image_source_component
- sherpa.ui.image_source_component(id, model=None, newframe=False, tile=False)
Display a component of the source expression in the image viewer.
This function evaluates and displays a component of the model expression for a data set, without any instrument response. Use
image_model_component
to include any response.The image viewer is automatically started if it is not already open.
- Parameters
id (int or str, optional) – The data set. If not given then the default identifier is used, as returned by
get_default_id
.model (str or sherpa.models.model.Model instance) – The component to display (the name, if a string).
newframe (bool, optional) – Create a new frame for the data? If
False
, the default, then the data will be displayed in the current frame.tile (bool, optional) – Should the frames be tiles? If
False
, the default, then only a single frame is displayed.
- Raises
sherpa.utils.err.IdentifierErr – If the data set does not exist or a source expression has not been set.
See also
get_source_component_image
Return the data used by image_source_component.
image_close
Close the image viewer.
image_fit
Display the data, model, and residuals for a data set in the image viewer.
image_model
Display the model for a data set in the image viewer.
image_model_component
Display a component of the model in the image viewer.
image_open
Open the image viewer.
image_source
Display the source expression for a data set in the image viewer.
Notes
The function does not follow the normal Python standards for parameter use, since it is designed for easy interactive use. When called with a single un-named argument, it is taken to be the
model
parameter. If given two un-named arguments, then they are interpreted as theid
andmodel
parameters, respectively.Image visualization is optional, and provided by the DS9 application.
Examples
Display the full source model and then just the ‘gsrc’ component for the default data set:
>>> image_source() >>> image_source_component(gsrc)
Display the ‘clus’ and ‘bgnd’ components of the model for the ‘img’ data set side by side:
>>> image_source_component('img', 'clus') >>> image_source_component('img', 'bgnd', newframe=True, ... tile=True)