lib.samples.profiles.Profiles¶

class lib.samples.profiles.Profiles(parameters, attrs=None)¶

Bases: cosmopipe.lib.utils.BaseClass

Class holding results of likelihood profiling.

init¶

Initial parameter values.

Type: ParamDict

bestfit¶

Best fit parameters.

Type: ParamDict

parabolic_errors¶

Parameter parabolic errors.

Type: ParamDict

deltachi2_errors¶

Lower and upper errors corresponding to \(\Delta \chi^{2} = 1\).

Type: ParamDict

covariance¶

Parameter covariance at best fit.

Type: ParamCovariance

Initialize Profiles.

Parameters

parameters (list, ParameterCollection) – Parameters used in likelihood profiling.
attrs (dict, default=None) – Other attributes.

Methods

`argmin`	Return index of best best fit among all the tries.
`concatenate`	Concatenate profiles together.
`copy`	Return shallow copy of `self`.
`deepcopy`
`extend`	Extend profiles with `other`.
`from_state`	Instantiate and initalize class with state dictionary.
`get`	Access attribute by name.
`has`	Has this attribute?
`is_mpi_broadcast`
`is_mpi_gathered`
`is_mpi_root`
`is_mpi_scattered`
`load`	Load class in numpy binary format from disk.
`load_auto`	If different formats are possible, this method should between them based on file name extension.
`log_critical`
`log_debug`
`log_error`
`log_info`
`log_warning`
`ntries`	Return number of tries.
`save`	Save class to disk.
`save_auto`	If different formats are possible, this method should between them based on file name extension.
`set_bestfit`	Set best fit parameter values `values`.
`set_covariance`	Set parameter covariance `covariance` for parameters `parameters`.
`set_deltachi2_errors`	Set parameter \(\Delta \chi^{2} = 1\) errors `values`.
`set_init`	Set initial parameter values `values`.
`set_metrics`	Set metrics (e.g.
`set_parabolic_errors`	Set parameter parabolic errors `values`.
`to_samples`	Export profiles as `Samples`.
`to_stats`	Export profiling quantities.

Attributes

`logger`
`mpiattrs`	MPI attributes
`mpicomm`
`mpiroot`
`mpistate`

argmin()¶: Return index of best best fit among all the tries.

classmethod concatenate(*others)¶

Concatenate profiles together.

Parameters: others (list) – List of Profiles instances.
Returns: new
Return type: Profiles

Warning

attrs of returned profiles contains, for each key, the last value found in others attrs dictionaries.

copy()¶: Return shallow copy of self.

extend(other)¶: Extend profiles with other.

classmethod from_state(state, mpiroot=0, mpicomm=None)¶: Instantiate and initalize class with state dictionary.

get(name)¶: Access attribute by name.

has(name)¶: Has this attribute?

classmethod load(filename, mpiroot=0, mpicomm=None)¶: Load class in numpy binary format from disk. If the loaded state contains __class__ and that exists in cls._registry, return instance of cls._registry[__class__] (instead of cls).

load_auto(*args, **kwargs)¶: If different formats are possible, this method should between them based on file name extension.

property mpiattrs¶: MPI attributes

ntries()¶: Return number of tries.

save(filename)¶: Save class to disk.

save_auto(*args, **kwargs)¶: If different formats are possible, this method should between them based on file name extension.

set_bestfit(values)¶: Set best fit parameter values values.

set_covariance(covariance, parameters=None)¶: Set parameter covariance covariance for parameters parameters.

set_deltachi2_errors(values)¶: Set parameter \(\Delta \chi^{2} = 1\) errors values.

set_init(values)¶: Set initial parameter values values.

set_metrics(values)¶: Set metrics (e.g. ‘loglkl’) dictionary values.

set_parabolic_errors(values)¶: Set parameter parabolic errors values.

classmethod to_samples(profiles, parameters=None, name='bestfit', select='min')¶

Export profiles as Samples. This is not statistically meaningful, but convenient to share plotting routines.

Parameters

profiles (list) – List of Profiles instances.
parameters (list, ParameterCollection, default=None) – Parameters to export. Defaults to all parameters.
name (string, default='bestfit') – Quantity to export as samples.
select (string, default='min') – Rule to select the quantity to export.

Returns

samples

Return type

Samples

to_stats(parameters=None, quantities=None, sigfigs=2, tablefmt='latex_raw', filename=None)¶

Export profiling quantities.

Parameters

parameters (list, ParameterCollection) – Parameters to export quantities for. Defaults to all parameters.
quantities (list, default=None) – Quantities to export. Defaults to ['bestfit','parabolic_errors','deltachi2_errors'].
sigfigs (int, default=2) – Number of significant digits. See utils.round_measurement().
tablefmt (string, default='latex_raw') – Format for summary table. See tabulate.tabulate().
filename (string default=None) – If not None, file name where to save summary table.

Returns

tab – Summary table.

Return type

string