from lib.skn_anm import *
from lib.gbs import *
import struct
import os
import shutil


def read_skn(filepath) -> AnmSkin:
    with open(filepath, "rb") as fp:
        init_filetrack(os.fstat(fp.fileno()).st_size)
        r = AnmFile.parse(fp, AnmSkin)
        print("Read %s%% of file" % stat_track())
        return r


def test():
    f = ["/home/tasty/Projects/gck-map-extract-objects/anm_skn/Verm_l0.skn"]
    my_vertex = Vec3(-0.927200, 0.099500, 3.108000)
    mini_dist_v = Vec3(0, 0, 0)
    for p in f:
        skn = read_skn(p)
        pprint(skn.default_obj_dictionnary)
        pprint(skn.node_dictionnary)
        for obj_name, obj in skn.default_obj_dictionnary.items():
            for cluster in obj.clusters:
                for vertex in cluster.vertices:
                    if vertex.distance(my_vertex) < mini_dist_v.distance(my_vertex):
                        mini_dist_v = vertex

    print("%s: dist=%s" % (mini_dist_v, mini_dist_v.distance(my_vertex)))


def print_vertices(file):
    skn = read_skn(file)
    pprint(skn)
    for obj_name in skn.default_obj_dictionnary:
        obj = skn.default_obj_dictionnary[obj_name]
        for cluster in obj.clusters:
            for vertex in cluster.vertices:
                print("v %s %s %s" % (vertex.x, vertex.y, vertex.z))


def link_gbs_skn():
    basepath = "/home/tasty/Projects/gck-map-extract-objects/test/rp_l0.apatch.gzp"
    skn = read_skn(basepath+".skn")
    gbs = GbsData()
    gbs.read(basepath+".gbs")

    vbase = 0
    with open("test.obj", "w") as fp:
        for obj_name, obj in skn.default_obj_dictionnary.items():
            for cluster in obj.clusters:
                for vertex in cluster.vertices:
                    base_vertex_i = vertex.index + vbase
                    base_vertex = gbs.vertices[base_vertex_i]
                    new_vertex = Vec3(base_vertex.x + vertex.x, base_vertex.y + vertex.y, base_vertex.z + vertex.z)
                    fp.write("v %s %s %s\n" % (new_vertex.x, new_vertex.y, new_vertex.z))
            vbase += obj.total_number_vertices


def main(file):
    skn = read_skn(file)
    pprint(skn)
    vbase = 0
    for tree in skn.tree_dictionnary:
        for obj_name in skn.tree_dictionnary[tree]:
            obj = skn.tree_dictionnary[tree][obj_name]
            for cluster in obj.clusters:
                if cluster.num_vertices <= 0:
                    print("NO VERTICES")
                for vertex in cluster.vertices:
                    pass
                    # print("vertex %s -> %s" % (vertex.index, vertex.index + vbase))
            vbase += obj.total_number_vertices

    with open("test.obj", "w") as fp:
        vbase = 0
        for obj_name, obj in skn.default_obj_dictionnary.items():
            for cluster in obj.clusters:
                ## 81: part of hair
                ## 12: left eye
                ## 9/13: leg or arm
                ## 15/17 is a boob
                if cluster.handle == 15:
                    # fp.write("name %s %s %s %s %s %s %s\n" % (cluster.bone_name.strip().replace(" ", ""), cluster.bounding_box[0].x, cluster.bounding_box[0].y, cluster.bounding_box[0].z, cluster.bounding_box[1].x, cluster.bounding_box[1].y, cluster.bounding_box[1].z))
                    for vertex in cluster.vertices:
                        # fp.write("index %s\n" % (vertex.index + vbase))
                        fp.write("%s %s %s 0 0 0\n" % (vertex.x, vertex.y, vertex.z))
            vbase += obj.total_number_vertices


def replace_vertex(x1, y1, z1, x2, y2, z2, skn_file):
    final = skn_file+".repl"
    if not os.path.exists(final):
        shutil.copy(skn_file, final)

    with open(final, "rb") as fp:
        fp.seek(0)
        bytesarr = bytearray(fp.read())

    bfind = x1+y1+z1
    brepl = x2+y2+z2
    bytesarr_new = bytesarr.replace(bfind, brepl)
    assert(bytesarr_new != bytesarr)
    with open(final, "ab+") as fp:
        fp.seek(0)
        fp.write(bytesarr_new)


def replace_vertices(file_input, skn_file):
    with open(skn_file, "rb") as fp:
        orig_bytes = bytearray(fp.read())

    with open(file_input, "r") as fp:
        lines = fp.readlines()
        to_search = []
        for line in lines:
            line = line.strip()
            if not line or line.startswith("#"):
                continue
            a = line.split(" ")
            print(line)
            assert(len(a) == 6)
            x1 = struct.pack("<f", float(a[0]))
            y1 = struct.pack("<f", float(a[1]))
            z1 = struct.pack("<f", float(a[2]))

            if (x1, y1, z1) in to_search:
                continue
            else:
                to_search.append((x1, y1, z1,))

            x2 = struct.pack("<f", float(a[3]))
            y2 = struct.pack("<f", float(a[4]))
            z2 = struct.pack("<f", float(a[5]))

            bfind = x1 + y1 + z1
            brepl = x2 + y2 + z2
            new_bytes = orig_bytes.replace(bfind, brepl)
            assert(new_bytes != orig_bytes)
            orig_bytes = new_bytes

    final = skn_file+".repl"
    if not os.path.exists(final):
        shutil.copy(skn_file, final)

    with open(final, "wb") as fp:
        print("writing final file %s..." % final)
        fp.write(orig_bytes)


def combine_files(input, newfile):
    with open(input, "r") as in_fp:
        in_lines = in_fp.readlines()

    with open(newfile, "r") as out_fp:
        out_lines = out_fp.readlines()

    assert(len(in_lines) == len(out_lines))

    for i in range(len(in_lines)):
        out_lines[i] = out_lines[i].replace("\n", "") + " " + in_lines[i]

    with open(newfile+".combined", "w") as o_fp:
        o_fp.writelines(out_lines)


if __name__ == "__main__":
    file = "/home/tasty/Projects/gck-map-extract-objects/test/MC_shotgun_L0.xx_mecc_flick.gzp.skn"
    s = read_skn(file)
    pprint(s)