locan.analysis.uncertainty.LocalizationUncertainty#

class locan.analysis.uncertainty.LocalizationUncertainty(meta=None, model=1, **kwargs)[source]#

Bases: _Analysis

Compute the Cramer Rao lower bound for localization uncertainty for each localization’s spatial coordinate in locdata.

Uncertainty is computed according to one of the following model functions:

  1. 1 / sqrt(intensity)

  2. psf_sigma / sqrt(intensity)

  3. f(psf_sigma, intensity, pixel_size, background)

Localization properties have to be available for all or each spatial dimension (like psf_sigma or psf_sigma_x). The localization property intensity must have the unit photons. The unit of pixel_size must be the same as that of position coordinates.

Parameters:

  • meta (locan.analysis.metadata_analysis_pb2.AMetadata | None) – Metadata about the current analysis routine.

  • model (int) – Model function for theoretical localization uncertainty.

  • kwargs (Any) – kwargs for the chosen model. If none are given the localization properties are taken from locdata.

Variables:

  • count (int) – A counter for counting instantiations.

  • parameter (dict) – A dictionary with all settings for the current computation.

  • meta (locan.analysis.metadata_analysis_pb2.AMetadata) – Metadata about the current analysis routine.

  • results (pandas.DataFrame) – Uncertainty for each localization and in each dimension.

Methods

__init__([meta, model])

compute(locdata)

Run the computation.

report(*args, **kwargs)

Show a report about analysis results.

Attributes

count

A counter for counting Analysis class instantiations (class attribute).
compute(locdata)[source]#

Run the computation.

Parameters:

locdata (LocData) – Localization data.

Return type:

Self

count: int = 0#

A counter for counting Analysis class instantiations (class attribute).