OpenVDB  10.0.1
Stats< ValueT, 1 > Class Template Reference

This class computes statistics (minimum value, maximum value, mean, variance and standard deviation) of a population of floating-point values. More...

`#include <nanovdb/util/GridStats.h>`

Inherits Extrema< ValueT, 1 >.

## Public Types

using ValueType = ValueT

## Public Member Functions

Stats ()

Statsadd (const ValueT &val, uint64_t n)
Add n samples with constant value val. More...

Add the samples from the other Stats instance. More...

size_t size () const

double avg () const
Return the arithmetic mean, i.e. average, value. More...

double mean () const
Return the arithmetic mean, i.e. average, value. More...

double var () const
Return the population variance. More...

double variance () const
Return the population variance. More...

double std () const
Return the standard deviation (=Sqrt(variance)) as defined from the (biased) population variance. More...

double stdDev () const
Return the standard deviation (=Sqrt(variance)) as defined from the (biased) population variance. More...

## Static Public Member Functions

static constexpr bool hasMinMax ()

static constexpr bool hasAverage ()

static constexpr bool hasStdDeviation ()

## Protected Types

using BaseT = Extrema< ValueT, 1 >

using RealT = double

size_t mSize

double mAvg

double mAux

## Detailed Description

### template<typename ValueT> class nanovdb::Stats< ValueT, 1 >

This class computes statistics (minimum value, maximum value, mean, variance and standard deviation) of a population of floating-point values.

variance = Mean[ (X-Mean[X])^2 ] = Mean[X^2] - Mean[X]^2, standard deviation = sqrt(variance)

Note
This class employs incremental computation and double precision.

## Member Typedef Documentation

 using BaseT = Extrema
protected
 using RealT = double
protected
 using ValueType = ValueT

## Constructor & Destructor Documentation

 Stats ( )
inline

## Member Function Documentation

 Stats& add ( const ValueT & val )
inline

 Stats& add ( const ValueT & val, uint64_t n )
inline

Add n samples with constant value val.

 Stats& add ( const Stats< ValueT, 1 > & other )
inline

Add the samples from the other Stats instance.

 double avg ( ) const
inline

Return the arithmetic mean, i.e. average, value.

 static constexpr bool hasAverage ( )
inlinestatic
 static constexpr bool hasMinMax ( )
inlinestatic
 static constexpr bool hasStdDeviation ( )
inlinestatic
 double mean ( ) const
inline

Return the arithmetic mean, i.e. average, value.

 size_t size ( ) const
inline
 double std ( ) const
inline

Return the standard deviation (=Sqrt(variance)) as defined from the (biased) population variance.

 double stdDev ( ) const
inline

Return the standard deviation (=Sqrt(variance)) as defined from the (biased) population variance.

 double var ( ) const
inline

Return the population variance.

Note
The unbiased sample variance = population variance * num/(num-1)
 double variance ( ) const
inline

Return the population variance.

Note
The unbiased sample variance = population variance * num/(num-1)

## Member Data Documentation

 double mAux
protected
 double mAvg
protected
 size_t mSize
protected