edges_cal.modelling.FixedLinearModel

class edges_cal.modelling.FixedLinearModel(*, model: Model, x, init_basis=None)[source]

A base class for a linear model fixed at a certain set of co-ordinates.

Using this class caches the basis functions at the particular coordinates, and thus speeds up the fitting of multiple sets of data at those co-ordinates.

Parameters:

model (edges_cal.modelling.Model) – The linear model to evaluate at the co-ordinates
x (numpy.ndarray) – A set of co-ordinates at which to evaluate the model.
init_basis – If the basis functions of the model, evaluated at x, are known already, they can be input directly to save computation time.

Methods

`__init__`(*, model, x[, init_basis])	Method generated by attrs for class FixedLinearModel.
`at_x`(x)	Return a new `FixedLinearModel` at given co-ordinates.
`fit`(ydata[, weights, xdata])	Create a linear-regression fit object.
`from_yaml`(loader, node)	Convert a representation node to a Python object.
`to_yaml`(dumper, data)	Method to convert to YAML format.
`with_nterms`(n_terms[, parameters])	Return a new `FixedLinearModel` with given nterms and parameters.
`with_params`(parameters)	Return a new `FixedLinearModel` with givne parameters.

Attributes

`basis`	The (cached) basis functions at default_x.
`n_terms`	The number of terms/parameters in the model.
`parameters`	The parameters of the model, if set.
`yaml_flow_style`
`yaml_loader`
`yaml_tag`
`model`
`x`