OpenVDB: Stats.h Source File

OpenVDB 3.2.0

Stats.h
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1 //
3 // Copyright (c) 2012-2016 DreamWorks Animation LLC
4 //
5 // All rights reserved. This software is distributed under the
6 // Mozilla Public License 2.0 ( http://www.mozilla.org/MPL/2.0/ )
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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 <functional>// for std::less
47 #include "Math.h"
48
49 namespace openvdb {
50 OPENVDB_USE_VERSION_NAMESPACE
51 namespace OPENVDB_VERSION_NAME {
52 namespace math {
53
55 template <typename ValueType, typename Less = std::less<ValueType> >
56 class MinMax
57 {
58 public:
59
61 MinMax(const ValueType &min, const ValueType &max) : mMin(min), mMax(max)
62 {
63 }
64
66 inline void add(const ValueType &val, const Less &less = Less())
67 {
68 if (less(val, mMin)) mMin = val;
69 if (less(mMax, val)) mMax = val;
70 }
71
73 inline const ValueType& min() const { return mMin; }
74
76 inline const ValueType& max() const { return mMax; }
77
79 inline void add(const MinMax& other, const Less &less = Less())
80 {
81 if (less(other.mMin, mMin)) mMin = other.mMin;
82 if (less(mMax, other.mMax)) mMax = other.mMax;
83 }
84
86 void print(const std::string &name= "", std::ostream &strm=std::cout, int precision=3) const
87 {
88 // Write to a temporary string stream so as not to affect the state
89 // (precision, field width, etc.) of the output stream.
90 std::ostringstream os;
91 os << std::setprecision(precision) << std::setiosflags(std::ios::fixed);
92 os << "MinMax ";
93 if (!name.empty()) os << "for \"" << name << "\" ";
94 os << " Min=" << mMin << ", Max=" << mMax << std::endl;
95 strm << os.str();
96 }
97
98 protected:
99
100 ValueType mMin, mMax;
101 };//end MinMax
102
105 class Extrema
106 {
107 public:
108
111 Extrema()
112 : mSize(0)
113 , mMin(std::numeric_limits<double>::max())
114 , mMax(-mMin)
115 {
116 }
117
119 void add(double val)
120 {
121 ++mSize;
122 mMin = std::min<double>(val, mMin);
123 mMax = std::max<double>(val, mMax);
124 }
125
127 void add(double val, uint64_t n)
128 {
129 mSize += n;
130 mMin = std::min<double>(val, mMin);
131 mMax = std::max<double>(val, mMax);
132 }
133
135 inline uint64_t size() const { return mSize; }
136
138 inline double min() const { return mMin; }
139
141 inline double max() const { return mMax; }
142
144 inline double range() const { return mMax - mMin; }
145
147 void add(const Extrema& other)
148 {
149 if (other.mSize > 0) this->join(other);
150 }
151
153 void print(const std::string &name= "", std::ostream &strm=std::cout, int precision=3) const
154 {
155 // Write to a temporary string stream so as not to affect the state
156 // (precision, field width, etc.) of the output stream.
157 std::ostringstream os;
158 os << std::setprecision(precision) << std::setiosflags(std::ios::fixed);
159 os << "Extrema ";
160 if (!name.empty()) os << "for \"" << name << "\" ";
161 if (mSize>0) {
162 os << "with " << mSize << " samples:\n"
163 << " Min=" << mMin
164 << ", Max=" << mMax
165 << ", Range="<< this->range() << std::endl;
166 } else {
167 os << ": no samples were added." << std::endl;
168 }
169 strm << os.str();
170 }
171
172 protected:
173
174 inline void join(const Extrema& other)
175 {
176 assert(other.mSize > 0);
177 mSize += other.mSize;
178 mMin = std::min<double>(mMin, other.mMin);
179 mMax = std::max<double>(mMax, other.mMax);
180 }
181
182 uint64_t mSize;
183 double mMin, mMax;
184 };//end Extrema
185
186
195 class Stats : public Extrema
196 {
197 public:
198 Stats()
199 : Extrema()
200 , mAvg(0.0)
201 , mAux(0.0)
202 {
203 }
204
206 void add(double val)
207 {
208 Extrema::add(val);
209 const double delta = val - mAvg;
210 mAvg += delta/double(mSize);
211 mAux += delta*(val - mAvg);
212 }
213
215 void add(double val, uint64_t n)
216 {
217 const double denom = 1.0/double(mSize + n);
218 const double delta = val - mAvg;
219 mAvg += denom * delta * double(n);
220 mAux += denom * delta * delta * double(mSize) * double(n);
221 Extrema::add(val, n);
222 }
223
225 void add(const Stats& other)
226 {
227 if (other.mSize > 0) {
228 const double denom = 1.0/double(mSize + other.mSize);
229 const double delta = other.mAvg - mAvg;
230 mAvg += denom * delta * double(other.mSize);
231 mAux += other.mAux + denom * delta * delta * double(mSize) * double(other.mSize);
232 Extrema::join(other);
233 }
234 }
235
237 inline double avg() const { return mAvg; }
239 inline double mean() const { return mAvg; }
241
243 //num/(num-1)
246 inline double var() const { return mSize<2 ? 0.0 : mAux/double(mSize); }
247 inline double variance() const { return this->var(); }
249
251 inline double std() const { return sqrt(this->var()); }
254 inline double stdDev() const { return this->std(); }
256
258 void print(const std::string &name= "", std::ostream &strm=std::cout, int precision=3) const
259 {
260 // Write to a temporary string stream so as not to affect the state
261 // (precision, field width, etc.) of the output stream.
262 std::ostringstream os;
263 os << std::setprecision(precision) << std::setiosflags(std::ios::fixed);
264 os << "Statistics ";
265 if (!name.empty()) os << "for \"" << name << "\" ";
266 if (mSize>0) {
267 os << "with " << mSize << " samples:\n"
268 << " Min=" << mMin
269 << ", Max=" << mMax
270 << ", Ave=" << mAvg
271 << ", Std=" << this->stdDev()
272 << ", Var=" << this->variance() << std::endl;
273 } else {
274 os << ": no samples were added." << std::endl;
275 }
276 strm << os.str();
277 }
278
279 protected:
280 using Extrema::mSize;
281 using Extrema::mMin;
282 using Extrema::mMax;
283 double mAvg, mAux;
284 }; // end Stats
285
286
288
289
292 class Histogram
293 {
294 public:
296 Histogram(double min, double max, size_t numBins = 10)
297 : mSize(0), mMin(min), mMax(max + 1e-10),
298 mDelta(double(numBins)/(max-min)), mBins(numBins)
299 {
300 if ( mMax <= mMin ) {
301 OPENVDB_THROW(ValueError, "Histogram: expected min < max");
302 } else if ( numBins == 0 ) {
303 OPENVDB_THROW(ValueError, "Histogram: expected at least one bin");
304 }
305 for (size_t i=0; i<numBins; ++i) mBins[i]=0;
306 }
307
310 Histogram(const Stats& s, size_t numBins = 10):
311 mSize(0), mMin(s.min()), mMax(s.max()+1e-10),
312 mDelta(double(numBins)/(mMax-mMin)), mBins(numBins)
313 {
314 if ( mMax <= mMin ) {
315 OPENVDB_THROW(ValueError, "Histogram: expected min < max");
316 } else if ( numBins == 0 ) {
317 OPENVDB_THROW(ValueError, "Histogram: expected at least one bin");
318 }
319 for (size_t i=0; i<numBins; ++i) mBins[i]=0;
320 }
321
325 inline bool add(double val, uint64_t n = 1)
326 {
327 if (val<mMin || val>mMax) return false;
328 mBins[size_t(mDelta*(val-mMin))] += n;
329 mSize += n;
330 return true;
331 }
332
335 bool add(const Histogram& other)
336 {
337 if (!isApproxEqual(mMin, other.mMin) || !isApproxEqual(mMax, other.mMax) ||
338 mBins.size() != other.mBins.size()) return false;
339 for (size_t i=0, e=mBins.size(); i!=e; ++i) mBins[i] += other.mBins[i];
340 mSize += other.mSize;
341 return true;
342 }
343
345 inline size_t numBins() const { return mBins.size(); }
347 inline double min() const { return mMin; }
349 inline double max() const { return mMax; }
351 inline double min(int n) const { return mMin+n/mDelta; }
353 inline double max(int n) const { return mMin+(n+1)/mDelta; }
355 inline uint64_t count(int n) const { return mBins[n]; }
357 inline uint64_t size() const { return mSize; }
358
360 void print(const std::string& name = "", std::ostream& strm = std::cout) const
361 {
362 // Write to a temporary string stream so as not to affect the state
363 // (precision, field width, etc.) of the output stream.
364 std::ostringstream os;
365 os << std::setprecision(6) << std::setiosflags(std::ios::fixed) << std::endl;
366 os << "Histogram ";
367 if (!name.empty()) os << "for \"" << name << "\" ";
368 if (mSize > 0) {
369 os << "with " << mSize << " samples:\n";
370 os << "==============================================================\n";
371 os << "|| # | Min | Max | Frequency | % ||\n";
372 os << "==============================================================\n";
373 for (int i = 0, e = int(mBins.size()); i != e; ++i) {
374 os << "|| " << std::setw(4) << i << " | " << std::setw(14) << this->min(i) << " | "
375 << std::setw(14) << this->max(i) << " | " << std::setw(9) << mBins[i] << " | "
376 << std::setw(3) << (100*mBins[i]/mSize) << " ||\n";
377 }
378 os << "==============================================================\n";
379 } else {
380 os << ": no samples were added." << std::endl;
381 }
382 strm << os.str();
383 }
384
385 private:
386 uint64_t mSize;
387 double mMin, mMax, mDelta;
388 std::vector<uint64_t> mBins;
389 };
390
391 } // namespace math
392 } // namespace OPENVDB_VERSION_NAME
393 } // namespace openvdb
394
395 #endif // OPENVDB_MATH_STATS_HAS_BEEN_INCLUDED
396
397 // Copyright (c) 2012-2016 DreamWorks Animation LLC
398 // All rights reserved. This software is distributed under the
399 // Mozilla Public License 2.0 ( http://www.mozilla.org/MPL/2.0/ )
openvdb::v3_2_0::math::Extrema::max
double max() const
Return the maximum value.
Definition: Stats.h:141
openvdb::v3_2_0::math::Histogram
This class computes a histogram, with a fixed interval width, of a population of floating-point value...
Definition: Stats.h:292
openvdb::v3_2_0::math::Extrema::add
void add(double val, uint64_t n)
Add n samples with constant value val.
Definition: Stats.h:127
openvdb::v3_2_0::math::MinMax::add
void add(const ValueType &val, const Less &less=Less())
Add a single sample.
Definition: Stats.h:66
Math.h
General-purpose arithmetic and comparison routines, most of which accept arbitrary value types (or at...
openvdb::v3_2_0::math::MinMax::mMin
ValueType mMin
Definition: Stats.h:100
OPENVDB_THROW
#define OPENVDB_THROW(exception, message)
Definition: Exceptions.h:97
openvdb::v3_2_0::math::Extrema::mSize
uint64_t mSize
Definition: Stats.h:182
openvdb::v3_2_0::math::Stats::add
void add(const Stats &other)
Add the samples from the other Stats instance.
Definition: Stats.h:225
openvdb::v3_2_0::math::MinMax::add
void add(const MinMax &other, const Less &less=Less())
Add the samples from the other Stats instance.
Definition: Stats.h:79
openvdb::v3_2_0::math::Histogram::size
uint64_t size() const
Return the population size, i.e., the total number of samples.
Definition: Stats.h:357
openvdb::v3_2_0::math::Extrema::size
uint64_t size() const
Return the size of the population, i.e., the total number of samples.
Definition: Stats.h:135
openvdb::v3_2_0::tools::composite::max
const boost::disable_if_c< VecTraits< T >::IsVec, T >::type & max(const T &a, const T &b)
Definition: Composite.h:132
openvdb::v3_2_0::math::MinMax::MinMax
MinMax(const ValueType &min, const ValueType &max)
Constructor.
Definition: Stats.h:61
openvdb::v3_2_0::math::Stats::Stats
Stats()
Definition: Stats.h:198
openvdb::v3_2_0::math::Histogram::min
double min(int n) const
Return the minimum value in the nth bin.
Definition: Stats.h:351
openvdb::v3_2_0::math::isApproxEqual
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
openvdb::v3_2_0::math::Extrema::add
void add(const Extrema &other)
Add the samples from the other Stats instance.
Definition: Stats.h:147
openvdb::v3_2_0::math::MinMax::mMax
ValueType mMax
Definition: Stats.h:100
openvdb::v3_2_0::math::Stats::variance
double variance() const
Return the population variance.
Definition: Stats.h:247
openvdb::v3_2_0::math::Extrema::range
double range() const
Return the range defined as the maximum value minus the minimum value.
Definition: Stats.h:144
openvdb::v3_2_0::math::Stats::mean
double mean() const
Return the arithmetic mean, i.e. average, value.
Definition: Stats.h:239
OPENVDB_VERSION_NAME
#define OPENVDB_VERSION_NAME
Definition: version.h:43
openvdb::v3_2_0::math::Histogram::min
double min() const
Return the lower bound of this histogram&#39;s value range.
Definition: Stats.h:347
openvdb::v3_2_0::math::Stats::print
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:258
openvdb::v3_2_0::math::Stats::stdDev
double stdDev() const
Return the standard deviation (=Sqrt(variance)) as defined from the (biased) population variance...
Definition: Stats.h:254
openvdb::v3_2_0::math::Histogram::add
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:335
openvdb
Definition: Exceptions.h:39
openvdb::v3_2_0::math::Stats
This class computes statistics (minimum value, maximum value, mean, variance and standard deviation) ...
Definition: Stats.h:195
openvdb::v3_2_0::math::Extrema::add
void add(double val)
Add a single sample.
Definition: Stats.h:119
openvdb::v3_2_0::math::Stats::add
void add(double val, uint64_t n)
Add n samples with constant value val.
Definition: Stats.h:215
openvdb::v3_2_0::math::Histogram::print
void print(const std::string &name="", std::ostream &strm=std::cout) const
Print the histogram to the specified output stream.
Definition: Stats.h:360
version.h
openvdb::v3_2_0::math::Extrema
This class computes the minimum and maximum values of a population of floating-point values...
Definition: Stats.h:105
openvdb::v3_2_0::math::Histogram::count
uint64_t count(int n) const
Return the number of samples in the nth bin.
Definition: Stats.h:355
openvdb::v3_2_0::math::Stats::add
void add(double val)
Add a single sample.
Definition: Stats.h:206
openvdb::v3_2_0::math::Extrema::min
double min() const
Return the minimum value.
Definition: Stats.h:138
openvdb::v3_2_0::math::MinMax::max
const ValueType & max() const
Return the maximum value.
Definition: Stats.h:76
openvdb::v3_2_0::math::Extrema::print
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:153
openvdb::v3_2_0::math::Histogram::numBins
size_t numBins() const
Return the number of bins in this histogram.
Definition: Stats.h:345
openvdb::v3_2_0::math::Histogram::Histogram
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:310
openvdb::v3_2_0::math::Extrema::mMin
double mMin
Definition: Stats.h:183
openvdb::v3_2_0::ValueError
Definition: Exceptions.h:88
openvdb::v3_2_0::math::Extrema::mMax
double mMax
Definition: Stats.h:183
openvdb::v3_2_0::math::Histogram::add
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:325
openvdb::v3_2_0::math::Stats::var
double var() const
Return the population variance.
Definition: Stats.h:246
openvdb::v3_2_0::math::Histogram::max
double max() const
Return the upper bound of this histogram&#39;s value range.
Definition: Stats.h:349
openvdb::v3_2_0::math::MinMax
Templated class to compute the minimum and maximum values.
Definition: Stats.h:56
openvdb::v3_2_0::math::Extrema::join
void join(const Extrema &other)
Definition: Stats.h:174
openvdb::v3_2_0::math::Histogram::Histogram
Histogram(double min, double max, size_t numBins=10)
Construct with given minimum and maximum values and the given bin count.
Definition: Stats.h:296
OPENVDB_USE_VERSION_NAMESPACE
#define OPENVDB_USE_VERSION_NAMESPACE
Definition: version.h:71
openvdb::v3_2_0::math::Stats::mAvg
double mAvg
Definition: Stats.h:283
openvdb::v3_2_0::math::Stats::mAux
double mAux
Definition: Stats.h:283
openvdb::v3_2_0::math::MinMax::min
const ValueType & min() const
Return the minimum value.
Definition: Stats.h:73
openvdb::v3_2_0::math::Extrema::Extrema
Extrema()
Constructor.
Definition: Stats.h:111
openvdb::v3_2_0::math::Histogram::max
double max(int n) const
Return the maximum value in the nth bin.
Definition: Stats.h:353
openvdb::v3_2_0::math::MinMax::print
void print(const std::string &name="", std::ostream &strm=std::cout, int precision=3) const
Print MinMax to the specified output stream.
Definition: Stats.h:86
openvdb::v3_2_0::tools::composite::min
const boost::disable_if_c< VecTraits< T >::IsVec, T >::type & min(const T &a, const T &b)
Definition: Composite.h:128