#include <Cholesky.hpp>
◆ Cholesky() [1/2]
Cholesky::Cholesky |
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const cs * |
mat = nullptr , |
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bool |
flagDecompose = true |
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) |
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◆ Cholesky() [2/2]
Cholesky::Cholesky |
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const Cholesky & |
m | ) |
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◆ ~Cholesky()
◆ _clean()
void Cholesky::_clean |
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private |
◆ _decompose()
void Cholesky::_decompose |
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bool |
verbose = false | ) |
const |
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private |
Finalize the construction of the QChol structure. Perform the Cholesky decomposition
- Parameters
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◆ _evalDirect()
Operate the operation: 'outv' = MAT * 'inv'
- Parameters
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[in] | inv | Array of input values |
[out] | outv | Array of output values |
Implements ALinearOp.
◆ _isDecomposed()
bool Cholesky::_isDecomposed |
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const |
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inlineprivate |
◆ _isDefined()
bool Cholesky::_isDefined |
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const |
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inlineprivate |
◆ computeLogDet()
double Cholesky::computeLogDet |
( |
| ) |
const |
◆ evalInverse()
Evaluate the product: 'outv' = MAT^{-1} * 'inv'
- Parameters
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[in] | inv | Array of input values |
[out] | outv | Array of output values |
Reimplemented from ALinearOp.
◆ getSize()
int Cholesky::getSize |
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const |
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overridevirtual |
◆ operator=()
◆ printout()
void Cholesky::printout |
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const char * |
title, |
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bool |
verbose = false |
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) |
| const |
◆ reset()
int Cholesky::reset |
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const cs * |
mat = nullptr , |
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bool |
flagDecompose = true |
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) |
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◆ simulate()
Simulate using Cholesky
- Parameters
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[out] | inv | input Vector |
[out] | outv | Simulated output vector |
◆ stdev()
void Cholesky::stdev |
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VectorDouble & |
vcur, |
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bool |
flagStDev = false |
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) |
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Perform the calculation of the Standard Deviation of Estimation Error
- Parameters
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[out] | vcur | Output array |
[in] | flagStDev | FALSE for a variance calculation, True for StDev. |
◆ _mat
◆ _matN
◆ _matS
◆ _work
The documentation for this class was generated from the following files: