Dataset

Dataset	A class representing a scientific database stored in a file
create_dataset(name[, description])	Create new LUE dataset
open_dataset(name[, mode])	Open existing LUE dataset
validate(name)	Check whether a file contains a valid LUE dataset
assert_is_valid(*args, **kwargs)	Overloaded function.

class lue.data_model.Dataset

A class representing a scientific database stored in a file

A LUE dataset contains collections of universes and phenomena.

New datasets can be created using create_dataset(). Existing datasets can be opened with open_dataset().

Note

A LUE dataset is not similar to an HDF5 dataset. An HDF5 dataset represents a multidimensional array in an HDF5 file. A LUE dataset is an HDF5 file containing many HDF5 objects, including HDF5 datasets.

add_phenomenon(self: lue.lue_py.data_model.Dataset, name: str, description: str = '') → lue.lue_py.data_model.Phenomenon

Add new phenomenon to dataset

Parameters:

• name (str) – Name of phenomenon to create

• description (str) – Description of phenomenon

Raises:

RuntimeError – In case the phenomenon cannot be created

Return type:

Phenomenon

add_universe(self: lue.lue_py.data_model.Dataset, name: str) → lue.lue_py.data_model.Universe

Add new universe to dataset

Parameters:

name (str) – Name of universe to create

Raises:

RuntimeError – In case the universe cannot be created

Return type:

Universe

property lue_version

Return version of LUE used to create the dataset

Return type:

str

property phenomena

Return phenomena collection

Return type:

Phenomena

property universes

Return universes collection

Return type:

Universes

lue.data_model.create_dataset(name: str, description: str = '') → lue.lue_py.data_model.Dataset

Create new LUE dataset

Parameters:

• name (str) – Name of dataset to create. If a file with this name already exists it will be overwritten.

• description (str) – Description

Return type:

Dataset

Newly created datasets can be validated using validate().

lue.data_model.open_dataset(name: str, mode: str = 'r') → lue.lue_py.data_model.Dataset

Open existing LUE dataset

Parameters:

• name (str) – Name of dataset to open

• mode (str) –

  String that specifies the mode in which the dataset is opened. The available modes are:

  Character	Meaning
  r	Open dataset for reading (default)
  w	Open dataset for writing, truncating the dataset first

Return type:

Dataset

Updated datasets can be validated using validate().

lue.data_model.validate(name: str) → lue.lue_py.data_model.hdf5.Issues

Check whether a file contains a valid LUE dataset

Parameters:

name (str) – Name of file to check

Returns:

Collection of issues found

Return type:

hdf5.Issues

See also: assert_is_valid()

lue.data_model.assert_is_valid(*args, **kwargs)

Overloaded function.

1. assert_is_valid(name: str, fail_on_warning: bool = True) -> None

   Check whether a file contains a valid LUE dataset

   param str name:

   Name of file to check

   param bool fail_on_warning:

   Whether or not to treat warnings as errors

   raises RuntimeError:

   If errors are found

   See also: validate()

2. assert_is_valid(file: lue.lue_py.data_model.hdf5.File, fail_on_warning: bool = True) -> None

   Check whether a file contains a valid LUE dataset

   param hdf5.File file:

   File to check

   param bool fail_on_warning:

   Whether or not to treat warnings as errors

   raises RuntimeError:

   If errors are found

   See also: validate()