spyrit.core.noise

Noise models

\[y \sim \mathcal{N}\left(z;\theta\right),\]

where \(\mathcal{N}\) the noise distribution, \(z\) represents the noiseless measurements, and \(\theta\) represents the parameters of the noise distribution.

There are two main classes in this module, which simulate Gaussian and Poisson noise.

Classes

Gaussian([sigma])	Simulate measurements corrupted by additive Gaussian noise
Poisson([alpha])	Simulate measurements corrupted by Poisson noise
PoissonApproxGauss([alpha])	Gaussian approximation of Poisson noise
PoissonApproxGaussSameNoise([alpha])	Gaussian approximation of Poisson noise
PoissonGaussian([alpha, sigma, mu, g])	Simulate measurements corrupted by Poisson noise