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Gray C++ Libraries
0.0.2
A set of C++ libraries for MSVC, GNU on Windows, WinCE, Linux
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#include <cValueStats.h>
Public Member Functions | |
| cValueStats (TYPE nValAvgStartingEst=0, UINT uSamplesMax=100) | |
| TYPE | get_ValAvg () const |
| void | put_ValAvg (TYPE nValAvg) |
| void | AddStat (TYPE nVal) |
Public Member Functions inherited from GrayLib::cValueRange< double > | |
| cValueRange (double tLo=cTypeLimit< double >::k_Min, double tHi=cTypeLimit< double >::k_Min) | |
| void | InitX (double nVal=cTypeLimit< double >::k_Min) |
| bool | isRangeValid () const |
| double | GetLinearX (double nVal2, double nRange2) const |
| double | GetLinearI (int nVal2, int nRange2=1000) const |
Public Member Functions inherited from Gray::cRangeT< TYPE > | |
| TYPE | get_Min () const |
| TYPE | get_Max () const |
| TYPE | get_Avg () const |
| TYPE | GetClampValue (TYPE nVal) const |
| bool | IsInsideI (TYPE nVal) const |
| bool | IsInsideX (TYPE nVal) const |
| TYPE | get_RangeI () const |
| TYPE | get_RangeX () const |
| TYPE | GetLinear1 (float fOne) const |
| int | GetSpinValueI (int iVal) const |
| void | SetZero () |
| void | put_Min (TYPE iLo) |
| void | put_Max (TYPE iHi) |
| void | SetRange (TYPE iLo, TYPE iHi) |
| void | NormalizeRange () |
| void | UnionValue (TYPE nVal) |
| bool | IsRangeOverlapI (const THIS_t &x) const |
| void | SetUnionRange (const THIS_t &x) |
Protected Member Functions | |
| void | AddStatW (TYPE nVal, TYPE nWeight) |
Protected Attributes | |
| const UINT | m_uSamplesMax |
| average is calculated over n samples. More... | |
| UINT | m_uSamplesQty |
| current number of samples I have processed. for AddStat(). More... | |
| TYPE | m_nValAvg |
| running average. More... | |
Additional Inherited Members | |
Public Attributes inherited from Gray::cRangeT< TYPE > | |
| TYPE | m_Lo |
| low range value. More... | |
| TYPE | m_Hi |
| inclusive high side of range. int size = (hi-lo)+1, float size = hi-lo ?? weird. More... | |
compile stats over multiple samples. mean, std deviation ? ASSUME TYPE = double or float.
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Assume each stat is of equal weight. e.g. regular sample intervals. Assume this is called at set intervals.
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Add a weighted value to the average.
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running average.
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average is calculated over n samples.
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current number of samples I have processed. for AddStat().