#!/usr/bin/env python3
# coding=utf-8

from data.parser.to_mrp.abstract_parser import AbstractParser


class NodeCentricParser(AbstractParser):
    def parse(self, prediction):
        output = {}

        output["id"] = self.dataset.id_field.vocab.itos[prediction["id"].item()]
        output["nodes"] = self.create_nodes(prediction)
        output["nodes"] = self.create_anchors(prediction, output["nodes"], join_contiguous=True, at_least_one=True)
        output["edges"] = self.create_edges(prediction, output["nodes"])

        return output

    def create_edge(self, source, target, prediction, edges, nodes):
        edge = {"source": source, "target": target, "label": None}
        edges.append(edge)

    def create_edges(self, prediction, nodes):
        N = len(nodes)
        edge_prediction = prediction["edge presence"][:N, :N]

        targets = [i for i, node in enumerate(nodes) if node["label"] in ["Source", "Target"]]
        sources = [i for i, node in enumerate(nodes) if node["label"] not in ["Source", "Target"]]

        edges = []
        for target in targets:
            for source in sources:
                if edge_prediction[source, target] >= 0.5:
                    self.create_edge(source, target, prediction, edges, nodes)

        return edges