# Copyright 2016-2020 The <NAME> at the California Institute of
# Technology (Caltech), with support from the Paul Allen Family Foundation,
# Google, & National Institutes of Health (NIH) under Grant U24CA224309-01.
# All rights reserved.
#
# Licensed under a modified Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.github.com/vanvalenlab/deepcell-datasets/LICENSE
#
# The Work provided may be used for non-commercial academic purposes only.
# For any other use of the Work, including commercial use, please contact:
# <EMAIL>
#
# Neither the name of Caltech nor the names of its contributors may be used
# to endorse or promote products derived from this software without specific
# prior written permission.
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Initialization Script for DeepCell Datasets Database"""

# This script should run when the Database is first brought online.
# It should traverse a given directory, locate metadata files, and import
# the information it finds into the relevant collection.

import os
import json
import fnmatch

from pathlib import Path
import numpy as np

from skimage.external import tifffile as tiff

import pandas as pd


def sorted_nicely(l):
    convert = lambda text: int(text) if text.isdigit() else text
    alphanum_key = lambda key: [convert(c) for c in re.split('([0-9]+)', key)]
    return sorted(l, key=alphanum_key)


def _datasets_available(self):
        # This function should be part of a different system and constantly maintained
        # This is a placeholder for a database that tells us what data is available
        for (cur_dir, sub_dirs, files) in os.walk(self.base_path):
            if not sub_dirs and not files:
                print(cur_dir)
                print('empty directory')
                print('--------------------------------')
            if not sub_dirs and len(files) == 2:
                print(cur_dir)
                print('only 1 file')
                print('--------------------------------')


def csv_loader():
    """Load Greenwald et al multiplex data using pandas and provided xlsx


    """
