This class computes statistics (minimum value, maximum value, mean, variance and standard deviation) of a population of floating-point values.
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#include <nanovdb/util/GridStats.h>
Inherits Extrema< ValueT, 0 >.
template<typename ValueT>
class nanovdb::Stats< ValueT, 0 >
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.
◆ BaseT
◆ RealT
◆ ValueType
◆ Stats() [1/2]
◆ Stats() [2/2]
Stats |
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const ValueT & |
val | ) |
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inline |
◆ add() [1/4]
◆ add() [2/4]
Add the samples from the other Stats instance.
◆ add() [3/4]
Stats& add |
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const ValueT & |
val | ) |
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inline |
◆ add() [4/4]
Stats& add |
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const ValueT & |
val, |
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uint64_t |
n |
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inline |
Add n samples with constant value val.
◆ avg()
Return the arithmetic mean, i.e. average, value.
◆ hasAverage()
static constexpr bool hasAverage |
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inlinestaticconstexpr |
◆ hasMinMax()
static constexpr bool hasMinMax |
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inlinestaticconstexpr |
◆ hasStdDeviation()
static constexpr bool hasStdDeviation |
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inlinestaticconstexpr |
◆ max() [1/2]
const ValueT& max |
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const |
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inlineinherited |
◆ max() [2/2]
◆ mean()
◆ min() [1/2]
const ValueT& min |
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const |
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inlineinherited |
◆ min() [2/2]
◆ operator bool()
◆ size() [1/2]
static constexpr size_t size |
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inlinestaticconstexprinherited |
◆ size() [2/2]
◆ std()
Return the standard deviation (=Sqrt(variance)) as defined from the (biased) population variance.
◆ stdDev()
◆ var()
Return the population variance.
- Note
- The unbiased sample variance = population variance * num/(num-1)
◆ variance()
double variance |
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const |
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inline |
◆ mAux
◆ mAvg
◆ mMax
◆ mMin
◆ mSize