<filename>src/pybel_tools/analysis/mechanisms.py
# -*- coding: utf-8 -*-

"""This module contains functions to compare generated sub-graphs to canonical sub-graphs."""

from typing import Any, Mapping

from pybel import BELGraph
from pybel.struct import get_subgraphs_by_annotation
from ..generation import generate_bioprocess_mechanisms
from ..utils import tanimoto_set_similarity

__all__ = [
    'compare',
]


def compare(graph: BELGraph, annotation: str = 'Subgraph') -> Mapping[str, Mapping[str, float]]:
    """Compare generated mechanisms to actual ones.

    1. Generates candidate mechanisms for each biological process
    2. Gets sub-graphs for all NeuroMMSig signatures
    3. Make tanimoto similarity comparison for all sets

    :return: A dictionary table comparing the canonical subgraphs to generated ones
    """
    canonical_mechanisms = get_subgraphs_by_annotation(graph, annotation)
    canonical_nodes = _transform_graph_dict_to_node_dict(canonical_mechanisms)

    candidate_mechanisms = generate_bioprocess_mechanisms(graph)
    candidate_nodes = _transform_graph_dict_to_node_dict(candidate_mechanisms)

    return {
        canonical_name: {
            candidate_bp: tanimoto_set_similarity(candidate_nodes, canonical_nodes)
            for candidate_bp, candidate_graph in candidate_nodes.items()
        }
        for canonical_name, canonical_graph in canonical_nodes.items()
    }


def _transform_graph_dict_to_node_dict(d: Mapping[Any, BELGraph]):
    return {
        key: set(graph)
        for key, graph in d.items()
    }

<filename>src/pybel_tools/analysis/mechanisms.py
# -*- coding: utf-8 -*-

"""This module contains functions to compare generated sub-graphs to canonical sub-graphs."""

from typing import Any, Mapping

from pybel import BELGraph
from pybel.struct import get_subgraphs_by_annotation
from ..generation import generate_bioprocess_mechanisms
from ..utils import tanimoto_set_similarity

__all__ = [
    'compare',
]


def compare(graph: BELGraph, annotation: str = 'Subgraph') -> Mapping[str, Mapping[str, float]]:
    """Compare generated mechanisms to actual ones.

    1. Generates candidate mechanisms for each biological process
    2. Gets sub-graphs for all NeuroMMSig signatures
    3. Make tanimoto similarity comparison for all sets

    :return: A dictionary table comparing the canonical subgraphs to generated ones
    """
    canonical_mechanisms = get_subgraphs_by_annotation(graph, annotation)
    canonical_nodes = _transform_graph_dict_to_node_dict(canonical_mechanisms)

    candidate_mechanisms = generate_bioprocess_mechanisms(graph)
    candidate_nodes = _transform_graph_dict_to_node_dict(candidate_mechanisms)

    return {
        canonical_name: {
            candidate_bp: tanimoto_set_similarity(candidate_nodes, canonical_nodes)
            for candidate_bp, candidate_graph in candidate_nodes.items()
        }
        for canonical_name, canonical_graph in canonical_nodes.items()
    }


def _transform_graph_dict_to_node_dict(d: Mapping[Any, BELGraph]):
    return {
        key: set(graph)
        for key, graph in d.items()
    }

# -*- coding: utf-8 -*- This module contains functions to compare generated sub-graphs to canonical sub-graphs. Compare generated mechanisms to actual ones.      1. Generates candidate mechanisms for each biological process     2. Gets sub-graphs for all NeuroMMSig signatures     3. Make tanimoto similarity comparison for all sets      :return: A dictionary table comparing the canonical subgraphs to generated ones