usage: __main__.py [-h] [--conn_threshold CONN_THRESHOLD]
[--filtering_mask FILTERING_MASK] [--avg_node_wise]
[--append_json] [--indent INDENT] [--sort_keys]
[-v [{DEBUG,INFO,WARNING,ERROR}]] [-f]
in_conn_matrix out_json
Evaluate graph theory measures from functional connectivity matrices.
The functional connectivity matrix is assumed to come from fMRI bold
correlations (-1 to 1 values). Hence, the matrix is first
made strictly positive (absolute value) and thresholded above a certain
correlation value (default: 0.25) as recommended in the litterature.
The computed connectivity measures are: modularity, assortativity,
participation, clustering, nodal_strength, and rich_club.
This script evaluates the measures one subject at the time. To generate a
population dictionary (similarly to other scil_connectivity_* scripts), use
the --append_json option as well as using the same output filename.
>>> for i in hcp/*/; do scil_connectivity_functional_graph_measures
${i}/sc_prob.npy ${i}/len_prob.npy hcp_prob.json
--append_json --avg_node_wise; done
Some measures output one value per node, the default behavior is to list
them all. To obtain only the average use the --avg_node_wise option.
For more details about the measures, please refer to
- https://sites.google.com/site/bctnet/
- https://github.com/aestrivex/bctpy/wiki
This script is under the GNU GPLv3 license, for more detail please refer to
https://www.gnu.org/licenses/gpl-3.0.en.html
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Reference:
[1] Rubinov, Mikail, and Olaf Sporns. "Complex network measures of brain
connectivity: uses and interpretations." Neuroimage 52.3 (2010):
1059-1069.
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positional arguments:
in_conn_matrix Input fonctional connectivity matrix (.npy).
out_json Path of the output json.
options:
-h, --help show this help message and exit
--conn_threshold CONN_THRESHOLD
Threshold for the functional connectivity values. All values
lower or equal to will be set to zero. (default: 0.25)
--filtering_mask FILTERING_MASK
Binary filtering mask to apply before computing the measures.
--avg_node_wise Return a single value for node-wise measures.
--append_json If the file already exists, will append to the dictionary.
-v [{DEBUG,INFO,WARNING,ERROR}]
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.
Json options:
--indent INDENT Indent for json pretty print.
--sort_keys Sort keys in output json.
2.2.2