Graph Controllability
Graph Controllability Transformation
Class for extraction of controllability measures. Allows for extraction of controllability measures.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
mod_control |
int
|
Whether to calculate nodewise modal controllability (1) or not (0). |
1
|
ave_control |
int
|
Whether to calculate nodewise average controllability (1) or not (0). |
1
|
adjacency_axis |
int
|
position of the adjacency matrix, default being zero |
0
|
n_processes |
int
|
Number of processes to use for multiprocessing |
0
|
logs |
str
|
None
|
Extraction of Graph Controllability measures
Instead of using the controllability measures in a PHOTONAI pipeline, you are also able to extract the measures with PHOTONAI Graph and generate a CSV file for use with third party software.
from photonai_graph.Controllability.controllability_measures import ControllabilityMeasureTransform
transform = ControllabilityMeasureTransform()
transform.extract_measures(X_in, "./output.csv")
Extract controllability measures and write them to a csv file
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
X |
np.ndarray
|
Input numpy array to transform |
None
|
path |
str
|
Output path for generated CSV |
None
|
ids |
List[int]
|
List of ids for the graphs. If None the graphs are enumerated |
None
|
node_list |
List[str]
|
List of names for the nodes. If None the nodes of the graphs are enumerated and entitled by the calculated controllability measure |
None
|