pint.pintk.pulsar.Pulsar

class pint.pintk.pulsar.Pulsar(parfile=None, timfile=None, ephem=None, fitter='GLSFitter')[source]

Bases: object

Wrapper class for a pulsar.

Contains the toas, model, residuals, and fitter

Methods

add_jump(selected)

jump the toas selected or un-jump them if already jumped

add_model_params()

This automatically adds the next available unfit prefix parameters to the model so they show up on the GUI

add_phase_wrap(selected, phase)

Add a phase wrap to selected points in the TOAs object

dayofyear()

Return the day of the year for all the TOAs of this pulsar

delete_TOAs(indices, selected)

fit(selected[, iters, compute_random])

Run a fit using the specified fitter

getDefaultFitter([downhill])

orbitalphase()

For a binary pulsar, calculate the orbital phase.

print_chi2(selected)

random_models(selected)

Compute and plot random models

resetAll()

reset_TOAs()

reset_model()

update_resids()

write_fit_summary()

Summarize fitting results

year()

Return the decimal year for all the TOAs of this pulsar

Attributes

name

orbitalphase()[source]

For a binary pulsar, calculate the orbital phase. Otherwise, return an array of unitless quantities of zeros

dayofyear()[source]

Return the day of the year for all the TOAs of this pulsar

year()[source]

Return the decimal year for all the TOAs of this pulsar

add_model_params()[source]

This automatically adds the next available unfit prefix parameters to the model so they show up on the GUI

write_fit_summary()[source]

Summarize fitting results

add_phase_wrap(selected, phase)[source]

Add a phase wrap to selected points in the TOAs object

Turn on pulse number tracking in the model, if it isn’t already

Parameters:
  • selected – boolean array to apply to toas, True = selected toa

  • phase – phase difference to be added, i.e. -0.5, +2, etc.

add_jump(selected)[source]

jump the toas selected or un-jump them if already jumped

Parameters:

selected – boolean array to apply to toas, True = selected toa

fit(selected, iters=4, compute_random=False)[source]

Run a fit using the specified fitter

random_models(selected)[source]

Compute and plot random models