Documentation

Help on module mp3treesim:

NOTE

This is a documentation of the exposed FUNCTIONS only.

FUNCTIONS

Create tree structure from DOT file

read_dotfile(path, labeled_only=False, exclude=None)
    Reads a dot file and returns its MP3-treesim tree representation.

    NOTE: the tree should have an attribute `label` for each node. 
    In case this is not true, the label of the node will be it's ID.    
    It recommended to use the `label` attribute.
    Labels in a node must be separated by a comma.

    Parameters: 
    path (str): Path to the dot file
    labeled_only (bool): If true nodes without attribute `label` will be ignored, meaning that T is a partially labeled tree.
    exclude (list(str)): List of labels to exclude from computation

    Returns: 
    Tree: MP3-treesim tree representation

Create tree structure from DOT string

read_dotstring(string, labeled_only=False, exclude=None)
    Reads a string containing a dot graph and returns its MP3-treesim tree representation.

    NOTE: the tree should have an attribute `label` for each node. 
    In case this is not true, the label of the node will be it's ID.    
    It recommended to use the `label` attribute.
    Labels in a node must be separated by a comma.

    Parameters: 
    string (str): dot representation of the tree
    labeled_only (bool): If true nodes without attribute `label` will be ignored, meaning that T is a partially labeled tree.
    exclude (list(str)): List of labels to exclude from computation

    Returns: 
    Tree: MP3-treesim tree representation

Build tree from networkx AGraph

build_tree(T, labeled_only=False, exclude=None)
    Builds the MP3-treesim tree representation from a networkx representation.

    NOTE: the tree must have a attribute `label` for each node. Labels in a node
    must be separated by a comma.

    Parameters:
    T (nx.nx_agraph): Tree in networkx representation
    labeled_only (bool): If true nodes without attribute `label` 
    will be ignored, meaning that T is a partially labeled tree.
    exclude (list(str)): List of labels to exclude from computation

    Returns:
    Tree: MP3-treesim tree representation

Draw trees

draw_tree(tree):
    Draw the tree using networkx's drawing methods.

    NOTE 1: Networkx uses matplotlib to display the tree. If you are using a Notebook-like
    environment (Jupyter, CoLab) it will be display automatically. 
    If you are using it from command line it will be necessary to run `plt.show()` to 
    display it.

    NOTE 2: Due to an unreliable behaviour of netxwork and pygraph it is necessary to
    create a copy of the input tree and loop over the nodes twice. Beware this in case
    you want to display very large trees.

    Parameters: 
    tree: MP3-treesim tree representation

Computation of similarity

similarity(tree1, tree2, mode='sigmoid', cores=1)
    Compute the similarity score of the two trees.
    
    Parameters: 
    tree1 (Tree): MP3-treesim tree representation
    tree2 (Tree): MP3-treesim tree representation
    
    Keyword arguments:
    mode (str): 'sigmoid', 'intersection', 'union'
                or 'geometric',
                sets the similarity calculation.
                By default is set to 'sigmoid'.
    sigmoid_mult (float): Multiplicator for the 
                    sigmoid calculation.
    cores (int); Number of cores used for the computation.
    
    Returns: 
    float: Similarity score