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PS_Alaska.py

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+# 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 datasets
+
+_PSAlaska_DESCRIPTION = """
+
+"""
+
+_ManualPick_CITATION = """\
+@InProceedings{huggingface:dataset,
+title = {A great new dataset},
+author={huggingface, Inc.
+},
+year={2020}
+}
+"""
+
+_ManualPick_DESCRIPTION = """\
+This dataset includes P and S phases recorded by the broadband stations in the Alaska Peninsula
+"""
+
+_PNTFIter1_CITATION = """
+"""
+
+_PNTFIter1_DESCRIPTION = """
+This dataset includes P and S phases predicted by the PhaseNet-TF using model trained by the manualpick dataset
+"""
+
+_PNTFIter1Combined_CITATION = """
+"""
+
+_PNTFIter1Combined_DESCRIPTION = """
+This dataset includes all P and S phases from PNTFiter1 dataset and all false negative arrivals of manualpick dataset
+"""
+
+_Data_URL = "/mnt/scratch/jieyaqi/alaska/final/PS_Alaska"
+
+
+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.
+          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=_Data_URL+"/ManualPick",
+            citation=_ManualPick_CITATION,
+        ),
+        PSAlaskaConfig(
+            name="PNTFIter1",
+            description=_PNTFIter1_DESCRIPTION,
+            data_url=_Data_URL+"/PNTFIter1",
+            citation=_PNTFIter1_CITATION,
+        ),
+        PSAlaskaConfig(
+            name="PNTFIter1_combined",
+            description=_PNTFIter1Combined_DESCRIPTION,
+            data_url=_Data_URL+"/PNTFIter1_combined",
+            citation=_PNTFIter1Combined_CITATION,
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "PNTFIter1_combined"
+    
+
+    def _info(self):
+
+        return datasets.DatasetInfo(
+            description=_PSAlaska_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)
+        stationf = dl_manager.download_and_extract(_Data_URL, 'stations.csv')
+        stationl = []
+        eventl = []
+        waveform_files = {}
+        with open(stationf, newline='') as csvfile:
+            r = csv.reader(csvfile, delimiter=',')
+            next(r)
+            for row in r:
+                stationl.append(row[-1])
+
+        with open(os.path.join(data_dir, 'catalogs.csv'), newline='') as csvfile:
+            r = csv.reader(csvfile, delimiter=',')
+            next(r)
+            for row in r:
+                eventl.append(row[3])
+
+        for e in eventl:
+            waveform_files[e] = os.path.join(data_dir, 'waveform', f'{e}.h5')
+
+        return [
+            datasets.SplitGenerator(
+                name="full",
+                gen_kwargs={
+                    "stations": stationl,
+                    "events": eventl,
+                    "waveform_files": waveform_files
+                },
+            ),
+        ]
+
+
+    def _generate_examples(self, stations, events, waveform_files):
+        
+        for e in events:
+            f = h5py.File(waveform_files[e], 'r')
+            for sta in f[e].keys():
+                key = f'{e}_{sta}'
+                meta = f[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": f[e][sta]
+                }
+            f.close()