Graphs - graph.py
This page documents MatSimPy functions that create and modify NetworkX graphs.
init_graph_from_atm
- def init_graph_from_atm(atm)
- Initializes an unconnected, undirected graph from a provided ASE atoms object.
Parameters:
- atm (ASE atoms object): The input molecule.
Returns:
- g (nx graph object): An unconnected graph made up of the atoms in our molecule, with attributes for the number and symbol of the element for each node.
c_subgraph_finder
Adapted from web resource. 1
- def c_subgraph_finder(graf)
- Takes a graph and returns every connected subgraph it has. Adapted from resource in footnote.
Parameters:
- graf (nx graph object): The input graph.
Returns:
- subgraphs (dict): A dictionary object, containing the connected subgraphs of graf, organized by size.
graph_visual
- def graph_visual(graf, cdict, label_string = "Type", printout = False, font = [22, "black"])
- Produces a labelled matplotlib visualization of a nx graph object.
Parameters:
- graf (nx graph): An input graph, with labelled nodes.
- cdict (ditc): A dict object containing int-colour combinations for each label type (i.e. {1 : “Red”, 2: “Blue”}).
- label_string (str): A str object used to pick the visualized label type, default is “Type”.
- printout (bool): A bool object that determines if the colour-coding is printed to the user, default is False.
- font (list): A list that contains the font size (int) and the font colour (str) of the user’s choice, default is [22, “black”].
Returns:
- None
gdegree
- def gdegree(graf)
- Obtains an array counting degrees of nodes present in a graph. Similar but distinct from the G.degree already present in the nx package.
Parameters:
- graf (nx graph): Input graph.
Returns:
- g_count (np array): An array indicating the number of nodes with i edges in graf, where i is the index of g_count.
state_stacker
- def state_stacker(state_array, num_class, readout = True)
- Produces arrays that contain information on uniqueness of state compositions for regions of interest with distinct class numbers present.
Parameters:
- state_array (array): A numpy array that acts as a dataset of ROI data containing types/classifications.
- num_class (int): The number of different classes in the data that we are being asked to sort.
- readout (bool): Determines if the user is shown a readout of the stacked states.
Returns:
- unique_states (array): The unique states present in the input data.
- unique_counts (array): Counts for unique states.
- unique_firsts (array): Indices for first instances of unique states.
- unique_inverse (array): The mapping needed to recreate the input data.