usage: __main__.py [-h]
[--length LENGTH_MATRIX | --inverse_length LENGTH_MATRIX]
[--bundle_volume VOLUME_MATRIX]
[--parcel_volume ATLAS LABELS_LIST | --parcel_surface ATLAS LABELS_LIST]
[--max_at_one | --sum_to_one | --log_10]
[-v [{DEBUG,INFO,WARNING}]] [-f]
in_matrix out_matrix
Normalize a connectivity matrix coming from
scil_tractogram_segment_bundles_for_connectivity.py.
3 categories of normalization are available:
-- Edge attributes
- length: Multiply each edge by the average bundle length.
Compensate for far away connections when using interface seeding.
Cannot be used with inverse_length.
- inverse_length: Divide each edge by the average bundle length.
Compensate for big connections when using white matter seeding.
Cannot be used with length.
- bundle_volume: Divide each edge by the average bundle length.
Compensate for big connections when using white matter seeding.
-- Node attributes (Mutually exclusive)
- parcel_volume: Divide each edge by the sum of node volume.
Compensate for the likelihood of ending in the node.
Compensate seeding bias when using interface seeding.
- parcel_surface: Divide each edge by the sum of the node surface.
Compensate for the likelihood of ending in the node.
Compensate for seeding bias when using interface seeding.
-- Matrix scaling (Mutually exclusive)
- max_at_one: Maximum value of the matrix will be set to one.
- sum_to_one: Ensure the sum of all edges weight is one
- log_10: Apply a base 10 logarithm to all edges weight
The volume and length matrix should come from the
scil_tractogram_segment_bundles_for_connectivity.py script.
A review of the type of normalization is available in:
Colon-Perez, Luis M., et al. "Dimensionless, scale-invariant, edge weight
metric for the study of complex structural networks." PLOS one 10.7 (2015).
However, the proposed weighting of edge presented in this publication is not
implemented.
Formerly: scil_normalize_connectivity.py
positional arguments:
in_matrix Input connectivity matrix. This is typically a streamline_count matrix (.npy).
out_matrix Output normalized matrix (.npy).
options:
-h, --help show this help message and exit
-v [{DEBUG,INFO,WARNING}]
Produces verbose output depending on the provided level.
Default level is warning, default when using -v is info.
-f Force overwriting of the output files.
Edge-wise options:
--length LENGTH_MATRIX
Length matrix used for edge-wise multiplication.
--inverse_length LENGTH_MATRIX
Length matrix used for edge-wise division.
--bundle_volume VOLUME_MATRIX
Volume matrix used for edge-wise division.
--parcel_volume ATLAS LABELS_LIST
Atlas and labels list for edge-wise division.
--parcel_surface ATLAS LABELS_LIST
Atlas and labels list for edge-wise division.
Scaling options:
--max_at_one Scale matrix with maximum value at one.
--sum_to_one Scale matrix with sum of all elements at one.
--log_10 Apply a base 10 logarithm to the matrix.