pint.fitter.WidebandState

class pint.fitter.WidebandState(fitter, model, full_cov=False, threshold=None)[source]

Methods

`predicted_chi2`(step, lambda_)	Predict the chi2 after taking a step based on the linear approximation
`take_step`(step[, lambda_])	Return a new state moved by lambda_*step.
`take_step_model`(step[, lambda_])	Make a new model reflecting the new parameters.

Attributes

`M`
`M_params_units_norm`
`U`
`U_s_Vt_xhat`
`Vt`
`chi2`
`covariance_matrix`
`mtcm`
`mtcm_mtcy_mtcmplain`
`mtcmplain`
`mtcy`
`norm`
`parameter_covariance_matrix`
`params`
`resids`
`s`
`step`
`units`
`xhat`

take_step(step, lambda_=1)[source]: Return a new state moved by lambda_*step.

predicted_chi2(step, lambda_): Predict the chi2 after taking a step based on the linear approximation

take_step_model(step, lambda_=1): Make a new model reflecting the new parameters.