nifreeze.utils.iterators module¶

Iterators to traverse the volumes in a 4D image.

nifreeze.utils.iterators.bvalue_iterator(*_, **kwargs) → Iterator[int][source]¶

Traverse the volumes in a DWI dataset by growing b-value.

Parameters:: bvals (list) – List of b-values corresponding to all orientations of the dataset. Please note that bvals is a keyword argument and MUST be provided to generate the volume sequence.
Yields:: int – The next index.

Examples

>>> list(bvalue_iterator(bvals=[0.0, 0.0, 1000.0, 1000.0, 700.0, 700.0, 2000.0, 2000.0, 0.0]))
[0, 1, 8, 4, 5, 2, 3, 6, 7]

nifreeze.utils.iterators.centralsym_iterator(size: int | None = None, **kwargs) → Iterator[int][source]¶

Traverse the dataset starting from the center and alternatingly progressing to the sides.

Parameters:

size (int or None, optional) – Number of volumes in the dataset. If None, size will be inferred from the bvals keyword argument.
bvals (list, optional (keyword argument)) – List of b-values corresponding to all orientations of the dataset. If size is provided, this argument will be ignored. Otherwise, size will be inferred from the length of bvals.

Yields:

int – The next index.

Examples

>>> list(centralsym_iterator(10))
[5, 4, 6, 3, 7, 2, 8, 1, 9, 0]
>>> list(centralsym_iterator(11))
[5, 4, 6, 3, 7, 2, 8, 1, 9, 0, 10]

nifreeze.utils.iterators.linear_iterator(size: int | None = None, **kwargs) → Iterator[int][source]¶

Traverse the dataset volumes in ascending order.

Parameters:

size (int or None, optional) – Number of volumes in the dataset. If None, size will be inferred from the bvals keyword argument.
bvals (list, optional (keyword argument)) – List of b-values corresponding to all orientations of a DWI dataset. If size is provided, this argument will be ignored. Otherwise, size will be inferred from the length of bvals.

Yields:

int – The next index.

Examples

>>> list(linear_iterator(10))
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

nifreeze.utils.iterators.random_iterator(size: int | None = None, **kwargs) → Iterator[int][source]¶

Traverse the dataset volumes randomly.

If the seed key is present in the keyword arguments, initializes the seed of Python’s random pseudo-random number generator library with the given value. Specifically, if False, None is used as the seed; if True, a default seed value is used.

Parameters:

size (int or None, optional) – Number of volumes in the dataset. If None, size will be inferred from the bvals keyword argument.
bvals (list, optional (keyword argument)) – List of b-values corresponding to all orientations of a DWI dataset. If size is provided, this argument will be ignored. Otherwise, size will be inferred from the length of bvals.
seed (int, bool, str, or None, optional (keyword argument)) – If int or str or None, initializes the seed of Python’s random generator with the given value. If False, the random generator is passed None. If True, a default seed value is set.

Yields:

int – The next index.

Examples

>>> list(random_iterator(15, seed=0))  # seed is 0
[1, 10, 9, 5, 11, 2, 3, 7, 8, 4, 0, 14, 12, 6, 13]
>>>  # seed is True -> the default value 20210324 is set
>>> list(random_iterator(15, seed=True))
[1, 12, 14, 5, 0, 11, 10, 9, 7, 8, 3, 13, 2, 6, 4]
>>> list(random_iterator(15, seed=20210324))
[1, 12, 14, 5, 0, 11, 10, 9, 7, 8, 3, 13, 2, 6, 4]
>>> list(random_iterator(15, seed=42))  # seed is 42
[8, 13, 7, 6, 14, 12, 5, 2, 9, 3, 4, 11, 0, 1, 10]