trx.streamlines_ops#

Attributes#

`MIN_NB_POINTS`
`KEY_INDEX`

Functions#

`intersection`(left, right)	Intersection of two streamlines dict (see hash_streamlines)
`difference`(left, right)	Difference of two streamlines dict (see hash_streamlines)
`union`(left, right)	Union of two streamlines dict (see hash_streamlines)
`get_streamline_key`(streamline[, precision])	Produces a key using a hash from a streamline using a few points only and
`hash_streamlines`(streamlines[, start_index, precision])	Produces a dict from streamlines
`perform_streamlines_operation`(operation, streamlines)	Peforms an operation on a list of list of streamlines

Module Contents#

trx.streamlines_ops.MIN_NB_POINTS = 5[source]#

trx.streamlines_ops.KEY_INDEX[source]#

trx.streamlines_ops.intersection(left, right)[source]#: Intersection of two streamlines dict (see hash_streamlines)

trx.streamlines_ops.difference(left, right)[source]#: Difference of two streamlines dict (see hash_streamlines)

trx.streamlines_ops.union(left, right)[source]#: Union of two streamlines dict (see hash_streamlines)

trx.streamlines_ops.get_streamline_key(streamline, precision=None)[source]#

Produces a key using a hash from a streamline using a few points only and the desired precision

Parameters:

streamlines: ndarray: A single streamline (N,3)
precision: int, optional: The number of decimals to keep when hashing the points of the streamlines. Allows a soft comparison of streamlines. If None, no rounding is performed.

Returns:

Value of the hash of the first/last MIN_NB_POINTS points of the streamline.

trx.streamlines_ops.hash_streamlines(streamlines, start_index=0, precision=None)[source]#

Produces a dict from streamlines

Produces a dict from streamlines by using the points as keys and the indices of the streamlines as values.

Parameters:

streamlines: list of ndarray: The list of streamlines used to produce the dict.
start_index: int, optional: The index of the first streamline. 0 by default.
precision: int, optional: The number of decimals to keep when hashing the points of the streamlines. Allows a soft comparison of streamlines. If None, no rounding is performed.

Returns:

A dict where the keys are streamline points and the values are indices
starting at start_index.

trx.streamlines_ops.perform_streamlines_operation(operation, streamlines, precision=0)[source]#

Peforms an operation on a list of list of streamlines

Given a list of list of streamlines, this function applies the operation to the first two lists of streamlines. The result in then used recursively with the third, fourth, etc. lists of streamlines.

A valid operation is any function that takes two streamlines dict as input and produces a new streamlines dict (see hash_streamlines). Union, difference, and intersection are valid examples of operations.

Parameters:

operation: callable: A callable that takes two streamlines dicts as inputs and preduces a new streamline dict.
streamlines: list of list of streamlines: The streamlines used in the operation.
precision: int, optional: The number of decimals to keep when hashing the points of the streamlines. Allows a soft comparison of streamlines. If None, no rounding is performed.

Returns:

streamlines: list of nib.streamline.ArraySequence: The streamlines obtained after performing the operation on all the input streamlines.
indices: np.ndarray: The indices of the streamlines that are used in the output.