# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the 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.apache.org/licenses/LICENSE-2.0
#
# 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.

"""P and S phase arrivals dataset for Alaska"""

import h5py
import csv
import os
import logging

import datasets

# Set up logging for debugging download issues
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)


_CITATION = """\
@InProceedings{huggingface:dataset,
title = {A great new dataset},
author={huggingface, Inc.
},
year={2020}
}
"""

_ManualPick_DESCRIPTION = """\
This dataset includes P and S phases from AACSE catalog recorded by the broadband stations in the Alaska Peninsula
"""

_ManualPick_ai4eps_DESCRIPTION = """\
This dataset includes P and S phases from AACSE catalog recorded by the broadband stations in the Alaska Peninsula in ai4eps format
"""

_PNTFIter1_DESCRIPTION = """
This dataset includes P and S phases predicted by the PhaseNet-TF using model trained by the manualpick dataset
"""

_PNTFIter1Combined_DESCRIPTION = """
This dataset includes all P and S phases from PNTFiter1 dataset and all false negative arrivals of ManualPick dataset
"""

_Base_URL = "https://huggingface.co/datasets/Aaaapril/PS_Alaska/resolve/main"
def get_data_url(dataset, n):
    return {
        "catalogs": f"{_Base_URL}/{dataset}/catalogs.csv",
        "phases": f"{_Base_URL}/{dataset}/phase_picks.csv",
        "waveform": f"{_Base_URL}/{dataset}/waveform.h5",
        "stations": f"{_Base_URL}/stations.json",
        "waveforms": [
            f"{_Base_URL}/{dataset}/waveform/{x:05d}-of-{n:05d}.zip" for x in range(n)
        ]
    }


class PSAlaskaConfig(datasets.BuilderConfig):

    def __init__(self, description, data_url, citation, **kwargs):
        """BuilderConfig for PS_Alaska.
        Args:
          features: `list[string]`, list of the features that will appear in the
            feature dict. Should not include "label".
          data_url: `string`, url to download the zip file from.
          citation: `string`, citation for the data set.
          data_url: `string`, url for information about the data set.
          label_classes: `list[string]`, the list of classes for the label if the
            label is present as a string. Non-string labels will be cast to either
            'False' or 'True'.
          **kwargs: keyword arguments forwarded to super.
        """
        super(PSAlaskaConfig, self).__init__(
            version = datasets.Version("1.0.0"),
            **kwargs)
        self.description = description
        self.data_url = data_url
        self.citation = citation


class PSAlaskaDataset(datasets.GeneratorBasedBuilder):
    """P and S phase arrivals dataset for Alaska"""

    VERSION = datasets.Version("1.0.0")

    BUILDER_CONFIGS = [
        PSAlaskaConfig(
            name="ManualPick",
            description=_ManualPick_DESCRIPTION,
            data_url=get_data_url("ManualPick", 4),
            citation=_CITATION,
        ),
        PSAlaskaConfig(
            name="ManualPick_ai4eps",
            description=_ManualPick_ai4eps_DESCRIPTION,
            data_url=get_data_url("ManualPick_ai4eps", 4),
            citation=_CITATION,
        ),
        PSAlaskaConfig(
            name="PNTFIter1",
            description=_PNTFIter1_DESCRIPTION,
            data_url=get_data_url("PNTFIter1", 19),
            citation=_CITATION,
        ),
        PSAlaskaConfig(
            name="PNTFIter1_combined",
            description=_PNTFIter1Combined_DESCRIPTION,
            data_url=get_data_url("PNTFIter1_combined", 20),
            citation=_CITATION,
        ),
    ]

    DEFAULT_CONFIG_NAME = "PNTFIter1_combined"
    

    def _info(self):

        return datasets.DatasetInfo(
            description=self.config.description,
            features=datasets.Features(
                {
                    "begin_time": datasets.Value("string"),
                    "end_time": datasets.Value("string"),
                    "component": datasets.Sequence(datasets.Value('string')),
                    "dt_s": datasets.Value("float"),
                    "event_id": datasets.Value("string"),
                    "station": datasets.Value("string"),
                    "network": datasets.Value("string"),
                    "phase_index": datasets.Sequence(datasets.Value('int32')),
                    "phase_time": datasets.Sequence(datasets.Value('string')),
                    "phase_type": datasets.Sequence(datasets.Value('string')),
                    "waveform": datasets.Array2D(shape=(3, 24000), dtype='float32'),
                }
            ),
            supervised_keys=("waveform", "phase_type"),
            citation=self.config.citation,
        )


    def _split_generators(self, dl_manager):

        urls = self.config.data_url
        data_dir = dl_manager.download_and_extract(urls)
        handler = h5py.File(data_dir['waveform'], 'r')

        return [
            datasets.SplitGenerator(
                name="full",
                gen_kwargs={
                    "handler": handler
                },
            ),
        ]


    def _generate_examples(self, handler):
        for e in handler.keys():
            for sta in handler[e].keys():
                key = f'{e}_{sta}'
                meta = handler[e][sta].attrs
                yield key, {
                    "begin_time": meta['begin_time'],
                    "end_time": meta['end_time'],
                    "component": meta['component'],
                    "dt_s": meta['dt_s'],
                    "event_id": meta['event_id'],
                    "station": meta['station'],
                    "network": meta['network'],
                    "phase_index": meta['phase_index'],
                    "phase_time": meta['phase_time'],
                    "phase_type": meta['phase_type'],
                    "waveform": handler[e][sta]
                }
            handler.close()