popsynth.auxiliary_sampler module

class popsynth.auxiliary_sampler.AuxiliaryParameter(default: Optional[float] = None, vmin: Optional[float] = None, vmax: Optional[float] = None, free: bool = True)

Bases: popsynth.utils.meta.Parameter

class popsynth.auxiliary_sampler.AuxiliarySampler(name: str, observed: bool = True, uses_distance: bool = False, uses_luminosity: bool = False, uses_sky_position: bool = False)

Bases: object

__init__(name: str, observed: bool = True, uses_distance: bool = False, uses_luminosity: bool = False, uses_sky_position: bool = False) → None

Base class for auxiliary samplers.

Parameters:

• name (str) – Name of the sampler
• observed (bool) – True if the property is observed, False if it is latent. Defaults to True
• uses_distance (bool) – True if sampler uses distance values
• uses_luminosity (bool) – True if sampler uses luminosities
• uses_sky_position (bool) – True if sampler uses sky positions

display()

draw(size: int = 1)

Draw the primary and secondary samplers. This is the main call.

Parameters:size (int) – The number of samples to draw

get_secondary_objects(recursive_secondaries: Optional[Dict[str, Any]] = None) → Dict[str, Any]

Get secondary objects.

Parameters:recursive_secondaries – Recursive dict of secondaries Returns:Dict of objects Return type:Dict[str, Any]

get_secondary_properties(graph=None, primary=None, spatial_distribution=None) → popsynth.auxiliary_sampler.SecondaryStorage

Get properties of secondary samplers.

Parameters:

• graph – Graph
• primary – Primary sampler
• spatial_distribution – Spatial Distribution

Returns:

Dict of samplers

Return type:

SamplerDict

has_secondary

if this sampler has a secondary :returns:

is_secondary

If another sampler depends on this

Returns:

luminosity_distance

luminosity distance if needed.

make_secondary(parent_name: str) → None

sets this sampler as secondary for book keeping

Parameters:parent_name (str) – Returns:

name

The name of the sampler

Returns:

obs_name

obs_values

The values obscured by measurement error.

Returns:

observation_sampler(size: int = 1) → numpy.ndarray

observed

if this sampler is observed

Returns:

parents

The parents of this sampler

reset()

Reset all the selections.

secondary_samplers

Secondary samplers. :returns: Dict of secondary samplers :rtype: SamplerDict

selection

The selection booleans on the values

Returns:

selector

The selection probability object

Returns:

set_luminosity(luminosity: Union[Sequence[Sequence[Sequence[Sequence[Sequence[Any]]]]], numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype], Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]], Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]]], Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]]]], Sequence[Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]]]]], bool, int, float, complex, str, bytes, Sequence[Union[bool, int, float, complex, str, bytes]], Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]], Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]], Sequence[Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]]]]) → None

Set the luminosity values.

Parameters:luminosity (ArrayLike) – Luminosity

set_secondary_sampler(sampler: popsynth.auxiliary_sampler.AuxiliarySampler) → None

Add a secondary sampler upon which this sampler will depend. The sampled values can be accessed via an internal dictionary with the samplers ‘name’

self._secondary_sampler[‘name’].true_values self._secondary_sampler[‘name’].obs_values

Parameters:sampler ("AuxiliarySampler") – An auxiliary sampler Returns:

set_selection_probability(selector: popsynth.selection_probability.selection_probability.SelectionProbability) → None

Set a selection probabilty for this sampler.

Parameters:selector (SelectionProbability) – A selection probability oobject Returns:

set_spatial_values(value: popsynth.distribution.SpatialContainer) → None

Set the spatial values.

Parameters:value (SpatialContainer) – Spatial values

true_sampler(size: int = 1)

true_values

The true or latent values

Returns:

truth

A dictionary containing true paramters used to simulate the distribution

uses_distance

If this uses distance

Returns:

uses_luminosity

If this uses luminosity

Returns:

uses_sky_position

If this uses sky position

Returns:

class popsynth.auxiliary_sampler.DerivedLumAuxSampler(name: str, uses_distance: bool = False)

Bases: popsynth.auxiliary_sampler.AuxiliarySampler

__init__(name: str, uses_distance: bool = False)

Base class for generating luminosity from other properties.

Parameters:

• name (str) – Name of the sampler
• uses_distance (bool) – True if sampler uses distance values

compute_luminosity()

class popsynth.auxiliary_sampler.NonObservedAuxSampler(name: str, uses_distance: bool = False, uses_luminosity: bool = False)

Bases: popsynth.auxiliary_sampler.AuxiliarySampler

__init__(name: str, uses_distance: bool = False, uses_luminosity: bool = False)

Base class for auxiliary samplers.

Parameters:

• name (str) – Name of the sampler
• observed (bool) – True if the property is observed, False if it is latent. Defaults to True
• uses_distance (bool) – True if sampler uses distance values
• uses_luminosity (bool) – True if sampler uses luminosities
• uses_sky_position (bool) – True if sampler uses sky positions

class popsynth.auxiliary_sampler.SecondaryContainer(name: str, true_values: Union[Sequence[Sequence[Sequence[Sequence[Sequence[Any]]]]], numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype], Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]], Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]]], Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]]]], Sequence[Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]]]]], bool, int, float, complex, str, bytes, Sequence[Union[bool, int, float, complex, str, bytes]], Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]], Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]], Sequence[Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]]]], obs_values: Union[Sequence[Sequence[Sequence[Sequence[Sequence[Any]]]]], numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype], Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]], Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]]], Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]]]], Sequence[Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]]]]], bool, int, float, complex, str, bytes, Sequence[Union[bool, int, float, complex, str, bytes]], Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]], Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]], Sequence[Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]]]], selection: Union[Sequence[Sequence[Sequence[Sequence[Sequence[Any]]]]], numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype], Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]], Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]]], Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]]]], Sequence[Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]]]]], bool, int, float, complex, str, bytes, Sequence[Union[bool, int, float, complex, str, bytes]], Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]], Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]], Sequence[Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]]]])

Bases: object

__init__(name: str, true_values: Union[Sequence[Sequence[Sequence[Sequence[Sequence[Any]]]]], numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype], Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]], Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]]], Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]]]], Sequence[Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]]]]], bool, int, float, complex, str, bytes, Sequence[Union[bool, int, float, complex, str, bytes]], Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]], Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]], Sequence[Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]]]], obs_values: Union[Sequence[Sequence[Sequence[Sequence[Sequence[Any]]]]], numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype], Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]], Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]]], Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]]]], Sequence[Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]]]]], bool, int, float, complex, str, bytes, Sequence[Union[bool, int, float, complex, str, bytes]], Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]], Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]], Sequence[Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]]]], selection: Union[Sequence[Sequence[Sequence[Sequence[Sequence[Any]]]]], numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype], Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]], Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]]], Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]]]], Sequence[Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype][numpy.dtype]]]]], bool, int, float, complex, str, bytes, Sequence[Union[bool, int, float, complex, str, bytes]], Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]], Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]], Sequence[Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]]]]) → None

A container for secondary properties that adds dict and dictionary access

Parameters:

• name (str) – the name of the secondary
• true_values (ArrayLike) –
• obs_values (ArrayLike) –
• selection (ArrayLike) –

Returns:

name

obs_values

The observed values of the sampler

Returns:

selection

The the slection of the values

Returns:

true_values

The true (latent) values of the sampler

Returns:

class popsynth.auxiliary_sampler.SecondaryStorage

Bases: dotmap.DotMap

__init__()

A container for secondary samplers

Returns:

add_secondary(secondary_values: popsynth.auxiliary_sampler.SecondaryContainer) → None

Add on a new secondary

Parameters:secondary_values (SecondaryContainer) – Returns: