Models#

class gammapy.modeling.models.Models(models=None, covariance_data=None)[source]#

Bases: DatasetModels, MutableSequence

Sky model collection.

Parameters:

modelsSkyModel, list of SkyModel or Models: Sky models.

Attributes Summary

`covariance`	Covariance as a `Covariance` object.
`frozen`	Boolean mask, True if all parameters of a given model are frozen.
`names`	List of model names.
`parameters`	Parameters as a `Parameters` object.
`parameters_unique_names`	List of unique parameter names.
`positions`	Positions of the models as a `SkyCoord`.
`wcs_geom`	Minimum WCS geom in which all the models are contained.

Methods Summary

`append`(value)	S.append(value) -- append value to the end of the sequence
`clear`()
`copy`([copy_data])	Deep copy.
`count`(value)
`extend`(values)	S.extend(iterable) -- extend sequence by appending elements from the iterable
`freeze`([model_type])	Freeze parameters depending on model type.
`from_dict`(data[, path])	Create from dictionary.
`from_yaml`(yaml_str[, path, checksum])	Create from YAML string.
`index`(value, [start, [stop]])	Raises ValueError if the value is not present.
`insert`(idx, model)	S.insert(index, value) -- insert value before index
`plot_positions`([ax])	Plot the centers of the spatial models on a given WCS axis.
`plot_regions`([ax, kwargs_point, path_effect])	Plot extent of the spatial models on a given WCS axis.
`pop`([index])	Raise IndexError if list is empty or index is out of range.
`read`(filename[, checksum])	Read from YAML file.
`read_covariance`(path[, filename])	Read covariance data from file.
`reassign`(dataset_name, new_dataset_name)	Reassign a model from one dataset to another.
`remove`(value)	S.remove(value) -- remove first occurrence of value.
`restore_status`([restore_values])	Context manager to restore status.
`reverse`()	S.reverse() -- reverse IN PLACE
`select`([name_substring, datasets_names, ...])	Select models that meet all specified conditions.
`select_from_geom`(geom, **kwargs)	Select models that fall inside a given geometry.
`select_mask`(mask[, margin, ...])	Check if sky models contribute within a mask map.
`select_region`(regions[, wcs])	Select sky models with center position contained within a given region.
`selection_mask`([name_substring, ...])	Create a mask of models, that meet all specified conditions.
`set_parameters_bounds`(tag, model_type[, ...])	Set bounds for the selected models types and parameters names.
`set_prior`(parameters, priors)
`to_dict`([full_output, overwrite_templates])	Convert to dictionary.
`to_parameters_table`()	Convert model parameters to a `Table`.
`to_regions`()	Return a list of the regions for the spatial models.
`to_template_sky_model`(geom[, ...])	Merge a list of models into a single `SkyModel`.
`to_template_spectral_model`(geom[, mask])	Merge a list of models into a single `TemplateSpectralModel`.
`to_yaml`([full_output, overwrite_templates])	Convert to YAML string.
`unfreeze`([model_type])	Restore parameters frozen status to default depending on model type.
`update_link_label`()	Update linked parameters labels used for serialisation and print.
`update_parameters_from_table`(t)	Update models from a `Table`.
`write`(path[, overwrite, full_output, ...])	Write to YAML file.
`write_covariance`(filename, **kwargs)	Write covariance to file.

Attributes Documentation

covariance#: Covariance as a Covariance object.

frozen#: Boolean mask, True if all parameters of a given model are frozen.

names#: List of model names.

parameters#: Parameters as a Parameters object.

parameters_unique_names#: List of unique parameter names. Return formatted as model_name.par_type.par_name.

positions#: Positions of the models as a SkyCoord.

wcs_geom#: Minimum WCS geom in which all the models are contained.

Methods Documentation

append(value)#: S.append(value) – append value to the end of the sequence

clear() → None -- remove all items from S#

copy(copy_data=False)#

Deep copy.

Parameters:

copy_databool: Whether to copy data attached to template models.

Returns:

models: Models: Copied models.

count(value) → integer -- return number of occurrences of value#

extend(values)#: S.extend(iterable) – extend sequence by appending elements from the iterable

freeze(model_type=None)#

Freeze parameters depending on model type.

Parameters:

model_type{None, “spatial”, “spectral”}: Freeze all parameters or only spatial or only spectral. Default is None.

classmethod from_dict(data, path='')#: Create from dictionary.

classmethod from_yaml(yaml_str, path='', checksum=False)#

Create from YAML string.

Parameters:

yaml_strstr: yaml str
pathstr: base path of model files
checksumbool, optional: Whether to perform checksum verification. Default is False.

index(value[, start[, stop]]) → integer -- return first index of value.#

Raises ValueError if the value is not present.

Supporting start and stop arguments is optional, but recommended.

insert(idx, model)[source]#: S.insert(index, value) – insert value before index

plot_positions(ax=None, **kwargs)#

Plot the centers of the spatial models on a given WCS axis.

Parameters:

axWCSAxes, optional: Axes to plot on. If no axes are given, an all-sky WCS is chosen using a CAR projection. Default is None.
**kwargsdict: Keyword arguments passed to scatter.

Returns:

axWcsAxes: WCS axes.

plot_regions(ax=None, kwargs_point=None, path_effect=None, **kwargs)#

Plot extent of the spatial models on a given WCS axis.

Parameters:

axWCSAxes, optional: Axes to plot on. If no axes are given, an all-sky WCS is chosen using a CAR projection. Default is None.
kwargs_pointdict, optional: Keyword arguments passed to Line2D for plotting of point sources. Default is None.
path_effectPathEffect, optional: Path effect applied to artists and lines. Default is None.
**kwargsdict: Keyword arguments passed to Artist.

Returns:

axWcsAxes: WCS axes.

pop([index]) → item -- remove and return item at index (default last).#: Raise IndexError if list is empty or index is out of range.

classmethod read(filename, checksum=False)#

Read from YAML file.

Parameters:

filenamestr: input filename
checksumbool, optional: Whether to perform checksum verification. Default is False.

read_covariance(path, filename='_covariance.dat', **kwargs)#

Read covariance data from file.

Parameters:

pathstr or Path: Base path.
filenamestr: Filename.
**kwargsdict: Keyword arguments passed to read.

reassign(dataset_name, new_dataset_name)#

Reassign a model from one dataset to another.

Parameters:

dataset_namestr or list: Name of the datasets where the model is currently defined.
new_dataset_namestr or list: Name of the datasets where the model should be defined instead. If multiple names are given the two list must have the save length, as the reassignment is element-wise.

remove(value)#: S.remove(value) – remove first occurrence of value. Raise ValueError if the value is not present.

restore_status(restore_values=True)#

Context manager to restore status.

A copy of the values is made on enter, and those values are restored on exit.

Parameters:

restore_valuesbool, optional: Restore values if True, otherwise restore only frozen status and covariance matrix. Default is True.

reverse()#: S.reverse() – reverse IN PLACE

select(name_substring=None, datasets_names=None, tag=None, model_type=None, frozen=None)#

Select models that meet all specified conditions.

Parameters:

name_substringstr, optional: Substring contained in the model name. Default is None.
datasets_namesstr or list, optional: Name of the dataset. Default is None.
tagstr or list, optional: Model tag. Default is None.
model_type{‘None’, ‘spatial’, ‘spectral’}: Type of model, used together with “tag”, if the tag is not unique. Default is None.
frozenbool, optional: If True, select models with all parameters frozen; if False, exclude them. Default is None.

Returns:

modelsDatasetModels: Selected models.

select_from_geom(geom, **kwargs)#

Select models that fall inside a given geometry.

Parameters:

geomGeom: Geometry to select models from.
**kwargsdict: Keyword arguments passed to select_mask.

Returns:

modelsDatasetModels: Selected models.

select_mask(mask, margin='0 deg', use_evaluation_region=True)#

Check if sky models contribute within a mask map.

Parameters:

maskWcsNDMap of boolean type: Map containing a boolean mask.
marginQuantity, optional: Add a margin in degree to the source evaluation radius. Used to take into account PSF width. Default is “0 deg”.
use_evaluation_regionbool, optional: Account for the extension of the model or not. Default is True.

Returns:

modelsDatasetModels: Selected models contributing inside the region where mask==True.

select_region(regions, wcs=None)#

Select sky models with center position contained within a given region.

Parameters:

regionsstr, Region or list of Region: Region or list of regions (pixel or sky regions accepted). A region can be defined as a string ind DS9 format as well. See http://ds9.si.edu/doc/ref/region.html for details.
wcsWCS, optional: World coordinate system transformation. Default is None.

Returns:

modelsDatasetModels: Selected models.

selection_mask(name_substring=None, datasets_names=None, tag=None, model_type=None, frozen=None)#

Create a mask of models, that meet all specified conditions.

Parameters:

name_substringstr, optional: Substring contained in the model name. Default is None.
datasets_namesstr or list of str, optional: Name of the dataset. Default is None.
tagstr or list of str, optional: Model tag. Default is None.
model_type{‘None’, ‘spatial’, ‘spectral’}: Type of model, used together with “tag”, if the tag is not unique. Default is None.
frozenbool, optional: Select models with all parameters frozen if True, exclude them if False. Default is None.

Returns:

masknumpy.array: Boolean mask, True for selected models.

set_parameters_bounds(tag, model_type, parameters_names=None, min=None, max=None, value=None)#

Set bounds for the selected models types and parameters names.

Parameters:

tagstr or list: Tag of the models.
model_type{“spatial”, “spectral”, “temporal”}: Type of model.
parameters_namesstr or list, optional: Parameters names. Default is None.
minfloat, optional: Minimum value. Default is None.
maxfloat, optional: Maximum value. Default is None.
valuefloat, optional: Initial value. Default is None.

set_prior(parameters, priors)[source]#

to_dict(full_output=False, overwrite_templates=False)#: Convert to dictionary.

to_parameters_table()#: Convert model parameters to a Table.

to_regions()#

Return a list of the regions for the spatial models.

Returns:

regions: list of SkyRegion: Regions.

to_template_sky_model(geom, spectral_model=None, name=None)#

Merge a list of models into a single SkyModel.

Parameters:

geomGeom: Map geometry of the result template model.
spectral_modelSpectralModel, optional: One of the NormSpectralModel. Default is None.
namestr, optional: Name of the new model. Default is None.

Returns:

modelSkyModel: Template sky model.

to_template_spectral_model(geom, mask=None)#

Merge a list of models into a single TemplateSpectralModel.

For each model the spatial component is integrated over the given geometry where the mask is true and multiplied by the spectral component value in each energy bin.

Parameters:

geomGeom: Map geometry on which the template model is computed.
maskMap with bool dtype.: Evaluate the model only where the mask is True.

Returns:

modelTemplateSpectralModel: Template spectral model.

to_yaml(full_output=False, overwrite_templates=False)#

Convert to YAML string.

Parameters:

full_outputbool, optional: Store full parameter output. Default is False.
overwrite_templatesbool, optional: Overwrite templates FITS files. Default is False.

unfreeze(model_type=None)#

Restore parameters frozen status to default depending on model type.

Parameters:

model_type{None, “spatial”, “spectral”}: Restore frozen status to default for all parameters or only spatial or only spectral. Default is None.

update_link_label()#: Update linked parameters labels used for serialisation and print.

update_parameters_from_table(t)#: Update models from a Table.

write(path, overwrite=False, full_output=False, overwrite_templates=False, write_covariance=True, checksum=False)#

Write to YAML file.

Parameters:

pathpathlib.Path or str: Path to write files.
overwritebool, optional: Overwrite existing file. Default is False.
full_outputbool, optional: Store full parameter output. Default is False.
overwrite_templatesbool, optional: Overwrite templates FITS files. Default is False.
write_covariancebool, optional: Whether to save the covariance. Default is True.
checksumbool, optional: When True adds a CHECKSUM entry to the file. Default is False.

write_covariance(filename, **kwargs)#

Write covariance to file.

Parameters:

filenamestr: Filename.
**kwargsdict: Keyword arguments passed to write.