Observation

Observation#

class scarlet2.Observation(data, weights, psf=None, wcs=None, channels=None, renderer=None, name=None)[source]#

Bases: Module

Content and definition of an observation

property N#: Number of unmasked pixels in the observation

__call__()#: Evaluate the model

check_set_renderer(frame)[source]#

Check existence of renderer, or set it by calling match()

Parameters:: frame (Frame) – The frame to match
Return type:: None

data: Array#: Observed data

eval_chi_square_in_box_and_border(scene, border_width=3)[source]#

Evaluate the weighted mean (weighted by the inverse variance weights) of the squared residuals for each source. Chi square is also computed for the perimeter outside the box of with border_width.

Parameters:

scene (Scene) – Scene containing the sources
border_width (int) – width of the border around the source box

Return type:

Dict of sources indices and their corresponding Dict of residuals inside and outside source box.

frame: Frame#: Metadata to describe what view of the sky data amounts to

get(name=None)#

Get parameter(s) from this module

Parameters:: name (str, optional) – Name of parameter. If not set, returns all parameters.
Returns:: requested data arrays for parameters
Return type:: dict

goodness_of_fit(model)[source]#

Evaluate the goodness of the model fit to the data

For a Gaussian noise model, the gof is defined as the averaged squared deviation of the model from the data, scaled by the variance of the data, aka mean chi squared \(\frac{1}{N}\sum_i=1^N w_i (m_i - d_i)^2\) with inverse variance weights \(w_i\).

Up to a normalization, the gof is identical to log-likelihood.

Parameters:: model (array) – The (pre-rendered) predicted data cube, typically from evaluating Scene
Return type:: float

log_likelihood(model)[source]#

The logarithm the likelihood of data given model

Parameters:: model (array) – The (pre-rendered) predicted data cube, typically from evaluating Scene
Return type:: float

match(frame, renderer=None)[source]#

Construct the mapping between frame (from the model) and this observation frame

Parameters:

frame (Frame) – Model frame, typically scarlet2.Scene.frame for the current scene.
renderer (Renderer, optional) – Custom transformation to translate the frame (from the model) to this observation frame. If not set, this method will attempt to create the mapping from the information in both frames.

Return type:

None

name: str#: Name to describe the observation

property parameters#

Parameters defined for this module

Returns:: name: (node, param) mapping for all parameters
Return type:: dict

render(model, **kwargs)[source]#

Render model in the frame of this observation

Parameters:

model (array) – The (pre-rendered) predicted data cube, typically from evaluating Scene
kwargs (dict) – Additional keyword arguments to pass to the renderer

Returns:

Prediction of the observation given the model. Has the same shape as data.

Return type:

array

renderer: Renderer#: Renderer to translate from the model frame the observation frame

replace(name, value)#

Replace member attribuge name with value

Parameters:

name (str) – Name of member to replace
value (any) – Value to replace member with

Returns:

The modified module.

Return type:

Module

replace_subtree(where, value, parameters=None)#

Replace the subtree where(self) with value and carry over all other parameters

Unlike replace(), value does not need to have the same structure as the subtree it replaces, e.g. an array morphology can be replaced by a SersicMorphology. Parameters defined for this module remain attached to the same nodes, except those inside the replaced subtree, which are dropped.

Parameters:

where (callable) – Function module -> node that selects the subtree to replace, as in equinox.tree_at()
value (any) – Replacement for the subtree. If this module has a frame, attributes of value given in sky coordinates are converted to pixel coordinates of that frame.
parameters (callable, optional) – Function module -> None that is called with the new module inside of a Parameters context to define parameters for the replacement, e.g. by calling Parameter on nodes of value.

Returns:

The modified module.

Return type:

Module

Examples

>>> sersic = SersicMorphology(n=jnp.array(2.), size=jnp.array(2.), shape=morph.shape)
>>> def sersic_parameters(morph):
>>>     Parameter(morph.n, name="n:0", prior=dist.Uniform(0.5, 6))
>>>     Parameter(morph.size, name="size:0", constraint=constraints.positive, stepsize=0.1)
>>>
>>> scene_ = scene.replace_subtree(lambda sc: sc.sources[0].morphology, sersic, sersic_parameters)

Observation

Contents

Observation#