spyrit.core.noise.PoissonApproxGauss.forward

PoissonApproxGauss.forward(z: tensor) → tensor

Corrupt measurement by Gaussian approximation of Poisson noise

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

Args:

z (torch.tensor): Measurements \(z\) with arbitrary shape.

Returns:

torch.tensor: Noisy measurement \(y\) with the same shape as z.

Raises:

RuntimeError: If there are negative values in the input tensor.

Example:

Two different noisy measurement vectors

>>> import spyrit.core.noise as sn
>>> import torch
>>> noise = sn.PoissonApproxGauss(100)
>>> z = torch.empty(10, 4).uniform_(0, 1)
>>> y = noise(z)
>>> print(y.shape)
torch.Size([10, 4])
>>> print(f"Noiseless measurements in ({torch.min(z):.2f} , {torch.max(z):.2f})")
Noiseless measurements in (...)
>>> print(f"Noisy measurements in ({torch.min(y):.2f} , {torch.max(y):.2f})")
Noisy measurements in (...)

>>> y = noise(z)
>>> print(f"Noisy measurements in ({torch.min(y):.2f} , {torch.max(y):.2f})")
Noisy measurements in (...)