Datasets

class gammapy.datasets.Datasets

Bases: MutableSequence

Container class that holds a list of datasets.

Parameters:

datasetsDataset or list of Dataset

Datasets.

Attributes Summary

contributes_to_stat	Stat contributions.
energy_axes_are_aligned	Whether all contained datasets have aligned energy axis.
energy_ranges	Get global energy range of datasets.
gti	GTI table.
is_all_same_energy_shape	Whether all contained datasets have the same data shape.
is_all_same_shape	Whether all contained datasets have the same data shape.
is_all_same_type	Whether all contained datasets are of the same type.
meta_table	Meta table.
models	Unique models (Models).
names
parameters	Unique parameters (Parameters).

Methods Summary

copy()	Deep copy.
index(value, [start, [stop]])	Raises ValueError if the value is not present.
info_table([cumulative])	Get info table for datasets.
insert(idx, dataset)	S.insert(index, value) -- insert value before index
read(filename[, filename_models, lazy, ...])	De-serialize datasets from YAML and FITS files.
select_time(time_min, time_max[, atol])	Select datasets in a given time interval.
slice_by_energy(energy_min, energy_max)	Select and slice datasets in energy range.
stack_reduce([name, nan_to_num])	Reduce the Datasets to a unique Dataset by stacking them together.
stat_sum()	Compute joint statistic function value.
to_spectrum_datasets(region)	Extract spectrum datasets for the given region.
write(filename[, filename_models, ...])	Serialize datasets to YAML and FITS files.

Attributes Documentation

contributes_to_stat

Stat contributions.

Returns:

contributionsarray

Array indicating which dataset contributes to the likelihood.

energy_axes_are_aligned

Whether all contained datasets have aligned energy axis.

energy_ranges

Get global energy range of datasets.

The energy range is derived as the minimum / maximum of the energy ranges of all datasets.

Returns:

energy_min, energy_maxQuantity

Energy range.

gti

GTI table.

is_all_same_energy_shape

Whether all contained datasets have the same data shape.

is_all_same_shape

Whether all contained datasets have the same data shape.

is_all_same_type

Whether all contained datasets are of the same type.

meta_table

Meta table.

models

Unique models (Models).

Duplicate model objects have been removed. The order of the unique models remains.

names

parameters

Unique parameters (Parameters).

Duplicate parameter objects have been removed. The order of the unique parameters remains.

Methods Documentation

copy()

Deep copy.

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.

info_table(cumulative=False)

Get info table for datasets.

Parameters:

cumulativebool

Cumulate information across all datasets. If True, all model-dependent information will be lost. Default is False.

Returns:

info_tableTable

Info table.

insert(idx, dataset)

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

classmethod read(filename, filename_models=None, lazy=True, cache=True, checksum=True)

De-serialize datasets from YAML and FITS files.

Parameters:

filenamestr or Path

File path or name of datasets yaml file.

filename_modelsstr or Path, optional

File path or name of models yaml file. Default is None.

lazybool

Whether to lazy load data into memory. Default is True.

cachebool

Whether to cache the data after loading. Default is True.

checksumbool

Whether to perform checksum verification. Default is False.

Returns:

datasetgammapy.datasets.Datasets

Datasets.

select_time(time_min, time_max, atol='1e-6 s')

Select datasets in a given time interval.

Parameters:

time_min, time_maxTime

Time interval.

atolQuantity

Tolerance value for time comparison with different scale. Default 1e-6 sec.

Returns:

datasetsDatasets

Datasets in the given time interval.

slice_by_energy(energy_min, energy_max)

Select and slice datasets in energy range.

The method keeps the current dataset names. Datasets that do not contribute to the selected energy range are dismissed.

Parameters:

energy_min, energy_maxQuantity

Energy bounds to compute the flux point for.

Returns:

datasetsDatasets

Datasets.

stack_reduce(name=None, nan_to_num=True)

Reduce the Datasets to a unique Dataset by stacking them together.

This works only if all datasets are of the same type and with aligned geometries, and if a proper in-place stack method exists for the Dataset type.

For details, see Stacking Multiple Datasets.

Parameters:

namestr, optional

Name of the stacked dataset. Default is None.

nan_to_numbool

Non-finite values are replaced by zero if True. Default is True.

Returns:

datasetDataset

The stacked dataset.

stat_sum()

Compute joint statistic function value.

to_spectrum_datasets(region)

Extract spectrum datasets for the given region.

To get more detailed information, see the corresponding function associated to each dataset type: to_spectrum_dataset or to_spectrum_dataset.

Parameters:

regionSkyRegion

Region definition.

Returns:

datasetsDatasets

List of SpectrumDataset.

write(filename, filename_models=None, overwrite=False, write_covariance=True, checksum=True)

Serialize datasets to YAML and FITS files.

Parameters:

filenamestr or Path

File path or name of datasets yaml file.

filename_modelsstr or Path, optional

File path or name of models yaml file. Default is None.

overwritebool, optional

Overwrite existing file. Default is False.

write_covariancebool

save covariance or not. Default is True.

checksumbool

When True adds both DATASUM and CHECKSUM cards to the headers written to the FITS files. Default is True.

__init__(datasets=None)

classmethod __new__(*args, **kwargs)