pint.models.noise_model.PLDMNoise

class pint.models.noise_model.PLDMNoise[source]

Bases: CorrelatedNoiseComponent

Model of DM variations as radio frequency-dependent noise with a power-law spectrum.

Variations in DM over time result from both the proper motion of the pulsar and the changing electron number density along the line of sight from the solar wind and ISM. In particular, Kolmogorov turbulence in the ionized ISM will induce stochastic DM variations with a power law spectrum. Timing errors due to unmodelled DM variations can therefore appear very similar to intrinsic red noise, however the amplitude of these variations will scale with the inverse of the square of the (Earth Doppler corrected) radio frequency.

Parameters supported:

Name / Aliases	Description	Kind
TNDMAMP	Amplitude of powerlaw DM noise in tempo2 format	number
TNDMGAM	Spectral index of powerlaw DM noise in tempo2 format	number
TNDMC	Number of DM noise frequencies.	integer
TNDMFLOG	Number of logarithmically spaced DM noise frequencies in the basis.	integer
TNDMFLOG_FACTOR	Scaling factor for the log-spaced DM frequencies (2 -> [1/8, 1/4, 1/2, …]).	number
TNDMTSPAN	Time span corresponding to the fundamental frequency of the DM noise Fourier series (data span is used by default).	yr

References

Lentati et al. 2014, MNRAS 437(3), 3004-3023 [1]

Methods

`add_param`(param[, deriv_func, setup])	Add a parameter to the Component.
`get_dm_noise_basis`(toas)	The DM part of the basis matrix for wideband datasets.
`get_noise_basis`(toas)	Return a Fourier design matrix for DM noise.
`get_noise_weights`(toas)	Return power law DM noise weights.
`get_params_of_type`(param_type)	Get all the parameters in timing model for one specific Parameter subtype.
`get_plc_vals`()	Retrieve power-law parameters and frequency-basis parameters from the model, substituting defaults if unspecified.
`get_prefix_mapping_component`(prefix)	Get the index mapping for the prefix parameters.
`get_time_frequencies`(toas)	Return the frequencies of the noise model
`get_wideband_noise_basis`(toas)	The wideband noise basis including both TOA and DM parts.
`is_in_parfile`(para_dict)	Check if this subclass included in parfile.
`match_param_aliases`(alias)	Return the parameter corresponding to this alias.
`param_help`()	Print help lines for all available parameters in model.
`pl_dm_basis_weight_pair`(toas)	Return a Fourier design matrix and power law DM noise weights.
`pl_dm_cov_matrix`(toas)
`print_par`([format])	param format: Parfile output format. PINT outputs the 'tempo', 'tempo2' and 'pint'
`register_deriv_funcs`(func, param)	Register the derivative function in to the deriv_func dictionaries.
`remove_param`(param)	Remove a parameter from the Component.
`set_special_params`(spcl_params)
`setup`()	Finalize construction loaded values.
`validate`()	Validate loaded values.
`validate_toas`(toas)	Check that this model component has TOAs where needed.

Attributes

`aliases_map`	Return all the aliases and map to the PINT parameter name.
`category`
`component_types`
`free_params_component`	Return the free parameters in the component.
`introduces_correlated_errors`
`introduces_dm_errors`
`is_time_correlated`
`param_prefixs`
`register`

get_plc_vals() → Tuple[float, float, int, int, float][source]: Retrieve power-law parameters and frequency-basis parameters from the model, substituting defaults if unspecified.

get_time_frequencies(toas: TOAs) → Tuple[ndarray, ndarray][source]: Return the frequencies of the noise model

get_noise_basis(toas: TOAs) → ndarray[source]

Return a Fourier design matrix for DM noise.

See the documentation for pl_dm_basis_weight_pair function for details.

get_noise_weights(toas: TOAs) → ndarray[source]

Return power law DM noise weights.

See the documentation for pl_dm_basis_weight_pair for details.

pl_dm_basis_weight_pair(toas: TOAs) → Tuple[ndarray, ndarray][source]

Return a Fourier design matrix and power law DM noise weights.

A Fourier design matrix contains the sine and cosine basis_functions in a Fourier series expansion. Here we scale the design matrix by (fref/f)**2, where fref = 1400 MHz to match the convention used in enterprise.

The weights used are the power-law PSD values at frequencies n/T, where n is in [1, TNDMC] and T is the total observing duration of the dataset.

add_param(param: Parameter, deriv_func: Callable | None = None, setup: bool = False)

Add a parameter to the Component.

The parameter is stored in an attribute on the Component object. Its name is also recorded in a list, self.params.

Parameters:

param (pint.models.Parameter) – The parameter to be added.
deriv_func (function) – Derivative function for parameter.

property aliases_map: Dict[str, str]

Return all the aliases and map to the PINT parameter name.

This property returns a dictionary from the current in timing model parameters’ aliase to the pint defined parameter names. For the aliases of a prefixed parameter, the aliase with an existing prefix index maps to the PINT defined parameter name with the same index. Behind the scenes, the indexed parameter adds the indexed aliase to its aliase list.

property free_params_component: List[str]

Return the free parameters in the component.

This function collects the non-frozen parameters.

Return type:: A list of free parameters.

get_dm_noise_basis(toas): The DM part of the basis matrix for wideband datasets. This is non-zero only for DM noise. The output is a numpy array but it has units of dmu/s by convention since the noise amplitudes are defined to have dimensions of time.

get_params_of_type(param_type: str) → List[str]: Get all the parameters in timing model for one specific Parameter subtype.

get_prefix_mapping_component(prefix: str) → Dict[int, str]

Get the index mapping for the prefix parameters.

Parameters:: prefix (str) – Name of prefix.
Returns:: A dictionary with prefix parameter real index as key and parameter name as value.
Return type:: dict

get_wideband_noise_basis(toas): The wideband noise basis including both TOA and DM parts. The TOA part of the matrix is dimensionless but the DM part of the basis has units of dmu/s.

is_in_parfile(para_dict: Dict) → bool

Check if this subclass included in parfile.

Parameters:: para_dict (dictionary) – A dictionary contain all the parameters with values in string from one parfile
Returns:: Whether the subclass is included in the parfile.
Return type:: bool

match_param_aliases(alias: str) → str

Return the parameter corresponding to this alias.

Parameters:: alias (str) – Alias name.

Note

This function only searches the parameter aliases within the current component. If one wants to search the aliases in the scope of TimingModel, please use TimingModel.match_param_aliase().

param_help() → str: Print help lines for all available parameters in model.

print_par(format: Literal['tempo', 'tempo2', 'pint'] = 'pint') → str

Parameters:: format (str, optional) – Parfile output format. PINT outputs the ‘tempo’, ‘tempo2’ and ‘pint’ format. The defaul format is pint. Actual formatting done elsewhere.
Returns:: str
Return type:: formatted line for par file

register_deriv_funcs(func: Callable, param: str) → None

Register the derivative function in to the deriv_func dictionaries.

Parameters:

func (callable) – Calculates the derivative
param (str) – Name of parameter the derivative is with respect to

remove_param(param: str | Parameter) → None

Remove a parameter from the Component.

Parameters:: param (str or pint.models.Parameter) – The parameter to remove.

setup() → None: Finalize construction loaded values.

validate() → None: Validate loaded values.

validate_toas(toas) → None: Check that this model component has TOAs where needed.