OpenVDB  2.0.0
Stats.h
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34 
35 #ifndef OPENVDB_MATH_STATS_HAS_BEEN_INCLUDED
36 #define OPENVDB_MATH_STATS_HAS_BEEN_INCLUDED
37 
38 #include <iosfwd> // for ostringstream
39 #include <openvdb/version.h>
40 #include <iostream>
41 #include <iomanip>
42 #include <sstream>
43 #include <vector>
44 #include "Math.h"
45 
46 namespace openvdb {
48 namespace OPENVDB_VERSION_NAME {
49 namespace math {
50 
59 class Stats
60 {
61 public:
62  Stats(): mSize(0), mAvg(0.0), mAux(0.0),
63  mMin(std::numeric_limits<double>::max()), mMax(-mMin) {}
64 
66  void add(double val)
67  {
68  mSize++;
69  mMin = std::min<double>(val, mMin);
70  mMax = std::max<double>(val, mMax);
71  const double delta = val - mAvg;
72  mAvg += delta/double(mSize);
73  mAux += delta*(val - mAvg);
74  }
75 
77  void add(double val, uint64_t n)
78  {
79  mMin = std::min<double>(val, mMin);
80  mMax = std::max<double>(val, mMax);
81  const double denom = 1.0/double(mSize + n);
82  const double delta = val - mAvg;
83  mAvg += denom*delta*n;
84  mAux += denom*delta*delta*mSize*n;
85  mSize += n;
86  }
87 
89  void add(const Stats& other)
90  {
91  if (other.mSize > 0) {
92  mMin = std::min<double>(mMin, other.mMin);
93  mMax = std::max<double>(mMax, other.mMax);
94  const double denom = 1.0/double(mSize + other.mSize);
95  const double delta = other.mAvg - mAvg;
96  mAvg += denom*delta*other.mSize;
97  mAux += other.mAux + denom*delta*delta*mSize*other.mSize;
98  mSize += other.mSize;
99  }
100  }
101 
103  uint64_t size() const { return mSize; }
105  double min() const { return mMin; }
107  double max() const { return mMax; }
109  double mean() const { return mAvg; }
112  double variance() const { return mSize<2 ? 0.0 : mAux/double(mSize); }
115  double stdDev() const { return sqrt(this->variance()); }
116 
118  void print(const std::string &name= "", std::ostream &strm=std::cout, int precision=3) const
119  {
120  // Write to a temporary string stream so as not to affect the state
121  // (precision, field width, etc.) of the output stream.
122  std::ostringstream os;
123  os << std::setprecision(precision) << std::setiosflags(std::ios::fixed);
124  os << "Statistics ";
125  if (!name.empty()) os << "for \"" << name << "\" ";
126  if (mSize>0) {
127  os << "with " << mSize << " samples:\n"
128  << " Min=" << mMin
129  << ", Max=" << mMax
130  << ", Ave=" << mAvg
131  << ", Std=" << this->stdDev()
132  << ", Var=" << this->variance() << std::endl;
133  } else {
134  os << ": no samples were added." << std::endl;
135  }
136  strm << os.str();
137  }
138 
139 private:
140  uint64_t mSize;
141  double mAvg, mAux, mMin, mMax;
142 }; // end Stats
143 
144 
146 
147 
151 {
152 public:
154  Histogram(double min, double max, size_t numBins = 10)
155  : mSize(0), mMin(min), mMax(max+1e-10),
156  mDelta(double(numBins)/(max-min)), mBins(numBins)
157  {
158  assert(numBins > 1);
159  assert(mMax-mMin > 1e-10);
160  for (size_t i=0; i<numBins; ++i) mBins[i]=0;
161  }
162 
165  Histogram(const Stats& s, size_t numBins = 10):
166  mSize(0), mMin(s.min()), mMax(s.max()+1e-10),
167  mDelta(double(numBins)/(mMax-mMin)), mBins(numBins)
168  {
169  assert(numBins > 1);
170  assert(mMax-mMin > 1e-10);
171  for (size_t i=0; i<numBins; ++i) mBins[i]=0;
172  }
173 
177  bool add(double val, uint64_t n = 1)
178  {
179  if (val<mMin || val>mMax) return false;
180  mBins[size_t(mDelta*(val-mMin))] += n;
181  mSize += n;
182  return true;
183  }
184 
187  bool add(const Histogram& other)
188  {
189  if (!isApproxEqual(mMin, other.mMin) || !isApproxEqual(mMax, other.mMax) ||
190  mBins.size() != other.mBins.size()) return false;
191  for (size_t i=0, e=mBins.size(); i!=e; ++i) mBins[i] += other.mBins[i];
192  mSize += other.mSize;
193  return true;
194  }
195 
197  size_t numBins() const { return mBins.size(); }
199  double min() const { return mMin; }
201  double max() const { return mMax; }
203  double min(int n) const { return mMin+n/mDelta; }
205  double max(int n) const { return mMin+(n+1)/mDelta; }
207  uint64_t count(int n) const { return mBins[n]; }
209  uint64_t size() const { return mSize; }
210 
212  void print(const std::string& name = "", std::ostream& strm = std::cout) const
213  {
214  // Write to a temporary string stream so as not to affect the state
215  // (precision, field width, etc.) of the output stream.
216  std::ostringstream os;
217  os << std::setprecision(6) << std::setiosflags(std::ios::fixed) << std::endl;
218  os << "Histogram ";
219  if (!name.empty()) os << "for \"" << name << "\" ";
220  if (mSize > 0) {
221  os << "with " << mSize << " samples:\n";
222  os << "==============================================================\n";
223  os << "|| # | Min | Max | Frequency | % ||\n";
224  os << "==============================================================\n";
225  for (size_t i=0, e=mBins.size(); i!=e; ++i) {
226  os << "|| " << std::setw(4) << i << " | " << std::setw(14) << this->min(i) << " | "
227  << std::setw(14) << this->max(i) << " | " << std::setw(9) << mBins[i] << " | "
228  << std::setw(3) << (100*mBins[i]/mSize) << " ||\n";
229  }
230  os << "==============================================================\n";
231  } else {
232  os << ": no samples were added." << std::endl;
233  }
234  strm << os.str();
235  }
236 
237 private:
238  uint64_t mSize;
239  double mMin, mMax, mDelta;
240  std::vector<uint64_t> mBins;
241 };
242 
243 } // namespace math
244 } // namespace OPENVDB_VERSION_NAME
245 } // namespace openvdb
246 
247 #endif // OPENVDB_MATH_STATS_HAS_BEEN_INCLUDED
248 
249 // Copyright (c) 2012-2013 DreamWorks Animation LLC
250 // All rights reserved. This software is distributed under the
251 // Mozilla Public License 2.0 ( http://www.mozilla.org/MPL/2.0/ )
OPENVDB_API Hermite max(const Hermite &, const Hermite &)
min and max operations done directly on the compressed data.
double mean() const
Return the mean value.
Definition: Stats.h:109
General-purpose arithmetic and comparison routines, most of which accept arbitrary value types (or at...
double min() const
Return the minimum value.
Definition: Stats.h:105
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:187
double min(int n) const
Return the minimum value in the nth bin.
Definition: Stats.h:203
double stdDev() const
Return the standard deviation (=Sqrt(variance)) as defined from the (biased) population variance...
Definition: Stats.h:115
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:165
uint64_t size() const
Return the population size, i.e., the total number of samples.
Definition: Stats.h:209
This class computes statistics (minimum value, maximum value, mean, variance and standard deviation) ...
Definition: Stats.h:59
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:177
void add(const Stats &other)
Add the samples from the other Stats instance.
Definition: Stats.h:89
Stats()
Definition: Stats.h:62
Histogram(double min, double max, size_t numBins=10)
Construct with given minimum and maximum values and the given bin count.
Definition: Stats.h:154
void add(double val, uint64_t n)
Add n samples with constant value val.
Definition: Stats.h:77
std::string str() const
String representation.
#define OPENVDB_VERSION_NAME
Definition: version.h:45
double min() const
Return the lower bound of this histogram&#39;s value range.
Definition: Stats.h:199
uint64_t size() const
Return the size of the population, i.e., the total number of samples.
Definition: Stats.h:103
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:118
OPENVDB_API Hermite min(const Hermite &, const Hermite &)
min and max operations done directly on the compressed data.
double max() const
Return the upper bound of this histogram&#39;s value range.
Definition: Stats.h:201
double max() const
Return the maximum value.
Definition: Stats.h:107
size_t numBins() const
Return the number of bins in this histogram.
Definition: Stats.h:197
uint64_t count(int n) const
Return the number of samples in the nth bin.
Definition: Stats.h:207
double variance() const
Return the population variance.
Definition: Stats.h:112
void add(double val)
Add a single sample.
Definition: Stats.h:66
void print(const std::string &name="", std::ostream &strm=std::cout) const
Print the histogram to the specified output stream.
Definition: Stats.h:212
double max(int n) const
Return the maximum value in the nth bin.
Definition: Stats.h:205
#define OPENVDB_USE_VERSION_NAMESPACE
Definition: version.h:56
bool isApproxEqual(const Hermite &lhs, const Hermite &rhs)
Definition: Hermite.h:470
This class computes a histogram, with a fixed interval width, of a population of floating-point value...
Definition: Stats.h:150