fouriax.PoissonGaussianNoise

class PoissonGaussianNoise(count_scale=1.0, read_noise_std=0.0, clip_min=0.0, clip_max=None)

Bases: SensorNoiseModel

Shot noise plus additive Gaussian read noise in measurement units.

Parameters:

• count_scale (float)

• read_noise_std (float)

• clip_min (float | None)

• clip_max (float | None)

__init__(count_scale=1.0, read_noise_std=0.0, clip_min=0.0, clip_max=None)

Parameters:

• count_scale (float)

• read_noise_std (float)

• clip_min (float | None)

• clip_max (float | None)

Return type:

None

Methods

__init__([count_scale, read_noise_std, ...])
covariance(expected)	Return the analytic measurement covariance matrix.
expected_variance(expected)	Return per-element variance for the noise model at the expected signal.
precision(expected, *[, regularize])	Return the analytic inverse covariance (precision) matrix.
sample(expected, *, key)	Draw a noisy sample from the measurement distribution.

Attributes

clip_max
clip_min
count_scale
read_noise_std

count_scale: float = 1.0

read_noise_std: float = 0.0

clip_min: float | None = 0.0

clip_max: float | None = None

sample(expected, *, key)

Draw a noisy sample from the measurement distribution.

Parameters:

• expected (Array)

• key (Array)

Return type:

Array

expected_variance(expected)

Return per-element variance for the noise model at the expected signal.

Parameters:

expected (Array)

Return type:

Array