A Discrete-Event Network Simulator
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basic-data-calculators.h
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1 /* -*- Mode:C++; c-file-style:"gnu"; indent-tabs-mode:nil; -*- */
2 /*
3  * Copyright (c) 2008 Drexel University
4  *
5  * This program is free software; you can redistribute it and/or modify
6  * it under the terms of the GNU General Public License version 2 as
7  * published by the Free Software Foundation;
8  *
9  * This program is distributed in the hope that it will be useful,
10  * but WITHOUT ANY WARRANTY; without even the implied warranty of
11  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
12  * GNU General Public License for more details.
13  *
14  * You should have received a copy of the GNU General Public License
15  * along with this program; if not, write to the Free Software
16  * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
17  *
18  * Author: Joe Kopena (tjkopena@cs.drexel.edu)
19  */
20 
21 #ifndef BASIC_DATA_CALCULATORS_H
22 #define BASIC_DATA_CALCULATORS_H
23 
24 #include "data-calculator.h"
25 #include "data-output-interface.h"
26 #include "ns3/type-name.h"
27 
28 namespace ns3 {
29 
36 //------------------------------------------------------------
37 //--------------------------------------------
38 template <typename T = uint32_t>
40  public StatisticalSummary {
41 public:
43  virtual ~MinMaxAvgTotalCalculator();
44 
49  static TypeId GetTypeId (void);
50 
55  void Update (const T i);
59  void Reset ();
60 
65  virtual void Output (DataOutputCallback &callback) const;
66 
71  long getCount () const { return m_count; }
76  double getSum () const { return m_total; }
81  double getMin () const { return m_min; }
86  double getMax () const { return m_max; }
91  double getMean () const { return m_meanCurr; }
96  double getStddev () const { return std::sqrt (m_varianceCurr); }
101  double getVariance () const { return m_varianceCurr; }
106  double getSqrSum () const { return m_squareTotal; }
107 
108 protected:
109  virtual void DoDispose (void);
110 
111  uint32_t m_count;
112 
115  T m_min;
116  T m_max;
117 
118  double m_meanCurr;
119  double m_sCurr;
120  double m_varianceCurr;
121 
122  double m_meanPrev;
123  double m_sPrev;
124 
125  // end MinMaxAvgTotalCalculator
126 };
127 
128 //----------------------------------------------
129 template <typename T>
131 {
132  m_count = 0;
133 
134  m_total = 0;
135  m_squareTotal = 0;
136 
137  m_meanCurr = NaN;
138  m_sCurr = NaN;
139  m_varianceCurr = NaN;
140 
141  m_meanPrev = NaN;
142  m_sPrev = NaN;
143 }
144 
145 template <typename T>
147 {
148 }
149 
150 template <typename T>
151 void
153 {
155  // MinMaxAvgTotalCalculator::DoDispose
156 }
157 
158 /* static */
159 template <typename T>
160 TypeId
162 {
163  static TypeId tid = TypeId ( ("ns3::MinMaxAvgTotalCalculator<"
164  + TypeNameGet<T> ()
165  + ">").c_str () )
166  .SetParent<Object> ()
167  .SetGroupName ("Stats")
168  .AddConstructor<MinMaxAvgTotalCalculator<T> > ()
169  ;
170  return tid;
171 }
172 
173 template <typename T>
174 void
176 {
177  if (m_enabled) {
178  m_count++;
179 
180  m_total += i;
181  m_squareTotal += i*i;
182 
183  if (m_count == 1)
184  {
185  m_min = i;
186  m_max = i;
187  }
188  else
189  {
190  m_min = (i < m_min) ? i : m_min;
191  m_max = (i > m_max) ? i : m_max;
192  }
193 
194  // Calculate the variance based on equations (15) and (16) on
195  // page 216 of "The Art of Computer Programming, Volume 2",
196  // Second Edition. Donald E. Knuth. Addison-Wesley
197  // Publishing Company, 1973.
198  //
199  // The relationships between the variance, standard deviation,
200  // and s are as follows
201  //
202  // s
203  // variance = -----------
204  // count - 1
205  //
206  // -------------
207  // /
208  // standard_deviation = / variance
209  // \/
210  //
211  if (m_count == 1)
212  {
213  // Set the very first values.
214  m_meanCurr = i;
215  m_sCurr = 0;
216  m_varianceCurr = m_sCurr;
217  }
218  else
219  {
220  // Save the previous values.
221  m_meanPrev = m_meanCurr;
222  m_sPrev = m_sCurr;
223 
224  // Update the current values.
225  m_meanCurr = m_meanPrev + (i - m_meanPrev) / m_count;
226  m_sCurr = m_sPrev + (i - m_meanPrev) * (i - m_meanCurr);
227  m_varianceCurr = m_sCurr / (m_count - 1);
228  }
229  }
230  // end MinMaxAvgTotalCalculator::Update
231 }
232 
233 template <typename T>
234 void
236 {
237  m_count = 0;
238 
239  m_total = 0;
240  m_squareTotal = 0;
241 
242  m_meanCurr = NaN;
243  m_sCurr = NaN;
244  m_varianceCurr = NaN;
245 
246  m_meanPrev = NaN;
247  m_sPrev = NaN;
248  // end MinMaxAvgTotalCalculator::Reset
249 }
250 
251 template <typename T>
252 void
254 {
255  callback.OutputStatistic (m_context, m_key, this);
256 }
257 
258 
265 //------------------------------------------------------------
266 //--------------------------------------------
267 template <typename T = uint32_t>
269 public:
271  virtual ~CounterCalculator();
272 
277  static TypeId GetTypeId (void);
278 
282  void Update ();
287  void Update (const T i);
288 
293  T GetCount () const;
294 
299  virtual void Output (DataOutputCallback &callback) const;
300 
301 protected:
302  virtual void DoDispose (void);
303 
305 
306  // end CounterCalculator
307 };
308 
309 
310 //--------------------------------------------
311 template <typename T>
313  m_count (0)
314 {
315 }
316 
317 template <typename T>
319 {
320 }
321 /* static */
322 template <typename T>
323 TypeId
325 {
326  static TypeId tid = TypeId ( ("ns3::CounterCalculator<"
327  + TypeNameGet<T> ()
328  + ">").c_str () )
329  .SetParent<Object> ()
330  .SetGroupName ("Stats")
331  .AddConstructor<CounterCalculator<T> > ()
332  ;
333  return tid;
334 }
335 
336 template <typename T>
337 void
339 {
340  DataCalculator::DoDispose ();
341  // CounterCalculator::DoDispose
342 }
343 
344 template <typename T>
345 void
347 {
348  if (m_enabled) {
349  m_count++;
350  }
351  // end CounterCalculator::Update
352 }
353 
354 template <typename T>
355 void
357 {
358  if (m_enabled) {
359  m_count += i;
360  }
361  // end CounterCalculator::Update
362 }
363 
364 template <typename T>
365 T
367 {
368  return m_count;
369  // end CounterCalculator::GetCount
370 }
371 
372 template <typename T>
373 void
375 {
376  callback.OutputSingleton (m_context, m_key, m_count);
377  // end CounterCalculator::Output
378 }
379 
380 // end namespace ns3
381 };
382 
383 
384 #endif /* BASIC_DATA_CALCULATORS_H */
double getSum() const
Returns the sum.
Abstract class for calculating statistical data.
static TypeId GetTypeId(void)
Register this type.
double getMin() const
Returns the minimum value.
T m_min
Minimum value of MinMaxAvgTotalCalculator.
double getVariance() const
Returns the current variance.
T GetCount() const
Returns the count of the CounterCalculator.
T m_total
Total value of MinMaxAvgTotalCalculator.
double getSqrSum() const
Returns the sum of squares.
double getMax() const
Returns the maximum value.
uint64_t GetCount(const std::map< Mac48Address, uint64_t > &counter, Mac48Address addr)
void Reset()
Reinitializes all variables of MinMaxAvgTotalCalculator.
virtual void DoDispose(void)
Destructor implementation.
const double NaN
Stored representation of NaN.
Every class exported by the ns3 library is enclosed in the ns3 namespace.
T m_count
Count value of CounterCalculator.
virtual void DoDispose(void)
Destructor implementation.
static TypeId GetTypeId(void)
Register this type.
Template class MinMaxAvgTotalCalculator.
double m_meanPrev
Previous mean of MinMaxAvgTotalCalculator.
double m_meanCurr
Current mean of MinMaxAvgTotalCalculator.
virtual void Output(DataOutputCallback &callback) const
Outputs the data based on the provided callback.
Callback class for the DataOutput classes.
void Update(const T i)
Updates all variables of MinMaxAvgTotalCalculator.
double m_varianceCurr
Current variance of MinMaxAvgTotalCalculator.
long getCount() const
Returns the count.
double m_sPrev
Previous s of MinMaxAvgTotalCalculator.
Calculates data during a simulation.
T m_max
Maximum value of MinMaxAvgTotalCalculator.
void Update()
Increments count by 1.
double getMean() const
Returns the mean value.
A base class which provides memory management and object aggregation.
Definition: object.h:87
virtual void OutputStatistic(std::string key, std::string variable, const StatisticalSummary *statSum)=0
Outputs the data from the specified StatisticalSummary.
Template class CounterCalculator.
virtual void OutputSingleton(std::string key, std::string variable, int val)=0
Associates the integer value with the variable name for a specific output format. ...
T m_squareTotal
Sum of squares value of MinMaxAvgTotalCalculator.
double m_sCurr
Current s of MinMaxAvgTotalCalculator.
a unique identifier for an interface.
Definition: type-id.h:58
virtual void Output(DataOutputCallback &callback) const
Outputs the data based on the provided callback.
TypeId SetParent(TypeId tid)
Set the parent TypeId.
Definition: type-id.cc:923
virtual void DoDispose(void)
Destructor implementation.
uint32_t m_count
Count value of MinMaxAvgTotalCalculator.
double getStddev() const
Returns the standard deviation.