35 #ifndef OPENVDB_MATH_STATS_HAS_BEEN_INCLUDED
36 #define OPENVDB_MATH_STATS_HAS_BEEN_INCLUDED
39 #include <openvdb/version.h>
61 , mMin(std::numeric_limits<double>::
max())
70 mMin = std::min<double>(val, mMin);
71 mMax = std::max<double>(val, mMax);
75 void add(
double val, uint64_t n)
78 mMin = std::min<double>(val, mMin);
79 mMax = std::max<double>(val, mMax);
83 inline uint64_t
size()
const {
return mSize; }
86 inline double min()
const {
return mMin; }
89 inline double max()
const {
return mMax; }
94 if (other.
mSize > 0) this->join(other);
98 void print(
const std::string &name=
"", std::ostream &strm=std::cout,
int precision=3)
const
102 std::ostringstream os;
103 os << std::setprecision(precision) << std::setiosflags(std::ios::fixed);
105 if (!name.empty()) os <<
"for \"" << name <<
"\" ";
107 os <<
"with " << mSize <<
" samples:\n"
109 <<
", Max=" << mMax << std::endl;
111 os <<
": no samples were added." << std::endl;
120 assert(other.
mSize > 0);
121 mSize += other.
mSize;
122 mMin = std::min<double>(mMin, other.
mMin);
123 mMax = std::max<double>(mMax, other.
mMax);
153 const double delta = val - mAvg;
154 mAvg += delta/double(mSize);
155 mAux += delta*(val - mAvg);
159 void add(
double val, uint64_t n)
161 const double denom = 1.0/double(mSize + n);
162 const double delta = val - mAvg;
163 mAvg += denom * delta * double(n);
164 mAux += denom * delta * delta * double(mSize) * double(n);
165 Extrema::add(val, n);
171 if (other.
mSize > 0) {
172 const double denom = 1.0/double(mSize + other.
mSize);
173 const double delta = other.
mAvg - mAvg;
174 mAvg += denom * delta * double(other.
mSize);
175 mAux += other.
mAux + denom * delta * delta * double(mSize) * double(other.
mSize);
176 Extrema::join(other);
181 inline double avg()
const {
return mAvg; }
183 inline double mean()
const {
return mAvg; }
190 inline double var()
const {
return mSize<2 ? 0.0 : mAux/double(mSize); }
191 inline double variance()
const {
return this->var(); }
195 inline double std()
const {
return sqrt(this->var()); }
198 inline double stdDev()
const {
return this->std(); }
202 void print(
const std::string &name=
"", std::ostream &strm=std::cout,
int precision=3)
const
206 std::ostringstream os;
207 os << std::setprecision(precision) << std::setiosflags(std::ios::fixed);
209 if (!name.empty()) os <<
"for \"" << name <<
"\" ";
211 os <<
"with " << mSize <<
" samples:\n"
215 <<
", Std=" << this->stdDev()
216 <<
", Var=" << this->variance() << std::endl;
218 os <<
": no samples were added." << std::endl;
224 using Extrema::mSize;
241 : mSize(0), mMin(min), mMax(max+1e-10),
242 mDelta(double(numBins)/(max-min)), mBins(numBins)
245 assert(mMax-mMin > 1e-10);
246 for (
size_t i=0; i<numBins; ++i) mBins[i]=0;
252 mSize(0), mMin(s.
min()), mMax(s.
max()+1e-10),
253 mDelta(double(numBins)/(mMax-mMin)), mBins(numBins)
256 assert(mMax-mMin > 1e-10);
257 for (
size_t i=0; i<numBins; ++i) mBins[i]=0;
263 inline bool add(
double val, uint64_t n = 1)
265 if (val<mMin || val>mMax)
return false;
266 mBins[size_t(mDelta*(val-mMin))] += n;
276 mBins.size() != other.mBins.size())
return false;
277 for (
size_t i=0, e=mBins.size(); i!=e; ++i) mBins[i] += other.mBins[i];
278 mSize += other.mSize;
283 inline size_t numBins()
const {
return mBins.size(); }
285 inline double min()
const {
return mMin; }
287 inline double max()
const {
return mMax; }
289 inline double min(
int n)
const {
return mMin+n/mDelta; }
291 inline double max(
int n)
const {
return mMin+(n+1)/mDelta; }
293 inline uint64_t
count(
int n)
const {
return mBins[n]; }
295 inline uint64_t
size()
const {
return mSize; }
298 void print(
const std::string& name =
"", std::ostream& strm = std::cout)
const
302 std::ostringstream os;
303 os << std::setprecision(6) << std::setiosflags(std::ios::fixed) << std::endl;
305 if (!name.empty()) os <<
"for \"" << name <<
"\" ";
307 os <<
"with " << mSize <<
" samples:\n";
308 os <<
"==============================================================\n";
309 os <<
"|| # | Min | Max | Frequency | % ||\n";
310 os <<
"==============================================================\n";
311 for (
int i = 0, e =
int(mBins.size()); i != e; ++i) {
312 os <<
"|| " << std::setw(4) << i <<
" | " << std::setw(14) << this->
min(i) <<
" | "
313 << std::setw(14) << this->
max(i) <<
" | " << std::setw(9) << mBins[i] <<
" | "
314 << std::setw(3) << (100*mBins[i]/mSize) <<
" ||\n";
316 os <<
"==============================================================\n";
318 os <<
": no samples were added." << std::endl;
325 double mMin, mMax, mDelta;
326 std::vector<uint64_t> mBins;
333 #endif // OPENVDB_MATH_STATS_HAS_BEEN_INCLUDED
void print(const std::string &name="", std::ostream &strm=std::cout) const
Print the histogram to the specified output stream.
Definition: Stats.h:298
void add(double val, uint64_t n)
Add n samples with constant value val.
Definition: Stats.h:75
double min() const
Return the minimum value.
Definition: Stats.h:86
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:202
Histogram(double min, double max, size_t numBins=10)
Construct with given minimum and maximum values and the given bin count.
Definition: Stats.h:240
double min(int n) const
Return the minimum value in the nth bin.
Definition: Stats.h:289
void add(double val, uint64_t n)
Add n samples with constant value val.
Definition: Stats.h:159
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:98
double variance() const
Return the population variance.
Definition: Stats.h:191
General-purpose arithmetic and comparison routines, most of which accept arbitrary value types (or at...
double var() const
Return the population variance.
Definition: Stats.h:190
void add(double val)
Add a single sample.
Definition: Stats.h:150
uint64_t size() const
Return the size of the population, i.e., the total number of samples.
Definition: Stats.h:83
double min() const
Return the lower bound of this histogram's value range.
Definition: Stats.h:285
uint64_t mSize
Definition: Stats.h:126
size_t numBins() const
Return the number of bins in this histogram.
Definition: Stats.h:283
double mAvg
Definition: Stats.h:227
bool add(double val, uint64_t n=1)
Add n samples with constant value val, provided that the val falls within this histogram's value rang...
Definition: Stats.h:263
double mAux
Definition: Stats.h:227
void add(const Extrema &other)
Add the samples from the other Stats instance.
Definition: Stats.h:92
#define OPENVDB_VERSION_NAME
Definition: version.h:43
This class computes the minimum and maximum values of a population of floating-point values...
Definition: Stats.h:53
double mean() const
Return the arithmetic mean, i.e. average, value.
Definition: Stats.h:183
Definition: Exceptions.h:39
This class computes statistics (minimum value, maximum value, mean, variance and standard deviation) ...
Definition: Stats.h:139
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:251
This class computes a histogram, with a fixed interval width, of a population of floating-point value...
Definition: Stats.h:236
OPENVDB_API Hermite min(const Hermite &, const Hermite &)
min and max operations done directly on the compressed data.
bool isApproxEqual(const Hermite &lhs, const Hermite &rhs)
Definition: Hermite.h:470
void add(double val)
Add a single sample.
Definition: Stats.h:67
void add(const Stats &other)
Add the samples from the other Stats instance.
Definition: Stats.h:169
double stdDev() const
Return the standard deviation (=Sqrt(variance)) as defined from the (biased) population variance...
Definition: Stats.h:198
double mMin
Definition: Stats.h:127
Stats()
Definition: Stats.h:142
OPENVDB_API Hermite max(const Hermite &, const Hermite &)
min and max operations done directly on the compressed data.
double mMax
Definition: Stats.h:127
double max() const
Return the upper bound of this histogram's value range.
Definition: Stats.h:287
double max(int n) const
Return the maximum value in the nth bin.
Definition: Stats.h:291
void join(const Extrema &other)
Definition: Stats.h:118
std::string str() const
String representation.
#define OPENVDB_USE_VERSION_NAMESPACE
Definition: version.h:71
uint64_t count(int n) const
Return the number of samples in the nth bin.
Definition: Stats.h:293
Extrema()
Constructor.
Definition: Stats.h:59
double max() const
Return the maximum value.
Definition: Stats.h:89
uint64_t size() const
Return the population size, i.e., the total number of samples.
Definition: Stats.h:295
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:273