/* * Copyright (c) 2003-2005 The Regents of The University of Michigan * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are * met: redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer; * redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution; * neither the name of the copyright holders nor the names of its * contributors may be used to endorse or promote products derived from * this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT * OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT * LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. * * Authors: Nathan Binkert */ /** @file * Declaration of Statistics objects. */ /** * @todo * * Generalized N-dimensinal vector * documentation * key stats * interval stats * -- these both can use the same function that prints out a * specific set of stats * VectorStandardDeviation totals * Document Namespaces */ #ifndef __BASE_STATISTICS_HH__ #define __BASE_STATISTICS_HH__ #include #include #ifdef __SUNPRO_CC #include #endif #include #include #include #include #include #include #include #include "base/stats/info.hh" #include "base/stats/output.hh" #include "base/stats/types.hh" #include "base/cast.hh" #include "base/cprintf.hh" #include "base/intmath.hh" #include "base/refcnt.hh" #include "base/str.hh" #include "base/types.hh" class Callback; /** The current simulated tick. */ extern Tick curTick(); /* A namespace for all of the Statistics */ namespace Stats { template class InfoProxy : public Base { protected: Stat &s; public: InfoProxy(Stat &stat) : s(stat) {} bool check() const { return s.check(); } void prepare() { s.prepare(); } void reset() { s.reset(); } void visit(Output &visitor) { visitor.visit(*static_cast(this)); } bool zero() const { return s.zero(); } }; template class ScalarInfoProxy : public InfoProxy { public: ScalarInfoProxy(Stat &stat) : InfoProxy(stat) {} Counter value() const { return this->s.value(); } Result result() const { return this->s.result(); } Result total() const { return this->s.total(); } }; template class VectorInfoProxy : public InfoProxy { protected: mutable VCounter cvec; mutable VResult rvec; public: VectorInfoProxy(Stat &stat) : InfoProxy(stat) {} size_type size() const { return this->s.size(); } VCounter & value() const { this->s.value(cvec); return cvec; } const VResult & result() const { this->s.result(rvec); return rvec; } Result total() const { return this->s.total(); } }; template class DistInfoProxy : public InfoProxy { public: DistInfoProxy(Stat &stat) : InfoProxy(stat) {} }; template class VectorDistInfoProxy : public InfoProxy { public: VectorDistInfoProxy(Stat &stat) : InfoProxy(stat) {} size_type size() const { return this->s.size(); } }; template class Vector2dInfoProxy : public InfoProxy { public: Vector2dInfoProxy(Stat &stat) : InfoProxy(stat) {} }; struct StorageParams { virtual ~StorageParams(); }; class InfoAccess { protected: /** Set up an info class for this statistic */ void setInfo(Info *info); /** Save Storage class parameters if any */ void setParams(const StorageParams *params); /** Save Storage class parameters if any */ void setInit(); /** Grab the information class for this statistic */ Info *info(); /** Grab the information class for this statistic */ const Info *info() const; public: /** * Reset the stat to the default state. */ void reset() { } /** * @return true if this stat has a value and satisfies its * requirement as a prereq */ bool zero() const { return true; } /** * Check that this stat has been set up properly and is ready for * use * @return true for success */ bool check() const { return true; } }; template class InfoProxyType> class DataWrap : public InfoAccess { public: typedef InfoProxyType Info; protected: Derived &self() { return *static_cast(this); } protected: Info * info() { return safe_cast(InfoAccess::info()); } public: const Info * info() const { return safe_cast(InfoAccess::info()); } protected: /** * Copy constructor, copies are not allowed. */ DataWrap(const DataWrap &stat); /** * Can't copy stats. */ void operator=(const DataWrap &); public: DataWrap() { this->setInfo(new Info(self())); } /** * Set the name and marks this stat to print at the end of simulation. * @param name The new name. * @return A reference to this stat. */ Derived & name(const std::string &name) { Info *info = this->info(); info->setName(name); info->flags.set(display); return this->self(); } const std::string &name() const { return this->info()->name; } /** * Set the character(s) used between the name and vector number * on vectors, dist, etc. * @param _sep The new separator string * @return A reference to this stat. */ Derived & setSeparator(const std::string &_sep) { this->info()->setSeparator(_sep); return this->self(); } const std::string &setSeparator() const { return this->info()->separatorString; } /** * Set the description and marks this stat to print at the end of * simulation. * @param desc The new description. * @return A reference to this stat. */ Derived & desc(const std::string &_desc) { this->info()->desc = _desc; return this->self(); } /** * Set the precision and marks this stat to print at the end of simulation. * @param _precision The new precision * @return A reference to this stat. */ Derived & precision(int _precision) { this->info()->precision = _precision; return this->self(); } /** * Set the flags and marks this stat to print at the end of simulation. * @param f The new flags. * @return A reference to this stat. */ Derived & flags(Flags _flags) { this->info()->flags.set(_flags); return this->self(); } /** * Set the prerequisite stat and marks this stat to print at the end of * simulation. * @param prereq The prerequisite stat. * @return A reference to this stat. */ template Derived & prereq(const Stat &prereq) { this->info()->prereq = prereq.info(); return this->self(); } }; template class InfoProxyType> class DataWrapVec : public DataWrap { public: typedef InfoProxyType Info; // The following functions are specific to vectors. If you use them // in a non vector context, you will get a nice compiler error! /** * Set the subfield name for the given index, and marks this stat to print * at the end of simulation. * @param index The subfield index. * @param name The new name of the subfield. * @return A reference to this stat. */ Derived & subname(off_type index, const std::string &name) { Derived &self = this->self(); Info *info = self.info(); std::vector &subn = info->subnames; if (subn.size() <= index) subn.resize(index + 1); subn[index] = name; return self; } // The following functions are specific to 2d vectors. If you use // them in a non vector context, you will get a nice compiler // error because info doesn't have the right variables. /** * Set the subfield description for the given index and marks this stat to * print at the end of simulation. * @param index The subfield index. * @param desc The new description of the subfield * @return A reference to this stat. */ Derived & subdesc(off_type index, const std::string &desc) { Info *info = this->info(); std::vector &subd = info->subdescs; if (subd.size() <= index) subd.resize(index + 1); subd[index] = desc; return this->self(); } void prepare() { Derived &self = this->self(); Info *info = this->info(); size_t size = self.size(); for (off_type i = 0; i < size; ++i) self.data(i)->prepare(info); } void reset() { Derived &self = this->self(); Info *info = this->info(); size_t size = self.size(); for (off_type i = 0; i < size; ++i) self.data(i)->reset(info); } }; template class InfoProxyType> class DataWrapVec2d : public DataWrapVec { public: typedef InfoProxyType Info; /** * @warning This makes the assumption that if you're gonna subnames a 2d * vector, you're subnaming across all y */ Derived & ysubnames(const char **names) { Derived &self = this->self(); Info *info = this->info(); info->y_subnames.resize(self.y); for (off_type i = 0; i < self.y; ++i) info->y_subnames[i] = names[i]; return self; } Derived & ysubname(off_type index, const std::string &subname) { Derived &self = this->self(); Info *info = this->info(); assert(index < self.y); info->y_subnames.resize(self.y); info->y_subnames[index] = subname.c_str(); return self; } std::string ysubname(off_type i) const { return this->info()->y_subnames[i]; } }; ////////////////////////////////////////////////////////////////////// // // Simple Statistics // ////////////////////////////////////////////////////////////////////// /** * Templatized storage and interface for a simple scalar stat. */ class StatStor { private: /** The statistic value. */ Counter data; public: struct Params : public StorageParams {}; public: /** * Builds this storage element and calls the base constructor of the * datatype. */ StatStor(Info *info) : data(Counter()) { } /** * The the stat to the given value. * @param val The new value. */ void set(Counter val) { data = val; } /** * Increment the stat by the given value. * @param val The new value. */ void inc(Counter val) { data += val; } /** * Decrement the stat by the given value. * @param val The new value. */ void dec(Counter val) { data -= val; } /** * Return the value of this stat as its base type. * @return The value of this stat. */ Counter value() const { return data; } /** * Return the value of this stat as a result type. * @return The value of this stat. */ Result result() const { return (Result)data; } /** * Prepare stat data for dumping or serialization */ void prepare(Info *info) { } /** * Reset stat value to default */ void reset(Info *info) { data = Counter(); } /** * @return true if zero value */ bool zero() const { return data == Counter(); } }; /** * Templatized storage and interface to a per-tick average stat. This keeps * a current count and updates a total (count * ticks) when this count * changes. This allows the quick calculation of a per tick count of the item * being watched. This is good for keeping track of residencies in structures * among other things. */ class AvgStor { private: /** The current count. */ Counter current; /** The tick of the last reset */ Tick lastReset; /** The total count for all tick. */ mutable Result total; /** The tick that current last changed. */ mutable Tick last; public: struct Params : public StorageParams {}; public: /** * Build and initializes this stat storage. */ AvgStor(Info *info) : current(0), lastReset(0), total(0), last(0) { } /** * Set the current count to the one provided, update the total and last * set values. * @param val The new count. */ void set(Counter val) { total += current * (curTick() - last); last = curTick(); current = val; } /** * Increment the current count by the provided value, calls set. * @param val The amount to increment. */ void inc(Counter val) { set(current + val); } /** * Deccrement the current count by the provided value, calls set. * @param val The amount to decrement. */ void dec(Counter val) { set(current - val); } /** * Return the current count. * @return The current count. */ Counter value() const { return current; } /** * Return the current average. * @return The current average. */ Result result() const { assert(last == curTick()); return (Result)(total + current) / (Result)(curTick() - lastReset + 1); } /** * @return true if zero value */ bool zero() const { return total == 0.0; } /** * Prepare stat data for dumping or serialization */ void prepare(Info *info) { total += current * (curTick() - last); last = curTick(); } /** * Reset stat value to default */ void reset(Info *info) { total = 0.0; last = curTick(); lastReset = curTick(); } }; /** * Implementation of a scalar stat. The type of stat is determined by the * Storage template. */ template class ScalarBase : public DataWrap { public: typedef Stor Storage; typedef typename Stor::Params Params; protected: /** The storage of this stat. */ char storage[sizeof(Storage)] __attribute__ ((aligned (8))); protected: /** * Retrieve the storage. * @param index The vector index to access. * @return The storage object at the given index. */ Storage * data() { return reinterpret_cast(storage); } /** * Retrieve a const pointer to the storage. * for the given index. * @param index The vector index to access. * @return A const pointer to the storage object at the given index. */ const Storage * data() const { return reinterpret_cast(storage); } void doInit() { new (storage) Storage(this->info()); this->setInit(); } public: /** * Return the current value of this stat as its base type. * @return The current value. */ Counter value() const { return data()->value(); } public: ScalarBase() { this->doInit(); } public: // Common operators for stats /** * Increment the stat by 1. This calls the associated storage object inc * function. */ void operator++() { data()->inc(1); } /** * Decrement the stat by 1. This calls the associated storage object dec * function. */ void operator--() { data()->dec(1); } /** Increment the stat by 1. */ void operator++(int) { ++*this; } /** Decrement the stat by 1. */ void operator--(int) { --*this; } /** * Set the data value to the given value. This calls the associated storage * object set function. * @param v The new value. */ template void operator=(const U &v) { data()->set(v); } /** * Increment the stat by the given value. This calls the associated * storage object inc function. * @param v The value to add. */ template void operator+=(const U &v) { data()->inc(v); } /** * Decrement the stat by the given value. This calls the associated * storage object dec function. * @param v The value to substract. */ template void operator-=(const U &v) { data()->dec(v); } /** * Return the number of elements, always 1 for a scalar. * @return 1. */ size_type size() const { return 1; } Counter value() { return data()->value(); } Result result() { return data()->result(); } Result total() { return result(); } bool zero() { return result() == 0.0; } void reset() { data()->reset(this->info()); } void prepare() { data()->prepare(this->info()); } }; class ProxyInfo : public ScalarInfo { public: std::string str() const { return to_string(value()); } size_type size() const { return 1; } bool check() const { return true; } void prepare() { } void reset() { } bool zero() const { return value() == 0; } void visit(Output &visitor) { visitor.visit(*this); } }; template class ValueProxy : public ProxyInfo { private: T *scalar; public: ValueProxy(T &val) : scalar(&val) {} Counter value() const { return *scalar; } Result result() const { return *scalar; } Result total() const { return *scalar; } }; template class FunctorProxy : public ProxyInfo { private: T *functor; public: FunctorProxy(T &func) : functor(&func) {} Counter value() const { return (*functor)(); } Result result() const { return (*functor)(); } Result total() const { return (*functor)(); } }; template class ValueBase : public DataWrap { private: ProxyInfo *proxy; public: ValueBase() : proxy(NULL) { } ~ValueBase() { if (proxy) delete proxy; } template Derived & scalar(T &value) { proxy = new ValueProxy(value); this->setInit(); return this->self(); } template Derived & functor(T &func) { proxy = new FunctorProxy(func); this->setInit(); return this->self(); } Counter value() { return proxy->value(); } Result result() const { return proxy->result(); } Result total() const { return proxy->total(); }; size_type size() const { return proxy->size(); } std::string str() const { return proxy->str(); } bool zero() const { return proxy->zero(); } bool check() const { return proxy != NULL; } void prepare() { } void reset() { } }; ////////////////////////////////////////////////////////////////////// // // Vector Statistics // ////////////////////////////////////////////////////////////////////// /** * A proxy class to access the stat at a given index in a VectorBase stat. * Behaves like a ScalarBase. */ template class ScalarProxy { private: /** Pointer to the parent Vector. */ Stat &stat; /** The index to access in the parent VectorBase. */ off_type index; public: /** * Return the current value of this stat as its base type. * @return The current value. */ Counter value() const { return stat.data(index)->value(); } /** * Return the current value of this statas a result type. * @return The current value. */ Result result() const { return stat.data(index)->result(); } public: /** * Create and initialize this proxy, do not register it with the database. * @param i The index to access. */ ScalarProxy(Stat &s, off_type i) : stat(s), index(i) { } /** * Create a copy of the provided ScalarProxy. * @param sp The proxy to copy. */ ScalarProxy(const ScalarProxy &sp) : stat(sp.stat), index(sp.index) {} /** * Set this proxy equal to the provided one. * @param sp The proxy to copy. * @return A reference to this proxy. */ const ScalarProxy & operator=(const ScalarProxy &sp) { stat = sp.stat; index = sp.index; return *this; } public: // Common operators for stats /** * Increment the stat by 1. This calls the associated storage object inc * function. */ void operator++() { stat.data(index)->inc(1); } /** * Decrement the stat by 1. This calls the associated storage object dec * function. */ void operator--() { stat.data(index)->dec(1); } /** Increment the stat by 1. */ void operator++(int) { ++*this; } /** Decrement the stat by 1. */ void operator--(int) { --*this; } /** * Set the data value to the given value. This calls the associated storage * object set function. * @param v The new value. */ template void operator=(const U &v) { stat.data(index)->set(v); } /** * Increment the stat by the given value. This calls the associated * storage object inc function. * @param v The value to add. */ template void operator+=(const U &v) { stat.data(index)->inc(v); } /** * Decrement the stat by the given value. This calls the associated * storage object dec function. * @param v The value to substract. */ template void operator-=(const U &v) { stat.data(index)->dec(v); } /** * Return the number of elements, always 1 for a scalar. * @return 1. */ size_type size() const { return 1; } public: std::string str() const { return csprintf("%s[%d]", stat.info()->name, index); } }; /** * Implementation of a vector of stats. The type of stat is determined by the * Storage class. @sa ScalarBase */ template class VectorBase : public DataWrapVec { public: typedef Stor Storage; typedef typename Stor::Params Params; /** Proxy type */ typedef ScalarProxy Proxy; friend class ScalarProxy; friend class DataWrapVec; protected: /** The storage of this stat. */ Storage *storage; size_type _size; protected: /** * Retrieve the storage. * @param index The vector index to access. * @return The storage object at the given index. */ Storage *data(off_type index) { return &storage[index]; } /** * Retrieve a const pointer to the storage. * @param index The vector index to access. * @return A const pointer to the storage object at the given index. */ const Storage *data(off_type index) const { return &storage[index]; } void doInit(size_type s) { assert(s > 0 && "size must be positive!"); assert(!storage && "already initialized"); _size = s; char *ptr = new char[_size * sizeof(Storage)]; storage = reinterpret_cast(ptr); for (off_type i = 0; i < _size; ++i) new (&storage[i]) Storage(this->info()); this->setInit(); } public: void value(VCounter &vec) const { vec.resize(size()); for (off_type i = 0; i < size(); ++i) vec[i] = data(i)->value(); } /** * Copy the values to a local vector and return a reference to it. * @return A reference to a vector of the stat values. */ void result(VResult &vec) const { vec.resize(size()); for (off_type i = 0; i < size(); ++i) vec[i] = data(i)->result(); } /** * Return a total of all entries in this vector. * @return The total of all vector entries. */ Result total() const { Result total = 0.0; for (off_type i = 0; i < size(); ++i) total += data(i)->result(); return total; } /** * @return the number of elements in this vector. */ size_type size() const { return _size; } bool zero() const { for (off_type i = 0; i < size(); ++i) if (data(i)->zero()) return false; return true; } bool check() const { return storage != NULL; } public: VectorBase() : storage(NULL) {} ~VectorBase() { if (!storage) return; for (off_type i = 0; i < _size; ++i) data(i)->~Storage(); delete [] reinterpret_cast(storage); } /** * Set this vector to have the given size. * @param size The new size. * @return A reference to this stat. */ Derived & init(size_type size) { Derived &self = this->self(); self.doInit(size); return self; } /** * Return a reference (ScalarProxy) to the stat at the given index. * @param index The vector index to access. * @return A reference of the stat. */ Proxy operator[](off_type index) { assert (index >= 0 && index < size()); return Proxy(this->self(), index); } }; template class VectorProxy { private: Stat &stat; off_type offset; size_type len; private: mutable VResult vec; typename Stat::Storage * data(off_type index) { assert(index < len); return stat.data(offset + index); } const typename Stat::Storage * data(off_type index) const { assert(index < len); return stat.data(offset + index); } public: const VResult & result() const { vec.resize(size()); for (off_type i = 0; i < size(); ++i) vec[i] = data(i)->result(); return vec; } Result total() const { Result total = 0.0; for (off_type i = 0; i < size(); ++i) total += data(i)->result(); return total; } public: VectorProxy(Stat &s, off_type o, size_type l) : stat(s), offset(o), len(l) { } VectorProxy(const VectorProxy &sp) : stat(sp.stat), offset(sp.offset), len(sp.len) { } const VectorProxy & operator=(const VectorProxy &sp) { stat = sp.stat; offset = sp.offset; len = sp.len; return *this; } ScalarProxy operator[](off_type index) { assert (index >= 0 && index < size()); return ScalarProxy(stat, offset + index); } size_type size() const { return len; } }; template class Vector2dBase : public DataWrapVec2d { public: typedef Vector2dInfoProxy Info; typedef Stor Storage; typedef typename Stor::Params Params; typedef VectorProxy Proxy; friend class ScalarProxy; friend class VectorProxy; friend class DataWrapVec; friend class DataWrapVec2d; protected: size_type x; size_type y; size_type _size; Storage *storage; protected: Storage *data(off_type index) { return &storage[index]; } const Storage *data(off_type index) const { return &storage[index]; } public: Vector2dBase() : storage(NULL) {} ~Vector2dBase() { if (!storage) return; for (off_type i = 0; i < _size; ++i) data(i)->~Storage(); delete [] reinterpret_cast(storage); } Derived & init(size_type _x, size_type _y) { assert(_x > 0 && _y > 0 && "sizes must be positive!"); assert(!storage && "already initialized"); Derived &self = this->self(); Info *info = this->info(); x = _x; y = _y; info->x = _x; info->y = _y; _size = x * y; char *ptr = new char[_size * sizeof(Storage)]; storage = reinterpret_cast(ptr); for (off_type i = 0; i < _size; ++i) new (&storage[i]) Storage(info); this->setInit(); return self; } Proxy operator[](off_type index) { off_type offset = index * y; assert (index >= 0 && offset + y <= size()); return Proxy(this->self(), offset, y); } size_type size() const { return _size; } bool zero() const { return data(0)->zero(); #if 0 for (off_type i = 0; i < size(); ++i) if (!data(i)->zero()) return false; return true; #endif } void prepare() { Info *info = this->info(); size_type size = this->size(); for (off_type i = 0; i < size; ++i) data(i)->prepare(info); info->cvec.resize(size); for (off_type i = 0; i < size; ++i) info->cvec[i] = data(i)->value(); } /** * Reset stat value to default */ void reset() { Info *info = this->info(); size_type size = this->size(); for (off_type i = 0; i < size; ++i) data(i)->reset(info); } bool check() const { return storage != NULL; } }; ////////////////////////////////////////////////////////////////////// // // Non formula statistics // ////////////////////////////////////////////////////////////////////// /** The parameters for a distribution stat. */ struct DistParams : public StorageParams { const DistType type; DistParams(DistType t) : type(t) {} }; /** * Templatized storage and interface for a distrbution stat. */ class DistStor { public: /** The parameters for a distribution stat. */ struct Params : public DistParams { /** The minimum value to track. */ Counter min; /** The maximum value to track. */ Counter max; /** The number of entries in each bucket. */ Counter bucket_size; /** The number of buckets. Equal to (max-min)/bucket_size. */ size_type buckets; Params() : DistParams(Dist) {} }; private: /** The minimum value to track. */ Counter min_track; /** The maximum value to track. */ Counter max_track; /** The number of entries in each bucket. */ Counter bucket_size; /** The number of buckets. Equal to (max-min)/bucket_size. */ size_type buckets; /** The smallest value sampled. */ Counter min_val; /** The largest value sampled. */ Counter max_val; /** The number of values sampled less than min. */ Counter underflow; /** The number of values sampled more than max. */ Counter overflow; /** The current sum. */ Counter sum; /** The sum of squares. */ Counter squares; /** The number of samples. */ Counter samples; /** Counter for each bucket. */ VCounter cvec; public: DistStor(Info *info) : cvec(safe_cast(info->storageParams)->buckets) { reset(info); } /** * Add a value to the distribution for the given number of times. * @param val The value to add. * @param number The number of times to add the value. */ void sample(Counter val, int number) { if (val < min_track) underflow += number; else if (val > max_track) overflow += number; else { size_type index = (size_type)std::floor((val - min_track) / bucket_size); assert(index < size()); cvec[index] += number; } if (val < min_val) min_val = val; if (val > max_val) max_val = val; sum += val * number; squares += val * val * number; samples += number; } /** * Return the number of buckets in this distribution. * @return the number of buckets. */ size_type size() const { return cvec.size(); } /** * Returns true if any calls to sample have been made. * @return True if any values have been sampled. */ bool zero() const { return samples == Counter(); } void prepare(Info *info, DistData &data) { const Params *params = safe_cast(info->storageParams); assert(params->type == Dist); data.type = params->type; data.min = params->min; data.max = params->max; data.bucket_size = params->bucket_size; data.min_val = (min_val == CounterLimits::max()) ? 0 : min_val; data.max_val = (max_val == CounterLimits::min()) ? 0 : max_val; data.underflow = underflow; data.overflow = overflow; data.cvec.resize(params->buckets); for (off_type i = 0; i < params->buckets; ++i) data.cvec[i] = cvec[i]; data.sum = sum; data.squares = squares; data.samples = samples; } /** * Reset stat value to default */ void reset(Info *info) { const Params *params = safe_cast(info->storageParams); min_track = params->min; max_track = params->max; bucket_size = params->bucket_size; min_val = CounterLimits::max(); max_val = CounterLimits::min(); underflow = Counter(); overflow = Counter(); size_type size = cvec.size(); for (off_type i = 0; i < size; ++i) cvec[i] = Counter(); sum = Counter(); squares = Counter(); samples = Counter(); } }; /** * Templatized storage and interface for a histogram stat. */ class HistStor { public: /** The parameters for a distribution stat. */ struct Params : public DistParams { /** The number of buckets.. */ size_type buckets; Params() : DistParams(Hist) {} }; private: /** The minimum value to track. */ Counter min_bucket; /** The maximum value to track. */ Counter max_bucket; /** The number of entries in each bucket. */ Counter bucket_size; /** The current sum. */ Counter sum; /** The sum of logarithm of each sample, used to compute geometric mean. */ Counter logs; /** The sum of squares. */ Counter squares; /** The number of samples. */ Counter samples; /** Counter for each bucket. */ VCounter cvec; public: HistStor(Info *info) : cvec(safe_cast(info->storageParams)->buckets) { reset(info); } void grow_up(); void grow_out(); void grow_convert(); /** * Add a value to the distribution for the given number of times. * @param val The value to add. * @param number The number of times to add the value. */ void sample(Counter val, int number) { assert(min_bucket < max_bucket); if (val < min_bucket) { if (min_bucket == 0) grow_convert(); while (val < min_bucket) grow_out(); } else if (val >= max_bucket + bucket_size) { if (min_bucket == 0) { while (val >= max_bucket + bucket_size) grow_up(); } else { while (val >= max_bucket + bucket_size) grow_out(); } } size_type index = (int64_t)std::floor((val - min_bucket) / bucket_size); assert(index >= 0 && index < size()); cvec[index] += number; sum += val * number; squares += val * val * number; logs += log(val) * number; samples += number; } /** * Return the number of buckets in this distribution. * @return the number of buckets. */ size_type size() const { return cvec.size(); } /** * Returns true if any calls to sample have been made. * @return True if any values have been sampled. */ bool zero() const { return samples == Counter(); } void prepare(Info *info, DistData &data) { const Params *params = safe_cast(info->storageParams); assert(params->type == Hist); data.type = params->type; data.min = min_bucket; data.max = max_bucket + bucket_size - 1; data.bucket_size = bucket_size; data.min_val = min_bucket; data.max_val = max_bucket; int buckets = params->buckets; data.cvec.resize(buckets); for (off_type i = 0; i < buckets; ++i) data.cvec[i] = cvec[i]; data.sum = sum; data.logs = logs; data.squares = squares; data.samples = samples; } /** * Reset stat value to default */ void reset(Info *info) { const Params *params = safe_cast(info->storageParams); min_bucket = 0; max_bucket = params->buckets - 1; bucket_size = 1; size_type size = cvec.size(); for (off_type i = 0; i < size; ++i) cvec[i] = Counter(); sum = Counter(); squares = Counter(); samples = Counter(); logs = Counter(); } }; /** * Templatized storage and interface for a distribution that calculates mean * and variance. */ class SampleStor { public: struct Params : public DistParams { Params() : DistParams(Deviation) {} }; private: /** The current sum. */ Counter sum; /** The sum of squares. */ Counter squares; /** The number of samples. */ Counter samples; public: /** * Create and initialize this storage. */ SampleStor(Info *info) : sum(Counter()), squares(Counter()), samples(Counter()) { } /** * Add a value the given number of times to this running average. * Update the running sum and sum of squares, increment the number of * values seen by the given number. * @param val The value to add. * @param number The number of times to add the value. */ void sample(Counter val, int number) { Counter value = val * number; sum += value; squares += value * value; samples += number; } /** * Return the number of entries in this stat, 1 * @return 1. */ size_type size() const { return 1; } /** * Return true if no samples have been added. * @return True if no samples have been added. */ bool zero() const { return samples == Counter(); } void prepare(Info *info, DistData &data) { const Params *params = safe_cast(info->storageParams); assert(params->type == Deviation); data.type = params->type; data.sum = sum; data.squares = squares; data.samples = samples; } /** * Reset stat value to default */ void reset(Info *info) { sum = Counter(); squares = Counter(); samples = Counter(); } }; /** * Templatized storage for distribution that calculates per tick mean and * variance. */ class AvgSampleStor { public: struct Params : public DistParams { Params() : DistParams(Deviation) {} }; private: /** Current total. */ Counter sum; /** Current sum of squares. */ Counter squares; public: /** * Create and initialize this storage. */ AvgSampleStor(Info *info) : sum(Counter()), squares(Counter()) {} /** * Add a value to the distribution for the given number of times. * Update the running sum and sum of squares. * @param val The value to add. * @param number The number of times to add the value. */ void sample(Counter val, int number) { Counter value = val * number; sum += value; squares += value * value; } /** * Return the number of entries, in this case 1. * @return 1. */ size_type size() const { return 1; } /** * Return true if no samples have been added. * @return True if the sum is zero. */ bool zero() const { return sum == Counter(); } void prepare(Info *info, DistData &data) { const Params *params = safe_cast(info->storageParams); assert(params->type == Deviation); data.type = params->type; data.sum = sum; data.squares = squares; data.samples = curTick(); } /** * Reset stat value to default */ void reset(Info *info) { sum = Counter(); squares = Counter(); } }; /** * Implementation of a distribution stat. The type of distribution is * determined by the Storage template. @sa ScalarBase */ template class DistBase : public DataWrap { public: typedef DistInfoProxy Info; typedef Stor Storage; typedef typename Stor::Params Params; protected: /** The storage for this stat. */ char storage[sizeof(Storage)] __attribute__ ((aligned (8))); protected: /** * Retrieve the storage. * @return The storage object for this stat. */ Storage * data() { return reinterpret_cast(storage); } /** * Retrieve a const pointer to the storage. * @return A const pointer to the storage object for this stat. */ const Storage * data() const { return reinterpret_cast(storage); } void doInit() { new (storage) Storage(this->info()); this->setInit(); } public: DistBase() { } /** * Add a value to the distribtion n times. Calls sample on the storage * class. * @param v The value to add. * @param n The number of times to add it, defaults to 1. */ template void sample(const U &v, int n = 1) { data()->sample(v, n); } /** * Return the number of entries in this stat. * @return The number of entries. */ size_type size() const { return data()->size(); } /** * Return true if no samples have been added. * @return True if there haven't been any samples. */ bool zero() const { return data()->zero(); } void prepare() { Info *info = this->info(); data()->prepare(info, info->data); } /** * Reset stat value to default */ void reset() { data()->reset(this->info()); } }; template class DistProxy; template class VectorDistBase : public DataWrapVec { public: typedef VectorDistInfoProxy Info; typedef Stor Storage; typedef typename Stor::Params Params; typedef DistProxy Proxy; friend class DistProxy; friend class DataWrapVec; protected: Storage *storage; size_type _size; protected: Storage * data(off_type index) { return &storage[index]; } const Storage * data(off_type index) const { return &storage[index]; } void doInit(size_type s) { assert(s > 0 && "size must be positive!"); assert(!storage && "already initialized"); _size = s; char *ptr = new char[_size * sizeof(Storage)]; storage = reinterpret_cast(ptr); Info *info = this->info(); for (off_type i = 0; i < _size; ++i) new (&storage[i]) Storage(info); this->setInit(); } public: VectorDistBase() : storage(NULL) {} ~VectorDistBase() { if (!storage) return ; for (off_type i = 0; i < _size; ++i) data(i)->~Storage(); delete [] reinterpret_cast(storage); } Proxy operator[](off_type index) { assert(index >= 0 && index < size()); return Proxy(this->self(), index); } size_type size() const { return _size; } bool zero() const { for (off_type i = 0; i < size(); ++i) if (!data(i)->zero()) return false; return true; } void prepare() { Info *info = this->info(); size_type size = this->size(); info->data.resize(size); for (off_type i = 0; i < size; ++i) data(i)->prepare(info, info->data[i]); } bool check() const { return storage != NULL; } }; template class DistProxy { private: Stat &stat; off_type index; protected: typename Stat::Storage *data() { return stat.data(index); } const typename Stat::Storage *data() const { return stat.data(index); } public: DistProxy(Stat &s, off_type i) : stat(s), index(i) {} DistProxy(const DistProxy &sp) : stat(sp.stat), index(sp.index) {} const DistProxy & operator=(const DistProxy &sp) { stat = sp.stat; index = sp.index; return *this; } public: template void sample(const U &v, int n = 1) { data()->sample(v, n); } size_type size() const { return 1; } bool zero() const { return data()->zero(); } /** * Proxy has no state. Nothing to reset. */ void reset() { } }; ////////////////////////////////////////////////////////////////////// // // Formula Details // ////////////////////////////////////////////////////////////////////// /** * Base class for formula statistic node. These nodes are used to build a tree * that represents the formula. */ class Node : public RefCounted { public: /** * Return the number of nodes in the subtree starting at this node. * @return the number of nodes in this subtree. */ virtual size_type size() const = 0; /** * Return the result vector of this subtree. * @return The result vector of this subtree. */ virtual const VResult &result() const = 0; /** * Return the total of the result vector. * @return The total of the result vector. */ virtual Result total() const = 0; /** * */ virtual std::string str() const = 0; }; /** Reference counting pointer to a function Node. */ typedef RefCountingPtr NodePtr; class ScalarStatNode : public Node { private: const ScalarInfo *data; mutable VResult vresult; public: ScalarStatNode(const ScalarInfo *d) : data(d), vresult(1) {} const VResult & result() const { vresult[0] = data->result(); return vresult; } Result total() const { return data->result(); }; size_type size() const { return 1; } /** * */ std::string str() const { return data->name; } }; template class ScalarProxyNode : public Node { private: const ScalarProxy proxy; mutable VResult vresult; public: ScalarProxyNode(const ScalarProxy &p) : proxy(p), vresult(1) { } const VResult & result() const { vresult[0] = proxy.result(); return vresult; } Result total() const { return proxy.result(); } size_type size() const { return 1; } /** * */ std::string str() const { return proxy.str(); } }; class VectorStatNode : public Node { private: const VectorInfo *data; public: VectorStatNode(const VectorInfo *d) : data(d) { } const VResult &result() const { return data->result(); } Result total() const { return data->total(); }; size_type size() const { return data->size(); } std::string str() const { return data->name; } }; template class ConstNode : public Node { private: VResult vresult; public: ConstNode(T s) : vresult(1, (Result)s) {} const VResult &result() const { return vresult; } Result total() const { return vresult[0]; }; size_type size() const { return 1; } std::string str() const { return to_string(vresult[0]); } }; template class ConstVectorNode : public Node { private: VResult vresult; public: ConstVectorNode(const T &s) : vresult(s.begin(), s.end()) {} const VResult &result() const { return vresult; } Result total() const { size_type size = this->size(); Result tmp = 0; for (off_type i = 0; i < size; i++) tmp += vresult[i]; return tmp; } size_type size() const { return vresult.size(); } std::string str() const { size_type size = this->size(); std::string tmp = "("; for (off_type i = 0; i < size; i++) tmp += csprintf("%s ",to_string(vresult[i])); tmp += ")"; return tmp; } }; template struct OpString; template<> struct OpString > { static std::string str() { return "+"; } }; template<> struct OpString > { static std::string str() { return "-"; } }; template<> struct OpString > { static std::string str() { return "*"; } }; template<> struct OpString > { static std::string str() { return "/"; } }; template<> struct OpString > { static std::string str() { return "%"; } }; template<> struct OpString > { static std::string str() { return "-"; } }; template class UnaryNode : public Node { public: NodePtr l; mutable VResult vresult; public: UnaryNode(NodePtr &p) : l(p) {} const VResult & result() const { const VResult &lvec = l->result(); size_type size = lvec.size(); assert(size > 0); vresult.resize(size); Op op; for (off_type i = 0; i < size; ++i) vresult[i] = op(lvec[i]); return vresult; } Result total() const { const VResult &vec = this->result(); Result total = 0.0; for (off_type i = 0; i < size(); i++) total += vec[i]; return total; } size_type size() const { return l->size(); } std::string str() const { return OpString::str() + l->str(); } }; template class BinaryNode : public Node { public: NodePtr l; NodePtr r; mutable VResult vresult; public: BinaryNode(NodePtr &a, NodePtr &b) : l(a), r(b) {} const VResult & result() const { Op op; const VResult &lvec = l->result(); const VResult &rvec = r->result(); assert(lvec.size() > 0 && rvec.size() > 0); if (lvec.size() == 1 && rvec.size() == 1) { vresult.resize(1); vresult[0] = op(lvec[0], rvec[0]); } else if (lvec.size() == 1) { size_type size = rvec.size(); vresult.resize(size); for (off_type i = 0; i < size; ++i) vresult[i] = op(lvec[0], rvec[i]); } else if (rvec.size() == 1) { size_type size = lvec.size(); vresult.resize(size); for (off_type i = 0; i < size; ++i) vresult[i] = op(lvec[i], rvec[0]); } else if (rvec.size() == lvec.size()) { size_type size = rvec.size(); vresult.resize(size); for (off_type i = 0; i < size; ++i) vresult[i] = op(lvec[i], rvec[i]); } return vresult; } Result total() const { const VResult &vec = this->result(); const VResult &lvec = l->result(); const VResult &rvec = r->result(); Result total = 0.0; Result lsum = 0.0; Result rsum = 0.0; Op op; assert(lvec.size() > 0 && rvec.size() > 0); assert(lvec.size() == rvec.size() || lvec.size() == 1 || rvec.size() == 1); /** If vectors are the same divide their sums (x0+x1)/(y0+y1) */ if (lvec.size() == rvec.size() && lvec.size() > 1) { for (off_type i = 0; i < size(); ++i) { lsum += lvec[i]; rsum += rvec[i]; } return op(lsum, rsum); } /** Otherwise divide each item by the divisor */ for (off_type i = 0; i < size(); ++i) { total += vec[i]; } return total; } size_type size() const { size_type ls = l->size(); size_type rs = r->size(); if (ls == 1) { return rs; } else if (rs == 1) { return ls; } else { assert(ls == rs && "Node vector sizes are not equal"); return ls; } } std::string str() const { return csprintf("(%s %s %s)", l->str(), OpString::str(), r->str()); } }; template class SumNode : public Node { public: NodePtr l; mutable VResult vresult; public: SumNode(NodePtr &p) : l(p), vresult(1) {} const VResult & result() const { const VResult &lvec = l->result(); size_type size = lvec.size(); assert(size > 0); vresult[0] = 0.0; Op op; for (off_type i = 0; i < size; ++i) vresult[0] = op(vresult[0], lvec[i]); return vresult; } Result total() const { const VResult &lvec = l->result(); size_type size = lvec.size(); assert(size > 0); Result result = 0.0; Op op; for (off_type i = 0; i < size; ++i) result = op(result, lvec[i]); return result; } size_type size() const { return 1; } std::string str() const { return csprintf("total(%s)", l->str()); } }; ////////////////////////////////////////////////////////////////////// // // Visible Statistics Types // ////////////////////////////////////////////////////////////////////// /** * @defgroup VisibleStats "Statistic Types" * These are the statistics that are used in the simulator. * @{ */ /** * This is a simple scalar statistic, like a counter. * @sa Stat, ScalarBase, StatStor */ class Scalar : public ScalarBase { public: using ScalarBase::operator=; }; /** * A stat that calculates the per tick average of a value. * @sa Stat, ScalarBase, AvgStor */ class Average : public ScalarBase { public: using ScalarBase::operator=; }; class Value : public ValueBase { }; /** * A vector of scalar stats. * @sa Stat, VectorBase, StatStor */ class Vector : public VectorBase { }; /** * A vector of Average stats. * @sa Stat, VectorBase, AvgStor */ class AverageVector : public VectorBase { }; /** * A 2-Dimensional vecto of scalar stats. * @sa Stat, Vector2dBase, StatStor */ class Vector2d : public Vector2dBase { }; /** * A simple distribution stat. * @sa Stat, DistBase, DistStor */ class Distribution : public DistBase { public: /** * Set the parameters of this distribution. @sa DistStor::Params * @param min The minimum value of the distribution. * @param max The maximum value of the distribution. * @param bkt The number of values in each bucket. * @return A reference to this distribution. */ Distribution & init(Counter min, Counter max, Counter bkt) { DistStor::Params *params = new DistStor::Params; params->min = min; params->max = max; params->bucket_size = bkt; params->buckets = (size_type)ceil((max - min + 1.0) / bkt); this->setParams(params); this->doInit(); return this->self(); } }; /** * A simple histogram stat. * @sa Stat, DistBase, HistStor */ class Histogram : public DistBase { public: /** * Set the parameters of this histogram. @sa HistStor::Params * @param size The number of buckets in the histogram * @return A reference to this histogram. */ Histogram & init(size_type size) { HistStor::Params *params = new HistStor::Params; params->buckets = size; this->setParams(params); this->doInit(); return this->self(); } }; /** * Calculates the mean and variance of all the samples. * @sa DistBase, SampleStor */ class StandardDeviation : public DistBase { public: /** * Construct and initialize this distribution. */ StandardDeviation() { SampleStor::Params *params = new SampleStor::Params; this->doInit(); this->setParams(params); } }; /** * Calculates the per tick mean and variance of the samples. * @sa DistBase, AvgSampleStor */ class AverageDeviation : public DistBase { public: /** * Construct and initialize this distribution. */ AverageDeviation() { AvgSampleStor::Params *params = new AvgSampleStor::Params; this->doInit(); this->setParams(params); } }; /** * A vector of distributions. * @sa VectorDistBase, DistStor */ class VectorDistribution : public VectorDistBase { public: /** * Initialize storage and parameters for this distribution. * @param size The size of the vector (the number of distributions). * @param min The minimum value of the distribution. * @param max The maximum value of the distribution. * @param bkt The number of values in each bucket. * @return A reference to this distribution. */ VectorDistribution & init(size_type size, Counter min, Counter max, Counter bkt) { DistStor::Params *params = new DistStor::Params; params->min = min; params->max = max; params->bucket_size = bkt; params->buckets = (size_type)ceil((max - min + 1.0) / bkt); this->setParams(params); this->doInit(size); return this->self(); } }; /** * This is a vector of StandardDeviation stats. * @sa VectorDistBase, SampleStor */ class VectorStandardDeviation : public VectorDistBase { public: /** * Initialize storage for this distribution. * @param size The size of the vector. * @return A reference to this distribution. */ VectorStandardDeviation & init(size_type size) { SampleStor::Params *params = new SampleStor::Params; this->doInit(size); this->setParams(params); return this->self(); } }; /** * This is a vector of AverageDeviation stats. * @sa VectorDistBase, AvgSampleStor */ class VectorAverageDeviation : public VectorDistBase { public: /** * Initialize storage for this distribution. * @param size The size of the vector. * @return A reference to this distribution. */ VectorAverageDeviation & init(size_type size) { AvgSampleStor::Params *params = new AvgSampleStor::Params; this->doInit(size); this->setParams(params); return this->self(); } }; template class FormulaInfoProxy : public InfoProxy { protected: mutable VResult vec; mutable VCounter cvec; public: FormulaInfoProxy(Stat &stat) : InfoProxy(stat) {} size_type size() const { return this->s.size(); } const VResult & result() const { this->s.result(vec); return vec; } Result total() const { return this->s.total(); } VCounter &value() const { return cvec; } std::string str() const { return this->s.str(); } }; template class SparseHistInfoProxy : public InfoProxy { public: SparseHistInfoProxy(Stat &stat) : InfoProxy(stat) {} }; /** * Implementation of a sparse histogram stat. The storage class is * determined by the Storage template. */ template class SparseHistBase : public DataWrap { public: typedef SparseHistInfoProxy Info; typedef Stor Storage; typedef typename Stor::Params Params; protected: /** The storage for this stat. */ char storage[sizeof(Storage)]; protected: /** * Retrieve the storage. * @return The storage object for this stat. */ Storage * data() { return reinterpret_cast(storage); } /** * Retrieve a const pointer to the storage. * @return A const pointer to the storage object for this stat. */ const Storage * data() const { return reinterpret_cast(storage); } void doInit() { new (storage) Storage(this->info()); this->setInit(); } public: SparseHistBase() { } /** * Add a value to the distribtion n times. Calls sample on the storage * class. * @param v The value to add. * @param n The number of times to add it, defaults to 1. */ template void sample(const U &v, int n = 1) { data()->sample(v, n); } /** * Return the number of entries in this stat. * @return The number of entries. */ size_type size() const { return data()->size(); } /** * Return true if no samples have been added. * @return True if there haven't been any samples. */ bool zero() const { return data()->zero(); } void prepare() { Info *info = this->info(); data()->prepare(info, info->data); } /** * Reset stat value to default */ void reset() { data()->reset(this->info()); } }; /** * Templatized storage and interface for a sparse histogram stat. */ class SparseHistStor { public: /** The parameters for a sparse histogram stat. */ struct Params : public DistParams { Params() : DistParams(Hist) {} }; private: /** Counter for number of samples */ Counter samples; /** Counter for each bucket. */ MCounter cmap; public: SparseHistStor(Info *info) { reset(info); } /** * Add a value to the distribution for the given number of times. * @param val The value to add. * @param number The number of times to add the value. */ void sample(Counter val, int number) { cmap[val] += number; samples += number; } /** * Return the number of buckets in this distribution. * @return the number of buckets. */ size_type size() const { return cmap.size(); } /** * Returns true if any calls to sample have been made. * @return True if any values have been sampled. */ bool zero() const { return samples == Counter(); } void prepare(Info *info, SparseHistData &data) { MCounter::iterator it; data.cmap.clear(); for (it = cmap.begin(); it != cmap.end(); it++) { data.cmap[(*it).first] = (*it).second; } data.samples = samples; } /** * Reset stat value to default */ void reset(Info *info) { cmap.clear(); samples = 0; } }; class SparseHistogram : public SparseHistBase { public: /** * Set the parameters of this histogram. @sa HistStor::Params * @param size The number of buckets in the histogram * @return A reference to this histogram. */ SparseHistogram & init(size_type size) { SparseHistStor::Params *params = new SparseHistStor::Params; this->setParams(params); this->doInit(); return this->self(); } }; class Temp; /** * A formula for statistics that is calculated when printed. A formula is * stored as a tree of Nodes that represent the equation to calculate. * @sa Stat, ScalarStat, VectorStat, Node, Temp */ class Formula : public DataWrapVec { protected: /** The root of the tree which represents the Formula */ NodePtr root; friend class Temp; public: /** * Create and initialize thie formula, and register it with the database. */ Formula(); /** * Create a formula with the given root node, register it with the * database. * @param r The root of the expression tree. */ Formula(Temp r); /** * Set an unitialized Formula to the given root. * @param r The root of the expression tree. * @return a reference to this formula. */ const Formula &operator=(Temp r); /** * Add the given tree to the existing one. * @param r The root of the expression tree. * @return a reference to this formula. */ const Formula &operator+=(Temp r); /** * Return the result of the Fomula in a vector. If there were no Vector * components to the Formula, then the vector is size 1. If there were, * like x/y with x being a vector of size 3, then the result returned will * be x[0]/y, x[1]/y, x[2]/y, respectively. * @return The result vector. */ void result(VResult &vec) const; /** * Return the total Formula result. If there is a Vector * component to this Formula, then this is the result of the * Formula if the formula is applied after summing all the * components of the Vector. For example, if Formula is x/y where * x is size 3, then total() will return (x[1]+x[2]+x[3])/y. If * there is no Vector component, total() returns the same value as * the first entry in the VResult val() returns. * @return The total of the result vector. */ Result total() const; /** * Return the number of elements in the tree. */ size_type size() const; void prepare() { } /** * Formulas don't need to be reset */ void reset(); /** * */ bool zero() const; std::string str() const; }; class FormulaNode : public Node { private: const Formula &formula; mutable VResult vec; public: FormulaNode(const Formula &f) : formula(f) {} size_type size() const { return formula.size(); } const VResult &result() const { formula.result(vec); return vec; } Result total() const { return formula.total(); } std::string str() const { return formula.str(); } }; /** * Helper class to construct formula node trees. */ class Temp { protected: /** * Pointer to a Node object. */ NodePtr node; public: /** * Copy the given pointer to this class. * @param n A pointer to a Node object to copy. */ Temp(NodePtr n) : node(n) { } /** * Return the node pointer. * @return the node pointer. */ operator NodePtr&() { return node; } public: /** * Create a new ScalarStatNode. * @param s The ScalarStat to place in a node. */ Temp(const Scalar &s) : node(new ScalarStatNode(s.info())) { } /** * Create a new ScalarStatNode. * @param s The ScalarStat to place in a node. */ Temp(const Value &s) : node(new ScalarStatNode(s.info())) { } /** * Create a new ScalarStatNode. * @param s The ScalarStat to place in a node. */ Temp(const Average &s) : node(new ScalarStatNode(s.info())) { } /** * Create a new VectorStatNode. * @param s The VectorStat to place in a node. */ Temp(const Vector &s) : node(new VectorStatNode(s.info())) { } Temp(const AverageVector &s) : node(new VectorStatNode(s.info())) { } /** * */ Temp(const Formula &f) : node(new FormulaNode(f)) { } /** * Create a new ScalarProxyNode. * @param p The ScalarProxy to place in a node. */ template Temp(const ScalarProxy &p) : node(new ScalarProxyNode(p)) { } /** * Create a ConstNode * @param value The value of the const node. */ Temp(signed char value) : node(new ConstNode(value)) { } /** * Create a ConstNode * @param value The value of the const node. */ Temp(unsigned char value) : node(new ConstNode(value)) { } /** * Create a ConstNode * @param value The value of the const node. */ Temp(signed short value) : node(new ConstNode(value)) { } /** * Create a ConstNode * @param value The value of the const node. */ Temp(unsigned short value) : node(new ConstNode(value)) { } /** * Create a ConstNode * @param value The value of the const node. */ Temp(signed int value) : node(new ConstNode(value)) { } /** * Create a ConstNode * @param value The value of the const node. */ Temp(unsigned int value) : node(new ConstNode(value)) { } /** * Create a ConstNode * @param value The value of the const node. */ Temp(signed long value) : node(new ConstNode(value)) { } /** * Create a ConstNode * @param value The value of the const node. */ Temp(unsigned long value) : node(new ConstNode(value)) { } /** * Create a ConstNode * @param value The value of the const node. */ Temp(signed long long value) : node(new ConstNode(value)) { } /** * Create a ConstNode * @param value The value of the const node. */ Temp(unsigned long long value) : node(new ConstNode(value)) { } /** * Create a ConstNode * @param value The value of the const node. */ Temp(float value) : node(new ConstNode(value)) { } /** * Create a ConstNode * @param value The value of the const node. */ Temp(double value) : node(new ConstNode(value)) { } }; /** * @} */ inline Temp operator+(Temp l, Temp r) { return NodePtr(new BinaryNode >(l, r)); } inline Temp operator-(Temp l, Temp r) { return NodePtr(new BinaryNode >(l, r)); } inline Temp operator*(Temp l, Temp r) { return NodePtr(new BinaryNode >(l, r)); } inline Temp operator/(Temp l, Temp r) { return NodePtr(new BinaryNode >(l, r)); } inline Temp operator-(Temp l) { return NodePtr(new UnaryNode >(l)); } template inline Temp constant(T val) { return NodePtr(new ConstNode(val)); } template inline Temp constantVector(T val) { return NodePtr(new ConstVectorNode(val)); } inline Temp sum(Temp val) { return NodePtr(new SumNode >(val)); } /** Dump all statistics data to the registered outputs */ void dump(); void reset(); void enable(); bool enabled(); /** * Register a callback that should be called whenever statistics are * reset */ void registerResetCallback(Callback *cb); /** * Register a callback that should be called whenever statistics are * about to be dumped */ void registerDumpCallback(Callback *cb); std::list &statsList(); typedef std::map MapType; MapType &statsMap(); typedef std::map NameMapType; NameMapType &nameMap(); bool validateStatName(const std::string &name); } // namespace Stats void debugDumpStats(); #endif // __BASE_STATISTICS_HH__