Models

class gammapy.modeling.models.Models(models=None)

Bases: gammapy.modeling.models.core.DatasetModels, collections.abc.MutableSequence

Sky model collection.

Parameters

modelsSkyModel, list of SkyModel or Models

Sky models

Attributes Summary

covariance
names
parameters
parameters_unique_names	List of unique parameter names as model_name.par_type.par_name

Methods Summary

append(value)	S.append(value) – append value to the end of the sequence
clear()
copy()	A deep copy.
count(value)
extend(values)	S.extend(iterable) – extend sequence by appending elements from the iterable
from_dict(data[, path])	Create from dict.
from_yaml(yaml_str[, path])	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
pop([index])	Raise IndexError if list is empty or index is out of range.
read(filename)	Read from YAML file.
read_covariance(path[, filename])	Read covariance data from file
remove(value)	S.remove(value) – remove first occurrence of value.
reverse()	S.reverse() – reverse IN PLACE
select([dataset_name, tag, name_substring])	Select subset of models correspondiog to a given dataset
to_dict([full_output])	Convert to dict.
to_yaml([full_output])	Convert to YAML string.
write(path[, overwrite, full_output, …])	Write to YAML file.
write_covariance(filename, **kwargs)	Write covariance to file

Attributes Documentation

covariance

names

parameters

parameters_unique_names

List of unique parameter names as model_name.par_type.par_name

Methods Documentation

append(value)

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

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

copy()

A deep copy.

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

extend(values)

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

classmethod from_dict(data, path='')

Create from dict.

classmethod from_yaml(yaml_str, path='')

Create from YAML string.

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)

S.insert(index, value) – insert value before index

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)

Read from YAML file.

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

Read covariance data from file

Parameters

filenamestr

Filename

**kwargsdict

Keyword arguments passed to read

remove(value)

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

reverse()

S.reverse() – reverse IN PLACE

select(dataset_name=None, tag=None, name_substring=None)

Select subset of models correspondiog to a given dataset

Parameters

dataset_namestr

Name of the dataset

tagstr

Model tag

name_substringstr

Substring contained in the model name

Returns

dataset_modelDatasetModels

Dataset models

to_dict(full_output=False)

Convert to dict.

to_yaml(full_output=False)

Convert to YAML string.

write(path, overwrite=False, full_output=False, write_covariance=True)

Write to YAML file.

Parameters

pathpathlib.Path or str

path to write files

overwritebool

overwrite files

write_covariancebool

save covariance or not

write_covariance(filename, **kwargs)

Write covariance to file

Parameters

filenamestr

Filename

**kwargsdict

Keyword arguments passed to write