# This file is part of project Sverchok. It's copyrighted by the contributors
# recorded in the version control history of the file, available from
# its original location https://github.com/nortikin/sverchok/commit/master
#
# SPDX-License-Identifier: GPL3
# License-Filename: LICENSE


from collections import namedtuple
from itertools import chain, cycle
import numpy as np

import bpy

from sverchok.node_tree import SverchCustomTreeNode
from sverchok.data_structure import updateNode, numpy_list_match_modes, iter_list_match_func


SplitModes = namedtuple('SplitModes', ['cuts', 'steps'])
SPLIT_MODE = SplitModes('Cuts', 'Steps')


def split_by_cuts(verts_a, verts_b, cuts, list_match_mode='REPEAT'):
    """
    Generate lines between two given points
    :param verts_a: list of tuple(float, float, float)
    :param verts_b: list of tuple(float, float, float)
    :param cuts: list of int
    :return: numpy array with shape (number of vertices, 3), list of tuple(int, int)
    """
    line_number = max(len(cuts), len(verts_a), len(verts_b))
    list_match_f = iter_list_match_func[list_match_mode]
    params = list_match_f([cuts, verts_a, verts_b])
    verts_number = sum([cuts + 2 if cuts >= 0 else 2 for _, cuts in
                        zip(range(line_number), params[0])])


    verts_lines = np.empty((verts_number, 3))
    edges_lines = []
    num_added_verts = 0
    indexes = iter(range(int(1e+100)))

    for i, c, va, vb in zip(range(line_number), *params):
        va, vb = np.array(va), np.array(vb)
        verts_line = generate_verts(va, vb, c)
        edges_lines.extend([(i, i + 1) for i, _ in zip(indexes, verts_line[:-1])])
        verts_lines[num_added_verts: num_added_verts + len(verts_line)] = verts_line
        num_added_verts += len(verts_line)

    return verts_lines, edges_lines


def split_by_steps(verts_a, verts_b, steps=None, list_match_mode='REPEAT'):
    """
    Generate one line between given points, steps subdivide line proportionally
    Multiple lines can be generated
    :param steps: list of values, each step is nest segment of a same line
    :param verts_a: list of tuple(float, float, float)
    :param verts_b: list of tuple(float, float, float)
    :return: numpy array with shape(number of vertices, 3), list of tuple(int, int)
    """
    if steps is None:
        steps = [1]
    steps = [0] + steps
    line_number = max([len(verts_a), len(verts_b)])
    vert_number = line_number * len(steps)
    verts_lines = np.empty((vert_number, 3))
    edges_lines = []
    num_added_verts = 0
    indexes = iter(range(int(1e+100)))
    list_match_f = iter_list_match_func[list_match_mode]
    params = list_match_f([verts_a, verts_b])
    for i_line, va, vb in zip(range(line_number), *params):
        va, vb = np.array(va), np.array(vb)
        size = np.linalg.norm(vb - va)
        norm_factor = sum(steps) / size
        sts = [st / norm_factor for st in steps]
        accum_steps = np.add.accumulate(sts)
        norm_direction = (vb - va) / size
        line_verts = np.full((len(sts), 3), norm_direction)
        line_verts = line_verts * accum_steps.reshape((len(sts), 1))
        line_verts = line_verts + va

        edges_lines.extend([(i, i + 1) for i, _ in zip(indexes, range(len(line_verts) - 1))])
        verts_lines[num_added_verts: num_added_verts + len(line_verts)] = line_verts
        num_added_verts += len(line_verts)
    return verts_lines, edges_lines


def generate_verts(va, vb, cuts):
    # interpolate vertices between two given
    if cuts <= 0:
        return np.array((va, vb))
    x = np.linspace(va[0], vb[0], cuts + 2)
    y = np.linspace(va[1], vb[1], cuts + 2)
    z = np.linspace(va[2], vb[2], cuts + 2)
    return np.stack((x, y, z), axis=-1)


def split_lines_to_objects(verts, edges):
    """
    detect lines and split them into separate objects
    vertices and edges should be ordered according generator lines logic
    :param verts: numpy array with shape(n, 3)
    :param edges: list of tuple(int, int)
    :return: list of np arrays, list of list of tuple(int, int)
    """
    split_slice = [0]
    for i in range(len(edges)):
        split_slice[-1] += 1
        # current edge - (0, 1), next edge - (1, 2) - still on the same line
        # current edge - (1, 2), next edge - (3, 4) - the current line is finished
        is_end = True if i + 1 >= len(edges) else True if edges[i][1] != edges[i + 1][0] else False
        if is_end:
            split_slice[-1] += 1
            if i != len(edges) - 1:
                split_slice.append(split_slice[-1])
    edges_out = [[(i, i + 1) for i in range(len(v_num) - 1)]
                 for v_num in np.split(np.empty(len(verts)), split_slice)[:-1]]
    return np.split(verts, split_slice)[:-1], edges_out


def iter_last(l):
    return chain(l, cycle([l[-1]]))


class SvSegmentGenerator(bpy.types.Node, SverchCustomTreeNode):
    """
    Triggers: 2pt Line

    Can subdivide output edge
    Vertices can be as numpy array
    """
    bl_idname = 'SvSegmentGenerator'
    bl_label = 'Segment'
    bl_icon = 'GRIP'
    sv_icon = 'SV_LINE'

    def update_node(self, context):
        if self.split_mode == SPLIT_MODE.cuts:
            self.inputs['Cuts'].hide_safe = False
            self.inputs['Steps'].hide_safe = True
        elif self.split_mode == SPLIT_MODE.steps:
            self.inputs['Cuts'].hide_safe = True
            self.inputs['Steps'].hide_safe = False
        updateNode(self, context)

    split_mode: bpy.props.EnumProperty(items=[(n, n, '') for n in SPLIT_MODE], update=update_node)
    a: bpy.props.FloatVectorProperty(name='A', update=updateNode)
    b: bpy.props.FloatVectorProperty(name='B', default=(0.5, 0.5, 0.5), update=updateNode)
    cuts_number: bpy.props.IntProperty(name='Num cuts', min=0, update=updateNode)
    as_numpy: bpy.props.BoolProperty(name="Numpy output", description="Format of output data", update=updateNode)
    split: bpy.props.BoolProperty(name="Split to objects", description="Each object in separate object",
                                   update=updateNode, default=True)
    list_match_global: bpy.props.EnumProperty(
        name="List Match Gobal",
        description="Behavior on different list lengths, multiple objects level",
        items=numpy_list_match_modes, default="REPEAT",
        update=updateNode)
    list_match_local: bpy.props.EnumProperty(
        name="List Match Local",
        description="Behavior on different list lengths, object level",
        items=numpy_list_match_modes, default="REPEAT",
        update=updateNode)

    def draw_buttons(self, context, layout):
        layout.prop(self, 'split_mode', expand=True)

    def draw_buttons_ext(self, context, layout):
        list_match = layout.box()
        list_match.label(text='List Match:')
        list_match.prop(self, "list_match_global", text='Global')
        list_match.prop(self, "list_match_local", text='Local')
        layout.prop(self, 'as_numpy')
        layout.prop(self, 'split')

    def rclick_menu(self, context, layout):
        layout.prop_menu_enum(self, "list_match_global")
        layout.prop_menu_enum(self, "list_match_local")
        layout.prop(self, 'split')
        layout.prop(self, 'as_numpy')

    def sv_init(self, context):
        self.inputs.new('SvVerticesSocket', 'A').prop_name = 'a'
        self.inputs.new('SvVerticesSocket', 'B').prop_name = 'b'
        self.inputs.new('SvStringsSocket', 'Cuts').prop_name = 'cuts_number'
        self.inputs.new('SvStringsSocket', 'Steps').hide = True
        self.outputs.new('SvVerticesSocket', 'Verts')
        self.outputs.new('SvStringsSocket', 'Edges')

    def process(self):
        num_objects = max([len(sock.sv_get(deepcopy=False, default=[])) for sock in self.inputs])
        out = []
        list_match_f = iter_list_match_func[self.list_match_global]
        params = list_match_f([sock.sv_get(deepcopy=False, default=[[None]]) for sock in self.inputs])
        for i, a, b, c, st in zip(range(num_objects), *params):
            if self.split_mode == SPLIT_MODE.cuts:
                out.append(split_by_cuts(a, b, c, self.list_match_local))
            elif self.split_mode == SPLIT_MODE.steps:
                out.append(split_by_steps(a, b, st, self.list_match_local))
        if self.split:
            temp = [split_lines_to_objects(*data) for data in out]
            out = [v for res in temp for v in zip(*res)]
        if not self.as_numpy:
            out = [(ar.tolist(), edges) for ar, edges in out]
        [sock.sv_set(data) for sock, data in zip(self.outputs, zip(*out))]


def register():
    bpy.utils.register_class(SvSegmentGenerator)


def unregister():
    bpy.utils.unregister_class(SvSegmentGenerator)
