import argparse

import numpy as np

import nibabel as nib

from skimage.transform import resize as skires

import csv

import yaml

import numpy as np

def str2bool(v):

    if v.lower() in ['true', 1]:

        return True

    elif v.lower() in ['false', 0]:

        return False

    else:

        raise argparse.ArgumentTypeError('Boolean value expected.')

class DotDict:

    def __init__(self, dictionary):

        self._dict = dictionary

    def __getattr__(self, attr):

        value = self._dict[attr]

        if isinstance(value, dict):

            return DotDict(value)

        return value

def parse_args():

    parser = argparse.ArgumentParser()

    parser.add_argument('--network', default=None, help='architecture name')

    parser.add_argument('--name', default=None, help='model name')

    parser = parser.parse_args()

    with open(f'outputs/{parser.network}/{parser.name}/config.yml', 'r') as f:

        config = yaml.load(f, Loader=yaml.FullLoader)

    config = DotDict(config)

    return config

def save_vol(vol, type, path):

    vol = np.transpose(vol, (2, 1, 0))

    affine = np.eye(4)

    nifti_file = nib.Nifti1Image(vol.astype(np.int8), affine) if type=='labels' else nib.Nifti1Image(vol, affine)

    nib.save(nifti_file, path)    

def resize_vol(vol, new_size):

    return skires(vol, new_size, order=1, preserve_range=True, anti_aliasing=False)

def write_csv(path, data):

    with open(path, mode='a', newline='') as file:

        iteration = csv.writer(file)

        iteration.writerow(data)

    file.close()