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
