spyrit.core.noise.PoissonApproxGauss

class spyrit.core.noise.PoissonApproxGauss(alpha: float = 1.0)

Bases: Poisson

Gaussian approximation of Poisson noise

\[y \sim \alpha z + \sqrt{\alpha z} \cdot \mathcal{N}(0, 1), \quad \text{with }z\ge 0\]

where \(\alpha\) represents the intensity of the noiseless measurements \(z\), and \(\mathcal{N}(0, 1)\) is a Gaussian distribution with zero mean and unit variance.

This is an approximation of \(y \sim \mathcal{P}\left(\alpha z\right)\), where \(\mathcal{P}\) is the Poisson distribution. Computing the Gaussian approximation is faster than the original Poisson model.

Args:

alpha (float): The intensity of the measurements. Defaults to 1.

Attributes:

alpha (float): Intensity of the measurements.

Methods

forward(z)

Corrupt measurement by Gaussian approximation of Poisson noise