# -*- coding: utf-8 -*-
# Copyright (c) Vispy Development Team. All Rights Reserved.
# Distributed under the (new) BSD License. See LICENSE.txt for more info.
"""
Graph utilities
===============

A module containing several graph utility functions.
"""

import numpy as np

def issparse(obj):
    try:
        from scipy.sparse import issparse as _issparse
        return _issparse(obj)
    except ModuleNotFoundError:
        return False


def _get_edges(adjacency_mat):
    func = _sparse_get_edges if issparse(adjacency_mat) else _ndarray_get_edges
    return func(adjacency_mat)


def _sparse_get_edges(adjacency_mat):
    return np.concatenate((adjacency_mat.row[:, np.newaxis],
                           adjacency_mat.col[:, np.newaxis]), axis=-1)


def _ndarray_get_edges(adjacency_mat):
    # Get indices of all non zero values
    i, j = np.where(adjacency_mat)

    return np.concatenate((i[:, np.newaxis], j[:, np.newaxis]), axis=-1)


def _get_directed_edges(adjacency_mat):
    if issparse(adjacency_mat):
        from scipy import sparse
        triu = sparse.triu
        tril = sparse.tril
        func = _sparse_get_edges
    else:
        triu = np.triu
        tril = np.tril
        func = _ndarray_get_edges

    upper = triu(adjacency_mat)
    lower = tril(adjacency_mat)

    return np.concatenate((func(upper), func(lower)))


def _straight_line_vertices(adjacency_mat, node_coords, directed=False):
    """
    Generate the vertices for straight lines between nodes.

    If it is a directed graph, it also generates the vertices which can be
    passed to an :class:`ArrowVisual`.

    Parameters
    ----------
    adjacency_mat : array
        The adjacency matrix of the graph
    node_coords : array
        The current coordinates of all nodes in the graph
    directed : bool
        Wether the graph is directed. If this is true it will also generate
        the vertices for arrows which can be passed to :class:`ArrowVisual`.

    Returns
    -------
    vertices : tuple
        Returns a tuple containing containing (`line_vertices`,
        `arrow_vertices`)
    """
    if not issparse(adjacency_mat):
        adjacency_mat = np.asarray(adjacency_mat, float)

    if (adjacency_mat.ndim != 2 or adjacency_mat.shape[0] !=
            adjacency_mat.shape[1]):
        raise ValueError("Adjacency matrix should be square.")

    arrow_vertices = np.array([])

    edges = _get_edges(adjacency_mat)
    line_vertices = node_coords[edges.ravel()]

    if directed:
        arrows = np.array(list(_get_directed_edges(adjacency_mat)))
        arrow_vertices = node_coords[arrows.ravel()]
        arrow_vertices = arrow_vertices.reshape((len(arrow_vertices)//2, 4))

    return line_vertices, arrow_vertices


def _rescale_layout(pos, scale=1):
    """
    Normalize the given coordinate list to the range [0, `scale`].

    Parameters
    ----------
    pos : array
        Coordinate list
    scale : number
        The upperbound value for the coordinates range

    Returns
    -------
    pos : array
        The rescaled (normalized) coordinates in the range [0, `scale`].

    Notes
    -----
    Changes `pos` in place.
    """
    pos -= pos.min(axis=0)
    pos *= scale / pos.max()

    return pos
