pint.fitter.Fitter

class pint.fitter.Fitter(toas, model, track_mode=None, residuals=None)

Bases: object

Base class for objects encapsulating fitting problems.

The fitting function should be defined as the fit_toas() method.

The Fitter object makes a copy.deepcopy() of the model and stores it in the .model attribute. This is the model used for fitting, and it can be modified, for example by freezing or thawing parameters (fitter.model.F0.frozen = False). When .fit_toas() is executed this model will be updated to reflect the results of the fitting process.

The Fitter also caches a copy of the original model so it can be restored with reset_model().

Try pint.fitter.Fitter.auto() to automatically get the appropriate fitter type

Variables:

• model (pint.models.timing_model.TimingModel) – The model the fitter is working on. Once fit_toas() has been run, this model will be modified to reflect the results.

• model_init (pint.models.timing_model.TimingModel) – The initial, prefit model.

Parameters:

• toas (a pint TOAs instance) – The input toas.

• model (a pint timing model instance) – The initial timing model for fitting.

• track_mode (str, optional) – How to handle phase wrapping. This is used when creating pint.residuals.Residuals objects, and its meaning is defined there.

• residuals (pint.residuals.Residuals) – Initial residuals. This argument exists to support an optimization, where GLSFitter is used to compute chi2 for appropriate Residuals objects.

Methods

auto(toas, model[, downhill, track_mode, ...])	Automatically return the proper pint.fitter.Fitter object depending on the TOAs and model.
fit_toas([maxiter, debug])	Run fitting operation.
ftest(parameter, component[, remove, ...])	Compare the significance of adding/removing parameters to a timing model.
get_allparams()	Return a dict of all param names and values.
get_derived_params([returndict])	Return a string with various derived parameters from the fitted model
get_designmatrix()	Return the model's design matrix for these TOAs.
get_fitparams()	Return a dict of fittable param names and quantity.
get_fitparams_num()	Return a dict of fittable param names and numeric values.
get_fitparams_uncertainty()	Return a dict of fittable param names and numeric values.
get_parameter_correlation_matrix([...])	Show the parameter correlation matrix post-fit.
get_parameter_covariance_matrix([...])	Show the parameter covariance matrix post-fit.
get_params_dict([which, kind])	Return a dict mapping parameter names to values.
get_summary([nodmx])	Return a human-readable summary of the Fitter results.
make_resids(model)
minimize_func(x, *args)	Wrapper function for the residual class.
plot()	Make residuals plot.
print_summary()	Write a summary of the TOAs to stdout.
reset_model()	Reset the current model to the initial model.
set_fitparams(*params)	Update the "frozen" attribute of model parameters.
set_param_uncertainties(fitp)	Set the model parameters to the value contained in the input dict.
set_params(fitp)	Set the model parameters to the value contained in the input dict.
update_model([chi2])	Update the model to reflect fit results and TOA properties.
update_resids()	Update the residuals.

Attributes

covariance_matrix

classmethod auto(toas, model, downhill=True, track_mode=None, residuals=None, **kwargs)

Automatically return the proper pint.fitter.Fitter object depending on the TOAs and model.

In general the downhill fitters are to be preferred. See https://github.com/nanograv/PINT/wiki/How-To#choose-a-fitter for the logic used.

Parameters:

• toas (a pint TOAs instance) – The input toas.

• model (a pint timing model instance) – The initial timing model for fitting.

• downhill (bool, optional) – Whether or not to use the downhill fitter variant

• track_mode (str, optional) – How to handle phase wrapping. This is used when creating pint.residuals.Residuals objects, and its meaning is defined there.

• residuals (pint.residuals.Residuals) – Initial residuals. This argument exists to support an optimization, where GLSFitter is used to compute chi2 for appropriate Residuals objects.

Returns:

Returns appropriate subclass

Return type:

pint.fitter.Fitter

fit_toas(maxiter=None, debug=False)

Run fitting operation.

This method needs to be implemented by subclasses. All implementations should call self.model.validate() and self.model.validate_toas() before doing the fitting.

get_summary(nodmx=False)

Return a human-readable summary of the Fitter results.

Parameters:

nodmx (bool) – Set to True to suppress printing DMX parameters in summary

get_derived_params(returndict=False)

Return a string with various derived parameters from the fitted model

Parameters:

returndict (bool, optional) – Whether to only return the string of results or also a dictionary

Returns:

• results (str)

• parameters (dict, optional)

See also

pint.models.timing_model.TimingModel.get_derived_params()

print_summary()

Write a summary of the TOAs to stdout.

plot()

Make residuals plot.

This produces a time residual plot.

update_model(chi2=None)

Update the model to reflect fit results and TOA properties.

This is called by fit_toas to ensure that parameters like START, FINISH, EPHEM, and DMDATA are set in the model to reflect the TOAs in actual use.

reset_model()

Reset the current model to the initial model.

update_resids()

Update the residuals.

Run after updating a model parameter.

get_designmatrix()

Return the model’s design matrix for these TOAs.

get_parameter_covariance_matrix(with_phase=False, pretty_print=False, prec=3)

Show the parameter covariance matrix post-fit.

If with_phase, then show and return the phase column as well. If pretty_print, then also pretty-print on stdout the matrix. prec is the precision of the floating point results.

get_parameter_correlation_matrix(with_phase=False, pretty_print=False, prec=3, usecolor=True)

Show the parameter correlation matrix post-fit.

If with_phase, then show and return the phase column as well. If pretty_print, then also pretty-print on stdout the matrix. prec is the precision of the floating point results. If usecolor is True, then pretty printing will have color.

ftest(parameter, component, remove=False, full_output=False, maxiter=1)

Compare the significance of adding/removing parameters to a timing model.

Parameters:

• parameter (PINT parameter object) – (may be a list of parameter objects)

• component (String) – Name of component of timing model that the parameter should be added to (may be a list) The number of components must equal number of parameters.

• remove (Bool) – If False, will add the listed parameters to the model. If True will remove the input parameters from the timing model.

• full_output (Bool) – If False, just returns the result of the F-Test. If True, will also return the new model’s residual RMS (us), chi-squared, and number of degrees of freedom of new model.

• maxiter (int) – How many times to run the linear least-squares fit, re-evaluating the derivatives at each step for the F-tested model. Default is one.

Returns:

ftFloat

F-test significance value for the model with the larger number of components over the other. Computed with pint.utils.FTest().

resid_rms_testFloat (Quantity)

If full_output is True, returns the RMS of the residuals of the tested model fit. Will be in units of microseconds as an astropy quantity. If wideband fitter this will be the time residuals.

resid_wrms_testFloat (Quantity)

If full_output is True, returns the Weighted RMS of the residuals of the tested model fit. Will be in units of microseconds as an astropy quantity. If wideband fitter this will be the time residuals.

chi2_testFloat

If full_output is True, returns the chi-squared of the tested model. If wideband fitter this will be the total chi-squared of the combined residual.

dof_testInt

If full_output is True, returns the degrees of freedom of the tested model. If wideband fitter this will be the total chi-squared of the combined residual.

dm_resid_rms_testFloat (Quantity)

If full_output is True and a wideband timing fitter is used, returns the RMS of the DM residuals of the tested model fit. Will be in units of pc/cm^3 as an astropy quantity.

dm_resid_wrms_testFloat (Quantity)

If full_output is True and a wideband timing fitter is used, returns the Weighted RMS of the DM residuals of the tested model fit. Will be in units of pc/cm^3 as an astropy quantity.

Return type:

dictionary

minimize_func(x, *args)

Wrapper function for the residual class.

This is meant to be passed to scipy.optimize.minimize. The function must take a single list of input values, x, and a second optional tuple of input arguments. It returns a quantity to be minimized (in this case chi^2).

get_params_dict(which='free', kind='quantity')

Return a dict mapping parameter names to values.

See pint.models.timing_model.TimingModel.get_params_dict().

set_fitparams(*params)

Update the “frozen” attribute of model parameters. Deprecated.

get_allparams()

Return a dict of all param names and values. Deprecated.

get_fitparams()

Return a dict of fittable param names and quantity. Deprecated.

get_fitparams_num()

Return a dict of fittable param names and numeric values. Deprecated.

get_fitparams_uncertainty()

Return a dict of fittable param names and numeric values. Deprecated.

set_params(fitp)

Set the model parameters to the value contained in the input dict.

See pint.models.timing_model.TimingModel.set_param_values().

set_param_uncertainties(fitp)

Set the model parameters to the value contained in the input dict.

See pint.models.timing_model.TimingModel.set_param_uncertainties().