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STIR 6.5.0
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Generates noise realisations according to Poisson statistics but allowing for scaling. More...
#include "stir/GeneralisedPoissonNoiseGenerator.h"
Public Member Functions | |
| GeneralisedPoissonNoiseGenerator (const float scaling_factor=1.0F, const bool preserve_mean=false) | |
| Constructor intialises the andom number generator with a fixed seed. | |
| void | seed (unsigned int) |
| The seed value for the random number generator. | |
| float | generate_random (const float mu) |
| generate a random number according to a distribution with mean mu | |
| template<int num_dimensions, class elemTout, class elemTin> | |
| void | generate_random (Array< num_dimensions, elemTout > &array_out, const Array< num_dimensions, elemTin > &array_in) |
| void | generate_random (ProjData &output_projdata, const ProjData &input_projdata) |
Generates noise realisations according to Poisson statistics but allowing for scaling.
A scaling_factor is used to multiply the input data before generating the Poisson random number. This means that a scaling_factor larger than 1 will result in less noisy data.
If preserve_mean=, the mean of the output data will be equal to scaling_factor*mean_of_input, otherwise it will be equal to mean_of_input, but then the output is no longer Poisson distributed. false,
| stir::GeneralisedPoissonNoiseGenerator::GeneralisedPoissonNoiseGenerator | ( | const float | scaling_factor = 1.0F, |
| const bool | preserve_mean = false ) |
Constructor intialises the andom number generator with a fixed seed.
References GeneralisedPoissonNoiseGenerator(), and seed().
Referenced by GeneralisedPoissonNoiseGenerator().
| void stir::GeneralisedPoissonNoiseGenerator::seed | ( | unsigned int | value | ) |
The seed value for the random number generator.
References stir::error().
Referenced by GeneralisedPoissonNoiseGenerator().