OpenVDB  3.1.0
Stats.h
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36 
37 #ifndef OPENVDB_MATH_STATS_HAS_BEEN_INCLUDED
38 #define OPENVDB_MATH_STATS_HAS_BEEN_INCLUDED
39 
40 #include <iosfwd> // for ostringstream
41 #include <openvdb/version.h>
42 #include <iostream>
43 #include <iomanip>
44 #include <sstream>
45 #include <vector>
46 #include "Math.h"
47 
48 namespace openvdb {
50 namespace OPENVDB_VERSION_NAME {
51 namespace math {
52 
55 class Extrema
56 {
57 public:
58 
62  : mSize(0)
63  , mMin(std::numeric_limits<double>::max())
64  , mMax(-mMin)
65  {
66  }
67 
69  void add(double val)
70  {
71  ++mSize;
72  mMin = std::min<double>(val, mMin);
73  mMax = std::max<double>(val, mMax);
74  }
75 
77  void add(double val, uint64_t n)
78  {
79  mSize += n;
80  mMin = std::min<double>(val, mMin);
81  mMax = std::max<double>(val, mMax);
82  }
83 
85  inline uint64_t size() const { return mSize; }
86 
88  inline double min() const { return mMin; }
89 
91  inline double max() const { return mMax; }
92 
94  inline double range() const { return mMax - mMin; }
95 
97  void add(const Extrema& other)
98  {
99  if (other.mSize > 0) this->join(other);
100  }
101 
103  void print(const std::string &name= "", std::ostream &strm=std::cout, int precision=3) const
104  {
105  // Write to a temporary string stream so as not to affect the state
106  // (precision, field width, etc.) of the output stream.
107  std::ostringstream os;
108  os << std::setprecision(precision) << std::setiosflags(std::ios::fixed);
109  os << "Extrema ";
110  if (!name.empty()) os << "for \"" << name << "\" ";
111  if (mSize>0) {
112  os << "with " << mSize << " samples:\n"
113  << " Min=" << mMin
114  << ", Max=" << mMax
115  << ", Range="<< this->range() << std::endl;
116  } else {
117  os << ": no samples were added." << std::endl;
118  }
119  strm << os.str();
120  }
121 
122 protected:
123 
124  inline void join(const Extrema& other)
125  {
126  assert(other.mSize > 0);
127  mSize += other.mSize;
128  mMin = std::min<double>(mMin, other.mMin);
129  mMax = std::max<double>(mMax, other.mMax);
130  }
131 
132  uint64_t mSize;
133  double mMin, mMax;
134 };//end Extrema
135 
136 
145 class Stats : public Extrema
146 {
147 public:
149  : Extrema()
150  , mAvg(0.0)
151  , mAux(0.0)
152  {
153  }
154 
156  void add(double val)
157  {
158  Extrema::add(val);
159  const double delta = val - mAvg;
160  mAvg += delta/double(mSize);
161  mAux += delta*(val - mAvg);
162  }
163 
165  void add(double val, uint64_t n)
166  {
167  const double denom = 1.0/double(mSize + n);
168  const double delta = val - mAvg;
169  mAvg += denom * delta * double(n);
170  mAux += denom * delta * delta * double(mSize) * double(n);
171  Extrema::add(val, n);
172  }
173 
175  void add(const Stats& other)
176  {
177  if (other.mSize > 0) {
178  const double denom = 1.0/double(mSize + other.mSize);
179  const double delta = other.mAvg - mAvg;
180  mAvg += denom * delta * double(other.mSize);
181  mAux += other.mAux + denom * delta * delta * double(mSize) * double(other.mSize);
182  Extrema::join(other);
183  }
184  }
185 
187  inline double avg() const { return mAvg; }
189  inline double mean() const { return mAvg; }
191 
193  //num/(num-1)
196  inline double var() const { return mSize<2 ? 0.0 : mAux/double(mSize); }
197  inline double variance() const { return this->var(); }
199 
201  inline double std() const { return sqrt(this->var()); }
204  inline double stdDev() const { return this->std(); }
206 
208  void print(const std::string &name= "", std::ostream &strm=std::cout, int precision=3) const
209  {
210  // Write to a temporary string stream so as not to affect the state
211  // (precision, field width, etc.) of the output stream.
212  std::ostringstream os;
213  os << std::setprecision(precision) << std::setiosflags(std::ios::fixed);
214  os << "Statistics ";
215  if (!name.empty()) os << "for \"" << name << "\" ";
216  if (mSize>0) {
217  os << "with " << mSize << " samples:\n"
218  << " Min=" << mMin
219  << ", Max=" << mMax
220  << ", Ave=" << mAvg
221  << ", Std=" << this->stdDev()
222  << ", Var=" << this->variance() << std::endl;
223  } else {
224  os << ": no samples were added." << std::endl;
225  }
226  strm << os.str();
227  }
228 
229 protected:
230  using Extrema::mSize;
231  using Extrema::mMin;
232  using Extrema::mMax;
233  double mAvg, mAux;
234 }; // end Stats
235 
236 
238 
239 
243 {
244 public:
246  Histogram(double min, double max, size_t numBins = 10)
247  : mSize(0), mMin(min), mMax(max+1e-10),
248  mDelta(double(numBins)/(max-min)), mBins(numBins)
249  {
250  assert(numBins > 1);
251  assert(mMax-mMin > 1e-10);
252  for (size_t i=0; i<numBins; ++i) mBins[i]=0;
253  }
254 
257  Histogram(const Stats& s, size_t numBins = 10):
258  mSize(0), mMin(s.min()), mMax(s.max()+1e-10),
259  mDelta(double(numBins)/(mMax-mMin)), mBins(numBins)
260  {
261  assert(numBins > 1);
262  assert(mMax-mMin > 1e-10);
263  for (size_t i=0; i<numBins; ++i) mBins[i]=0;
264  }
265 
269  inline bool add(double val, uint64_t n = 1)
270  {
271  if (val<mMin || val>mMax) return false;
272  mBins[size_t(mDelta*(val-mMin))] += n;
273  mSize += n;
274  return true;
275  }
276 
279  bool add(const Histogram& other)
280  {
281  if (!isApproxEqual(mMin, other.mMin) || !isApproxEqual(mMax, other.mMax) ||
282  mBins.size() != other.mBins.size()) return false;
283  for (size_t i=0, e=mBins.size(); i!=e; ++i) mBins[i] += other.mBins[i];
284  mSize += other.mSize;
285  return true;
286  }
287 
289  inline size_t numBins() const { return mBins.size(); }
291  inline double min() const { return mMin; }
293  inline double max() const { return mMax; }
295  inline double min(int n) const { return mMin+n/mDelta; }
297  inline double max(int n) const { return mMin+(n+1)/mDelta; }
299  inline uint64_t count(int n) const { return mBins[n]; }
301  inline uint64_t size() const { return mSize; }
302 
304  void print(const std::string& name = "", std::ostream& strm = std::cout) const
305  {
306  // Write to a temporary string stream so as not to affect the state
307  // (precision, field width, etc.) of the output stream.
308  std::ostringstream os;
309  os << std::setprecision(6) << std::setiosflags(std::ios::fixed) << std::endl;
310  os << "Histogram ";
311  if (!name.empty()) os << "for \"" << name << "\" ";
312  if (mSize > 0) {
313  os << "with " << mSize << " samples:\n";
314  os << "==============================================================\n";
315  os << "|| # | Min | Max | Frequency | % ||\n";
316  os << "==============================================================\n";
317  for (int i = 0, e = int(mBins.size()); i != e; ++i) {
318  os << "|| " << std::setw(4) << i << " | " << std::setw(14) << this->min(i) << " | "
319  << std::setw(14) << this->max(i) << " | " << std::setw(9) << mBins[i] << " | "
320  << std::setw(3) << (100*mBins[i]/mSize) << " ||\n";
321  }
322  os << "==============================================================\n";
323  } else {
324  os << ": no samples were added." << std::endl;
325  }
326  strm << os.str();
327  }
328 
329 private:
330  uint64_t mSize;
331  double mMin, mMax, mDelta;
332  std::vector<uint64_t> mBins;
333 };
334 
335 } // namespace math
336 } // namespace OPENVDB_VERSION_NAME
337 } // namespace openvdb
338 
339 #endif // OPENVDB_MATH_STATS_HAS_BEEN_INCLUDED
340 
341 // Copyright (c) 2012-2015 DreamWorks Animation LLC
342 // All rights reserved. This software is distributed under the
343 // Mozilla Public License 2.0 ( http://www.mozilla.org/MPL/2.0/ )
void add(const Stats &other)
Add the samples from the other Stats instance.
Definition: Stats.h:175
void add(double val, uint64_t n)
Add n samples with constant value val.
Definition: Stats.h:77
double min() const
Return the minimum value.
Definition: Stats.h:88
void print(const std::string &name="", std::ostream &strm=std::cout, int precision=3) const
Print extrema to the specified output stream.
Definition: Stats.h:103
This class computes the minimum and maximum values of a population of floating-point values...
Definition: Stats.h:55
General-purpose arithmetic and comparison routines, most of which accept arbitrary value types (or at...
Stats()
Definition: Stats.h:148
double mAvg
Definition: Stats.h:233
bool add(const Histogram &other)
Add all the contributions from the other histogram, provided that it has the same configuration as th...
Definition: Stats.h:279
uint64_t size() const
Return the size of the population, i.e., the total number of samples.
Definition: Stats.h:85
double mAux
Definition: Stats.h:233
Histogram(const Stats &s, size_t numBins=10)
Construct with the given bin count and with minimum and maximum values taken from a Stats object...
Definition: Stats.h:257
uint64_t mSize
Definition: Stats.h:132
double max(int n) const
Return the maximum value in the nth bin.
Definition: Stats.h:297
bool isApproxEqual(const Type &a, const Type &b)
Return true if a is equal to b to within the default floating-point comparison tolerance.
Definition: Math.h:370
const boost::disable_if_c< VecTraits< T >::IsVec, T >::type & min(const T &a, const T &b)
Definition: Composite.h:105
double mean() const
Return the arithmetic mean, i.e. average, value.
Definition: Stats.h:189
void add(const Extrema &other)
Add the samples from the other Stats instance.
Definition: Stats.h:97
uint64_t size() const
Return the population size, i.e., the total number of samples.
Definition: Stats.h:301
size_t numBins() const
Return the number of bins in this histogram.
Definition: Stats.h:289
bool add(double val, uint64_t n=1)
Add n samples with constant value val, provided that the val falls within this histogram&#39;s value rang...
Definition: Stats.h:269
void print(const std::string &name="", std::ostream &strm=std::cout) const
Print the histogram to the specified output stream.
Definition: Stats.h:304
Histogram(double min, double max, size_t numBins=10)
Construct with given minimum and maximum values and the given bin count.
Definition: Stats.h:246
#define OPENVDB_VERSION_NAME
Definition: version.h:43
double var() const
Return the population variance.
Definition: Stats.h:196
Definition: Exceptions.h:39
This class computes statistics (minimum value, maximum value, mean, variance and standard deviation) ...
Definition: Stats.h:145
double max() const
Return the upper bound of this histogram&#39;s value range.
Definition: Stats.h:293
double min(int n) const
Return the minimum value in the nth bin.
Definition: Stats.h:295
void add(double val)
Add a single sample.
Definition: Stats.h:69
double range() const
Return the range defined as the maximum value minus the minimum value.
Definition: Stats.h:94
double variance() const
Return the population variance.
Definition: Stats.h:197
uint64_t count(int n) const
Return the number of samples in the nth bin.
Definition: Stats.h:299
const boost::disable_if_c< VecTraits< T >::IsVec, T >::type & max(const T &a, const T &b)
Definition: Composite.h:109
double mMin
Definition: Stats.h:133
double min() const
Return the lower bound of this histogram&#39;s value range.
Definition: Stats.h:291
This class computes a histogram, with a fixed interval width, of a population of floating-point value...
Definition: Stats.h:242
double mMax
Definition: Stats.h:133
void print(const std::string &name="", std::ostream &strm=std::cout, int precision=3) const
Print statistics to the specified output stream.
Definition: Stats.h:208
void join(const Extrema &other)
Definition: Stats.h:124
void add(double val, uint64_t n)
Add n samples with constant value val.
Definition: Stats.h:165
#define OPENVDB_USE_VERSION_NAMESPACE
Definition: version.h:71
double stdDev() const
Return the standard deviation (=Sqrt(variance)) as defined from the (biased) population variance...
Definition: Stats.h:204
void add(double val)
Add a single sample.
Definition: Stats.h:156
Extrema()
Constructor.
Definition: Stats.h:61
double max() const
Return the maximum value.
Definition: Stats.h:91