Models

These are extra lmfit models created for APAV.

`PowerLawShiftModel`

class apav.analysis.models.PowerLawShiftModel(*args, **kwargs)[source]

Shifted power law model

This model defines a shifted power law with refined parameter min/max/initial values for APAV

guess(data, x=None, **kwargs)[source]: Estimate initial model parameter values from data.

class apav.analysis.models.ExponentialGaussianModel(*args, **kwargs)[source]

Exponential gaussian model

This model defines an exponentially modified gaussian with refined parameter min/max/initial values for APAV

guess(*args, **kwargs)[source]

Guess starting values for the parameters of a model.

Parameters:

data (array_like) – Array of data (i.e., y-values) to use to guess parameter values.
x (array_like) – Array of values for the independent variable (i.e., x-values).
**kws (optional) – Additional keyword arguments, passed to model function.

Returns:

params (Parameters) – Initial, guessed values for the parameters of a Model.
.. versionchanged:: 1.0.3 – Argument x is now explicitly required to estimate starting values.