Upload DiaMed.py

DiaMed.py

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+# coding=utf-8
+# 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.
+"""DIAMED"""
+
+import os
+import json
+import math
+
+import datasets
+
+_DESCRIPTION = """\
+DIAMED
+"""
+
+_HOMEPAGE = ""
+
+_LICENSE = "Apache License 2.0"
+
+_URL = "https://huggingface.co/datasets/DiaMED/DiaMED/resolve/main/data.zip"
+
+_CITATION = """\
+
+"""
+
+class DiaMed(datasets.GeneratorBasedBuilder):
+    """DIAMED"""
+
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+
+        features = datasets.Features(
+            {
+                "identifier": datasets.Value("string"),
+                "title": datasets.Value("string"),
+                "clinical_case": datasets.Value("string"),
+                "topic": datasets.Value("string"),
+                "keywords": datasets.Sequence(
+                    datasets.Value("string"),
+                ),
+                "domains": datasets.Sequence(
+                    datasets.Value("string"),
+                ),
+                "collected_at": datasets.Value("string"),
+                "published_at": datasets.Value("string"),
+                "source_url": datasets.Value("string"),
+                "source_name": datasets.Value("string"),
+                "license": datasets.Value("string"),
+                "figures_urls": datasets.Sequence(
+                    datasets.Value("string"),
+                ),
+                "figures_paths": datasets.Sequence(
+                    datasets.Value("string"),
+                ),
+                "figures": datasets.Sequence(
+                    datasets.Image(),
+                ),
+                "icd-10": datasets.features.ClassLabel(names=[
+                    'A00-B99  Certain infectious and parasitic diseases',
+                    'C00-D49  Neoplasms',
+                    'D50-D89  Diseases of the blood and blood-forming organs and certain disorders involving the immune mechanism',
+                    'E00-E89  Endocrine, nutritional and metabolic diseases',
+                    'F01-F99  Mental, Behavioral and Neurodevelopmental disorders',
+                    'G00-G99  Diseases of the nervous system',
+                    'H00-H59  Diseases of the eye and adnexa',
+                    'H60-H95  Diseases of the ear and mastoid process',
+                    'I00-I99  Diseases of the circulatory system',
+                    'J00-J99  Diseases of the respiratory system',
+                    'K00-K95  Diseases of the digestive system',
+                    'L00-L99  Diseases of the skin and subcutaneous tissue',
+                    'M00-M99  Diseases of the musculoskeletal system and connective tissue',
+                    'N00-N99  Diseases of the genitourinary system',
+                    'O00-O9A  Pregnancy, childbirth and the puerperium',
+                    'P00-P96  Certain conditions originating in the perinatal period',
+                    'Q00-Q99  Congenital malformations, deformations and chromosomal abnormalities',
+                    'R00-R99  Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified',
+                    'S00-T88  Injury, poisoning and certain other consequences of external causes',
+                    'U00-U85  Codes for special purposes',
+                    'V00-Y99  External causes of morbidity',
+                    'Z00-Z99  Factors influencing health status and contact with health services',
+                ]),
+            }
+        )
+        
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+
+        data_dir = dl_manager.download_and_extract(_URL)
+        print("#"*50)
+        print(data_dir)
+        # data_dir = "./splits/"
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "base_path": data_dir,
+                    "filepath": data_dir + "/splits/train.json",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "base_path": data_dir,
+                    "filepath": data_dir + "/splits/validation.json",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "base_path": data_dir,
+                    "filepath": data_dir + "/splits/test.json",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, base_path, filepath):
+
+        with open(filepath, encoding="utf-8") as f:
+
+            data = json.load(f)
+
+            for key, d in enumerate(data):
+
+                if str(d["icd-10"]) == "nan" or d["icd-10"].find("Plusieurs cas cliniques") != -1 or d["icd-10"].find("Aucune annotation") != -1:
+                    continue
+
+                yield key, {
+                    "identifier": d["identifier"],
+                    "title": d["title"],
+                    "clinical_case": d["clinical_case"],
+                    "topic": d["topic"],
+                    "keywords": d["keywords"],
+                    "domains": d["domain"],
+                    "collected_at": d["collected_at"],
+                    "published_at": d["published_at"],
+                    "source_url": d["source_url"],
+                    "source_name": d["source_name"],
+                    "license": d["license"],
+                    "figures_urls": d["figures"],
+                    "figures": [base_path + fg.lstrip(".") for fg in d["local_figures"]],
+                    "figures_paths": [base_path + fg.lstrip(".") for fg in d["local_figures"]],
+                    "icd-10": d["icd-10"],
+                }