////////////////////////////////////////////////////////////// 816 817/** 818 * A proxy class to access the stat at a given index in a VectorBase stat. 819 * Behaves like a ScalarBase. 820 */ 821template <class Stat> 822class ScalarProxy 823{ 824 private: 825 /** Pointer to the parent Vector. */ 826 Stat &stat; 827 828 /** The index to access in the parent VectorBase. */ 829 off_type index; 830 831 public: 832 /** 833 * Return the current value of this stat as its base type. 834 * @return The current value. 835 */ 836 Counter value() const { return stat.data(index)->value(); } 837 838 /** 839 * Return the current value of this statas a result type. 840 * @return The current value. 841 */ 842 Result result() const { return stat.data(index)->result(); } 843 844 public: 845 /** 846 * Create and initialize this proxy, do not register it with the database. 847 * @param i The index to access. 848 */ 849 ScalarProxy(Stat &s, off_type i) 850 : stat(s), index(i) 851 { 852 } 853 854 /** 855 * Create a copy of the provided ScalarProxy. 856 * @param sp The proxy to copy. 857 */ 858 ScalarProxy(const ScalarProxy &sp) 859 : stat(sp.stat), index(sp.index) 860 {} 861 862 /** 863 * Set this proxy equal to the provided one. 864 * @param sp The proxy to copy. 865 * @return A reference to this proxy. 866 */ 867 const ScalarProxy & 868 operator=(const ScalarProxy &sp) 869 { 870 stat = sp.stat; 871 index = sp.index; 872 return *this; 873 } 874 875 public: 876 // Common operators for stats 877 /** 878 * Increment the stat by 1. This calls the associated storage object inc 879 * function. 880 */ 881 void operator++() { stat.data(index)->inc(1); } 882 /** 883 * Decrement the stat by 1. This calls the associated storage object dec 884 * function. 885 */ 886 void operator--() { stat.data(index)->dec(1); } 887 888 /** Increment the stat by 1. */ 889 void operator++(int) { ++*this; } 890 /** Decrement the stat by 1. */ 891 void operator--(int) { --*this; } 892 893 /** 894 * Set the data value to the given value. This calls the associated storage 895 * object set function. 896 * @param v The new value. 897 */ 898 template <typename U> 899 void 900 operator=(const U &v) 901 { 902 stat.data(index)->set(v); 903 } 904 905 /** 906 * Increment the stat by the given value. This calls the associated 907 * storage object inc function. 908 * @param v The value to add. 909 */ 910 template <typename U> 911 void 912 operator+=(const U &v) 913 { 914 stat.data(index)->inc(v); 915 } 916 917 /** 918 * Decrement the stat by the given value. This calls the associated 919 * storage object dec function. 920 * @param v The value to substract. 921 */ 922 template <typename U> 923 void 924 operator-=(const U &v) 925 { 926 stat.data(index)->dec(v); 927 } 928 929 /** 930 * Return the number of elements, always 1 for a scalar. 931 * @return 1. 932 */ 933 size_type size() const { return 1; } 934 935 public: 936 std::string 937 str() const 938 { 939 return csprintf("%s[%d]", stat.info()->name, index); 940 } 941}; 942 943/** 944 * Implementation of a vector of stats. The type of stat is determined by the 945 * Storage class. @sa ScalarBase 946 */ 947template <class Derived, class Stor> 948class VectorBase : public DataWrapVec<Derived, VectorInfoProxy> 949{ 950 public: 951 typedef Stor Storage; 952 typedef typename Stor::Params Params; 953 954 /** Proxy type */ 955 typedef ScalarProxy<Derived> Proxy; 956 friend class ScalarProxy<Derived>; 957 friend class DataWrapVec<Derived, VectorInfoProxy>; 958 959 protected: 960 /** The storage of this stat. */ 961 Storage *storage; 962 size_type _size; 963 964 protected: 965 /** 966 * Retrieve the storage. 967 * @param index The vector index to access. 968 * @return The storage object at the given index. 969 */ 970 Storage *data(off_type index) { return &storage[index]; } 971 972 /** 973 * Retrieve a const pointer to the storage. 974 * @param index The vector index to access. 975 * @return A const pointer to the storage object at the given index. 976 */ 977 const Storage *data(off_type index) const { return &storage[index]; } 978 979 void 980 doInit(size_type s) 981 { 982 assert(s > 0 && "size must be positive!"); 983 assert(!storage && "already initialized"); 984 _size = s; 985 986 char *ptr = new char[_size * sizeof(Storage)]; 987 storage = reinterpret_cast<Storage *>(ptr); 988 989 for (off_type i = 0; i < _size; ++i) 990 new (&storage[i]) Storage(this->info()); 991 992 this->setInit(); 993 } 994 995 public: 996 void 997 value(VCounter &vec) const 998 { 999 vec.resize(size()); 1000 for (off_type i = 0; i < size(); ++i) 1001 vec[i] = data(i)->value(); 1002 } 1003 1004 /** 1005 * Copy the values to a local vector and return a reference to it. 1006 * @return A reference to a vector of the stat values. 1007 */ 1008 void 1009 result(VResult &vec) const 1010 { 1011 vec.resize(size()); 1012 for (off_type i = 0; i < size(); ++i) 1013 vec[i] = data(i)->result(); 1014 } 1015 1016 /** 1017 * Return a total of all entries in this vector. 1018 * @return The total of all vector entries. 1019 */ 1020 Result 1021 total() const 1022 { 1023 Result total = 0.0; 1024 for (off_type i = 0; i < size(); ++i) 1025 total += data(i)->result(); 1026 return total; 1027 } 1028 1029 /** 1030 * @return the number of elements in this vector. 1031 */ 1032 size_type size() const { return _size; } 1033 1034 bool 1035 zero() const 1036 { 1037 for (off_type i = 0; i < size(); ++i) 1038 if (data(i)->zero()) 1039 return false; 1040 return true; 1041 } 1042 1043 bool 1044 check() const 1045 { 1046 return storage != NULL; 1047 } 1048 1049 public: 1050 VectorBase() 1051 : storage(NULL) 1052 {} 1053 1054 ~VectorBase() 1055 { 1056 if (!storage) 1057 return; 1058 1059 for (off_type i = 0; i < _size; ++i) 1060 data(i)->~Storage(); 1061 delete [] reinterpret_cast<char *>(storage); 1062 } 1063 1064 /** 1065 * Set this vector to have the given size. 1066 * @param size The new size. 1067 * @return A reference to this stat. 1068 */ 1069 Derived & 1070 init(size_type size) 1071 { 1072 Derived &self = this->self(); 1073 self.doInit(size); 1074 return self; 1075 } 1076 1077 /** 1078 * Return a reference (ScalarProxy) to the stat at the given index. 1079 * @param index The vector index to access. 1080 * @return A reference of the stat. 1081 */ 1082 Proxy 1083 operator[](off_type index) 1084 { 1085 assert (index >= 0 && index < size()); 1086 return Proxy(this->self(), index); 1087 } 1088}; 1089 1090template <class Stat> 1091class VectorProxy 1092{ 1093 private: 1094 Stat &stat; 1095 off_type offset; 1096 size_type len; 1097 1098 private: 1099 mutable VResult vec; 1100 1101 typename Stat::Storage * 1102 data(off_type index) 1103 { 1104 assert(index < len); 1105 return stat.data(offset + index); 1106 } 1107 1108 const typename Stat::Storage * 1109 data(off_type index) const 1110 { 1111 assert(index < len); 1112 return stat.data(offset + index); 1113 } 1114 1115 public: 1116 const VResult & 1117 result() const 1118 { 1119 vec.resize(size()); 1120 1121 for (off_type i = 0; i < size(); ++i) 1122 vec[i] = data(i)->result(); 1123 1124 return vec; 1125 } 1126 1127 Result 1128 total() const 1129 { 1130 Result total = 0.0; 1131 for (off_type i = 0; i < size(); ++i) 1132 total += data(i)->result(); 1133 return total; 1134 } 1135 1136 public: 1137 VectorProxy(Stat &s, off_type o, size_type l) 1138 : stat(s), offset(o), len(l) 1139 { 1140 } 1141 1142 VectorProxy(const VectorProxy &sp) 1143 : stat(sp.stat), offset(sp.offset), len(sp.len) 1144 { 1145 } 1146 1147 const VectorProxy & 1148 operator=(const VectorProxy &sp) 1149 { 1150 stat = sp.stat; 1151 offset = sp.offset; 1152 len = sp.len; 1153 return *this; 1154 } 1155 1156 ScalarProxy<Stat> 1157 operator[](off_type index) 1158 { 1159 assert (index >= 0 && index < size()); 1160 return ScalarProxy<Stat>(stat, offset + index); 1161 } 1162 1163 size_type size() const { return len; } 1164}; 1165 1166template <class Derived, class Stor> 1167class Vector2dBase : public DataWrapVec2d<Derived, Vector2dInfoProxy> 1168{ 1169 public: 1170 typedef Vector2dInfoProxy<Derived> Info; 1171 typedef Stor Storage; 1172 typedef typename Stor::Params Params; 1173 typedef VectorProxy<Derived> Proxy; 1174 friend class ScalarProxy<Derived>; 1175 friend class VectorProxy<Derived>; 1176 friend class DataWrapVec<Derived, Vector2dInfoProxy>; 1177 friend class DataWrapVec2d<Derived, Vector2dInfoProxy>; 1178 1179 protected: 1180 size_type x; 1181 size_type y; 1182 size_type _size; 1183 Storage *storage; 1184 1185 protected: 1186 Storage *data(off_type index) { return &storage[index]; } 1187 const Storage *data(off_type index) const { return &storage[index]; } 1188 1189 public: 1190 Vector2dBase() 1191 : storage(NULL) 1192 {} 1193 1194 ~Vector2dBase() 1195 { 1196 if (!storage) 1197 return; 1198 1199 for (off_type i = 0; i < _size; ++i) 1200 data(i)->~Storage(); 1201 delete [] reinterpret_cast<char *>(storage); 1202 } 1203 1204 Derived & 1205 init(size_type _x, size_type _y) 1206 { 1207 assert(_x > 0 && _y > 0 && "sizes must be positive!"); 1208 assert(!storage && "already initialized"); 1209 1210 Derived &self = this->self(); 1211 Info *info = this->info(); 1212 1213 x = _x; 1214 y = _y; 1215 info->x = _x; 1216 info->y = _y; 1217 _size = x * y; 1218 1219 char *ptr = new char[_size * sizeof(Storage)]; 1220 storage = reinterpret_cast<Storage *>(ptr); 1221 1222 for (off_type i = 0; i < _size; ++i) 1223 new (&storage[i]) Storage(info); 1224 1225 this->setInit(); 1226 1227 return self; 1228 } 1229 1230 Proxy 1231 operator[](off_type index) 1232 { 1233 off_type offset = index * y; 1234 assert (index >= 0 && offset + y <= size()); 1235 return Proxy(this->self(), offset, y); 1236 } 1237 1238 1239 size_type 1240 size() const 1241 { 1242 return _size; 1243 } 1244 1245 bool 1246 zero() const 1247 { 1248 return data(0)->zero(); 1249#if 0 1250 for (off_type i = 0; i < size(); ++i) 1251 if (!data(i)->zero()) 1252 return false; 1253 return true; 1254#endif 1255 } 1256 1257 void 1258 prepare() 1259 { 1260 Info *info = this->info(); 1261 size_type size = this->size(); 1262 1263 for (off_type i = 0; i < size; ++i) 1264 data(i)->prepare(info); 1265 1266 info->cvec.resize(size); 1267 for (off_type i = 0; i < size; ++i) 1268 info->cvec[i] = data(i)->value(); 1269 } 1270 1271 /** 1272 * Reset stat value to default 1273 */ 1274 void 1275 reset() 1276 { 1277 Info *info = this->info(); 1278 size_type size = this->size(); 1279 for (off_type i = 0; i < size; ++i) 1280 data(i)->reset(info); 1281 } 1282 1283 bool 1284 check() const 1285 { 1286 return storage != NULL; 1287 } 1288}; 1289 1290////////////////////////////////////////////////////////////////////// 1291// 1292// Non formula statistics 1293// 1294////////////////////////////////////////////////////////////////////// 1295/** The parameters for a distribution stat. */ 1296struct DistParams : public StorageParams 1297{ 1298 const DistType type; 1299 DistParams(DistType t) : type(t) {} 1300}; 1301 1302/** 1303 * Templatized storage and interface for a distrbution stat. 1304 */ 1305class DistStor 1306{ 1307 public: 1308 /** The parameters for a distribution stat. */ 1309 struct Params : public DistParams 1310 { 1311 /** The minimum value to track. */ 1312 Counter min; 1313 /** The maximum value to track. */ 1314 Counter max; 1315 /** The number of entries in each bucket. */ 1316 Counter bucket_size; 1317 /** The number of buckets. Equal to (max-min)/bucket_size. */ 1318 size_type buckets; 1319 1320 Params() : DistParams(Dist) {} 1321 }; 1322 1323 private: 1324 /** The minimum value to track. */ 1325 Counter min_track; 1326 /** The maximum value to track. */ 1327 Counter max_track; 1328 /** The number of entries in each bucket. */ 1329 Counter bucket_size; 1330 1331 /** The smallest value sampled. */ 1332 Counter min_val; 1333 /** The largest value sampled. */ 1334 Counter max_val; 1335 /** The number of values sampled less than min. */ 1336 Counter underflow; 1337 /** The number of values sampled more than max. */ 1338 Counter overflow; 1339 /** The current sum. */ 1340 Counter sum; 1341 /** The sum of squares. */ 1342 Counter squares; 1343 /** The number of samples. */ 1344 Counter samples; 1345 /** Counter for each bucket. */ 1346 VCounter cvec; 1347 1348 public: 1349 DistStor(Info *info) 1350 : cvec(safe_cast<const Params *>(info->storageParams)->buckets) 1351 { 1352 reset(info); 1353 } 1354 1355 /** 1356 * Add a value to the distribution for the given number of times. 1357 * @param val The value to add. 1358 * @param number The number of times to add the value. 1359 */ 1360 void 1361 sample(Counter val, int number) 1362 { 1363 if (val < min_track) 1364 underflow += number; 1365 else if (val > max_track) 1366 overflow += number; 1367 else { 1368 size_type index = 1369 (size_type)std::floor((val - min_track) / bucket_size); 1370 assert(index < size()); 1371 cvec[index] += number; 1372 } 1373 1374 if (val < min_val) 1375 min_val = val; 1376 1377 if (val > max_val) 1378 max_val = val; 1379 1380 sum += val * number; 1381 squares += val * val * number; 1382 samples += number; 1383 } 1384 1385 /** 1386 * Return the number of buckets in this distribution. 1387 * @return the number of buckets. 1388 */ 1389 size_type size() const { return cvec.size(); } 1390 1391 /** 1392 * Returns true if any calls to sample have been made. 1393 * @return True if any values have been sampled. 1394 */ 1395 bool 1396 zero() const 1397 { 1398 return samples == Counter(); 1399 } 1400 1401 void 1402 prepare(Info *info, DistData &data) 1403 { 1404 const Params *params = safe_cast<const Params *>(info->storageParams); 1405 1406 assert(params->type == Dist); 1407 data.type = params->type; 1408 data.min = params->min; 1409 data.max = params->max; 1410 data.bucket_size = params->bucket_size; 1411 1412 data.min_val = (min_val == CounterLimits::max()) ? 0 : min_val; 1413 data.max_val = (max_val == CounterLimits::min()) ? 0 : max_val; 1414 data.underflow = underflow; 1415 data.overflow = overflow; 1416 1417 data.cvec.resize(params->buckets); 1418 for (off_type i = 0; i < params->buckets; ++i) 1419 data.cvec[i] = cvec[i]; 1420 1421 data.sum = sum; 1422 data.squares = squares; 1423 data.samples = samples; 1424 } 1425 1426 /** 1427 * Reset stat value to default 1428 */ 1429 void 1430 reset(Info *info) 1431 { 1432 const Params *params = safe_cast<const Params *>(info->storageParams); 1433 min_track = params->min; 1434 max_track = params->max; 1435 bucket_size = params->bucket_size; 1436 1437 min_val = CounterLimits::max(); 1438 max_val = CounterLimits::min(); 1439 underflow = Counter(); 1440 overflow = Counter(); 1441 1442 size_type size = cvec.size(); 1443 for (off_type i = 0; i < size; ++i) 1444 cvec[i] = Counter(); 1445 1446 sum = Counter(); 1447 squares = Counter(); 1448 samples = Counter(); 1449 } 1450}; 1451 1452/** 1453 * Templatized storage and interface for a histogram stat. 1454 */ 1455class HistStor 1456{ 1457 public: 1458 /** The parameters for a distribution stat. */ 1459 struct Params : public DistParams 1460 { 1461 /** The number of buckets.. */ 1462 size_type buckets; 1463 1464 Params() : DistParams(Hist) {} 1465 }; 1466 1467 private: 1468 /** The minimum value to track. */ 1469 Counter min_bucket; 1470 /** The maximum value to track. */ 1471 Counter max_bucket; 1472 /** The number of entries in each bucket. */ 1473 Counter bucket_size; 1474 1475 /** The current sum. */ 1476 Counter sum; 1477 /** The sum of logarithm of each sample, used to compute geometric mean. */ 1478 Counter logs; 1479 /** The sum of squares. */ 1480 Counter squares; 1481 /** The number of samples. */ 1482 Counter samples; 1483 /** Counter for each bucket. */ 1484 VCounter cvec; 1485 1486 public: 1487 HistStor(Info *info) 1488 : cvec(safe_cast<const Params *>(info->storageParams)->buckets) 1489 { 1490 reset(info); 1491 } 1492 1493 void grow_up(); 1494 void grow_out(); 1495 void grow_convert(); 1496 1497 /** 1498 * Add a value to the distribution for the given number of times. 1499 * @param val The value to add. 1500 * @param number The number of times to add the value. 1501 */ 1502 void 1503 sample(Counter val, int number) 1504 { 1505 assert(min_bucket < max_bucket); 1506 if (val < min_bucket) { 1507 if (min_bucket == 0) 1508 grow_convert(); 1509 1510 while (val < min_bucket) 1511 grow_out(); 1512 } else if (val >= max_bucket + bucket_size) { 1513 if (min_bucket == 0) { 1514 while (val >= max_bucket + bucket_size) 1515 grow_up(); 1516 } else { 1517 while (val >= max_bucket + bucket_size) 1518 grow_out(); 1519 } 1520 } 1521 1522 size_type index = 1523 (int64_t)std::floor((val - min_bucket) / bucket_size); 1524 1525 assert(index >= 0 && index < size()); 1526 cvec[index] += number; 1527 1528 sum += val * number; 1529 squares += val * val * number; 1530 logs += log(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.logs = logs; 1571 data.squares = squares; 1572 data.samples = samples; 1573 } 1574 1575 /** 1576 * Reset stat value to default 1577 */ 1578 void 1579 reset(Info *info) 1580 { 1581 const Params *params = safe_cast<const Params *>(info->storageParams); 1582 min_bucket = 0; 1583 max_bucket = params->buckets - 1; 1584 bucket_size = 1; 1585 1586 size_type size = cvec.size(); 1587 for (off_type i = 0; i < size; ++i) 1588 cvec[i] = Counter(); 1589 1590 sum = Counter(); 1591 squares = Counter(); 1592 samples = Counter(); 1593 logs = Counter(); 1594 } 1595}; 1596 1597/** 1598 * Templatized storage and interface for a distribution that calculates mean 1599 * and variance. 1600 */ 1601class SampleStor 1602{ 1603 public: 1604 struct Params : public DistParams 1605 { 1606 Params() : DistParams(Deviation) {} 1607 }; 1608 1609 private: 1610 /** The current sum. */ 1611 Counter sum; 1612 /** The sum of squares. */ 1613 Counter squares; 1614 /** The number of samples. */ 1615 Counter samples; 1616 1617 public: 1618 /** 1619 * Create and initialize this storage. 1620 */ 1621 SampleStor(Info *info) 1622 : sum(Counter()), squares(Counter()), samples(Counter()) 1623 { } 1624 1625 /** 1626 * Add a value the given number of times to this running average. 1627 * Update the running sum and sum of squares, increment the number of 1628 * values seen by the given number. 1629 * @param val The value to add. 1630 * @param number The number of times to add the value. 1631 */ 1632 void 1633 sample(Counter val, int number) 1634 { 1635 Counter value = val * number; 1636 sum += value; 1637 squares += value * value; 1638 samples += number; 1639 } 1640 1641 /** 1642 * Return the number of entries in this stat, 1 1643 * @return 1. 1644 */ 1645 size_type size() const { return 1; } 1646 1647 /** 1648 * Return true if no samples have been added. 1649 * @return True if no samples have been added. 1650 */ 1651 bool zero() const { return samples == Counter(); } 1652 1653 void 1654 prepare(Info *info, DistData &data) 1655 { 1656 const Params *params = safe_cast<const Params *>(info->storageParams); 1657 1658 assert(params->type == Deviation); 1659 data.type = params->type; 1660 data.sum = sum; 1661 data.squares = squares; 1662 data.samples = samples; 1663 } 1664 1665 /** 1666 * Reset stat value to default 1667 */ 1668 void 1669 reset(Info *info) 1670 { 1671 sum = Counter(); 1672 squares = Counter(); 1673 samples = Counter(); 1674 } 1675}; 1676 1677/** 1678 * Templatized storage for distribution that calculates per tick mean and 1679 * variance. 1680 */ 1681class AvgSampleStor 1682{ 1683 public: 1684 struct Params : public DistParams 1685 { 1686 Params() : DistParams(Deviation) {} 1687 }; 1688 1689 private: 1690 /** Current total. */ 1691 Counter sum; 1692 /** Current sum of squares. */ 1693 Counter squares; 1694 1695 public: 1696 /** 1697 * Create and initialize this storage. 1698 */ 1699 AvgSampleStor(Info *info) 1700 : sum(Counter()), squares(Counter()) 1701 {} 1702 1703 /** 1704 * Add a value to the distribution for the given number of times. 1705 * Update the running sum and sum of squares. 1706 * @param val The value to add. 1707 * @param number The number of times to add the value. 1708 */ 1709 void 1710 sample(Counter val, int number) 1711 { 1712 Counter value = val * number; 1713 sum += value; 1714 squares += value * value; 1715 } 1716 1717 /** 1718 * Return the number of entries, in this case 1. 1719 * @return 1. 1720 */ 1721 size_type size() const { return 1; } 1722 1723 /** 1724 * Return true if no samples have been added. 1725 * @return True if the sum is zero. 1726 */ 1727 bool zero() const { return sum == Counter(); } 1728 1729 void 1730 prepare(Info *info, DistData &data) 1731 { 1732 const Params *params = safe_cast<const Params *>(info->storageParams); 1733 1734 assert(params->type == Deviation); 1735 data.type = params->type; 1736 data.sum = sum; 1737 data.squares = squares; 1738 data.samples = curTick(); 1739 } 1740 1741 /** 1742 * Reset stat value to default 1743 */ 1744 void 1745 reset(Info *info) 1746 { 1747 sum = Counter(); 1748 squares = Counter(); 1749 } 1750}; 1751 1752/** 1753 * Implementation of a distribution stat. The type of distribution is 1754 * determined by the Storage template. @sa ScalarBase 1755 */ 1756template <class Derived, class Stor> 1757class DistBase : public DataWrap<Derived, DistInfoProxy> 1758{ 1759 public: 1760 typedef DistInfoProxy<Derived> Info; 1761 typedef Stor Storage; 1762 typedef typename Stor::Params Params; 1763 1764 protected: 1765 /** The storage for this stat. */ 1766 char storage[sizeof(Storage)] __attribute__ ((aligned (8))); 1767 1768 protected: 1769 /** 1770 * Retrieve the storage. 1771 * @return The storage object for this stat. 1772 */ 1773 Storage * 1774 data() 1775 { 1776 return reinterpret_cast<Storage *>(storage); 1777 } 1778 1779 /** 1780 * Retrieve a const pointer to the storage. 1781 * @return A const pointer to the storage object for this stat. 1782 */ 1783 const Storage * 1784 data() const 1785 { 1786 return reinterpret_cast<const Storage *>(storage); 1787 } 1788 1789 void 1790 doInit() 1791 { 1792 new (storage) Storage(this->info()); 1793 this->setInit(); 1794 } 1795 1796 public: 1797 DistBase() { } 1798 1799 /** 1800 * Add a value to the distribtion n times. Calls sample on the storage 1801 * class. 1802 * @param v The value to add. 1803 * @param n The number of times to add it, defaults to 1. 1804 */ 1805 template <typename U> 1806 void sample(const U &v, int n = 1) { data()->sample(v, n); } 1807 1808 /** 1809 * Return the number of entries in this stat. 1810 * @return The number of entries. 1811 */ 1812 size_type size() const { return data()->size(); } 1813 /** 1814 * Return true if no samples have been added. 1815 * @return True if there haven't been any samples. 1816 */ 1817 bool zero() const { return data()->zero(); } 1818 1819 void 1820 prepare() 1821 { 1822 Info *info = this->info(); 1823 data()->prepare(info, info->data); 1824 } 1825 1826 /** 1827 * Reset stat value to default 1828 */ 1829 void 1830 reset() 1831 { 1832 data()->reset(this->info()); 1833 } 1834}; 1835 1836template <class Stat> 1837class DistProxy; 1838 1839template <class Derived, class Stor> 1840class VectorDistBase : public DataWrapVec<Derived, VectorDistInfoProxy> 1841{ 1842 public: 1843 typedef VectorDistInfoProxy<Derived> Info; 1844 typedef Stor Storage; 1845 typedef typename Stor::Params Params; 1846 typedef DistProxy<Derived> Proxy; 1847 friend class DistProxy<Derived>; 1848 friend class DataWrapVec<Derived, VectorDistInfoProxy>; 1849 1850 protected: 1851 Storage *storage; 1852 size_type _size; 1853 1854 protected: 1855 Storage * 1856 data(off_type index) 1857 { 1858 return &storage[index]; 1859 } 1860 1861 const Storage * 1862 data(off_type index) const 1863 { 1864 return &storage[index]; 1865 } 1866 1867 void 1868 doInit(size_type s) 1869 { 1870 assert(s > 0 && "size must be positive!"); 1871 assert(!storage && "already initialized"); 1872 _size = s; 1873 1874 char *ptr = new char[_size * sizeof(Storage)]; 1875 storage = reinterpret_cast<Storage *>(ptr); 1876 1877 Info *info = this->info(); 1878 for (off_type i = 0; i < _size; ++i) 1879 new (&storage[i]) Storage(info); 1880 1881 this->setInit(); 1882 } 1883 1884 public: 1885 VectorDistBase() 1886 : storage(NULL) 1887 {} 1888 1889 ~VectorDistBase() 1890 { 1891 if (!storage) 1892 return ; 1893 1894 for (off_type i = 0; i < _size; ++i) 1895 data(i)->~Storage(); 1896 delete [] reinterpret_cast<char *>(storage); 1897 } 1898 1899 Proxy operator[](off_type index) 1900 { 1901 assert(index >= 0 && index < size()); 1902 return Proxy(this->self(), index); 1903 } 1904 1905 size_type 1906 size() const 1907 { 1908 return _size; 1909 } 1910 1911 bool 1912 zero() const 1913 { 1914 for (off_type i = 0; i < size(); ++i) 1915 if (!data(i)->zero()) 1916 return false; 1917 return true; 1918 } 1919 1920 void 1921 prepare() 1922 { 1923 Info *info = this->info(); 1924 size_type size = this->size(); 1925 info->data.resize(size); 1926 for (off_type i = 0; i < size; ++i) 1927 data(i)->prepare(info, info->data[i]); 1928 } 1929 1930 bool 1931 check() const 1932 { 1933 return storage != NULL; 1934 } 1935}; 1936 1937template <class Stat> 1938class DistProxy 1939{ 1940 private: 1941 Stat &stat; 1942 off_type index; 1943 1944 protected: 1945 typename Stat::Storage *data() { return stat.data(index); } 1946 const typename Stat::Storage *data() const { return stat.data(index); } 1947 1948 public: 1949 DistProxy(Stat &s, off_type i) 1950 : stat(s), index(i) 1951 {} 1952 1953 DistProxy(const DistProxy &sp) 1954 : stat(sp.stat), index(sp.index) 1955 {} 1956 1957 const DistProxy & 1958 operator=(const DistProxy &sp) 1959 { 1960 stat = sp.stat; 1961 index = sp.index; 1962 return *this; 1963 } 1964 1965 public: 1966 template <typename U> 1967 void 1968 sample(const U &v, int n = 1) 1969 { 1970 data()->sample(v, n); 1971 } 1972 1973 size_type 1974 size() const 1975 { 1976 return 1; 1977 } 1978 1979 bool 1980 zero() const 1981 { 1982 return data()->zero(); 1983 } 1984 1985 /** 1986 * Proxy has no state. Nothing to reset. 1987 */ 1988 void reset() { } 1989}; 1990 1991////////////////////////////////////////////////////////////////////// 1992// 1993// Formula Details 1994// 1995////////////////////////////////////////////////////////////////////// 1996 1997/** 1998 * Base class for formula statistic node. These nodes are used to build a tree 1999 * that represents the formula. 2000 */ 2001class Node : public RefCounted 2002{ 2003 public: 2004 /** 2005 * Return the number of nodes in the subtree starting at this node. 2006 * @return the number of nodes in this subtree. 2007 */ 2008 virtual size_type size() const = 0; 2009 /** 2010 * Return the result vector of this subtree. 2011 * @return The result vector of this subtree. 2012 */ 2013 virtual const VResult &result() const = 0; 2014 /** 2015 * Return the total of the result vector. 2016 * @return The total of the result vector. 2017 */ 2018 virtual Result total() const = 0; 2019 2020 /** 2021 * 2022 */ 2023 virtual std::string str() const = 0; 2024}; 2025 2026/** Reference counting pointer to a function Node. */ 2027typedef RefCountingPtr<Node> NodePtr; 2028 2029class ScalarStatNode : public Node 2030{ 2031 private: 2032 const ScalarInfo *data; 2033 mutable VResult vresult; 2034 2035 public: 2036 ScalarStatNode(const ScalarInfo *d) : data(d), vresult(1) {} 2037 2038 const VResult & 2039 result() const 2040 { 2041 vresult[0] = data->result(); 2042 return vresult; 2043 } 2044 2045 Result total() const { return data->result(); }; 2046 2047 size_type size() const { return 1; } 2048 2049 /** 2050 * 2051 */ 2052 std::string str() const { return data->name; } 2053}; 2054 2055template <class Stat> 2056class ScalarProxyNode : public Node 2057{ 2058 private: 2059 const ScalarProxy<Stat> proxy; 2060 mutable VResult vresult; 2061 2062 public: 2063 ScalarProxyNode(const ScalarProxy<Stat> &p) 2064 : proxy(p), vresult(1) 2065 { } 2066 2067 const VResult & 2068 result() const 2069 { 2070 vresult[0] = proxy.result(); 2071 return vresult; 2072 } 2073 2074 Result 2075 total() const 2076 { 2077 return proxy.result(); 2078 } 2079 2080 size_type 2081 size() const 2082 { 2083 return 1; 2084 } 2085 2086 /** 2087 * 2088 */ 2089 std::string 2090 str() const 2091 { 2092 return proxy.str(); 2093 } 2094}; 2095 2096class VectorStatNode : public Node 2097{ 2098 private: 2099 const VectorInfo *data; 2100 2101 public: 2102 VectorStatNode(const VectorInfo *d) : data(d) { } 2103 const VResult &result() const { return data->result(); } 2104 Result total() const { return data->total(); }; 2105 2106 size_type size() const { return data->size(); } 2107 2108 std::string str() const { return data->name; } 2109}; 2110 2111template <class T> 2112class ConstNode : public Node 2113{ 2114 private: 2115 VResult vresult; 2116 2117 public: 2118 ConstNode(T s) : vresult(1, (Result)s) {} 2119 const VResult &result() const { return vresult; } 2120 Result total() const { return vresult[0]; }; 2121 size_type size() const { return 1; } 2122 std::string str() const { return to_string(vresult[0]); } 2123}; 2124 2125template <class T> 2126class ConstVectorNode : public Node 2127{ 2128 private: 2129 VResult vresult; 2130 2131 public: 2132 ConstVectorNode(const T &s) : vresult(s.begin(), s.end()) {} 2133 const VResult &result() const { return vresult; } 2134 2135 Result 2136 total() const 2137 { 2138 size_type size = this->size(); 2139 Result tmp = 0; 2140 for (off_type i = 0; i < size; i++) 2141 tmp += vresult[i]; 2142 return tmp; 2143 } 2144 2145 size_type size() const { return vresult.size(); } 2146 std::string 2147 str() const 2148 { 2149 size_type size = this->size(); 2150 std::string tmp = "("; 2151 for (off_type i = 0; i < size; i++) 2152 tmp += csprintf("%s ",to_string(vresult[i])); 2153 tmp += ")"; 2154 return tmp; 2155 } 2156}; 2157 2158template <class Op> 2159struct OpString; 2160 2161template<> 2162struct OpString<std::plus<Result> > 2163{ 2164 static std::string str() { return "+"; } 2165}; 2166 2167template<> 2168struct OpString<std::minus<Result> > 2169{ 2170 static std::string str() { return "-"; } 2171}; 2172 2173template<> 2174struct OpString<std::multiplies<Result> > 2175{ 2176 static std::string str() { return "*"; } 2177}; 2178 2179template<> 2180struct OpString<std::divides<Result> > 2181{ 2182 static std::string str() { return "/"; } 2183}; 2184 2185template<> 2186struct OpString<std::modulus<Result> > 2187{ 2188 static std::string str() { return "%"; } 2189}; 2190 2191template<> 2192struct OpString<std::negate<Result> > 2193{ 2194 static std::string str() { return "-"; } 2195}; 2196 2197template <class Op> 2198class UnaryNode : public Node 2199{ 2200 public: 2201 NodePtr l; 2202 mutable VResult vresult; 2203 2204 public: 2205 UnaryNode(NodePtr &p) : l(p) {} 2206 2207 const VResult & 2208 result() const 2209 { 2210 const VResult &lvec = l->result(); 2211 size_type size = lvec.size(); 2212 2213 assert(size > 0); 2214 2215 vresult.resize(size); 2216 Op op; 2217 for (off_type i = 0; i < size; ++i) 2218 vresult[i] = op(lvec[i]); 2219 2220 return vresult; 2221 } 2222 2223 Result 2224 total() const 2225 { 2226 const VResult &vec = this->result(); 2227 Result total = 0.0; 2228 for (off_type i = 0; i < size(); i++) 2229 total += vec[i]; 2230 return total; 2231 } 2232 2233 size_type size() const { return l->size(); } 2234 2235 std::string 2236 str() const 2237 { 2238 return OpString<Op>::str() + l->str(); 2239 } 2240}; 2241 2242template <class Op> 2243class BinaryNode : public Node 2244{ 2245 public: 2246 NodePtr l; 2247 NodePtr r; 2248 mutable VResult vresult; 2249 2250 public: 2251 BinaryNode(NodePtr &a, NodePtr &b) : l(a), r(b) {} 2252 2253 const VResult & 2254 result() const 2255 { 2256 Op op; 2257 const VResult &lvec = l->result(); 2258 const VResult &rvec = r->result(); 2259 2260 assert(lvec.size() > 0 && rvec.size() > 0); 2261 2262 if (lvec.size() == 1 && rvec.size() == 1) { 2263 vresult.resize(1); 2264 vresult[0] = op(lvec[0], rvec[0]); 2265 } else if (lvec.size() == 1) { 2266 size_type size = rvec.size(); 2267 vresult.resize(size); 2268 for (off_type i = 0; i < size; ++i) 2269 vresult[i] = op(lvec[0], rvec[i]); 2270 } else if (rvec.size() == 1) { 2271 size_type size = lvec.size(); 2272 vresult.resize(size); 2273 for (off_type i = 0; i < size; ++i) 2274 vresult[i] = op(lvec[i], rvec[0]); 2275 } else if (rvec.size() == lvec.size()) { 2276 size_type size = rvec.size(); 2277 vresult.resize(size); 2278 for (off_type i = 0; i < size; ++i) 2279 vresult[i] = op(lvec[i], rvec[i]); 2280 } 2281 2282 return vresult; 2283 } 2284 2285 Result 2286 total() const 2287 { 2288 const VResult &vec = this->result(); 2289 const VResult &lvec = l->result(); 2290 const VResult &rvec = r->result(); 2291 Result total = 0.0; 2292 Result lsum = 0.0; 2293 Result rsum = 0.0; 2294 Op op; 2295 2296 assert(lvec.size() > 0 && rvec.size() > 0); 2297 assert(lvec.size() == rvec.size() || 2298 lvec.size() == 1 || rvec.size() == 1); 2299 2300 /** If vectors are the same divide their sums (x0+x1)/(y0+y1) */ 2301 if (lvec.size() == rvec.size() && lvec.size() > 1) { 2302 for (off_type i = 0; i < size(); ++i) { 2303 lsum += lvec[i]; 2304 rsum += rvec[i]; 2305 } 2306 return op(lsum, rsum); 2307 } 2308 2309 /** Otherwise divide each item by the divisor */ 2310 for (off_type i = 0; i < size(); ++i) { 2311 total += vec[i]; 2312 } 2313 2314 return total; 2315 } 2316 2317 size_type 2318 size() const 2319 { 2320 size_type ls = l->size(); 2321 size_type rs = r->size(); 2322 if (ls == 1) { 2323 return rs; 2324 } else if (rs == 1) { 2325 return ls; 2326 } else { 2327 assert(ls == rs && "Node vector sizes are not equal"); 2328 return ls; 2329 } 2330 } 2331 2332 std::string 2333 str() const 2334 { 2335 return csprintf("(%s %s %s)", l->str(), OpString<Op>::str(), r->str()); 2336 } 2337}; 2338 2339template <class Op> 2340class SumNode : public Node 2341{ 2342 public: 2343 NodePtr l; 2344 mutable VResult vresult; 2345 2346 public: 2347 SumNode(NodePtr &p) : l(p), vresult(1) {} 2348 2349 const VResult & 2350 result() const 2351 { 2352 const VResult &lvec = l->result(); 2353 size_type size = lvec.size(); 2354 assert(size > 0); 2355 2356 vresult[0] = 0.0; 2357 2358 Op op; 2359 for (off_type i = 0; i < size; ++i) 2360 vresult[0] = op(vresult[0], lvec[i]); 2361 2362 return vresult; 2363 } 2364 2365 Result 2366 total() const 2367 { 2368 const VResult &lvec = l->result(); 2369 size_type size = lvec.size(); 2370 assert(size > 0); 2371 2372 Result result = 0.0; 2373 2374 Op op; 2375 for (off_type i = 0; i < size; ++i) 2376 result = op(result, lvec[i]); 2377 2378 return result; 2379 } 2380 2381 size_type size() const { return 1; } 2382 2383 std::string 2384 str() const 2385 { 2386 return csprintf("total(%s)", l->str()); 2387 } 2388}; 2389 2390 2391////////////////////////////////////////////////////////////////////// 2392// 2393// Visible Statistics Types 2394// 2395////////////////////////////////////////////////////////////////////// 2396/** 2397 * @defgroup VisibleStats "Statistic Types" 2398 * These are the statistics that are used in the simulator. 2399 * @{ 2400 */ 2401 2402/** 2403 * This is a simple scalar statistic, like a counter. 2404 * @sa Stat, ScalarBase, StatStor 2405 */ 2406class Scalar : public ScalarBase<Scalar, StatStor> 2407{ 2408 public: 2409 using ScalarBase<Scalar, StatStor>::operator=; 2410}; 2411 2412/** 2413 * A stat that calculates the per tick average of a value. 2414 * @sa Stat, ScalarBase, AvgStor 2415 */ 2416class Average : public ScalarBase<Average, AvgStor> 2417{ 2418 public: 2419 using ScalarBase<Average, AvgStor>::operator=; 2420}; 2421 2422class Value : public ValueBase<Value> 2423{ 2424}; 2425 2426/** 2427 * A vector of scalar stats. 2428 * @sa Stat, VectorBase, StatStor 2429 */ 2430class Vector : public VectorBase<Vector, StatStor> 2431{ 2432}; 2433 2434/** 2435 * A vector of Average stats. 2436 * @sa Stat, VectorBase, AvgStor 2437 */ 2438class AverageVector : public VectorBase<AverageVector, AvgStor> 2439{ 2440}; 2441 2442/** 2443 * A 2-Dimensional vecto of scalar stats. 2444 * @sa Stat, Vector2dBase, StatStor 2445 */ 2446class Vector2d : public Vector2dBase<Vector2d, StatStor> 2447{ 2448}; 2449 2450/** 2451 * A simple distribution stat. 2452 * @sa Stat, DistBase, DistStor 2453 */ 2454class Distribution : public DistBase<Distribution, DistStor> 2455{ 2456 public: 2457 /** 2458 * Set the parameters of this distribution. @sa DistStor::Params 2459 * @param min The minimum value of the distribution. 2460 * @param max The maximum value of the distribution. 2461 * @param bkt The number of values in each bucket. 2462 * @return A reference to this distribution. 2463 */ 2464 Distribution & 2465 init(Counter min, Counter max, Counter bkt) 2466 { 2467 DistStor::Params *params = new DistStor::Params; 2468 params->min = min; 2469 params->max = max; 2470 params->bucket_size = bkt; 2471 params->buckets = (size_type)ceil((max - min + 1.0) / bkt); 2472 this->setParams(params); 2473 this->doInit(); 2474 return this->self(); 2475 } 2476}; 2477 2478/** 2479 * A simple histogram stat. 2480 * @sa Stat, DistBase, HistStor 2481 */ 2482class Histogram : public DistBase<Histogram, HistStor> 2483{ 2484 public: 2485 /** 2486 * Set the parameters of this histogram. @sa HistStor::Params 2487 * @param size The number of buckets in the histogram 2488 * @return A reference to this histogram. 2489 */ 2490 Histogram & 2491 init(size_type size) 2492 { 2493 HistStor::Params *params = new HistStor::Params; 2494 params->buckets = size; 2495 this->setParams(params); 2496 this->doInit(); 2497 return this->self(); 2498 } 2499}; 2500 2501/** 2502 * Calculates the mean and variance of all the samples. 2503 * @sa DistBase, SampleStor 2504 */ 2505class StandardDeviation : public DistBase<StandardDeviation, SampleStor> 2506{ 2507 public: 2508 /** 2509 * Construct and initialize this distribution. 2510 */ 2511 StandardDeviation() 2512 { 2513 SampleStor::Params *params = new SampleStor::Params; 2514 this->doInit(); 2515 this->setParams(params); 2516 } 2517}; 2518 2519/** 2520 * Calculates the per tick mean and variance of the samples. 2521 * @sa DistBase, AvgSampleStor 2522 */ 2523class AverageDeviation : public DistBase<AverageDeviation, AvgSampleStor> 2524{ 2525 public: 2526 /** 2527 * Construct and initialize this distribution. 2528 */ 2529 AverageDeviation() 2530 { 2531 AvgSampleStor::Params *params = new AvgSampleStor::Params; 2532 this->doInit(); 2533 this->setParams(params); 2534 } 2535}; 2536 2537/** 2538 * A vector of distributions. 2539 * @sa VectorDistBase, DistStor 2540 */ 2541class VectorDistribution : public VectorDistBase<VectorDistribution, DistStor> 2542{ 2543 public: 2544 /** 2545 * Initialize storage and parameters for this distribution. 2546 * @param size The size of the vector (the number of distributions). 2547 * @param min The minimum value of the distribution. 2548 * @param max The maximum value of the distribution. 2549 * @param bkt The number of values in each bucket. 2550 * @return A reference to this distribution. 2551 */ 2552 VectorDistribution & 2553 init(size_type size, Counter min, Counter max, Counter bkt) 2554 { 2555 DistStor::Params *params = new DistStor::Params; 2556 params->min = min; 2557 params->max = max; 2558 params->bucket_size = bkt; 2559 params->buckets = (size_type)ceil((max - min + 1.0) / bkt); 2560 this->setParams(params); 2561 this->doInit(size); 2562 return this->self(); 2563 } 2564}; 2565 2566/** 2567 * This is a vector of StandardDeviation stats. 2568 * @sa VectorDistBase, SampleStor 2569 */ 2570class VectorStandardDeviation 2571 : public VectorDistBase<VectorStandardDeviation, SampleStor> 2572{ 2573 public: 2574 /** 2575 * Initialize storage for this distribution. 2576 * @param size The size of the vector. 2577 * @return A reference to this distribution. 2578 */ 2579 VectorStandardDeviation & 2580 init(size_type size) 2581 { 2582 SampleStor::Params *params = new SampleStor::Params; 2583 this->doInit(size); 2584 this->setParams(params); 2585 return this->self(); 2586 } 2587}; 2588 2589/** 2590 * This is a vector of AverageDeviation stats. 2591 * @sa VectorDistBase, AvgSampleStor 2592 */ 2593class VectorAverageDeviation 2594 : public VectorDistBase<VectorAverageDeviation, AvgSampleStor> 2595{ 2596 public: 2597 /** 2598 * Initialize storage for this distribution. 2599 * @param size The size of the vector. 2600 * @return A reference to this distribution. 2601 */ 2602 VectorAverageDeviation & 2603 init(size_type size) 2604 { 2605 AvgSampleStor::Params *params = new AvgSampleStor::Params; 2606 this->doInit(size); 2607 this->setParams(params); 2608 return this->self(); 2609 } 2610}; 2611 2612template <class Stat> 2613class FormulaInfoProxy : public InfoProxy<Stat, FormulaInfo> 2614{ 2615 protected: 2616 mutable VResult vec; 2617 mutable VCounter cvec; 2618 2619 public: 2620 FormulaInfoProxy(Stat &stat) : InfoProxy<Stat, FormulaInfo>(stat) {} 2621 2622 size_type size() const { return this->s.size(); } 2623 2624 const VResult & 2625 result() const 2626 { 2627 this->s.result(vec); 2628 return vec; 2629 } 2630 Result total() const { return this->s.total(); } 2631 VCounter &value() const { return cvec; } 2632 2633 std::string str() const { return this->s.str(); } 2634}; 2635 2636template <class Stat> 2637class SparseHistInfoProxy : public InfoProxy<Stat, SparseHistInfo> 2638{ 2639 public: 2640 SparseHistInfoProxy(Stat &stat) : InfoProxy<Stat, SparseHistInfo>(stat) {} 2641}; 2642 2643/** 2644 * Implementation of a sparse histogram stat. The storage class is 2645 * determined by the Storage template. 2646 */ 2647template <class Derived, class Stor> 2648class SparseHistBase : public DataWrap<Derived, SparseHistInfoProxy> 2649{ 2650 public: 2651 typedef SparseHistInfoProxy<Derived> Info; 2652 typedef Stor Storage; 2653 typedef typename Stor::Params Params; 2654 2655 protected: 2656 /** The storage for this stat. */ 2657 char storage[sizeof(Storage)]; 2658 2659 protected: 2660 /** 2661 * Retrieve the storage. 2662 * @return The storage object for this stat. 2663 */ 2664 Storage * 2665 data() 2666 { 2667 return reinterpret_cast<Storage *>(storage); 2668 } 2669 2670 /** 2671 * Retrieve a const pointer to the storage. 2672 * @return A const pointer to the storage object for this stat. 2673 */ 2674 const Storage * 2675 data() const 2676 { 2677 return reinterpret_cast<const Storage *>(storage); 2678 } 2679 2680 void 2681 doInit() 2682 { 2683 new (storage) Storage(this->info()); 2684 this->setInit(); 2685 } 2686 2687 public: 2688 SparseHistBase() { } 2689 2690 /** 2691 * Add a value to the distribtion n times. Calls sample on the storage 2692 * class. 2693 * @param v The value to add. 2694 * @param n The number of times to add it, defaults to 1. 2695 */ 2696 template <typename U> 2697 void sample(const U &v, int n = 1) { data()->sample(v, n); } 2698 2699 /** 2700 * Return the number of entries in this stat. 2701 * @return The number of entries. 2702 */ 2703 size_type size() const { return data()->size(); } 2704 /** 2705 * Return true if no samples have been added. 2706 * @return True if there haven't been any samples. 2707 */ 2708 bool zero() const { return data()->zero(); } 2709 2710 void 2711 prepare() 2712 { 2713 Info *info = this->info(); 2714 data()->prepare(info, info->data); 2715 } 2716 2717 /** 2718 * Reset stat value to default 2719 */ 2720 void 2721 reset() 2722 { 2723 data()->reset(this->info()); 2724 } 2725}; 2726 2727/** 2728 * Templatized storage and interface for a sparse histogram stat. 2729 */ 2730class SparseHistStor 2731{ 2732 public: 2733 /** The parameters for a sparse histogram stat. */ 2734 struct Params : public DistParams 2735 { 2736 Params() : DistParams(Hist) {} 2737 }; 2738 2739 private: 2740 /** Counter for number of samples */ 2741 Counter samples; 2742 /** Counter for each bucket. */ 2743 MCounter cmap; 2744 2745 public: 2746 SparseHistStor(Info *info) 2747 { 2748 reset(info); 2749 } 2750 2751 /** 2752 * Add a value to the distribution for the given number of times. 2753 * @param val The value to add. 2754 * @param number The number of times to add the value. 2755 */ 2756 void 2757 sample(Counter val, int number) 2758 { 2759 cmap[val] += number; 2760 samples += number; 2761 } 2762 2763 /** 2764 * Return the number of buckets in this distribution. 2765 * @return the number of buckets. 2766 */ 2767 size_type size() const { return cmap.size(); } 2768 2769 /** 2770 * Returns true if any calls to sample have been made. 2771 * @return True if any values have been sampled. 2772 */ 2773 bool 2774 zero() const 2775 { 2776 return samples == Counter(); 2777 } 2778 2779 void 2780 prepare(Info *info, SparseHistData &data) 2781 { 2782 MCounter::iterator it; 2783 data.cmap.clear(); 2784 for (it = cmap.begin(); it != cmap.end(); it++) { 2785 data.cmap[(*it).first] = (*it).second; 2786 } 2787 2788 data.samples = samples; 2789 } 2790 2791 /** 2792 * Reset stat value to default 2793 */ 2794 void 2795 reset(Info *info) 2796 { 2797 cmap.clear(); 2798 samples = 0; 2799 } 2800}; 2801 2802class SparseHistogram : public SparseHistBase<SparseHistogram, SparseHistStor> 2803{ 2804 public: 2805 /** 2806 * Set the parameters of this histogram. @sa HistStor::Params 2807 * @param size The number of buckets in the histogram 2808 * @return A reference to this histogram. 2809 */ 2810 SparseHistogram & 2811 init(size_type size) 2812 { 2813 SparseHistStor::Params *params = new SparseHistStor::Params; 2814 this->setParams(params); 2815 this->doInit(); 2816 return this->self(); 2817 } 2818}; 2819 2820class Temp; 2821/** 2822 * A formula for statistics that is calculated when printed. A formula is 2823 * stored as a tree of Nodes that represent the equation to calculate. 2824 * @sa Stat, ScalarStat, VectorStat, Node, Temp 2825 */ 2826class Formula : public DataWrapVec<Formula, FormulaInfoProxy> 2827{ 2828 protected: 2829 /** The root of the tree which represents the Formula */ 2830 NodePtr root; 2831 friend class Temp; 2832 2833 public: 2834 /** 2835 * Create and initialize thie formula, and register it with the database. 2836 */ 2837 Formula(); 2838 2839 /** 2840 * Create a formula with the given root node, register it with the 2841 * database. 2842 * @param r The root of the expression tree. 2843 */ 2844 Formula(Temp r); 2845 2846 /** 2847 * Set an unitialized Formula to the given root. 2848 * @param r The root of the expression tree. 2849 * @return a reference to this formula. 2850 */ 2851 const Formula &operator=(Temp r); 2852 2853 /** 2854 * Add the given tree to the existing one. 2855 * @param r The root of the expression tree. 2856 * @return a reference to this formula. 2857 */ 2858 const Formula &operator+=(Temp r); 2859 2860 /** 2861 * Divide the existing tree by the given one. 2862 * @param r The root of the expression tree. 2863 * @return a reference to this formula. 2864 */ 2865 const Formula &operator/=(Temp r); 2866 2867 /** 2868 * Return the result of the Fomula in a vector. If there were no Vector 2869 * components to the Formula, then the vector is size 1. If there were, 2870 * like x/y with x being a vector of size 3, then the result returned will 2871 * be x[0]/y, x[1]/y, x[2]/y, respectively. 2872 * @return The result vector. 2873 */ 2874 void result(VResult &vec) const; 2875 2876 /** 2877 * Return the total Formula result. If there is a Vector 2878 * component to this Formula, then this is the result of the 2879 * Formula if the formula is applied after summing all the 2880 * components of the Vector. For example, if Formula is x/y where 2881 * x is size 3, then total() will return (x[1]+x[2]+x[3])/y. If 2882 * there is no Vector component, total() returns the same value as 2883 * the first entry in the VResult val() returns. 2884 * @return The total of the result vector. 2885 */ 2886 Result total() const; 2887 2888 /** 2889 * Return the number of elements in the tree. 2890 */ 2891 size_type size() const; 2892 2893 void prepare() { } 2894 2895 /** 2896 * Formulas don't need to be reset 2897 */ 2898 void reset(); 2899 2900 /** 2901 * 2902 */ 2903 bool zero() const; 2904 2905 std::string str() const; 2906}; 2907 2908class FormulaNode : public Node 2909{ 2910 private: 2911 const Formula &formula; 2912 mutable VResult vec; 2913 2914 public: 2915 FormulaNode(const Formula &f) : formula(f) {} 2916 2917 size_type size() const { return formula.size(); } 2918 const VResult &result() const { formula.result(vec); return vec; } 2919 Result total() const { return formula.total(); } 2920 2921 std::string str() const { return formula.str(); } 2922}; 2923 2924/** 2925 * Helper class to construct formula node trees. 2926 */ 2927class Temp 2928{ 2929 protected: 2930 /** 2931 * Pointer to a Node object. 2932 */ 2933 NodePtr node; 2934 2935 public: 2936 /** 2937 * Copy the given pointer to this class. 2938 * @param n A pointer to a Node object to copy. 2939 */ 2940 Temp(NodePtr n) : node(n) { } 2941 2942 /** 2943 * Return the node pointer. 2944 * @return the node pointer. 2945 */ 2946 operator NodePtr&() { return node; } 2947 2948 public: 2949 /** 2950 * Create a new ScalarStatNode. 2951 * @param s The ScalarStat to place in a node. 2952 */ 2953 Temp(const Scalar &s) 2954 : node(new ScalarStatNode(s.info())) 2955 { } 2956 2957 /** 2958 * Create a new ScalarStatNode. 2959 * @param s The ScalarStat to place in a node. 2960 */ 2961 Temp(const Value &s) 2962 : node(new ScalarStatNode(s.info())) 2963 { } 2964 2965 /** 2966 * Create a new ScalarStatNode. 2967 * @param s The ScalarStat to place in a node. 2968 */ 2969 Temp(const Average &s) 2970 : node(new ScalarStatNode(s.info())) 2971 { } 2972 2973 /** 2974 * Create a new VectorStatNode. 2975 * @param s The VectorStat to place in a node. 2976 */ 2977 Temp(const Vector &s) 2978 : node(new VectorStatNode(s.info())) 2979 { } 2980 2981 Temp(const AverageVector &s) 2982 : node(new VectorStatNode(s.info())) 2983 { } 2984 2985 /** 2986 * 2987 */ 2988 Temp(const Formula &f) 2989 : node(new FormulaNode(f)) 2990 { } 2991 2992 /** 2993 * Create a new ScalarProxyNode. 2994 * @param p The ScalarProxy to place in a node. 2995 */ 2996 template <class Stat> 2997 Temp(const ScalarProxy<Stat> &p) 2998 : node(new ScalarProxyNode<Stat>(p)) 2999 { } 3000 3001 /** 3002 * Create a ConstNode 3003 * @param value The value of the const node. 3004 */ 3005 Temp(signed char value) 3006 : node(new ConstNode<signed char>(value)) 3007 { } 3008 3009 /** 3010 * Create a ConstNode 3011 * @param value The value of the const node. 3012 */ 3013 Temp(unsigned char value) 3014 : node(new ConstNode<unsigned char>(value)) 3015 { } 3016 3017 /** 3018 * Create a ConstNode 3019 * @param value The value of the const node. 3020 */ 3021 Temp(signed short value) 3022 : node(new ConstNode<signed short>(value)) 3023 { } 3024 3025 /** 3026 * Create a ConstNode 3027 * @param value The value of the const node. 3028 */ 3029 Temp(unsigned short value) 3030 : node(new ConstNode<unsigned short>(value)) 3031 { } 3032 3033 /** 3034 * Create a ConstNode 3035 * @param value The value of the const node. 3036 */ 3037 Temp(signed int value) 3038 : node(new ConstNode<signed int>(value)) 3039 { } 3040 3041 /** 3042 * Create a ConstNode 3043 * @param value The value of the const node. 3044 */ 3045 Temp(unsigned int value) 3046 : node(new ConstNode<unsigned int>(value)) 3047 { } 3048 3049 /** 3050 * Create a ConstNode 3051 * @param value The value of the const node. 3052 */ 3053 Temp(signed long value) 3054 : node(new ConstNode<signed long>(value)) 3055 { } 3056 3057 /** 3058 * Create a ConstNode 3059 * @param value The value of the const node. 3060 */ 3061 Temp(unsigned long value) 3062 : node(new ConstNode<unsigned long>(value)) 3063 { } 3064 3065 /** 3066 * Create a ConstNode 3067 * @param value The value of the const node. 3068 */ 3069 Temp(signed long long value) 3070 : node(new ConstNode<signed long long>(value)) 3071 { } 3072 3073 /** 3074 * Create a ConstNode 3075 * @param value The value of the const node. 3076 */ 3077 Temp(unsigned long long value) 3078 : node(new ConstNode<unsigned long long>(value)) 3079 { } 3080 3081 /** 3082 * Create a ConstNode 3083 * @param value The value of the const node. 3084 */ 3085 Temp(float value) 3086 : node(new ConstNode<float>(value)) 3087 { } 3088 3089 /** 3090 * Create a ConstNode 3091 * @param value The value of the const node. 3092 */ 3093 Temp(double value) 3094 : node(new ConstNode<double>(value)) 3095 { } 3096}; 3097 3098 3099/** 3100 * @} 3101 */ 3102 3103inline Temp 3104operator+(Temp l, Temp r) 3105{ 3106 return NodePtr(new BinaryNode<std::plus<Result> >(l, r)); 3107} 3108 3109inline Temp 3110operator-(Temp l, Temp r) 3111{ 3112 return NodePtr(new BinaryNode<std::minus<Result> >(l, r)); 3113} 3114 3115inline Temp 3116operator*(Temp l, Temp r) 3117{ 3118 return NodePtr(new BinaryNode<std::multiplies<Result> >(l, r)); 3119} 3120 3121inline Temp 3122operator/(Temp l, Temp r) 3123{ 3124 return NodePtr(new BinaryNode<std::divides<Result> >(l, r)); 3125} 3126 3127inline Temp 3128operator-(Temp l) 3129{ 3130 return NodePtr(new UnaryNode<std::negate<Result> >(l)); 3131} 3132 3133template <typename T> 3134inline Temp 3135constant(T val) 3136{ 3137 return NodePtr(new ConstNode<T>(val)); 3138} 3139 3140template <typename T> 3141inline Temp 3142constantVector(T val) 3143{ 3144 return NodePtr(new ConstVectorNode<T>(val)); 3145} 3146 3147inline Temp 3148sum(Temp val) 3149{ 3150 return NodePtr(new SumNode<std::plus<Result> >(val)); 3151} 3152 3153/** Dump all statistics data to the registered outputs */ 3154void dump(); 3155void reset(); 3156void enable(); 3157bool enabled(); 3158 3159/** 3160 * Register a callback that should be called whenever statistics are 3161 * reset 3162 */ 3163void registerResetCallback(Callback *cb); 3164 3165/** 3166 * Register a callback that should be called whenever statistics are 3167 * about to be dumped 3168 */ 3169void registerDumpCallback(Callback *cb); 3170 3171std::list<Info *> &statsList(); 3172 3173typedef std::map<const void *, Info *> MapType; 3174MapType &statsMap(); 3175 3176typedef std::map<std::string, Info *> NameMapType; 3177NameMapType &nameMap(); 3178 3179bool validateStatName(const std::string &name); 3180 3181} // namespace Stats 3182 3183void debugDumpStats(); 3184 3185#endif // __BASE_STATISTICS_HH__
| 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__
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