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/*
* Copyright (c) 2019-2020 Arm Limited
* All rights reserved.
*
* The license below extends only to copyright in the software and shall
* not be construed as granting a license to any other intellectual
* property including but not limited to intellectual property relating
* to a hardware implementation of the functionality of the software
* licensed hereunder. You may use the software subject to the license
* terms below provided that you ensure that this notice is replicated
* unmodified and in its entirety in all distributions of the software,
* modified or unmodified, in source code or in binary form.
*
* Copyright (c) 2003-2005 The Regents of The University of Michigan
* Copyright (c) 2017, Centre National de la Recherche Scientifique
* 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,
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* 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.
*/
/** @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 <algorithm>
#include <cassert>
#ifdef __SUNPRO_CC
#include <math.h>
#endif
#include <cmath>
#include <functional>
#include <iosfwd>
#include <list>
#include <map>
#include <memory>
#include <string>
#include <vector>
#include "base/stats/group.hh"
#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/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 Stat, class Base>
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<Base *>(this));
}
bool zero() const { return s.zero(); }
};
template <class Stat>
class ScalarInfoProxy : public InfoProxy<Stat, ScalarInfo>
{
public:
ScalarInfoProxy(Stat &stat) : InfoProxy<Stat, ScalarInfo>(stat) {}
Counter value() const { return this->s.value(); }
Result result() const { return this->s.result(); }
Result total() const { return this->s.total(); }
};
template <class Stat>
class VectorInfoProxy : public InfoProxy<Stat, VectorInfo>
{
protected:
mutable VCounter cvec;
mutable VResult rvec;
public:
VectorInfoProxy(Stat &stat) : InfoProxy<Stat, VectorInfo>(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 Stat>
class DistInfoProxy : public InfoProxy<Stat, DistInfo>
{
public:
DistInfoProxy(Stat &stat) : InfoProxy<Stat, DistInfo>(stat) {}
};
template <class Stat>
class VectorDistInfoProxy : public InfoProxy<Stat, VectorDistInfo>
{
public:
VectorDistInfoProxy(Stat &stat) : InfoProxy<Stat, VectorDistInfo>(stat) {}
size_type size() const { return this->s.size(); }
};
template <class Stat>
class Vector2dInfoProxy : public InfoProxy<Stat, Vector2dInfo>
{
public:
Vector2dInfoProxy(Stat &stat) : InfoProxy<Stat, Vector2dInfo>(stat) {}
Result total() const { return this->s.total(); }
};
struct StorageParams
{
virtual ~StorageParams();
};
class InfoAccess
{
private:
Info *_info;
protected:
/** Set up an info class for this statistic */
void setInfo(Group *parent, 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:
InfoAccess()
: _info(nullptr) {};
/**
* 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 Derived, template <class> class InfoProxyType>
class DataWrap : public InfoAccess
{
public:
typedef InfoProxyType<Derived> Info;
protected:
Derived &self() { return *static_cast<Derived *>(this); }
protected:
Info *
info()
{
return safe_cast<Info *>(InfoAccess::info());
}
public:
const Info *
info() const
{
return safe_cast<const Info *>(InfoAccess::info());
}
public:
DataWrap() = delete;
DataWrap(const DataWrap &) = delete;
DataWrap &operator=(const DataWrap &) = delete;
DataWrap(Group *parent, const char *name, const char *desc)
{
auto info = new Info(self());
this->setInfo(parent, info);
if (parent)
parent->addStat(info);
if (name) {
info->setName(parent, name);
info->flags.set(display);
}
if (desc)
info->desc = desc;
}
/**
* 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 <class Stat>
Derived &
prereq(const Stat &prereq)
{
this->info()->prereq = prereq.info();
return this->self();
}
};
template <class Derived, template <class> class InfoProxyType>
class DataWrapVec : public DataWrap<Derived, InfoProxyType>
{
public:
typedef InfoProxyType<Derived> Info;
DataWrapVec(Group *parent = nullptr, const char *name = nullptr,
const char *desc = nullptr)
: DataWrap<Derived, InfoProxyType>(parent, name, desc)
{}
// 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<std::string> &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<std::string> &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 Derived, template <class> class InfoProxyType>
class DataWrapVec2d : public DataWrapVec<Derived, InfoProxyType>
{
public:
typedef InfoProxyType<Derived> Info;
DataWrapVec2d(Group *parent, const char *name, const char *desc)
: DataWrapVec<Derived, InfoProxyType>(parent, name, desc)
{
}
/**
* @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 Derived, class Stor>
class ScalarBase : public DataWrap<Derived, ScalarInfoProxy>
{
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 *>(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<const Storage *>(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(Group *parent = nullptr, const char *name = nullptr,
const char *desc = nullptr)
: DataWrap<Derived, ScalarInfoProxy>(parent, name, desc)
{
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 <typename U>
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 <typename U>
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 <typename U>
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 std::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 T>
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 T>
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)(); }
};
/**
* A proxy similar to the FunctorProxy, but allows calling a method of a bound
* object, instead of a global free-standing function.
*/
template <class T, class V>
class MethodProxy : public ProxyInfo
{
private:
T *object;
typedef V (T::*MethodPointer) () const;
MethodPointer method;
public:
MethodProxy(T *obj, MethodPointer meth) : object(obj), method(meth) {}
Counter value() const { return (object->*method)(); }
Result result() const { return (object->*method)(); }
Result total() const { return (object->*method)(); }
};
template <class Derived>
class ValueBase : public DataWrap<Derived, ScalarInfoProxy>
{
private:
ProxyInfo *proxy;
public:
ValueBase(Group *parent, const char *name, const char *desc)
: DataWrap<Derived, ScalarInfoProxy>(parent, name, desc),
proxy(NULL)
{
}
~ValueBase() { if (proxy) delete proxy; }
template <class T>
Derived &
scalar(T &value)
{
proxy = new ValueProxy<T>(value);
this->setInit();
return this->self();
}
template <class T>
Derived &
functor(T &func)
{
proxy = new FunctorProxy<T>(func);
this->setInit();
return this->self();
}
/**
* Extended functor that calls the specified method of the provided object.
*
* @param obj Pointer to the object whose method should be called.
* @param method Pointer of the function / method of the object.
* @return Updated stats item.
*/
template <class T, class V>
Derived &
method(T *obj, V (T::*method)() const)
{
proxy = new MethodProxy<T,V>(obj, method);
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 Stat>
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 <typename U>
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 <typename U>
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 <typename U>
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 Derived, class Stor>
class VectorBase : public DataWrapVec<Derived, VectorInfoProxy>
{
public:
typedef Stor Storage;
typedef typename Stor::Params Params;
/** Proxy type */
typedef ScalarProxy<Derived> Proxy;
friend class ScalarProxy<Derived>;
friend class DataWrapVec<Derived, VectorInfoProxy>;
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<Storage *>(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(Group *parent, const char *name, const char *desc)
: DataWrapVec<Derived, VectorInfoProxy>(parent, name, desc),
storage(nullptr), _size(0)
{}
~VectorBase()
{
if (!storage)
return;
for (off_type i = 0; i < _size; ++i)
data(i)->~Storage();
delete [] reinterpret_cast<char *>(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 Stat>
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<Stat>
operator[](off_type index)
{
assert (index >= 0 && index < size());
return ScalarProxy<Stat>(stat, offset + index);
}
size_type size() const { return len; }
};
template <class Derived, class Stor>
class Vector2dBase : public DataWrapVec2d<Derived, Vector2dInfoProxy>
{
public:
typedef Vector2dInfoProxy<Derived> Info;
typedef Stor Storage;
typedef typename Stor::Params Params;
typedef VectorProxy<Derived> Proxy;
friend class ScalarProxy<Derived>;
friend class VectorProxy<Derived>;
friend class DataWrapVec<Derived, Vector2dInfoProxy>;
friend class DataWrapVec2d<Derived, Vector2dInfoProxy>;
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(Group *parent, const char *name, const char *desc)
: DataWrapVec2d<Derived, Vector2dInfoProxy>(parent, name, desc),
x(0), y(0), _size(0), storage(nullptr)
{}
~Vector2dBase()
{
if (!storage)
return;
for (off_type i = 0; i < _size; ++i)
data(i)->~Storage();
delete [] reinterpret_cast<char *>(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<Storage *>(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();
}
/**
* 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;
}
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 distribution 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), min(0), max(0), bucket_size(0),
buckets(0) {}
};
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 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<const Params *>(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<const Params *>(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<const Params *>(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), buckets(0) {}
};
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<const Params *>(info->storageParams)->buckets)
{
reset(info);
}
void grow_up();
void grow_out();
void grow_convert();
void add(HistStor *);
/**
* 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 < 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<const Params *>(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<const Params *>(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)
{
sum += val * number;
squares += val * val * number;
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<const Params *>(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)
{
sum += val * number;
squares += val * val * number;
}
/**
* 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<const Params *>(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 Derived, class Stor>
class DistBase : public DataWrap<Derived, DistInfoProxy>
{
public:
typedef DistInfoProxy<Derived> 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 *>(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<const Storage *>(storage);
}
void
doInit()
{
new (storage) Storage(this->info());
this->setInit();
}
public:
DistBase(Group *parent, const char *name, const char *desc)
: DataWrap<Derived, DistInfoProxy>(parent, name, desc)
{
}
/**
* 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 <typename U>
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());
}
/**
* Add the argument distribution to the this distribution.
*/
void add(DistBase &d) { data()->add(d.data()); }
};
template <class Stat>
class DistProxy;
template <class Derived, class Stor>
class VectorDistBase : public DataWrapVec<Derived, VectorDistInfoProxy>
{
public:
typedef VectorDistInfoProxy<Derived> Info;
typedef Stor Storage;
typedef typename Stor::Params Params;
typedef DistProxy<Derived> Proxy;
friend class DistProxy<Derived>;
friend class DataWrapVec<Derived, VectorDistInfoProxy>;
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<Storage *>(ptr);
Info *info = this->info();
for (off_type i = 0; i < _size; ++i)
new (&storage[i]) Storage(info);
this->setInit();
}
public:
VectorDistBase(Group *parent, const char *name, const char *desc)
: DataWrapVec<Derived, VectorDistInfoProxy>(parent, name, desc),
storage(NULL)
{}
~VectorDistBase()
{
if (!storage)
return ;
for (off_type i = 0; i < _size; ++i)
data(i)->~Storage();
delete [] reinterpret_cast<char *>(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 Stat>
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 <typename U>
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:
/**
* 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;
virtual ~Node() {};
};
/** Shared pointer to a function Node. */
typedef std::shared_ptr<Node> 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 Stat>
class ScalarProxyNode : public Node
{
private:
const ScalarProxy<Stat> proxy;
mutable VResult vresult;
public:
ScalarProxyNode(const ScalarProxy<Stat> &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 T>
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 std::to_string(vresult[0]); }
};
template <class T>
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 ", std::to_string(vresult[i]));
tmp += ")";
return tmp;
}
};
template <class Op>
struct OpString;
template<>
struct OpString<std::plus<Result> >
{
static std::string str() { return "+"; }
};
template<>
struct OpString<std::minus<Result> >
{
static std::string str() { return "-"; }
};
template<>
struct OpString<std::multiplies<Result> >
{
static std::string str() { return "*"; }
};
template<>
struct OpString<std::divides<Result> >
{
static std::string str() { return "/"; }
};
template<>
struct OpString<std::modulus<Result> >
{
static std::string str() { return "%"; }
};
template<>
struct OpString<std::negate<Result> >
{
static std::string str() { return "-"; }
};
template <class Op>
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<Op>::str() + l->str();
}
};
template <class Op>
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 override
{
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 override
{
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 override
{
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 override
{
return csprintf("(%s %s %s)", l->str(), OpString<Op>::str(), r->str());
}
};
template <class Op>
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<Scalar, StatStor>
{
public:
using ScalarBase<Scalar, StatStor>::operator=;
Scalar(Group *parent = nullptr, const char *name = nullptr,
const char *desc = nullptr)
: ScalarBase<Scalar, StatStor>(parent, name, desc)
{
}
};
/**
* A stat that calculates the per tick average of a value.
* @sa Stat, ScalarBase, AvgStor
*/
class Average : public ScalarBase<Average, AvgStor>
{
public:
using ScalarBase<Average, AvgStor>::operator=;
Average(Group *parent = nullptr, const char *name = nullptr,
const char *desc = nullptr)
: ScalarBase<Average, AvgStor>(parent, name, desc)
{
}
};
class Value : public ValueBase<Value>
{
public:
Value(Group *parent = nullptr, const char *name = nullptr,
const char *desc = nullptr)
: ValueBase<Value>(parent, name, desc)
{
}
};
/**
* A vector of scalar stats.
* @sa Stat, VectorBase, StatStor
*/
class Vector : public VectorBase<Vector, StatStor>
{
public:
Vector(Group *parent = nullptr, const char *name = nullptr,
const char *desc = nullptr)
: VectorBase<Vector, StatStor>(parent, name, desc)
{
}
};
/**
* A vector of Average stats.
* @sa Stat, VectorBase, AvgStor
*/
class AverageVector : public VectorBase<AverageVector, AvgStor>
{
public:
AverageVector(Group *parent = nullptr, const char *name = nullptr,
const char *desc = nullptr)
: VectorBase<AverageVector, AvgStor>(parent, name, desc)
{
}
};
/**
* A 2-Dimensional vecto of scalar stats.
* @sa Stat, Vector2dBase, StatStor
*/
class Vector2d : public Vector2dBase<Vector2d, StatStor>
{
public:
Vector2d(Group *parent = nullptr, const char *name = nullptr,
const char *desc = nullptr)
: Vector2dBase<Vector2d, StatStor>(parent, name, desc)
{
}
};
/**
* A simple distribution stat.
* @sa Stat, DistBase, DistStor
*/
class Distribution : public DistBase<Distribution, DistStor>
{
public:
Distribution(Group *parent = nullptr, const char *name = nullptr,
const char *desc = nullptr)
: DistBase<Distribution, DistStor>(parent, name, desc)
{
}
/**
* 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;
// Division by zero is especially serious in an Aarch64 host,
// where it gets rounded to allocate 32GiB RAM.
assert(bkt > 0);
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<Histogram, HistStor>
{
public:
Histogram(Group *parent = nullptr, const char *name = nullptr,
const char *desc = nullptr)
: DistBase<Histogram, HistStor>(parent, name, desc)
{
}
/**
* 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<StandardDeviation, SampleStor>
{
public:
/**
* Construct and initialize this distribution.
*/
StandardDeviation(Group *parent = nullptr, const char *name = nullptr,
const char *desc = nullptr)
: DistBase<StandardDeviation, SampleStor>(parent, name, desc)
{
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<AverageDeviation, AvgSampleStor>
{
public:
/**
* Construct and initialize this distribution.
*/
AverageDeviation(Group *parent = nullptr, const char *name = nullptr,
const char *desc = nullptr)
: DistBase<AverageDeviation, AvgSampleStor>(parent, name, desc)
{
AvgSampleStor::Params *params = new AvgSampleStor::Params;
this->doInit();
this->setParams(params);
}
};
/**
* A vector of distributions.
* @sa VectorDistBase, DistStor
*/
class VectorDistribution : public VectorDistBase<VectorDistribution, DistStor>
{
public:
VectorDistribution(Group *parent = nullptr, const char *name = nullptr,
const char *desc = nullptr)
: VectorDistBase<VectorDistribution, DistStor>(parent, name, desc)
{
}
/**
* 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<VectorStandardDeviation, SampleStor>
{
public:
VectorStandardDeviation(Group *parent = nullptr, const char *name = nullptr,
const char *desc = nullptr)
: VectorDistBase<VectorStandardDeviation, SampleStor>(parent, name,
desc)
{
}
/**
* 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<VectorAverageDeviation, AvgSampleStor>
{
public:
VectorAverageDeviation(Group *parent = nullptr, const char *name = nullptr,
const char *desc = nullptr)
: VectorDistBase<VectorAverageDeviation, AvgSampleStor>(parent, name,
desc)
{
}
/**
* 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 Stat>
class FormulaInfoProxy : public InfoProxy<Stat, FormulaInfo>
{
protected:
mutable VResult vec;
mutable VCounter cvec;
public:
FormulaInfoProxy(Stat &stat) : InfoProxy<Stat, FormulaInfo>(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 Stat>
class SparseHistInfoProxy : public InfoProxy<Stat, SparseHistInfo>
{
public:
SparseHistInfoProxy(Stat &stat) : InfoProxy<Stat, SparseHistInfo>(stat) {}
};
/**
* Implementation of a sparse histogram stat. The storage class is
* determined by the Storage template.
*/
template <class Derived, class Stor>
class SparseHistBase : public DataWrap<Derived, SparseHistInfoProxy>
{
public:
typedef SparseHistInfoProxy<Derived> 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 *>(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<const Storage *>(storage);
}
void
doInit()
{
new (storage) Storage(this->info());
this->setInit();
}
public:
SparseHistBase(Group *parent, const char *name, const char *desc)
: DataWrap<Derived, SparseHistInfoProxy>(parent, name, desc)
{
}
/**
* 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 <typename U>
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<SparseHistogram, SparseHistStor>
{
public:
SparseHistogram(Group *parent = nullptr, const char *name = nullptr,
const char *desc = nullptr)
: SparseHistBase<SparseHistogram, SparseHistStor>(parent, name, desc)
{
}
/**
* 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<Formula, FormulaInfoProxy>
{
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(Group *parent = nullptr, const char *name = nullptr,
const char *desc = nullptr);
Formula(Group *parent, const char *name, const char *desc,
const 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=(const Temp &r);
template<typename T>
const Formula &operator=(const T &v)
{
*this = Temp(v);
return *this;
}
/**
* 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);
/**
* Divide the existing tree by the given 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(const NodePtr &n) : node(n) { }
Temp(NodePtr &&n) : node(std::move(n)) { }
/**
* Return the node pointer.
* @return the node pointer.
*/
operator NodePtr&() { return node; }
/**
* Makde gcc < 4.6.3 happy and explicitly get the underlying node.
*/
NodePtr getNodePtr() const { 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 <class Stat>
Temp(const ScalarProxy<Stat> &p)
: node(new ScalarProxyNode<Stat>(p))
{ }
/**
* Create a ConstNode
* @param value The value of the const node.
*/
Temp(signed char value)
: node(new ConstNode<signed char>(value))
{ }
/**
* Create a ConstNode
* @param value The value of the const node.
*/
Temp(unsigned char value)
: node(new ConstNode<unsigned char>(value))
{ }
/**
* Create a ConstNode
* @param value The value of the const node.
*/
Temp(signed short value)
: node(new ConstNode<signed short>(value))
{ }
/**
* Create a ConstNode
* @param value The value of the const node.
*/
Temp(unsigned short value)
: node(new ConstNode<unsigned short>(value))
{ }
/**
* Create a ConstNode
* @param value The value of the const node.
*/
Temp(signed int value)
: node(new ConstNode<signed int>(value))
{ }
/**
* Create a ConstNode
* @param value The value of the const node.
*/
Temp(unsigned int value)
: node(new ConstNode<unsigned int>(value))
{ }
/**
* Create a ConstNode
* @param value The value of the const node.
*/
Temp(signed long value)
: node(new ConstNode<signed long>(value))
{ }
/**
* Create a ConstNode
* @param value The value of the const node.
*/
Temp(unsigned long value)
: node(new ConstNode<unsigned long>(value))
{ }
/**
* Create a ConstNode
* @param value The value of the const node.
*/
Temp(signed long long value)
: node(new ConstNode<signed long long>(value))
{ }
/**
* Create a ConstNode
* @param value The value of the const node.
*/
Temp(unsigned long long value)
: node(new ConstNode<unsigned long long>(value))
{ }
/**
* Create a ConstNode
* @param value The value of the const node.
*/
Temp(float value)
: node(new ConstNode<float>(value))
{ }
/**
* Create a ConstNode
* @param value The value of the const node.
*/
Temp(double value)
: node(new ConstNode<double>(value))
{ }
};
/**
* @}
*/
inline Temp
operator+(Temp l, Temp r)
{
return Temp(std::make_shared<BinaryNode<std::plus<Result> > >(l, r));
}
inline Temp
operator-(Temp l, Temp r)
{
return Temp(std::make_shared<BinaryNode<std::minus<Result> > >(l, r));
}
inline Temp
operator*(Temp l, Temp r)
{
return Temp(std::make_shared<BinaryNode<std::multiplies<Result> > >(l, r));
}
inline Temp
operator/(Temp l, Temp r)
{
return Temp(std::make_shared<BinaryNode<std::divides<Result> > >(l, r));
}
inline Temp
operator-(Temp l)
{
return Temp(std::make_shared<UnaryNode<std::negate<Result> > >(l));
}
template <typename T>
inline Temp
constant(T val)
{
return Temp(std::make_shared<ConstNode<T> >(val));
}
template <typename T>
inline Temp
constantVector(T val)
{
return Temp(std::make_shared<ConstVectorNode<T> >(val));
}
inline Temp
sum(Temp val)
{
return Temp(std::make_shared<SumNode<std::plus<Result> > >(val));
}
/** Dump all statistics data to the registered outputs */
void dump();
void reset();
void enable();
bool enabled();
const Info* resolve(const std::string &name);
/**
* Register reset and dump handlers. These are the functions which
* will actually perform the whole statistics reset/dump actions
* including processing the reset/dump callbacks
*/
typedef void (*Handler)();
void registerHandlers(Handler reset_handler, Handler dump_handler);
/**
* 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);
/**
* Process all the callbacks in the reset callbacks queue
*/
void processResetQueue();
/**
* Process all the callbacks in the dump callbacks queue
*/
void processDumpQueue();
std::list<Info *> &statsList();
typedef std::map<const void *, Info *> MapType;
MapType &statsMap();
typedef std::map<std::string, Info *> NameMapType;
NameMapType &nameMap();
bool validateStatName(const std::string &name);
} // namespace Stats
void debugDumpStats();
#endif // __BASE_STATISTICS_HH__