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"""QuakeFlow_SC: A dataset of earthquake waveforms organized by earthquake events and based on the HDF5 format.""" |
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from typing import Dict, List, Optional, Tuple, Union |
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import datasets |
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import fsspec |
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import h5py |
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import numpy as np |
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import torch |
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_CITATION = """\ |
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@InProceedings{huggingface:dataset, |
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title = {SCEDC dataset for QuakeFlow}, |
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author={Zhu et al.}, |
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year={2023} |
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} |
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""" |
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_DESCRIPTION = """\ |
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A dataset of earthquake waveforms organized by earthquake events and based on the HDF5 format. |
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""" |
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_HOMEPAGE = "" |
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_LICENSE = "" |
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_REPO = "https://huggingface.co/datasets/AI4EPS/quakeflow_nc/resolve/main/waveform_h5" |
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_FILES = [ |
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"1999.h5", |
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"2000.h5", |
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"2001.h5", |
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"2002.h5", |
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"2003.h5", |
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"2004.h5", |
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"2005.h5", |
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"2006.h5", |
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"2007.h5", |
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"2008.h5", |
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"2009.h5", |
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"2010.h5", |
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"2011.h5", |
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"2012.h5", |
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"2013.h5", |
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"2014.h5", |
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"2015.h5", |
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"2016.h5", |
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"2017.h5", |
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"2018.h5", |
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"2019_0.h5", |
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"2019_1.h5", |
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"2019_2.h5", |
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"2020_0.h5", |
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"2020_1.h5", |
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"2021.h5", |
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"2022.h5", |
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"2023.h5", |
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] |
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_URLS = { |
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"station": [f"{_REPO}/{x}" for x in _FILES], |
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"event": [f"{_REPO}/{x}" for x in _FILES], |
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"station_train": [f"{_REPO}/{x}" for x in _FILES[:-1]], |
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"event_train": [f"{_REPO}/{x}" for x in _FILES[:-1]], |
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"station_test": [f"{_REPO}/{x}" for x in _FILES[-1:]], |
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"event_test": [f"{_REPO}/{x}" for x in _FILES[-1:]], |
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} |
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class BatchBuilderConfig(datasets.BuilderConfig): |
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""" |
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yield a batch of event-based sample, so the number of sample stations can vary among batches |
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Batch Config for QuakeFlow_SC |
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""" |
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def __init__(self, **kwargs): |
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super().__init__(**kwargs) |
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class QuakeFlow_SC(datasets.GeneratorBasedBuilder): |
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"""QuakeFlow_SC: A dataset of earthquake waveforms organized by earthquake events and based on the HDF5 format.""" |
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VERSION = datasets.Version("1.1.0") |
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nt = 8192 |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig( |
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name="station", version=VERSION, description="yield station-based samples one by one of whole dataset" |
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), |
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datasets.BuilderConfig( |
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name="event", version=VERSION, description="yield event-based samples one by one of whole dataset" |
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), |
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datasets.BuilderConfig( |
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name="station_train", |
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version=VERSION, |
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description="yield station-based samples one by one of training dataset", |
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), |
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datasets.BuilderConfig( |
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name="event_train", version=VERSION, description="yield event-based samples one by one of training dataset" |
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), |
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datasets.BuilderConfig( |
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name="station_test", version=VERSION, description="yield station-based samples one by one of test dataset" |
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), |
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datasets.BuilderConfig( |
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name="event_test", version=VERSION, description="yield event-based samples one by one of test dataset" |
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), |
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] |
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DEFAULT_CONFIG_NAME = ( |
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"station_test" |
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) |
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def _info(self): |
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if ( |
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(self.config.name == "station") |
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or (self.config.name == "station_train") |
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or (self.config.name == "station_test") |
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): |
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features = datasets.Features( |
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{ |
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"data": datasets.Array2D(shape=(3, self.nt), dtype="float32"), |
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"phase_time": datasets.Sequence(datasets.Value("string")), |
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"phase_index": datasets.Sequence(datasets.Value("int32")), |
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"phase_type": datasets.Sequence(datasets.Value("string")), |
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"phase_polarity": datasets.Sequence(datasets.Value("string")), |
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"begin_time": datasets.Value("string"), |
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"end_time": datasets.Value("string"), |
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"event_time": datasets.Value("string"), |
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"event_time_index": datasets.Value("int32"), |
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"event_location": datasets.Sequence(datasets.Value("float32")), |
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"station_location": datasets.Sequence(datasets.Value("float32")), |
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}, |
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) |
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elif (self.config.name == "event") or (self.config.name == "event_train") or (self.config.name == "event_test"): |
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features = datasets.Features( |
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{ |
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"data": datasets.Array3D(shape=(None, 3, self.nt), dtype="float32"), |
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"phase_time": datasets.Sequence(datasets.Sequence(datasets.Value("string"))), |
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"phase_index": datasets.Sequence(datasets.Sequence(datasets.Value("int32"))), |
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"phase_type": datasets.Sequence(datasets.Sequence(datasets.Value("string"))), |
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"phase_polarity": datasets.Sequence(datasets.Sequence(datasets.Value("string"))), |
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"begin_time": datasets.Value("string"), |
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"end_time": datasets.Value("string"), |
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"event_time": datasets.Value("string"), |
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"event_time_index": datasets.Value("int32"), |
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"event_location": datasets.Sequence(datasets.Value("float32")), |
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"station_location": datasets.Sequence(datasets.Sequence(datasets.Value("float32"))), |
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}, |
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) |
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else: |
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raise ValueError(f"config.name = {self.config.name} is not in BUILDER_CONFIGS") |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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urls = _URLS[self.config.name] |
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files = ["waveform_h5/1999.h5", "waveform_h5/2000.h5"] |
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print(files) |
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if self.config.name == "station" or self.config.name == "event": |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"filepath": files[:-1], |
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"split": "train", |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={"filepath": files[-1:], "split": "test"}, |
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), |
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] |
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elif self.config.name == "station_train" or self.config.name == "event_train": |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"filepath": files, |
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"split": "train", |
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}, |
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), |
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] |
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elif self.config.name == "station_test" or self.config.name == "event_test": |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={"filepath": files, "split": "test"}, |
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), |
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] |
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else: |
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raise ValueError("config.name is not in BUILDER_CONFIGS") |
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def _generate_examples(self, filepath, split): |
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for file in filepath: |
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with fsspec.open(file, "rb") as fs: |
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with h5py.File(fs, "r") as fp: |
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event_ids = list(fp.keys()) |
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for event_id in event_ids: |
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event = fp[event_id] |
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event_attrs = event.attrs |
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begin_time = event_attrs["begin_time"] |
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end_time = event_attrs["end_time"] |
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event_location = [ |
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event_attrs["longitude"], |
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event_attrs["latitude"], |
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event_attrs["depth_km"], |
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] |
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event_time = event_attrs["event_time"] |
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event_time_index = event_attrs["event_time_index"] |
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station_ids = list(event.keys()) |
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if len(station_ids) == 0: |
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continue |
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if ( |
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(self.config.name == "station") |
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or (self.config.name == "station_train") |
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or (self.config.name == "station_test") |
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): |
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waveforms = np.zeros([3, self.nt], dtype="float32") |
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for i, sta_id in enumerate(station_ids): |
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waveforms[:, : self.nt] = event[sta_id][:, : self.nt] |
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attrs = event[sta_id].attrs |
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phase_type = attrs["phase_type"] |
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phase_time = attrs["phase_time"] |
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phase_index = attrs["phase_index"] |
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phase_polarity = attrs["phase_polarity"] |
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station_location = [attrs["longitude"], attrs["latitude"], -attrs["elevation_m"] / 1e3] |
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yield f"{event_id}/{sta_id}", { |
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"data": waveforms, |
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"phase_time": phase_time, |
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"phase_index": phase_index, |
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"phase_type": phase_type, |
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"phase_polarity": phase_polarity, |
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"begin_time": begin_time, |
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"end_time": end_time, |
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"event_time": event_time, |
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"event_time_index": event_time_index, |
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"event_location": event_location, |
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"station_location": station_location, |
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} |
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elif ( |
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(self.config.name == "event") |
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or (self.config.name == "event_train") |
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or (self.config.name == "event_test") |
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): |
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waveforms = np.zeros([len(station_ids), 3, self.nt], dtype="float32") |
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phase_type = [] |
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phase_time = [] |
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phase_index = [] |
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phase_polarity = [] |
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station_location = [] |
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for i, sta_id in enumerate(station_ids): |
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waveforms[i, :, : self.nt] = event[sta_id][:, : self.nt] |
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attrs = event[sta_id].attrs |
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phase_type.append(list(attrs["phase_type"])) |
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phase_time.append(list(attrs["phase_time"])) |
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phase_index.append(list(attrs["phase_index"])) |
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phase_polarity.append(list(attrs["phase_polarity"])) |
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station_location.append( |
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[attrs["longitude"], attrs["latitude"], -attrs["elevation_m"] / 1e3] |
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) |
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yield event_id, { |
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"data": waveforms, |
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"phase_time": phase_time, |
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"phase_index": phase_index, |
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"phase_type": phase_type, |
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"phase_polarity": phase_polarity, |
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"begin_time": begin_time, |
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"end_time": end_time, |
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"event_time": event_time, |
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"event_time_index": event_time_index, |
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"event_location": event_location, |
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"station_location": station_location, |
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} |
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