#!/usr/bin/env python

import gudhi
import argparse
import math
import errno
import os
import numpy as np

""" This file is part of the Gudhi Library - https://gudhi.inria.fr/ -
    which is released under MIT.
    See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full
    license details.
    Author(s):       Vincent Rouvreau

    Copyright (C) 2016 Inria

    Modification(s):
      - YYYY/MM Author: Description of the modification
"""

__author__ = "Vincent Rouvreau"
__copyright__ = "Copyright (C) 2016 Inria"
__license__ = "MIT"

parser = argparse.ArgumentParser(
    description="AlphaComplex and RipsComplex "
    "persistence creation from points read in "
    "a OFF file. Bottleneck distance computation"
    " on each dimension",
    epilog="Example: "
    "example/alpha_rips_persistence_bottleneck_distance.py "
    "-f ../data/points/tore3D_1307.off -t 0.15 -d 3",
)
parser.add_argument("-f", "--file", type=str, required=True)
parser.add_argument("-t", "--threshold", type=float, default=0.5)
parser.add_argument("-d", "--max_dimension", type=int, default=1)

args = parser.parse_args()
with open(args.file, "r") as f:
    first_line = f.readline()
    if (first_line == "OFF\n") or (first_line == "nOFF\n"):
        point_cloud = gudhi.read_points_from_off_file(off_file=args.file)
        print("##############################################################")
        print("RipsComplex creation from points read in a OFF file")

        message = "RipsComplex with max_edge_length=" + repr(args.threshold)
        print(message)

        rips_complex = gudhi.RipsComplex(
            points=point_cloud, max_edge_length=args.threshold
        )

        rips_stree = rips_complex.create_simplex_tree(
            max_dimension=args.max_dimension)

        message = "Number of simplices=" + repr(rips_stree.num_simplices())
        print(message)

        rips_stree.compute_persistence()

        print("##############################################################")
        print("AlphaComplex creation from points read in a OFF file")

        message = "AlphaComplex with max_edge_length=" + repr(args.threshold)
        print(message)

        alpha_complex = gudhi.AlphaComplex(points=point_cloud)
        alpha_stree = alpha_complex.create_simplex_tree(
            max_alpha_square=(args.threshold * args.threshold)
        )

        message = "Number of simplices=" + repr(alpha_stree.num_simplices())
        print(message)

        alpha_stree.compute_persistence()

        max_b_distance = 0.0
        for dim in range(args.max_dimension):
            # Alpha persistence values needs to be transform because filtration
            # values are alpha square values
            alpha_intervals = np.sqrt(alpha_stree.persistence_intervals_in_dimension(dim))

            rips_intervals = rips_stree.persistence_intervals_in_dimension(dim)
            bottleneck_distance = gudhi.bottleneck_distance(
                rips_intervals, alpha_intervals
            )
            message = (
                "In dimension "
                + repr(dim)
                + ", bottleneck distance = "
                + repr(bottleneck_distance)
            )
            print(message)
            max_b_distance = max(bottleneck_distance, max_b_distance)

        print("==============================================================")
        message = "Bottleneck distance is " + repr(max_b_distance)
        print(message)

    else:
        raise FileNotFoundError(errno.ENOENT, os.strerror(errno.ENOENT),
                                args.file)


    f.close()
